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economic re p ort of the president transmitted to the congress february 2012 together with the annual report of the council of economic advisers united states government printing office washington : 2012 For sale by the Superintendent of Documents, U.S. Government Printing Office Internet: bookstore.gpo.gov Phone: toll free (866) 512-1800; DC area (202) 512-1800 Fax: (202) 512-2104 Mail: Stop IDCC, Washington, DC 20402-0001 ISBN 978-0-16-090181-2 C O N T E N T S Page ECONOMIC REPORT OF THE PRESIDENT................................................ 1 ANNUAL REPORT OF THE COUNCIL OF ECONOMIC ADVISERS* 7 CHAPTER 1. TO RECOVER, REBALANCE, AND REBUILD.............. 21 CHAPTER 2. THE YEAR IN REVIEW AND THE YEARS AHEAD..................................................................... 37 CHAPTER 3. RESTORING FISCAL RESPONSIBILITY......................... 81 CHAPTER 4. S TABILIZING AND HEALING THE HOUSING MARKET............................................................ 99 CHAPTER 5. INTERNATIONAL TRADE AND FINANCE................ 129 CHAPTER 6. JOBS AND INCOME: TODAY AND TOMORROW............................................ 163 CHAPTER 7. RESERVING AND MODERNIZING P THE SAFETY NET............................................................. 197 CHAPTER 8. IMPROVING THE QUALITY OF LIFE THROUGH SMART REGULATION, INNOVATION, CLEAN ENERGY, AND PUBLIC INVESTMENT....................... 231 REFERENCES .............................................................................................. 267 APPENDIX A EPORT TO THE PRESIDENT ON THE R ACTIVITIES OF THE COUNCIL OF ECONOMIC ADVISERS DURING 2011............................................... 293 APPENDIX B. STATISTICAL TABLES RELATING TO INCOME, EMPLOYMENT, AND PRODUCTION....................... 307 ____________ *For a detailed table of contents of the Council’s Report, see page 11. iii economic report of the president economic report of the president To the Congress of the United States: One of the fundamental tenets of the American economy has been that if you work hard, you can do well enough to raise a family, own a home, send your kids to college, and put a little money away for retirement. That’s the promise of America. The defining issue of our time is how to keep that promise alive. We can either settle for a country where a shrinking number of people do very well while a growing number of Americans barely get by, or we can restore an economy where everyone gets a fair shot, everyone does their fair share, and everyone plays by the same set of rules. Long before the recession that began in December 2007, job growth was insufficient for our growing population. Manufacturing jobs were leaving our shores. Technology made businesses more efficient, but also made some jobs obsolete. The few at the top saw their incomes rise like never before, but most hardworking Americans struggled with costs that were growing, paychecks that were not, and personal debt that kept piling up. In 2008, the house of cards collapsed. We learned that mortgages had been sold to people who could not afford them or did not understand them. Banks had made huge bets and doled out big bonuses with other people’s money. Regulators had looked the other way, or did not have the authority to stop the bad behavior. It was wrong. It was irresponsible. And it plunged our economy into a crisis that put millions out of work, saddled us with more debt, and left innocent, hardworking Americans holding the bag. In the year before I took office, we lost nearly 5 million private sector jobs. And we lost almost another 4 million before our policies were in full effect. Those are the facts. But so are these: In the last 23 months, businesses have created 3.7 million jobs. Last year, they created the most jobs since 2005. American manufacturers are hiring again, creating jobs for the Economic Report of the President | 3 first time since the late 1990s. And we have put in place new rules to hold Wall Street accountable, so a crisis like this never happens again. Some, however, still advocate going back to the same economic policies that stacked the deck against middle-class Americans for way too many years. And their philosophy is simple: We are better off when everybody is left to fend for themselves and play by their own rules. That philosophy is wrong. The more Americans who succeed, the more America succeeds. These are not Democratic values or Republican values. They are American values. And we have to reclaim them. This is a make-or-break moment for the middle class, and for all those who are working to get into the middle class. It is a moment when we can go back to the ways of the past—to growing deficits, stagnant incomes and job growth, declining opportunity, and rising inequality—or we can make a break from the past. We can build an economy by restoring our greatest strengths: American manufacturing, American energy, skills for American workers, and a renewal of American values—an economy built to last. When it comes to the deficit, we have already agreed to more than $2 trillion in cuts and savings. But we need to do more, and that means making choices. Right now, we are poised to spend nearly $1 trillion more on what was supposed to be a temporary tax break for the wealthiest 2 percent of Americans. Right now, because of loopholes and shelters in the tax code, a quarter of all millionaires pay lower tax rates than millions of middle-class households. I believe that tax reform should follow the Buffett Rule. If you make more than $1 million a year, you should not pay less than 30 percent in taxes. In fact, if you are earning a million dollars a year, you should not get special tax subsidies or deductions. On the other hand, if you make under $250,000 a year, like 98 percent of American families do, your taxes should not go up. Americans know that this generation’s success is only possible because past generations felt a responsibility to each other, and to the future of their country. Now it is our turn. Now it falls to us to live up to that same sense of shared responsibility. This year’s Economic Report of the President, prepared by the Council of Economic Advisers, describes the emergency rescue measures taken to end the recession and support the ongoing recovery, and lays out a blueprint for an economy built to last. It explains how we are restoring our strengths as a Nation—our innovative economy, our strong manufacturing base, and our workers—by investing in the technologies of the future, in companies that create jobs here in America, and in education 4 | Economic Report of the President and training programs that will prepare our workers for the jobs of tomorrow. We must ensure that these investments benefit everyone and increase opportunity for all Americans or we risk threatening one of the features that defines us as a Nation—that America is a country in which anyone can do well, regardless of how they start out. No one built this country on their own. This Nation is great because we built it together. If we remember that truth today, join together in common purpose, and maintain our common resolve, then I am as confident as ever that our economic future is hopeful and strong. the white house february 2012 Economic Report of the President | 5 the annual report of the council of economic advisers letter of transmittal Council of Economic Advisers Washington, D.C., February 17, 2012 Mr. President: The Council of Economic Advisers herewith submits its 2012 Annual Report in accordance of the Employment Act of 1946 as amended by the Full Employment and Balanced Growth Act of 1978. Sincerely, Alan B. Krueger Chairman Katharine G. Abraham Member Carl Shapiro Member 9 C O N T E N T S Page CHAPTER 1. TO RECOVER, REBALANCE, AND REBUILD........ 21 RECOVERING FROM THE GREAT RECESSION...........................................23 REBALANCING AT HOME AND ABROAD....................................................29 Restoring Fiscal Responsibility........................................................ 30 REBUILDING A STRONGER ECONOMY........................................................30 Jobs and Income: Today and Tomorrow........................................ 31 Preserving and Modernizing the Safety Net................................... 32 Improving the Quality of Life through Smart Regulation, Innovation, Clean Energy, and Public Investment........................ 33 CONCLUSION..........................................................................................................34 CHAPTER 2. THE YEAR IN REVIEW AND THE YEARS AHEAD............................................................................................ 37 AN ECONOMY IN RECOVERY: KEY EVENTS OF 2011..............................38 AN ECONOMY IN RECOVERY: THE LINGERING EFFECTS OF FINANCIAL CRISES...............................................................................................42 DEVELOPMENTS IN 2011 AND THE NEAR-TERM OUTLOOK...............46 Consumption and Saving................................................................. 46 Developments in Housing Markets................................................. 51 Business Fixed Investment............................................................... 53 Manufacturing Output.................................................................... 54 Business Inventories......................................................................... 57 Government Outlays, Consumption, and Investment................... 57 State and Local Governments.......................................................... 59 Real Exports and Imports................................................................ 60 Labor Market Trends....................................................................... 61 Wages, Labor Productivity, and Prices........................................... 63 Financial Markets............................................................................ 66 11 Small Businesses and the Recovery.................................................. 67 THE LONG-TERM OUTLOOK............................................................................74 Growth in GDP over the Long Term.............................................. 76 CONCLUSION..........................................................................................................79 CHAPTER 3. RESTORING FISCAL RESPONSIBILITY.................. 81 DETERMINANTS OF CURRENT DEFICITS....................................................82 Falling Effective Tax Rates on Upper-Income Taxpayers............. 85 Heterogeneity in Effective Tax Rates among High-Income Taxpayers.......................................................................................... 86 Addressing the Role Of Exclusions and Deductions in Effective Tax Burdens....................................................................... 87 THE FISCAL OUTLOOK.......................................................................................88 Medium-Term Budget Projections.................................................. 89 The Vital Role of Economic Growth in Future Fiscal Outcomes................................................................................ 91 Improvement in Long-Run Budget Projections.............................. 92 THE IMPORTANCE OF RESTORING FISCAL SUSTAINABILITY...................................................................................................93 THE PRESIDENT’S BALANCED APPROACH TO DEFICIT REDUCTION..........................................................................................95 CHAPTER 4. STABILIZING AND HEALING THE HOUSING MARKET.................................................................................. 99 THE HOUSING CRISIS AND THE INITIAL POLICY RESPONSES............................................................................................................ 101 Initial Policy Responses to the Crisis............................................. 103 Negative Equity: An Unprecedented and Pervasive Problem.......................................................................... 105 MACROECONOMIC EFFECTS OF HOUSING MARKET WEAKNESS............................................................................................................ 107 Consumption Effects....................................................................... 110 Residential Construction and Home Ownership Patterns.......... 114 STRUCTURAL PROBLEMS IN HOUSING MARKET................................. 117 Adjudicating Legal Disputes.......................................................... 118 Incentive Conflicts.......................................................................... 119 12 | Annual Report of the Council of Economic Advisers POLICY ACTIONS............................................................................................... 120 Building on the Experience of Existing Programs........................ 121 New Levers in Housing Policy....................................................... 124 CONCLUSION....................................................................................................... 126 CHAPTER 5. INTERNATIONAL TRADE AND FINANCE..........129 THE EURO-AREA CRISIS AND ITS IMPLICATIONS FOR THE UNITED STATES............................................................................... 131 Outlook for Europe and Implications for the U.S. Economy.................................................................................. 137 International Cooperation in Resolving Crises............................ 138 FOREIGN DIRECT INVESTMENT, INTERNATIONAL TRADE, AND THE U.S. ECONOMY................................................................................ 139 Investment in the United States by Foreign Companies.............. 140 The National Export Initiative...................................................... 143 The Role of Services in Export Growth and America’s Current Account Balance............................................................... 148 Policy Initiatives to Support Export Growth in Goods and Services......................................................................... 153 CONCLUSION....................................................................................................... 161 CHAPTER 6. JOBS AND INCOME: TODAY AND TOMORROW..................................................................163 JOBS AND EMPLOYMENT................................................................................ 164 THE DYNAMICS OF LABOR MARKET TRENDS....................................... 167 Job Dynamics.................................................................................. 167 Worker Flows.................................................................................. 172 Earnings and Income Mobility over the Career and between Generations...................................................................... 174 Overall Trends in Income and Rising Inequality......................... 178 Long-Term Unemployment........................................................... 181 PREPARING FOR TOMORROW’S LABOR MARKET................................ 183 Education and the Workers of Tomorrow.................................... 183 Increasing Educational Attainment.............................................. 189 Federally Supported Job Training................................................. 192 CONCLUSION....................................................................................................... 195 Contents | 13 CHAPTER 7. PRESERVING AND MODERNIZING THE SAFETY NET.....................................................................................197 UNEMPLOYMENT INSURANCE..................................................................... 200 The Economics of Unemployment Insurance............................... 201 Recent Trends in UI Receipt and Its Effect on Household Income.......................................................................... 202 Policy Innovations.......................................................................... 203 OTHER SAFETY NET PROGRAMS................................................................. 206 HEALTH INSURANCE........................................................................................ 209 The Economics of Employer-Sponsored Health Insurance.......... 209 Medicaid and CHIP: A Health Care Safety Net for Children..................................................................................... 211 Expanding Health Care Coverage: The Affordable Care Act.......................................................................................... 214 Provisions of the Affordable Care Act Now in Place................... 215 The Economic Benefits of Expanding Insurance Coverage......... 217 The Affordable Care Act and Medicare........................................ 219 RETIREMENT SECURITY.................................................................................. 220 Declining Retirement Preparedness.............................................. 221 Challenges to the Retirement Safety Net....................................... 222 Policies to Address Retirement Saving Challenges....................... 228 CONCLUSION....................................................................................................... 229 CHAPTER 8. IMPROVING THE QUALITY OF LIFE THROUGH SMART REGULATION, INNOVATION, CLEAN ENERGY, AND PUBLIC INVESTMENT...........................................................................231 A SMART APPROACH TO REGULATIONS................................................. 232 Designing Smart Regulations......................................................... 233 Smart Regulations in Practice....................................................... 234 Retrospective Analysis.................................................................... 238 “Look-Back” Initiative.................................................................... 240 Improvements in Everyday Life..................................................... 242 INNOVATION....................................................................................................... 243 Measuring Innovation.................................................................... 245 Intellectual Property Rights and Patent Reform.......................... 246 14 | Annual Report of the Council of Economic Advisers Private and Public Investments in R&D...................................... 247 Commercialization......................................................................... 250 Wireless Broadband and Spectrum Policy.................................... 251 CLEAN & SECURE ENERGY............................................................................. 252 Enhancing Energy Security............................................................ 252 Reducing Demand.......................................................................... 253 Increasing Domestic Energy Supplies............................................ 253 Reducing Emissions........................................................................ 254 Supporting Clean Energy R&D and Infrastructure..................... 255 INFRASTRUCTURE............................................................................................. 259 The State of the Nation’s Infrastructure....................................... 259 Government and Private Sector Roles in Infrastructure............. 261 Financing Infrastructure Investments........................................... 262 Recent and Current Federal Infrastructure Initiatives................ 264 CONCLUSION....................................................................................................... 266 REFERENCES.............................................................................................267 APPENDIXES A. B. Report to the President on the Activities of the Council of Economic Advisers During 2011........................................................ 293 Statistical Tables Relating to Income, Employment, and Production.............................................................................................. 307 FIGURES 1-1. 1-2. 1-3. 1-4. 2-1. 2-2. 2-3. 2-4. Median Household Income, 1979–2010.............................................. 22 Change in Nonfarm Payrolls, 2007–2011............................................ 27 Unemployment Rate Increases in Recessions Associated with Financial Crises........................................................................................ 28 Earnings Ratio: College Degree or More to High School Degree, 1963–2010................................................................................................. 33 Real GDP Growth by Quarter, 2007–2011.......................................... 39 Real GDP During Recoveries................................................................. 43 Real GDP in Recessions Associated with Financial Crises............... 45 Unemployment Rate Increases in Recessions Associated with Financial Crises........................................................................................ 45 Contents | 15 2-5. 2-6. 2-7. 2-8. 2-9. 2-10. 2-11. 2-12. 2-13. 2-14. 2-15. 2-16. 3-1. 3-2. 3-3. 3-4. 4-1. 4-2. 4-3. 4-4. 4-5. 5-1. 5-2. 5-3. 5-4. 5-5. 5-6. 5-7. 5-8. 16 | Consumption and Wealth Relative to Disposable Personal Income (DPI), 1952–2011...................................................................... 47 Business Fixed Investment and Cash Flow, 1990–2011.................... 55 Weekly Initial Unemployment Insurance Claims, 2004–2012......... 61 Private Nonfarm Employment During Recoveries............................ 62 Unemployment Rate, 1979–2011.......................................................... 63 Consumer Price Inflation, 2004–2011.................................................. 65 Price Markup over Unit Labor Costs, Nonfarm Business, 1947–2011................................................................................................. 65 10–Year Treasury Yields, 2004–2012................................................... 66 Private Sector Job Recovery by Firm Size, 2007–2011....................... 68 Small Business Commercial and Industrial Loans, 2007–2011........ 69 Employment Outlook for Small Businesses, 2003–2012................... 73 Labor Force Participation and Educational Enrollment, Ages 16–24, 2002–2011.......................................................................... 78 Selected Components of Deficit Projections: 2009–2019.................. 84 Average Tax Rates for Selected Income Groups Under a Fixed Income Distribution, 1960–2010................................................ 86 Average Individual Income Tax Rates by Income Quintile, 2000 and 2008.......................................................................................... 87 Projected Medium-Term Budget Deficits, 2011–2022...................... 89 Housing Busts in U.S. History............................................................. 102 Price-to-Rent Ratio and Mortgage Debt............................................ 103 S&P/Case-Shiller: January 2009 Expectations of Future House Prices and Actual Price Index................................................. 104 The Distribution of Underwater Mortgages By State, 2011............ 106 Employment Growth: Nontradable Industries................................. 114 Real GDP Growth, 2000–2011............................................................ 130 Economic and Fiscal Indicators for Selected Euro-Area Countries................................................................................................ 132 10-Year Bond Spreads Relative to Germany, 2010–2012................ 134 Share of Each State’s Goods Exports to the European Union by State, 2010............................................................................. 138 Annual FDI Inflows, Selected Countries, 2006–2010...................... 141 Change in Manufacturing Unit Labor Costs, 2002–2010............... 146 U.S. Current Account Balance and Its Components, 2000–2011............................................................................................... 149 Contribution to Services Surplus by Service Sector Category, 2010....................................................................................... 151 Annual Report of the Council of Economic Advisers 6-1. 6-2. 6-3. 6-4. 6-5. 6-6. 6-7. 6-8. 6-9. 6-10. 6-11. 6-12. 6-13. 7-1. 7-2. 7-3. 7-4. 7-5. 7-6. 7-7. 8-1. 8-2. Monthly Change in Private Sector Employment, 1980–2011........ 164 Unemployment Rate, 1980–2012........................................................ 165 BDS Estimates of Annual Gross Job Gain and Loss Rates, 1980–2009............................................................................................... 170 BED Estimates of Quarterly Gross Job Gain and Loss Rates, 1990–2011............................................................................................... 171 Hires and Separations, 2001–2011...................................................... 172 Flows into and out of Unemployment as Percent of the Labor Force, 1990–2012....................................................................... 173 The Great Gatsby Curve: Inequality and Intergenerational Mobility................................................................................................... 177 Percent of Households with Annual Income within 50 Percent of the Median......................................................................................... 178 Growth in Real After–Tax Income, 1979 –2007............................... 179 Share of Total U.S. Income Earned by Top 1 Percent, 1913–2010............................................................................................... 180 Median Duration of Unemployment and Long-Term Unemployed as a Percent of Total Unemployed, 1980–2011......... 182 Average Annual Earnings by Worker Education Level, 1963–2010............................................................................................... 187 Difference Between Projected Employment Growth Rate by Education and Average Projected Employment Growth Rate, 2010–2020............................................................................................... 188 Share of Household Income from Unemployment Insurance among Recipients in 2010, by Household Type............................... 203 Percentage of Private Sector Establishments Offering Health Insurance by Number of Employees, 1996–2010............................. 211 Percentage of Workers Without Health Insurance and the Ratio of Per Capita Health Expenditures to Median Income, 1979–2010............................................................................................... 212 Percentage of Children and Adults Without Health Insurance, 1988–2010............................................................................................... 213 Percentage of Young Adults Without Health Insurance, 2010 Q3 and 2011 Q2........................................................................... 216 The National Retirement Risk Index, 1983–2009............................ 223 Percent of Individuals with Various Shares of Family Income from Social Security, by Age of Householder, 2010......................... 225 Benefits and Costs of Regulations, 2001–2011.................................. 235 Economic Growth, Vehicle Safety, and Air Quality, 1980–2010............................................................................................... 244 Contents | 17 TABLES 2-1. 2-2. 2-3. 3-1. 5-1. 5-2. 5-3. 5-4. 7-1. 7-2. Administration Economic Forecast...................................................... 74 Alternative Labor Market Forecasts, as of February 2012................. 75 Components of Actual and Potential Real GDP Growth, 1952–2022................................................................................................. 77 Distribution of Average Federal Tax Rates.......................................... 88 Growth in U.S. Goods Exports, by Product...................................... 145 Dissection of U.S. Goods Export Growth, by Market...................... 148 Cross-Border Services Exports by Type and Country, 2010........... 154 Cross-Border Services Imports by Type and Country, 2010.......... 154 Number of Participants and Total Federal Expenditures for Safety Net Programs, 2010............................................................. 207 Distribution of Wealth Components for Households Aged 65–69, 2008.................................................................................. 225 BOXES Box 2-1: SBA’s Role in Financing Small Firms During the Recovery.......... 70 Box 6-1: Work-Life Balance............................................................................. 184 Box 8-1 Developing Domestic Energy: Shale Gas and Shale Oil................ 256 DATA WATCH Data Watch 1-1: Innovation in Measurement................................................. 24 Data Watch 1-2: Revisions to Estimates of the Gross Domestic Product... 26 Data Watch 2-1: The Data Implications of the Transition to a Services-Based Economy ...................................................................... 52 Data Watch 2-2: Investment in Intangibles..................................................... 56 Data Watch 3-1: Data from the IRS Statistics of Income Division.............. 92 Data Watch 3-2: Measuring Government Debt across Countries................ 96 Data Watch 4-1: Need for a Comprehensive Source of Data on Mortgage Debt and Performance........................................................ 111 Data Watch 4-2: Need for a Comprehensive Source of Data on Home Sales........................................................................................ 116 Data Watch 5-1: The Role of the New Office of Financial Research in Combating Global Financial Risks..................................................... 136 Data Watch 6-1: Measurement of Startups.................................................... 169 Data Watch 6-2: Intergenerational Mobility................................................. 176 Data Watch 7-1: The Census Bureau’s Supplemental Poverty Measure... 198 Data Watch 7-2: Health Data for Policy......................................................... 218 Data Watch 8-1: The Value of Information—the PACE Survey................ 240 18 | Annual Report of the Council of Economic Advisers ECONOMICS APPLICATIONS Economic Application Box 3-1: Measuring Progressivity in the Tax Code ...................................................................................... 90 Economics Application Box 4-1: Making a Decision about Refinancing a Mortgage........................................................................ 108 Economics Application Box 6-1: Calculating the Cost of College............. 193 Economics Application Box 7-1: Financial Literacy and Common Mistakes Made by Retirement Savers .............................. 226 Economics Application Box 8-1: Comparing Benefits and Costs.............. 236 Contents | 19 C H A P T E R 1 TO RECOVER, REBALANCE, AND REBUILD T he problems that caused the deep recession that began at the end of 2007 and lasted until mid-2009 were a long time in the making and will not be solved overnight. But in 2011, the Nation continued to recover from the Great Recession and to make progress toward building a stronger foundation for more balanced and sustainable economic growth in the future. The economy has expanded for 10 straight quarters. As a result of this growth, by the third quarter of 2011, the real gross domestic product (GDP) of the United States had surpassed its peak level at the start of the 2007–09 recession. Sustaining and strengthening the ongoing recovery remains a top priority for the Obama Administration, while seeking to address the fundamental imbalances and other problems that had built up for decades and erupted with the financial and economic crisis in 2008. The pace of the recovery has not been faster because of the severity of the financial and economic crisis and the unique nature of the problems that led to the crisis in the first place. These problems included excess borrowing in the run-up to the financial crisis that subsequently caused massive deleveraging by households, a massive loss of wealth during the financial crisis that continues to constrain consumption, and excess residential home building during the housing boom that continues to cause weakness in residential construction and the housing sector. Fundamentally, many of the problems that have plagued the economy in the past decade can be traced to weak income growth for middle-class workers. This can be seen in Figure 1-1, which displays the median household’s income each year after adjusting for inflation. Income growth was stagnant for middle-income earners in the 2001–07 period and, as is common, declined in the recessions at the end and beginning of the decade. Had income grown at the same average annual rate in the first decade of the 2000s as it did in the 1990s, middle-income households would have greatly improved their financial situation. 21 Figure 1-1 Median Household Income, 1979–2010 Dollars (2010) 60,000 Projection if median household income had grown during the 2000s at the same rate as it did during the 1990s 58,000 56,000 54,000 52,000 50,000 2010 48,000 Actual 46,000 44,000 42,000 1979 1983 1987 1991 1995 1999 2003 2007 Note: Shading denotes recession. Source: CEA calculations and Census Bureau. A related phenomenon is that the size of the middle class has shrunk. This disturbing trend has taken place over several decades. While those at the top of the income distribution have seen strong income growth, many in the middle and at the bottom have struggled. Many economists have argued that, when confronted with easy credit and nontransparent terms, many families borrowed at an unsustainable rate to make up for the weak income growth they experienced in the 2000s. Strengthening and expanding the middle class, and adequately reforming the financial sector, are therefore at the root of the Obama Administration’s strategy to reestablish an economy that is built to last. In addition to lingering effects of the financial crisis and the longstanding problem of weak income growth for the middle class, the recovery in 2011 faced additional shocks from natural disasters in Asia, unrest in the Middle East that caused oil prices to spike, self-inflicted wounds to confidence from the contentious debt ceiling debate over the summer, and stress in European debt markets. Despite these encumbrances—and with the support, in part, of measures the President signed into law in December 2010, including the payroll tax cut, the extension of unemployment insurance, and 100 percent business expensing—private-sector employment has increased for 23 straight months, and the unemployment rate fell from a high of 10.0 percent in October 2009 to 8.3 percent in January 2012. Over the course of 22 | Chapter 1 2011, the unemployment rate fell by 0.9 percentage points, the largest drop in any year since 1994. Most of that decline occurred in the last three months of 2011. The sharp drop in unemployment toward the end of 2011 took economic forecasters by surprise, because unemployment was projected to remain in the high-8-percent range by many forecasters, including the Council of Economic Advisers (CEA). As part of the Budget process, the CEA, together with the Office of Management and Budget and Treasury officials, made its forecast of economic outcomes in mid-November 2011. Since that forecast was locked down, the reported unemployment rate has now fallen by 0.7 percentage points, and the advance estimate of GDP growth for the fourth quarter of 2011 exceeded what most forecasters had expected in November. In view of the new information, the consensus of Blue Chip forecasters lowered its forecast of the unemployment rate for the end of 2012 by about 0.8 percentage point, to 8.1 percent. The more optimistic private forecasters expect the rate to be below 8.0 percent at the end of the year. In Chapter 2, the Report illustrates the latest forecasting range for the unemployment rate. One of the reasons for the range of forecasting uncertainty is that it is unclear how many of the President’s job creation initiatives Congress will enact in the coming year. Respected private forecasters have estimated that a continuation of the 2 percentage point payroll tax cut and extended unemployment insurance benefits through the remainder of 2012 could significantly boost economic growth and job creation. The Administration’s economic strategy continues to be to: 1) pursue avenues to raise demand for U.S. goods and services in the short run to support the ongoing recovery and put more people back to work; 2) develop credible policies to return to a fiscally sustainable path in the intermediate and long term; and 3) invest in education, innovation, research, domestic energy, and infrastructure in order to build a stronger foundation for future economic growth and an expanding middle class. Put simply, the Nation needs to recover, rebalance, and rebuild. As described in this Report, in many instances, when Congress has not acted, the President has taken steps to implement this agenda. Recovering from the Great Recession When President Obama took office on January 20, 2009, the U.S. economy was contracting at an alarming rate, and employment was falling by more than 700,000 jobs a month. The plunge in economic activity was even deeper than the Bureau of Economic Analysis initially reported: revised estimates showed that the economy contracted at an 8.9 percent annualized To Recover, Rebalance, and Rebuild | 23 Data Watch 1-1: Innovation in Measurement Economic statistics are central to understanding how the economy is working—whether consumer spending is growing or shrinking, the extent to which businesses are investing in equipment and software, the number of people currently employed, and the wages they are earning, among many other examples. This year’s Economic Report of the President highlights the role that accurate and timely economic measurement plays in supporting sound economic decisions by policymakers, businesses, and families. In a series of Data Watch boxes, the Report offers examples of recently developed data series that shed light on economic performance, significant gaps in available economic data, and opportunities for improvements in the Nation’s economic measures. The growing integration of technology in our daily lives has created an abundance of new possibilities for producing better and more timely data based on nontraditional sources of information. As Census Bureau Director Robert Groves has written, “(t)he volume of data generated outside the government statistical systems is increasing much faster than the volume of data collected by the statistical systems; almost all of these data are digitized in electronic files” (Groves 2012). Nontraditional sources of information include both digital administrative data (e.g., tax records and records related to participation in government transfer programs) and records generated in the private sector (e.g., data from Internet searches, scanner data and social media data). There is a long history of using administrative records to produce economic statistics—under strict standards of confidentiality. The Obama Administration has endeavored to create new databases that track student performance across different stages of education, as well as the performance of postsecondary educational institutions. Once these databases have been developed, analyses of the outcomes achieved by students with different educational experiences will help to guide improvements in instructional quality and college choice. Innovative statistics based on electronic records compiled as a byproduct of commercial activity also can be informative. Adding series based on Google Trends to economic forecasting models, for example, can improve those models’ predictive power. The number of search queries for a particular make of automobiles in the last two weeks of a month, for instance, turns out to be a good predictor of sales of that car, and the number of searches for real estate agencies is one of the best predictors of current home sales (Choi and Varian 2009). Unlike government survey data, data based on electronic records generated for commercial or administrative purposes may not be nationally representative, and expanding access to these records, even 24 | Chapter 1 for purely statistical purposes, can pose privacy concerns that must be addressed. But their use also has the potential to improve and enrich existing official statistics. The Bureau of Economic Analysis, for example, plans to use credit card data to improve its statistics on international travel services. The Census Bureau is exploring the use of administrative data on receipt of government benefits to improve estimates of income in its household surveys. Other uses of both commercial and administrative data to improve official statistics can easily be imagined. Government statistical agencies can play a vital role in this burgeoning field by providing survey data to improve the representativeness of nonsurvey data, and the Federal statistical agencies can improve their measures by integrating private-sector information. Progress in this area will ultimately lead to better informed decisions by policymakers, businesses, and families. rate in the last quarter of 2008, from the initial advanced estimate of 3.8 percent, the largest quarterly downward revision in history. The Administration immediately took bold steps to turn around an economy in free fall. It worked to stem the job losses and put people back to work through the American Recovery and Reinvestment Act of 2009 (the Recovery Act), and it shored up the banking system and stabilized the financial sector through a series of measures including stress tests for banks and rigorous requirements for banks to raise private capital and repay the government for funds from the Troubled Asset Relief Program, and it rescued the American auto industry. Soon after the Recovery Act was passed, the contraction of GDP slowed markedly to –0.7 percent in the second quarter of 2009 from –6.7 percent in the preceding quarter. Economic growth turned positive in the third quarter of 2009, and the economy has grown at an annualized growth rate of 2.4 percent over the past 10 quarters. The economy is continuing to recover from the most severe downturn since the Great Depression. Despite numerous adverse headwinds—both domestic and international—that threatened the recovery, the U.S. economy displayed notable resilience in 2011. Private nonfarm employment growth, shown in Figure 1-2, averaged 174,000 jobs per month in 2011, and 218,000 jobs per month over the past three months (ending in January 2012). Private employers added more than 2.1 million jobs in 2011, the most in any year since 2005. At $15.3 trillion dollars, real GDP now exceeds its pre-recession peak. Clearly, this improvement since the end of the recession represents real progress. Nevertheless, given the depth and severity of the Great Recession, To Recover, Rebalance, and Rebuild | 25 Data Watch 1-2: Revisions to Estimates of the Gross Domestic Product The gross domestic product (GDP) is a summary measure of the Nation’s economic activity, constructed as the sum of personal consumption, gross private investment, net exports, and government expenditures. The first estimate of GDP appears within a month after the end of the quarter to which it applies and is based, in part, on source data that are preliminary and incomplete. More complete data are available for the second estimate, published the following month, and the third estimate, released the month after that; each of these revisions incorporates new or revised information from private and public sources, including monthly and quarterly Census Bureau surveys. Annual revisions to the National Income and Product Accounts allow the Bureau of Economic Analysis (BEA) to catch up in an organized way with further revisions to the source data used to compute GDP and to incorporate additional data available only at yearly frequencies. About every five years, a benchmark revision incorporates data from the Economic Censuses (Landefeld, Seskin, and Fraumeni 2008). Between 1983 and 2009, revisions in the annualized growth rate of real quarterly GDP between the first and latest available estimate averaged 1.2 percentage points in absolute value (Fixler, GreenawayMcGrevy, and Grimm 2011). A dramatic example is provided by the revisions to the GDP growth rate for the fourth quarter of 2008, which was originally reported as –3.8 percent and later revised down to –8.9 percent in the annual revision released in July 2011. This was the largest downward revision to the quarterly data ever reported. Taken as a whole, the revised data for 2008 and 2009 indicated that the recent recession was considerably more severe than originally reported. While revisions to initial GDP estimates for the United States can be substantial, they are smaller than the average for other large developed economies (see, for example, Faust, Rogers, and Wright 2005). And despite sometimes sizable revisions, early estimates of quarterly GDP growth generally do a good job of capturing increases or decreases in growth rates, as well as the timing of cyclical peaks and troughs (Fixler and Grimm 2005). Further, research has found that there is only limited potential to improve the initial GDP estimates given the contemporaneous information available to the BEA (Dynan and Elmendorf 2001; McKenzie, Tosetto, and Fixler 2008). Still, more accurate early estimates of GDP would be helpful to policymakers and businesses. Improving the quality and timeliness of the source data available to the BEA is the best way to accomplish this objective. 26 | Chapter 1 stronger economic growth and faster job gains are needed to make full use of the Nation’s human and physical resources. On the whole, the pace of real GDP growth so far during this recovery has been almost as fast as was the case at a similar stage of the recoveries following the 1991 and 2001 recessions, which is noteworthy progress given that the earlier recoveries received a strong boost from residential home building and State and local government spending. Because of the excess home and office construction during the housing bubble, construction of structures has been notably weak so far in this recovery. In addition, once Recovery Act funds began to phase out, State and local governments cut spending and laid off workers at a faster pace. Both of these developments are unprecedented headwinds that were not present during other postwar recoveries. As has been the pattern in recent recoveries, job growth has lagged a resumption of economic growth. Job growth started in February 2010, 8 months after the official conclusion of the 2007–09 recession, versus 11 months after the end of the 1991 recession and 21 months after the end of the 2001 recession. From February 2010 through January 2012 (months 8 through 31 after the official end of the recession), private-sector employers added a net total of 3.7 million jobs. Over the comparable period of the recovery from the 1991 recession, businesses added 3.0 million jobs (from November 1991 to October 1993), and over the comparable period of the Figure 1-2 Change in Nonfarm Payrolls, 2007–2011 Thousands, seasonally adjusted 400 200 0 Jan-12 -200 -400 -600 Total (excluding Census hiring) -800 Private -1,000 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Note: Shading denotes recession. Source: Bureau of Labor Statistics. To Recover, Rebalance, and Rebuild | 27 Figure 1-3 Unemployment Rate Increases in Recessions Associated with Financial Crises Percentage point increase from business-cycle peak Malaysia (1997:Q4) 1.1 Thailand (1996:Q3) 2.9 Japan (1993:Q1) 3.1 Philippines (1998:Q1) 3.7 Norway (1988:Q1) 3.8 U.S. (2007:Q4) 5.1 Colombia (1998:Q2) 5.5 Argentina (1998:Q2) 6.0 Hong Kong (1997:Q3) 6.4 South Korea (1997:Q3) 6.5 Indonesia (1997:Q4) 6.6 Average 14 7.7 Sweden (1990:Q1) Spain (1978:Q2) Finland (1990:Q1) U.S. (1929:Q3) 0 5 10.5 12.5 14.8 24.5 10 15 20 25 Note: Financial crises are from recessions identified by Reinhart and Rogoff (2009) as associated with major, systemic financial crises. Each data point represents the increase from the business-cycle peak to the subsequent peak in the unemployment rate. U.S. business-cycle peaks are defined by the National Bureau of Economic Research, and the business-cycle peaks of other countries refer to the peaks of real GDP. Unemployment rates for Argentina, Colombia, Indonesia, Malaysia, and Thailand are based on annual data. "Average 14" excludes the 2007–2009 U.S. recession. Source: Reinhart and Rogoff (2009); National Bureau of Economic Research; International Monetary Fund, World Economic Outlook and International Financial Statistics; Moore (1961); national sources; CEA calculations. recovery from the 2001 recession, businesses added 1.1 million jobs (July 2002 to June 2004). The catastrophic financial crisis that exacerbated the economic downturn during the second half of 2008 is an important reason why the pace of the recovery has not been stronger. As discussed in Chapter 2, previous research finds that recessions associated with financial crises not only tend to be deeper than other types of economic downturns but also longer lasting. Yet, as bad as the Great Recession was, the United States appears to have fared relatively better than other countries that have experienced severe financial crises, in large part because of the emergency actions that were taken to strengthen the economy and stabilize the financial system. In a group of 14 countries identified by the economists Carmen Reinhart and Kenneth Rogoff as having experienced severe financial crises, these crises were followed by a real GDP decline of more than 10 percent, on average. In contrast, U.S. output decreased by substantially less. In addition, from each country’s business cycle peak to their subsequent peak unemployment rate, the unemployment rate across these 14 countries increased by an average of 7.7 percentage points as a result of their financial crises (Figure 1-3).1 1 Figure 1-3 shows the average increase in the unemployment rate across 14 financial crisis recessions, regardless of how many quarters it took the unemployment rate to reach its peak. Figure 2-4, in contrast, shows the average rise in the unemployment rate in each quarter elapsed from the beginning of each recession. 28 | Chapter 1 Although still a large increase relative to previous postwar recessions, the U.S. unemployment rate rose by 5.1 percentage points from the last quarter of 2007 to the fourth quarter of 2009, about 2.6 points less than the average country’s experience. The financial crisis was precipitated largely by lax credit standards, inadequate oversight, excessive debt, and a boom-and-bust cycle in housing prices, which led to unsustainable expansions in residential construction and consumer spending. Chapter 4 highlights the challenges that remain in the housing market, deriving primarily from institutional frictions, and explains the Administration’s initiatives for addressing many of the interlinked housing market problems. Rebalancing at Home and Abroad Once economic recovery began in mid-2009, the Obama Administration took steps to restore balance to the U.S. economy to help prevent the sorts of excesses that led to the financial crisis that erupted in 2008. In June 2009, the President presented his proposals for Wall Street reform. Those proposals began a process that culminated at the end of July 2010 with President Obama signing the Wall Street Reform and Consumer Protection Act of 2010. Progress is being made on rebalancing the sources of economic growth as well. Business investment has begun to rebound. The mix of business investment has shifted from residential and structures toward equipment and software, the types of investments that expand capacity, help workers become more productive, and build a foundation for sustainable growth. Exports as a share of GDP have also grown by 13 percent since the end of the recession. The growth in exports puts the United States on track to meet the President’s goal of doubling exports by the end of 2014. More rebalancing is needed, and the adjustment process may continue to cause headwinds for the recovery. As Chapter 3 details, government balance sheets need to shift by both cutting unnecessary spending and raising revenue to continue needed investments in the future. In September 2011, President Obama submitted a balanced plan to the Joint Select Committee on Deficit Reduction that would have reduced the deficit by $4 trillion over 10 years with a mix of spending cuts and additional revenue, and the President remains committed to pursuing a balanced approach to put America on a sustainable fiscal path. Finally, rebalancing in the economy is required so that the gains of economic growth provide more opportunity for the middle class and those struggling to get into the middle class. One step in this direction is provided To Recover, Rebalance, and Rebuild | 29 by the landmark Affordable Care Act, which will provide premium assistance tax credits for those without access to affordable health insurance to obtain coverage. The new law will also begin to lower the rate of health care cost growth. Additionally, improvements in K–12 education and greater access to postsecondary education will provide more opportunity for middle-class families and those struggling to get into the middle class. Restoring Fiscal Responsibility In the late 1990s, the Federal Government was generating budget surpluses, both annually and throughout the 10-year budget window, as well as actually paying down the national debt. Since 2001, Federal debt has been growing unsustainably, primarily as a result of the 2001 and 2003 tax cuts that were skewed toward the wealthiest, increased military operations, the unfunded Medicare prescription drug benefit, and slow job and economic growth. Although safety net stabilizers and job creation measures in the short term are important to keep the recovery gaining momentum, the longterm Federal debt must be reduced. Chapter 3 details how Federal debt shifted sharply from a downward to an upward path to reach today’s unsustainable heights, and what the options are for reducing the long-term debt. Recognizing the economic risks associated with increased budget deficits, the Administration and Congress agreed on a $1 trillion deficit reduction package in the Budget Control Act of 2011—with an additional $1.2 trillion to $1.5 trillion in further reductions scheduled to follow. In his Fiscal Year 2013 Budget, the President has proposed a balanced approach that recognizes the need to prioritize spending initiatives while aligning revenues with current spending. Rebuilding a Stronger Economy President Obama has emphasized that the United States can outeducate, out-innovate, and out-build the rest of the world. Accomplishing this goal will require a Federal Government that lives within its means and makes targeted cuts to government spending while maintaining essential safety net services. But it will also require continuing to invest in the Nation’s future—training and educating workers; increasing the commitment to research and technology; and building new roads and bridges, highspeed rail, and high-speed Internet. In cities and towns throughout America, the benefits of these investments are clear. Investments in education, innovation, clean energy, and infrastructure are an essential down payment on the future. These investments today will be the foundation of long-term output and employment growth in the 30 | Chapter 1 future, robust wage growth for all Americans, and improvements in the quality of life. As emphasized, the Nation can afford these investments only by getting its fiscal house in order. The Federal Government has to live within its means to make room for things it absolutely needs, without jeopardizing essential safety net programs or the ability to make investments for the future. That is why President Obama urged Congress to find common ground so that government policies can, with the private sector, accelerate, not impede, economic growth and sharpen America’s competitive edge in the world. Measured GDP growth is not the only contributor to the quality of life that Americans seek to enjoy. Government investments as well as regulatory policies can improve well-being by correcting market failures and protecting safety, health, and environmental quality. In fashioning long-term policies, the Nation should not overlook those factors that contribute to well-being even if they are not fully captured in economic statistics. Jobs and Income: Today and Tomorrow Problems that were building in the labor market for well over a decade were amplified by the Great Recession. Chapter 6 explains where the labor market is today and distinguishes between the effects of the recession and longer-term trends in employment and income that predated the recession. The goals of current policies are twofold: to increase job growth in the near term, and to prepare Americans of all ages for the jobs of the future. The chapter discusses the President’s job creation proposals and the key role they can play in supporting job growth in the near term. One notable long-term trend that can be stopped is the sharp decline in manufacturing jobs. From 2000 to 2007, the economy lost nearly 4 million manufacturing jobs, as these positions migrated overseas. Another 2 million manufacturing jobs were lost during the 2007–09 recession. Thanks, in part, to the President’s efforts to rescue the American auto industry, manufacturing companies have been adding jobs for the first time since the late 1990s. On net, 400,000 manufacturing jobs have been added in the past two years. The auto industry was central to the rebound in manufacturing: although the auto industry accounts for only 6 percent of industrial production, it is responsible for 23 percent of the increase in industrial production since the end of the recession. As discussed in Chapter 5 and Chapter 6, a number of companies have indicated that they are bringing jobs back to the United States because of the Nation’s high productivity and growing cost advantages. The President has laid out a bold agenda to support this trend and to encourage more manufacturing production at home. To Recover, Rebalance, and Rebuild | 31 Investments in education will build on America’s highly productive workforce and are essential to prepare today’s children for the jobs of tomorrow. Increasing educational attainment for low-income children would substantially improve their chances of moving up the rungs of the ladder of opportunity. As shown in Figure 1-4, the average earnings of college-educated workers has risen to a level twice as high as that of workers with only a high school diploma. And the unemployment rate of college graduates is about half of the national average. Yet while the benefits of education have grown, the growth in the relative share of college-educated American workers has slowed since 1980 (Goldin and Katz 2008). In the last few years, however, there has been an increase in school enrollment, and the President has set a goal for the United States to have the highest share of 25- to 34-year-olds with a college degree of any country by 2020. Chapter 6 lays out the strides the Obama Administration has made in bettering the education system at every level, making higher education more affordable, and improving job training programs. Making sure American workers have the right set of skills is also critical for a revival of manufacturing jobs and jobs in other high-paying sectors. The United States has a comparative advantage in high-technology, innovative sectors, but jobs in such sectors require a highly skilled workforce. As technology changes, advanced manufacturing products can become an even more important segment of the U.S. economy. Cars, for example, are now a highly advanced product: fully 30 percent of the value of many automobiles is derived from computer software, electronic components, and intellectual property, according to industry estimates. Thus, the President’s education and job training strategy is a necessary complement to proposals to strengthen the manufacturing sector. Preserving and Modernizing the Safety Net The recession highlighted the need for a strong safety net as millions of Americans, through no fault of their own, lost their jobs and saw their savings decline. In addition to cushioning the shock of income loss, safety net programs are important for long-term growth because they help maintain consumer demand in a downturn and make it easier for entrepreneurs to take risks, knowing that if they fail, they will have access to a minimum level of support. As the economy has undergone major changes, the safety net has not always adapted with it. Chapter 7 describes this changing landscape and the steps the Administration has taken to modernize the safety net for a more dynamic economy and more mobile workforce. The President has already reformed health care to give millions more Americans access to care and to 32 | Chapter 1 Figure 1-4 Earnings Ratio: College Degree or More to High School Degree, 1963–2010 Ratio 2.2 2.1 2.0 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1963 1972 1981 1990 1999 2008 Source: CEA calculations using March Current Population Survey data for workers aged 25–65 who worked at least 35 hours a week and for at least 50 weeks in the calendar year. Before 1992, education groups are defined based on the highest grade of school or year of college completed. Beginning in 1992, groups are defined based on the highest degree or diploma earned. Earnings are deflated using the CPI-U. Calculations are based on survey data collected in March of each year and reflect average wage and salary income for the previous calendar year. bring down costs. He has also called for the largest changes to the unemployment insurance program in 60 years and proposes to improve retirement preparedness by broadening the reach of individual retirement accounts, simplifying financial decisions for retirement savers and retirees, and promoting financial literacy. Improving the Quality of Life through Smart Regulation, Innovation, Clean Energy, and Public Investment Rebuilding the American economy entails investments in the foundations of economic growth—education, infrastructure, and research and development. Government investments in innovation and infrastructure and smart government regulations improve the quality of life and help the economy to operate more efficiently. The President has reduced burdensome regulations, where possible, but smart regulations have also enabled Americans to live longer, healthier, and more productive lives. As discussed in Chapter 8, the Obama Administration has made significant reforms to the regulatory system to To Recover, Rebalance, and Rebuild | 33 better measure relevant costs and benefits and to establish a review process that will result in continual improvement of the regulatory architecture. A focus on quality of life also emphasizes public investments in innovation and infrastructure. Technological breakthroughs improve the quality of life in ways that are not fully captured by measures of economic activity. Cellular telephones, for example, generate large increases in convenience that benefit consumers without being fully captured in measures of GDP. Similarly, investments in infrastructure improve productivity but also have other, even larger benefits. A strong infrastructure system, for example, facilitates shorter commuting times, increasing leisure time and improving well-being. Ensuring that America has abundant clean energy to power the economy of the future is also a prerequisite for raising the quality of life and enhancing the Nation’s security. Early in 2011, President Obama noted that, “The United States of America cannot afford to bet our long-term prosperity and security on a resource that will eventually run out.” The Administration laid out a Blueprint for a Secure Energy Future, a comprehensive strategy that focuses on three key areas: developing and securing America’s energy supplies, including oil and natural gas; providing consumers with choices to reduce costs and save energy; and innovating our way to a clean energy future. This past year has seen remarkable progress toward reaching many of these energy goals. In 2011, domestic oil production was the highest it has been in the past eight years and natural gas production reached an all-time high. At the same time, the Administration has advanced common-sense new standards to ensure the safe and responsible development of these resources. Conclusion The U.S. economy has been expanding for two and a half years, but the pace of economic growth and job growth has not been fast enough given the deep hole that was created by the sharp recession that started at the end of 2007. The economic challenges that the United States faces are the direct result of problems that took years to build up and that came to a boil in the financial and economic crisis of 2007–09. While actions taken to prevent a deeper recession and to strengthen the recovery have made a difference, the Nation is still recovering from that profound crisis and the problems that led to it. Because household income for vast swaths of the middle class had stagnated, many families borrowed to support their consumption and to buy houses that later fell in value. Families are now paying down debt, which is restraining consumption and economic growth. Meanwhile, because of the 34 | Chapter 1 collapse of the housing boom, builders have been reluctant to build new homes, and construction workers had a 16.4 percent unemployment rate in 2011. And the government budget moved from surplus and debt reduction at the end of the 1990s to deficit and increasing debt in the early 2000s, as the priorities in Washington at that time shifted to increased spending to prosecute two wars while cutting taxes in a skewed and inefficient way. These are the Nation’s principal economic challenges, not uncertainty about economic policies, taxes, or regulations. To economists, the solution to these problems is clear: the Nation needs to raise demand for its goods and services in the short run to strengthen and sustain the economic recovery and put more people back to work, while pursuing credible policies to return to a fiscally sustainable path in the intermediate and long term and investing more in education, innovation, clean domestic energy, research and development, and infrastructure to raise long-run growth and expand the middle class. To Recover, Rebalance, and Rebuild | 35 C H A P T E R 2 THE YEAR IN REVIEW AND THE YEARS AHEAD T he U.S. economy continued to recover in 2011 from the deep recession that began at the end of 2007. The real value of goods and services produced in the economy, as measured by gross domestic product adjusted for changes in prices (real GDP), has now grown in each of the past 10 quarters. In the third quarter of 2011, real output surpassed the level last reached at the business-cycle peak in the fourth quarter of 2007. Employment continued to expand in 2011, and the private sector created more than 3 million new jobs in 2010 and 2011, about in line with the recovery from the 1991 recession and faster than the recovery from the 2001 recession. However, the level of unemployment remains too high, and the pace of the recovery in output and employment would in all likelihood be faster if it were not for the lingering effects of the financial crisis. The destruction of household wealth during the financial crisis and the deep recession that followed appears to have restrained the growth of consumption during the recovery, particularly in services. Investment in new residential construction also remains much weaker than in typical recoveries, a reflection of soft demand since the recession as well as the vast amount of overbuilding of houses during the years leading up to the crisis. Growth in other components of demand, such as business investment and exports, has followed trajectories more typical of business-cycle recoveries, and in some cases has been even stronger than average. To put the current U.S. recovery in historical and international context, this chapter presents an overview of the influential work by Charles Kindleberger (1978) and Carmen Reinhart and Kenneth Rogoff (2009), who argue that recessions associated with financial crises are typically deeper than normal downturns and that the recoveries that follow tend to take longer. As severe as the recession was, the drop in U.S. real GDP after the financial crisis of 2008 was smaller than the average decline in recessions associated with other severe, systemic financial crises in various countries 37 over the past 40 years. Similarly, the rise in U.S. unemployment was less extreme than the average experience following these financial crises, and it peaked earlier. As of January 2012, the unemployment rate has fallen by 1.7 percentage points since peaking in October 2009. This chapter also reviews the developments of 2011 for individual sectors of the U.S. economy. In the household sector, credit conditions continued to improve, and purchases of durable goods—such as motor vehicles—rose at a robust pace. Households continued to work down debt in 2011. As noted, growth in consumption remained somewhat restrained, however, as households continued to pay down debt and growth in nominal income slowed. In the business sector, investment in equipment and software posted solid gains in 2011, and global demand for U.S. goods and services was strong. The growth in U.S. exports supported job creation in 2011 as well as the continued expansion of manufacturing output. Conditions in residential real estate markets continued to stabilize in 2011, with a modest uptick toward the end of the year, but demand for new housing remained weak. Spending by State and local governments was also severely restrained in 2011 by tight budgets. Much of the weakness in these areas can be tied directly to the financial crisis and the problems that precipitated the crisis. An Economy in Recovery: Key Events of 2011 Real GDP rose 1.6 percent over the four quarters of 2011 after having risen 3.1 percent in 2010. Output expanded at an annual rate of only 0.8 percent in the first half of the year, when a series of shocks—among them a sharp rise in the price of oil due to turmoil in the Middle East—appeared to reduce consumer and business sentiment and dampen economic activity. As the effects of the transitory shocks waned in the second half of the year, real GDP growth picked up to an average annual rate of 2.3 percent (Figure 2-1). Nonfarm private payroll employment expanded by 2.1 million jobs during the twelve months of 2011, having added 1.3 million jobs in the last 10 months of 2010. The recovery in payroll employment, like that in real output, was uneven over the months of 2011. Payrolls expanded moderately near the beginning of the year, but job creation slowed in the spring and summer before picking up again in the fall. The unemployment rate fell over the course of the year, from 9.4 percent in December 2010 to 8.5 percent in December 2011, and then to 8.3 percent in January 2012. A Series of Global Shocks and Revised GDP Data. A succession of global shocks turned 2011 into a turbulent year for the U.S. economy. The collapse of Libyan crude oil production during that nation’s revolution caused world oil markets to tighten near the beginning of the year. The price 38 | Chapter 2 Figure 2-1 Real GDP Growth by Quarter, 2007–2011 Percent change (annual rate) 6 3.6 4 2 3.8 3.9 3.8 3.0 1.7 1.7 1.3 0.5 2.8 2.5 2.3 0.4 1.3 1.8 0 -2 -4 -0.7 2011:Q4 -1.8 -3.7 -6 -6.7 -8 -10 -8.9 2007:Q1 2008:Q1 2009:Q1 2010:Q1 2011:Q1 Note: Shaded area represents recession. Source: Bureau of Economic Analysis, National Income and Product Accounts. refiners paid for crude oil rose from an average of $78 a barrel in the second half of 2010 to $101 a barrel in the first half of 2011. The $23 per-barrel increase led to higher gasoline prices, eroded the real purchasing power of disposable personal income by more than $50 billion at an annual rate, and dampened consumer confidence. Consumers appear to have reacted with a combination of reduced spending on other goods and services and a lower saving rate than might otherwise have been the case. The 2 percentage point cut in the payroll tax for workers that President Obama proposed and the Congress passed near the end of 2010 helped offset the impact of higher oil prices. Another supply shock hit the world economy in March 2011, when an earthquake struck northeastern Japan and set off a tsunami, a disaster that resulted in a devastating human toll and required a massive rebuilding effort. Economic activity across the globe slowed because damage to Japan’s electrical grid disrupted industrial output throughout the country. As a result, global supply chains in some industries faced shortages of key parts. In the United States, vehicle assembly plants were forced to cut production when supplies of critical parts produced in Japan became scarce. U.S. motor vehicle production fell 21.2 percent at an annual rate in the second quarter before rebounding in the third and fourth quarters. In the summer, concerns mounted over sovereign debts and financial institutions in Europe and the likelihood of a global slowdown in economic The Year in Review and the Years Ahead | 39 growth. In addition, the contentious debate in Congress over raising the statutory debt ceiling kept financial markets on edge and appeared to weigh on equity markets over the summer and fall. In addition, revised estimates of U.S. real GDP released by the Bureau of Economic Analysis (BEA) in July 2011 revealed that the 2007–09 recession was more severe than had been originally reported. Real GDP fell at an average annual rate of 7.8 percent in the fourth quarter of 2008 and the first quarter of 2009, the sharpest two-quarter contraction since quarterly GDP data began being collected in 1947. The change to the estimate for the fourth quarter of 2008 was particularly stark. The BEA originally estimated that output contracted at an annual rate of 3.8 percent that quarter, but its July 2011 revised estimate showed an 8.9 percent rate of contraction. The downward change of 5.1 percentage points was the largest downward adjustment to the quarterly data ever reported. The BEA also revised down the average annual rate of growth during the recovery (from the second quarter of 2009 through the first quarter of 2011) by 0.2 percentage point, to 2.6 percent. Policy Developments in late 2010 and 2011. Supportive policies enacted near the end of 2010—the Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act (TRUIRJCA)—cushioned the adverse shocks experienced in 2011. Provisions in the legislation included a 2 percentage point reduction in workers’ payroll taxes and a continuation of the extended and emergency unemployment benefit programs through the end of 2011. In the absence of this legislation, real GDP growth over the four quarters of 2011 would have been lower by 0.9 to 2.8 percentage points, according to the Congressional Budget Office (CBO 2011b). Because the legislative package was constructed to be temporary (including mostly one- and two-year provisions), it had little effect on the long-term deficit. The American Recovery and Reinvestment Act (Recovery Act), enacted in early 2009 when real GDP was contracting at an annual rate of more than 6 percent and employment was falling by more than 700,000 jobs a month, also continued to support the level of real GDP in 2011, although its effect, which had been designed to be strongest during 2009 and 2010, was gradually declining. In 2011, Recovery Act–related outlays, obligations, and tax cuts totaled $117 billion, down from $350 billion a year earlier, as measured in the National Income and Product Accounts. The Council of Economic Advisers (CEA 2011) estimates that the Recovery Act increased GDP as of the second quarter of 2011, relative to what it otherwise would have been, by 2.0 to 2.9 percent and raised employment by between 2.2 million and 4.2 million jobs. The CBO and outside analysts have also presented estimates in this range. 40 | Chapter 2 In 2011, the Administration proposed additional steps to strengthen and sustain the economic recovery in the wake of world events that posed increasing risks to growth. Before a joint session of Congress on September 8, 2011, the President proposed the American Jobs Act to strengthen the current recovery and spur the creation of new jobs. The American Jobs Act incorporated a number of proposals that some independent economists estimated could have boosted payrolls by 1.3 million to 1.9 million jobs by the end of 2012 (for example, Macroeconomic Advisers 2011). Equally important, the American Jobs Act would not have added to the long-term Federal Budget deficit. The CBO (2011a) estimated that revenue raisers recommended by the President in September would have more than offset the cost of the proposed tax cuts and investments. Specifically, the bill proposed limiting deductions and exclusions for upper-income taxpayers, taxing carried interest earned on private equity and hedge fund investments at the same rate as ordinary income, and eliminating certain tax provisions for oil and gas production companies. The full American Jobs Act did not pass Congress in the form that the President proposed. Nevertheless, the President kept pressing for measures to support economic growth and job creation and will keep doing so until every American looking for work can get a job. In November, the President won enactment of one element of the American Jobs Act: a new tax credit for America’s veterans that provides up to $5,600 to businesses that hire veterans who have been unemployed for more than 26 weeks and $9,600 for businesses that hire a veteran with a service-related disability. And, in the waning days of 2011, the President signed into law a 2-month extension of the 2 percentage point reduction in workers’ payroll taxes and of the emergency and extended unemployment insurance programs. Those initiatives were mostly paid for by an increase in guarantee fees charged to lenders by Fannie Mae and Freddie Mac. The President has called on Congress to extend these policies for the entire calendar year. The extension of the payroll tax cut for the rest of 2012 would help approximately 160 million full-time and part-time workers and provide a typical worker with an additional $40 in each bi-weekly paycheck. The full-year extension of unemployment insurance programs would prevent 5 million unemployed workers from exhausting benefits this year and help support the equivalent of about 500,000 cumulative job-years of employment by the end of 2014 as these benefits are spent. Policy actions by the Federal Reserve also supported the recovery in 2011. Monetary policy remained accommodative throughout the year, with the Federal Open Market Committee (FOMC) maintaining a target range for the federal funds rate of 0 to 0.25 percent. During the first half The Year in Review and the Years Ahead | 41 of the year, the FOMC continued to advise that economic conditions were “likely to warrant exceptionally low levels for the federal funds rate for an extended period.” In June, the Federal Reserve completed the program first announced in November 2010 under which it purchased $600 billion of longer-term Treasury securities, and the FOMC maintained its policy of reinvesting principal payments from its holdings of debt and mortgagebacked securities issued by Fannie Mae and Freddie Mac. The FOMC took steps in the second half of 2011 and in the early part of 2012 to further ease conditions in financial markets and to provide additional support to the recovery. In the statement released following its August 2011 meeting, the FOMC said that it expected economic conditions to warrant exceptionally low levels for the federal funds rate at least through mid-2013. In January 2012, the committee extended this period until at least late-2014. The committee voted at its September 2011 meeting to extend the average maturity of the Federal Reserve’s holdings of Treasury securities in order to lower longer-term interest rates. In response to the escalation of the sovereign debt crisis in Europe, the FOMC approved an extension of the temporary U.S. dollar liquidity swap arrangements with a number of foreign central banks in June and again in November.1 An Economy in Recovery: The Lingering Effects of Financial Crises The 2007–08 financial crisis and the drop in economic activity during the recession were unprecedented. In the two and a half years that have elapsed since the official end of the recession, real U.S. GDP has risen 6.2 percent, enough to recoup the 5.1 percent loss of real output recorded during the recession. The pace of GDP growth during the recovery has been almost the same as the rates of growth observed during the recoveries that followed the 1991 and 2001 recessions (Figure 2-2), although private employment has grown at a faster pace than in the 2001 recession. A major reason that the rate of real GDP growth has not been faster during the current recovery involves the lingering effects of the financial crisis. As argued by Kindleberger (1978) and Reinhart and Rogoff (2009), recessions linked with financial crises tend to be deeper than other recessions, and the subsequent recoveries take longer. Hall (2010) and Woodford (2010) argue that recessions around financial crises are worse, in part, 1 The Federal Reserve receives collateral in the form of foreign currency during the life of the transaction. The exchange rate used for the transaction is based on the market exchange rate at the time of the transaction. The swap is unwound at the same exchange rate, so the Fed is not exposed to any currency risk resulting from the transaction. 42 | Chapter 2 Figure 2-2 Real GDP During Recoveries Indexed to 100 at NBER-defined trough 112 110 1991 108 2001 106 Current (2009:Q2 trough) 104 102 100 98 96 94 92 90 -12 -10 -8 -6 -4 -2 Trough 2 Quarters from trough 4 6 8 10 12 Source: Bureau of Economic Analysis, National Income and Product Accounts; National Bureau of Economic Research; CEA calculations. because the critical intermediation role played by the financial sector is disrupted. Financial crises also tend to spread across countries, temporarily reducing the volume of world trade and restraining growth of output during the recovery, as noted by Reinhart and Rogoff (2009) and IMF (2009). Housing slumps are also typically associated with slower growth during recoveries (Howard, Martin, and Wilson 2011). Some sectors of the U.S. economy are recovering at a moderate pace, while growth in other sectors continues to be restrained by the lingering effects of the financial crisis. In the current recovery, real U.S. exports have risen at a robust pace and have exceeded their average rate of growth in the preceding eight recoveries. Business fixed investment has been about as strong in the current recovery as in the average U.S. recovery. Real residential investment, in contrast, had barely returned to its level at the business-cycle trough by the very end of 2011, whereas this type of investment in a typical U.S. recovery would have increased roughly 34 percent over a comparable period. In addition, real expenditures by State and local governments have continued to decline, on balance, during the current recovery, instead of rising, as they had in every other postwar recovery. Personal consumption expenditures have risen more slowly in the current recovery than in the average U.S. recovery. The slower recovery in consumer spending may partly reflect the sharp losses in household net worth caused by the financial crisis and the high levels of consumer The Year in Review and the Years Ahead | 43 debt—including mortgage debt—taken on during the period leading up to the financial crisis. After the collapse in house prices destroyed large amounts of household net worth, households have reduced their consumption as they work down debt taken on before the crisis. To put the 2007–09 U.S. recession in international and historical contexts, Figure 2-3 compares the depth and duration of the 2007-09 recession in the United States with 14 recessions including the 1929 downturn in the United States, a group of recessions categorized by Reinhart and Rogoff (2009) as occurring near major systemic banking crises.2 The horizontal bars on the left of the figure refer to the decline in real output measured in each of the recessions, and the bars on the right report the length of each recession, measured as the number of quarters between the peak and trough of real output. While the drop in real U.S. GDP reached as high as 8.9 percent at an annual rate in the last quarter of 2008, the figure shows that the cumulative decline in GDP was 5.1 percent during the recession. This was the biggest drop in U.S. output during any business-cycle contraction since the Great Depression, although it was less drastic than the declines in output experienced in most other financial crises, and well below the average decline of 10.2 percent. The duration of the recent U.S. downturn, which measured six quarters, was about 10 percent shorter than the average. The breadth and speed of the emergency economic recovery measures that were put in place to address the financial and economic crisis, including the Recovery Act and Financial Stability Plan, as well as extraordinary actions by the Federal Reserve Board, are the main reasons why the economy avoided a steeper and more prolonged decline, with growth returning by the middle of 2009. Figure 2-4 compares the rise in the unemployment rate in the United States between the fourth quarter of 2007 and January 2012 with the average rise in unemployment following the business-cycle peaks for the 14 financial crises shown in Figure 2-3. Between the fourth quarter of 2007 and the fourth quarter of 2009, the U.S. unemployment rate rose more sharply than the average cumulative rise over the first 8 quarters after these business-cycle peaks, but then it peaked and declined over the next two years—an outcome less severe than the average rise in unemployment around other financial crises. If the United States had followed the path of the average country during a financial crisis recession, the unemployment rate would have been 10.4 percent in January 2012 instead of 8.3 percent. 2 The crises shown in Figure 2-3 are the major, systemic banking crises included in Reinhart and Rogoff (2009) Table 14-3. The analysis here differs from Reinhart and Rogoff (2009) in that we use seasonally adjusted quarterly real GDP rather than annual real GDP per capita. 44 | Chapter 2 Figure 2-3 Real GDP in Recessions Associated with Financial Crises Duration of downturn (quarters) Percent decline peak-to-trough -0.4 -1.2 -1.6 -2.8 -5.1 Spain (1978:Q2) 3 Philippines (1998:Q1) 3 Japan (1993:Q1) 3 Norway (1988:Q1) 3 United States (2007:Q4) 12 Colombia (1998:Q2) -6.8 4 South Korea (1997:Q3) -8.3 3 Hong Kong (1997:Q3) -8.8 5 Average 14 -10.2 6.6 Malaysia (1997:Q4) -11.2 3 Finland (1990:Q1) -12.7 13 Thailand (1996:Q3) -14.9 8 Indonesia (1997:Q4) -17.8 4 Argentina (1998:Q2) -19.9 15 United States (1929:Q3) -30.7 -35 6 Sweden (1990:Q1) -5.6 -30 14 -25 -20 -15 -10 -5 0 5 10 15 20 25 0 10 20 Percent decline Duration in quarters Note: Financial crisis dates are from Reinhart and Rogoff (2009). U.S. business cycles are defined by the National Bureau of Economic Research, and the business cycles of other countries refer to the peaks and troughs of real GDP. "Average 14" excludes current U.S. cycle. Source: Reinhart and Rogoff (2009); National Bureau of Economic Research; International Monetary Fund, World Economic Outlook (2010) and data from authors; Gordon and Krenn (2010); national sources; CEA calculations. Figure 2-4 Unemployment Rate Increases in Recessions Associated with Financial Crises 6 Percentage point change from business-cycle peak 5 Average 14 4 United States (2007:Q4-2012:Q1) 3 2 1 0 0 2 4 6 8 10 12 14 Quarters after business-cycle peak 16 18 20 Note: "Average 14" shows the average rise in the unemployment rate in each quarter after the business-cycle peaks identified by Reinhart and Rogoff (2009) as being associated with major, systemic financial crises. Financial crises are shown in Figure 2-3. U.S. business-cycle peaks are defined by the National Bureau of Economic Research, and the business-cycle peaks of other countries refer to the peaks of real GDP. Quarterly unemployment rates for Argentina, Colombia, Indonesia, Malaysia, and Thailand are based on annual data. The 2012:Q1 value for the United States is through January 2012. Source: Reinhart and Rogoff (2009); National Bureau of Economic Research; International Monetary Fund, International Financial Statistics, World Economic Outlook (2010), and data from authors; Moore (1961); national sources; CEA calculations. The Year in Review and the Years Ahead | 45 According to analysis by the Congressional Budget Office and privatesector forecasters, the Recovery Act, the Financial Stability Plan, and the extraordinary and exigent actions taken by the Federal Reserve had sizable, positive effects on U.S. GDP and employment in 2009. Rather than plunging into what many think could have been a second Great Depression, the U.S. economy began to grow again in the second half of 2009. As a result, the 2007–09 recession was shallower and shorter in duration than the average recession experienced by a country after a major financial crisis, and unemployment started to come down sooner and swifter. Developments in 2011 and the Near-Term Outlook Consumption and Saving Consumer spending—a category that makes up about 70 percent of GDP—rose moderately in 2011, as credit conditions continued to ease, household liabilities fell relative to income, and the labor market continued to recover. Gains over the year were uneven, however, in the face of upheavals at the beginning of the year. Partly reflecting these shocks, real consumer spending rose at an annual rate of only 1.4 percent in the first half of 2011, having increased more than 3 percent at an annual rate in the second half of 2010. The slowdown in spending growth would have been more severe in the absence of the workers’ payroll tax cut, which offset oil price shocks early in the year and supported household consumption. The disturbances that slowed consumption growth in the early part of the year proved transitory, and their effects dissipated in the second half of the year; oil prices stabilized over the summer, and by the fourth quarter, production (and availability) of motor vehicles had returned to levels that prevailed before the earthquake in Japan disrupted supply chains. The second half of 2011 brought new challenges, however. Concerns about the weakening pace of growth in several industrialized economies—most notably in Europe—escalated during the summer, and the contentious debates held in Congress over raising the statutory debt ceiling unsettled equity markets. The stock market and consumer confidence both fell in the third quarter before rebounding in the fourth quarter and early 2012. Despite these headwinds, the growth rate of real consumer spending picked up in the third and fourth quarters to an average annual rate of 1.9 percent. Several key developments in 2011 shaped the contours of consumer spending. Household Income in 2011. Nominal personal income grew 3.9 percent during the four quarters of 2011, a somewhat slower pace of growth 46 | Chapter 2 than in 2010. Growth in nominal personal income was held down in 2011 by a slowdown in job growth near the middle of the year. Real disposable personal income, which is personal income less personal taxes and adjusted for price changes, edged down 0.1 percent over the four quarters of 2011 after having risen 3.5 percent in the year-earlier period. The purchasing power of wages and salaries was curtailed somewhat in 2011 by a run-up in food and energy prices in the first half of the year, which appeared to have passed through to the prices of some other goods and services as well. As noted, tax policies passed near the end of 2010 helped cushion some of the effects of these price increases on consumers while providing an additional boost to income. The Administration seeks to extend the workers’ payroll tax cut in 2012 and to provide additional immediate support for aggregate demand through the continuation of extended unemployment insurance benefits and other measures initially proposed in the American Jobs Act. Household Wealth and Saving in 2011. The wealth-to-income ratio, depicted in Figure 2-5, declined in the third quarter of 2011 after rising, on balance, since the beginning of 2009. The consumption rate (shown in the figure as the share of disposable income consumed) tends to fluctuate with the wealth-to-income ratio. As a rule of thumb, a one dollar drop in wealth tends to reduce annual consumer spending by about two to five cents, although the source of the wealth change (housing or equities, for example) Figure 2-5 Consumption and Wealth Relative to Disposable Personal Income (DPI), 1952–2011 Consumption/DPI ratio 1.10 1.05 6 Total-wealth-to-DPI ratio (right axis) 1.00 0.95 Years of disposable income 7 2011:Q3 Consumption-to-DPI ratio (left axis) 5 4 2011:Q4 0.90 0.85 0.80 3 Stock market wealth-to-DPI ratio (right axis) Net housing wealth-to-DPI ratio (right axis) 2011:Q3 2 1 2011:Q3 0 0.75 1952 1960 1968 1976 1984 1992 2000 2008 Source: Bureau of Economic Analysis, National Income and Product Accounts; Federal Reserve Board, Z.1; CEA calculations. The Year in Review and the Years Ahead | 47 also may matter. The decline in the wealth-to-income ratio from the second quarter of 2007 to its low point in the first quarter of 2009 amounted to 1.8 years of income. (In other words, household wealth declined by the amount of income earned in 1.8 years). The drop in the wealth-to-income ratio over this period was the deepest sustained decline since 1952, when these data began to be compiled. Of the total decline, 1.1 years were lost from the decline in stock market wealth, and about 0.6 year from net housing wealth. All told, a drop in wealth of this magnitude could be expected to reduce personal consumption expenditures by about 6.7 percent. Equity prices fell during the summer of 2011 before regaining most of the losses toward the end of the year. Driven in part by the rise in uncertainty during the debt ceiling debate as well as external events in Japan and Europe, consumer sentiment also dropped to low levels in the summer before partially rebounding toward year’s end. Households continued to work down their debt through the third quarter of 2011 (the latest data available as this report goes to press). The personal saving rate—expressed in the National Income and Product Accounts as a share of disposable personal income—fluctuated around 5 percent for the first half of 2011, about the same rate as in 2010 but below the average rate of about 6 percent observed in the first half of 2009. The personal saving rate fell in the second half of 2011 to 3.8 percent, a decline from the first half of 2011 that may have partially reflected the pick up in purchases of consumer durables, especially new vehicles. Purchases of new motor vehicles, are counted as a consumption outlay in the National Income and Product Accounts even though households view these purchases as investment, and so a rise in vehicle purchases reduces the personal saving rate. Looking ahead, the personal saving rate appears roughly consistent at current levels with household wealth. As a consequence, while some further drops in the saving rate are possible, the growth rate of real consumer spending in the years ahead would be expected to largely mirror the growth rate of income, barring a dramatic change in asset prices. Even so, further increases in household purchases of durable goods, perhaps reflecting pentup demand for motor vehicle purchases that were deferred during the recession, may reduce the saving rate temporarily. Some of the recent patterns in aggregate spending and saving behavior—including the sluggish growth in consumer spending—may reflect the sharp rise over the past 30 years in the inequality in the income distribution in the United States. As the Congressional Budget Office recently noted, the top 1 percent of families had a 278 percent increase in their real after-tax income from 1979 to 2007, while the middle 60 percent had an increase of less than 40 percent. As a result of these trends, the very top income earners 48 | Chapter 2 have pulled much further ahead of everyone else. (See Chapter 6 for a discussion of shifts in the income distribution.) The effects of this dramatic shift in the income distribution on aggregate demand are hard to document, although some of the spending patterns in the Consumer Expenditure Survey reveal evidence of the increasing inequality of income. For example, the share of income spent on luxury goods and services, such as entertainment, relative to necessities, such as food, is higher for high-income households than for low-income households, and this gap has widened over time (Aguiar and Bils 2011). Several authors have argued that increases in inequality have likely adversely affected the economy.3 For example, the rise in income inequality may have reduced aggregate demand, because the highest income earners typically spend a lower share of their income—at least over intermediate horizons—than do other income groups. The following calculation illustrates the potential magnitude of this effect. As shown in recent research by Piketty and Saez (2003, 2010), the share of all income going to the top 1 percent has risen sharply over the past three decades, rising by 13.5 percentage points, from 10 percent to 23.5 percent, between 1979 and 2007. This is the equivalent of about $1.2 trillion of annual income in 2007. Research on the saving rate (or marginal propensity to consume) of families at the very top of the income distribution is scarce, but one study (Dynan, Skinner, and Zeldes 2004) implies that the top 1 percent of households save about half of their total current income, while the population at large has a saving rate of about 10 percent of their total income.4 This finding implies that if another $1.2 trillion had been earned by the bottom 99 percent instead of the top 1 percent of income earners, annual consumption could have been about $480 billion—or about 5 percent—higher. There are many caveats to this calculation, because the marginal propensity to consume is not well established for the extreme upper end of the income distribution. In addition, aggregate consumption may not have been reduced by a full 5 percent because the dramatic shift in the income distribution likely led many households to accrue more debt. In his book Fault Lines, Raghuram Rajan (Rajan 2010) argues that slow income growth for the middle class led, in part, to the rising levels of debt and the overleveraging that played a central role in the 2007–08 financial crisis.5 3 See Rajan (2010) and Reich (2010). Kaldor (1956) provides some early research in this area. 4 The saving rate cited here refers to the change in real net worth as a share of real pre-tax income, a measure that differs from the personal saving rate reported in the National Income and Product Accounts. 5 Note that the increase in leverage by the middle class may explain why the aggregate saving rate did not rise despite the shift in income to high savers. The Year in Review and the Years Ahead | 49 Increases in the inequality of income have been developing for some time, but their effects on aggregate demand may have become more pronounced in the wake of the financial crisis. Increasing levels of debt during 1979–2007 may have masked the influence of the rising inequality of incomes on aggregate consumer spending, because increased access to credit card debt, other consumer loans, and mortgage loans allowed the growth of purchases to outpace the growth of income for most income groups. With the onset of the recession and financial crisis, however, the scope for this level of borrowing came to an abrupt end. Access to credit, particularly for mortgages, was severely restricted, and the average consumer was left with elevated levels of debt taken on before the crisis. Since the crisis, the process of deleveraging appears to have reduced consumption below what it would have been otherwise. By targeting support to a broad group of American workers—including those with a higher propensity to spend additional income—the measures the President put forward in the American Jobs Act, like the payroll tax cut and extension of unemployment benefits, are likely to have a greater impact on consumption and aggregate demand than alternative measures. Other Influences on Consumption in 2011. For the second consecutive year, lending standards eased, as reported in the Federal Reserve’s senior loan officer survey, and consumer credit expanded modestly over the first three quarters of 2011. The level of overall household debt fell in 2011, reflecting a decline in mortgage debt. The decline in real household debt outstanding in the current recovery has been unprecedented, which suggests that the process of deleveraging has played a sizable role in household consumption decisions in recent years. Reflecting, in part, the improvement in credit availability since 2009, household consumption of durable goods, including items such as new and used automobiles as well as household electronics, furniture, and other appliances has risen at a solid pace in the current recovery and somewhat more strongly than the rates of growth observed during the recoveries that followed the 1991 and 2001 recessions. Household consumption of nondurable goods and services, in contrast, has risen at a slower pace in the current recovery than in most previous U.S. recoveries. Real consumer spending on services has increased only 2.9 percent so far in the current recovery, whereas this type of spending grew by an average of 10.7 percent over the first ten quarters of the previous eight recoveries. Consumer spending on services has been particularly weak in categories such as housing services, financial services, and insurance, likely reflecting the continuing effects of 50 | Chapter 2 the financial crisis, and on categories that are more discretionary, such as recreation and gambling.6 Restrained demand for services may have implications for the labor market, because the production of services accounts for about two-thirds of U.S. GDP and a larger share of U.S. employment. (For a discussion of the measurement of services see Data Watch 2-1.) Although it is difficult to tie final consumption of a particular type of good or service to employment in that industry (the purchase of a new motor vehicle creates jobs in a number of service industries, for example), jobs in service-producing sectors accounted for about 68 percent of total nonfarm payroll employment in 2007.7 Developments in Housing Markets After posting steep declines during the 2007-09 recession, activity in the housing sector remained at subdued levels in the first half of 2011 before edging up in the second half of the year. New housing starts were about 607,000 units in 2011, an increase of 3.7 percent from the level in 2010. New housing starts remain well below the long-run trend in U.S. housing demand. According to researchers at the Joint Center for Housing Studies at Harvard University, projected rates of household formation and immigration for the period 2010 through 2020 are consistent with housing starts in the range of 1.6 million to 1.9 million units a year (Masnick, McCue, and Belsky 2010). Activity in the housing sector is likely to remain below these levels for some time, however, as new construction continues to be restrained by a sizable overhang of vacant properties for sale. House prices, discussed in more detail in Chapter 4, fell 4.7 percent, on net, during the twelve months of 2011, according to the CoreLogic home price index. Distressed sales—which include short sales and sales of properties owned by lenders (real-estate owned, or REO)—remained a headwind in 2011: CoreLogic estimates that 1.6 million properties were seriously delinquent, in foreclosure, or owned by lenders in October 2011, equal to about five months of supply at the current pace of sales. The modest rates of growth in personal income and the tighter mortgage underwriting standards observed in recent years also kept sales and starts below their long-run trend levels. 6 Consumption of services is more difficult to measure than is consumption of goods, and estimates for 2011 may be revised considerably when the Services Annual Survey is incorporated into the National Income and Product Accounts. Nonetheless, the pattern of weaker-than-normal growth in services consumption in the current recovery has been quite pronounced through 2010, a period for which estimates reflect the latest annual survey. 7 Industries counted in this figure include professional and business services, education and health services, leisure and hospitality, other services, and government services. The Year in Review and the Years Ahead | 51 Data Watch 2-1: The Data Implications of the Transition to a Services-Based Economy In 1947, services represented less than 40 percent of U.S. gross domestic product (GDP). Today, service industries account for almost 70 percent of total U.S. domestic output. For many years, however, the measurement of service activity lagged the sector’s growing importance. A fundamental challenge in measuring the value of services is the disparate range of activities encompassed within the service sector. The Bureau of Economic Analysis (BEA) defines services as “products that cannot be stored and are consumed at the place and time of their purchase.” This includes, for instance, medical consultations, admission to movie theaters, Internet subscriptions, haircuts, and apartment rents, but also some less apparent things such as meals at restaurants, check clearing by banks, and the “rental value” of homeownership. (Although the purchase of a newly constructed home is categorized under residential investment, the BEA estimates the amount homeowners would have had to pay to rent similar houses and classifies this imputed rent under housing services.) A major breakthrough in the measurement of service output came with the introduction of the North American Industry Classification System (NAICS) beginning in 1997 to replace the Standard Industrial Classification (SIC) system. Originally developed during the 1930s and reflecting the economy of its time, the SIC provided far more detail for goods-producing industries such as manufacturing and mining than for service-producing industries. The 1997 NAICS added more than 149 new services industries. Just as important, a process was put in place to add new industries to NAICS as they develop. A parallel effort carried out over the past decade, the development of the North American Product Classification System, similarly will provide a consistent basis for categorizing the rich array of outputs produced in the growing service sector. The quality of the source data on the volume of service transactions also has improved over time. Since the 1980s, the BEA has collected data on international trade in services. In 2004, the Census Bureau introduced the Quarterly Services Survey (QSS) to provide more timely data on domestic consumption of services. The QSS, normally published about 2½ months after the end of each quarter, allows the BEA to incorporate actual survey data on many services into its quarterly estimates of GDP, rather than relying on “judgmental trends.” Furthermore, the Census Bureau has expanded the scope of its annual surveys of the service sector. In fact, the Services Annual Survey and the Quarterly Services Survey both now capture 55 percent of U.S. GDP—equaling the 52 | Chapter 2 coverage of services in the Economic Census and marking substantial improvement relative to even just a few years ago. Measurement of real activity in the service sector requires appropriate price deflators for service outputs. In 1990, the Producer Price Index (PPI) covered less than 5 percent of U.S. service output. Today, thanks to a concerted effort by the Bureau of Labor Statistics, PPI deflators are available for more than three-quarters of domestically provided services. This has translated directly into more accurate estimates of real GDP. Nevertheless, as the U.S. economy continues to evolve, the work of accurately measuring service activity grows accordingly. Despite recent innovations in the collection of primary source data, there are still conceptual issues pertaining to the appraisal and definition of services that remain unresolved. As an example, improvements in health care have contributed to longer life spans and better quality of life, but there is not a consensus about how to value and incorporate these benefits in a national income accounting framework. Similarly, industries such as finance largely produce intangible outputs that are difficult even to identify, much less quantify. Furthermore, although estimates of international trade in services are now more detailed than was the case before the 1980s, the statistics still could and should be improved. Data on the prices of traded services are extremely limited, and even the most disaggregated data collected by the BEA on services extend to only 36 categories, in contrast to thousands of categories for manufactured goods. Continued research and investment in the development of data on services are needed to ensure timely and accurate measurement of the U.S. economy. Although home prices in some parts of the country have stabilized, CoreLogic estimates that more than 20 percent of homeowners with mortgages remained underwater at the end of the third quarter of 2011 (that is, the value of the mortgage exceeds the house price). The share of mortgages in the foreclosure process remained elevated by historical standards in 2011 and changed little from the level in 2010, as reported by the Mortgage Bankers Association. For a description of the Administration’s housing policy proposals, see Chapter 4. Business Fixed Investment Business fixed investment grew at a solid 7.3 percent annual rate during the four quarters of 2011, after rising 11.1 percent at an annual rate The Year in Review and the Years Ahead | 53 in the four quarters of 2010. Among the two main components of business fixed investment, spending on equipment and software investment grew 9.0 percent over the four quarters of 2011, and investment in nonresidential structures increased 2.7 percent. Within equipment and software, purchases of transportation equipment rose at a brisk 22.7 percent annual rate over the four quarters of 2011, after having surged at a 68.1 percent annual rate in 2010. Business outlays on information technology rose at a 4.1 percent annual rate over the four quarters of 2011, a third consecutive year of solid growth. Investment in industrial equipment also grew notably, posting a four-quarter increase of 15.2 percent. (For more information on how investment is defined, see Data Watch 2-2.) Investment growth among the categories of nonresidential structures was mixed in 2011. On one hand, investment in mining and drilling structures was strong, reflecting elevated oil prices as well as some advances in technology that have enabled drilling at new sites. (See Chapter 8.) Investment in commercial and health care structures, on the other hand, edged down over the four quarters of 2011. The strength of business fixed investment since mid-2009 reflects several developments. Investment fell sharply during the recession, and, as the prospects for sales have begun to improve, businesses have invested in recent years to replace aging equipment. In addition, the Administration’s 100 percent business expensing policy boosted business investment by allowing firms to take an immediate deduction on investments made in new equipment in 2011. The President has proposed extending this provision into 2012. Business investment may be positioned to grow rapidly if demand accelerates because corporations have plenty of internal funds (Figure 2-6). Corporate profits continued to rise in 2011 and were above their pre-recession level, while corporate dividends have returned roughly to pre-recession levels. Largely as a result, corporate cash flow, a measure that includes undistributed profits and depreciation and represents the internal funds available for investment, has also risen substantially during the recovery. A large share of these investable funds has been channeled to financial investments rather than to new physical capital, as can be seen by the rising level of liquid assets held by nonfinancial corporations. Manufacturing Output The real output of U.S. factories rose 3.7 percent over the twelve months of 2011 after having risen 6.4 percent in 2010, according to the manufacturing component of the industrial production index published 54 | Chapter 2 Figure 2-6 Business Fixed Investment and Cash Flow, 1990–2011 Percent of potential GDP 14 13 12 11 2011:Q3 Nonresidential fixed investment Cash flow 10 9 2011:Q4 8 7 Liquid assets held by nonfinancial corporations 6 5 1990:Q1 1993:Q1 1996:Q1 1999:Q1 2002:Q1 2005:Q1 2008:Q1 2011:Q1 Note: Potential GDP is a CBO estimate. Cash flow, from the National Income and Product Accounts, and nonfinancial liquid assets are plotted using three-quarter moving averages. Source: Bureau of Economic Analysis, National Income and Product Accounts; Federal Reserve Board (Flow of Funds L.102); Congressional Budget Office. by the Federal Reserve Board. The manufacturing sector has been growing faster than the rest of the economy during the recovery, with real output rising at an average annual rate of 5.7 percent since its low in June of 2009—its fastest pace of growth in a decade. The rise in manufacturing output during the recovery has provided a considerable boost to the U.S. economy. Following two decades of shrinking employment—a trend that reflected both increases in automation and the lower labor costs in emerging-market economies—manufacturers in the United States have added more than 400,000 jobs since employment in the sector reached its low in January 2010. These numbers reflect an emerging trend of some companies bringing jobs back to the United States, as discussed in the special report, Investing in America: Building an Economy that Lasts (White House 2012). This nascent trend likely reflects, in part, the improvement in unit labor costs in the United States relative to many of our trading partners in recent years. (See Chapter 5 for more discussion of the rising competitiveness of U.S. industry.) The robust gains in manufacturing output during the recovery appear to reflect rising investment demand for domestically-produced capital goods from both domestic and foreign customers. The rebound of the U.S. motor vehicle industry has played a particularly large role, with the production of motor vehicles and parts directly accounting for about 23 percent of the increase in manufacturing output since mid-2009. As U.S. demand for new The Year in Review and the Years Ahead | 55 Data Watch 2-2: Investment in Intangibles Investment can be defined as devoting resources to produce a durable asset that will yield a future flow of services. Until recently, measures of investment in the National Income and Product Accounts (NIPAs) were restricted to investments in physical capital such as buildings, machinery, and equipment; new residential construction; and net additions to inventories. In today’s knowledge economy, however, intangible assets such as computer software and scientific innovations make increasingly important contributions to economic growth. The Bureau of Economic Analysis (BEA) has begun to incorporate investments in intangible capital into the NIPAs. The first step in this direction, taken in 1999, was to treat spending on computer software as an investment outlay, which enters GDP directly, rather than as a business expense, which is considered an intermediate input rather than a part of final demand; the treatment of government spending on computer software was changed at the same time. Because business and government spending on computer software had been growing rapidly compared to other types of spending, these changes raised the measured growth rate of GDP slightly. In 2013, BEA plans to begin treating spending on scientific research and development as an investment rather than an expense; had this treatment been in effect historically, it too would have raised the average measured rate of growth of GDP in recent decades. Some researchers have argued that investment in intangibles should be defined even more broadly (Corrado, Hulten, and Sichel 2009; Corrado and Hulten 2010). In addition to research and development that builds on a scientific base of knowledge, for example, there is an argument for treating as investment the money firms spend on other sorts of new product development, such as the development of new motion pictures or new financial services products. Businesses also spend money on strategic planning, the implementation of new business processes, and employee training, all of which may add significantly to future productivity and thus arguably should be treated as investment as well. Taking an even broader perspective, time and money devoted to formal education add to the human capital of the American workforce and thus to its future productivity. While accounting accurately for the value of these investments poses some difficult measurement challenges (Abraham 2010), their importance to future economic growth should not be overlooked. According to some research (Krueger 1999), returns on human capital generate the lion’s share of national income. 56 | Chapter 2 vehicles has recovered, the Detroit auto companies along with the foreigndomiciled auto companies have been expanding U.S. production to serve both U.S. and foreign markets. Over the past two years, the entire U.S. auto industry—including dealerships and suppliers of auto parts—has added nearly 160,000 jobs. General Motors was the world’s top-selling automaker in 2011, Ford is investing in new American plants, and sales at Chrysler grew faster in 2011 than in recent years. In addition to rescuing the American auto industry, the Administration has more broadly supported American manufacturing through its efforts to reduce barriers for American businesses to sell products all over the world. To build on the progress already made, the President laid out in his 2012 State of the Union address a Blueprint for an America Built to Last, which included proposals to encourage companies to create manufacturing jobs in the United States while removing tax deductions for shipping jobs overseas. Business Inventories Businesses continued to build inventories during 2011, and inventories in the manufacturing and trade sectors remained lean relative to sales. Inventory investment—measured as the change in inventories from one quarter to the next—is typically an important contributor to the changes in real GDP during recessions and the early stages of recoveries. Over the course of 2011, real inventory investment stepped up in the first quarter and then slowed in the second and third quarters, but closed out the year on a high note. The slower pace of inventory investment in the second quarter reflected, in part, the reduced rate of motor vehicle production caused by disruptions to the flow of auto parts following the earthquake and tsunami in Japan. Altogether, real inventory investment added roughly 0.2 percentage point to real GDP growth between the fourth quarter of 2010 and the fourth quarter of 2011. Government Outlays, Consumption, and Investment The Federal budget deficit during Fiscal Year 2011—which ended on September 30—was $1.3 trillion, roughly unchanged from the year before. As a share of GDP, the deficit fell to 8.7 percent in FY 2011 from 9.0 percent in FY 2010. Federal receipts rose 6.5 percent during FY 2011, largely driven by a 21.5 percent increase in individual income tax receipts. Corporate tax receipts fell 5.4 percent in FY 2011, partly reflecting the introduction of 100 percent depreciation for business equipment investment in calendar year 2011 (up from 50 percent in calendar year 2010), which pulls forward deductions that businesses would otherwise receive over several years. Corporate tax receipts in FY 2011 were only about half what they were in FY 2007, The Year in Review and the Years Ahead | 57 even as domestic corporate profits (excluding Federal Reserve Banks) were roughly unchanged.8 In contrast, individual income tax receipts in FY 2011 were more than 90 percent of their FY 2007 level. Federal outlays rose 4.2 percent in FY 2011 from FY 2010 but remained steady as a share of GDP at 24.1 percent. According to the CBO, approximately half of the year-over-year increase in Federal outlays reflects re-evaluations of the cumulative cost of the Troubled Asset Relief Program (TARP).9 The President’s FY 2013 Budget estimates that the cumulative cost of TARP will be $67.8 billion, well below the Administration’s 2009 estimate of $341 billion. Nominal spending on defense grew more slowly in FY 2011 than in recent years. Combined total spending on Social Security, Medicare, and Medicaid rose in FY 2011, though at a slower pace than the average over the past three years. According to the Department of Labor, extended unemployment benefits and emergency unemployment benefits are on track to be about $60 billion in 2011, following total benefits of $80 billion in 2010. The past three years of unemployment benefits stabilized consumer spending at a level higher than would have occurred absent this income support. In addition, the 2 percentage point reduction in payroll taxes through the end of 2011 lowered tax liabilities by about $114 billion. During the four quarters of calendar year 2011, real Federal expenditures on consumption and gross investment, as measured in the National Income and Product Accounts, declined 3.3 percent; federal defense spending fell 3.7 percent over the four quarters of 2011, and federal nondefense spending declined 2.6 percent. As projected in the Administration’s FY 2013 Budget, which includes demand-supporting initiatives for FY 2012 that have not yet been approved by the Congress, the deficit as a share of GDP will fall from 8.7 percent in FY 2011 to 5.5 percent in FY 2013, and to 3.4 percent in FY 2015. The fullemployment deficit as a share of GDP (the budget deficit that would exist if the economy were at full employment) would be roughly unchanged in FY 2012 and fall by about 3 percentage points in FY 2013 and by another 1.5 percentage points in FY 2014. This fiscal consolidation will restrain the 8 The divergence of corporate profits and corporate tax receipts between 2007 and 2011 reflects changes in tax policy and differences in how profits in the National Income and Product Accounts (NIPA) and corporate taxable income are calculated. Business credits for corporations have increased between 2007 and 2011. The components of NIPA profits that are not counted in taxable income include capital gains, bad debt, and Federal Reserve profits. 9 The CBO (2011c) estimates the net present value of the cumulative cost of TARP each year and—if costs are revised down—records the changes in these valuations in the Budget as a negative outlay. The CBO adjusted down the total cost of the program in FY 2010 and FY 2011, but the downward adjustment in FY 2011 was smaller than in FY 2010. 58 | Chapter 2 growth of demand in those years, but an increase in private-sector demand in those years is projected to fill in the gap. Looking further ahead, the deficit reduction from the cuts mandated by the Budget Control Act of 2011 and the expiration of the tax cuts on upper-income Americans enacted between 2001 and 2003, combined with the winding down of operations in Afghanistan and Iraq, will bring deficits down to approximately 2.8 percent of GDP near the end of the 10-year budget window. Policy changes recommended in the FY 2013 Budget put the debt on a stable or declining path as a share of the economy and would—if enacted—place the budget in a fiscally sustainable position in the ten-year budget window. State and Local Governments State and local governments remained under severe fiscal pressure in 2011, and, as noted, declines in this sector’s revenues have forced sharper declines in real State and local consumption and gross investment than in earlier U.S. recoveries. Although nominal State and local government tax receipts continued to increase in 2011, Federal funds from the Recovery Act—which helped support State and local governments during 2009 and 2010—declined, and employment continued to contract. State and local tax revenues rose about 4 percent, or $50 billion, during the four quarters through the third quarter of 2011, roughly the same pace as during the year-earlier period. About half of the rise came from personal income taxes. State and local taxes on production and imports—a category that includes sales and property taxes—increased about $32 billion over this period, while corporate taxes were down $8 billion. Federal grantsin-aid to the states plunged $87.8 billion during the four quarters of 2011 after rising notably during 2009 and 2010; both the earlier increase and the 2011 decline were attributable to the Recovery Act, which was designed to offer temporary support to State and local governments. Current State and local government expenditures—which include transfers to individuals as well as government consumption—fell 0.2 percent over the four quarters of 2011, following a 4.4 percent increase in the year-earlier period. Reflecting, in part, the decline in Federal grants-in-aid between the third quarters of 2010 and 2011, the operating position of State and local governments deteriorated to an aggregate deficit of $83 billion by the third quarter of 2011, the fourth consecutive year of operating deficits for the State and local sector. Employment in State and local government declined by 235,000 in 2011, and employment in the sector fell 660,000 from its peak in August The Year in Review and the Years Ahead | 59 2008 to December 2011. About 36 percent of the jobs lost over this period were in education. Real investment by State and local governments in structures, such as schools, roads, and bridges, fell 9.9 percent during the four quarters of 2011, a decline notably steeper than those of the preceding three years. Some of the decline is attributable to the expiration of the Build America Bonds program at the end of 2010. Part of the Recovery Act, the program subsidized municipal bonds issued for infrastructure development and helped finance $181 billion worth of capital projects, including schools, bridges, and hospitals (Department of Treasury 2011). State and local governments have made tough budget decisions during the past four years. They will likely continue doing so in 2012 as Federal transfers diminish, and past declines in house prices erode the property tax base. The Administration took important steps in 2010 and 2011 to help State and local governments maintain critical services in public safety and education. In addition to the grants-in-aid components of the Recovery Act, the Administration eased the burden on State and local governments in August 2010 by establishing a new teacher job fund and by extending the enhanced Federal matching formula for certain social services and medical insurance expenditures covered by the States. In 2011, the President proposed additional funds as part of the American Jobs Act to prevent layoffs of teachers, police, and firefighters. To support infrastructure investment, the Administration also included funds in the American Jobs Act to modernize more than 35,000 schools. Real Exports and Imports Real exports grew 5.2 percent during the four quarters of 2011 after jumping 8.8 percent in 2010. As noted, the rebound in exports since the trough of the recession has been strong and reflects rising demand for U.S. goods and services abroad. Total exports rose at an average rate of almost 16 percent per year between 2009 and the twelve-month period that ended in November 2011, an increase that creates jobs for U.S. workers and puts U.S. exports on track to meet the President’s goal of doubling nominal exports between 2009 and the end of 2014. Meeting this goal depends, in part, on healthy growth of the world economy; world growth, however, may falter in the near term for reasons related to the sovereign debt crisis in Europe. Maintaining robust exports is a key to building an American economy that can prosper in the global economy in the years to come (see Chapter 5). Real imports also grew in 2011, expanding 3.8 percent over the four quarters of the year. The rise in real imports over the past year likely reflects 60 | Chapter 2 the increase in consumer spending on goods, the rise in real business fixed investment, and the continued recovery in industrial production in 2011. All told, real net exports—exports less imports—made a small positive contribution to the rise in real GDP over the four quarters of 2011, after subtracting from real GDP growth in the year-earlier period. Labor Market Trends The job market continued to heal in 2011, adding a total of 1.8 million jobs. The private-sector added 2.1 million jobs during the twelve months of 2011, while State and local government employment fell by 235,000. The growth in private-sector jobs was the strongest since 2005. Private sector payroll employment has grown in each month since February 2010, and layoffs—as measured by the four-week average of initial claims for unemployment insurance—have come down considerably over this period (Figure 2-7). The four-week average of initial claims continued to recede through the end of January 2012. Private-sector job growth during the current recovery has been similar to that in the 1991 recovery and faster than that in the 2001 recovery, as illustrated in Figure 2-8. As is typical, the recovery in jobs since 2009 has lagged the recovery in output. Growth in private nonfarm jobs in the current recovery began nine months after the business-cycle trough. By comparison, Figure 2-7 Weekly Initial Unemployment Insurance Claims, 2004–2012 Thousands, seasonally adjusted 700 600 500 400 Week ended 1/28/2012 300 200 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Note: Four-week moving average. Shading denotes recession. Source: Department of Labor, Employment and Training Administration. 2011 The Year in Review and the Years Ahead 2012 | 61 payrolls first began expanding consistently twelve months into the 1990–91 recovery, and sustained private-sector job growth in the 2001 recovery did not begin until 21 months after the official end date of the recession. Thus, although the 2007–09 recession lasted longer and featured job losses much deeper than those in the recessions of 1990–91 and 2001, recovery in the labor market began somewhat sooner. Nonetheless, the steep rate of job loss during the recession has left the rate of unemployment high. During the recovery the unemployment rate receded from its peak of 10.0 percent in October 2009 to 8.3 percent by January 2012. The unemployment rate dropped by 0.6 percentage point between October 2011 and January 2012 (Figure 2-9). Other measures of labor market slack—such as the “U-6” unemployment rate published by the Bureau of Labor Statistics—have also declined over the past year. The U-6 measure includes in the pool of unemployed workers those who are underemployed or are marginally attached to the labor force, that is, would like a job but are not currently searching for work. The U-6 unemployment rate in January 2012 was a percentage point below its year-earlier level. In addition to tracking the number of jobs added in 2011, other margins of labor market adjustment such as the workweek also contain important information about the pace of the recovery. At the business-cycle peak in the fourth quarter of 2007, the workweek for all private-sector employees Figure 2-8 Private Nonfarm Employment During Recoveries Indexed to 100 at NBER-defined trough 108 106 Current (June 2009 trough) 104 1991 102 100 2001 98 96 -6 Trough 6 12 18 24 30 36 Months from trough Source: Bureau of Labor Statistics, Current Employment Statistics; National Bureau of Economic Research; CEA calculations. 62 | -36 -30 Chapter 2 -24 -18 -12 Percent 11 Figure 2-9 Unemployment Rate, 1979–2012 10 9 8 Jan-12 7 6 5 4 3 1979 1983 1987 1991 1995 1999 2003 Note: Shaded areas represent recessions. Source: Bureau of Labor Statistics, Current Population Survey. 2007 2011 averaged 34.6 hours. By the second quarter of 2009, it had shortened 0.8 hour. By the fourth quarter of 2011, the workweek increased to 34.4 hours, recovering most of the hours lost during the recession. A 0.1 hour lengthening of the workweek is roughly equivalent, in terms of labor input, to an increase in employment of more than 300,000 jobs. Wages, Labor Productivity, and Prices Hourly compensation rose at about the same pace in 2011 as in 2010. The employment cost index for private-sector workers, including wages and benefits, rose 2.1 percent over the twelve months of 2011, roughly the same as the year-earlier increase. Nominal hourly compensation in the nonfarm business sector—a measure based primarily on compensation in the National Income and Product Accounts—rose 1.7 percent during the four quarters of 2011, up slightly from the pace during 2010 but well below the average increase of about 4.0 percent in 2006 and 2007. Labor productivity in the nonfarm business sector (that is, real output per hour worked) rose about 0.5 percent during the four quarters of 2011, a slower pace of growth than during the preceding two years. Averaged over the nearly four years since the business-cycle peak, labor productivity grew at a 1.8 percent annual rate. The Year in Review and the Years Ahead | 63 Consumer prices—as measured by the consumer price index (CPI)— rose almost 3 percent during the twelve months of 2011, 1.6 percentage points more than they did in 2010 (Figure 2-10). The cost of food, crude oil, and many other commodities rose sharply in the first half of 2011, and some of these increases were passed through to consumer prices for food and energy products. Excluding food and energy products, the core CPI rose a more moderate 2.2 percent during the 12 months of 2011 after rising at an unusually slow pace of 0.8 percent in 2010. Over the second half of 2011, overall consumer price inflation fell considerably as the price pressures from the earlier increases in energy and commodity prices waned. After rising at an annual rate of 3.8 percent in the first six months of the year, consumer price inflation fell to 2.2 percent between June and December. Most of the inflation in nonfarm business prices during the past four years has been due to a rise in the price markup over unit labor costs rather than to rising unit labor costs. Hourly compensation has risen at a roughly 2 percent annual rate during the four years since the business-cycle peak, but this growth has been offset by growth of labor productivity also by an annual rate of about 2 percent during the same period, leaving unit labor costs essentially unchanged. Over the long run, prices of nonfarm business output rise in a roughly parallel fashion to unit labor costs, so the markup of prices relative to unit labor costs has been flat, although it has certainly fluctuated in the short run. As can be seen in Figure 2-11, this long-term property of the U.S. economy appears to have broken down over the past decade. The markup has now risen to its highest level in post–World War II history, with much of that increase taking place over the past four years. Because the markup of prices over unit labor costs is the inverse of the labor share of output, saying that an increase in the price markup is the highest in postwar history is equivalent to saying that the labor share of output has fallen to its lowest level. The Administration expects consumer prices to rise slightly below 2 percent a year for the next few years, edging up to a 2.1 percent annual rate in the long run. The long-run projection is in line with the levels of inflation deemed by the Federal Reserve as consistent with stable prices and full employment, and only slightly below survey measures of long-run inflation expectations and the 5-year forward inflation rate implied by the yields on inflation-protected Treasury securities.10 Moreover, because slack in the labor market remains, the economy has considerable room to expand without increasing price pressures. 10 The Survey of Professional Forecasters projects the CPI will grow at an average annual rate of 2.5 percent from 2011 through 2020. 64 | Chapter 2 Figure 2-10 Consumer Price Inflation, 2004–2011 12-month percent change 6 5 Headline Dec-11 4 3 2 1 Core 0 -1 -2 -3 2004 2005 2006 2007 2008 2009 Source: Bureau of Labor Statistics, Consumer Price Index. 2010 2011 2012 Figure 2-11 Price Markup over Unit Labor Costs, Nonfarm Business, 1947–2011 Ratio of prices to unit labor costs 2.00 2011:Q4 1.75 Markup over unit labor costs 1.50 Average markup 1947:Q1-2011:Q4: 1.57 1.25 1947:Q1 1957:Q1 1967:Q1 1977:Q1 1987:Q1 1997:Q1 2007:Q1 Note: Shading denotes recession. Source: Bureau of Economic Analysis, National Income and Product Accounts; Bureau of Labor Statistics, Productivity and Costs; CEA calculations. The Year in Review and the Years Ahead | 65 Financial Markets The past year was a volatile one for financial markets. Concerns that had arisen late in 2009 over sovereign debt in Greece and Portugal continued into 2011 and spread to several larger countries in the European Union, with effects that were felt worldwide. Following a 12.8 percent gain in 2010, U.S. equity prices—as measured by the Standard and Poor’s 500 Composite Index—were essentially flat in 2011. External factors weighed heavily on investor sentiment at times over the course of the year. After rising more than 8 percent from the end of 2010 through April, equity values plunged during the summer, reflecting the uncertainty surrounding the European sovereign debt problems and the protracted negotiations over raising the statutory U.S. Federal debt ceiling. Measures of market volatility—such as the Market Volatility Index (VIX)—rose sharply in mid-2011 before retreating near the end of the year. The VIX reached levels in 2011 that were about equal to those in mid-2009 but remained well below record levels in late 2008. The day-to-day changes in the S&P index exceeded 1 percentage point on 96 days in 2011, 20 days more than in 2010. In 2005 and 2006, swings in the S&P index exceeded a percentage point only 30 times per year on average. Yields on 10-year Treasury notes were 1.98 percent in December 2011, down from 3.29 percent in December 2010 (Figure 2-12). Ten-year yields rose to a monthly high of 3.58 percent in February of 2011, as investors Percent 6 Figure 2-12 10-Year Treasury Yields, 2004–2012 5 Nominal 4 Feb.2 3 2 Real 1.86% 1 0 -0.30% -1 2004 2005 2006 2007 Source: Federal Reserve Board, H.15. 66 | Chapter 2 2008 2009 2010 2011 2012 elevated their outlook for the U.S. economy. Renewed concerns about sovereign debt issues in Europe, however, triggered a flight to safety that pushed down long-term rates, on balance, during the remainder of 2011. The Federal Reserve System’s program to lengthen the maturity of the portfolio of their U.S. government debt also held down long-term rates. Over the final five months of the year, 10-year Treasury yields fluctuated around 2 percent, and real long-term interest rates at the same maturity, as indicated by the market for Treasury Inflation-Protected Securities, fluctuated around zero. When the Administration’s economic forecast was finalized in midNovember 2011, interest rates, both short- and long-term, were recognized as being in the low end of their historical range. Yet, in light of the Federal Reserve’s August 9 announcement that “economic conditions … are likely to warrant exceptionally low levels for the federal funds rate at least through mid-2013,” the Administration did not foresee any material changes in short-term interest rates over the near term. Thus, the Administration’s projected path for 91-day Treasury bills, calibrated from rates in the market for federal funds futures, anticipated that these rates would remain extremely low until the second half of 2013. The FOMC forecasted in January 2012 that these rates would remain low at least through late 2014. Small Businesses and the Recovery Small firms—with fewer than 500 employees—account for about half of private-sector nonfarm employment. Between 1993 and 2010, more than half of firms in the private sector had 1 to 4 employees, and nearly 98 percent had fewer than 100 employees. Figure 2-13 illustrates that small firms experienced proportionately larger job losses than large firms during the recession and until early 2010. Similarly, the number of bank loans to small firms fell dramatically during the recession and—although it has stabilized since—still has not returned to pre-recession levels (see Figure 2-14). In 13 consecutive quarters between 2007:Q1 and 2010:Q1, respondents to the Federal Reserve’s Senior Loan Officer Opinion Survey reported that credit tightened or remained tight for small firms (those with less than $50 million in annual sales) and that, since 2010, credit standards for large firms eased at a faster rate than for small firms. Small firms depend more on banks for financing than do larger firms, in part because larger firms have access to other forms of finance, including public debt and equity markets, typically unavailable to small firms. Petersen and Rajan (1994) have documented the critical relationship between banks and small firms and showed that over half of financing for small firms came The Year in Review and the Years Ahead | 67 Figure 2-13 Private Sector Job Recovery by Firm Size, 2007–2011 Indexed to 100 at 2007:Q4 102 100 98 96 2011:Q2 94 Large firms 92 Small firms 90 88 2007:Q1 2008:Q1 2009:Q1 2010:Q1 2011:Q1 Note: Small firms have fewer than 500 employees. Shaded area denotes recession. Source: Bureau of Labor Statistics, Business Employment Dynamics. from bank finance. 11 Economists have modeled a link between the supply of credit and macroeconomic activity (Bernanke 1983; Holmstrom and Tirole 1997; and Peek and Rosengren 2000). Credit conditions have been shown to affect a variety of specific macroeconomic outcomes, including investment spending, inventories, and economic growth and development (Fazzari, Hubbard, and Petersen 1988; King and Levine 1993; Kashyap, Lamont, and Stein 1994; Levine and Zervos 1998; Rajan and Zingales 1998; and Guiso, Sapienza, and Zingales 2004). Gertler and Gilchrist (1994) find that smaller manufacturing firms respond more to money supply conditions than larger firms, and Kroszner, Laeven, and Klingebiel (2007) use cross-country evidence to show that banking crises negatively affect bank-dependent firms more than they affect firms less dependent on bank finance. The credit-contraction hypothesis has been used to explain the steeper loss of employment in small firms. Until recently, however, the literature from the recent financial crisis has largely been unable to disentangle the contributions of credit-supply and aggregate-demand conditions. DuyganBump, Levkov, and Montoriol-Garriga (2011) use data from the Current Population Survey, Compustat, and the National Survey of Small Business 11 Small firms in their paper are the smallest 10 percent of the sample measured by the book value of assets. Their sample, which is drawn from the Federal Reserve’s National Survey of Small Business Finances conducted in 1988 and 1989, contains 3,404 firms with fewer than 500 employees. 68 | Chapter 2 Figure 2-14 Small Business Commercial and Industrial Loans, 2007–2011 Billions of dollars 400 350 Value of loans (left axis) Number of loans (right axis) Millions of loans 40 35 2011:Q3 300 30 250 25 200 20 150 15 100 10 50 5 0 2007 2008 2009 2010 Note: Loans with original amounts of less than $1 million. Source: Federal Deposit Insurance Corporation, Statistics on Banking. 2011 0 Finances to separate the contributions of these two factors. They find that, as in previous recessions involving banking crises, following the crisis of 2007–09, the likelihood of becoming unemployed was greater in sectors that were more dependent on external finance. Further, among firms highly dependent on banks for financing, the likelihood that an employee will become unemployed is greater in small firms (defined as those with 99 or fewer employees).12 The authors do not observe such a divergence in unemployment incidence in firms with low dependence on external finance. Prior to the financial crisis, the share of lending to small businesses by the largest banks—those with assets of over $50 billion—had risen substantially (Corner and Bhaskar 2010). Since 2009, however, financing has been constrained and it remains so for small firms seeking funding. Simultaneously, the data show that other financial institutions—smaller banks, credit unions, and other alternative lenders—and governmentsponsored programs have filled part of this gap. Between January and December 2011, Biz2Credit, a private firm that matches over 1.5 million small businesses seeking loans to nearly 500 lenders and loan intermediaries, reports that loan-approval rates by large banks fell 3.1 percentage points, while increasing 3.6 percentage points at small banks, 8.5 percentage points 12 This evidence does not address whether the credit-supply conditions are due to factors related to lower credit quality. The Year in Review and the Years Ahead | 69 Box 2-1: SBA’s Role in Financing Small Firms During the Recovery The Small Business Administration (SBA) was created by Congress in 1953 to aid and provide technical support for small businesses.1 Many SBA programs seek to minimize the riskiness of small-business loans for lenders by guaranteeing a portion of these loans against default. SBA collaborates with federal agencies and the White House to ensure that at least 23 percent of Federal Government contract opportunities, worth nearly $100 billion, are available to small businesses. Traditional SBA programs, the 7(a) and 504 loans, target small firms. These programs have been found to have a positive impact on local economic performance (Craig, Jackson, and Thomson 2005). In response to ongoing tight credit conditions facing small firms during the recovery, the Small Business Jobs Act of 2010 increased the loan limits for SBA loan guarantees. The limits for equipment and real estate loans were increased permanently and the limits for working capital loans through the SBA Express program were increased temporarily. Between FY2010 and FY2011, the number of SBA loans approved increased 12.5 percent, while the value of SBA loans approved increased 45.4 percent (see box figure). SBA increased overall lending supported to $30.5 billion in FY 2011, the highest ever lending year in its 60-year history.2 Recent economic research shows that new and young firms contribute disproportionately to job growth in the U.S. (see Chapter 6). The Obama Administration has created the Startup America initiative to support the role that startups play in economic growth and job creation. The initiative aims to accelerate high-growth entrepreneurship through policies that unlock access to capital for high-growth companies, create mentoring programs, accelerate lab-to-market innovation, and make government work better for entrepreneurs. As a part of the Startup America initiative, SBA is improving access to capital for high-growth small businesses. The SBA has launched two new Small Business Investment Company (SBIC) programs, each seeking to guarantee an additional $1 billion in private investment within five years: the Early-Stage Innovation Fund for seed- and early-stage companies and the Impact Investment Fund for companies in areas of national priority, including underserved markets and emerging 1The Small Business Administration’s definition of a small business uses guidelines that reflect, among other things, sales, employment levels, and sector of economic activity. These guidelines are available online at http://www.sba.gov/sites/default/files/Size_Standards_ Table.pdf. 2 Lending supported includes gross loan approvals for SBA’s 7(a) and 504 programs as well as third-party loans that are made by commercial lenders as part of the 504 funding package. The box figure depicts the value of loans 7(a) and 504 loans approved, which will be smaller than the value of loans supported. 70 | Chapter 2 sectors, such as energy and education. SBA licensed the first SBIC Impact Investment Fund in Michigan in July 2011. The InvestMichigan! Mezzanine Fund, with resources of $130 million, is a public-private partnership between SBA, Dow Chemical Company, and Michigan Growth Capital Partners that will be managed privately and will focus on funding new and small firms with plans to expand their operations and create jobs. SBA also deepened its commitment to underserved markets in 2011 with the implementation of the Underserved Markets Initiative, which will disseminate SBA resources to youth, rural, veteran, low-income, and other communities. SBA Loans Approved, 2006-2011 Billions of dollars 30 28 26 Thousands of loans 120 110 Value of Loans Number of Loans 100 24 90 22 20 80 18 70 16 60 14 50 12 10 2006 2007 2008 2009 2010 Source: Small Business Administration, Agency Financial Report, 2011. 2011 40 SBA augmented its role as a coordinator of federal agencies in supporting small businesses in 2011. As is common after financial crises, small firms are experiencing difficulties managing cash flow due to adverse credit conditions. To improve access to working capital for thousands of small firms, in September, President Obama issued an executive order to institute the QuickPay program, which requires an agency to pay its contractors within 15 days and, at a maximum, within 30 days. As with the QuickPay program, SBA plays a coordinating role for the Small Business Innovation Research (SBIR) program, which focuses on small high-technology firms and includes 11 granting agencies. Evidence suggests that SBA and SBIR involvement make a difference to young firms. Between 1983 and 1997 awardees of the SBIR program subsequently had substantially higher employment and sales growth compared to a matched sample of similar firms (Lerner 1999). In December, Congress passed a long-term reauthorization of the SBIR program that will increase its funding. The Year in Review and the Years Ahead | 71 at credit unions, and 12.9 percentage points at other alternative lenders, such as CDFIs, microlenders, and accounts-receivable financiers.13 In 2009, the Obama Administration increased the amount of capital invested in financial institutions and other entities to support small-business lending. This lending evolved along two lines: investing capital directly into financial institutions that provide small business loans and adding funding to new and existing programs that provide credit support to small business loans. In terms of direct investment that strengthened small-business lending, the Administration invested more than $11 billion in over 1,000 financial institutions, most of which were small banks but also including credit unions, Community Development Financial Institutions (CDFIs), and business loan funds. The programs that provide small-business credit support include the new State Small Business Credit Initiative (SSBCI), which is expected to channel $15 billion in new small-business lending, as well as existing programs, such as loan-guarantee programs housed at the Small Business Administration (SBA), the Department of Agriculture, and the Export-Import Bank. Other Administration initiatives also helped small firms gain access to capital at a critical period. For example, the Financial Stability program was modified in 2009 to protect auto parts suppliers, 82 percent of which employ less than 100 workers, to ensure that they would be paid for any parts they shipped, regardless of the fate of the recipient car company. Given the integral role auto-parts manufacturers play in the manufacturing supply chain, systemic failure in this sector would have had a substantial effect on the auto industry, the manufacturing supply chain, output, and employment.14 By the end of FY2011, marked increases in these capital-access programs were partly due to the introduction of two new programs administered by Treasury—the Small Business Lending Fund (SBLF) and the SSBCI—and increases in the scope of the aforementioned loan-guarantee programs. As of the beginning of January, institutions participating in the SBLF have increased lending to small businesses by roughly $3.5 billion over their baseline, and, in Fiscal Year 2011, SBA supported over $30 billion in loans. (Box 2-1 further describes the Administration’s efforts to address credit constraints among small businesses through the SBA’s loan-guarantee programs administered through bank finance and Startup America.) The most recent data on the expectations of small businesses concerning financing and future job growth suggest that these efforts, along with 13 Small firms in the Biz2Credit sample are firms with fewer than 500 employees and under $6 million in annual revenue. Loan-approval rates are based on a random sample of 1,000 firms in the Biz2Credit database reported each month between January 2011 and December 2011. 14 It is estimated that intervention in the auto industry broadly averted a loss of approximately 1.1 million jobs and hundreds of small businesses (White House 2010). 72 | Chapter 2 Figure 2-15 Employment Outlook for Small Businesses, 2003–2012 Percent of respondents 35 30 25 20 2012:Q1 Employment expected to increase over next 12 months 15 10 Employment expected to decrease over next 12 months 5 0 2003-Q3 2005-Q3 2007-Q3 2009-Q3 2011-Q3 Note: Small firms have less than $20 million in annual revenue. Shaded area denotes recession. Source: Wells Fargo/Gallup Small Business Survey cited in Jacobe (2012). the ongoing economic recovery, are having a positive effect. Small-business owners who responded to the Wells Fargo-Gallup survey conducted from January 9 to 13, 2012, for example, report being more optimistic than at any time since July 2008. This sentiment is largely attributed to sharp increases in their expectations related to their firms’ financial situation, i.e., revenue and cash flow.15 Moreover, respondents’ hiring plans have become more optimistic than at any point since January 2008, as Figure 2-15 illustrates. In early 2012, more small businesses expected to add new employees in the next 12 months (22 percent) than expected to let them go (8 percent). This is the biggest margin by which small businesses’ expectations for increasing jobs have exceeded those for decreasing jobs since the start of the financial crisis in 2008. The Long-Term Outlook Looking ahead, the Administration projects that the economic recovery that began in 2009 will continue and gather speed (Table 2-1). In the economic forecast, which was used to estimate the FY 2013 Budget, inflation 15 The Wells Fargo-Gallup telephone survey was based on a nationally representative sample of 604 firms extracted from the Dun & Bradstreet database of firms earning $20 million in annual revenue or less. See Jacobe (2012). The Year in Review and the Years Ahead | 73 remains moderate, interest rates rise gradually, and the rate of unemployment recedes. The Administration projects real GDP growth to rise to 3 percent in 2012 and 2013 after growing 1.6 percent during the four quarters of 2011. The Administration also expects the employment situation to continue to improve in coming years: The Administration’s unemployment rate forecast—also completed in mid-November 2011, when the latest-available reading on the unemployment rate was 9.0 percent for October, is shown in the first column of Table 2-2. The Budget forecast does not reflect the improvement in the job market since the forecast was finalized. Since that forecast was completed, the unemployment rate has fallen to 8.3 percent, beginning 2012 well below the 8.9 percent unemployment rate that had been forecast for the year as a whole. This should not be interpreted as a projection that the unemployment rate will rise: instead, it is the result of an out-of date forecast. The second, third, and fourth columns of Table 2-2 show a range of forecasts that were completed more recently so as to illustrate a plausible range through which the unemployment rate is likely to evolve. Table 2-1 Administration Economic Forecast Nominal GDP Real GDP (chaintype) GDP price index (chaintype) Consumer price index (CPI-U) Percent change, Q4-to-Q4 Interest rate, 91-day Treasury bills (percent) Interest rate, 10-year Treasury notes (percent) Level, calendar year 2010 (actual) 4.7 3.1 1.6 1.2 0.1 3.2 2011 4.0 1.7 2.2 3.6 0.1 2.8 2012 4.6 3.0 1.6 1.9 0.1 2.8 2013 4.7 3.0 1.6 1.9 0.2 3.5 2014 5.8 4.0 1.7 2.0 1.4 3.9 2015 6.1 4.2 1.8 2.0 2.7 4.4 2016 5.8 3.9 1.8 2.1 3.8 4.7 2017 5.7 3.8 1.8 2.1 4.1 5.0 2018 4.6 2.8 1.8 2.1 4.1 5.1 2019 4.4 2.6 1.8 2.1 4.1 5.1 2020 4.3 2.5 1.8 2.1 4.1 5.1 2021 4.3 2.5 1.8 2.1 4.1 5.3 2022 4.3 2.5 1.8 2.1 4.1 5.3 Note: 2011-2022 forecasts were based on data available as of November 15, 2011, and were used for the FY 2013 Budget. The interest rate on 91-day T-bills is measured on a secondary-market discount basis. Source: The forecast was done jointly by the Council of Economic Advisers, the Department of Commerce (Bureau of Economic Analysis), the Department of the Treasury, and the Office of Management and Budget. 74 | Chapter 2 Table 2-2 Alternative Labor Market Forecasts, as of February 2012 Unemployment rate (percent) Fourth quarter Annual average Blue Chipc low-high Feb-2012 FOMCd low-high Jan-2012 Nonfarm payroll employmente (average monthly change, Q4-to-Q4, thousands) Feb-2012 FY 2013 Budgeta Nov-2011 CBOb Dec-2011 2011 9.0 9.0 — — 146 2012 8.9 8.8 8.0 – 8.6 8.2 – 8.5 167 2013 8.6 9.1 7.4 – 8.4 7.4 – 8.1 220 2014 8.1 8.7 — 6.7 – 7.6 264 2015 7.3 7.4 — — 284 2016 6.5 6.3 — — 259 2017 5.8 5.7 — — 251 2018 5.5 5.5 — — 131 2019 5.4 5.5 — — 101 2020 5.4 5.4 — — 92 2021 5.4 5.4 — — 97 2022 5.4 5.3 — — 89 The Administration Budget forecast (done jointly by the Council of Economic Advisers, the Office of Management and Budget, the Department of the Treasury, and the Department of Commerce) was based on data available as of November 15, 2011. b The Congressional Budget Office forecast was completed in early December. c The Blue Chip Economic Indicators for February 2012 was based on a survey of more than 50 professional forecasters conducted on February 6-7, 2012. The high-10 and low-10 forecasts are the average of the ten highest and ten lowest forecasts. d The high and low end of the central tendency of the Federal Open Market Committee announced on January 25, 2012. e Based on data available on February 5, 2012. Source: Aspen Publishers, Blue Chip Economic Indicators; Federal Reserve, Federal Open Market Committee. a In early February, the ten forecasters with the lowest unemployment rate forecasts on the Blue Chip panel of professional forecasters projected that the unemployment rate would average 8.0 percent in 2012 and 7.4 percent in 2013 while the highest ten projected 8.6 and 8.4 percent for those two years. Similarly, the members of the Federal Reserve’s Open Market Committee projected a central-tendency band of 8.2 percent to 8.5 percent for the fourth quarter of 2012 and 7.4 to 8.1 percent for 2013. And it should be noted that the CBO and FOMC forecasts are somewhat out of date in view of the encouraging January labor market report. The Council of Economic Advisers’ forecast for the gain in payroll employment was finalized in early February, after the labor market report was released showing growth of 157,000, 203,000, and 243,000 in November, December, and January, respectively. Looking ahead, the average monthly change in payroll employment is projected to rise from 146,000 in 2011 to The Year in Review and the Years Ahead | 75 about 167,000 in 2012. At this pace, two million jobs will be created during 2012, an increase from the 1.8 million created last year. Despite shocks that slowed growth in 2011, the Administration expects an upturn in economic growth. With the economy now operating below its capacity and many resources still underutilized, we forecast that the recovery will continue to gain strength. Growth in GDP over the Long Term The growth rate of the economy over the long run is determined by the growth of its supply-side components, although growth rates over shorter periods can vary considerably. The growth rate that characterizes the long-run trend in real U.S. GDP—or potential GDP—plays an important role in guiding the Administration’s long-run forecast, because actual GDP tends to gravitate toward its potential in the long run. Between 2011:Q3 and 2022:Q4—the projection period for the FY 2013 Budget—potential real GDP is projected to grow at a 2.5 percent annual rate. Table 2-3 shows the Administration’s forecast for the contribution of each supply-side factor to the growth in potential real GDP. The factors include the population, the rate of labor force participation, the employed share of the labor force, the ratio of nonfarm business employment to household employment, the workweek, labor productivity, and the ratio of real GDP to nonfarm output. Each column in Table 2-3 shows the average annual growth rate for each component over a specific period of time: The first column shows the long-run average growth rates between the business-cycle peak of 1953 and the business-cycle peak of 2007, with business-cycle peaks chosen as end points to remove the substantial fluctuations within cycles and to reveal long-run trends. The second column shows average growth rates between 2007:Q4 and 2011:Q3, a period that includes the 2007-09 recession and the recovery so far. The third column shows the Administration’s projection for the 11-year period from 2011:Q3 to 2022:Q4, and the fourth column shows average projected growth rates between 2007:Q4 and 2022:Q4, a blended forecast period over which the effects of the recession and recovery are offsetting. The working-age population is projected to grow 1.0 percent a year, on average, over the projection period (line 1, column 3), the same rate of growth that is projected by the Census Bureau. Over this same period, the labor force participation rate is projected to decline 0.1 percent a year (line 2, column 3), primarily because of longstanding demographic trends. The projected moderate decline in the labor force participation rate reflects the balance of opposing influences. The entry of the baby-boom generation into its retirement years is expected to reduce the participation rate in the 76 | Chapter 2 Table 2-3 Components of Actual and Potential Real GDP Growth, 1952–2022 Growth ratea Component History, peak-topeak Recent history, since peak Forecast History and forecast, since peak 1953:Q2 to 2007:Q4b 2007:Q4 to 2011:Q3 2011:Q3 to 2022:Q4 2007:Q4 to 2022:Q4 1 Civilian noninstitutional population aged 16+ 1.4 1.1 1.0 1.0 2 Labor force participation rate 0.2 –0.8 –0.1 –0.3 3 Employed share of the labor force –0.0 –1.2 0.4 –0.0 4 Ratio of nonfarm business employment to household employment 0.0 –1.0 0.1 –0.2 5 Average weekly hours (nonfarm business) –0.3 –0.1 0.0 –0.0 6 Output per hour (productivity, nonfarm business) 2.1 1.9 2.3 2.2 7 Ratio of real GDP to nonfarm business output –0.2 0.2 –0.5 –0.3 8 Sum: Actual real GDP 3.2 0.1 3.1 2.4 9 Memo: Potential real GDP 3.2 2.5 2.5 2.5 All contributions are in percentage points at an annual rate. b 1953:Q2 and 2007:Q4 are business-cycle peaks. Note: Population, labor force, and household employment have been adjusted for discontinuities in the population series. Nonfarm business employment, workweek, and productivity come from the Labor Productivity and Costs database maintained by the Bureau of Labor Statistics. Source: Bureau of Labor Statistics, Current Population Survey, Labor Productivity and Costs; Bureau of Economic Analysis, National Income and Product Accounts; Department of the Treasury; Office of Management and Budget; CEA calculations. a coming years, but some of this reduction is projected to be offset as the labor market improves. The labor force participation rate may also receive a boost during the forecast period from the recent increase in the share of young adults enrolled in school. The share of young adults aged 16 to 24 enrolled in school rose well above its trend between January 2008 and December 2011, sufficient to account for the entire decline in the labor force participation rate for this age group over this period (Figure 2-16). As these young adults complete their education, they are expected to re-enter the labor force. Taking into account all of these effects, the labor force participation rate is projected to recede about 0.1 percent a year between now and 2022. The employed share of the labor force—which is equal to 1 minus the unemployment rate—is expected to increase 0.4 percent per year over the next 11 years (line 3, column 3) but to be nearly unchanged, on balance, between 2007 and 2022 (line 3, column 4). 16 Because of the recession, the employed share of the labor force has contributed negatively to GDP growth 16 To be precise, changes in the employment ratio reduce growth in real GDP by 0.04 percentage point per year between 2007:Q4 and 2022:Q4, because the unemployment rate in 2007:Q4 (4.8 percent) was below the level consistent with stable inflation, which is expected to remain stable at around 5.4 percent from 2007 through the end of the projection period. The Year in Review and the Years Ahead | 77 Figure 2-16 Labor Force Participation and Educational Enrollment, Ages 16–24, 2002–2011 Percent, seasonally adjusted 100 2011:Q4 90 Labor force participation and enrollment rate 80 70 Labor force participation rate 60 50 Educational enrollment rate 40 2002:Q1 2004:Q1 2006:Q1 2008:Q1 2010:Q1 2012:Q1 Note: Enrollment rate is defined as the number of those enrolled in school but not in the labor force as a share of the population. Shading denotes recession. Source: Bureau of Labor Statistics; CEA calculations. during the past four years, but the contribution is projected to turn positive during the projection period. The workweek is projected to remain roughly unchanged during the projection period (line 5, column 3) even though it has declined 0.3 percent a year, on average, over the long run (line 5, column 1). The workweek is expected to hold steady as a natural labor-market adaptation to the anticipated decline in the labor force participation rate. Labor productivity is projected to increase 2.3 percent a year over the forecast horizon (line 6, column 3), a slight increase over the average growth rate from 1953–2007 (line 6, column 1). The elevated rate of long-term unemployment poses some risk to the projection insofar as the human capital of workers may deteriorate with prolonged unemployment. On the other hand, higher rates of school enrollment among young adults in recent years, as noted, should contribute to productivity growth in the coming years. The ratio of real GDP to nonfarm business output is expected to subtract from GDP growth over the projection period (line 7, column 3), consistent with its long-run trend. The nonfarm business sector generally grows faster than other sectors, such as government, households, and nonprofit institutions, reflecting an accounting convention that holds productivity growth to zero for government. 78 | Chapter 2 Summing each of these pieces, real GDP is projected to rise at an average 3.1 percent a year over the projection period (line 8, column 3), notably faster than the 2.5 percent annual growth rate for potential real GDP (line 9, column 3). Actual GDP is expected to grow faster than potential GDP primarily because of the projected rise in the employment rate (line 3, column 3) as millions of workers who are currently unemployed find jobs. Smoothing through the effects of the recent business cycle, real GDP is expected to rise 2.4 percent a year, on average, over the 15-year period from 2007 to 2022, just short of the growth rate of potential real GDP of 2.5 percent because the economy in 2007 is estimated to have been above its trend. Real potential GDP is projected to rise 2.5 percent a year in 2007–2022 (line 8, column 4), more slowly than the long-term historical growth rate of 3.2 percent a year (line 8, column 1). The projected slowdown in real potential GDP growth reflects the lower projected growth rate of the working-age population and the aging of the baby-boom cohort into retirement. The effects of the financial crisis and the 2007–09 recession, in contrast, are expected to have little effect on the level of potential real GDP by the end of the projection, because the recession is not expected to permanently reduce any of the demographically-determined elements of long-term growth. An important question addressed in the budget outlook, however, is how quickly real GDP will return to its potential level. In the Administration’s 2013 Budget forecast, the U.S. economy catches up to potential real GDP in the second half of the forecast period. The historical record supports this forecast. The full recovery of real GDP during the decade following the Great Depression suggests that the U.S. economy can recover from a severe shock to return to this underlying trend level. Conclusion The U.S. economy continued to recover in 2011 from the severe effects of the financial crisis and the deep recession that followed. The rise in real GDP since the beginning of the recovery has been roughly similar to the trend in both following the 1991 and 2001 recessions, while private payroll growth came sooner and more swiftly than in the beginning of the recovery from the 2001 recession. The housing market began to show signs of life in 2011, and is likely to have a positive effect on the economy, though from a low base. As 2012 begins, the recovery appears most likely to proceed at a moderate pace over the coming year, with the gains in output and employment increasing in subsequent years, as credit conditions continue to ease The Year in Review and the Years Ahead | 79 and confidence improves. Ensuring this outcome requires policies that both restore balance to the economy by increasing aggregate demand and guard against the types of excesses that led to the crisis in the first place. With millions of Americans still unemployed, much work remains to restore the U.S. economy to full health. Only a prolonged and robust expansion can eliminate the large jobs deficit that opened up during the recession, and the economy as a whole has considerable room to grow. The fact that private job growth has closely tracked the pattern of the early 1990s expansion is encouraging, and highlights the importance of sustaining the recovery. 80 | Chapter 2 C H A P T E R 3 RESTORING FISCAL RESPONSIBILITY W hen President Obama took office three years ago, the Administration was given an annual deficit of $1.3 trillion and a projected 10-year fiscal shortfall of more than $8 trillion.1 The Administration has taken many steps to restore fiscal responsibility because large and sustained fiscal imbalances pose one of the Nation’s greatest economic challenges. Policymakers are charged with the dual imperative of safeguarding the ongoing economic recovery while simultaneously ensuring that future generations are not burdened with excessive debt and that future government borrowing does not unduly crowd out private investment. In the near term, sharp deficit reduction serves as a drag on aggregate demand and threatens to disrupt ongoing economic growth. In the long term, persistent budget deficits can reduce national saving, raise interest rates, and discourage private domestic investment, even in an economy as dynamic and robust as our own. These seemingly conflicting concerns make deficit reduction a crucial but delicate endeavor. Recognizing the economic risks associated with sustained large budget deficits, the Obama Administration has made deficit reduction a priority. In February 2010, the President signed the Statutory Pay-As-You-Go Act, a law that restored the commonsense principle of paying for permanent mandatory spending or tax changes—a rule that had lapsed or been waived during the previous decade. In March 2010, the President signed the Affordable Care Act, which both expands health coverage and directly addresses one of the key drivers of the long-term deficits, rising health care costs. Last summer, the President and Congress enacted a $1 trillion deficit-reduction package in the Budget Control Act of 2011, with a minimum $1.2 trillion 1 In this chapter only, unless otherwise noted, budget deficits and spending programs are reported in fiscal years and tax receipts are reported in calendar years. 81 in further reductions scheduled to follow. As a way forward, the President has laid out a balanced plan that would—in combination with the Budget Control Act and other deficit reduction measures taken since the beginning of 2011—cut the 10-year deficit by more than $4 trillion, bring the budget into primary balance so that revenues cover all noninterest expenditures, and reduce debt as a share of the economy. These steps represent a radical departure from the budget policies of the previous administration, which included a series of sweeping tax cuts skewed toward the wealthiest, establishment of the Medicare prescription drug benefit program, and wars in Iraq and Afghanistan—all enacted without being offset by cuts or additional revenue raised elsewhere in the budget. This chapter highlights the sources of budget deficits and public debt, describes projected budget outlooks, and outlines the Administration’s deficit-reduction plan, a balanced approach that recognizes the need to prioritize spending initiatives while aligning revenues with current spending by asking the highest-income Americans to contribute to deficit reduction, as well as closing loopholes for corporations and special interests. The President’s plan acknowledges that balancing the budget on the spending side of the ledger alone would hurt programs that help the middle class and those trying to get into it and put at risk other national priorities, such as investment in infrastructure and education. The prospective fiscal imbalances have been decades in the making. Restoring balance will necessitate bold and difficult reforms in government programs. Although the Affordable Care Act and the Budget Control Act were the most aggressive Federal deficit-reduction legislation in years, much work remains to be done. Because budget projections show continued fiscal imbalances, it is critical for Congress to work with the Administration to return the Nation to a sound fiscal outlook. Determinants of Current Deficits Under current law and established budget policy, which are reflected in the adjusted baseline of the Office of Management and Budget (OMB), the annual budget would improve rapidly as the economy recovers, falling from $1.3 trillion in 2011 (8.7 percent of GDP) to $662 billion in 2014 (3.9 percent of GDP). Despite these projected improvements, the deficits moving forward are expected to remain at unsustainable levels absent additional policy actions. The fiscal shortfall is not primarily driven by countercyclical policies enacted in response to the Great Recession. Instead, recent deficits are principally the result of spending policies enacted during the previous 82 | Chapter 3 administration, sweeping tax cuts initiated in 2001 and 2003,2 and economic conditions. While temporary policies designed to increase aggregate demand, improve business investment, and jump-start employment contributed to annual deficits immediately following the financial crisis, they are less costly than the previous decade’s spending and tax policies; most importantly, they are temporary emergency measures projected to have a minimal effect on annual budget deficits going forward. As noted, spending policies enacted in the early part of the previous decade are one of the primary causes of recent deficits. Wars in Iraq and Afghanistan, substantially more costly than initially announced by the previous administration, added $1.3 trillion in military spending between September 2001 and December 2011. The Medicare Part D prescription drug benefit, enacted in 2003, has raised Medicare spending by over $250 billion through calendar year 2011. Increased interest costs associated with these programs have driven deficits even higher. Tax cuts initiated in the previous decade, including those for the wealthiest individuals, have helped drive down tax revenues to historical lows. In particular, sweeping cuts in income and estate taxes, initially enacted in 2001 and 2003, have reduced revenue and increased interest costs by nearly $3.0 trillion between 2001 and 2011 (Ruffing and Horney 2011). In 2011, Federal tax receipts amounted to just 14.4 percent of GDP, far below the postwar average of 17.7 percent. Part of this revenue shortfall is attributable to temporary tax cuts designed to aid the economy and create jobs, and part to the slow rebound of wages, investment income, and corporate profits—the income base from which tax receipts are primarily derived. But several ongoing tax policy trends that long predated the financial crisis have also put downward pressure on tax revenue. By comparison, policies enacted to revitalize the economy and stabilize the financial system have contributed only moderately to deficits over the past several years, with a substantially waning impact after 2012. The American Recovery and Reinvestment Act (the Recovery Act) of 2009 cost $833 billion overall, while the most recent Troubled Asset Relief Program (TARP) cost estimate is just $68 billion. Other countercyclical measures, including the 2 percentage point payroll tax reduction for workers, have also carried relatively small costs, which have often been offset by other budget measures. For example, the Temporary Payroll Tax Cut Continuation Act of 2011, which temporarily extended the payroll tax cut, unemployment 2 These policies contributed to a historic gap between projected and realized budget outcomes. In 2001, following several years of budget surpluses, the Congressional Budget Office projected a cumulative surplus of $5.6 trillion between 2001 and 2011 (CBO 2001). No surplus was realized after 2001, and a cumulative deficit of $6.5 trillion accumulated between 2001 and 2011. Restoring Fiscal Responsibility | 83 benefits, and certain about-to-expire Medicare provisions regarding physician payments, included offsets that made the bill deficit neutral. Figure 3-1 compares the incremental cost of various post-2001 determinants of the deficit, including the wars in Iraq and Afghanistan, economic downturns, 2001 and 2003 tax cuts, financial stabilization measures, and economic stimulus initiatives. What the figure does not show is the path the deficit would have taken had the Great Recession persisted. The projections in the figure, based on Congressional Budget Office (CBO) data, incorporate both the direct economic growth owing to countercyclical measures undertaken by the Obama Administration and the subsequent projected economic recovery. If economic growth had turned negative instead of growing throughout 2009–11, or if the financial system had remained in turmoil, the tax base would have eroded further and the fiscal crisis would have been more severe. The connection between unused countercyclical fiscal policy and stunted economic growth has been shown time and again. From the Great Depression, to Japan’s Lost Decade, to international attempts to enact austerity measures during economic recessions, research has shown that in the absence of countercyclical measures, recessions become even more severe (Auerbach and Gale 2010). As painful as the past three years have been Figure 3-1 Selected Components of Deficit Projections: 2009–2019 Billions of dollars 1,600 War costs Bush-era tax cuts Recovery measures TARP, Fannie, and Freddie Economic downturn Deficit without these factors 1,400 1,200 1,000 800 600 400 200 0 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Note: Based on CBO budget projections. CBO employs different economic assumptions and methodology than OMB. As a result, the projections presented in this figure may differ from those presented by OMB. Source: Ruffing and Horney (2011). 84 | Chapter 3 for the U.S. economy, countercyclical measures brought the downturn to a quicker end and have reinforced the recovery. While demographic trends and rising health care costs pose serious challenges on the spending side of the ledger, the failure of tax revenue to match Federal spending remains a primary concern. Falling Effective Tax Rates on Upper-Income Taxpayers Effective tax rates, also known as average tax rates, are simply the amount of taxes paid as a share of total income. In contrast, marginal rates are defined as the taxes paid on an additional dollar of earnings. Tax preferences, such as preferential rates for investment income or deductions for particular activities, can drive effective tax rates far below marginal tax rates. As a result, effective tax rates have varied over time with periodic tax reforms and a shift in the composition of income among high earners toward business and capital income. Several of the President’s tax policy initiatives, including the American Opportunity Tax Credit, the expansion of refundable tax credits for families with children, and the cut in the payroll tax, have provided tax relief for middle-income Americans. In order to isolate the effects of changing tax policy on effective tax rates, a useful exercise is to track effective tax rates holding income characteristics constant. Under this methodology, as indicated in Figure 3-2, effective tax rates on middle-income Americans rose slightly in the 1960s and 1970s, and then remained mostly flat between 1980 and the start of the Obama Presidency. Effective tax rates for the top 1 percent have varied moderately over the past five decades, peaking in about 1980 before falling back to lower levels between the late 1980s and the present. In stark contrast, the wealthiest taxpayers have seen their effective tax rate plummet over the past five decades because of changes in Federal tax policies. The wealthiest 1-in-1,000 taxpayers pay barely a quarter of their income in Federal taxes today—half of what they would have contributed in 1960. Although trends in effective tax rates are attributable to a variety of factors, the tax cuts initiated under the previous administration had a notable impact. When the Economic Growth and Tax Relief Reconciliation Act of 2001 cut statutory income tax rates, high-income taxpayers benefited disproportionately, in large part because of the cut in the top rate from 39.6 percent to 35.0 percent. Two years later, in 2003, preferential rates on longterm capital gains and dividends were cut to historical lows of 15 percent, again resulting in large benefits for the upper-income taxpayers who realize the bulk of investment income. Treasury data show clearly that high-income families benefited the most from the 2001 and 2003 tax law changes. For example, as Figure 3-3 Restoring Fiscal Responsibility | 85 Average tax rate 60 Figure 3-2 Average Tax Rates for Selected Income Groups Under a Fixed Income Distribution, 1960–2010 Top 0.1% 50 40 30 Top 1% 20 Middle 20% 10 0 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Note: Average Federal (income plus Federal Insurance Contributions Act) tax rates for a sample of 2005 taxpayers after adjusting for growth in the National Average Wage Index. Source: Internal Revenue System Statistics of Income 2005 Public Use File, National Bureau of Economic Research TAXSIM, and CEA calculations. illustrates, between 2000 and 2008, income tax rates fell more for the top 1 percent and top 0.1 percent of the income distribution than for the middleincome quintile. Average individual income tax rates fell by 4.7 percentage points for families in the top 0.1 percent, but only by 3.7 percent for middleincome families. To help reduce the deficit consistent with the notion of shared responsibility, the President’s Fiscal Year 2013 Budget proposes to let the tax breaks expire for income above $250,000 a year, reversing a decade-long trend of unequal tax benefits for the wealthy, while making the tax cuts for those families making $250,000 or less permanent. Heterogeneity in Effective Tax Rates among High-Income Taxpayers The gradual drop in effective tax rates on high-income taxpayers is only part of the story. Effective tax rates on these taxpayers also vary widely because of the tax code’s differing treatment of various sources of income, allowances for changing the timing of taxes paid, and various deductions and credits. For example, a high-income taxpayer who is compensated primarily with cash wages might remit in excess of 30 percent of income in payroll and income taxes, while a high-income taxpayer who receives a large share of compensation in the form of interest in an investment fund (known as “carried interest”) would have a far lower tax rate. 86 | Chapter 3 Figure 3-3 Average Individual Income Tax Rates by Income Quintile, 2000 and 2008 Average tax rate 30 25 Average tax rate, 2000 20 15 Average tax rate, 2008 10 5 0 -5 -10 1st 2nd Middle 4th Highest Top 10 quintile quintile quintile quintile quintile percent Note: Quintiles are based on adjusted gross income. Source: Department of Treasury. Top 5 percent Top 1 percent Top 0.1 percent In 2012, among taxpayers in the highest income quintile, effective tax rates (including income, payroll, and corporate taxes) are expected to vary between 12.1 percent for those at the 10th percentile (in terms of effective tax rates) to 29.3 percent for those at the 90th percentile. That is, 10 percent of all high-income taxpayers are expected to pay less than 12.1 percent of their income in Federal taxes and another 10 percent are expected to pay more than 29.3 percent (the remaining 80 percent will pay somewhere in between the two rates). For the top 1 percent of taxpayers, the variation in rates is even starker. Among those in the top 1 percent, one in ten taxpayers is expected to pay less than 8.7 percent of their income in taxes, while another one in ten is expected to pay 34.6 percent or more (see Table 3-1). The variation is perhaps most evident at the very top of the income distribution. In 2008, the most recent year for which data are available, 30 of the 400 highest-earning taxpayers (7.5 percent) paid less than 10 percent of their income in Federal income taxes, while 59 (14.8 percent) paid in excess of 30 percent. Addressing the Role Of Exclusions and Deductions in Effective Tax Burdens As noted, effective tax rates vary widely because of myriad deductions, exemptions, and preferences in the tax code. Moreover, particular streams of income are excluded from taxation entirely. But, as noted, the expanding Restoring Fiscal Responsibility | 87 Table 3-1 Distribution of Average Federal Tax Rates Family cash income group Average rate at each breakpoint in the rate distribution 10th 25th Median 75th 90th Lowest quintile –13.7 0.0 5.4 13.1 15.5 Second quintile –8.7 0.5 7.2 17.0 20.9 Middle quintile 1.7 5.4 13.3 20.4 23.5 Fourth quintile 7.2 12.1 17.2 22.3 26.2 Highest quintile 12.1 17.4 21.9 26.0 29.3 0.0 5.0 14.5 20.7 25.0 8.7 21.2 29.6 32.3 34.6 Total Top 1 percent Note: Calculations assume 2012 tax law with an AMT patch and 2012 income levels, and includes individual income tax, corporate income tax, and payroll tax. For the lowest income quintile, the calculation of average rates and the distribution of average rates do not include families with negative income. These families are included in the total. Source: Department of Treasury. array of such tools within the tax code has enabled some high-income taxpayers to reduce their tax liability dramatically. Decades ago, the Alternative Minimum Tax (AMT) was enacted in an attempt to combat the low rates paid by some high-income taxpayers, but its poor design has caused it to fall primarily on upper-middle-income families from high-tax states, as well as on those with many children (Burman 2007). In addition, because the value of a deduction or exclusion is a function of a taxpayer’s marginal tax rate, deductions and exclusions from taxable income are typically worth much more to high-income households—as much as two to three times more— than to low- and middle-income ones. As a way to combat this “upside-down” system of tax incentives, the President has proposed several principles for tax reform. The President’s proposed Buffett rule would ensure that Americans making more than $1 million a year would pay no less a share of their income than middle-income families pay—in particular, no less than 30 percent of their income—in taxes. In addition, the President has proposed tax reform that would ensure fair incentives for the middle class, helping to equalize the value of tax expenditures across the income distribution. (For information on how to evaluate effective tax rates based on their progressivity, see Economics Application Box 3-1). The Fiscal Outlook Without the pro-growth policies of the past three years, future budget shortfalls would be even more severe. Moreover, the policies presented in the Administration’s Fiscal Year 2013 Budget significantly improve 88 | Chapter 3 projected medium-term deficits relative to an adjusted policy baseline, and projected long-term public debt continues to rapidly decline over the course of the Obama Administration. Medium-Term Budget Projections Under the OMB adjusted baseline, medium-term deficits gradually decline as a share of GDP—projected deficits fall from 8.7 percent of GDP in 2011 to 4.7 percent of GDP in 2022, as Figure 3-4 indicates. This adjusted baseline represents a medium-term scenario in which current policies continue throughout the decade. The scenario includes the continued indexation of AMT parameters, extension of the 2001 and 2003 tax cuts, and extension of the estate tax parameters at their current levels, as well as a continuation of current levels of spending for Overseas Contingency Operations and physician pay rates under Medicare. This improved fiscal outlook is due in large part to a recovering economy and the fiscal steps the Administration has already taken, including the Affordable Care Act and the Budget Control Act. Nonetheless, this adjusted baseline remains problematic and represents a fundamental imbalance between government spending and revenues. The President’s plan to rebalance revenue streams and spending priorities is detailed later in the chapter. Figure 3-4 Projected Medium-Term Budget Deficits, 2011–2022 Percent of GDP 10 9 8 7 6 5 4 Adjusted baseline 3 2 1 0 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Note: See text for policies incorporated in OMB's adjusted baseline. Source: Office of Management and Budget (2012a). Restoring Fiscal Responsibility | 89 Economics Application Box 3-1: Measuring Progressivity in the Tax Code Tax changes are typically evaluated based on several key criteria, including efficiency, simplicity, ease of compliance and administration, impact on economic activity, and progressivity. Progressivity is the measure of how a particular policy affects households with differing levels of income or resources. Fairness is the essence of progressivity; many taxes—particularly income taxes—are designed to ensure a lighter tax burden for households with less income and lower ability to pay. Economists typically define a progressive tax as one that has average tax rates that increase with income; under a progressive tax code, higher-income taxpayers devote a higher share of their income to taxes than other taxpayers. A progressive tax change is one that lowers average tax rates more for low- and middle-income households relative to others or raises average tax rates more for high-income households relative to others. For example, the recent 2 percentage point cut in the payroll tax is considered progressive because it reduces average tax rates more for low- and middle-income families compared to high-income families. Other measures of progressivity, such as measures that refer strictly to dollar changes in taxes paid or to the percentage change in taxes paid, can be misleading. For example, a tax cut might reduce taxes paid by low-income households from $100 to $50 (a change of 50 percent), and reduce taxes paid by high-income households from $500,000 to $400,000 (a change of just 20 percent). Some might argue that this change is progressive because it reduces taxes paid by lowincome households by proportionately more than it reduces taxes paid by high-income households, but this measure is actually inconclusive because it tells us nothing about the change in average tax rates. Along these same lines, metrics that focus on the share of taxes paid are not useful because they do not incorporate information on average tax rates by income group. The definition of income or well-being can also be important when measuring progressivity. Some forms of compensation—such as employer contributions to a retirement account or health insurance premiums paid by an employer—may not be considered income for tax purposes but might in principle be considered as income for measuring taxpayer resources. Similarly, income transfers such as unemployment compensation or Social Security benefits could be included in income when measuring progressivity. The extent to which the tax code equalizes income is expressed graphically by the Lorenz curve in the box, which shows the cumulative 90 | Chapter 3 distribution of income before and after taxes. The 45 degree line represents a perfectly equal distribution of income; the closer the Lorenz curve to that line of equality, the more equal the distribution of income. A progressive tax code is one that shifts the income distribution closer to the 45 degree line. In 2007, the tax code helped to improve the progressivity of the income distribution, as illustrated by the graph, by making after-tax income more equal than before-tax income. However, even the after-tax Lorenz curve was well below the 45 degree line, meaning that the distribution of after-tax income was highly skewed towards the highest-income taxpayers. Income Concentration, 2007 Cumulative share of income 100 90 80 70 60 Line of equality 50 40 After-tax income 30 Before-tax income 20 10 0 0 20 40 60 Cumulative share of population Source: Congressional Budget Office (2011a). 80 100 The Vital Role of Economic Growth in Future Fiscal Outcomes Budget discipline is nearly impossible to achieve in practice without healthy economic growth. Budget outcomes are sensitive to weak economic conditions. Deteriorating economic conditions resulting from the financial crisis are one of the most important determinants of projected medium-term deficits, accounting for $3.9 trillion in expected deficits between 2009 and 2019 (as shown earlier in Figure 3-1). OMB (2012b) projects that a 1 percentage point drop in GDP growth in 2012, not matched with a subsequent boost in GDP in later years, would increase the deficit by $720 billion over 10 years. Similarly, CBO (2011b) projects that an ongoing 0.1 percentage point Restoring Fiscal Responsibility | 91 Data Watch 3-1: Data from the IRS Statistics of Income Division The Statistics of Income (SOI) Division of the Treasury Department’s Internal Revenue Service produces informative annual statistics. The resulting information is an important input to the National Income and Product Accounts and has been invaluable for the evaluation of economic and tax policies, as well as for business decisions. One advantage of SOI statistics is that they are available for a long period of time: historical data series cover the period from 1916 to the present. Of particular interest are tabulations of selected items by county and ZIP Code, such as migration patterns. Extensive data also are available on businesses, including corporations, partnerships, and sole proprietorships. In response to increased globalization, for example, SOI produces regular reports on both foreign-owned U.S. corporations and U.S.-owned corporations operating in other counties. More than 14,000 detailed tables and regular reports are available to the public online through the Tax Stats pages located at www.irs.gov. Periodic special reports have examined topics such as pensions, foreign earned income, and noncash charitable contributions. Users may create custom tables using a table wizard application. Importantly, SOI painstakingly safeguards the confidentiality and anonymity of the underlying information it draws on. Statistics derived from the SOI provide a rich source of information for policymakers, business people, researchers, and public interest groups, among others. decrease in real GDP growth compared to its baseline forecast will add $310 billion to the projected 2012–2021 deficit. The link between economic growth and fiscal stability is, in fact, central to the rationale for countercyclical measures like the Recovery Act and the American Jobs Act. Although the countercyclical measures in these bills may impose an initial fiscal cost,3 the cost can be considered a down payment on future economic growth, which in turn can lead to a more stable fiscal policy. Economic growth leads to a sound fiscal outlook. Improvement in Long-Run Budget Projections Although the need for long-run deficit reduction is evident, recent Administration policies have already helped to partially close the long-run fiscal imbalance. As noted, the Budget Control Act of 2011 reduced Federal spending by $1 trillion over the next decade by making cuts to discretionary spending, with an additional $1.2 trillion in deficit reduction scheduled to 3 The President’s proposed American Jobs Act is deficit-neutral; all provisions are more than fully paid for. 92 | Chapter 3 come. The Administration regards this legislation as a down payment on deficit reduction, and last fall proposed to Congress an additional $3 trillion deficit-reduction package that would, by the middle of this decade, mean that current spending is no longer adding to the debt, and that debt is falling as a share of the economy. Health care legislation passed in 2010 is a key factor to gains in longrun deficit reduction. The Affordable Care Act addressed the Nation’s most profound long-run budget challenge by limiting the growth in health care costs in several ways. (Chapter 7 discusses Health Insurance Exchanges as well as other provisions of the Affordable Care Act and existing health programs.) The Act includes Medicare payment reforms that will restrain spending growth by rewarding improvements in health care productivity. It established the Center for Medicare and Medicaid Innovation, which will fund and test new strategies for providing high-quality care more efficiently, and the Independent Payment Advisory Board, which will recommend policies to reduce the growth in Medicare spending, without limiting beneficiaries’ access to care. The projections presented in this chapter assume that the provisions of the Affordable Care Act are fully implemented, limiting Medicare costs in the long run compared with previous law. The Medicare Trustees estimate these gains to be substantial, slowing the average longrange annual growth in Medicare spending per enrollee to just 0.2 percentage point a year above the growth in GDP per capita. This growth rate is significantly smaller than previous Medicare Trustee projections—a reduction that is largely attributable to the Affordable Care Act. These trends indicate that in the absence of recent health care reform, long-run budget projections would be substantially worse. The Importance of Restoring Fiscal Sustainability Reducing the deficit while the economy continues to recover requires a delicate balance. Looming fiscal shortfalls can seem a distant concern in the face of high unemployment and sluggish economic growth. But as a result of continued growth since 2009 and a gradual recovery from the financial crisis of 2008, the Administration maintains its view that short-term economic support and long-term fiscal responsibility can be complementary policies. Although reducing the deficit is a difficult task, it is critical to the Nation’s future. As the debt-to-GDP ratio has steadily risen, economists have become increasingly concerned about the consequences of persistent deficits. Not all types of deficit spending yield identical effects on the budget. The net economic effect of budget deficits depends critically on the Restoring Fiscal Responsibility | 93 characteristics of the underlying spending. Public borrowing to finance productive investment, including investment in infrastructure, technology, and education, can yield positive fiscal returns in the future. A more productive private sector will lead to higher profits and stronger wage growth, which will ultimately prove to boost revenues and reduce spending in later years. As such, government spending that makes the private sector more productive is distinctly different from spending devoted to consumption in the current period. Prolonged fiscal shortfalls also tend to raise interest rates. Today’s historically low interest rates may make that link between interest rates and deficits seem tenuous, but in typical economic circumstances, budget deficits drive interest rates higher by increasing the demand for saving. The consensus view among economists is that a 1 percent increase in the deficit relative to GDP leads to a 20- to 60- basis-point rise in interest rates (Gale and Orszag 2003). Higher interest rates depress interest-sensitive consumption (such as housing and durable goods) and diminish asset values and household wealth. Of perhaps greater concern is the potential for prolonged budget deficits to impact domestic private investment via elevated interest rates. All else equal, higher interest rates can divert savings away from productive domestic investment towards government securities; higher interest rates also encourage domestic and foreign savers to increase their net investment in the United States. Thus, higher budget deficits can be financed by a combination of reduced domestic private-sector investment, increased domestic saving, and additional lending by foreign investors. Although there is no consensus among economists on the relative share of each of these factors, studies often assume that about 25 percent of the increase in the budget deficit is met with increased private-sector saving (Elmendorf and Liebman 2000) and about 20 to 40 percent through increased foreign lending (Engen and Hubbard 2005). An active research agenda has considered how government debt affects the economy. According to research by economists Carmen Reinhart and Kenneth Rogoff (2010), “high debt/GDP levels (90 percent and above) are associated with notably lower growth outcomes.” Several aspects of this finding warrant mention. First, although slow growth and debt are correlated, high debt does not necessarily cause stagnant growth. In fact, some have theorized that stagnant growth leads to higher levels of debt, rather than the other way around (Irons and Bivens 2010). Second, some question whether the 90 percent threshold is appropriate for the largest economy in the world, especially given the ongoing appetite of foreign and domestic investors for Treasury debt and the relative attractiveness of investment in 94 | Chapter 3 the United States. Finally, some have argued that the key factor in measuring the impact of debt on the economy is debt held by the public, rather than total debt (including intragovernmental debt; see Data Watch 3-2 for further explanation). Although the precise impact of government debt on economic growth is subject to debate, economists agree that confidence is paramount in the relationship between government debt and financial markets. A long-term commitment to sound fiscal policies will reassure investors that the government can service its debt. More importantly, sound fiscal policy and a commitment to living within our means and investing in the future will ensure better access to capital by domestic investors, as well as higher standards of living for future generations. The President’s Balanced Approach to Deficit Reduction The President’s proposed framework for deficit reduction, laid out in the Fiscal Year 2013 Budget, represents a balanced approach along several dimensions. Deficit-reduction measures are phased in gradually to avoid disrupting the economic recovery. Ineffective spending programs are eliminated, while tax expenditures on the Nation’s wealthiest taxpayers are limited. Targeted investment initiatives, including those for education, infrastructure, and personal saving, are paid for by eliminating ineffective tax cuts to high-income taxpayers. Most importantly, the President’s Budget charts a sustainable fiscal course, ensuring that the budget deficit will fall to a sustainable level in the next 10 years and beyond. In sum, the President’s Budget represents a critical first step toward a stable and prosperous economic future and ensures that the American economy will remain competitive and vibrant for decades. The cornerstone of the President’s approach to deficit reduction—and perhaps the way in which it differs most from plans offered by others—is the balance it strikes between sustainable tax revenues and spending cuts. A deficit-reduction framework based on spending cuts alone would preclude the provision of basic protections provided to the Nation’s most vulnerable citizens and investment in the Nation’s future. The balanced approach of the President’s Budget preserves the basic functions of the Federal Government. Medicare and Medicaid are strengthened, ensuring health care for the nation’s elderly, low-income families, and individuals with disabilities. Social Security continues to provide a reliable, steady stream of income for retirees. The military continues to receive funding to serve American interests at home and abroad. Veterans continue to receive the support they Restoring Fiscal Responsibility | 95 Data Watch 3-2: Measuring Government Debt across Countries Differences in government accounting practices and in the types of assets held by central governments complicate the comparison of government debt across countries. These complications can lead to confusion over the most appropriate measure of government debt and the relative levels of debt for different countries. One source of misunderstanding is the distinction between public debt and total government debt. Public debt refers to government debt held by private investors, including individuals, pension funds, mutual funds, and corporations. Total government debt is the sum of public debt and intragovernmental debt—government debt held in government accounts, such as government securities held in the U.S. Social Security and Medicare trust funds. Economists widely recognize public debt as the more relevant measure since it is government borrowing from the private sector that can be expected to interact with credit markets. In most Organisation for Economic Co-operation and Development (OECD) countries, there is little intragovernmental debt. In the United States and Canada, however, budgetary conventions give rise to large accumulations of such debt. At the end of December 2011, U.S. debt totaled $15.2 trillion, of which $10.5 trillion was held by the public and $4.8 trillion was intragovernmental debt. Intragovernmental debt is similarly important in Canada. Including intragovernmental debt when making international comparisons leads to an exaggerated impression of government indebtedness in the United States and Canada relative to other OECD nations. A second source of confusion is the distinction between gross debt and net debt. The OECD measures gross debt as total liabilities outstanding, including securities issued on behalf of the government (such as Treasury securities), currency, and liabilities to government employee pension funds. Net debt is measured as gross debt minus government-owned financial assets. The importance of this distinction varies across countries. In Japan, for example, the difference is stark: gross government debt equaled 220 percent of GDP in 2010, while net government debt was just 117 percent of GDP. A final source of misunderstanding concerns the particular government sector being measured. The OECD presents measures of general government debt, which encompasses debt at all levels of government, including State and local governments in the United States, and central government debt. Both of these measures carry economic significance, but the distinction matters insofar as central governments generally are not liable for debt incurred by other levels of government. 96 | Chapter 3 deserve. Investments in education, infrastructure, and innovation continue to be a priority. Many other deficit-reduction plans fall short in these areas. While the President’s Budget makes and maintains critical investments in areas important to growth and competitiveness, it also institutes broadly shared sacrifices to reduce the deficit. The Administration proposes to achieve $1 trillion in discretionary spending savings over the next 10 years through the budgetary caps established by the Budget Control Act; $30 billion in deficit reduction through cutting or consolidating ineffective, duplicative, or outdated Federal programs; adopting a new defense strategy that cuts defense spending by 9 percent relative to the Fiscal Year 2012 Budget; limiting funding for Overseas Contingency Operations to $450 billion through 2021; a $60 billion fee on large financial firms; adjustments to the Medicare and Medicaid programs to make them more efficient and cost-effective; and a reform of the Federal civilian workers’ retirement plan that saves $21 billion over the next decade. As the President’s deficit-reduction strategy cuts long-run deficits, it also supports the economic recovery. The cornerstone of this support is the American Jobs Act, one of the boldest pieces of pro-employment legislation in decades. At the end of 2011, the President signed into law several key parts of the American Jobs Act, including a short-term extension of both the payroll tax cut and extended unemployment benefits that were set to expire at the end of 2011. Extending the payroll tax cut into 2012 added an average of $40 to each paycheck of 160 million American workers. If continued through 2012 as the President favors, extended unemployment benefits will save 5 million job seekers from depleting their benefits and will create nearly 500,000 jobs through 2014 as workers spend their extra income. To bolster labor market conditions and spur near-term economic growth, the President proposes pushing ahead with elements of the American Jobs Act and with additional job-creating measures. Among those proposals are an initial $50 billion investment in roads, rails, and runways through surface transportation reauthorization legislation; aid to states and localities to rehire teachers and first responders; additional incentives for Americans to invest in energysaving home improvements through the Homestar Bill; incentives to private industry to upgrade offices, stores, universities, hospitals, and commercial buildings through the Better Buildings Initiative; a 10 percent income tax credit to encourage small businesses to hire new employees and to increase wages; the halting of an automatic increase in student loan interest to ease the burden on students; funds to modernize at least 35,000 schools; a renewed Build America Bonds program to help finance the modernization and upgrading of America’s infrastructure; reauthorization of Clean Energy Manufacturing Tax Credits to spur the creation of manufacturing jobs Restoring Fiscal Responsibility | 97 in the advanced energy technology sector; continuation of provisions to allow businesses to write off the full amount of new investments next year; and enactment of Project Rebuild, a series of policies aimed at connecting unemployed workers in distressed communities with efforts to rehabilitate residential and commercial properties. The President’s deficit-reduction framework also calls for tax reform that will simplify the tax code and lower rates, cut unfair and unnecessary tax expenditures, increase growth and job creation in the United States, observe the Buffett rule, and raise $1.5 trillion from the highest-income Americans to be devoted to deficit reduction. To begin a national conversation about tax reform, the President has offered a detailed set of measures to close specific tax loopholes, broaden the tax base, and allow the high–income tax cuts of the past decade to expire. With this conversation, the President’s Budget begins to reclaim the Nation’s fiscal future and restore fiscal responsibility by making balanced and necessary policy decisions. 98 | Chapter 3 C H A P T E R 4 STABILIZING AND HEALING THE HOUSING MARKET T he recession that began at the end of 2007 is inextricably linked with the bursting of the housing bubble that had built up over the previous decade. The ensuing shock to financial markets, and the more than $7 trillion in lost housing wealth, prolonged and deepened the downturn and has been a headwind for the economic recovery. Although the housing market is showing signs of stabilization, the healing process is not complete in many parts of the country. The bursting of the bubble was a culmination of a multiyear process of rapid growth in house prices fueled by excess capital flows into the United States. These flows were converted into home mortgages by various financial intermediaries using lax underwriting standards and channeled through the financial system with an increasingly complex web of mortgage securitizations. These trends, in turn, created unmoored expectations of continuous price growth that caused a spike in residential construction. The overheated housing market ultimately proved to be unsustainable, and the return to more realistic levels has been very painful for the economy. As this process continues to unfold, responsible policies are needed to assist the market in its transition to a new, sustainable equilibrium supported by a prudent and robust financial framework. In this context, healing the housing market requires laying the foundation for balanced and sustainable growth, while repairing and improving the housing finance system that helped inflate the housing bubble. The effects of the drop in housing prices have been amplified by the uniqueness of housing as a financial asset class. Indeed, housing is the single most important asset for a majority of American households. Houses generate a steady stream of consumption services for their owners, as well as enabling them to send their children to local schools and use neighborhood amenities ranging from parks to retail stores to hospitals. They also create demand and jobs as homeowners furnish their homes and invest in their 99 maintenance. By virtue of their tangibility, houses also serve as an important form of collateral for other borrowing purposes, notably startup financing for small businesses. Housing collateral attracts lender financing, making housing the most levered asset in household portfolios and closely linking the health of the housing market to that of the broader financial sector. Consequently, declines in housing wealth can have a far greater effect on the economy than equivalent losses in other financial assets, such as equities. Setting the housing market back on track is a key step on the road to recovery. Yet housing presents several particular challenges, many of which derive from an array of institutional frictions in housing finance markets that have been exposed by the enormous scale and scope of home price declines and from very long lags in the adjustment in the stock of housing. This chapter highlights some of these challenges. They include a poorly functioning system for loss mitigation of nonperforming mortgages and effective disposition of mortgaged properties; inadequate origination of mortgage credit; and obstacles to refinancing, including the widespread phenomenon of negative equity. These deficiencies form a mutually reinforcing adverse feedback system in which negative equity raises the likelihood of delinquencies that often result in a drawn-out foreclosure process, eventually concluding with distressed sales that exert further downward pressure on home prices and thereby deepen the amount of negative equity. The large overhang of unresolved properties in distress, along with mortgage debt in excess of home value, further feeds this negative dynamic by depressing price expectations of potential homebuyers and lenders. Left unchecked, this dynamic creates a dangerous possibility for housing prices to overshoot and fall below their fundamental values, posing a difficult hurdle for sustained economic recovery. Some have argued that the best course of action is to rely on the market alone to work out the problems of struggling homeowners, negative equity, and foreclosed properties through liquidation. This approach disregards the risk of overshooting the bottom, and it fails to recognize the many complex incentive conflicts that exist between purely private parties, such as homeowners, investors, and mortgage servicers. These conflicts and the need to recognize and allocate housing losses to various economic actors, present a serious collective action problem, the resolution of which by the market has been sluggish, at best, over the past several years. Perhaps most important, a laissez-faire approach also disregards the spillover effects of large numbers of delinquencies and foreclosures on local housing markets, the financial system, and the toll they exact on American families and the economy in general. 100 | Chapter 4 The alternative to sitting back and waiting for these enormous challenges to work themselves out slowly and painfully is for the Government to engage in a series of coordinated, measured, and multifaceted policy actions. This approach involves working in conjunction with market participants and housing regulators to address the lingering effects of the bursting of the housing bubble, as suggested, for instance, in a recent Federal Reserve Board white paper (2012). This chapter describes a set of existing and proposed policy initiatives that target many of the interlinked housing market problems. Some of these policies are pursued through Government agencies, such as the Federal Housing Administration (FHA), the Department of Housing and Urban Development (HUD), and the Department of the Treasury. Others are undertaken in conjunction with private investors, and still others are carried out together with the government-sponsored enterprises (GSEs), Fannie Mae and Freddie Mac, under the supervision of their regulator, the Federal Housing Finance Agency (FHFA). The Housing Crisis and the Initial Policy Responses After growing at a rapid pace through the early years of the new century, home price appreciation ground to a halt in the summer of 2006. This change in the path of housing prices triggered an initial wave of subprime mortgage defaults, and the resulting losses quickly propagated through the global financial system, bringing it to the brink of collapse and ushering in a deep recession. By the beginning of 2009, nationwide measures of home prices had declined for 30 straight months, falling by a total of nearly 28 percent. This drop in the national average masks significant regional variation. In some states, like Florida and Nevada, where prices had gone up the fastest, housing prices plummeted by 35 to 50 percent from their peak. Price drops in some other states were much milder. Overall, as shown in Figure 4-1, the decline in inflation-adjusted home prices was unprecedented in the post-World War I U.S. economic experience in both its severity and its geographic scope. Some of the regional housing recessions—notably in California and New England in the early 1990s—generated sharp and long-lasting price declines, but neither was as steep and prolonged as the current episode. And during the Great Depression, the only other instance of nationwide price declines since WWI, much of the comparably-sized decline in nominal home prices was offset by a concurrent drop in general price levels, so the decline in real housing values was only about one-quarter as large as the one we recently experienced. Stabilizing and Healing the Housing Market | 101 Figure 4-1 Housing Busts in U.S. History Real price level compared to peak 110 100 Great Depression (national) 90 80 California 1990 70 Current (national) 60 50 0 2 Boston 1989 4 6 8 10 Years since housing peak Source: S&P/Case-Shiller Home Price Index; the Great Depression time series from Shiller (2005). 12 The unprecedented and ultimately unsustainable nature of housing market trends before 2007 is further highlighted in Figure 4-2. The dashed line depicts annualized growth in real levels of mortgage debt per homeowner household between 1991 and the third quarter of 2011. Mortgage debt balances grew at a rapid pace from 2001 to 2007, one that far exceeded growth in real income during this period. There were many factors behind the escalating household debt. In part, it reflected rising home prices and growing household leverage driven by extraction of home equity and shrinking down payment requirements. As households continued to accumulate mortgage debt in the expectation of ongoing housing appreciation, housing was becoming less and less affordable, as evidenced by the price-to-rent ratio series (the sold line) in the same figure. After remaining in a narrow range between 100 and 120 percent for nearly two decades, the price-to-rent ratio accelerated rapidly to peak at 186 percent in the first quarter of 2006. Once the bubble burst, falling prices and poor economic conditions resulted in steep increases in delinquencies and foreclosures across a broad spectrum of American homeowners. By the first quarter of 2009, nonperformance rates among prime borrowers rose nearly threefold relative to their level in the first quarter of 2005 (from 2.2 to 6.1 percent), while those for subprime loans spiked to nearly 25 percent, from 10.6 percent four years earlier. About 1.7 million homes were at some stage of the foreclosure 102 | Chapter 4 Dollars 160,000 Figure 4-2 Price-to-Rent Ratio and Mortgage Debt Price-to-rent ratio 200 180 140,000 Sept-11 120,000 100,000 Price-to-rent ratio (right axis) 80,000 60,000 160 140 120 100 Mortgage value per home-owning household ($2010) (left axis) 40,000 80 60 40 20,000 20 0 0 Mar-91 Mar-94 Mar-97 Mar-00 Mar-03 Mar-06 Mar-09 Source: CoreLogic; Department of Labor; Bureau of Labor Statistics, Consumer Price Index. process, and nearly 7 percent of total mortgage debt was seriously delinquent (more than 90 days past due). Market participants were deeply pessimistic about the future path for housing prices—the Case-Shiller index futures contracts traded in January of 2009 suggested that house prices were expected to fall an additional 10 percent by September 2010 (the dashed line in Figure 4-3). Other housing futures contracts traded in over-the-counter markets (not shown) were even more downbeat. Initial Policy Responses to the Crisis The broad meltdown in the financial sector called for a series of emergency responses by the Executive Branch, the Legislative Branch, and the Federal Reserve. The Federal Reserve undertook a series of aggressive monetary policy actions and launched a number of programs to support liquidity and lending activity in key financial markets. Congress passed the Housing and Economic Recovery Act (HERA) in July of 2008, which established the Federal Housing Finance Agency, the new regulator of the GSEs with greatly expanded powers. The HERA was followed by the Emergency Economic Stabilization Act in October of 2008, which established the Troubled Asset Relief Program. In one of its first major policy actions, the Obama Administration implemented the Financial Stability Plan in February 2009. A key part of Stabilizing and Healing the Housing Market | 103 Figure 4-3 S&P/Case-Shiller: January 2009 Expectations of Future House Prices and Actual Price Index Index: Jan 2000 = 100 240 Actual 220 200 Housing prices implied by futures contracts traded in January 2009 180 160 140 2006 2007 Source: Case Shiller. 2008 2009 2010 the plan focused on maintaining the flow of housing credit and helping responsible homeowners stay in their homes through the Making Home Affordable (MHA) program. In particular, the Treasury Department made an increased funding commitment to Fannie Mae and Freddie Mac, which had been placed in conservatorship six months earlier. The Federal Reserve, which had previously announced a program to purchase up to $600 billion of GSE debt and mortgage-backed securities, expanded the planned size of the program to $1.75 trillion in March 2009. These actions have resulted in economically meaningful and long-lasting reductions in mortgage interest rates (Gagnon et al. 2010) and credit availability (Fuster and Willen 2010). To help responsible households take advantage of these lower rates, the MHA included the Home Affordable Refinance Program (HARP), which was intended to enhance refinancing opportunities for borrowers who had insufficient equity in their homes. While HARP helped homeowners to hold onto their homes through more sustainable mortgages, other components of the MHA focused on restructuring mortgages of borrowers struggling to stay current on their loans. In particular, the Home Affordable Modification Program (HAMP) provided a streamlined approach to modification of delinquent loans and offered monetary incentives and procedural safe harbors to industry participants. To help communities manage the destruction caused when the housing market collapsed, the American Recovery and 104 | Chapter 4 Reinvestment Act of 2009 (the Recovery Act) provided additional support to the housing market by extending HUD’s Neighborhood Stabilization Program, which began under HERA. This program allocated funds to state and local governments and nonprofit organizations to mitigate foreclosures and to pursue innovative local approaches to deal with the economic effects of abandoned properties. The Recovery Act extended the first-time homebuyer credit established under HERA and increased it to $8,000. This program was extended further by the Workers, Homeownership, and Business Assistance Act of 2009. To date, these initial responses to the housing crisis have assisted several million households. The most recent housing scorecard released by the Department of the Treasury and HUD indicated that, as of December 2011, more than 930,000 homeowners had received permanent modifications under HAMP, putting the program on pace to reach the 1 million threshold early in 2012. Of equal importance, HAMP provided a template for major servicers to follow in conducting their own modifications outside of the program. To date, servicers have undertaken nearly 2.7 million socalled “proprietary” modifications, many of which would not have occurred without the standards established by HAMP. The scorecard also highlights 998,000 loans refinanced though HARP, as well as nearly 1.2 million borrowers helped through various FHA loss mitigation interventions. These programs have faced challenges from a number of structural problems in housing markets. These problems include incentive conflicts that arose when loan servicing was separated from loan ownership in mortgage securitizations, as well as uncertainty about legal liability in loan origination and loss mitigation practices. These problems have been greatly exacerbated by erosion in collateral values, which have increasingly fallen below the value of associated loans and put more than one in five mortgage borrowers “under water.” These dramatic declines in collateral necessitate eventual recognition of economic losses and allocation of such losses to various economic actors. As policymakers have increasingly focused on addressing these deficiencies, each of these original MHA programs has undergone substantial modification, described more fully in the following sections. Negative Equity: An Unprecedented and Pervasive Problem As noted, widespread declines in housing prices resulted in more than a $7 trillion fall in aggregate housing wealth. These losses were borne to at least some extent by most homeowners. For some homeowners, however, falling prices not only wiped out their housing wealth in its entirety but also pushed the value of their homes below the value of outstanding mortgages. The resulting “negative” equity, which is estimated to total $700 billion, has Stabilizing and Healing the Housing Market | 105 become one of the legacy hallmarks of the housing price bubble. This negative equity resulted from large home price declines combined with a number of other factors. According to recent estimates, as many as 10.7 million (or 22 percent of) borrowers are under water. The aggregate negative equity is unequally distributed across the nation. Six states with the highest incidence of negative equity—Arizona, California, Florida, Georgia, Michigan, and Nevada—account for more than half of all underwater borrowers and of the aggregate amount of negative equity (Figure 4-4). All of these states have experienced steep declines in house prices. Negative equity has been associated with a number of problems over and above those caused by the more widespread loss in housing wealth. Underwater borrowers find it difficult, if not impossible, to take advantage of record low interest rates through refinancing, because lenders and investors are unwilling to take on uncollateralized credit risk. The inability to refinance prevents households from lowering their monthly mortgage payments. It also undermines the effectiveness of monetary policy that aims to lower borrowing costs to businesses and households and thus encourage greater economic activity. (For more on the decision to refinance, see Economics Application Box 4-1). Underwater households have weakened incentives to invest in their property, since the expected gains from their investment are likely going to be absorbed by the lender. As a result, underwater households underinvest Figure 4-4 The Distribution of Underwater Mortgages By State, 2011 Legend < 10% 10% - 20% 21% - 29% > 29% N/A Source: CoreLogic. 106 | Chapter 4 in home improvements and maintenance, which leads to the overall decline in the quality of the nation’s housing stock (Melzer 2010). Negative equity has also been associated with heightened realized default rates. Several recent academic and industry studies have found that the higher their negative equity, the more likely households are to become delinquent (Bajari, Chu, and Park 2010; Elul et al. 2010). Recent work by Federal Reserve Board economists (Bhutta, Dokko, and Shan 2010) shows that a household’s equity position amplifies the effect of unemployment shocks on default and that this interaction grows in strength with the degree of negative equity. (For more on data challenges in evaluating the financial situation of homeowners, see Data Watch 4-1). Household delinquency and the ensuing foreclosures are very costly, as they disrupt the social fabric of neighborhoods and cause lenders to engage in an expensive and drawn-out process of liquidation. Moreover, foreclosures not only lower the value of the foreclosed property itself; they also have a sizable spillover effect on valuations of neighboring homes. According f to a recent academic study (Campbell, Giglio, and Pathak 2011), each foreclosure within a 0.1 mile radius of a given house lowers its predicted sale price by 7.2 percent. Negative equity also poses a roadblock for efficient reallocation of housing resources. Families naturally buy and sell houses over their life cycle and in response to shocks such as illness or divorce. The necessity to write a sizable check to the lender upon sale makes it effectively impossible for liquidity-constrained households to trade their houses without creditimpairing actions such as delinquency; deed-in-lieu, in which a borrower returns the property to the lender; or short sale, in which a house is sold for less than the balance of debts secured by the property. Negative equity also has the potential to limit underwater borrowers’ ability to pursue employment opportunities in other geographic areas. The empirical evidence to date, however, has largely suggested that the adverse effect of negative equity on labor mobility—the so-called “house lock effect”—is fairly limited. Macroeconomic Effects of Housing Market Weakness The housing sector plays an important role in determining the health of the broader economy. Two aspects of this relationship are particularly important—the effect of housing wealth on household consumption and the direct contribution of residential construction to gross domestic product (GDP). Stabilizing and Healing the Housing Market | 107 Economics Application Box 4-1: Making a Decision about Refinancing a Mortgage Mortgage rates in the United States reached historic lows in 2011, presenting an opportunity for many homeowners to save money by refinancing their fixed-rate mortgages. However, refinancing typically involves a number of costs that push the effective interest rate above the rates reported in news media. These costs include those associated with obtaining a new loan, such as title insurance and various administrative fees; risk-management charges related to loan origination (for example “points”); underwriting charges for appraisal of the house; and the more mundane costs of gathering documentation. How does a homeowner decide whether it is worth paying the additional costs to reap the benefit of the lower rate? The first step in evaluating refinancing is to get a clear and comprehensive summary of costs associated with a new loan; these should be provided by your loan officer or mortgage broker on a HUD-1 form. While many of these costs can be rolled into the loan, some have to be paid in cash up front. The second step is to lay out the stream of all payments required under the original loan and the new loan used for refinancing. Although this process may seem involved, it will allow you to take into account refinancing costs as well as the fact that you will be making payments on a refinanced mortgage over a longer period than you will have remaining on the existing mortgage. Third, those payment streams need to be converted into one number—the amount of spending today that this stream of payments is worth. This is known as the net present value or NPV. The net present value discounts costs paid in the future to reflect the time value of money and the uncertainty associated with future returns. In the simplest possible form, it is better to have a dollar today than a dollar tomorrow, as this dollar can be invested and grow in value by the time tomorrow arrives. Hence, all future payments are discounted relative to today’s outlays. The choice of the discount rate merits a separate discussion that is beyond the scope of this example. However, some common choices include discounting at the risk-free rate (commonly approximated by the 10-year Treasury rate) or the expected rate of return for the stock market (approximated, say, by the long-term average return on the S&P 500 index). The NPV calculation can be carried out with a spreadsheet program such as Microsoft Excel or on a number of websites. Once NPV values are computed for both payment streams, the one with the lower value is the better choice. 108 | Chapter 4 The computation and comparison of net present values is the main idea behind a broad range of online calculators designed to answer the question of whether refinancing makes sense. An example can be found on Jack Guttentag’s Mortgage Professor’s Website at http://www.mtgprofessor.com/calculators/Calculator3a.html. Some mortgage brokers are fond of making use of simple rules of thumb as a shortcut for using the NPV approach. For example, they may suggest that “the new mortgage rate has to be 1 percentage point lower to justify refinancing with typical closing costs.” Recent estimates of such rule-ofthumb threshold differences in interest rates have varied between 1 and 1.5 percentage points. One often overlooked cost of refinancing has not yet been mentioned. By refinancing today, one generally forgoes the opportunity to refinance in the future if interest rates were to drop a bit further. Suppose you determine that refinancing a 5.75 percent loan into a 4.5 percent loan is advantageous from an NPV standpoint. Then refinancing the original loan into a 4.25 percent loan would be even more beneficial, but refinancing from a 4.5 percent loan would not. This difference between payments at 4.5 percent and 4.25 percent is essentially the value of the forgone option to delay refinancing. The value of preserving this option has fluctuated over time, because it clearly depends on the volatility of interest rates, the economic outlook, and the ability to maintain access to credit markets-a nontrivial concern for today’s borrowers. In recent work, Sumit Agarwal, John Driscoll and David Laibson (2007) calculated the optimal interest rate differential at which to refinance that explicitly takes into account the aforementioned option value (these calculations can be found at http://zwicke.nber.org/refinance/). Take, for example, a family that plans to stay in their house for 10 years, has a $250,000 mortgage at 6 percent interest rate and has a marginal tax rate of 28 percent. For this family, assuming an upfront fee of 1 percentage point of mortgage value (1 point) and cash closing costs of $2,000, refinancing is optimal if the interest rate on the new mortgage is 4.6 percent or less. Unlike the simple rule of thumb, this calculation takes into account family expectations of the future inflation rate, interest rate volatility, and how long they plan to stay in the house—the option value determinants—which affect the ultimate recommendation. Stabilizing and Healing the Housing Market | 109 Consumption Effects The standard approach in economics has been to assume that households consume about the same fraction of the increase in their wealth each year, regardless of its source. Numerous econometric studies have come up with a range of estimates that relate changes in household consumption to changes in wealth (Poterba 2000). Although there is no single agreed-upon value, the consensus range is fairly narrow—the fraction of each additional dollar in wealth consumed in a given year (what economists call the marginal propensity to consume out of wealth, or MPC) is estimated to be roughly between three and five cents. Applying the lower of these estimates to the $7.25 trillion in housing wealth losses to date implies consumption losses of $218 billion a year, or 1.5 percent of GDP. Under standard Okun’s law assumptions, this GDP impact, in turn, translates into a 0.75 percentage point increase in the unemployment rate. The severity of losses experienced during the recession that began in December of 2007 in both national output and in labor markets makes these estimates appear too small. One of the possible explanations for this puzzle may be that declines in housing wealth have a more profound effect on consumption than equivalent declines in other forms of wealth. Case, Quigley, and Shiller (2005, 2011) find strong empirical evidence in support of this hypothesis by exploiting substantial variation across states in house price paths and holdings of equity assets. In particular, they relate quarterly growth rates in house prices and equity holdings to quarterly growth rates in state-level retail sales and find that the consumption response is more sensitive to changes in housing wealth than to changes in stock market wealth. It is noteworthy that both the level of the response and the difference between sensitivities to financial and housing wealth shocks increase substantially once the recent experience is incorporated in the data (the 2011 study includes data from 2000 through 2010.) Why would households respond more to housing wealth shocks? Part of the likely answer has to do with the very different distributions of ownership of various financial asset classes. Most financial assets other than liquidity-restricted retirement plans are heavily concentrated at the top of the wealth distribution. In contrast, holdings of housing assets are much more uniformly spread across different wealth, income, and demographic strata. At the peak of the housing market in the third quarter of 2006, home ownership stood near a record high at 69 percent. Although home ownership rates among African American and Hispanic households were noticeably lower (49 percent and 50 percent, respectively), they vastly exceed ownership rates of all other financial assets other than bank accounts for these two groups. Perhaps more important, housing assets make up a much 110 | Chapter 4 Data Watch 4-1: Need for a Comprehensive Source of Data on Mortgage Debt and Performance There are currently four basic sources of loan-level data on mortgage debt: the Home Mortgage Disclosure Act (HMDA) database, data reported by mortgage servicers, credit bureau data, and public records data. Each of these sources provides insight about mortgage holdings, but the existing system is inadequate for measuring the extent and ownership of financial obligations backed by residential real estate. The HMDA database contains data required to be publicly reported for all mortgages. It is useful for measuring long-term trends in mortgage application volumes and originations, but contains little information on loan terms or performance following origination. Further, HMDA data are released only annually with a significant lag. In contrast, proprietary data sets from loan servicers, such as Lender Processing Services (LPS) and CoreLogic, have useful information on loan characteristics and performance but underrepresent certain loan and investor types. They also have little detail on borrower income or credit scores following origination and lack information on other debt obligations, including those collateralized by the same real estate. The credit bureau data track borrower credit scores and performance on multiple debt obligations over time, but tell us little about loan terms and mortgage contract type and nothing about the employment status and current income of homeowners. Public records contain legal notices of property-related transactions, such as mortgage origination and foreclosure, but they contain little information beyond the reason for creating the record, loan amount, and an associated property identifier. Linking these data sources to produce a more comprehensive database is a challenging undertaking, but a pilot version developed by a team of researchers at Freddie Mac and the Federal Reserve Board has laid a strong foundation for this effort. A combined database could make available critical statistics on the health of the housing market. For example, it could establish a link between first- and second-lien mortgages on the same property, providing key information on the overall extent of borrowers’ leverage in different housing markets. This, in turn, would enable better risk management by first-lien lenders and private investors, as well as better design and implementation of government and private-sector loss mitigation programs. In addition, by utilizing statistical sampling techniques, such a database could correct for known biases across different data sources. Reliance on sampling also could reduce operational burden, allowing for more timely reporting. Stabilizing and Healing the Housing Market | 111 larger fraction of wealth among lower income households. Whereas housing accounted for nearly two-thirds of the overall assets of households in the bottom half of the wealth distribution in 2007, it constituted only 25 percent of assets for those in the top decile, and only 10 percent for those in the top percentile. Shocks to housing wealth not only affect more households than other wealth shocks; they also apply disproportionately to those at the lower end of the wealth distribution. A Pew Research Center report issued in July 2011 provides a stark illustration of these trends, concentrating on the disparate effects of the burst housing bubble on the wealth of minority and white households. Because home equity accounts for a much greater share of household wealth among minorities—59 percent for African Americans and 65 percent for Hispanics in 2005, compared with 44 percent for whites—minority households experienced much greater losses from the housing downturn. These losses were further compounded by the uneven geographic distribution of house price declines. As underscored by the Pew report, more than 40 percent of the nation’s Hispanic households resided in the five states with the steepest price drops—Arizona, California, Florida, Michigan and Nevada—while only about one in five of all white and African American households resided in those states. For Hispanics in those five states, declining home prices have nearly wiped out household net worth, with median values collapsing from about $51,000 in 2005 to just $6,000 in 2009. These trends matter to consumption because empirical research has pointed out systematic differences in marginal propensities to consume across income groups. For example, studies that analyzed the consumption effects of the 2001 and 2008 tax rebates using actual household expenditure data found that low-income households and those with low liquid wealth spent considerably higher fractions of these rebates. These effects were identified in credit card data (Agarwal, Liu, and Souleles 2007), the multiple-category Consumer Expenditure Survey (Johnson, Parker, and Souleles 2006), and automobile purchases (Parker et al. 2011). The fact that housing wealth losses were concentrated among the subset of households most responsive to such shocks may account in part for the magnitude of the observed declines in consumption. Indeed, a recent study by Mian, Rao, and Sufi (2011) shows that households with low levels of nonhousing financial assets experienced much greater declines in consumption for a given decline in home prices. A growing economics literature highlights the importance of household debt balances in influencing the severity of economic slumps. Most of the growth in household debt between 2002 and 2006 can be traced to mortgage-related borrowing, which increased by nearly $5 trillion (or 94 percent of the total increase) over this period. As housing values collapsed, 112 | Chapter 4 many households found their balance sheets tilting heavily toward debt. Household efforts to bring their balance sheets closer to equilibrium leverage can potentially proceed along several avenues. Households can default on their debt obligations. They can accelerate repayment of their debts. Or they can repair their asset base through more aggressive saving. Collectively, these approaches are often referred to as deleveraging. A series of empirical papers attempts to quantify the effect of such deleveraging on consumption (Mian and Sufi 2010; Mian, Rao, and Sufi 2011). These papers broadly suggest that the levered nature of household housing assets amplified the effect of pure wealth losses from the crash in housing prices. The studies compared the consumption response in counties with different pre-recession levels of household debt and found that counties with the highest debt levels experienced much larger and longer-lasting drops in consumption than counties with low debt levels. This finding held true for consumer durables, such as automobiles, appliances, and furniture, as well as for consumption of groceries. These counties also exhibit patterns consistent with deleveraging, as increases in the numbers of defaults, and debt paybacks by non-defaulters are much higher in high-debt counties than in low-debt ones. These trends in consumption in turn affect local employment, particularly in sectors that produce locally consumed goods and services, such as restaurants and retail establishments (Mian and Sufi 2011). Figure 4-5 illustrates the divergence in employment trends in such nontradable industry sectors for high- and low-debt counties. In contrast, the traded goods sectors (not shown) display no such divergence, suggesting that the run-up in debt and bursting of the housing bubble have caused the contraction in aggregate demand. Aside from the consumption effects of debt reduction or increases in savings needed to deleverage, households with impaired balance sheets may also have difficulty obtaining credit, which would further affect their consumption (Hall 2010). Before the crisis, the ability to use home equity as loan collateral served as an important source of financing for household purchases of goods and services. For example, Doms, Dunn, and Vine (2008) find that the increasing ease of tapping home equity credit in the early 2000s allowed homeowners to use their housing wealth to finance various forms of consumption. Another example of the pernicious effects of over-leveraging on access to credit, discussed earlier, is the inability of homeowners with low or negative equity stakes to refinance into low-interest mortgages. Moreover, reductions in the collateral value of houses have a negative effect on the economic recovery by restricting one of the primary channels for financing startup businesses. Stabilizing and Healing the Housing Market | 113 Indexed: 2007 = 1 1.05 Figure 4-5 Employment Growth: Nontradable Industries Low household debt counties 1.03 1.01 0.99 High household debt counties 0.97 0.95 0.93 0.91 2005 2006 2007 2008 2009 2010 Source: Quarterly Census of Employment and Wages; Mian and Sufi (2011). Residential Construction and Home Ownership Patterns As discussed in Chapter 2, residential construction in 2011 remained at very subdued, albeit stable, levels. Starts of new housing units averaged a little over 600,000, roughly in line with the levels observed in 2009 and 2010. Housing starts of both single- and multi-family structures remain far below their peak 2006 levels of 2 million units, weighed down by the cyclical weakness in demand, the slow pace of household formation, high inventories of vacant properties for sale, and tight financing conditions for homebuilders. In addition to cyclical headwinds, residential construction has been impeded by the need to reallocate the nation’s housing stock from owneroccupied to rental units, as a growing number of households exited the ranks of homeowners through foreclosures. Recent research by Federal Reserve economists analyzes the moving decisions of homeowners who went through foreclosure between 1999 and 2010 (Molloy and Shan 2011). This study finds that post-foreclosure households do not tend to move in with others to defray their living expenses. Rather, the overwhelming majority of them (76 percent) end up renting single-family housing units. This evidence suggests that many of the newly foreclosed households will continue to exhibit strong preference for single-family structures. However, the conversion of an owner-occupied house to a rental property takes a certain amount of time, especially if the home is repossessed at the 114 | Chapter 4 conclusion of the foreclosure process. Repossessed homes need to be sold, often rehabilitated, and then marketed to potential renters. This process is made all the more difficult by tight credit conditions for financing investment properties, evidenced by historically high shares of all-cash purchases and by execution problems in amassing property portfolios necessary to realize any economies of scale through multiple foreclosure auctions. In the meantime, prices in rental markets have been trending upward, pointing to the critical importance of efficient conversion of foreclosed properties and providing some of the necessary impetus for this process. A well-functioning mechanism for disposition and conversion of distressed properties into rental units has the potential to ease the downward pressure on owner-occupied house prices by removing a part of bank-owned and shadow inventory of soon-to-be-foreclosed properties from the sales market. (See the Data Watch 4-2 for discussion of challenges in measuring home sales.) Demand for rental housing is likely to grow at a healthy rate over the next few years, creating an ongoing need to convert existing homes to rental. First, household formation is poised to accelerate. As numerous observers have pointed out, household formation slowed dramatically during the 2007–09 recession and has only recently begun to grow. Data from the Census Bureau show formation of fewer than 400,000 new households in both 2009 and 2010, well below the 2002–07 annual average of 1.3 million. The primary part of this trend is cyclical, deriving both from high unemployment rates among the young and from a substantial drop-off in immigration. A 2010 study done for the Mortgage Bankers Association (Painter 2010) suggests that historically, as economic conditions improved, individuals who delayed forming households during recession years were more likely to turn to rental markets to fulfill their housing needs. Second, credit conditions have tightened considerably in recent years. Successful mortgage applicants have substantially higher average credit scores and are required to put up larger down payments than was the case in the era of rapidly rising house prices. For potential homebuyers who are unable to put down 20 percent of the purchase price, loans through the FHA and the U.S. Departments of Veterans Affairs (VA) and Agriculture have become the primary and, in many cases, only avenues for mortgage financing—providing a vital counter-cyclical buffer to sustain access to credit through the crisis. Consequently, the agencies’ market share has risen rapidly, with the FHA accounting for nearly 40 percent of all house purchase loans in 2010. Among minority households, in particular, the FHA and VA loans became the predominant form of financing for home purchase. Between 2005 and 2010, the share of FHA/VA loans has skyrocketed from Stabilizing and Healing the Housing Market | 115 Data Watch 4-2: Need for a Comprehensive Source of Data on Home Sales On December 21, 2011, the National Association of Realtors (NAR) announced substantial downward revisions going back to 2007 of previously reported data on sales of existing homes. The revisions reduced the estimated home sale projection for 2011 from nearly 5 million units to 4.25 million units, and reduced the number of reported home sales between 2007 and 2010 by nearly 3 million units. Although the implied pace of change in recent home sales was largely unaffected, lower sales levels caused a reevaluation of housing market conditions, and, by causing realtor commissions to be revised downward, are expected to lower the level of GDP. To a certain extent, revisions to the NAR data are inevitable. The NAR sales estimates are based on reports from a subset of regional Multiple Listing Services (MLS). The data from the covered areas must be weighted to represent the areas that are not covered and adjustments must be made to this weighting over time. Further, the NAR cannot directly measure sales transactions conducted outside of Multiple Listing Services platforms. These “unlisted” transactions may include houses sold by owners without realtor assistance, sales carried out by builders, and some foreclosure sales. These sales channels vary in importance over the housing cycle and across different geographies, something that can be difficult to capture accurately on a current basis. NAR revisions also reflect the fragmented nature of local MLS systems and their evolution over time. Historically, many metropolitan regions were represented by several MLS databases. The NAR obtained actual sales data from a subset of these databases and adjusted the numbers to account for sales recorded in the remainder. MLS systems have undergone considerable recent consolidation. As NAR adjustments lagged consolidation of MLS systems, reported sales were being grossed up by outdated factors and thus were systematically overstated. Since all property sales are publicly documented by local deed registration systems, it theoretically should be feasible to use these records to estimate sales volumes across all jurisdictions and all channels, and with minimal time delay. The main hurdle to constructing a comprehensive national data source for real estate transactions will be to integrate data across disjointed and dissimilar county-level recording systems. Such data, however, would represent a reliable and timely source of information on sales activity—useful information for macroeconomic forecasters and an important gauge of health in the nation’s housing markets. 116 | Chapter 4 15 percent to 80 percent of all purchase mortgages originated to AfricanAmerican households and from 8 percent to 75 percent of all purchase mortgages originated to Hispanic households. During the past three years, at least 60 percent of all first-time home buyers financed their purchases with FHA or VA loans. Young households surveyed by Fannie Mae repeatedly cite an insufficiently strong “credit history” and “not having enough for a down payment” as two of the biggest obstacles to homeownership. Third, younger households that just experienced a historic decline in housing prices may be less optimistic about homeownership. Recent research (Malmendier and Nagel 2011) showed that households coming of age during periods of sizable declines in the equity market stayed away from equity ownership in the future. For such households, a longer lifetime perspective could not offset the dramatic price declines experienced early in life, which thus tended to have a strong and long-lasting influence on subsequent economic behavior. It is premature to say whether a similar “Depression babies” effect is applicable to today’s young renters. The scant survey evidence available on this question is mixed. On one hand, the Fannie Mae surveys indicate that the majority of young households continue to regard housing as a good financial investment and homeownership as a desirable goal. On the other hand, a series of special supplements to the Michigan Survey of Consumer Sentiment suggest that younger households hold more pessimistic views of homeownership, although this result is limited to a subset of responders with personal knowledge of someone who experienced foreclosure or substantial home price declines (Bracha and Jamison 2011). In sum, the weakness in the housing sector continues to weigh heavily on macroeconomic performance. The enormity of losses in housing wealth and the uneven distribution of those losses in the population, along with the substantial weakening of household balance sheets burdened by debt overhang, have an outsized effect on consumption. High unresolved inventories of distressed properties, along with a concurrent need for large-scale rebalancing of the housing stock, contribute to ongoing difficulties in the residential construction sector. These challenges are compounded by several structural problems in housing markets that have been exposed by the crisis. Understanding and addressing these institutional frictions represents a necessary step in formulating appropriate policy actions. Structural Problems in Housing Market The shock to the housing market laid bare serious deficiencies in the existing infrastructure for servicing delinquent mortgage loans, liquidating Stabilizing and Healing the Housing Market | 117 foreclosed properties, and adjudicating legal disputes between various parties. These deficiencies have impaired the effectiveness of loss mitigation efforts and may also be affecting borrowers’ ability to access mortgage credit. Adjudicating Legal Disputes Rapid growth in the volume and complexity of securitized mortgage credit during the bubble years outpaced developments in case law adjudicating legal liability for representations and warranties associated with loan underwriting. The resulting legal uncertainty has the potential to impede origination of new mortgage credit if it unnecessarily adds to lender liability vis-à-vis mortgage investors. During the standard loan origination process an underwriter provides legally binding representations and warranties (R&W) backing the veracity of collected information. Representations and warranties encompass such crucial elements of the loan application as borrower income, available assets, and the appraised value of the house. Within a specified period of time following securitization, an agent of the investors (the Trustee) conducts a postsale audit of loan documentation. If the Trustee finds R&W violations on a particular loan, the originator is obligated to buy back that loan from the securitized pool. A similar audit may be conducted in the event of mortgage default, when the discovery of R&W violations on defaulted loans would also result in the investor “putting back” the loan to the originator. These put-back rights create a liability for originators that is designed to serve an important quality control function: the originator must bear the risk of loss on defaulted loans with R&W violations. As the number of intermediaries between the underwriter and loan investor grew, the transmission of this liability by each party along the chain became less well understood, and quality control standards became more difficult to enforce. For example, many financial institutions increasingly relied on independent mortgage brokers to carry out customer prospecting and loan underwriting, especially in urban and minority-dominated neighborhoods that have been historically underserved by traditional lenders. Because mortgage brokers did not have sufficient capital to originate and hold a substantial number of loans, they quickly sold their mortgages to a larger financial institution, which, in turn, would securitize the resulting loan portfolio in broader capital markets. In effect, mortgage brokers functioned as independent contractors for banks that would eventually securitize these loans. In a twist on a common description of mortgage securitization, “originate-to-distribute,” this business model was labeled as “outsource-to-originate-to-distribute.” 118 | Chapter 4 In theory, established financial institutions that securitized loans had ample incentives to exercise due diligence. They retained liability for representations and warranties, and carried reputational risk, as well as the risk that they might not be able to pass faulty loans back to the originating mortgage brokers. Yet, there is empirical evidence that at least some banks actively securitized loans originated by mortgage brokers with little or no documentation—the so-called “liar” loans that can be easily falsified (Jiang, Nelson, and Vytlacil 2011). The lengthening of the chain of financial intermediaries made the evaluation and assignment of liability for faulty underwriting processes considerably more complicated. The complexity of the claims, and the sheer number of lawsuits that are being litigated on a loan-by-loan basis, suggest that court resolution will take considerable time, which poses a challenge to stabilizing the housing market and accelerating a recovery. Incentive Conflicts Before securitization became prevalent, the majority of mortgages was funded directly by banks and other deposit-taking financial institutions. These loans were held on lenders’ own balance sheets and were typically serviced by them as well. Securitization of mortgage credit either through GSEs or private label issuers allowed the expansion of funding to broader capital markets. As a result, bank-funded (or portfolio) mortgages became less prevalent, ceding ground to GSE and private-label securitizations (PLS). By 2007, the share of aggregate residential mortgage debt held on portfolio had fallen to 37 percent from 48 percent in 1992, while that held by the PLS investors nearly quadrupled to 19 percent over the same time period. Investors in mortgage-backed securities relied on third-party servicers to collect monthly payments, transmit those payments to various investor classes, and mitigate losses on nonperforming mortgages. The separation of mortgage ownership and servicing gave rise to a number of incentive conflicts between loan investors and their servicers, which made problem mortgages more difficult to address. These relationships are generally governed by “pooling and servicing agreements” (PSAs) that specify permissible actions servicers may take in dealing with delinquent loans. Although the overriding PSA principle is maximization of the value of the loan pool, some litigation was necessary to clarify this principle. Even now that the principle has been established, it can be interpreted in several different ways, particularly for mortgage pools with multiple investor classes or tranches. In particular, junior investors that are second in line (or lower) to receive flows generated by mortgage pools have an incentive to legally challenge modification actions that curtail overall cash flows. The resulting Stabilizing and Healing the Housing Market | 119 internecine “tranche warfare” discourages servicer actions. Indeed, some observers have argued that servicers tailor their loss mitigation practices to minimize the risk of litigation by their investors. Because loan modification is an expensive and uncertain undertaking, servicers may have an incentive to pursue foreclosures as the least legally contentious option. Indeed, recent research found evidence of considerably lower likelihood of modifications for privately securitized mortgages than for portfolio-held loans where no conflicts of interest are present (Piskorski, Seru, and Vig 2010; Agarwal et al. 2011). Moreover, because servicer compensation is based on the unpaid principal balance of performing loans, their incentives are skewed toward modification practices that favor reductions in interest rates and adding unpaid loan balances (or arrears) to the principal, even when that is not the most effective approach to ensuring long-term performance of the loan. These incentive conflicts, coupled with the absence of established legal precedent, effectively limited early modification efforts on securitized mortgages to three alternatives: adding arrears to principal and either lowering the interest rate or freezing it on adjustable-rate mortgages (Agarwal et al. 2011). The unveiling of the Home Affordable Modification Program in early 2009 substantially changed the playing field for loan modifications. By establishing a standardized approach to modifying mortgage contracts that explicitly maximized the return to investors as a group, the program reduced the exposure of servicers performing such modifications to investor lawsuits. The HAMP standards have served as a catalyst for spurring rapid growth in mortgage modification efforts across the industry. As servicers built up their distressed loan infrastructure to accommodate HAMP, they also switched their own modification focus to more aggressive methods that emphasize loan affordability. Policy Actions Both the complexity of the existing challenges in the housing market and the importance to the broader economy of resolving these challenges call for a robust and multifaceted menu of policy actions. Over the past three years, the Administration’s housing policy has continued to expand to fit the circumstances, building on the experience of the early responses to the crisis. The Administration is pursuing additional innovative approaches designed to help households refinance their mortgages and maintain access to credit, to avoid unnecessary and costly foreclosures, to stabilize housing prices, and to help communities rebuild after experiencing a wave of foreclosures and erosion in property values. 120 | Chapter 4 Building on the Experience of Existing Programs A number of program modifications are focused on counteracting the corrosive effects of negative equity. These modifications also seek to overcome a set of institutional hurdles that have thus far limited the effectiveness of certain policy actions. In particular, the Administration worked with the Federal Housing Finance Agency and private market participants to improve HARP—the existing refinancing program for borrowers with insufficient or negative equity in their homes whose mortgages are guaranteed by Fannie Mae or Freddie Mac. The revised program guidelines announced in November 2011 expand the pool of eligible borrowers by removing limits on loan-to-value ratios and extending the program deadline until December 2013. The program also lowers refinancing costs by reducing unnecessary pricing overlays and negotiating favorable pricing on some of the major closing cost items, such as title insurance. The revised HARP also addresses some of the difficult institutional hurdles, such as coordination problems with second-lien holders and mortgage insurers. The changes also lower some of the representation and warranty requirements for existing loan servicers, thereby encouraging greater lender participation. In a bid to further increase use of HARP, the revised program allows servicers to solicit some potentially eligible borrowers directly. Furthermore, major lenders have committed to dedicate additional origination capacity and resources to refinancing HARP borrowers. Whereas changes in HARP were aimed at dulling the adverse effects of negative equity on the ability of currently performing borrowers to refinance their loans, other HAMP initiatives tackled the issues posed by negative equity in modifying loans of delinquent borrowers. In particular, the Principal Reduction Alternative (PRA), announced in October 2010, augments the original HAMP focus on affordability with elimination of a portion of the mortgage balance. The PRA builds on the insight that high levels of negative equity contribute to mortgage default over and above the effects of loan affordability. Consequently, modifications of delinquent loans with high loan-to-value (LTV) ratios may be more effective if they include a principal reduction component. The PRA requires servicers of non-GSE loans to evaluate the benefit of principal reduction for loans that exceed the appraised value of the house by 15 percent or more (that is, have LTV ratios above 115 percent) in making their HAMP determinations. To encourage servicers to use the PRA, HAMP provides monetary incentives for investors to write down principal. At the same time, the PRA seeks to lessen the risk of moral hazard by implementing principal write-down in three annual installments and making it conditional on continuous performance of the Stabilizing and Healing the Housing Market | 121 modified mortgage. Under this earned principal reduction structure, a borrower has a strong incentive to remain current, which enhances the net present value of the PRA modifications to investors. To further encourage investors to evaluate the use of principal reduction in modifying problem loans, the Treasury has recently announced a tripling of the PRA monetary incentives. The Treasury also offered to extend PRA incentives to Fannie Mae- and Freddie Mac-insured loans. The pace of PRA modifications has picked up appreciably in the past few months, with more than one in four HAMP modifications receiving principal reductions. According to the latest Treasury report, more than 36,000 permanent modifications that include principal reduction had been implemented by the end of November 2011 (Department of the Treasury 2011). The median PRA loan had an LTV ratio of 158 percent before modification and a target ratio after modification of 115 percent. The median amount of principal forgiveness for active permanent PRA modifications was about $66,000. Because servicers are not required to offer principal reduction and usually may do so only when permitted by the loan investor, the growing use of the program suggests increasing acceptance of principal reduction as an effective loss mitigation tool by private investors. Similar acceptance is echoed in servicer actions on private, nonHAMP, modifications. Several servicers have shifted their focus to principal reduction for deeply underwater delinquent loans held in securitization trusts. These reductions are typically earned over time to encourage borrowers to maintain loan performance. Principal reductions are also often coupled with a shared appreciation component that exchanges forgiven principal for an equity stake in the property. If the market value of the house in a future sale or refinancing exceeds its value at the time of principal reduction, the borrower shares a part of the appreciation with the lender. Much like the earned principal reduction, shared appreciation effectively raises the borrower’s costs of defaulting to qualify for principal forgiveness. Another HAMP-related initiative recently announced by the Department of the Treasury expands the reach of the program by broadening eligibility. One of the reasons many borrowers have not been able to take advantage of the program is that eligibility was tied to first-lien mortgages. Some borrowers with high medical debts, for example, but relatively average mortgage burdens, did not previously qualify for the program. By expanding eligibility, the changes aim to extend loan modifications to such borrowers and lower the number of preventable foreclosures. The Administration has also expanded housing assistance for unemployed or underemployed homeowners. To help out-of-work homeowners avoid foreclosure, these programs generally provide for a period of 122 | Chapter 4 forbearance of all or part of the monthly mortgage payment. In July of 2011, as the length of unemployment spells continued to exceed forbearance periods for many of the unemployed homeowners, the FHA and the Treasury announced the extension of forbearance to 12 months. This change applies to mortgage servicers that participate in the HAMP’s unemployment initiative program (HAMP UP), as well as to the FHA Special Forbearance program. Following the Administration’s lead, two major lenders and the GSEs have recently announced their commitment to provide up to 12 months of mortgage payment forbearance to unemployed borrowers. Mortgage payment assistance for unemployed or underemployed homeowners has become a prominent feature of state level programs developed under the Hardest Hit Fund (HHF). The President announced the establishment of the Fund in February 2010 to provide targeted aid to families in states that have been hit hard by the economic and housing market downturn. HHF currently provides assistance to homeowners in 18 states and the District of Columbia. The specific programs are designed by state housing finance agencies and take into account local market conditions. In addition to helping unemployed borrowers, HHF programs commonly include efforts to fund innovative approaches to modification of delinquent mortgages and to allow homeowners to transition into more affordable places of residence. Furthermore, in June of 2011 HUD launched the Emergency Homeowners Loan Program (EHLP) which provided $1 billion in interestfree loans to help keep borrowers in non-HHF states who are unemployed, or who suffer from a severe medical condition, from losing their homes. The EHLP is available to borrowers with a long track record of staying current on their mortgages but who find their ability to continue doing so compromised by job loss or illness. EHLP loans are secured by a junior lien note on the homeowner’s principal residence, and the balance on these loans is forgiven in 20 percent increments for each year the borrower remains current on regular mortgage payments. The Administration’s Project Rebuild, introduced as part of the American Jobs Act in September 2011, is another example of building on the experience of existing housing programs. While the revised HARP and the HAMP PRA focus on negative equity, Project Rebuild addresses the damaging effects of foreclosed or abandoned homes on neighborhood property values, economic prospects, and social fabric. Project Rebuild seeks to integrate and expand strategies proven successful under the Neighborhood Stabilization Program to deal with vacant and foreclosed properties. In particular, it explicitly allows federal funding to support for-profit development subject to HUD oversight. It also extends rehabilitation efforts to Stabilizing and Healing the Housing Market | 123 commercial as well as residential properties. Project Rebuild further calls for expanding support for land banks that work at the local level to acquire, hold, and redevelop distressed properties. Federal funds granted under the project would provide land banks with capital infusions that can be leveraged with private-sector investments to finance long-term redevelopment strategies. New Levers in Housing Policy Refinancing. The Administration has called on Congress to pass legislation that will enable more homeowners to refinance their mortgages at today’s historically low interest rates. First, the HARP program is available only to homeowners whose loans are owned or guaranteed by the GSEs. This restriction has left some borrowers unable to refinance their loans only because their mortgages were kept on the originating bank’s books or were securitized in the private, as opposed to the GSE, market—events largely outside of a borrower’s control. To remove this arbitrary distinction, the Administration proposes that the FHA be authorized to offer streamlined refinancing to non-GSE borrowers with standard mortgage contracts. To limit risks to the taxpayers, the proposal emulates HARP in requiring eligible borrowers to have remained current on their mortgages and to meet certain underwriting standards. Another risk-management component of the proposal includes capping the loan-to-value ratio of eligible loans. Second, while enhancements to HARP announced in November of 2011 will increase the reach of the program, more can be done to reduce the barriers to refinancing of GSE-backed loans. Such steps would include harmonizing underwriting requirements for mortgages with LTV ratios below and above 80 percent; further reducing loan fees because GSEs do not acquire any new credit risk by refinancing these loans; fully aligning the treatment of representations and warranties for refinancing with the existing or new mortgage servicers; and removing remaining differences in HARP requirements that still exist between Fannie Mae and Freddie Mac. These changes are aimed at streamlining the operational requirements of the HARP program and making it more accessible to a greater number of borrowers. By leveling the playing field between existing and new servicers, the proposed changes also seek to harness competitive forces to bring more interest savings to borrowers. Third, the Administration’s proposal helps address the problem of negative equity by providing a pathway for responsible homeowners who refinance their mortgages to rebuild their equity more quickly. Under this option, home owners would refinance into a shorter-maturity (20-year, for example) mortgage and commit to deploying the savings from refinancing 124 | Chapter 4 to rebuilding equity in their homes. As an example, consider a borrower who has a 6.5 percent mortgage originated in 2006 with an outstanding balance of $200,000, whose house is worth $160,000 (a loan-to-value ratio of 125). This borrower could lower the monthly payment by $166 by refinancing into a 20-year mortgage at 3.75 percent. Should the borrower choose to keep their mortgage payment at its original level and direct the $166 in savings to principal reduction, the outstanding mortgage balance would decline to $152,000 in five years. Under the proposal, underwater borrowers would have the choice of pursuing this pathway to rebuild their home equity. To assist borrowers who make this choice, the proposal directs the GSEs and the FHA to cover the closing costs of their refinanced loans. Servicing standards. The experience of the past few years showed that the Nation is not well served by the patchwork of rules that govern the mortgage servicing system. To improve accountability and align incentives in the mortgage servicing industry, the Administration recently released a unified framework of servicing standards—the Homeowner Bill of Rights— that is designed to better serve borrowers, investors, and the overall housing market. The Administration will work closely with the Consumer Financial Protection Bureau (CFPB) and other independent regulators, Congress, and other stakeholders to create a more robust and comprehensive set of rules driven by a set of core principles outlined in the framework. These principles include full disclosure of all fees provided in understandable language upfront, with any changes disclosed before they go into effect. The framework also requires servicers to implement standards and practices that minimize conflicts of interest, such as those that exist between multiple investor classes and those that arise when the servicer simultaneously owns a secondary lien on the property. To make loss mitigation actions more timely and effective, servicers are required to contact homeowners who have demonstrated hardship or fallen delinquent, and provide them with a comprehensive set of options to avoid foreclosure. Servicers must further allow homeowners the right to appeal denials for mortgage modification to an independent third party and provide homeowners who find themselves in economic distress with access to a customer service employee with a complete record of previous communications with that homeowner. To minimize inappropriate foreclosure actions, servicers may schedule a foreclosure sale only after they have certified in writing that all loss mitigation alternatives have been considered. To ensure compliance, servicers must maintain strong controls over servicing and loss mitigation operations and subject these controls to periodic independent audits. The Homeowner Bill of Rights is meant to provide an enforceable set of rules, not just guidance, for the servicing industry. Stabilizing and Healing the Housing Market | 125 Conversion of Repossessed Properties into Rental Units. An orderly, fair process for disposition of foreclosed properties remains a key objective of housing policy. Given the ongoing reduction in rates of homeownership, many foreclosed properties will have to be converted to rental units, a process that typically involves rehabilitation. The demand for this type of housing stock will come mainly from private investors whose activity to date has been hampered by execution problems in putting together property portfolios through a series of small-scale acquisitions. Tight credit conditions for financing investment properties have further limited the ability of private investors to fill the gap in demand. To counteract these problems, the FHFA, with the Departments of Treasury and Housing and Urban Development, initiated a process to manage the sale of REO properties held by Fannie Mae, Freddie Mac and the FHA. The goal of this effort is to allow private investors to bid on acquiring pools of REO properties in exchange for a commitment to rehabilitate and manage the properties as rental units. Bulk purchases will make it easier for investors to achieve economies of scale as they implement their individual business strategies. Qualified bidders must demonstrate evidence of property management experience and adequate capital resources, as well as agree to abide by property usage restrictions. For instance, antiflipping provisions establish minimum time periods that an investor must hold the property before seeking to sell it, and minimum reinvestment requirements impose certain quality standards for rented properties. In many ways, the REO-to-rental conversion program seeks to build on the best practices established by successful policy interventions during the crisis. The program focuses on leveraging the expertise and financial resources of private investors, while preserving value for the taxpayers. It looks to avoid rigid top-down solutions, allowing for customization at the local level. And it makes use of the unique position of the GSEs and FHA as owners of large nationwide inventories of distressed properties to provide a large-scale, transparent, and predictable mechanism for converting these properties to better suit local housing demands. Furthermore, the process is intended to help the industry develop a viable framework for acquiring and managing large-scale scattered-site rental portfolios. Similar to the HAMP experience, this framework may well help establish industry standards. Conclusion Developments in the housing market played a central role in the financial crisis and the ensuing recession, and they continue to present a headwind for the economic recovery. Although housing markets are stabilizing 126 | Chapter 4 in many regions, the healing process will inevitably take time. This is a reflection of both the magnitude of the recent housing price collapse and the many institutional obstacles on the path to a new equilibrium. Getting to the end of this path will require unwinding accumulated inventories of foreclosed homes, whether by finding new owners or by converting them to rental units. It will require enabling more homeowners to refinance their mortgages at today’s low interest rates. It will require resolving multiple conflicts of interest in the modification of delinquent loans and providing meaningful assistance to unemployed homeowners as they search for new jobs that would allow them to remain in their homes. It will require restoring access to credit for responsible borrowers and repairing household balance sheets hard hit by erosion of home equity. And it will require working out legal uncertainties and fixing up mortgage finance markets. Instead of waiting for these processes to play themselves out slowly and painfully, the Administration has embarked on a series of multifaceted and fiscally responsible actions in partnership with private market participants and housing regulators to proactively repair the housing market and ease the transition to a new and stable equilibrium. The new policy initiatives seek to enable refinancing, to unlock access to credit for responsible underwater homeowners, to reallocate foreclosed properties to the rental market, to prevent unnecessary foreclosures for borrowers struggling with temporary loss of income, to implement sustainable modifications of delinquent loans, and to repair the frayed infrastructure of mortgage servicing and mortgage finance. Stabilizing and Healing the Housing Market | 127 C H A P T E R 5 INTERNATIONAL TRADE AND FINANCE O ver the past year, global economic growth has slowed, largely due to a range of challenges in the advanced economies. These adverse shocks are, for the most part, unrelated to policies or business decisions undertaken within the borders of the United States. Nevertheless, in an integrated global economy, the United States cannot fully escape their impact. One could hardly begin with a starker example of an adverse shock to the world economy than the massive earthquake that struck Japan’s northeastern coast on March 11. This earthquake was the most powerful to have hit Japan in recorded history, triggering tsunami waves that leveled towns and claimed nearly 16,000 lives. Alongside the devastating human toll, the disaster also had a major impact on the Japanese economy. The International Monetary Fund (IMF) estimates that the Japanese economy contracted by 0.9 percent in 2011. The economic impact also extended far beyond Japan’s borders. For months afterward, supply chains around the world, especially in the automotive industry, were disrupted by production slowdowns and parts shortages. While Japan’s severe economic slowdown in 2011 was driven by a natural disaster, those elsewhere in the developed world were largely a product of forces outside of nature. Slow growth has exacerbated sovereign debt and deficit problems in Europe, and austerity measures put into place in response have impeded near-term growth in a number of euro-area countries. In January, the IMF reported that the euro area’s gross domestic product (GDP) grew 1.6 percent in 2011, down from 1.9 percent in 2010, and predicted that the euro area would contract by 0.5 percent in 2012. Growth in the United Kingdom has also slowed significantly, in part reflecting tight fiscal policies, and is estimated by the IMF to have been only 0.9 percent in 2011. With the European Union, Japan, and the United States collectively accounting for almost 60 percent of global GDP, slower growth 129 Figure 5-1 Real GDP Growth, 2000–2011 Annualized quarterly percent change 12 Emerging 10 markets 8 6 4 2 0 -2 United States, European Union, and Japan -4 2011:Q3 -6 -8 -10 2002:Q1 2004:Q1 2006:Q1 2008:Q1 2010:Q1 Note: Weights come from each nation’s share of GDP within each aggregate. Source: Country sources; International Monetary Fund, World Economic Outlook, September 2011; CEA calculations. in these economies was sufficient to lower growth at the global level in 2011, as Figure 5-1 illustrates. In the face of the broad-based slowdown in economic growth in the developed economies, growth in emerging markets also decelerated.1 Slower growth in import demand in the large economies meant slower export growth in emerging markets.2 For example, growth in China is decelerating because of a decline in export growth as well as a slowdown in domestic real estate investment. Although the IMF predicts China is likely to grow more than 8 percent in 2012, its slowdown contributes to the loss of momentum in global growth. 1 The growth slowdown in some emerging markets also reflected the impact of policy tightening in some countries to prevent overheating. As the year progressed, concerns about overheating tended to give way to concerns about the economic slowdown in the developed countries. 2 The emerging markets aggregate in Figure 5-1 includes Argentina, Brazil, Chile, China, Colombia, Hong Kong, India, Indonesia, Israel, Malaysia, Mexico, Peru, Russia, Singapore, South Africa, South Korea, Taiwan, Thailand, Turkey, Ukraine, and Venezuela. Seventeen member states of the European Union (the EU-27) use the euro. They are Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Malta, Netherlands, Portugal, the Slovak Republic, Slovenia, and Spain. 130 | Chapter 5 Viewed in the context of these external challenges, the growth of U.S. exports over the past year has been a particular bright spot. Despite a slowing global economy, America’s exports of goods and services have surpassed their pre-crisis peaks and have been growing more than fast enough to meet the President’s goal of doubling the 2009 export level by the end of 2014. Many factors are contributing to this fast pace of growth, including continued productivity growth in manufacturing, a shift in unit labor costs that favors U.S. businesses over those in other advanced countries, and technological innovation in the energy sector, which is improving America’s trade balance in petroleum products. A possible further weakening of foreign demand conditions, however, could pose a risk to future U.S. export growth. Global economic events could also affect the U.S. economy through financial links between the United States and the rest of the world. These links have increased dramatically in recent decades. U.S.-owned assets abroad and foreign-owned assets in the United States increased more than six-fold between 1994 and 2010. “Global rebalancing” has been a major theme of U.S. international economic policy since the beginning of the Obama Administration. In the years before the global financial crisis erupted in 2008, large asymmetries had developed in the global economy. Several countries characterized by large, persistent current account surpluses, including Germany, Japan, and China, relied too heavily on unsustainable growth in net exports to drive economic growth. Several other countries characterized by large, persistent current account deficits, including the United States, relied on unsustainable growth in household consumption and construction of residential real estate. A more symmetric, better balanced pattern of growth is needed throughout the major economies. In the United States, future growth must be driven less by consumption and more by net exports and investment. Conversely, countries that have traditionally run large current account surpluses need to rely more on domestic consumption and less heavily on net exports. So far, the United States has made significant progress toward rebalancing. For progress to continue, however, U.S. exports must grow even more, and consumption in the surplus countries must increase. The Euro-Area Crisis and Its Implications for the United States A key potential risk in 2012 to the U.S. and global economic recoveries remains the sovereign-debt and banking crises in Europe. Economic and fiscal conditions vary greatly among the 17 economies in the euro area, as illustrated in Figure 5-2. Although there is significant heterogeneity among International Trade and Finance | 131 Figure 5-2 Economic and Fiscal Indicators for Selected Euro-Area Countries a. GDP Growth (Percent) Greece Italy 2000–2007 average 2012 projection Portugal Spain France Germany Netherlands Ireland Belgium Austria Finland Slovak Republic Estonia -4 -2 0 2 4 6 8 Note: Projections include revisions as of January 2012. Source: International Monetary Fund, World Economic Outlook, September 2011. 10 b. Public Debt–GDP Ratio (Percent) Estonia Slovak Republic Finland Netherlands 2000–2007 average 2012 projection Spain Austria Germany France Belgium Portugal Ireland Italy Greece 0 50 100 150 Source: International Monetary Fund, World Economic Outlook, September 2011. 132 | Chapter 5 200 euro-area economies, economic and fiscal conditions in most of them deteriorated throughout 2011. In 2012, the economies of Estonia, Finland, and the Slovak Republic are predicted to grow by more than 2 percent, but those in Greece, Italy, Portugal, and Spain are predicted to shrink by more than 1.5 percent. Similarly, the ratio of general government gross debt to GDP is projected to be roughly 70 percent or below in Estonia, Finland, the Netherlands, the Slovak Republic, and Spain and above 110 percent in Greece, Ireland, Italy, and Portugal. Economic research shows that there are many determinants of sovereign credit risk or sovereign borrowing costs, including individual factors (Berg and Sachs 1988) and global financial factors (Eichengreen and Mody 2000; Longstaff et al. 2011). Since early 2010, both sets of factors raised borrowing costs for some smaller and a few larger economies in the euro area. The European Commission (EC) and the IMF negotiated assistance programs for Ireland (November 2010), Portugal (May 2011), and Greece (May 2010, July 2011, and October 2011). In October 2011, the sovereign-debt crisis intensified in Italy and Spain, the third- and fourth-largest economies in the euro area.3 In response to the marked increase in sovereign borrowing costs, the European Central Bank (ECB) intervened, resuming its Securities Markets Program, in an effort designed to lower sovereign bond yields by purchasing government debt in secondary markets. European leaders and institutions have also introduced and expanded various measures to inhibit contagion, such as the European Financial Stability Facility. While these measures have helped contain the sovereign-debt crisis in Europe, significant risks remain. Market participants are expressing ongoing concerns about the fiscal conditions of Italy and Spain, as well as Greece and Portugal, in part because of fears that economic growth in these countries is likely to be sluggish for a prolonged period, exacerbating their fiscal situation. European banks are among the largest holders of European government debt. (See Financial Stability Oversight Council 2011 for a discussion of the interconnections between U.S. banks, European banks, and European government debt.) As concerns about sovereign debt rose, spreads widened on sovereign bond yields relative to German bond yields in June 2011 (as highlighted in Figure 5-3), leading to deteriorating conditions of both solvency and liquidity among European banks. Toward the end of 2011, many European banks were facing shortened maturities and higher costs of funding in the interbank market, an important source of bank liquidity. In December 2011, after two successive cuts in interest rates, the ECB took major steps to provide increased liquidity to euro-area banks. Among 3 Assistance programs for Greece negotiated in 2011 have not yet been implemented. International Trade and Finance | 133 Figure 5-3 10-Year Bond Spreads Over German Bonds, 2010–2012 a. Greece and Portugal Basis points 3,600 3,200 2,800 2,400 2,000 Greece Jan. 31 1,600 1,200 800 Portugal 400 0 Jan-2010 Jul-2010 Source: Bloomberg. Jan-2011 Jul-2011 Jan-2012 b. Italy, Spain, Belgium, and France Basis points 600 Italy 500 Spain Belgium 400 France 300 200 100 0 Jan-2010 Jul-2010 Source: Bloomberg. 134 | Chapter 5 Jan. 31 Jan-2011 Jul-2011 Jan-2012 other measures, the ECB’s new longer-term refinancing operation extended the maturity of loans offered to banks from one year to three years, and the ECB eased collateral requirements for those loans. The Federal Reserve also extended and reduced the cost of dollar liquidity swap arrangements to the ECB, as it had done during the credit freeze of 2008–09. A currency liquidity swap is an agreement between two or more parties to exchange a set amount of a given currency for another currency at a given price until a specific date in the future. In this case, the Federal Reserve provides dollars for periods ranging from overnight to as long as three months in exchange for the currency of the foreign central bank. In turn, the foreign central bank can lend the dollars during the specified period in its local markets, helping to relieve funding pressures in those markets and to prevent the spread of strains to markets elsewhere. Given the interconnectedness of European and U.S. banks and the presence of branches, agencies, and subsidiaries of European banks in the United States, adverse financial conditions in Europe can be transmitted to American financial institutions. According to the Federal Reserve’s Senior Loan Officer Opinion Survey, several European branches tightened standards on commercial and industrial (C&I) loans over the second half of 2011, in contrast to U.S. and other foreign banks. The C&I loans on the books of European branches in the United States have in fact declined noticeably since the middle of 2011. Such financial data are being monitored closely. One of the goals of recent financial oversight embedded in the Dodd-Frank Wall Street Reform and Consumer Protection Act is to reduce systemic risk by increasing transparency. Among other things, the new law supports trading of financial instruments on central exchanges, including derivatives. (For a discussion of the role of the Office of Financial Research in fostering transparency, see Data Watch 5-1.) Similarly, trade and investment links between the United States and Europe are broad and deep, and, in recent years, of growing importance relative to the rest of the world. Europe is a significant destination for U.S. exports, accounting for more than 20 percent of U.S. goods exports and nearly 40 percent of U.S. service exports. In addition, sales by European affiliates of U.S. multinational firms totaled $3.1 trillion in 2008, making up more than half of the $6.1 trillion in total sales abroad by U.S. multinational firms. Furthermore, Europe is the leading foreign source of investment and jobs in America, accounting for $173.2 billion, or 76 percent, of all foreign direct investment (FDI) inflows into the United States in 2010. International Trade and Finance | 135 Data Watch 5-1: The Significance of the Office of Financial Research (OFR) in Combating Global Risks to the U.S. Financial System The recent financial crisis presented a stark example of the need for comprehensive data on the financial system. While the initial catalyst for the financial crisis was a decline in U.S. housing prices that in 2007 led to a dramatic rise in subprime mortgage defaults (Brunnermeier 2009), neither market participants nor policymakers were aware of the extent to which leverage, reliance on ultra-cheap short-term funding, and a web of interconnected transactions and claims had built up in the financial system prior to that time. It became clear that investors had placed too high a value on the underlying homes, real estate, and other assets that were supposed to stand behind their investments. Consequently, as defaults on mortgages multiplied, they triggered a wholesale flight from related financial securities, which spread across countries and financial markets. The inadequacy of information available to assess risks properly magnified that flight from risk (Squam Lake Working Group 2009). The resulting credit crunch ultimately triggered a global economic recession from which many countries are still recovering. Responding to the devastating effects of the financial crisis, on July 21, 2010, Congress enacted the Dodd-Frank Wall Street Reform and Consumer Protection Act (PL 111-203). The creation of the OFR in that Act addresses two glaring deficiencies in the financial data infrastructure that were revealed by the crisis. First, the OFR is charged with increasing the availability of financial information so that policymakers can better identify, analyze and monitor potential risks to the U.S. financial system. Critically, given the interconnectedness of global financial markets, this legislation permits the acquisition of data from financial institutions related to their activities globally that may pose a threat to the financial stability of the United States. Second, OFR is charged with improving the quality of financial information, in part by standardizing the types and formats of data that are reported to regulators. Standardized data would make it easier for policymakers to accurately evaluate whether a financial institution or group of institutions—located either domestically or abroad—or certain financial activities in which they may be engaged pose a threat to the U.S. financial system. Over the past eighteen months, the OFR has laid the critical groundwork for enhancing both the quantity and the quality of financial information that is available to U.S. policymakers. The OFR is in the midst of comprehensively cataloguing the data that are currently held and collected by U.S. financial regulators. Concurrently, the OFR will collaborate with the member agencies of the Financial Stability Oversight Council to identify and fill deficiencies in the collection of 136 | Chapter 5 data on financial markets. Likewise, the OFR has taken an important step toward enhancing the quality of the financial data infrastructure through the promotion of a global Legal Entity Identifier (LEI) for financial institutions. At the G-20 Cannes Summit, leaders supported the development of a global LEI and tasked the Financial Stability Board with coordinating this work. U.S. policymakers have partnered with the global financial services industry, foreign regulators, and associations such as the International Organization for Standardization to develop and begin to implement a universal standard for identifying counterparties to financial transactions (Department of Treasury 2011). In time, further initiatives will be undertaken to meet the information needs of regulators in fulfilling the mandate of the Dodd-Frank Wall Street Reform Act and responding to potential threats to the financial stability of the United States. Outlook for Europe and Implications for the U.S. Economy As noted, the crisis in Europe has slowed both current and predicted growth. The IMF estimates that euro-area growth in 2011 was 1.6 percent, but for 2012, the IMF forecasts that economies in the euro area will contract by 0.5 percent. Faltering consumer confidence in Europe has spread to countries outside the euro area. Britain’s Nationwide Consumer Confidence Index fell for the fifth month in a row in November 2011, reaching an all-time low of 36 points, compared with a historical average of 77. Economic growth projections for the European Union for 2012 are lower than for 2011: -0.1 percent in 2012 compared with 1.6 percent for 2011 (IMF 2012). A slowdown in Europe could affect the U.S. economy through two channels in addition to the finance channel mentioned above: trade and direct investment. Exports. The share of U.S. goods exports to Europe has been over 20 percent for decades. A severe financial episode in Europe could reduce exports from businesses throughout the United States. As is the case with flows of inward investment, exports to Europe are distributed broadly across the United States, as displayed in Figure 5-4. The European Union is the destination for more than 20 percent of total goods exports from Alabama, Connecticut, Indiana, Massachusetts, South Carolina, and West Virginia. Exports range from cars, aircraft, and semiconductors, to coal, gold, soybeans, kaolin, and live chickens. Moreover, export data for commodities underestimate the extent of U.S. trade with Europe because, as noted, more than one-third of U.S. service exports go to Europe. Shrinking purchases of International Trade and Finance | 137 Figure 5-4 Share of Each State's Goods Exports to the European Union by State, 2010 Legend < 5% 5% - 9.9% 10% - 14.9% 15% - 20% > 20% Note: This map depicts the state from which the product is last shipped, which is not necessarily the state in which the product is produced. Products with multiple stages of production often move across state boundaries more than once before leaving the country. Source: U.S. Census Bureau, Foreign Trade Data. American goods and services by Europeans could have a significant impact on U.S. employment in several states. Foreign Direct Investment. Declines in output, profit, and investor confidence in Europe could have an adverse effect on the ability and willingness of European firms to invest in American firms and jobs. The United States received more than $228 billion in FDI from all foreign sources in 2010, over 75 percent of which came from Europe. Between 2004 and 2010, FDI flowed into every state, with Texas receiving the most, followed by Alaska, California, New York, Indiana, Illinois, Ohio, Alabama, South Carolina, and Georgia. International Cooperation in Resolving Crises The data in Figure 5-3 starkly reflect growing concerns of market participants regarding the scope and magnitude of euro-area bank and sovereign-credit risk. In the last decade, systemic risk related to financial crises has received more attention in the economics literature, including studies by Allen and Gale (2000), Kaminsky, Reinhart, and Vegh (2003), Frankel and Wei (2005), Reinhart and Rogoff (2009), and Ang and Longstaff (2011). While Europe has the capacity to take responsibility for addressing its crisis through decisive policy action and a credible financial backstop, the United States has made clear that the international community has a strong interest in the successful resolution of the crisis. The Administration 138 | Chapter 5 is engaging with European governments both bilaterally and in multilateral forums. The United States has also been involved in the response to the crisis through its role in the IMF. The Administration continues to urge movement along several dimensions in Europe: robust implementation of countries’ agreed fiscal and structural reform programs, in the context of steps that euro-area leaders have outlined to reform fiscal governance in the euro area; a more substantial financial firewall to ensure that governments can borrow at sustainable interest rates while executing policies to strengthen the foundations for growth and to reduce their debts; and measures to ensure that European banks have sufficient liquidity and are adequately capitalized to maintain the full confidence of depositors and creditors. Global and U.S. economic performance will depend, in part, on the swift resolution of problems in the euro area. In such times of global economic and financial disequilibrium, U.S. coordination with international partners remains essential. Foreign Direct Investment, International Trade, and the U.S. Economy Experience and economic theory suggest that a global economy can provide enormous advantages for American workers, consumers, and firms. In the absence of international trade and investment, a country can consume only what it produces, it can invest only what it saves, it can use only the technology that it creates, and it can take advantage of only those natural resources within its borders. Countries that have deliberately cut themselves off from international trade and investment for extensive periods of time have paid a stiff price in forgone opportunities for investment, consumption, and growth. North Korea, a nation that has pursued this kind of isolation assiduously, illustrates this point in a powerful and tragic way. Before Kim Il-Sung seized power in northern Korea, it was at least as rich as southern Korea. Today, per capita GDP in South Korea is over 17 times higher than that of North Korea. One of America’s achievements after World War II was helping to build the open and integrated global trading and investment system that now incorporates almost all of the world’s economies. Of course, this system brings challenges, along with opportunities. The Obama Administration has focused on meeting the challenges of this system in ways that enable American workers and firms to make the most of the rich opportunities provided by a more open global trading and investment system. At the same time, the Administration has sought to ensure, through strong enforcement International Trade and Finance | 139 efforts, that other countries play by the rules of the system, and it has sought to protect those who are potentially adversely affected by global competition with a stronger safety net and an improved training and reemployment system (discussed in Chapters 6 and 7). Investment in the United States by Foreign Companies The United States had the largest annual flow of inbound FDI of any economy in the world in every year between 2006 and 2010. By 2010, the cumulative FDI stock in the United States had reached nearly $3.5 trillion— more than three times the FDI stock in each of the next three largest recipients (Hong Kong, France, and the United Kingdom) and more than five times China’s cumulative inbound FDI stock ($579 billion). Given the rapid GDP growth of large emerging markets such as Brazil, India, and China, both before and after the global financial crisis, it is not surprising that these countries and other emerging markets are absorbing an increasing fraction of the world’s FDI. Nevertheless, their inflows remained substantially below those into the United States throughout this period. Like trade flows, FDI flows tend to be procyclical, rising when the global economy expands and contracting when it shrinks. In late 2008 and 2009, as the global economy sank into its deepest postwar recession, FDI inflows around the world contracted (Figure 5-5); by 2009, total FDI flows were roughly 60 percent of their 2007 levels. Nonetheless, the United States remained the largest destination for new FDI inflows. As both the U.S. and global economies recovered from the recession, FDI inflows into the United States increased 49 percent from 2009 to 2010. Then, as global growth slowed again in 2011, FDI into the United States also decelerated. Through the third quarter of 2011, FDI inflows into the United States were running roughly 4 percent below 2010 levels. If the global economy returns to normal growth rates, FDI inflows into the United States will likely resume their growth. The Nation continues to offer a set of “fundamental attractors” to foreign investors that other countries struggle to match. One such attractor is the sheer size of America’s domestic market. In 2010, America’s GDP was nearly two-and-a-half times larger than that of China, the world’s second-largest economy. The United States also offers potential investors a strong rule of law, a highly skilled, motivated workforce, a highly developed financial system, and effective protection of property rights. The United States continues to lead the world in key technologies, attracting investment by firms eager to conduct worldclass research in close proximity to the world’s top universities. For all of these reasons, leading companies around the world continue to be attracted to investment opportunities within the borders of the United States. 140 | Chapter 5 Figure 5-5 Annual FDI Inflows, Selected Countries, 2006–2010 $ Billions 350 300 250 United States 200 150 100 50 China Brazil Russia India 0 2006 2007 2008 2009 2010 Source: United Nations Conference on Trade and Development (UNCTAD). The Benefits of FDI. U.S. affiliates of foreign firms make significant contributions to U.S. employment, output, investment, research and development (R&D), and exports. The Bureau of Economic Analysis (BEA) of the U.S. Department of Commerce surveys the activities of foreign-owned affiliates in the United States. According to its data, in 2008, subsidiaries of foreign companies accounted for nearly 5 percent of U.S. private-sector jobs, more than 11 percent of all U.S. private capital investment, more than 14 percent of all U.S. private-sector R&D, and 19 percent of all U.S. goods exported. In that year, the U.S. employees of these global companies earned an average annual compensation of about $73,000—about one-third more than the economy-wide average. Economic research shows that the benefits of foreign investment are even greater than these measures indicate. When foreign subsidiaries use advanced technologies and effective management to achieve high levels of productivity in their U.S. operations, the benefits can “spill over” to their American competitors (Keller and Yeaple 2009). As U.S. firms increasingly interact in their home market with highly productive foreign subsidiaries, the U.S. firms may be able to learn from their competitors’ strengths. Keller and Yeaple find that 14 percent of the aggregate productivity growth between 1987 and 1996 (a period of rapidly rising FDI in the United States) resulted from FDI-related productivity spillovers. These spillovers were International Trade and Finance | 141 particularly valuable for small firms, which do not routinely encounter these competitors in markets outside the United States. One reason proximity matters is that employees who move from foreign firms to domestic firms are often an important conduit through which knowledge diffuses from foreign to domestic firms (Poole forthcoming). While foreign firms sometimes establish entirely new enterprises in the United States, with newly constructed plants and newly hired workers (known as “greenfield” investment), they more often gain a foothold in the U.S. market by merging with or acquiring existing domestic businesses. These transactions can be beneficial. Finally, FDI can help connect domestic firms to export networks and opportunities. The importance of such connections is well documented in developing countries (Aitken, Hanson, and Harrison 1997), but the United States can also benefit from such connections. Encouraging FDI in the United States. The Obama Administration has taken vigorous steps to facilitate and promote inward FDI in the United States. As emerging markets expand, the forces of economic gravity are likely to pull more and more of the world’s FDI inflows into these economies. Recognizing the reality of greater global competition for FDI, the Obama Administration has set up SelectUSA, a “one-stop shop” based in the Department of Commerce that helps both foreign and U.S. investors find the best options for their prospective businesses within the borders of the United States. SelectUSA is the first systematic Federal Government initiative to identify, inform, assist, and attract potential investors to the United States. It is also finding ways to partner with state and local economic development agencies, so that governments at all levels can coordinate efforts to attract investment. In the United States, state, local, and regional economic development organizations (EDOs) facilitate business investment attraction, retention, and expansion. SelectUSA can help these organizations compete more successfully with alternative production sites outside the United States; it can also function as an important resource for these organizations on international investment issues. SelectUSA’s activities cover a broad range of investment promotion functions. Staff respond to investment inquiries, help connect investors to appropriate federal and state agencies, and educate investors regarding relevant U.S. policies and procedures. SelectUSA staff and senior leadership also serve as ombudsmen for the investment community in Washington, working across the Federal Government to address investor concerns and issues involving federal agencies. Finally, SelectUSA works with U.S. EDO officials and U.S. embassies and consulates to organize events abroad that enable U.S. locales to promote themselves as a destination for FDI. President Obama has recently called for a substantial increase in support for SelectUSA, proposing 142 | Chapter 5 $12 million in new resources and an increase in staff to 35 full-time employees. Complementing this investment, President Obama has proposed to increase the presence of the Department of Commerce’s U.S. and Foreign Commercial Service officers in key markets. These new officers will enhance the ability of the U.S. global network of embassies and consulates to promote FDI in the United States. President Obama has also called for tax reforms that will help attract more FDI. These proposals include a decrease in the United States’ corporate income tax rate, as well as additional tax incentives for firms that manufacture, conduct R&D, or invest in the capability to produce clean energy products within the borders of the United States. At the same time, the President’s proposals eliminate incentives for U.S. firms to move jobs and production offshore. By complementing the United States’ fundamental attractors with well-targeted FDI promotion efforts, the Federal Government can help ensure that the United States remains a premier destination for foreign direct investment for many years to come. The National Export Initiative In his January 2010 State of the Union address, President Obama set a goal of doubling U.S. exports of goods and services in five years, meaning that nominal exports would double from their 2009 level of $1.58 trillion to an annual level of $3.16 trillion by the end of 2014. To meet that goal, nominal U.S. exports must grow an average of 15 percent a year. So far, exports have grown even faster, putting the U.S. economy on track to meet the President’s goal. In fact, the United States is currently ahead of schedule, despite the recent global trade slowdown. Over the 12 months ending in November 2011, total U.S. exports of goods and services exceeded $2.08 trillion, surpassing the pre-crisis peak level of $1.7 trillion and establishing a historical record. Current data suggest that the ratio of exports to GDP nearly reached 14 percent in 2011, another historical record. Anatomy of Recent Growth in Goods Exports. U.S. trade data provide an interesting picture of the markets and goods in which America’s export growth has been concentrated since the global financial crisis. Table 5-1 ranks U.S. export goods categories in order of the biggest increases in export value between the first half of 2009 and the first half of 2011. The top 10 categories collectively account for 72 percent of the total value increase in exports between the two periods. The biggest increases have been concentrated in manufacturing industries characterized by high technology and capital intensity and in primary products, reflecting America’s abundant endowments of human and physical capital, its technological prowess, and its natural-resource wealth. International Trade and Finance | 143 Between the first half of 2009 and the first half of 2011, the United States increased its exports of vehicles by more than $26 billion (83 percent); its exports of engines, appliances, and general machinery by more than $25 billion (35 percent); and its exports of electrical machinery by more than $19 billion (33 percent). Exports of plastics, organic chemicals, and steel and ferrous metals increased by 53 percent, 57 percent, and 78 percent, respectively. These data point to America’s competitiveness in important sectors of manufacturing. At the same time, the data reaffirm the United States’ strength as an exporter of natural-resource-intensive goods. Exports of mineral fuels and oils (a commodity dominated by shale oil) surged by 150 percent, or more than $35 billion, over the two-year period. That surge stems from technological breakthroughs in horizontal drilling and hydraulic fracturing that are allowing U.S. producers to extract oil from previously unusable areas; these technological developments are reviewed further in Chapter 8. Fuel exports have grown so much that the United States became a net exporter in 2011, for the first time in decades. The United States remains the world’s largest importer of crude oil, and U.S. net imports of crude remain large relative to net exports of fuel products, but increased domestic production is offsetting some crude oil imports. Exports of gold, diamonds, and precious metals grew 94 percent, reflecting the high prices of those commodities on international markets. Exports of cereals grew 77 percent, reflecting America’s strength as a producer of agricultural commodities. This strength is also reflected in the impressive growth of total agricultural exports, a broader category not shown in the table, which increased by 51.8 percent over the same period, an expansion of $24 billion in dollar terms. The U.S. Department of Agriculture reports that U.S. agricultural exports reached a record high of $137.4 billion in Fiscal Year 2011, and that America’s agricultural sector recorded a trade surplus of $42 billion over that period. America’s ranchers, farmers, and producers are benefiting from the Administration’s focus on free trade agreements and increased market access abroad. Trends Driving Growth in Goods Exports. The sharp growth in goods exports reflects, in part, the impact of recovering from the depth of the global financial and economic crisis. It also reflects the impact of coordinated Federal Government action flowing from the President’s National Export Initiative. These actions amplify the positive influence of longer-term trends that are enhancing the competitiveness of the U.S. tradable goods sector, particularly in manufacturing. U.S. workers are more productive than those of any other G-20 economy, and U.S. productivity growth has been especially strong in the manufacturing sector. However, highly productive 144 | Chapter 5 Table 5-1 Growth in U.S. Goods Exports, by Product Product HS-code Export growth, 2009:H1–2011:H1 Change ($ Billions) Change (% ) 12-month sum (Sept. 2010– Aug. 2011) ($ Billions) Mineral fuels (including shale oil) 27 35.8 150 113.3 Vehicles and parts 87 26.3 83 112.7 Engines, appliances, and general machinery 84 25.7 35 198.7 Electrical machinery and equipment accessories 85 19.1 33 157.3 Precious metals and gems 71 16.6 94 64.9 Plastics 39 10.2 53 57.5 Organic chemicals 29 8.0 57 44.4 Optical equipment and medical devices 90 7.4 24 78.0 Cereals 10 6.7 77 27.8 Iron and steel 72 5.5 78 23.8 Note: Export growth is measured between the first half of 2009 (2009:H1) and the first half of 2011 (2011:H1). Source: U.S. International Trade Commission. U.S. workers can be placed at a competitive disadvantage because of low labor costs abroad. This disadvantage was especially severe in the early years of the 2000s when the enduring effects of earlier financial crises in many parts of the world depressed production costs in much of Asia, Brazil, Russia, and elsewhere. Since then, continued robust productivity growth in the United States, particularly in the manufacturing sector, has been reinforced by a gradual realignment of the currencies of many U.S. trading partners. The result has been a sharp improvement in relative unit labor costs in the United States. For example, the U.S. Bureau of Labor Statistics (BLS) tracks changes over time in the unit labor cost of manufacturing in the United States and in key trading partners. U.S. hourly compensation in manufacturing has grown over the past decade, but rapid productivity growth in the United States has reduced the cost of producing a unit of manufactured output. Meanwhile, measured in U.S. dollars, the cost of producing a unit of manufactured output in key trading partners has risen, in some cases substantially. Of the 19 economies tracked by the BLS, only Taiwan managed to improve its unit labor cost position more than the United States did.4 Figure 5-6 displays changes in manufacturing unit labor costs for some of the key economies tracked by the BLS. 4 Although the BLS does not track Chinese unit labor costs, it has tracked an index of import prices from China since 2003, and the most recent movements in this index suggest that Chinese unit labor costs are also rising. International Trade and Finance | 145 Percent Figure 5-6 Change in Manufacturing Unit Labor Costs, 2002–2010 100 79.0 80 67.6 60 40.8 40 20 0 -20 14.1 -23.0 Taiwan -10.8 2.1 17.1 44.1 20.8 2.9 Singapore Japan United Korea Sweden Germany France Canada Italy Kingdom United States -40 Source: Bureau of Labor Statistics. The impact of these shifts can be seen in a number of industries including the auto industry. As U.S. auto demand recovers, the Big 3 domestic auto companies and the foreign-domiciled companies have been expanding U.S. production. This expansion is designed not only to serve the U.S. market but also to use U.S. production sites as an export platform from which to serve other markets within the Americas and beyond. Ford has announced intentions to increase investment in the United States, both to serve the U.S. market and to export. Such plans include insourcing production of its F-650 and F-750 medium-duty trucks to Ohio from Mexico; it also reportedly plans to move manufacture of components like transmission oil pumps from China to Michigan. Improved competitiveness also appears to be reflected in employment data. U.S. manufacturers have added jobs for two consecutive years, something that had not happened since the late 1990s. Manufacturing employment has grown faster in the United States than in any other leading developed economy since the start of the recovery. As of the most recent period for which comprehensive data are available, the United States has added more net manufacturing jobs since the start of 2010 than the rest of the Group of 7 countries put together, with over 300,000 created since December 2009. While the economy is still far from recovering all the manufacturing jobs lost during the recession, signs suggest that the United 146 | Chapter 5 States may be experiencing a manufacturing revival. Between 2010:Q1 and 2011:Q3, manufacturing employment rose 2.5 percent in the United States compared with 2.4 percent in Germany and 1.8 percent in Canada. In some industries, the advantage created by high U.S. productivity is reinforced by the additional advantage of abundant, domestic, low-cost natural gas. Only a few years ago, leaders of the domestic organic chemical industry predicted that shortages in natural gas would dramatically raise the domestic price of natural gas, one of their key inputs. Without adequate domestic supplies of natural gas at reasonable prices, it seemed likely that chemical production would have to shift overseas. Since the mid-2000s, however, the discovery of new natural gas reserves, such as those within the Marcellus Shale Formation, and the development of hydraulic fracturing techniques to extract natural gas from these reserves have led to rapidly growing domestic production and relatively low domestic prices for households and downstream industrial users. By keeping domestic energy costs relatively low, the increased supply from this resource supports energy-intensive manufacturing in the United States. In fact, companies such as Dow Chemical and Westlake Chemical have announced intentions to make major investments in new U.S. facilities over the next several years. In the longer run, the scale of America’s natural gas endowment appears to be large enough that exports of natural gas to other major markets could be economically viable. The Obama Administration is taking steps to ensure that this resource is developed in a safe and environmentally responsible way. However, in most of the manufacturing industries where American firms continue to enjoy robust export sales, U.S. producers rely principally on high productivity, rather than inexpensive inputs, to offset the higher wages and other labor compensation they pay their U.S. workers. The openness and competitive intensity of the American economy have been a key source of our national strength, since they have increased the efficiency of U.S. firms and industries. (See Hsieh and Klenow 2009, 2011 for recent research.) As a consequence, even extremely low wages in developing countries are not sufficient to provide a commanding cost advantage with respect to U.S. firms, at least in some product categories. Exports can also be measured by looking at major destination markets. Table 5-2 ranks destination markets by the increase in value of exports between the first half of 2009 and the first half of 2011. The top 10 markets collectively accounted for 70 percent of the total increase in export value. Export flows to Canada and Mexico increased by nearly $80 billion. Much of the rest of the U.S. export expansion was driven by exports to Asia. Even the tsunami-battered Japanese economy purchased nearly $8 billion more International Trade and Finance | 147 Table 5-2 Dissection of U.S. Goods Export Growth, by Market Market Export growth, 2009:H1–2011:H1 12-month sum (Sept. 2010–Aug. 2011) ($ Billions) Change ($ Billions) Change (% ) Canada 43.1 45 272.2 Mexico 36.3 62 187.1 China, Mainland 19.2 63 102.2 Euro Area 16.1 20 193.2 Republic of Korea 9.0 72 42.1 Brazil 8.4 71 40.2 Japan 7.7 31 64.3 Hong Kong 6.9 71 31.9 Taiwan 6.0 80 27.5 Singapore 5.0 51 30.5 Note: Export growth is measured between the first half of 2009 (2009:H1) and the first half of 2011 (2011:H1). Source: U.S. International Trade Commission. in U.S. exports in the first half of 2011 than it did in the first half of 2009. Outside of North America and Asia, Brazil continued to display its emerging economic importance, absorbing a 71 percent increase in U.S. exports that, in dollar terms, slightly exceeded export growth to Japan. The Role of Services in Export Growth and America’s Current Account Balance While export growth is critical, exports are just one component of the current account balance, the most comprehensive measure of the Nation’s exchange of goods and services with the rest of the world. The main components of the current account include exports and imports of goods, exports and imports of services, and the income balance—the difference between the income American firms earn from their foreign businesses and the income foreign firms earn from their U.S. businesses. A look at the recent history of the U.S. current account balance and its key components reveals some interesting patterns. Although U.S. exports of goods are at historical highs, reflecting in part the improved competitiveness of American manufacturers, the U.S. trade deficit in goods (which does not include trade in services) has nevertheless widened significantly since early 2009, as an expanding economy has boosted demand for imports (Figure 5-7). The trajectory of the U.S. current account, however, is following a different path now than it did in the previous recovery, and the difference primarily reflects the impact of the other two main elements of the current account—services trade and the U.S. income balance. 148 | Chapter 5 From the early 2000s through 2006, the current account balance tracked the trade balance in goods quite closely. The two series began to diverge in late 2007. The balance on goods remained in deep deficit, but the trade surplus in services began to increase, and the income balance grew even more rapidly. When the global financial crisis hit in earnest in the third quarter of 2008, U.S. growth and import demand dried up, and the two series moved closely together (this time rapidly toward balance) through early 2009. Then, as financial markets stabilized and growth resumed, a gap opened up once again. The balance on goods deteriorated, but the services surplus expanded and the income balance grew even more sharply, largely offsetting the declining balance in goods and keeping the current account relatively stable. More recently, the goods trade balance appears to have broadly stabilized, whereas the services surplus and the income balance continue to grow. With a need to further strengthen the current account balance, federal policymakers recognize the need not only to encourage exports of goods, but also to expand the important role that services trade can play in that process. The Prospects for Trade Growth in Services. Like most other advanced economies, U.S. GDP is dominated by service industries. According to the Bureau of Economic Analysis, services, broadly defined, account for more than 60 percent of U.S. GDP. However, the role of business services within Figure 5-7 U.S. Current Account Balance and Its Components, 2000–2011 $ Billions 100 Balance on income 50 Balance on services 0 -50 -100 Overall current account balance -150 Balance on goods -200 -250 2000:Q1 2011:Q3 2002:Q1 2004:Q1 2006:Q1 2008:Q1 2010:Q1 Note: The current account balance above includes goods, services, and income, but does not include unilateral transfers. Source: Bureau of Economic Analysis. International Trade and Finance | 149 the U.S. economy is less widely recognized. In 2007, a year unaffected by the recent severe downturn and gradual recovery, business services, a collection of industries that includes finance, engineering services, research and development services, and software production, employed 25 percent of the U.S. workforce according to data from the Economic Census. The share of employment in business services was substantially larger than in the entire manufacturing sector in that year (10 percent), and the average wage in business services, $56,000, was significantly higher than in manufacturing ($46,000) (Jensen 2011). While services remain more difficult to trade than goods, advances in communications technologies and the growing ease and declining expense of international travel are making business services increasingly tradable across countries. As this trend gained strength, employment in the business service sector increased almost 30 percent between 1997 and 2007, while manufacturing employment decreased more than 20 percent. Most tradable business services rely intensively on highly skilled experts, which the United States has in large numbers. In other words, the growing tradability of business services plays to America’s comparative advantage. Some evidence of this potential is apparent when one looks at the broader context of America’s trade across the full range of service industries. Services exports have expanded dramatically, growing by 114 percent between 1997 and 2010, according to official data. They now account for nearly 30 percent of total U.S. exports. Imports of services have also expanded rapidly, but the U.S. surplus in services trade, already large, has more than tripled since 2003. What are the categories of services exports, and what is their relative contribution to the surplus? Figure 5-8 depicts the aggregate service trade flows in the five main categories tracked by official statistics and measures their contribution to America’s overall services trade surplus. Travel exports reflect the spending of foreign tourists and business travelers to the United States who purchase goods and services here, while travel imports reflect purchases made by U.S. residents traveling abroad. The United States remains among the world’s leading tourist destinations and runs a surplus in travel trade. The Obama Administration has sought to expand U.S. travel exports with unprecedented federal action to promote international tourism in the United States. In 2010, the President signed into law the Travel Promotion Act, which established the Corporation for Travel Promotion, now known as Brand USA, a public-private partnership dedicated to promoting travel to the United States. The State Department has also increased its visa-processing capacity in priority countries like Brazil 150 | Chapter 5 Thousands Figure 5-8 Contribution to Services Surplus by Service Sector Category, 2010 $ Billions 90 72 70 Royalties and license fees Other private services 70 50 30 28 10 -10 4 Travel Passenger fares -11 Other transportation -30 Source: Bureau of Economic Analysis. and China to ensure that the United States benefits from the rapid expansion of outbound tourism from these emerging markets. Moreover, on January 19, the President established a Task Force on Travel and Competitiveness that will develop a National Travel and Tourism Strategy with a goal of making the United States the world’s top travel and tourism destination. The benefits of that strategy include not only the potential increase in travel exports, but also lower travel imports as it will provide Americans with more and better choices of travel and tourism destinations within the United States. Because of their value as public goods, the government has an important role in ensuring that national treasures such as Yellowstone National Park and the Statue of Liberty are appropriately maintained and made accessible to domestic and international tourists. While there are many private, state, and local destinations in the United States, public expenditures on the National Park System (NPS) are much lower than the benefits they provide to all Americans, even to those who are not necessarily planning a vacation or visit to one of the 397 destinations that make up the NPS (National Research Council 1996). This provides yet another example of the ways in which investments in the environment yield benefits for the economy (Chapter 8). In the category of passenger fares, exports are those received by U.S. carriers from foreign residents; imports are those paid by U.S. residents International Trade and Finance | 151 to foreign carriers. Other transportation exports and imports include U.S. international transactions arising from the transportation of goods by ocean, air, land, pipeline, and inland water carriers. Royalties and license fees cover transactions with nonresidents that involve intangible assets, including patents and trade secrets, which are involved in the production of goods. This category also includes copyrights, trademarks, franchises, rights to reproduce or distribute motion pictures and television recordings, rights to broadcast live events, software licensing fees, and other intellectual property rights. In 2010, this category was the largest single contributor to the services surplus, highlighting the importance to the United States of enforcement of strong intellectual property rights in other countries.5 The final category, other private services (OPS), generates by far the highest level of exports, and it is this category in which the promise of business services exports is seen. The main services included in OPS are education, financial, insurance, telecommunications, and business, professional, and technical services. The most important subcategory—business, professional, and technical services—accounts for more than half of OPS exports. Altogether, OPS exports expanded by about 150 percent from 2000 through 2010—a compound average growth rate of nearly 10 percent a year. The additional detail on service exports and imports presented in Table 5-3 and Table 5-4 underlines two important facts about U.S. services trade. First, the other advanced industrial countries are still America’s dominant trading partners in this sector, both as markets and as suppliers. As rapid economic growth raises income levels in large emerging markets, however, U.S. service export flows to these countries are likely to grow. Second, as noted, the surplus in services is disproportionately driven by two categories—other private services and royalties and licensing—that are skillintensive and thus conform to America’s comparative advantage as a technologically advanced nation with an abundant supply of highly educated workers. This supply of skilled workers and the broader role that education plays in the U.S. labor market is discussed in Chapter 6. In addition to exporting services, U.S. firms provide services through affiliates in foreign markets. Over the past decade, services provided through affiliates have grown rapidly, and in 2009, the most recent year for which comprehensive data are available, services supplied through the foreign affiliates of U.S. firms totaled $1.1 trillion. Of course, U.S. customers also 5 In fact, the official numbers for royalty and license fees may understate, perhaps substantially, America’s receipts for the use of its intangible assets. A report submitted last year by leading international economists (Feenstra et al. 2010) noted the ability of multinational corporations to effectively locate their intellectual property in low-tax jurisdictions, minimizing their global tax liability as well as measured U.S. royalties and license fees. 152 | Chapter 5 purchase services from the U.S. affiliates of foreign firms. These purchases totaled $668.8 billion in 2009. The difference between services received from and supplied to the United States via the channel of affiliate sales was $407.6 billion, providing yet another reflection of America’s comparative advantage in this domain (Koncz-Bruner and Flatness 2011). Policy Initiatives to Support Export Growth in Goods and Services Recent economic research has focused on U.S. firm productivity and the fixed cost of exporting as fundamental determinants of U.S. exports at the firm and product level (Bernard et al. 2003; Melitz 2003). Fixed costs for firms are associated not only with the decision to begin exporting but also with the decision to export to a specific country. Before significant exports to a given country can begin, a prospective exporting firm must develop a strategy that allows it to compete successfully against experienced rivals in that country, which operates under a different legal system and may use a different language. Successful exporters must invest considerable management attention and time to developing this strategy before they can begin to earn any returns from exporting. The costs of serving a particular foreign market may also increase if the firm’s products and complementary services must be significantly altered to meet the demands and tastes of customers in that market. Exporters also must incur the costs of finding distribution channels in the foreign country and the ongoing costs of transporting their goods across national borders and contending with tariff or nontariff barriers to trade. These costs are worth incurring only if the firm is dynamic and productive enough to have a high probability of success. Federal programs exist to help firms deal with these costs. While private firms must take the lead in crafting their export strategies, the Department of Commerce’s International Trade Administration maintains offices of trade professionals in more than 100 U.S. communities and 77 foreign countries to help U.S. firms become export-ready, identify target markets, and navigate the demands of foreign regulation and cultural differences. The Federal Government can also use effective multilateral, bilateral, or regional trade negotiations to reduce the costs imposed on U.S. firms by foreign tariff and nontariff barriers. It can also seek to ensure that American firms face a level playing field by insisting that U.S. trading partners honor their treaty commitments regarding market access for U.S. firms. Finally, in circumstances in which a particular exporter faces financing constraints or the threat of subsidized finance for international competitors, the Federal Government can seek to alleviate these constraints and counter foreign International Trade and Finance | 153 Table 5-3 Cross-Border Services Exports by Type and Country, 2010 2010 Exports ($ Millions) Country Royalties Passenger Other transand license fares portation fees Other private services Total private services Travel All countries 530,274 103,505 30,931 39,936 105,583 250,320 Total for the top 10 countries 290,680 59,489 19,659 20,395 65,607 125,530 Canada 50,521 16,641 4,182 2,984 8,287 18,427 United Kingdom 48,535 8,765 2,801 3,641 6,864 26,464 Japan 44,750 10,198 4,360 3,555 10,721 15,916 Ireland 24,840 1,033 280 300 12,850 10,377 Germany 24,118 4,534 1,248 2,779 6,181 9,376 Mexico 24,110 6,117 2,612 1,226 2,526 11,629 China 21,135 3,780 1,225 2,296 3,333 10,501 Switzerland 20,313 1,043 320 1,169 8,281 9,500 Brazil 16,515 4,236 1,683 998 3,123 6,475 France 15,843 3,142 948 1,447 3,441 6,865 239,594 44,016 11,272 19,541 39,976 124,790 Other countries Source: Bureau of Economic Analysis. Table 5-4 Cross-Border Services Imports by Type and Country, 2010 2010 Imports ($ Millions) Country Royalties Passenger Other transand license fares portation fees Other private services Total private services Travel All countries 368,036 75,507 27,279 51,202 33,450 180,598 Total for the top 10 countries 215,078 33,704 11,410 25,382 25,071 119,511 Canada 39,652 4,324 3,705 3,107 3,031 25,485 United Kingdom 31,740 245 974 16 30,505 Japan 25,579 6,539 501 4,404 1,036 13,099 Ireland 23,541 3,278 1,331 5,670 7,817 5,445 Germany 22,476 2,606 2,562 3,632 3,187 10,489 Mexico 19,665 630 399 1,748 5,272 11,616 China 15,067 2,409 1,473 1,887 4,016 5,282 Switzerland 13,730 8,999 697 904 379 2,751 Brazil 13,661 2,108 207 156 141 11,049 France Other countries 9,967 2,566 535 2,900 176 3,790 152,958 41,803 15,869 25,820 8,379 61,087 Source: Bureau of Economic Analysis. 154 | Chapter 5 — government efforts. Over the past three years, the Obama Administration has placed renewed emphasis on all of these policy domains. Free Trade Agreements with Colombia, Panama, and Korea. The Obama Administration has worked to restore the Nation’s economic stability and support jobs for more Americans with the expansion of smart, responsible trade policy. From day one, the Obama Administration has insisted on higher standards for trade agreements. The President moved to address important concerns that the Administration, certain stakeholders, and Members of Congress had with respect to the situations in Colombia, Panama, and Korea. This domestic consultation and further consultations with U.S. trading partners took time, as did negotiations with Congress to ensure that the passage of the free trade agreements was accompanied by a strengthening of America’s Trade Adjustment Assistance program for workers adversely impacted by international competition and by an extension of key trade preference programs. Once this process was complete, Congress passed the three agreements in quick succession in the fall of 2011, marking the biggest step forward in American trade liberalization in nearly two decades. Of the three agreements, the most economically significant was the Korea–United States free trade agreement, which was expected to boost annual U.S. goods exports to Korea by as much as $11 billion. The agreement also included Korean commitments expected to result in considerable expansion of U.S. services exports. The Trans-Pacific Partnership. In November 2009, President Obama announced the Administration’s intention to participate in Trans-Pacific Partnership (TPP) negotiations to conclude a free trade agreement with key trading partners in the Asia-Pacific region. The agreement aims to set a new and higher standard for regional free trade agreements, not only addressing the traditional core issues in such agreements but broadening the scope to include regulatory coherence and priorities for small and medium-size enterprises. In addition to the United States, the other countries participating in the negotiations currently include Australia, Brunei Darussalam, Chile, Malaysia, New Zealand, Peru, Singapore, and Vietnam. At the November 2011 APEC meeting in Honolulu, TPP leaders announced the broad outlines of a TPP agreement. In addition to existing negotiating partners, Japan, Canada, and Mexico have formally expressed their interest in joining TPP negotiations. While no decision has been made yet by the TPP countries regarding expanding negotiations, interest by Japan, Canada, and Mexico in the TPP demonstrates the economic and strategic importance of this initiative to the Asia-Pacific region. Support for Small Exporters. In a world of imperfect financial markets, the costs of financing export operations pose an additional barrier for International Trade and Finance | 155 smaller firms. Given that export opportunities can come to small exporters with significant risks attached, domestic financial institutions may regard a small firm that is highly dependent on exports as a riskier (and therefore less creditworthy) borrower than one with an exclusively domestic focus. The relatively modest financing needs of small exporters are a further disincentive to private financial institutions, which would have to engage in timeconsuming assessments of the firm, its products, and the country-specific risks involved in a transaction to originate only a small loan with limited value for the lending institution. Unless it is obvious to the lender that the firm has excellent prospects for significant export growth, and brings with it the near certainty of rapid expansion in loan volume, the money a private bank can make on such a transaction is limited relative to the transaction costs themselves. To address these issues the Federal Government has directed the Export-Import Bank of the United States to proactively support small and medium-size firms. First established in the 1930s to finance U.S. international trade when and where private-sector financing was difficult or unreasonably costly to obtain, the Ex-Im Bank has historically focused much of its lending activity on larger, established exporters. The Obama Administration, however, has encouraged the bank to substantially increase lending to smaller firms, and in Fiscal Year 2010, the Ex-Im Bank authorized $5 billion—20 percent of its total authorizations—to support small businesses as primary exporters. The Ex-Im Bank approved 3,091 transactions involving small business exporters—88 percent of total authorizations. In the same year, the bank issued 2,524 insurance policies to small business exporters, 90 percent of such policies for the year. The bank also authorized a record $2.2 billion in working-capital guarantees, 70 percent of which supported small business. Financial support for the expanding international activities of small business extends beyond the Ex-Im Bank. The Overseas Private Investment Corporation (OPIC), the U.S. Government’s development finance institution, extends medium- to long-term financing through direct loans, loan guaranties, political risk insurance, and support for investment funds to eligible investment projects in developing and emerging markets, where conventional financial institutions often are reluctant or unable to lend. In Fiscal Year 2011, 78 percent of OPIC’s projects, representing nearly $1 billion in commitments, involved American small and medium-sized businesses.6 6 The Ex-Im Bank and OPIC follow the Small Business Administration’s definition of a small business, using guidelines that reflect, among other things, sales, employment levels, and sector of economic activity. These guidelines are available online at http://www.sba.gov/sites/default/files/Size_Standards_Table.pdf. 156 | Chapter 5 Promoting U.S. Economic Interests Abroad. Even as it seeks to open up new markets for American business through new trade agreements, the Obama Administration is also working to protect American commercial interests under existing trade agreements. An historic victory came in May 2011, when the World Trade Organization (WTO) issued a final ruling siding with the United States in its case against the European Union over illegal subsidies to Airbus. After decades of dispute and more than five years of official proceedings, the WTO ruled that the EU governments had provided $18 billion in illegal subsidies to Airbus and ordered them removed by the end of the year. U.S. Trade Representative Ron Kirk hailed the ruling, saying, “The WTO Appellate Body has confirmed without a doubt that Airbus received massive subsidies for more than 40 years and that these subsidies have greatly harmed the United States, including causing Boeing to lose sales and market share in key markets throughout the world.” If the European Union fails to comply with the WTO directive, the United States can seek the right to impose countermeasures. In its ongoing dialogue with China, the Obama Administration secured a strong commitment from Chinese President Hu Jintao that China would stop discriminating against U.S. technologies and intellectual property in its government procurement plans. The Administration is monitoring developments closely to ensure that market realities conform to central government directives. The United States has filed a WTO case against China, challenging the troubling imposition by China of antidumping and countervailing duties against imports of U.S. chicken “broiler products.” The Administration scored another major victory in January 2012 when the WTO’s Appellate Body upheld a WTO panel ruling condemning Chinese export quotas and duties on certain key industrial raw materials as a violation of China’s WTO commitments. These actions add to a series of cases in which the Federal Government has taken action at the WTO to protect U.S. economic interests jeopardized by Chinese policy in areas such as steel products, electronic payment services, and wind power equipment. In November 2011, the United States gained China’s confirmation through bilateral negotiations that it would not require foreign electric vehicle manufacturers to transfer technology to Chinese enterprises or to establish Chinese brands as a condition for investing and selling in China. One year earlier, the United States successfully persuaded China to adopt transparent and non-discriminatory technology standards for its emerging smart grid market and to remain technologically neutral with regard to the development of third-generation and future technologies for its telecommunications market. International Trade and Finance | 157 Several of America’s trading partners, including China, have effectively imposed bans on U.S. meat product exports. These bans have no scientific basis, and the Administration has been trying to bring these bans to an end as soon as possible. In 2011, agreements were reached to resume exports to Chile and Egypt. Fifty-seven countries have removed their avian influenza bans on imports of poultry products from the United States since 2008. Most of the countries that imposed bans on the import of U.S. swine, pork, and pork products in the wake of international concern over the H1N1 virus have removed those bans. With strong support from the United States, Russia concluded negotiations to join the WTO in December 2011. In supporting Russia’s WTO accession, the Obama Administration has laid the basis for a more effective, rules-based approach to managing U.S. trade relations with the largest economy not yet inside the WTO system. The Administration will be working with Congress to end application of the “Jackson-Vanik” amendment to Russia so that the United States can enjoy all of the benefits of Russia’s membership in the WTO and U.S. companies and workers can compete on a level playing field with those of other WTO Members in exporting products and services to Russia.7 To further enhance the Federal Government’s ability to protect the Nation’s commercial interests, the President is creating and seeking funding for a new Trade Enforcement Unit, which will significantly enhance the Administration’s capabilities to aggressively challenge unfair trade practices under international and domestic trade rules. The President is also proposing to improve trade inspection capabilities of the Customs and Border Patrol and the Food and Drug Administration, to increase the likelihood of stopping counterfeit, pirated, or unsafe goods before they enter the U.S. market. Certain countries, including China, aggressively use subsidized capital to promote their exports, and appear to offer such export financing on better terms than allowed under current international best practices. In response, the Administration will actively employ its existing authorities so that the Ex-Im Bank can provide U.S. firms competing for domestic or third-country sales with matching financial support to counter foreign noncompetitive official financing that fails to observe international best practices. The IMF estimates that sub-Saharan Africa will grow by 5.5 percent in 2012, faster than advanced, emerging, and developing economies as a whole. Between 2000 and 2010, five of the 10 fastest-growing economies in the world were in sub-Saharan Africa, and trade between Africa and the 7 The Jackson-Vanik amendment is a provision in the 1974 Trade Act that denies most favored nation status to certain countries that restrict emigration. It was introduced during the Cold War, partly as a response to efforts by the Soviet Union to restrict emigration. 158 | Chapter 5 rest of the world increased more than 200 percent. Central to the United States’ economic policy for Africa is the African Growth and Opportunity Act (AGOA), which provides duty-free access to a broad range of exports from 37 eligible sub-Saharan African countries. To help African countries make the most of AGOA’s trade benefits, the United States funds technical assistance work at Regional Trade Hubs. The United States also fosters investment by negotiating Bilateral Investment Treaties (BITs) with African countries. In 2009, the United States launched BIT negotiations with Mauritius, and, in 2011, the U.S. Senate ratified the U.S.-Rwanda BIT. In agriculture and other sectors, the U.S. Agency for International Development uses public-private partnerships to build new markets and has been recognized by the Organisation for Economic Co-operation and Development as the best among its peers with respect to private-sector engagement. The Millennium Challenge Corporation (MCC) is partnering with American and local businesses. From helping the Port of Cotonou in Benin cut its average customs-clearance time in half to facilitating an American company’s efforts to provide much-needed power to Tanzania’s national grid, the MCC is investing in infrastructure to expand trade, commerce, and development across the African continent. Other agencies—including OPIC and the Ex-Im Bank—have significantly increased their investment in Africa. These activities are consistent with the goals of President Obama’s Presidential Policy Directive on Global Development signed in September 2010 that establishes a new model for U.S. development efforts. Tax Reform to Promote American Competitiveness. The Administration’s proposed reform of the U.S. corporate income tax seeks to enhance American competitiveness, promote investment in the United States, and support continued robust growth of American exports. As part of a comprehensive tax reform plan, the President has proposed a reduction in the U.S. corporate income tax rate, with additional incentives available for firms that manufacture, conduct research and development, or invest in the capability to produce clean energy products within the borders of the United States. At the same time, the President addresses longstanding features of the American corporate tax system that encourage some companies to move jobs and production overseas. Increasing Market Access for Services. As noted, the United States has a strong comparative advantage in services. The global market for services trade, however, remains far more closed than the global market for manufactured goods. The long history of extensive trade in goods, the relatively simple nature of many barriers (tariffs and quotas) to such trade, and the cumulative result of six decades of multilateral, bilateral, and regional trade International Trade and Finance | 159 liberalization efforts have resulted in a global economy in which formal barriers to trade in manufactured goods are reasonably low, especially in the advanced industrial countries. The barriers to trade in services are more complex and harder to quantify. Hufbauer, Schott, and Wong (2010) review a number of methodologies for quantifying the barriers to trade in services and present new estimates at the country level of the tariff equivalents of these barriers. Their findings suggest that the aggregate level of discrimination against services imports in important emerging markets such as China, India, and Indonesia is equivalent to a tariff on these imports of more than 60 percent. The size of these barriers may not be surprising—extensive international trade in services is a recent phenomenon, and diplomatic efforts to open services markets are just beginning—but these barriers deprive American firms of critical export opportunities to rapidly emerging markets in an area where their international comparative advantage is the strongest. America’s productive exporters of services cannot solve this problem on their own. The President is committed to negotiating effectively and aggressively for increased liberalization of services trade. The Administration has already made progress in bilateral and regional trade agreements, but the largest emerging-market economies have not yet been fully engaged in these initiatives. The primary multilateral means for seeking greater services market access has been through negotiations pursuant to the General Agreement on Trade in Services (GATS) and, to a lesser degree, the WTO Agreement on Government Procurement. While taking existing GATS disciplines and market access commitments into account, the United States is also pursuing additional pathways to services liberalization, including a new, multiparty agreement open to any country ready to take on high standards and address new issues such as trade in the digital economy. Other advanced countries and progressive developing countries are likely to share the U.S. interest in pushing for greater liberalization of services trade and may be willing partners in this effort. Recent scholarship demonstrates that services liberalization is in the interest of countries that are importing services as well as those that are exporting services. Better access to world-class services raises productivity and living standards in emerging-market economies. Interesting evidence on this point comes from a randomized experiment in India (Bloom et al. 2011). Researchers based at Stanford University and the World Bank randomly selected a set of Indian textile factories to receive a complimentary five-month program of consulting services from a leading international firm. Upon arriving in these factories, the researchers and consultants found that productivity was hampered by poor management practices. Over the next 160 | Chapter 5 five months, the consultants worked with the firms to implement standard management practices proven to have enhanced productivity, output, and profitability in the West. When the project ended, the “treated” factories had cut defects roughly in half, substantially reduced inventories, and increased output, while the control factories saw little change. The authors calculate that these performance improvements increased profits by about $350,000 a year. These are sufficiently large increases that the firms would have made enough money from the consulting projects to be able to pay the consultants commercial rates for their engagement in the projects. Given the magnitude of the improvement, why had the firms not adopted these practices earlier? The researchers’ results suggest that informational barriers were the primary factor explaining the lack of adoption. What is true for India is likely to be true throughout the developing world. By reducing barriers to trade in services, developing countries can help their own firms move toward the productivity frontier achieved in the West. Conclusion Over the course of 2011, the pace of growth in the global economy slowed, posing challenges for the U.S. recovery. Nevertheless, U.S. exports have climbed to record high levels, the current account deficit narrowed to 2.9 percent of GDP in the third quarter, and the economy has begun to rebalance its sources of growth, laying the foundation for sustained future expansion. The greatest threats to continued progress in these domains lie beyond America’s borders. Provided Europe’s debt crisis can be resolved, America’s export growth and progress toward rebalancing are likely to continue at a brisk pace. Other developments in the global economy, notably the continued expansion of international trade in services and the interest of major trading partners in new U.S. trade initiatives, provide a foundation of new opportunities on which the U.S. economy can build in the years to come. International Trade and Finance | 161 C H A P T E R 6 JOBS AND INCOME: TODAY AND TOMORROW R ecessions caused by financial crises typically cause large declines in aggregate demand, as households that have borrowed excessively during the boom years bring down their debt during and after the recession. This deleveraging cycle takes time and disrupts the labor market, because reductions in consumer spending mean that employers require fewer workers to satisfy customer demand. Long-term problems that have been building over several decades pose a further set of challenges for the labor market. Inequality was sharply rising and earnings were stagnant for middle-income families for many years before the latest recession. And job growth from the end of the 2001 recession through 2007 was the weakest for any recovery in more than five decades. The Great Recession exacerbated these problems. Despite the severe damage caused by the recession that began in December 2007, the labor market is gradually improving. Sustained privatesector job growth resumed more quickly after the official end of the 2007–09 recession than it did after the two previous recessions (Figure 6-1). Private employers have now added jobs, on net, every month since February 2010. In 2011, 2.1 million private-sector jobs were added to the economy, the most in any year since 2005. But, given the depth of the 2007–09 recession, the recovery has not yet resulted in enough new jobs to replace all of those that were lost. Continuing the recovery is essential to putting more Americans back to work. And even as the economy and job market recover, long-term trends that predate the recession continue to pose a challenge for American families and businesses. Responding to these challenges, the President has proposed measures that independent economists predict would create millions of jobs. To make sure that Americans are equipped to compete in the economy of the future, the President has also taken steps to improve K–12 education and to make college more accessible and affordable for middle-class families, 163 Figure 6-1 Monthly Change in Private-Sector Employment, 1980–2012 Thousands 1,200 900 600 Jan-12 300 0 -300 -600 -900 Jan-1980 Jan-1985 Jan-1990 Jan-1995 Jan-2000 Jan-2005 Jan-2010 Note: The large fluctuations in private-sector employment in 1983 were due to strike activity. Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. actions that should help to mitigate the long-term trend of growing income inequality. Jobs and Employment The traditional pattern has been that as both the U.S. economy and population have grown, so too has the number of jobs filled by American workers. Between January 1980 and July 1990, from business-cycle peak to business-cycle peak, total U.S. employment grew by an average of 151,000 net new payroll jobs a month; it grew even more quickly, at a rate of 178,000 payroll jobs a month, between July 1990 and March 2001, again from business-cycle peak to business-cycle peak. But this long-term pattern of job growth changed around the turn of the millennium. Between March 2001 and December 2007, the economy added a monthly average of only 68,000 total jobs and only 50,000 private-sector jobs. U.S. job creation slowed even as productivity growth remained relatively strong, and even as other developed countries, such as the United Kingdom and Canada, maintained robust job growth. Against this backdrop of weak employment growth beginning in about 2000, the economy fell into recession in December 2007 and began to shed jobs at the end of 2008 at a rate unprecedented in the postwar era. 164 | Chapter 6 During 2008 and 2009, the economy lost an average of 361,000 jobs a month, reaching a high of 818,000 jobs in January 2009. As the recession continued, the unemployment rate doubled, from 5.0 percent in April 2008 to a peak of 10.0 percent in October 2009, a rate not seen since 1983 (Figure 6-2). Soon after the President signed the American Recovery and Reinvestment Act (Recovery Act) on February 17, 2009, the pace of job loss slowed. The private sector has added jobs in each of the past 23 months, registering a cumulative gain of 3.7 million jobs since February 2010, including 2.1 million jobs in 2011. Private-sector job growth has averaged 159,000 jobs per month since February 2010, and 218,000 jobs per month in the last three months (ending in January 2012). The recession has had a large and continuing negative fiscal impact on State and local governments, however, and they continue to shed workers, thus offsetting some of the private-sector job growth. Nonetheless, with the support provided by the Recovery Act and by the payroll tax cut and unemployment insurance extensions contained in the Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act of 2010, the U.S. economy has added jobs in every month since February 2010, excluding temporary Census hires. The continuing recovery has brought the unemployment rate down from a peak of 10.0 percent in October 2009 to 8.3 percent in January Percent 12 Figure 6-2 Unemployment Rate, 1980–2012 10 8 Jan-12 6 4 2 0 Jan-1980 Jan-1985 Jan-1990 Jan-1995 Jan-2000 Jan-2005 Jan-2010 Note: Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. Jobs and Income: Today and Tomorrow | 165 2012. The 0.9 percentage point decline in the unemployment rate that occurred in 2011 is the largest in any calendar year since 1994. The pace of the recovery has varied across sectors of the economy, with those sectors most harmed by the financial crisis the slowest to recover. Since February 2010, when the private sector began consistently adding jobs, job growth has been strong in industries such as education and health services (+717,000 jobs as of January 2012); trade, transportation, and utilities (+683,000 jobs); and manufacturing (+400,000), but is still weak in some sectors, notably construction (+43,000 jobs) and State and local government (-456,000 jobs). The continued weakness in these two sectors reflects the severity of the financial crisis and the recession’s impact on the housing market and on government revenues. The pace of recovery has also differed across demographic groups. The Hispanic unemployment rate reached a peak of 13.1 percent twice, first in August 2009 and then again in November 2010. The unemployment rate for African Americans reached 16.7 percent in March 2010 and then again as recently as August 2011. The unemployment rates for Hispanics and African Americans as of January 2012 are well below their respective peaks—down 2.6 percentage points for Hispanics and 3.1 percentage points for African Americans—but still remain elevated. Trends in the labor force participation rate and in the employmentto-population ratio that pre-date the recession, and were exacerbated by the recession, are a continuing concern. After trending upward for most of the post-World-War-II period, largely because of increases in the fraction of women in the labor force, the participation rate has been in a secular decline since the late 1990s, driven by declining participation of Americans between the ages of 16 and 54, as well as by the aging of the workforce. These same developments have also lowered the employment-to-population ratio. The labor force participation rate fell further in the recession. As discussed in Chapter 2, many of those who have left the labor force since the beginning of the recession have enrolled in school. Extended unemployment insurance benefits have encouraged workers who lost their jobs through no fault of their own to keep searching for work, thereby maintaining a connection to the labor force. Helping more Americans get back to work more quickly remains the top priority of the Administration’s economic policy. That is why, in September 2011, President Obama proposed the American Jobs Act to support and speed up the ongoing recovery for American workers and their families. More recently, the President’s 2012 State of the Union Address and Fiscal Year 2013 Budget laid out a blueprint for an economy built to last on American manufacturing, American energy, skills for American workers, and American values. 166 | Chapter 6 The Dynamics of Labor Market Trends Underlying the changes in employment is a dynamic process through which firms are born and die, jobs are gained and lost, and workers transition in and out of employment and between jobs. These labor market dynamics have strong cyclical properties that have been very much at work during and since the recession, but secular trends are also changing the functioning of the U.S. labor market over the long run. Job Dynamics The job market is dynamic, with new firms entering and others exiting, and some growing and others contracting. The dynamic job market is supported by a safety net that helps to protect workers when job transitions do not occur smoothly and that gives entrepreneurs a backstop when they take risks with potentially high payoffs in future productivity. The importance of the many facets of the safety net is discussed in detail in Chapter 7. These job dynamics are characterized by gross flows of job gains and job losses across firms. Gross job gains are measured as jobs created in new and expanding firms, while gross job losses are measured as jobs that disappear in firms that are contracting or closing.1 Net job growth in a given period is the difference between gross job gains and gross job losses: where and NETt is the net number of jobs created by firms in the economy in period t; Gt is the amount of gross job gains in the period; Lt is the amount of gross job losses; i is a firm; C is the set of firms that are either new or have grown in period t; D is the set of firms that have either exited or contracted in period t; and N is the number of jobs. To calculate the rates of net job growth, gross job gains, and gross job losses, each of these values is divided by overall employment in the economy 1 Alternative measures of gross job gains and gross job losses use units of observation other than the firm, such as the establishment, generally a physical location of business activity where goods and services are produced. Using units smaller than firms leads to higher rates of gross gains and losses because jobs that flow across the units within a firm are counted in the gross measures. Jobs and Income: Today and Tomorrow | 167 averaged between one period and the next period. So, for example, the rate of gross job gains in period t is:2 Recent work by economists using the Business Dynamic Statistics (BDS) data at the U.S. Census Bureau demonstrates the tremendous dynamism of private-sector employment in the United States (Haltiwanger, Jarmin, and Miranda 2010; Haltiwanger 2011). Between 1980 and 2009 (the most recent year of BDS data), approximately 17 percent of all jobs in the private sector in an average year were added in that year at new or expanding firms; approximately 15 percent of jobs in an average year were gone by the next year because firms closed or contracted. While both large and small firms contribute to gross job gains and losses, small firms tend to gain and lose jobs disproportionately and to account disproportionately for net job growth. Recent research suggests that an important part of the explanation for the disproportionate amount of both gross job gains and gross job losses accounted for by small firms is that they tend to be young. Put differently, startups and other young firms drive the large rates of job gains and losses in small firms. Between 1980 and 2009, for example, 18.2 percent of overall gross job gains each year were in new firms—mostly small new firms—even though new firms accounted for only 3.1 percent of employment (Data Watch 6-1). These numbers make clear the importance and contribution of America’s entrepreneurs to the dynamism of the economy. The annual average rates of job gains and losses between 1980 and 2009 mask two important features of heterogeneity across time—secular, or long-term, trends, and cyclical patterns. The rates of both gross gains and gross losses have been declining over time. Whereas, on average, 18.2 percent of private-sector jobs in the 1980s were newly created positions in startups or expanding firms, gross job gains fell to 16.8 percent of total private-sector employment in the 1990s and to 15.8 percent between 2000 and 2009 (Figure 6-3). Similarly, gross job losses were slightly more than 16.2 percent of overall private-sector employment in the 1980s but fell to 14.9 percent in the 1990s and then remained largely the same between 2000 and 2009. These secular declines also are apparent when one focuses more narrowly on startups. Gross job gains from startups accounted, on average, 2 The data on U.S. firms capture gross flows over a 12-month period beginning and ending in March. So, for example, the rate of job gains in year t=2009 refers to information on jobs gained in firms between March 2008 and March 2009. 168 | Chapter 6 Data Watch 6-1: Measurement of Startups Research based on a new Census Bureau data set called the Longitudinal Business Database (LBD) has led to new discoveries about the important role that startups play in creating jobs. The LBD contains annual information on virtually the entire universe of U.S. nonfarm private businesses that paid Federal payroll and income taxes between 1976 and 2009, and it will continue to be updated as new data become available. LBD data are available both at the level of the firm—a measurement unit combining all of the economic activity of a business that occurs under common operational control—and at the level of individual establishments—physical locations of economic activity where goods and services are produced. The initial data are derived from quarterly Internal Revenue Service filings that are compiled by the Census Bureau and augmented with data collected through the Census Bureau Economic Censuses and business surveys. The final LBD data set contains annual information on payroll, employment size, industry, and other key economic variables for both firms and establishments. One of the key advances of the LBD is its ability to track the births and deaths of firms. When a new economic entity is reported in the administrative sources used to create the LBD, the Census Bureau determines whether that new economic entity is a new firm, a new establishment that is part of an existing firm, or an establishment that has undergone a change in legal form because of a merger, change in ownership, or some other similar change. Through this process, the Census Bureau is able to identify essentially all new private payroll startups. The creation of the LBD has allowed researchers to study comprehensively the process of private-sector job gains and losses. One of the most important findings has been how important startups are to the dynamism of the U.S. economy. For example, Haltiwanger, Jarmin, and Miranda (2010) find that about 2.5 million net new private-sector jobs were gained in 2005. Firm startups created nearly 3.5 million net new jobs in that year, while all other firms together lost about 1 million jobs on net. More information on the LBD is available from the Census Bureau at http://www.ces.census.gov/index.php/bds/bds_home. The Bureau of Labor Statistics has produced a separate database, the Business Employment Dynamics (BED), which tracks gross quarterly job gains and losses; more information about the BED is available at http://www.bls.gov/bdm. Jobs and Income: Today and Tomorrow | 169 Figure 6-3 BDS Estimates of Annual Gross Job Gain and Loss Rates, 1980–2009 Percent of total U.S. private-sector jobs 25 Gross jobs gained 20 15 Gross jobs lost 10 5 0 1980 1985 1990 Note: Shading denotes recession. Source: Census Bureau. 1995 2000 2005 2010 for 3.6 percent of the overall number of private-sector jobs in the 1980s but for only 2.7 percent between 2000 and 2009. The rates of gross job gains and losses exhibit not only secular declines but cyclical patterns as well. Gross job gains are procyclical, increasing in expansions and declining in recessions, whereas gross job losses are countercyclical, increasing during recessions and declining in expansions. In the depths of the recent recession, gross job losses rose sharply, but the decline in gross job gains was even more notable. An alternative data set produced by the Bureau of Labor Statistics (BLS) offers more frequent and more recent data than the BDS. The Business Employment Dynamics (BED) reports quarterly data on payroll employment at the level of the Employer Identification Number (EIN). An EIN is a tax-reporting construct rather than an economic construct, but the unit of observation in the BED consists in most cases of all of the operations of a particular firm located within a given U.S. state. Movements in gross job gains and losses in the BED on an annualized basis since its 1990 inception are broadly similar to those in the BDS; most important, the BED also shows a trend decline in gross gain and loss rates since 2000. The quarter-to-quarter movements shown in Figure 6-4, which are based on BED data through the second quarter of 2011 (the most recent quarter of data available), show a large increase in the rate of gross job losses toward the beginning of the recession; the rate reached a peak in the 170 | Chapter 6 Figure 6-4 BED Estimates of Quarterly Gross Job Gain and Loss Rates, 1990–2011 Percent of total U.S. private-sector jobs 14 12 10 Gross jobs gained 8 6 Gross jobs lost 2011:Q2 4 2 0 1990:Q1 1994:Q1 1998:Q1 2002:Q1 Note: Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. Source: 2006:Q1 2010:Q1 first quarter of 2009, and then returned to approximately the pre-recession trend by the beginning of 2010. The BED data also show a precipitous fall in the rate of gross job gains during the recession, and although that decline reversed and gross job gains exceeded gross job losses by the second quarter of 2010, the gains so far have resulted in too few new jobs to accommodate the large number of individuals who lost jobs in the 2007–09 recession. Now that researchers have documented the long-term secular slowdown in job gains and losses, the underlying reasons for the slowdown and its implications for the future of the U.S. economy are fast becoming the subject of an active debate. One possible reason for the slowdown in job reallocation is the aging of the population. Older workers may be less likely to become entrepreneurs, and research has documented a positive correlation between worker age and job tenure (Davis et al. 2007; Krueger 2010). But while the U.S. population is indeed aging, it is and will remain much younger than the population in the countries of Western Europe. So, to the extent that aging can explain part of the slowdown in job flows in the United States, other countries can be expected to experience slowdowns as well. Further research is needed to better understand the secular trends in job flows in the United States, and international comparisons could be helpful in this regard. Because of the importance of entrepreneurship to the vitality of the economy, the President last year launched Startup America, a national Jobs and Income: Today and Tomorrow | 171 campaign to improve the environment for high-growth entrepreneurs by expanding their access to capital and connecting them with mentors, helping the Nation’s veterans start businesses, reducing barriers to entrepreneurship, and fostering entrepreneurship in communities. Worker Flows The reallocation of jobs across firms is accompanied by the flows of individual workers between firms and in and out of employment. Overall, the net change in employment at a firm must by definition equal the difference between the firm’s hires and separations. But the rates of worker flows are larger than the rates of job reallocation: a firm may maintain stable employment (no gross job gains or losses) from one year to the next while having many individual workers come and go from within its employee ranks. On a monthly basis, flows of workers into firms (hires) and out of firms (separations) are large. As captured since December 2000 in the BLS Job Openings and Labor Turnover Survey, hires and separations have both averaged more than 4.7 million a month and have tended to track each other closely over time. As Figure 6-5 illustrates, firm hires and separations before the start of the recession in 2007 were notably below the levels observed before the start of the 2001 recession. Figure 6-5 Hires and Separations, 2001–2011 Thousands 6,000 5,500 5,000 Separations 4,500 Nov-11 Hires 4,000 3,500 3,000 Jan-2001 Jan-2003 Jan-2005 Jan-2007 Note: Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. 172 | Chapter 6 Jan-2009 Jan-2011 As the U.S. economy fell into recession in December 2007, worker flows slowed notably, with large monthly declines in the number of separations, and even more precipitous monthly declines in the number of hires. A decline in separations during a recession may seem counterintuitive, but it is attributable to a large decline in the frequency of workers quitting their jobs; quits are usually a sign of workers leaving jobs voluntarily for better opportunities. So while layoffs were increasing over this period, the decline in quits swamped the increase in layoffs. Overall, the economy on net was shedding jobs at a very fast pace during the recession because the decline in hiring in absolute numbers was larger than the decline in separations. Hires and separations both began to rise in the second quarter of 2010, but both remained below pre-recession levels at the end of 2011. One can also study flows of workers into and out of employment, unemployment, and the labor force. Perhaps most important over time are the flows into and out of unemployment, which can be calculated using the Current Population Survey (CPS). Because of the structure of the CPS, in any given month three-quarters of the sample members have also been interviewed in the previous month, making it possible to use these repeat respondents to follow transitions into and out of unemployment. The BLS has been constructing these flows each month since 1990 in a manner that also matches up with the level of reported unemployment. Figure 6-6 Figure 6-6 Flows into and out of Unemployment as Percent of the Labor Force, 1990–2012 Percent 4.0 Inflow rate 3.5 Outflow rate Jan-12 3.0 2.5 2.0 1.5 Feb-1990 Feb-1994 Feb-1998 Feb-2002 Feb-2006 Note: Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. Feb-2010 Jobs and Income: Today and Tomorrow | 173 displays the extent of inflows and outflows as a percent of the total labor force for each month from the start of 1990 through January 2012. Although the BLS labor force flow series goes back only to 1990 and is dominated by strong cyclical movements, the data in Figure 6-6 through the end of 2007 suggest a secular decline in both the inflow and outflow rate. A similar decline has also been documented elsewhere (see, for example, Davis, Faberman, and Haltiwanger 2006) for years before 1990, using alternative methods of calculating unemployment inflows and outflows. As with job flows, the aging of the population may account for some of these secular declines, because older workers tend to leave jobs less often than younger workers and, when they do, are more likely to leave the labor force permanently. But the declining flows into and out of unemployment also may reflect other forces that have lowered the rates of gross job gains and losses over the past three decades. As the recession began, monthly inflows and outflows from unemployment both stood at approximately 2.4 percent of the labor force. Both began to rise steeply, but the inflow rate rose more quickly than the outflow rate, increasing the unemployment rate to levels not seen in approximately 30 years. Put differently, both the increase in the monthly average probability of a worker entering unemployment and the decrease in the monthly average probability of an unemployed worker exiting unemployment have, as in a typical recession, contributed to the observed rise in unemployment (Elsby, Michaels, and Solon 2009). Since March 2009, unemployment inflow and outflow rates, measured as a share of the labor force, each have been over 3 percent. Because the outflow rate was notably higher than the inflow rate near the end of 2011, the unemployment rate has fallen. The labor market is still recovering from the cyclical impacts of the recession. And it is still subject to the long-term slower trend in gross job gains and losses, as well as to the long-term decline in the share of the population that is employed. In the face of these trends, the Administration has pursued and continues to pursue robust policies to foster faster job creation in the short run, as well as an economic environment in which existing firms have reasons to increase employment, new firms are able to grow and innovate, and workers can find satisfying employment. Earnings and Income Mobility over the Career and between Generations Although the Nation’s labor market is highly dynamic in terms of worker flows, the United States has had low rates of income mobility for decades, both across the career and across generations. 174 | Chapter 6 Low rates of income mobility across the career are especially notable for men, whose higher rates of labor force attachment make them much less likely than women to have years with zero earnings. Kopczuk, Saez, and Song (2010) show that the annual earnings of a man averaged across 11 years early in his working career are highly predictive of his annual earnings averaged across 11 years later in his working career. For example, a man in one of the bottom two quintiles of the income distribution early in his lifetime has less than a 10 percent chance of rising to the top quintile 20 years later. Family (or individual) incomes in one generation are also highly correlated with family (or individual) incomes in the next generation. In other words, the children of parents who are poor are more likely than the children of well-off parents to be poor when they grow up. A common measure of mobility across generations is the intergenerational elasticity (IGE) of earnings or income, which is defined as the percentage difference in a child’s income associated with a 1 percent difference in the parent’s income.3 These IGE estimates are sensitive to several measurement issues, particularly fluctuations in incomes from year to year. Studies based on U.S. data that deal appropriately with these measurement issues suggest that plausible estimates of the average IGE between fathers and sons are between 0.4 and 0.6. An IGE of 0.4 means that if one father earned 20 percent more than another over their lifetime, the first father’s son on average would earn 8 percent more than the second father’s son; an IGE of 0.6 means that the first father’s son would earn 12 percent more on average than the second father’s son. That is, the higher the IGE is, the lower economic mobility is between the generations. Data limitations make it difficult to infer whether the IGE or the correlation between parents’ and children’s income has changed significantly over time (Data Watch 6-2). Lee and Solon (2009) conclude that the IGE in the United States was fairly stable for cohorts born between 1952 and 1975, while Aaronson and Mazumder (2008) present evidence suggesting that it has increased in the past 30 years, implying that intergenerational mobility has fallen. None of the available research has suggested a decline in the IGE over time. Moreover, the widening of income inequality has meant that it is harder for someone born into the bottom to move to the middle or the top of the income distribution. The high degree of persistence in incomes between generations in the United States is especially noteworthy in the context of cross-country comparisons. Corak (2011) makes such a comparison and finds that the average 3 IGEs most commonly have been estimated as the regression coefficient resulting from a linear regression of the logarithm of the income (or earnings) of a child on a measure of the logarithm of income (or earnings) of a parent or family. Jobs and Income: Today and Tomorrow | 175 Data Watch 6-2: Intergenerational Mobility One measure of opportunity is the extent to which children grow up to live in better economic and social circumstances than their parents. While there has been useful research on this topic, data limitations have hampered attempts of economists and other social scientists to measure the extent of intergenerational mobility. Researchers interested in intergenerational mobility in the United States most commonly have used one of two nationally representative surveys to assess the relationships between the income and occupations of children and those of their parents—the Panel Study of Income Dynamics or the National Longitudinal Survey. Neither of these surveys was designed specifically to address questions concerning intergenerational mobility, however, and the lack of precision resulting from the relatively small numbers of people surveyed makes it difficult to discern trends in economic mobility. Grusky and Cumberworth (2010) have suggested that, if organized into an administrative database with strict confidentiality protections, information gleaned from U.S. tax records could allow researchers to gain a much fuller picture of the evolution of earnings and career outcomes between generations. Mazumder (2005) has taken a step in this direction, using data from the Survey of Income and Program Participation linked to Social Security earnings records to study the relationship between parents’ earnings and the later earnings of their adult sons. He finds that the intergenerational elasticity of earnings is around 0.6, which is larger than had been found in previous studies, probably because he had access to more accurate earnings histories. estimated IGE of 0.47 for men in the United States, while lower than the IGE for countries such as the United Kingdom (0.50) and South Africa (0.69), is much higher than the IGE for men in countries such as Sweden (0.27), Norway (0.17), Finland (0.18), and Denmark (0.15). Jäntti et al. (2006) also compare IGEs for men’s incomes in some of the same countries and report similar estimates.4 While many factors contribute to cross-country differences in intergenerational mobility, one clear pattern is that countries with more intergenerational mobility also tend to have lower point-in-time income inequality. Figure 6-7 plots the relationship across 13 industrialized countries between the IGE of the earnings of fathers and sons as reported in Corak (2011) 4 One exception is that Jäntti et al. report a somewhat lower IGE (0.31) for the United Kingdom, below that of the United States but still well above those in Nordic countries. Following the literature, this discussion focuses on IGEs for men, because in many countries the inconsistent labor force participation of women complicates the estimation of their IGEs. 176 | Chapter 6 and the Gini coefficient of after-tax 1985 income as reported in the OECD statistical database. The Gini coefficient, shown along the horizontal axis of the figure, is a common measure of income inequality; higher values mean higher levels of income inequality. Higher IGEs along the vertical axis mean less intergenerational mobility. The United States appears in the upper right part of Figure 6-7, indicating both high inequality and low intergenerational mobility. As other research has shown, the finding of a positive relationship between IGE and inequality—a relationship that Krueger (2012) has referred to as “the Great Gatsby Curve”—is robust to alternative choices of countries, intergenerational mobility measures, and year in which income inequality is measured (see, for example, Corak 2011; Andrews and Leigh 2009; OECD 2010). This robust relationship suggests that at least some of the same mechanisms that drive income inequality also drive intergenerational mobility. For example, a rise in the rate of return to schooling can be expected to lead to both a rise in point-in-time income inequality and a decline in intergenerational mobility because educational attainment is positively correlated across generations. The educational system also may contribute to the pattern in Figure 6-7. Research has found a strong negative correlation between spending on public education and IGEs across countries (Ichino, Karabarounis, and Figure 6-7 The Great Gatsby Curve: Inequality and Intergenerational Mobility Intergenerational earnings elasticity 0.6 Italy 0.5 United Kingdom United States France 0.4 Spain Germany 0.3 Finland 0.1 0.15 New Zealand Sweden 0.2 Japan Norway Canada Denmark 0.2 0.25 0.3 Gini coefficient (1985) 0.35 0.4 Source: Corak (2011) and OECD. Jobs and Income: Today and Tomorrow | 177 Moretti 2011). This pattern suggests that public investments in supporting children may help to reduce persistent inequality across generations. Similarly, the OECD has concluded that educational policies ranging from support for early childhood education to measures that support postsecondary education for students from low-income backgrounds can increase intergenerational income mobility (OECD 2010). As discussed later in this chapter, the Administration has taken multiple steps to improve the quality of education and to provide opportunities for all students to earn a postsecondary credential or degree. Overall Trends in Income and Rising Inequality Irrespective of the persistence in income across generations, the rungs on the ladder of the income distribution in the United States have moved farther apart, and income growth has been stagnant for the middle class for a decade. One indicator of the evolution of income over time is annual real median household income, which rose in the United States from the late 1960s through the late 1990s, was stagnant in the first part of the 2000s, and then, as is typical during recessions and their aftermath, fell between 2007 and 2010 (the last year for which data are available). Figure 6-8 Percent of Households with Annual Income within 50 Percent of the Median Percent 52 50.3 50 47.3 48 45.6 46 44.2 44 42.2 42 40 38 1970 1980 1990 2000 Source: Department of Labor, Bureau of Labor Statistics; CEA calculations. 178 | Chapter 6 2010 Figure 6-9 Growth in Real After-Tax Income, 1979–2007 Percent change 300 278 250 200 150 100 65 50 0 18 Lowest quintile 35 28 Second quintile Middle quintile 43 Fourth quintile 81st-99th Top 1 percent percentiles Source: Congressional Budget Office. Rising income inequality is another major development in the United States economy (see, for example, Autor, Katz, and Kearney 2008; Card and DiNardo 2002; CEA 1997). Growing dispersion of household incomes, a manifestation of growing dispersion of earnings, means that fewer and fewer households have incomes in the middle band of the income distribution. This can be seen clearly in Figure 6-8. In 1970, just over 50 percent of households had incomes within 50 percent of the median; that share fell to just over 44 percent in 2000 and to just over 42 percent in 2010. Another way to look at changes in the distribution of income is to examine the rates of income growth for households at different income levels. A report released by the Congressional Budget Office (CBO) in October 2011 examines real growth in after-tax (and transfer) household income from 1979 through 2007 across quintiles and the top 1 percent of the income distribution. Figure 6-9, reproducing information from the CBO report, provides stark evidence of the rise in inequality, showing that real after-tax incomes grew by just 18 percent over nearly 30 years for those in the bottom income quintile and rose only somewhat more rapidly for those in the middle 60 percent of the distribution, but grew by a stunning 278 percent for those in the top 1 percent of the distribution. As a result of these divergent growth rates, increasingly more income has been concentrated at the top and less at the bottom of the income distribution. The CBO reports that the share of total after-tax household income Jobs and Income: Today and Tomorrow | 179 for the bottom four income quintiles was lower in 2007 than it was in 1979, and the share for those in the 81st to 99th percentiles was essentially flat. For the top 1 percent, however, the share more than doubled, from almost 8 percent in 1979 to 17 percent in 2007. Piketty and Saez (2003, 2010), using data and definitions of income slightly different from the CBO report, focus on income inequality between those at various places in the very top of the distribution and the rest of the population. They find that the share of income prior to taxes and transfers excluding capital gains going to the earners in the 90–95th percentile of the distribution barely changed between 1979 and 2010 and that the share of income going to those in the 95–99th percentiles rose from almost 13 percent to about 16 percent. But the share of income going to the top 1 percent of earners rose from 8 percent in 1979 to 18 percent in 2007, the highest it had been since the Roaring Twenties, and it still stood at over 17 percent in 2010 (Figure 6-10). Rising inequality has important implications in the context of low rates of intergenerational mobility. As incomes become more unequal, larger increases in household income are necessary for families to move from a lower part of the income distribution to a higher part—for example, from a level of household income that classifies a family as living in poverty to one that puts it in the middle of the distribution. Low rates of economic Figure 6-10 Share of Total U.S. Income Earned by Top 1 Percent, 1913–2010 Percent of total U.S. income 20 18 16 14 12 10 8 6 1913 1923 1933 1943 1953 1963 1973 1983 1993 2003 Note: Total income includes wages and salaries (including bonuses and stock -option exercises), pensions, profits, farm income, dividends, interest, and rental income. Source: Piketty and Saez (2003, 2010); authors provided an estimate for 2010 based on partial returns. 180 | Chapter 6 mobility across generations imply that children born in poverty are more likely to remain in poverty as adults, while children born to higher-income parents are more likely to have higher incomes as adults. As long as income inequality is increasing, those adult children will find themselves even farther away from the middle class than their parents were. Perhaps even more worrisome, the Great Gatsby curve in Figure 6-7 suggests that a rise in inequality for the current generation of families could lead to a slowdown in economic mobility for the next generation. The confluence of rising inequality and low economic mobility over the past three decades poses a real threat to the future of the United States as a land of opportunity. Social and economic mobility across generations are at risk of declining unless concerted efforts are devoted to providing more opportunities for those born into lower-income households. Long-Term Unemployment The upheaval in the labor market brought on by the recession that started in late 2007 is primarily a cyclical phenomenon. A major challenge, especially given the long-term changes in the labor market that were underway even before the recession, is how to prevent these cyclical dislocations from having permanent effects on workers’ prospects. This means that pathways for the long-term unemployed to return to the workforce are a particular priority The protracted high level of unemployment has led to large numbers of long-term unemployed workers—those who have been out of work for more than 26 weeks. Currently, 5.5 million workers—more than two-fifths of all unemployed individuals—have been jobless for more than 26 weeks, and over 1.8 million have been without a job for more than two years. Historically, as depicted in Figure 6-11, the share of the unemployed that has been unemployed for more than 26 weeks has been quite cyclical, starting at a relatively low point right before a recession, growing thereafter, and usually peaking many months into the recovery before gradually declining. Another useful measure of unemployment duration is the median duration—the amount of time that the person in the middle of the distribution has spent unemployed to date. Typically, this measure has been similarly cyclical, and as a result of the 2007–09 recession it remains elevated at 21.1 weeks. A long period of joblessness is obviously first and foremost a serious hardship for the individuals involved. The loss of income due to unemployment can wreak havoc on households’ finances, often necessitating liquidation of savings. Households with unemployed members are more likely to fall behind on their bills and to suffer foreclosure or bankruptcy; foreclosures Jobs and Income: Today and Tomorrow | 181 Figure 6-11 Median Duration of Unemployment and Long-Term Unemployed as a Percent of Total Unemployed, 1980 –2012 Percent 50 Jan-12 Weeks 30 25 40 Long-term unemployed as a percent of total unemployed (left axis) 30 20 15 20 10 10 5 Median duration of unemployment (right axis) 0 Jan-1980 Jan-1985 Jan-1990 Jan-1995 Jan-2000 Note: Shading denotes recession. Source: Department of Labor, Bureau of Labor Statistics. Jan-2005 Jan-2010 0 also can have adverse effects on the prices of neighboring homes. To help the long-term unemployed keep their homes, the Administration created a version of the Home Affordable Modification Program (HAMP) for the unemployed, called HAMP UP, in which unemployed homeowners were given a three month forbearance period on their mortgage payments. In July 2011, this forbearance period was extended to 12 months. Income losses associated with job loss can persist even after reemployment. Recent research examined male workers age 50 or younger with at least three years of tenure who lost their jobs in mass layoffs (defined as employment decreases of at least 30 percent over two years at their place of employment) between 1980 and 2005. The researchers concluded that job displacement led to a loss of 1.7 years of earnings, on average, accumulated over 20 years. Moreover, job displacement led to an average accumulated earnings loss of 2.8 years if the job was lost when the unemployment rate was above 8 percent, but the earnings loss was only half as large—1.4 years—if the job was lost when the unemployment rate was below 6 percent (Davis and von Wachter 2011). In addition to the mortgage forbearance program mentioned above, the Administration has supported the long-term unemployed by calling for extended unemployment compensation, which provides much-needed income to these workers and their families while the recipient searches for work. As explained in Chapter 7, continued extensions of the Emergency 182 | Chapter 6 Unemployment Compensation and Extended Benefits programs through 2012 are vital to those who remain unemployed. Additionally, the American Jobs Act proposal for extending unemployment benefits also included significant reforms to the unemployment insurance system designed to speed the return of benefit recipients to work. As part of his Fiscal Year 2013 Budget, the President is proposing a $12.5 billion Pathways Back to Work Fund to provide employment opportunities for vulnerable youth, low-income adults, and the long-term unemployed, and an expanded community college initiative to support state and community college partnerships with business to give workers the skills employers need. The President also is proposing to streamline training and employment services for dislocated workers, improving access to critical supports for getting the unemployed back into employment. Preparing for Tomorrow’s Labor Market Even as the Administration remains focused on strengthening and sustaining the recovery from the recession, the President continues to address the longer-term challenges in the structure of the American economy and labor market. To ensure that American workers are prepared to meet the evolving needs of employers, the Nation’s education and training system must provide the workers of tomorrow with the skills they will need for the jobs of tomorrow. At the same time, jobs and workplaces also must evolve to enable workers to fulfill family and other nonwork responsibilities (Box 6-1). This section describes what the jobs of tomorrow are likely to look like, why educating workers is a cornerstone of economic opportunity and growth, and how the Administration’s policies are working to prepare Americans for the jobs of tomorrow. Education and the Workers of Tomorrow The rise in wage and income inequality over recent decades is largely attributable to long-lasting structural changes in the U.S. economy. Among the changes are technological advances that have increased employer demand for a relatively more highly educated workforce, a slowdown in the expansion of educational attainment, and increased competition from overseas for many lower-paid jobs. Another is a decline in the share of the workforce covered by collective bargaining agreements and the decline in the real value of the minimum wage, both of which historically helped protect the wages of lower-paid workers.5 5 Extensive reviews of existing research can be found in Acemoglu and Autor (2011) and Autor and Katz (1999). Jobs and Income: Today and Tomorrow | 183 Box 6-1: Work-Life Balance in the Jobs of Tomorrow American household life has changed dramatically over the past half century in ways that have caused many workers to face conflicts between their work and personal lives. Women are now the majority recipients of bachelor’s and advanced degrees and compose nearly 50 percent of the workforce. Families rely increasingly on women’s earnings to make ends meet. In addition to managing care of children, both men and women juggle elder caregiving responsibilities with work. In 2008, approximately 43.5 million Americans served as unpaid caregivers to a family member over the age of 50. Workplace flexibility is also important for older Americans themselves. In 2011, the first of the baby boomers turned age 65. Workplace flexibility policies, such as part-time work or job sharing, facilitate a phased retirement that helps older workers transition slowly out of the workforce, allowing them to take care of their health needs and maintain their economic security while moving toward retirement. Workplace flexibility can be expanded by increasing workers’ control over when, where, and how much they work. These goals can be achieved through a variety of different arrangements that allow workers to continue making productive contributions to the workforce while also attending to family and other responsibilities. Arrangements range from job sharing, to phased retirement of older workers, to telecommuting. Workplace flexibility policies not only help employees balance work and family responsibilities but also can improve employers’ bottom lines. As in all business decisions, the critical considerations for employers in adoption of flexible workplace policies are the benefits and costs. Almost one-third of firms cite costs or limited funds as obstacles to implementing workplace flexibility arrangements. On the benefit side, however, as documented in CEA (2010), these practices can reduce turnover and improve recruitment, increasing the productivity of an employer’s workforce. Moreover, flexible workplace practices are associated with improved employee health and decreased absenteeism, a major cost for employers. The CEA study estimated that wholesale adoption of flexible workplace policies could save as much as $15 billion a year through greater productivity, lower turnover, and reduced absenteeism. Should more firms adopt such practices, the benefits to society, in the form of reduced traffic, improved employment outcomes, and more efficient allocation of workers to employers, could be even greater than the gains to individual firms and workers (Galinsky et al. 2011). Although the academic literature has identified numerous benefits from flexible workplace practices, along a variety of dimensions, the 184 | Chapter 6 adoption rates for these practices differ across industries and employers of different sizes. Goldin and Katz (2011) explored the prevalence of flexible workplace arrangements across industries and found that, although these practices are gaining in popularity, some industries lag behind, in particular the business and financial sectors. Overall, the CEA study reported that more than half of employers report allowing some workers to periodically change their starting and quitting times. However, only 28 percent of full-time workers and 39 percent of parttime workers report actually having flexible work hours. Even if some employers offer more flexible workplace arrangements, there remains the concern that their employees may not be taking advantage of those arrangements because either, in the case of unpaid leave, they cannot afford to bring home a smaller paycheck, or, in the case of paid leave, they are afraid to take leave for fear of missing out on advancements or not being viewed as a “team player.” A lack of data has hindered deeper understanding of the benefits and costs of flexibility, as well as knowledge about who is taking advantage of that flexibility. The largest, most detailed source of data, a survey of employers, provides information on practices that is now three years old and does not contain information for the smallest firms. The only nationally representative data from workers are seven years old and provide little information on the prevalence of flexible practices. While the existing evidence has demonstrated a strong connection between flexibility and productivity, additional research exploring the mechanism through which flexibility influences worker’s job satisfaction and firms’ profits would better inform policymakers and managers alike. In the summer of 2012, the results of a module added to the American Time Use Survey will provide expanded information about workplace flexibility from the workers’ perspective. The module asks survey respondents about their access to leave and flexible scheduling, how they use such policies to balance their work and personal responsibilities, and whether they fail to take advantage of existing policies because of a fear of negative consequences. These data will add to the existing knowledge base on workplace flexibility. Although the literature is small, the best available evidence suggests that adoption of more flexible practices can boost productivity, improve morale, and benefit the U.S. economy—all while strengthening families. Jobs and Income: Today and Tomorrow | 185 Because these structural changes have shifted demand toward a workforce with relatively more education, a substantial fraction of the overall increase in wage and income inequality is related to a growing divergence in earnings between those with more years of education and those with fewer years of education, as depicted in Figure 6-12. For example, in 2010, workers with a bachelor’s degree or higher earned nearly twice as much as those with a high school degree, a premium that has risen since 1980, when college graduates earned 45 percent more than high school graduates. In fact, even long before the most recent recession, the average real annual earnings of those with a high school degree or less fell below the levels of the 1970s. One important way to help stem the tide of rising inequality, and potentially to ameliorate the effects of low intergenerational economic mobility, is to increase the number of workers who obtain postsecondary education and earn higher wages as a result. For this reason, President Obama has set the ambitious goal of returning the United States, by 2020, to the world’s top spot in the share of 25- to 34-year-olds with a college degree. Increasing the number of workers who obtain postsecondary education is also vital for meeting the changing skill needs of firms. The BLS Employment Projections Program produces forecasts of employment by industry, occupation, and education on an approximately biennial basis. The industry employment forecasts are based on incorporating projections of the size of the labor force into a model of output growth across U.S. industries. These detailed industry employment forecasts are then mapped into projections of employment growth by occupation, and then into forecasts of growth in employment by education group. Beginning with the newly released projections for 2010–20, the BLS is projecting employment growth by education group by assigning to each occupation the typical level of formal education needed to enter the occupation, and then aggregating by education group the projected employment growth in the occupations requiring that level of education. As shown in Figure 6-13, the BLS projects that in the coming years, jobs requiring education beyond a high school degree will grow by more than the average, while occupations requiring at most a high school diploma will grow by less than the average. For example, between 2010 and 2020, employment in jobs that require an associate’s degree is projected to grow by 18.0 percent, 3.7 percentage points more than the average projected employment growth of 14.3 percent. Much of the divergence in employment growth across education groups is driven by the projected growth of sectors such as health care and education that intensively utilize workers in occupations that typically require education beyond a high school diploma. 186 | Chapter 6 Figure 6-12 Average Annual Earnings by Worker Education Level, 1963–2010 Dollars (2010) 80,000 Bachelor's degree or higher 70,000 60,000 Associate's degree or some college 50,000 High school degree 40,000 Less than high school 30,000 20,000 1963 1972 1981 1990 1999 2008 Note: The sample includes workers aged 25–65 who worked at least 35 hours a week and for at least 50 weeks in the calendar year. Before 1992, education groups are defined based on the highest grade of school or year of college completed. Beginning in 1992, groups are defined based on the highest degree or diploma earned. Earnings are deflated using the CPI-U. Calculations are based on survey data collected in March of each year and reflect average wage and salary income for the previous calendar year. Source: CEA calculations using March Current Population Survey Information that tracks the changing skill needs of firms can help Americans make informed career decisions. In addition to the statistics published by the BLS on existing and projected jobs by industry, occupation, and education, the potential exists to harness new data sources to gain a deeper understanding of what skills are in high demand. For example, the more than 50 million U.S.-based members of LinkedIn, an online professional networking company, typically provide to LinkedIn their job titles and the companies they work for, and upon joining, many members also provide information on their past work history. LinkedIn classifies members’ jobs by industry and occupation, often at a more detailed level than is available in government statistics. The resulting information can be used to track changes over time in the industries and occupations in which LinkedIn’s members work and to identify emerging sectors and job titles. LinkedIn’s members are not a nationally representative sample of the U.S. workforce, but because they tend to work in sectors of the economy that require higher levels of education, the information embodied in the changing distribution of the industries and occupations in which members are employed has the potential to inform the decisions of individuals considering specific educational and career paths. Jobs and Income: Today and Tomorrow | 187 Figure 6-13 Difference Between Projected Employment Growth Rate by Education and Average Projected Employment Growth Rate, 2010-2020 Doctoral or professional degree 5.6 Master's degree 7.4 Bachelor's degree 2.2 Associate's degree 3.7 Postsecondary non-degree award 2.6 Some college, no degree High school diploma or equivalent 3.2 -2.1 Less than high school -0.2 -10 -5 0 5 Percent change minus average percent change 10 Source: Department of Labor, Bureau of Labor Statistics. LinkedIn has produced initial tabulations from among its U.S. members of the growth rate of employment in industries and occupations since 2007. These tabulations are for a longitudinal sample of individuals, based on aggregated historical data from their resumes and other information that they provide, LinkedIn reports that two of the fastest-growing industries among their members between 2007 and 2011 were the Internet and oil and energy; two of the fastest-shrinking industries were newspapers and construction. Among the fastest-growing occupations were social media (including jobs titles such as social media manager, social media marketing manager, and social media specialist) and digital technology (including digital producer, digital product manager, digital strategist, and digital sales manager); LinkedIn reports that teachers and middle-management positions were among the shrinking occupations. One of the main drivers of the increasing relative demand for workers with more education and training is the continuing shift toward using machines or computers to perform the routine tasks once done by workers. Although the BLS, assuming a continuation of these trends, projects that the number of manufacturing jobs will decline between 2010 and 2020, the U.S. manufacturing sector has added more than 400,000 net new jobs since the beginning of 2010, the first sustained job growth in manufacturing since the late 1990s. 188 | Chapter 6 Some of the recent growth in manufacturing jobs is the direct result of firms that are choosing to produce goods in the United States rather than using overseas labor. The Administration is supporting this “insourcing” with new tax proposals that eliminate tax advantages for moving jobs overseas and reward companies that choose to invest in or bring jobs back to the United States. In addition, the President has proposed measures to revitalize the manufacturing sector. These measures include initiatives to help develop and produce advanced technologies, ensuring clean energy technologies that will fuel the 21st century economy are built in the United States; funding to help catalyze partnerships between universities and industries to develop new technologies for manufacturing products and processes; the creation of a new Interagency Trade Enforcement Center to challenge unfair trading practices; and tax incentives to promote job growth in communities hard-hit by factory closings. Increasing Educational Attainment To prepare for the jobs of tomorrow, it is essential to invest in the American workforce and to increase the number of young people who attain a college degree. Meeting the President’s college completion goal for 25- to 34-year-olds requires investments in early, primary, and secondary education to increase the number of students who are college-ready when they graduate from high school. Meeting the goal also requires policies and programs that make college more affordable and accessible. Teachers in the Nation’s public schools are crucial to preparing children for the jobs of tomorrow. During the depths of the recession, however, many State and local governments were forced to make cuts, resulting in the loss of more than 200,000 education jobs over the past three years. Had it not been for the combined $40 billion in targeted assistance through the Recovery Act’s State Fiscal Stabilization Fund and the Education Jobs Fund, the cuts would have been worse: these programs provided the resources to support 420,000 teacher job-years. Given the continued need to prevent teacher layoffs and to rehire many of the teachers who lost their jobs during the recession, the President’s FY 2013 Budget proposes a $25 billion teacher stabilization fund. The Administration also has made improving the quality of education a priority and has taken an innovative approach, using grant competitions and evaluations to fund promising practices and learn more about what works, from early childhood education through high school. A key part of this effort has been Race to the Top grants, established as part of the Recovery Act. Competitive grants have been awarded to states to undertake innovative reform in four areas of K–12 education: implementing rigorous Jobs and Income: Today and Tomorrow | 189 standards and assessments; using data to improve instruction and decisionmaking; recruiting and retaining effective teachers and principals; and turning around the lowest-performing schools. Race to the Top grants have catalyzed widespread reform even in states that did not win an award. In 2011, Race to the Top funds were also used for Early Learning Challenge grants to promote evidence-based evaluation of programs, develop strategies for families and parents to assess the quality of early learning programs, and create age-appropriate curricula and assessment systems. The Early Learning Challenge fund announced nine state grant winners in December 2011. As with the K–12 Race to the Top competition, although not all proposals were funded, the framework of providing competitive grants to states to formulate their own solutions focused local conversations on education reform. The Early Learning Challenge grants complement the Administration’s major investments in improving a cornerstone of early childhood education, the Head Start and Early Head Start programs, by increasing funding by $2.1 billion in two years through the Recovery Act, by nearly doubling the number of children and families served by Early Head Start, and by taking key steps to increase Head Start Center program quality and accountability. Notably, the Department of Health and Human Services has begun implementing new regulations that, for the first time, require current grantees that do not meet quality benchmarks to compete for continued funding. In addition to Race to the Top, the Administration has funded other important innovations in education. The Investing in Innovation Fund supports projects in K–12 education that test, validate, and scale up promising strategies and interventions that raise overall student achievement, close the achievement gap, and improve outcomes for high-need students. The Promise Neighborhoods initiative supports cradle-to-career wraparound services to improve educational outcomes for students in distressed highpoverty neighborhoods. The President’s 2012 State of the Union Address challenged all states to do what 21 states have already done: require all students to graduate from high school or stay in school until age 18. Raising the compulsory schooling age increases average educational attainment and, for those induced to stay in school longer, leads to higher earnings when those students become adults. In view of the positive externalities from schooling, economists Milton and Rose Friedman wrote, “What kind of governmental action is justified…? The most obvious is to require that each child receive a minimum amount of schooling of a specified kind” (Friedman and Friedman 1962). The President has committed to continued investments in America’s education system. Beyond making investments to help all students prepare 190 | Chapter 6 for college, the Administration is working to make college affordable for American families. In recent years, published college tuitions have risen sharply, posing a threat to the Nation’s growing need for workers with college-level skills. The Administration has made college accessibility and affordability a top priority. Through the Recovery Act and the Health Care and Education Reconciliation Act passed in 2010, the Administration raised the maximum Pell Grant award from $4,731 in 2008 to $5,550 in 2010, and the FY 2013 Budget calls for the maximum to increase to $5,635 for the 2013–14 school year. Some 8.1 million college students received an average of $3,700 in Pell Grants in 2009–10. These figures are up sharply from the year before President Obama took office, when 5.5 million college students received an average of $2,650 apiece in Pell aid, and the President remains committed to protecting these historic increases in Pell Grant awards. In addition, the American Opportunity Tax Credit (AOTC), established through the Recovery Act, provides up to $2,500 a year for college tuition and related expenses for American families. Compared with the Hope Scholarship that it largely replaces, the AOTC offers a higher maximum benefit; can be claimed for up to four, rather than only two, years of undergraduate education; has a higher income eligibility cutoff, making the credit available to more middle-class families; and is partially refundable, thereby also reaching lower-income families. This credit is estimated to have benefited 9.4 million students and their families in 2011. In December 2010, the President signed an extension of the AOTC through the end of 2012, and his FY 2013 Budget request proposes to make the AOTC permanent. Data from the College Board (2011) demonstrate the effectiveness of these Administration initiatives to keep college affordable (see also CEA 2011). The estimated average net price for full-time students attending public four-year institutions increased by only about $60 between 2007–08 and 2011–12, and the estimated average net price for full-time students attending public two-year and private nonprofit four-year institutions actually fell. To build on the successes of Pell expansions and the AOTC as well as lessons from K–12 education reform, the President has proposed a Race to the Top for College Completion and Affordability to make public colleges more affordable and a better value and to drive reforms that will help more students complete their degrees on time. The FY 2013 Budget also proposes reforms to the distribution of campus based-aid to reward colleges that are serving low-income students, setting tuitions responsibly, and offering a quality education that prepares students to obtain employment and repay their loans. Finally, the Budget proposes a new First in the World Fund that introduces an evidence-based framework, modeled after the Investing in Innovation initiative, to develop, validate, and scale up effective approaches Jobs and Income: Today and Tomorrow | 191 in higher education. (For a discussion of financing the cost of college, see Economics Applications Box 6-1.) Federally Supported Job Training The education of workers does not end when they complete formal schooling and enter the labor market. As the economy evolves, workers often need to develop new skills to meet the changing demands of firms. In many cases, firms partner with their workers to help them acquire new skills, but for workers who have lost their jobs or are seeking to change fields or careers, this option may not be available. Providing such workers with opportunities for training is especially important in today’s economy given the continued high rates of unemployment that are the direct result of the recession, and it will remain important in ensuring a skilled workforce well into the future. The Federal Government funds two main training programs for adults—the Trade Adjustment Assistance (TAA) program and the Workforce Investment Act (WIA) formula grant program. The WIA Adult and Dislocated Programs have by far the largest reach, serving 8.6 million participants in 2010 (the most recent year for which data are available) at a total annual cost of $3.8 billion.6 Created in 1998, the WIA system provides reemployment and training services to adults who are economically disadvantaged and to workers who have been displaced from their jobs. Importantly, WIA moved the design and management of job training programs to the local level by creating “one-stop” employment centers where job seekers can access all employment services of the Department of Labor. WIA provides both short-term services, including job search assistance and basic skills assessments, and longer-term services that involve more substantial career counseling as well as training services. Program participants work with a case worker to choose the menu of services that best meets their needs, although limited funds mean not all participants have access to all services deemed appropriate. Research suggests that the average WIA participant benefits from the program, although the quality of the services provided is somewhat uneven. One recent study found that, on average, WIA training programs for adults boosted employment and earnings, although there was substantial variation across states and across participants depending on which WIA program they were in and what kind of services they received (Heinrich, Mueser, and Troske 2008). Growing evidence from studies of state programs, particularly studies that track participants for a longer 6 Other smaller programs serving many fewer participants include the Employment Services Program and the Adult Basic Education Program. In addition, WIA also has a small program that serves economically disadvantaged youth. 192 | Chapter 6 Economics Application Box 6-1: Calculating the Cost of College The decision to attend college is one of life’s most important decisions. Individuals with a college degree earn substantially more throughout their working lives than otherwise similar non-degree holders, on average, but the dollar costs of college can be high and many students accumulate substantial debt. In addition, there is an “opportunity cost” of college—students are unable to work for pay while performing school-related tasks. One key piece of information that a prospective student should have is the actual dollar price of college that the student is likely to pay. The published costs of a year of college do not tell the full story. Many students receive Federal assistance, and individual colleges and universities often have their own need-based aid programs, as well as merit scholarships. The Department of Education has two particularly useful tools for prospective college students who would like to understand better what they are likely to pay in tuition, room and board, expenses, and fees. While the exact financial aid available to any particular student depends on a number of factors including household size, household income, and asset net worth, the Department of Education’s FAFSA4caster (http:// fafsa4caster.ed.gov/) can help students learn how much aid might be available. Using the College Navigator tool (https://nces.ed.gov/collegenavigator/), a prospective college student can learn how Federal, state and local, and institutional aid affect net prices at specific colleges. A menu-driven format allows a prospective student to select a college or set of colleges (say, by geography or type of degree) and discover the average net price paid by students of various income levels at each college on the prospective student’s list. The average net prices across schools can vary widely and can deviate substantially from the published costs. For example, information from the College Calculator shows that, for households with income between $48,000 and $75,000, the average annual cost of attending one of the top ten national universities (as ranked by U.S. News and World Report) in 2009–10 was $52,796. The average net price for those who received aid at one of those institutions, however, was a substantially lower $9,340. Meanwhile, large state schools with much lower published costs than the private universities can have higher net costs. For households in the $48,000–$75,000 income range that received aid, the average annual net cost (including the costs of living on campus) in 2009–10 at the top ten largest public universities was $13,486. Jobs and Income: Today and Tomorrow | 193 period of time, shows that training for adults can have large positive effects on earnings. Combining classroom learning with more hands-on training usually has led to the largest and most lasting impacts (Hotz, Imbens, and Klerman 2006; Dyke et al. 2006). The Trade Adjustment Assistance program was established in 1963 and has undergone numerous changes since its inception, but its basic purpose remains to provide training to workers displaced as the result of foreign competition. Eligible workers receive the same kinds of reemployment and training services offered to WIA participants, but more generous funding allows them to receive training for a longer period of time. Moreover, TAA provides income supplements to regular unemployment insurance benefits as well as an allowance for relocation. If the displaced worker is over 50 years old and finds a new job paying less than $50,000 a year, TAA also provides the worker the option to receive wage insurance in the amount of half the difference between his or her old and new wage (up to a cap of $10,000) for up to two years. Recognizing the importance of job training to American workers and their families, the President has proposed a major initiative to provide workers with the tools and skills they need to find new jobs—by forging new partnerships between community colleges and businesses to train 2 million skilled workers and by streamlining access to training and employment services for dislocated workers. The current system does not treat all workers who were dislocated because of economic shifts equally. As noted above, workers in tradeimpacted industries are eligible for extensive income support, training, and reemployment services under the TAA, while those who lose their jobs for other reasons receive less generous assistance. In this increasingly global economy, it is difficult to distinguish between trade, technology, outsourcing, consumer trends, and other economic shifts that cause displacement. The President believes that dislocated workers should be able to access a single program, visit a single location or go to a single web site to find information about and assistance with job and training opportunities in their community. Ensuring that displaced workers have the information and training they need to successfully return to work is important not only for those who have lost their jobs as a result of the 2007–09 recession, but also for those who will be in need of these services in the future. 194 | Chapter 6 Conclusion The 2007–09 recession severely disrupted a labor market that was already under stress from decades of rising inequality, stagnant middleclass incomes, and weak job growth in the 2001–07 recovery period. The job market has been recovering gradually since the end of the recession, and the Administration continues to make strengthening and sustaining the recovery in the job market a top priority. The policies proposed by the Administration will promote continued economic growth and job creation by supporting aggregate demand through an extension of the 2 percentage point payroll tax cut, the continuation of extended unemployment insurance benefits, investments in infrastructure, and assistance to states and localities to retain school teachers and first responders. Investments in expanded reemployment services and training for low-skilled and displaced workers will help get Americans back to work. And the President’s proposals to invest in elementary and secondary education and to make college more affordable will lay the foundation for a stronger economy in the future. Jobs and Income: Today and Tomorrow | 195 C H A P T E R 7 PRESERVING AND MODERNIZING THE SAFETY NET T oday’s dynamic, global economy, driven by rapid technological change, offers abundant benefits and opportunities—but also entails many risks. The Great Recession has made clearer than ever that a strong and flexible economy requires a robust safety net to protect families against major risks and to reduce the likelihood that temporary economic shocks will inflict permanent harm on families and the economy. In the first weeks after President Obama was inaugurated, the President and the Congress enacted policies to expand and strengthen the safety net in response to the ongoing economic crisis. The American Recovery and Reinvestment Act of 2009 (the Recovery Act) provided increased funding for a number of key safety net programs, including unemployment insurance (UI), Temporary Assistance for Needy Families (TANF), Medicaid, and the Earned Income Tax Credit (EITC). These and other safety net programs have been critical in cushioning American families from the effects of the Great Recession and in stabilizing the economy by supporting aggregate demand. One way to gauge the impact of the safety net is to consider the number of American families that would have been in poverty were it not for the support provided by specific programs. These effects are significant. In 2010, the official poverty rate was 15.1 percent, which translates to roughly 46 million people living in poverty. According to U.S. Census Bureau estimates, were it not for unemployment insurance benefits, 3.2 million more Americans would have been in poverty in 2010. This figure includes about 2.3 million nonelderly adults, 900,000 children, and 100,000 adults age 65 and older. Among families participating in the program, the receipt of UI benefits has the effect of cutting the poverty rate roughly in half (Gabe and Whittaker 2011). 197 Data Watch 7-1: The Census Bureau’s Supplemental Poverty Measure The official poverty measure was developed in the 1960s. According to this measure, a family is considered to be poor if its before-tax income falls below a “poverty line” that varies according to family size and composition. In 2011, the Census Bureau released an alternative to the official poverty measure that presents a more complete picture of poverty and of the effects of policies to support low-income families. This Supplemental Poverty Measure (SPM), developed early in the Obama Administration, is based on an approach recommended in 1995 by the National Academy of Sciences. Like the official poverty measure, the supplemental measure compares the resources available to a household with a threshold level of income that takes into account household composition. It differs from the official measure, however, both in how it calculates resources and in how it sets the thresholds. The supplemental measure adds in-kind assistance such as nutritional assistance and subsidized housing to household resources and subtracts necessary expenses such as taxes, child care, and other work-related expenses, as well as medical out-of-pocket costs. Its thresholds are calculated differently than those for the official poverty line, and they reflect geographic differences in housing costs. Overall, 16.0 percent of all Americans were estimated to be in poverty in 2010 according to the supplemental measure, compared with 15.2 percent using the official methodology.a Differences between the two measures vary across demographic groups. For example, because they disproportionately benefit from programs like the Earned Income Tax Credit (EITC) and the Supplemental Nutrition Assistance Program (SNAP), children are more likely to be in poverty according to the official measure, which does not account for support from these programs. By contrast, the poverty rate for elderly Americans is higher according to the supplemental measure, since unlike the official measure, it subtracts out-of-pocket medical expenses from income. The supplemental poverty measure allows researchers to isolate more accurately the effects of a specific policy, source of income, or category of expense on the prevalence of poverty. Among the programs studied by the Census Bureau, the EITC has the largest antipoverty effect; according to the supplemental measure, in the absence of the tax credit, an additional 6.1 million people would have been in poverty in 2010. Accounting for medical out-of-pocket expenses in the supplemental measure, on the other hand, moved 10 million individuals into poverty in 2010. a This official estimate differs from the usual published rate (of 15.1 percent) as unrelated individuals under 15 years of age are included in the universe. 198 | Chapter 7 The official definition of poverty does not account for the effect of taxes paid and tax credits, such as the Earned Income Tax Credit. Nor does it incorporate the value of in-kind benefits. As a result, the official measure does not reflect the benefit that American families receive from the EITC or important safety net programs, such as the Supplemental Nutrition Assistance Program (SNAP), on the official poverty rate. However, such a calculation is possible using an alternative measure of poverty, known as the Supplemental Poverty Measure (Data Watch 7-1). Using the supplemental measure, the Census Bureau estimated that in the absence of the EITC another 6.1 million Americans, nearly half of them children, would have been in poverty in 2010. In that same year, SNAP benefits lifted 2.9 million adults and 2.2 million children out of poverty. Considered all together, it is estimated that the social insurance and means-tested transfer programs that make up the safety net reduce the number of Americans falling below the poverty line by more than half (Ziliak 2011). Safety net programs can improve economic efficiency by supplementing private markets if they fail to provide adequate insurance against major economic risks. A fundamental market failure common to both insurance and annuity markets is adverse selection, which arises when consumers know more than insurers about their own risk—their expected medical claims, their likelihood of becoming unemployed, or their expected longevity (Rothschild and Stiglitz 1976). If insurance or annuity contracts are priced according to the average risk in a population, coverage will be attractive to those who know that they are at high risk and unattractive to those who know that they are at low risk. To the extent that high-risk consumers are more likely to purchase insurance, the cost of coverage will rise, which in turn will make coverage even less attractive to their low-risk counterparts. The gravity of the adverse selection problem will vary across types of insurance and, for a given type, across market segments. Some types of insurance, such as unemployment insurance, have virtually no private market. Private health insurance and annuity markets exist, though not without substantial support from tax and regulatory policies; even with this support, coverage remains costly and incomplete. In addition to addressing specific types of market failure, a strong safety net can promote growth and entrepreneurship. By providing a basic level of security, well-designed safety net programs help create an environment that encourages people to engage in value-creating activities such as changing jobs or starting a new business. A strong safety net is especially important in a global economy in which international trade and financial integration can bring both substantial benefits and increased risk. Robust cross-country evidence finds that economies that have stronger safety nets Preserving and Modernizing the Safety Net | 199 also tend to pursue more efficient economic policies (Rodrik 1998). Safety net programs also protect workers and their families from the labor market disruptions that can arise from technological change and other sources of fluctuation in demand. Finally, safety net programs can be an important component of automatic stabilizers—providing expansions in aggregate demand that help counteract the weakening of the economy during economic downturns. An effective and efficient safety net must adapt and evolve in response to changes in technology and economic conditions. This chapter provides an overview of the key components of the safety net in the United States, emphasizing recent policy developments and proposals to keep the nation’s safety net strong. Unemployment Insurance Unemployment insurance has long been an essential component of the safety net for workers who have lost a job through no fault of their own. In the recent period of high unemployment, the basic UI program and emergency extensions have provided critical support for millions of American families. In 2010, almost 10 percent of households received UI benefits—and that share is expected to fall back toward the pre-recession average of about 4 percent as the economy recovers. Unemployment insurance is a joint Federal-state program that covers nearly all civilian workers. During normal economic times, workers and employers contribute to state systems that pay benefits to unemployed workers for up to 26 weeks. During periods of high unemployment, extended benefits (EB) are available to workers who have exhausted regular UI benefits, with the costs normally shared between the Federal Government and states. Benefits are determined as a function of past wages, up to a cap. Although key program parameters vary across states, on average UI benefits replace roughly half of a recipient’s lost earnings. In 2011, the average weekly benefit was roughly $300. Historically the Federal Government has funded benefits for extended periods while the economy recovers from a serious downturn. It did so once during the 1950s, once during the 1960s, twice during the 1970s, and once each during the early 1980s, the 1990s, and the early 2000s. In each instance since the 1970s, extended benefits have been reauthorized, usually multiple times, in reaction to continued weakness in the labor market. In June 2008, Congress enacted the Emergency Unemployment Compensation (EUC) Program that added 13 weeks of Federally funded UI benefits. As the labor market continued to deteriorate, Congress extended the program 200 | Chapter 7 for workers in the hardest-hit states several times. In addition, starting in February 2009, Congress provided full Federal funding of extended jobless benefits. Together these policies allow workers in high-unemployment states to qualify for up to 99 weeks of benefits. The Economics of Unemployment Insurance Unemployment insurance benefits enable workers to minimize disruptions in spending caused by unanticipated income shocks (Baily 1978). Economic research indicates that this consumption-smoothing effect is important. According to one study, in the absence of UI, a typical family whose household head becomes unemployed lowers spending on food by 22 percent, while a family receiving UI benefits spends only 7 percent less on food (Gruber 1997). In addition to helping families whose income has been reduced due to job loss, by providing income to families that they can spend, UI benefits mitigate the impact of the recession on the broader economy. These benefits must be weighed against the cost of longer spells of unemployment potentially induced by the availability of UI—although in the current environment, any effect on spell length is likely to be comparatively small. Theoretical models of labor supply and job search predict that unemployed workers covered by more generous UI systems can take longer to find a new job (see, for example, Mortensen 1977). More recent work has shown that it is important to distinguish among reasons why UI increases the duration of unemployment. Traditionally, economists have interpreted the relationship between UI and duration in the context of a worker’s choice between work and leisure, assuming that UI reduces the effort devoted to job search. An alternative view, given that a large fraction of unemployed workers have limited assets, is that UI benefits allow workers to meet their basic needs while they search for a job that is a good match for their talents (Chetty 2008). Better matches generally translate to higher wages (leading to higher tax revenues), increased job satisfaction, and greater employment stability (which reduces employers’ hiring costs). The empirical research literature on the relationship between UI benefits and unemployment duration is sizable. Recent research suggests that UI benefits have small effects on unemployment duration even when the economy is strong (Card and Levine 2000). In periods of high unemployment, the consumption-smoothing benefit of UI will be especially valuable to workers, and any negative effects on worker search effort will be less important because of the scarcity of jobs (Kroft and Notowidigdo 2011; Schmieder, von Wachter, and Bender 2012). Consistent with this premise, research suggests that the recent expansion of extended and emergency benefits has had a minimal effect on the duration of unemployment spells and Preserving and Modernizing the Safety Net | 201 the unemployment rate (Farber and Valletta 2011; Rothstein 2011; Daly et al. 2012). Moreover, to the extent that the extension of benefits has affected the measured unemployment rate, it has done so not by reducing the probability that unemployed workers look for and find jobs, but by reducing the number of unemployed workers who have given up on searching for a new job (Rothstein 2011). This finding is important in light of evidence suggesting that during periods of high unemployment, many older workers who exhaust their UI benefits end up applying for Social Security Disability Insurance (Rutledge 2011). Recent Trends in UI Receipt and Its Effect on Household Income The share of households receiving UI rose from 4.1 percent in 2007 to 9.6 percent in 2010. Over the same period, the average annual amount received by households benefiting from UI rose from $4,400 to $8,340, mainly because of longer duration of benefit receipt but also because of the extra $25 in weekly benefits provided through FY 2010 by the Recovery Act. This money was crucial to keeping many families in their homes and able to pay other household expenses. As noted, UI lifts millions of families out of poverty. However, because a large share of benefits flows to middle-income workers, these antipoverty effects understate the economic impact of the program on participants. Households that received UI benefits in 2010 had a median income of $55,000 the previous year, which is only slightly less than the median income of working households that did not receive UI. Among all recipients, UI payments represented 23 percent of household income in 2010. The share of income represented by UI ranged from 15 percent for multiple-earner households without children to almost 36 percent for households with a single worker and no children (Figure 7-1).1 In addition to providing income insurance to families of unemployed workers, the UI system helps the economy as a whole (Auerbach and Feenberg 2000). Unemployment insurance is an automatic stabilizer that leans against the negative cycle of increased unemployment leading to reduced consumption, which leads to a further decline in economic activity. Since unemployed workers tend to spend rather than save their benefits, the impact on aggregate demand is fairly immediate. Because of the way that the emergency and extended benefits programs increase economic activity, they generate partially offsetting income and payroll tax revenues for the Federal Government and help state and local budgets by increasing sales tax revenues. In addition, without the income support provided by these 1 Because previous research suggests that recipients tend to understate the amount of unemployment benefits they receive (Meyer, Mok, and Sullivan 2009), these figures can be seen as lower-bound estimates of the effect of UI on household income. 202 | Chapter 7 Figure 7-1 Share of Household Income from Unemployment Insurance among Recipients in 2010, by Household Type Percent 40 34 35 36 30 25 23 20 15 15 15 10 5 0 Total Sole earners Sole earners Multiple earners Multiple earners with children without children with children without children Source: Current Population Survey, Annual Social and Economic Supplement. programs, more families would draw on other public programs. For these reasons, the Congressional Budget Office notes that extending UI benefits is the most timely and cost-effective policy for increasing economic activity and employment (CBO 2011). Policy Innovations The U.S. unemployment insurance system dates to the Great Depression of the 1930s. Originally, most covered workers were employed in manufacturing. At its inception, the UI system allowed for income smoothing for workers who would ultimately return to their old job or one like it. Research based on data from the early 1980s suggests that at that time 60 percent of UI spells ended with the worker being recalled to his or her original job (Corson and Nicholson 1983; Katz and Meyer 1991). Today, temporary layoffs are less common; increasingly, workers receiving UI benefits have been dislocated as the result of structural changes in the economy and must find a new industry or occupation. In many cases, wages in the new jobs these workers find are significantly lower than their former wages. Thus, workers today need income support while they are searching for a new job, but they also need training, job search support, and other assistance to help ease what can be a difficult transition. Preserving and Modernizing the Safety Net | 203 The first step to modernize the unemployment insurance program was taken in the UI Modernization Act, a part of the Recovery Act. The UI Modernization Act made $7 billion available to states that made reforms to their UI programs. States could receive a part of the incentive payment for using the most recent quarter as a part of the base period of earnings on which UI eligibility and benefit amounts are determined. This made it more likely that recent labor market entrants would meet the minimum earnings threshold for UI eligibility. States could receive the other part of their apportioned payment by adopting two of the following policies: allowing workers who were employed part-time previously to continue receiving UI while looking for part-time work, providing UI benefits to those who left their jobs for certain compelling family reasons, allowing workers to continue receiving UI for an additional six months if in an approved training program, and providing additional benefits for households with more dependents. These small incentive payments resulted in 36 states changing their UI laws. Building on these reforms, in the American Jobs Act the President called for further steps to improve the unemployment insurance program and expand reemployment services and job training, and has made these reforms a part of the FY 2013 Budget proposal. Although most UI policy innovations target workers who have already lost their jobs, another important policy goal is to reduce the number of workers who are laid off in the first place. One promising initiative is work-sharing. Under a work-sharing arrangement, workers whose hours are reduced in lieu of temporary layoffs receive partial UI benefits while remaining on the job and keeping their skills sharp. By allowing employers to retain skilled workers at reduced hours rather than laying them off, work-sharing makes it easier and less costly for employers to scale up production when orders increase. Twenty-four states now have work-sharing programs, and in the American Jobs Act, President Obama proposed incentives to help expand the program to more states. Workers who have been laid off need help finding a new job. The American Jobs Act included the Reemployment NOW program, a set of reforms to help UI claimants get back to work more quickly. The FY 2013 Budget continues this support. As a part of this initiative, the Administration has proposed requiring states to provide reemployment services, such as career and job search counseling, skills assessments, and assistance in identifying helpful resources to EUC recipients to speed their return to work. Face-to-face contacts also provide an opportunity to assess recipients’ eligibility for UI benefits. Research suggests that these services can lower program costs by reducing spells of UI receipt and eliminating payments to ineligible individuals (Black et al. 2003). 204 | Chapter 7 Because entrepreneurship is key to a dynamic economy, a modern UI system should make it easier for displaced workers to start their own businesses. The Administration has proposed allowing states to use Reemployment NOW funds to expand Self-Employment Assistance programs that pay UI benefits to recipients who are working full-time to establish a new business. Seven states already permit a similar use of unemployment insurance benefits. Under this program, entrepreneurship training would be facilitated through One-Stop Centers in collaboration with the Small Business Administration. A demonstration project, Growing America Through Entrepreneurship (Project GATE), provided training and one-onone counseling to anyone interested in creating, sustaining, or expanding a small business. A recent study found that GATE had a positive effect on new business starts for unemployed participants and higher total earnings after five years than a comparison group (Michaelides and Benus 2010). For jobless workers seeking to change occupations, lack of experience can be a significant barrier. With Reemployment NOW funds, states could experiment with Bridge to Work programs, which would allow EUC recipients to get short-term work-based experience that helps them maintain or enhance their skills. Under this program, private employers would be able to take on EUC recipients for up to 38 hours a week for a trial period of up to eight weeks with the workers receiving compensation through the EUC program. In addition, all program participants would be covered by workers’ compensation and be guaranteed at least the minimum wage. Finally, to support state creativity and flexibility, upon approval of the Secretary of Labor, states would be permitted to use Reemployment NOW funds to implement their own innovative strategies for connecting the longterm unemployed to employment opportunities. In addition to these efforts that build upon the existing Federallyfinanced unemployment compensation system to help with getting the long-term unemployed back to work, the President’s Budget includes other important and complementary initiatives that will contribute to the goal of ensuring that every American who wants a job can find one. As discussed in Chapter 6, these initiatives include streamlining training and employment services so that job seekers can visit a single location or go to a single web site to find the help they need; providing a universal core set of services to serve all dislocated workers; and introducing a new Pathways Back to Work fund to support employment opportunities for low-income youth, low-income adults and the long-term unemployed. Preserving and Modernizing the Safety Net | 205 Other Safety Net Programs Several means-tested programs also provide support to American families, especially those who have experienced adverse economic shocks. Table 7-1 reports the number of participants and Federal cost of several important programs. One of the largest Federal programs targeted at lowincome families is the Earned Income Tax Credit, a refundable tax credit for low-income workers. The assistance is available only to those with earnings, and the amount of the credit increases with a worker’s earned income up to a maximum level and then phases out at higher income levels. The maximum benefit amount increases with the number of children in the family, and the income level at which the credit begins to phase out differs according to taxpayer filing status (single or married couple filing jointly). As part of the Recovery Act, Congress created a new category with a higher credit for taxpayers with three or more children, providing those families as much as $600 extra, and increased the income level at which the credit phases out for married couples filing jointly by $3,000 over 2008 levels. The Tax Relief and Job Creation Act of 2010 extended these changes through 2012. Over 26 million working families and individuals received the EITC on their 2010 tax return, with the average claimant receiving $2,220. The benefits of the EITC go beyond the amount of the credit received. Studies have found that the EITC increases participation in the labor market (Eissa and Liebman 1996; Meyer and Rosenbaum 2000), improves maternal health outcomes (Evans and Garthwaite 2010) and helps low-income individuals acquire additional experience that contributes to higher earnings growth (Dahl, DeLeire, and Schwabish 2009). The Supplemental Nutrition Assistance Program (SNAP) is another critical safety net program targeted at low-income families. SNAP benefits are funded by the Federal Government and administered by states. Families and individuals qualify if their income and assets are sufficiently low. Participants usually receive their benefits on electronic benefit transfer cards that can be used only to purchase food. Nondisabled adults who have no dependents and who are not working or participating in a work training program can usually receive SNAP benefits only for three months over a three-year period. Roughly half of all SNAP participants were children, and more than three-quarters of all participant households included a child, an elderly person, or a disabled nonelderly person. Roughly a quarter of all children participated. In FY 2010, the average household participating in the SNAP program received monthly benefits worth $287; 40 percent of participating 206 | Chapter 7 Table 7-1 Number of Participants and Total Federal Expenditures for Safety Net Programs, 2010 Participants (millions) Federal expenditures (billions of dollars) Medicare 47.5 522.8 Old Age and Survivors Insurance 43.8 584.9 Unemployment insurance 10.4 158.3 Social Security Disability Insurance 10.2 127.7 Medicaid/Children's Health Insurance Program 58.3 281.9 Supplemental Nutrition Assistance Program 40.3 68.3 Earned Income Tax Credit 26.8 59.5 Supplemental Security Income 7.9 47.8 Public and assisted housing 4.7 37.9 Temporary Assistance for Needy Families 4.4 18.1 Social insurance Means-tested transfers and credits Note: Recipients are counts of individuals except for recipients of EITC (tax filing units) andhousing (families). Expenditures for UI, Medicaid/CHIP, SNAP, and TANF are for fiscal year 2010, and the number of recipients is the average of point-in-time recipients over fiscal year 2010. Public and assisted housing includes only programs operated by the Department of Housing and Urban Development, and recipients and expenditures are for fiscal year 2010. The number of SSI recipients is as of December 2010. For all other programs, the number of recipients represents those participating at any point in the (calendar) year. Federal expenditures include grants to states. Source: Center for Medicare and Medicaid Services, Social Security Administration, Department of Labor, Office of Management and Budget, Medicaid Payment Advisory Commission, Department of Agriculture, Internal Revenue Service, Department of Health and Human Services, Department of Housing and Urban Development. households received the maximum benefit for their family size—for example, $668 a month for a family of four. Both participation and expenditures are strongly countercyclical in the SNAP program, increasing during economic contractions and decreasing during expansions. Current projections are that SNAP enrollment will begin falling next year, as the economy continues to recover. Thus, like UI, SNAP not only provides direct benefits to participant households, but also has a stabilizing effect on the economy by limiting declines in consumption during economic downturns. The Recovery Act established the Emergency Contingency Fund for state Temporary Aid for Needy Families programs, which provided $5 billion to states for increased spending for basic assistance, nonrecurrent shortterm benefits, or subsidized employment. States expanded efforts in all three areas, including committing $1.3 billion to the largest targeted employment initiative in the history of welfare reform. Thirty-nine states in addition to the District of Columbia, Puerto Rico, and the Virgin Islands established subsidized employment programs, with an estimated 260,000 job slots created for adults and youth, many of them involving subsidies that created jobs with private sector employers. While most of these subsidized employment Preserving and Modernizing the Safety Net | 207 efforts were not sustained at previous levels after Recovery Act funding ended, many jurisdictions have maintained programs at a smaller scale. Based in part on the success of this initiative, the President has proposed the Pathways Back to Work Fund (discussed in Chapter 6) that would provide employment opportunities for low-income individuals and the long-term unemployed. Housing is the largest component of virtually every family’s budget, especially low-income families. The Federal safety net includes several programs designed to ensure that financial stress does not result in homelessness. Stable housing allows families to weather labor market shocks and is a precondition for children’s educational success. In addition to the 2.3 million families assisted by the Department of Housing and Urban Development’s project-based rental assistance and public housing programs, the largest Federal program aimed at low-income households is the Housing Choice Voucher program. The Housing Choice Voucher program served 2.1 million families in FY 2010, of which 90 percent included children, the elderly, or individuals with disabilities. As discussed in Chapter 4, the Administration has also developed new programs that help unemployed homeowners avoid foreclosure. Two other programs that are critical to the safety net provide benefits to Americans with disabilities. Social Security Disability Insurance (SSDI) is a social insurance program designed to offset the loss of wages of workers with long-term health conditions that prevent “substantial gainful activity.” Individuals with adequate Social Security–covered employment history, or children (disabled before age 22) of a retired, deceased, or disabled worker entitled to Social Security benefits, are covered by the program. Beneficiaries receive a cash benefit based on their income before becoming disabled, adjusted upward by wage inflation. In December 2010, more than 10 million people received SSDI benefits. Recipients become eligible for Medicare after two years, offsetting the loss of employer-sponsored health insurance. A second Federal program that assists persons with disabilities is Supplemental Security Income (SSI), a means-tested entitlement program that provides cash benefits to needy aged, blind, or disabled individuals. In December 2010, roughly 7.9 million Americans received SSI benefits; of that total, about 6.6 million qualified on the basis of a disability. The program is a particularly important source of income for older working-age adults: roughly one-quarter of all participants are between the ages of 50 and 64. A recent study illustrates how critical these programs are to their participants (DeCesaro and Hemmeter 2008). Using data from 2002, the study shows that nearly a quarter of SSDI and roughly half of SSI beneficiaries had family incomes that fell below the Federal poverty level. However, 208 | Chapter 7 the programs play an important role in keeping their beneficiaries out of extreme poverty, which is defined as having an income below 50 percent of the Federal poverty threshold. According to this study, the majority of SSDI recipients relied on that program for at least 75 percent of their income. While only 5 percent of SSI beneficiaries were in extreme poverty, taking away SSI benefits would have raised that figure above 40 percent. Health Insurance In March 2010, the President signed into law the Patient Protection and Affordable Care Act (the Affordable Care Act). When fully implemented, the Affordable Care Act will significantly strengthen the health care safety net, substantially increasing the number of Americans with health insurance and providing new protections and benefits to those who are already insured. The Affordable Care Act builds on and maintains the strengths of the current private system of employer-sponsored health coverage and insurance provided through Medicare, Medicaid, and the Children’s Health Insurance Program (CHIP). Therefore, the changes brought about by the new law need to be considered in the context of the current system. The Economics of Employer-Sponsored Health Insurance One of the defining features of the U.S. health care system is the central role played by employers. Today, roughly nine in ten Americans with private health insurance obtain their coverage through the workplace, either through their own employer or through the employer of a family member. Employer-sponsored insurance is generally much less costly for workers— who pay for coverage through reductions in their wages as well as direct premium contributions—than coverage purchased directly in the individual market. There are three main sources of savings. First, employer-sponsored group coverage greatly mitigates the problem of adverse selection. Because employer-sponsored groups are formed for reasons other than purchasing health insurance, they represent stable risk pools. Employer policies themselves contribute to this stability and to the spreading of risks. Within firms, the amount that employees are required to contribute toward premiums generally does not vary with health risk. Common employer and insurer policies—such as limiting periods when employees can sign up for coverage and requiring a minimum employee participation rate—prevent employees from declining coverage when they are healthy and joining the plan only when they need medical care. A stable risk pool translates to lower administrative costs as insurers need to devote fewer resources to underwriting. Administrative savings also Preserving and Modernizing the Safety Net | 209 come from economies of scale in marketing and administration. Because important costs vary with the number of contracts rather than the number of individuals covered by a contract, it is less expensive on a per-person basis to sell to a group of 1,000 than to sell to 1,000 individuals. Third, because employer expenditures on health insurance premiums are exempt from Federal and state income taxes and Social Security payroll taxes, employer-sponsored insurance can effectively be purchased with pretax dollars. For a typical worker in the 15 percent tax bracket, the tax exclusion reduces the cost of insurance by roughly one third (Gruber 2010). Overall, the estimated FY 2011 tax expenditure associated with the exemption from Federal taxes is $282 billion. Although the cost savings associated with employer provision of insurance can be large, the savings are not evenly distributed among employers. The advantages of more efficient risk pooling and economies of scale in marketing and administration increase with firm size. The value of the tax exemption is not explicitly tied to firm size, but because compensation tends to be higher in larger firms, this advantage is correlated with size as well. As a result, the larger the firm, the greater the probability it will offer health insurance. Figure 7-2 illustrates that, whereas nearly all firms with more than 50 employees offer health benefits, less than half of those with 2 to 24 employees do. Between 2000 and 2010, the share of private sector establishments with fewer than 50 workers that offer health insurance benefits declined from 47.2 percent to 39.2 percent. Firm size affects more than just whether workers are offered coverage. Among firms that offer insurance, large firms are substantially more likely to offer a choice of plans: more than 80 percent of private sector establishments with 1,000 or more employees offered a choice of health insurance options in 2010, compared with 18 percent of establishments with 50 or fewer employees. Employees who have a choice of plans tend to report greater satisfaction with their insurance coverage and their health care (Schone and Cooper 2001). And some very large firms have actively promoted strategies to improve health care quality and patient safety. Over the past two decades, rising health care costs have eroded the accessibility of employer-sponsored health insurance, especially for middleclass families who experienced relatively little income growth over that period. Figure 7-3 plots the percentage of workers who lack health insurance (left axis) against an estimate of their per capita health spending divided by their median income (right axis). Because the growth in health spending is a principal determinant of rising insurance premiums, this ratio can be seen to capture changes in the affordability of health insurance. The figure indicates that during the 1980s insurance became less affordable as health care costs 210 | Chapter 7 Figure 7-2 Percentage of Private Sector Establishments Offering Health Insurance by Number of Employees, 1996–2010 Percent 100 50+ employees 90 80 25–49 employees 70 60 10–24 employees 50 40 30 2–9 employees 20 10 0 1996 1998 2000 2002 2004 2006 Source: Medical Expenditure Panel Survey, Insurance Component. 2008 2010 grew faster than median incomes and the percentage of workers without coverage grew. In the mid-1990s, health care spending grew less rapidly and a strong economy caused median income to rise. As a result of this confluence, the affordability index remained relatively constant, and insurance coverage stabilized. However, health care cost growth picked up again in the late 1990s and has outstripped income growth for the past decade, causing coverage to decline once again. Medicaid and CHIP: A Health Care Safety Net for Children As insurance coverage has declined among working-age adults over the past two decades, coverage among children has actually increased because of expanded eligibility for public programs. Until the mid-1980s, Medicaid eligibility was tied to eligibility for Aid to Families with Dependent Children, the cash welfare program. Starting in 1986, the two programs were delinked, and income eligibility limits for Medicaid were increased. The most significant eligibility expansions came as part of the Omnibus Budget Reconciliation Acts of 1989 and 1990. As the data in Figure 7-4 depict, with these expansions the share of children without health insurance began to decline, even as the share of uninsured adults rose. By 1997, while 18 percent of nonelderly adults were uninsured, the share of children who were uninsured was 14 percent. Preserving and Modernizing the Safety Net | 211 Figure 7-3 Percentage of Workers Without Health Insurance and the Ratio of Per Capita Health Expenditures to Median Income, 1979 –2010 Ratio of expenditures to income 0.15 Percent uninsured 26 23 0.13 Percent of workers without insurance (left scale) 0.11 0.09 20 Per capita health expenditures for privately insured adults divided by median income among workers (right scale) 17 14 1979 1985 1990 1995 2000 Source: CEA extension of Gilmer and Kronick (2009). 2005 0.07 0.05 2010 0.03 That same year, Congress established the State Children’s Health Insurance Program (initially referred to as SCHIP, now CHIP) as part of the Balanced Budget Act of 1997. Like Medicaid, CHIP is funded jointly by states and the Federal Government, although CHIP allows states more flexibility in designing their programs. States began implementing CHIP in late 1997, and by 2000 every state program was up and running. Today, the income eligibility limit in 47 states and the District of Columbia is 200 percent of the Federal poverty level or greater. As a result of Medicaid and CHIP, the percentage of children who are uninsured has fallen since the late 1990s and is now less than half the adult rate. President Obama has built on the success of Medicaid and CHIP by making these programs even stronger. In the early days of the Administration, the President signed the Children’s Health Insurance Program Reauthorization Act of 2009, which extended funding for CHIP through September 2013. This legislation also introduced administrative reforms that improve program effectiveness, including new performance bonuses for states that successfully increase coverage by streamlining eligibility and enrollment procedures. Also in 2009, the Recovery Act provided additional support to states by boosting the Federal share of Medicaid at a time when program enrollment was increasing and state budgets were in crisis. Between 2008 and June 2011, over 212 | Chapter 7 Figure 7-4 Percentage of Children and Adults Without Health Insurance, 1988–2010 Percent 25 20 Age 18–64 15 Age under 18 10 5 0 1988 1993 1998 2003 2008 Note: Data for 1988 to 1998 adjusted to reflect CPS's 2011 revision to the health insurance editing process. Source: Current Population Survey, Annual Social and Economic Supplement. 4.4 million children gained coverage through Medicaid and CHIP. In 2010, the Affordable Care Act extended funding for CHIP through 2015. Because of Medicaid and CHIP, insurance coverage of children tends to be less sensitive to changes in macroeconomic conditions than that of adults. Research suggests that, holding other factors constant, a 1 percentage point increase in the national unemployment rate translates to almost a 1 point decrease in the percentage of nonelderly adults and children covered by employer-sponsored insurance (Holahan and Garrett 2009). Without a strong public insurance safety net for adults, more than half of the working-age Americans who lose employer-sponsored insurance during an economic downturn end up uninsured. For children, however, the loss of private coverage is mostly offset by an increase in public insurance. This discrepancy between the experience of adults and children will change with the full implementation of the Affordable Care Act, described below. Many studies indicate that the expansion of Medicaid and CHIP has also significantly improved access to health care. One study using data from the 1980s and early 1990s found that eligibility for public insurance roughly halved the probability that a child failed to have at least one physician visit a year (Currie and Gruber 1996a). Other research shows that increased Medicaid eligibility for children leads to an increase in hospitalizations Preserving and Modernizing the Safety Net | 213 overall, but a decrease in “preventable” admissions (that is, those that are avoidable if a child receives appropriate primary care) (Dafny and Gruber 2005). Improved access to care translates into better health outcomes, ranging from improvements in subjective health status (Currie, Decker, and Lin 2008) to reduced child mortality (Currie and Gruber 1996a, 1996b). Expanding Health Care Coverage: The Affordable Care Act The Affordable Care Act builds on the strengths of employersponsored insurance and on the success of earlier expansions of Medicaid and CHIP to expand and strengthen the health care safety net. By 2019, the Affordable Care Act is expected to increase the number of Americans with health insurance by more than 30 million. Roughly half of the coverage gain will come from raising Medicaid eligibility limits to 133 percent of the Federal poverty level. Because income eligibility limits for CHIP in all states already exceed this level, the law will expand Medicaid coverage mainly among nonelderly adults. Although the primary responsibility for administering Medicaid will remain with the states, funding for the expanded coverage will come almost entirely from the Federal Government. Most of the remaining coverage gains will come from private insurance purchased through state-level Affordable Insurance Exchanges. Individuals and families with incomes up to 400 percent of the Federal poverty level who do not have access to affordable employer-sponsored coverage that meets a minimum value will be eligible for premium tax credits that they can use to purchase coverage through an Exchange. These new tax credits are targeted at lower- and middle-income families who currently receive little or no benefit from the large tax subsidies that implicitly support the system of employer-sponsored insurance. The Affordable Care Act also establishes a Small Business Health Insurance Options Program (SHOP) in each state that gives small employers and their employees access to private health insurance plans and small business health insurance tax credits as well. The state-level Exchanges will extend to workers at small firms, the self-employed, part-time workers, and nonworkers many of the advantages of employer-sponsored insurance already enjoyed by employees of large firms: more efficient risk pooling and greater administrative economies of scale than are available in the current individual and small group market. Within an Exchange, consumers and employers will be able to choose from a broad menu of plans. To improve consumer choices, Exchanges will provide transparent information on premiums, benefits, cost-sharing, and plan quality—information that will help cut the high consumer search costs that push up premiums in the small group and individual health insurance markets (Cebul et al. 2011). By creating a marketplace in which consumers 214 | Chapter 7 can easily compare plans on the basis of price and quality, the Exchanges should increase competition among insurers. Considerable evidence from large employers shows that when employees are given a choice of health plans and clear information about premiums and benefits, they switch plans in response to small differences in premiums (Buchmueller 2009). The Affordable Care Act establishes new consumer protections for health insurance coverage purchased either through an Exchange or in the outside individual or small group market, many of which are already in effect today. Insurers will not be allowed to deny or limit coverage on the basis of an individual’s health status. Within certain limits, premiums may vary by age, geography, and smoking status, but not by individual health status, gender, or other factors. The Act also includes a requirement that individuals who can afford insurance maintain minimum essential coverage. These market reforms fill an important gap in the health care safety net. Provisions of the Affordable Care Act Now in Place Many of the insurance market reforms, along with the expansion of Medicaid and the creation of the Exchanges, will not take effect until 2014. Some provisions of the Affordable Care Act, however, have already been put into place. Insurers are now prohibited from retroactively cancelling coverage because of honest mistakes made on the application. The Act also eliminates lifetime dollar limits on essential health benefits and restricts the use of annual dollar limits. (Annual benefit limits will be eliminated completely by 2014.) Since July 2010, consumers who are uninsured and unable to get insurance because of a pre-existing condition can find subsidized coverage through the Pre-Existing Condition Insurance Plan. This temporary program gives uninsured individuals with costly conditions access to affordable insurance until the full set of consumer protections takes effect in 2014. As of the end of 2011, 45,000 individuals were enrolled. Another coverage-related provision of the law that is already in force allows young adults to remain on their parents’ private insurance policies until they reach age 26. This policy targets a population that is disproportionately uninsured. Although one reason large numbers of young adults have no health insurance is that people in this age group tend to be in good health and do not perceive a need for health care (the “young invincibles” hypothesis), a second important reason is lack of access to affordable coverage, because many young adults have not yet settled into full-time jobs that offer health benefits. As a result, the probability of being uninsured jumps between the ages of 18 and 19, as many young adults lose coverage under their parents’ employer-sponsored insurance. This loss of coverage Preserving and Modernizing the Safety Net | 215 translates to a significantly lower use of health care services (Anderson, Dobkin, and Gross 2012). The dependent coverage provision of the Affordable Care Act took effect on September 23, 2010. Data from several independent sources indicate that the policy has significantly increased the insurance coverage of young adults. Figure 7-5 presents data from one such source, the National Health Interview Survey, highlighting the change in insurance coverage for youth age 19 to 25 in comparison to a slightly older group, age 26 to 35. Because these two groups should face roughly similar labor market conditions, the experience of the older group provides a sense of what would have happened to the younger group had this provision of the Affordable Care Act not gone into effect. Estimates from the third quarter of 2010 show that 35.6 percent of the younger group was uninsured, compared with 27.7 percent of the older group. Between the third quarter of 2010 and the second quarter of 2011, insurance coverage was essentially unchanged for the older group. In contrast, among the younger group the share uninsured fell 8.3 percentage points. This change translates to a gain in health insurance coverage for approximately 2.5 million people. Because even before this policy, college students were able to stay on their parents’ insurance plans or obtain coverage through their school, the coverage gains arising from the Affordable Percent 40 Figure 7-5 Percentage of Young Adults Without Health Insurance, 2010 Q3 and 2011 Q2 35.6 35 30 27.3 27.7 28.3 25 20 15 10 5 0 2011 Q2 2010 Q3 Ages 19–25 Source: National Health Interview Survey. 216 | Chapter 7 2010 Q3 2011 Q2 Ages 26–35 Care Act have been concentrated among non-students and recent graduates. Many of these newly insured young adults are from lower middle-class families who are working to maintain their position in the economy in the face of not only the recent economic downturn, but long-run forces that have been working against the middle class for decades. The Economic Benefits of Expanding Insurance Coverage Expansion in health insurance coverage from the ACA can be expected to positively affect access to care, health, and financial security. These effects and the impact of other provisions of the Affordable Care Act will be important topics of research (see Data Watch 7-2). Research on previous coverage expansions suggests that health insurance can significantly improve all three outcomes. As noted, considerable research has examined the benefits of health insurance for children. One recent study (Finkelstein et al. 2011) examines the effect of insurance coverage on low-income adults. The study, which uses data from Oregon’s Medicaid program, has two especially notable features. First, its population sample is similar to the group that will gain Medicaid coverage as a result of the Affordable Care Act. Second, because of budgetary constraints, access to Medicaid coverage was determined randomly by a lottery, in the same way patients are assigned to treatment and control groups in a randomized control trial. As a result, the study avoids the fundamental problems of inference inherent to observational studies. The study finds that in the program’s first year insurance coverage significantly increased the use of outpatient and inpatient care and of prescription drugs. The added care led to increases in the share of men and women screened for high cholesterol and high blood sugar and in the share of women receiving mammograms and Pap tests. The study also noted significant gains in several self-reported measures of physical and mental health. These findings are especially striking because the health benefits of improved access to care are likely to grow over time. In addition to improving access to appropriate care, health insurance protects individuals and families from the financial risk associated with uncertain and potentially catastrophic medical costs. Today few uninsured families have the resources to cover the cost of a serious illness. According to one recent study, about a third of uninsured families have no financial assets at all, and the average uninsured family can afford to pay only 12 percent of the cost of a single hospitalization (Chappel, Kronick, and Glied 2011). The Oregon study used several financial outcomes to assess economic benefits of insurance. It found that individuals with health insurance were less likely to have unpaid bills sent to a collection agency and that they were significantly Preserving and Modernizing the Safety Net | 217 Data Watch 7-2: Health Data for Policy Health policy formulation and evaluation requires high-quality data on a broad range of outcomes. Federal surveys have provided the basis for a large research literature that informed the design of the Affordable Care Act. These surveys along with other Federal data programs will be important resources for monitoring the impact of the Act. One objective of the Affordable Care Act is to substantially increase the number of Americans with health insurance. The National Health Interview Survey (NHIS) sponsored by the Department of Health and Human Services (HHS) and three other surveys conducted by the Census Bureau—the Current Population Survey’s Annual Social and Economic Supplement, the Survey of Income and Program Participation, and the American Community Survey—provide data on various aspects of insurance coverage. Increased insurance coverage should lead to improved access to care and improved population health. The NHIS and another HHS survey, the Household Component of the Medical Expenditure Panel Survey (MEPS), combine information on insurance coverage with information on medical care utilization and health status. Another component of the MEPS surveys employers on key features of the health insurance they offer employees. Additional information on utilization comes from HHS surveys of health care providers, including office-based physicians, ambulatory care facilities, and hospitals. Two Federal data programs—the National Health Expenditure Accounts, produced by the Centers for Medicare and Medicaid Services, and the National Income and Product Accounts, produced by the Bureau of Economic Analysis—provide independent estimates of national health spending. Efforts also are under way at the Bureau of Labor Statistics to improve the collection of health data to better measure health sector prices and productivity (Bradley et al. 2010). Current initiatives by Federal agencies and academic researchers are aimed at developing data systems that support disease-based estimates of health spending (Aizcorbe, Retus, and Smith 2008). Research in this area focusing on selected conditions has shown that disease-based measures allow for a more nuanced understanding of what drives the growth in health spending. The results suggest that failing to account for changes in the inputs used to treat a particular condition and for improvements in health outcomes leads to an overestimate of health care inflation and an underestimate of productivity gains in the health sector (Aizcorbe and Nestoriak 2011). Whether this conclusion can be generalized is the subject of ongoing research. 218 | Chapter 7 less likely to report having to borrow money or skip paying other bills to pay medical expenses. These findings are consistent with earlier research showing that the advent of Medicare in 1965 generated large benefits in the form of reduced exposure to out-of-pocket medical expenditure risk (Finkelstein and McKnight 2008). The benefits of the Affordable Care Act’s coverage expansion are likely to spill over to the labor market as well. Because small firms cannot offer health insurance that matches in cost and quality the insurance offered by larger firms, they often find it difficult to compete with large firms in attracting and retaining workers. Similarly, the lack of affordable insurance options in the individual health insurance market poses a barrier to workers who would like to start their own business, work part-time, or retire before they are eligible for Medicare. Indeed, numerous studies find that the link between health insurance and full-time employment distorts decisions regarding labor supply, job mobility, and retirement (Gruber and Madrian 2004). By improving the health insurance options available to small employers and expanding the availability of affordable individual coverage, the Affordable Care Act should greatly reduce if not eliminate these distortions. The Affordable Care Act and Medicare Given the high and uncertain medical expenses faced by seniors, the health insurance coverage that Medicare provides for individuals age 65 and older is a critical component of the health care safety net. The inability of private markets alone to provide adequate health insurance coverage for seniors is a classic example of adverse selection (Akerlof 1970). Indeed, before Medicare was enacted in 1965, only an estimated one-quarter of seniors had meaningful private insurance (Finkelstein 2007). Today Medicare covers roughly 40 million elderly Americans and 8 million people under age 65 who qualify on the basis of disability. Although the Affordable Care Act’s coverage expansions and insurance market reforms are targeted at nonelderly Americans, the new law has important implications for Medicare as well. It provides new benefits to seniors by eliminating cost sharing for recommended preventive services, adds an annual wellness visit, and reduces out-of-pocket costs for prescription drugs in the Medicare Part D coverage gap. By the end of 2011, more than 24 million elderly Americans have benefited from the elimination of cost sharing for preventive benefits, and 3.6 million beneficiaries have received $2.1 billion in drug discounts. The Affordable Care Act also puts in place several strategies for reducing the growth in Medicare spending. Such efforts to “bend the cost curve” are essential to maintaining the long-run fiscal status of the program Preserving and Modernizing the Safety Net | 219 and reducing long-run Federal budget deficits. The Act includes important changes in the way Medicare pays doctors, hospitals, and other health care providers to create strong incentives for providers to redesign the way they deliver care, both to improve health and to use scarce resources more efficiently. The Medicare Shared Savings Program, for example, encourages physicians, hospitals, and other organizations to form Accountable Care Organizations (ACOs) to provide cost-effective, coordinated care to Medicare beneficiaries. Both the Shared Savings program and a similar Affordable Care Act initiative developed through the Center for Medicare and Medicaid Innovation (the Innovation Center) reward ACOs that are able to reduce the growth in health care spending while achieving high standards for clinical quality and patient satisfaction. The mission of the Innovation Center is to help transform the Medicare, Medicaid, and CHIP programs to deliver better health care, better health, and reduced costs. The center’s portfolio of initiatives includes demonstration projects that test new strategies for providing higher-quality health care more efficiently. These strategies include models of enhanced primary care; the use of episode-based bundled payments to improve care coordination; and a challenge grant program that will award up to $1 billion in grants to applicants who will implement the most compelling ideas for delivering better health, improved care, and lower costs to people enrolled in Medicare, Medicaid, and CHIP. Because of Medicare’s outsized role as a purchaser of health care, these initiatives are likely to spur similar innovations by private insurers. Retirement Security For older Americans, retirement savings in combination with Social Security benefits are a critical element of the safety net. These savings and benefits together allow retirees to maintain the living standards they had during their working lives and to protect themselves against downturns in the financial markets, unexpectedly high health care costs, and the risk of running down one’s assets. In addition, some Americans elect to accumulate additional savings in hopes of bequeathing assets to their heirs. From a broader societal perspective, private retirement savings fuel capital accumulation. Capital thus accumulated leads to greater investment, which in turn leads to a more productive workforce and stronger economic growth. In this sense, saving not only bolsters the standard of living in retirement for participating workers but also raises the quality of life for future generations. Over the years, policymakers have implemented a variety of policies to encourage capital accumulation, to protect retired households against 220 | Chapter 7 economic shocks, and to increase the likelihood that Americans enjoy the same quality of life during retirement that they enjoyed during their working years. The most prominent of these programs is Old Age and Survivors’ Insurance, also known as Social Security, which pays retiree benefits to more than 95 percent of elderly individuals in the United States. Social Security is the nation’s retirement security bedrock, paying out $596.7 billion to 44.4 million beneficiaries in 2011—an average annual benefit of $13,561. Social Security payments, combined with private savings and employer-provided retirement benefits, provide sufficient income to enjoy a comfortable retirement, and for many others, make the difference between meeting basic needs and living in poverty. In 2010 Social Security income lifted an estimated 13.8 million elderly Americans out of poverty. The program also provides a key safety net for survivors of deceased workers, helping roughly 6 million surviving spouses and children. Even as Social Security helps provide a stable source of income in retirement, tax preferences for retirement saving give working-age households greater incentive to accumulate assets toward retirement. Most tax-preferred accounts allow workers and their employers to make pre-tax contributions to a retirement account and also allow earnings on those contributions to accumulate tax-free; other accounts allow after-tax contributions to grow and be withdrawn tax-free. Many American households have responded to these tax incentives by building assets toward retirement, with total balances in defined-contribution and individual retirement accounts (IRAs) rising to nearly $9.2 trillion in 2010. The overall tax expenditure for the principal retirement saving incentives is substantial, totaling almost $120 billion in fiscal year 2010. Declining Retirement Preparedness Despite the availability of tax-related incentives to spur saving, many households have not accumulated sufficient assets to overcome the potential risks faced in retirement. By some estimates, the proportion of households with adequate retirement saving has been in decline for decades. As illustrated in Figure 7-6, the share of households “at risk” of experiencing marked declines in consumption in retirement rose from 31 percent in 1983 to 51 percent in 2009, with much of the recent change owing to declining housing values.2 For members of Generation X (individuals born between 2 These estimates are based on the National Retirement Risk Index (NRRI) produced by the Center for Retirement Research at Boston College. For each household, the NRRI estimates household income in retirement (based on projected assets at retirement) as a share of pre-retirement earnings; this percentage represents the replacement rate of pre-retirement earnings. Each household is assigned a benchmark “adequate” replacement rate; households that are more than 10 percent below the benchmark are deemed to be “at risk.” Preserving and Modernizing the Safety Net | 221 the mid-1960s and 1972), the situation is even more troubling, with nearly three in five households in that age group in danger of becoming unable to maintain their living standard in retirement (Munnell, Webb, and GolubSass 2009). Although retirement preparedness has been in decline in the aggregate, specific demographic groups are particularly vulnerable. Single individuals and low-income households are all especially likely to enter retirement with insufficient assets. For example, one estimate for 2009 identified 60 percent of low-income households as inadequate savers, compared with 42 percent of high-income households (Munnell, Webb, and Golub-Sass 2009). Another estimate found that 60.2 percent of single men had insufficient retirement wealth to maintain preretirement consumption, compared with 45.2 percent of married couples (Haveman et al. 2006). Recent economic shocks have impacted individuals nearing retirement. Between 2007 and 2009, Americans aged 55 to 64 saw their real median household income decline by 5 percent and their median net worth fall 15 percent—from $258,000 to $222,000 (Bricker et al. 2011). In addition, the value of housing—a key source of wealth for older Americans—has dropped 34 percent since the housing market’s peak in April 2006. The value of financial assets also declined precipitously following the financial crisis and has yet to rebound fully to pre-recession levels. The combination of declining asset values and lower income has further weakened retirement preparedness. Challenges to the Retirement Safety Net Several developments have contributed to the problem of inadequate retirement saving. A first-order concern is declining participation in employer-sponsored retirement plans. Between 2000 and 2010, the share of private sector workers between the ages of 21 and 64 who participated in an employer-sponsored retirement plan fell from 48 percent to 39 percent. The past several decades have also seen changes in the nature of private employer retirement plans. The share of private-sector workers covered by defined-benefit pension plans fell from 38 percent in 1980 to 20 percent in 2008 as many private employers switched to defined-contribution plans like 401(k) plans. Section 401(k) and other defined-contribution plans offer workers particular benefits, such as portability, high potential for growth, and flexibility. However, the shift to 401(k) plans (and to a lesser degree a shift from traditional defined-benefit pensions to hybrid defined-benefit plans such as cash balance plans) has also transferred substantial risk away from employers, placing greater responsibility on workers to accumulate and manage assets and exposing them to greater financial risk. 222 | Chapter 7 Figure 7-6 The National Retirement Risk Index, 1983–2009 Percent of households "at risk" 60 51 50 40 36 31 31 30 1983 1986 1989 30 38 40 43 44 2004 2007 38 20 10 0 1992 1995 1998 2001 2009 Source: Munnell, Webb, and Golub-Sass (2009). To take full advantage of the wide array of incentives for retirement saving, workers must assess complex details associated with establishing an account, making contributions, managing investments, and eventually making withdrawals. In the face of complex saving and investment decisions, some workers put off enrolling in employer-sponsored retirement programs or taking advantage of tax-preferred saving vehicles outside of employment. Such delays are costly in terms of lifetime asset accumulation. (See Economics Application Box 7-1 for more information on common mistakes made by retirement savers.) Another challenge to the retirement safety net is the uneven distribution of the benefits of the tax code’s generous incentives for retirement saving. Because these tax incentives are often provided as a deduction or exclusion from income, they are most valuable for taxpayers in higher tax brackets. In the aggregate, these incentives flow disproportionately to upperincome households; almost 80 percent of the total tax benefit is projected to go in 2012 to the richest 20 percent of households and more than 40 percent to households in the top 5 percent of the income distribution (Toder, Harris, and Lim 2011). The availability of employer-sponsored retirement saving options also varies by firm size. As with health insurance, small employers face significant challenges in establishing retirement plans. High per-participant Preserving and Modernizing the Safety Net | 223 administrative costs, frequent employee turnover, uncertain revenues, and lack of familiarity with plan design and characteristics all discourage small business owners from providing retirement plans. Their inability to provide these plans not only threatens retirement security for employees of small businesses but also can make small businesses less attractive to workers than larger employers are. These obstacles to retirement saving keep account balances low for many households. In 2011, more than half of all workers reported that the total value of their household’s savings is less than $25,000; 29 percent said they have less than $1,000 in savings (Helman, Copeland, and VanDerhei 2011). Although some of these workers may participate in defined-benefit pensions, others will enter retirement with little income outside of Social Security. One analysis of households aged 65 to 69 in 2008 showed that the median household had just $15,000 in financial assets and $5,000 in private retirement assets (Poterba, Venti, and Wise 2011). Most households in the sample had more wealth in housing equity than in liquid assets (Table 7-2). One of the toughest retirement challenges involves uncertainty about how long retirees are likely to live. With extended longevity comes the possibility that an individual will live longer than expected and will thus outlive his or her accumulated assets. This possibility increases as the time between retirement and expected age of death lengthens. In 1970 a worker retiring at age 65 could expect to live another 15.2 years; by 2008 that figure had grown to 18.7 years. Although extending life expectancy is an exceptional achievement for the United States, it also increasingly exposes retirees to the risk of outliving their assets outside of Social Security. In 2010, just 17 percent of Americans aged 65 to 69 relied on Social Security for more than 90 percent of their income, but the share almost doubled, to 33 percent, for Americans age 80 and older (Figure 7-7). Another serious risk is costly health shocks. Even with the protection provided by Medicare, many retirees face high out-of-pocket health expenditures, diminishing their retirement assets and threatening their well-being. Recent research estimates that for a 65-year-old couple, the expected present value of lifetime out-of-pocket medical costs exceeds $250,000, with a 5 percent risk that expenses will exceed $570,000 (Webb and Zhivan 2010). As discussed in Data Watch 7-1, out-of-pocket health costs can push retirees into poverty. The risk of large health expenditures and the possibility of outliving one’s assets force retirees to face difficult decisions about how much of their assets to consume in any given year. Uncertainty about lifespan, inflation, investment return, and unexpected medical expenses makes the “decumulation decision”—how much to withdraw from accumulated 224 | Chapter 7 Table 7-2 Distribution of Wealth Components for Households Aged 65–69, 2008 Thousands of dollars Financial assets Personal retirement account assets Financial + personal retirement account Housing equity Definedbenefit pension Social Security Net worth 10 0.0 0.0 0.0 0.0 0.0 0.0 197.0 20 0.3 0.0 0.8 5.0 0.0 154.3 297.3 30 2.0 0.0 5.5 42.0 0.0 214.5 413.6 40 6.0 0.0 20.0 80.0 0.0 267.9 564.0 50 15.0 5.0 52.0 120.0 0.0 315.3 731.1 60 32.0 28.8 104.0 162.0 25.3 379.0 898.4 70 70.0 75.0 195.0 229.5 116.8 463.3 1,146.4 80 145.0 142.0 375.0 349.2 238.5 542.9 1,483.4 90 358.0 347.0 711.0 585.0 468.9 643.1 2,103.0 Percentile Source: Poterba, Venti, and Wise (2011). saving—exceptionally complicated. Retirees who live longer than expected might find themselves with insufficient assets in the later years of life, at a time when they are most vulnerable and in need of a reliable stream of income. While private annuities can serve to mitigate many of these risks, annuities markets face a host of obstacles including regulatory barriers, Percent 100 Figure 7-7 Percent of Individuals with Various Shares of Family Income from Social Security, by Age of Householder, 2010 less than 50% 50-90% more than 90% 90 80 70 48% 44% 38% 63% 60 50 40 30 27% 28% 19% 20 10 29% 17% 25% 28% 33% 0 Age 65 to 69 Age 70 to 74 Age 75 to 79 Over age 80 Source: Current Population Survey, Annual Social and Economic Supplement. Preserving and Modernizing the Safety Net | 225 Economics Application Box 7-1: Financial Literacy and Common Mistakes Made by Retirement Savers A generation ago, when many workers were covered by definedbenefit plans, retirement savings decisions were relatively easy. Today, workers must take much more responsibility for ensuring that they have adequate income throughout retirement. Achieving that goal requires avoiding some mistakes commonly made in saving for retirement. Below is a list of five mistakes that people often make. Missing out on the tax benefits of saving. The tax code affords strong incentives for retirement saving. Participation in an employer-sponsored retirement plan or individual retirement account can yield thousands of dollars of extra retirement wealth over time. In addition, low- and middle-income households can take advantage of the Saver’s Credit, which effectively provides workers with a Government match on new saving. Workers can substantially increase their retirement savings by contributing early and taking advantage of tax benefits for retirement saving. For example, if a 25-year-old contributes $1,000 toward retirement in a taxable account, that $1,000 can be expected to grow to approximately $7,300 in today’s dollars by the time the worker reaches age 65. Taking advantage of tax benefits for saving can substantially increase this amount. If the same worker contributes $1,000 to a Roth IRA, that $1,000 can be expected to grow to nearly $10,300 in today’s dollars by the time the worker reaches age 65. As illustrated in the figure below, the benefits of tax-preferred saving increase over time. Simulated Accumulation for an Intial $1,000 Contribution to a Taxable Account or Roth IRA, 2012–2052 Dollars (2012) 12,000 10,000 8,000 6,000 4,000 Roth IRA Taxable Account 2,000 0 2010 2015 2020 2025 2030 2035 2040 2045 2050 Note: Calculations assume a 6 percent real rate of return and 15 percent tax rate. Source: CEA calculations. 226 | Chapter 7 Failing to participate in an employer-sponsored retirement plan. Some employer-sponsored retirement plans provide an employer match for money that an employee deposits into a retirement account. Taking advantage of an employer match is one of the best ways to leverage retirement contributions and rapidly accumulate saving. Many workers, especially new hires and young employees, however, leave this “free money” on the table by failing to sign up for a retirement plan. In 2001, only 57.5 percent of workers aged 20–29 participated in a company retirement plan even when one was offered (Kawachi, Smith, and Toder 2006). Failing to diversify retirement savings. Investment needs and risk appetites vary across households. However, concentrating all assets in one particular type of investment can prove risky, especially if that asset is stock in an employee’s company. One study found that in 2002, nearly 4 million workers invested in excess of 80 percent of their employer retirement plan assets in own-company stock (Mitchell and Utkus 2002). In general, investors can protect themselves against risk by spreading their assets across various types of investments. Losing investment returns to high fees. High fees can inhibit rapid accumulation of retirement wealth. Savers should pay attention to all investment fees, including those charged at purchase of a mutual fund, ongoing fees, fees charged by brokers and registered investment advisors, and fees charged on the purchase of annuity products. Although these fees are ordinarily charged for legitimate services provided, investors should incorporate the cost of fees in their purchase decisions. Cashing-out retirement savings. When workers leave a job, some fail to rollover their pension wealth into an IRA and pay a penalty for cashing out their retirement savings. These leakages in retirement savings make it difficult to arrive at retirement with adequate amounts of savings. In 2006, workers aged 15 to 60 cashed out $74 billion in retirement assets when changing jobs (GAO 2009). Failing to protect against longevity and health care risk in old age. As lifespans increase, more Americans will face the prospect of running out of money in old age. Planning for and protecting against the risk of outliving family assets as well as the need for long-term care is an essential part of the retirement security picture. Preserving and Modernizing the Safety Net | 227 behavioral aversion to annuities, and inadequate savings to purchase an annuity (Benartzi, Previtero, and Thaler 2011). Policies to Address Retirement Saving Challenges The President has proposed several policies to bolster Americans’ retirement saving behavior and lead to a more secure retirement for millions of families. Perhaps the most significant policy is the establishment of automatic IRAs for tens of millions of workers. This proposal builds on a broad literature showing that automatic enrollment can dramatically increase participation rates in workplace retirement plans. For example, Madrian and Shea (2001) show that the participation rate after one year of employment at a large corporation increased from 37.4 percent to 85.9 percent following the adoption of automatic enrollment. The President’s proposal would require most firms without qualified employee retirement plans to offer employees an automatic IRA option. By default, automatic IRA contributions would be funded by payroll deductions equal to 3 percent of pay, unless employees opted out of the program or elected to contribute a different amount. Firms would not contribute on behalf of the employee, and companies offering the automatic IRA to workers could claim a tax credit for the employer’s associated expenses up to $500 for the first year and $250 for the second year along with an additional tax credit of $25 per employee—up to a maximum of $250 a year for six years. The automatic IRA would transform the retirement saving landscape. Employees who previously accumulated little or nothing toward retirement would begin accumulating assets immediately. Upward of 40 million workers, all previously ineligible for workplace retirement saving plans, would be covered by the new proposal. About 80 percent of these workers would be low- and middle-income employees with less than $50,000 in annual wages, indicating that the IRA would primarily be targeted at workers who are more likely to have accumulated little savings. The Administration also proposes to increase the tax credit for small businesses that adopt, for the first time, a qualified employee retirement plan. Under current law, small businesses can receive up to $500 in tax credits—each year for up to three years—for establishing an employee retirement plan. The President proposes to double the maximum credit to $1,000 annually to provide a stronger incentive for small employers to establish workplace retirement plans. The Administration’s Budget eases the compliance burden for retirement savings by exempting retirees with modest accumulated saving from minimum required distribution (MRDs) rules. MRDs are established to ensure that retirees with high accumulated retirement assets direct those 228 | Chapter 7 assets towards retirement, and not use retirement accounts to shelter their income from estate taxes. The Administration proposes to exempt retirees with less than $75,000 in retirement savings from these rules. This move would simplify tax compliance for millions of elderly Americans, who would no longer need to calculate the amount and timing of their minimum required payouts. It would give millions of seniors greater freedom of choice as to when and how rapidly to spend their limited assets in retirement, while also adding flexibility to purchase lifetime income products—such as longevity annuities—that might violate MRD regulations. The Administration has made a commitment to financial literacy as a means of assisting Americans in making sound decisions regarding saving and investment. In 2010, the President signed an Executive Order creating the President’s Advisory Council on Financial Capability to assist the American people in understanding financial matters and making informed financial decisions. In addition, the Wall Street Reform and Consumer Protection Act of 2010 created the Consumer Financial Protection Bureau, which is charged with educating consumers about financial matters and enabling them to make sound financial decisions. And, in 2011, the Financial Literacy and Education Commission, established to coordinate Federal efforts to promote financial literacy, developed a new national strategy to enable Federal agencies to coordinate and promote all the Federal initiatives aimed at helping Americans make better financial choices. Taken together, these policies will lead to a more inclusive retirement saving landscape. Workers who would defer retirement saving because of financial inertia or behavioral obstacles will automatically be put on a path toward better saving. Easing MRD rules will simplify financial decisions in retirement for millions of elderly Americans. A coordinated national financial literacy campaign will help Americans become more active savers and will lead to improved investment decisions and smarter consumer behavior. More active saving, coupled with improved investment behavior, will increase the level of assets earmarked for retirement saving, leading to a more stable retirement for millions of Americans. Conclusion A strong and dynamic economy requires a robust and modern safety net to protect families against economic shocks and to provide a level of security that promotes entrepreneurship and economic growth. The challenging economic times of the past decade have made clear the important role that public policy can play in this area. In particular, unemployment insurance benefits, the Earned Income Tax Credit, and the Supplemental Preserving and Modernizing the Safety Net | 229 Nutrition Assistance Program have kept millions of American families out of poverty. Medicaid and the Children’s Health Insurance Program have ensured that children are able to maintain health insurance coverage even if their parents lose access to employer-sponsored plans. New policy initiatives will further strengthen the safety net. Although the current system of unemployment insurance has provided critical support for dislocated workers, the system can be modernized and improved. The President has proposed a number of innovative programs that would make it easier for jobless workers to invest in new skills or even start their own businesses. These proposals build on current programs that have been proven to work. The Affordable Care Act represents the most significant improvement in the health care safety net since the advent of Medicare and Medicaid in the mid-1960s. By 2019, the Act is expected to increase the number of Americans with health insurance by over 30 million, and it will put in place new consumer protections ensuring that health insurance coverage remains available and affordable for all Americans regardless of an individual’s health status or medical history. In the area of retirement security, the President has proposed a number of policies that will boost retirement savings, making it more likely that Americans will enter retirement with adequate assets to maintain their desired level of consumption. These efforts to strengthen the safety net will provide tangible benefits for the economy and families in the coming decades. 230 | Chapter 7 C H A P T E R 8 IMPROVING THE QUALITY OF LIFE THROUGH SMART REGULATION, INNOVATION, CLEAN ENERGY, AND PUBLIC INVESTMENT R ecent years have seen an unprecedented number of official efforts to improve, develop, and implement new measures of the quality of life and economic performance. Much of the groundwork for these efforts was laid in two important National Research Council reports. Nature’s Numbers, published in 1999, considered how to expand the national income accounts that track the country’s economic activity to properly take into account the environment and natural resources. Beyond the Market, published in 2005, proposed ways to integrate nonmarket activity into the accounts. This work has implications for economic policy. Carefully designed regulations can promote economic growth and improve the Nation’s quality of life. Water pollution, for example, can cause illness and destroy the livelihood of fishermen and others who rely on a healthy ecosystem to earn a living. Pollution, as Robert Kennedy noted, does not subtract from the gross domestic product. Appropriately balanced efforts to restrict harmful pollution can improve economic performance along with the health and safety of Americans. The theme of this chapter is that, properly measured, both economic growth and the Nation’s well-being can be increased by smart regulation, innovation and public investment in such fields as medical research, clean domestic energy and transportation infrastructure. 231 A Smart Approach to Regulations For more than a century, the United States has been a world leader in protecting the health and safety of its citizens through well-chosen regulations. Fuchs (1998 and 2010) attributes gains in life expectancy prior to World War II to improvements in “nonmedical factors: nutrition, sanitation, housing, and public health measures.” For example, in response to yellow fever and cholera outbreaks caused by water pollution, the Rivers and Harbors Act of 1899 gave the Army Corps of Engineers the authority to regulate the discharge into waterways of “refuse matter of any kind or description.” Similarly, public health concerns about unsanitary meat packing conditions and patent medicines containing narcotics gave rise to the Pure Food and Drug Act of 1906, which authorized the Food and Drug Administration (FDA) to inspect food and drug products and regulate their sale. In 1900, roughly one in every 200 Americans was addicted to narcotics found in patent medicines (DOJ n.d.). Following the disclosure requirements in the Pure Food and Drug Act, sales of patent medicines containing those substances fell by nearly a third (Musto 1999). As society evolves and technology changes, such basic protections afforded to citizens through regulation are updated and improved. Today, the water pollution controls provided for in the Rivers and Harbors Act have been incorporated into more expansive provisions in the Clean Water Act of 1972 and the Safe Drinking Water Act of 1974, which enable the Environmental Protection Agency (EPA) to promulgate regulations with the goal of making U.S. waters safe for drinking, swimming, and fishing. Similarly, the Pure Food and Drug Act of 1906 was amended by the Food, Drug, and Cosmetic Act of 1938 to give the FDA the authority to require evidence of safety for new drugs and to tighten food quality standards. It was amended again in 1962 to require manufacturers to prove drug effectiveness (Randall 2001). Most recently, the Food Safety Modernization Act of 2010 further improved the safety of food sold in the United States by, among other provisions, giving the FDA the authority to directly issue mandatory food recalls, requiring food processors to have plans in place for addressing safety risks, and requiring importers to verify food safety. Measuring the benefits of regulations for the quality of life is a formidable task. Some forms of regulation have a positive effect on economic growth, for example, by improving the health and vitality of the workforce, by promoting stable and efficient operation of financial markets, by speeding the adoption of energy-saving technologies, by improving educational outcomes, or by upgrading the operation of the transportation system. Much of the benefit from those types of regulations eventually translates 232 | Chapter 8 into increases in GDP. In other cases, such as the protection of the National Park System, safeguards against invasive species, or cleaner lakes for swimming and fishing, the benefits of regulation help the economy, but are less easily charted in the national accounts. For example, increased tourism or higher returns to commercial fishing resulting from cleaner water would be reflected in GDP, whereas the public’s increased appreciation of that cleaner water would not be. Designing Smart Regulations On January 18, 2011, President Obama issued Executive Order 13563, “Improving Regulation and Regulatory Review,” which lays out a balanced approach to regulation—to protect the health and safety of the American people in a way that maximizes net benefits to society, that uses the best information available, and that avoids unnecessary or overly burdensome requirements. The President called for an agency-wide review to reduce burdensome regulations. Underlying that approach is a belief that a smart, effective regulatory system depends on careful analysis of costs and benefits, both before and after regulatory action, including an informed public discussion. The Executive order directs the Office of Information and Regulatory Affairs (OIRA) of the Office of Management and Budget (OMB) to provide oversight, transparency, and discipline for executive agencies in the regulatory process, and coordinates that interagency review of rulemakings to ensure that regulations are consistent with applicable law. The net benefits of regulations finalized in 2011 are expected to be at their highest level in the last 10 years. And monetized savings from the retrospective review of regulations called for in the new Executive order are likely to exceed $10 billion over the next five years. Many of those regulations are intended to improve the quality of life by correcting market failures that lead to unsafe living or working environments. Effective regulations put into place rules that correct for significant market failures and thus achieve greater social benefits. “Smart regulations” are those that maximize the net benefits of a regulatory action to society. Benefit-cost analysis attempts to quantify and assign dollar values to the various effects of a regulation, which can be used to determine how it can reach its goal in the most efficient manner—that is, how it can generate the largest net benefits (the difference between total benefits and total costs) to society. Such information is useful for both policymakers and the public, even when economic efficiency is neither the only nor the overriding public policy objective, as in the case of protecting privacy. Benefit-cost analysis is used to estimate likely future benefits and costs of a proposed regulation, but it can also be used to “look back” at existing Improving the Quality of Life through Smart Regulation, | 233 Innovation, Clean Energy, and Public Investment regulations, based on evidence about the actual, realized benefits and costs of those regulations. Such retrospective analyses can be used both to improve existing regulations and to better evaluate new ones. Smart regulations thus seek to use the best information available in order to maximize net benefits by setting regulatory stringency at the most efficient level—the point at which the incremental benefits are equal to the incremental costs. For example, even though the marginal costs of seat belt standards increased over time (front-seat shoulder and rear-seat lap belts were mandated for cars in 1968 and for light trucks and vans in 1971, and three-point belts were required in the mid-1970s), those costs were far outweighed by the corresponding number of lives saved per year by seat belts (DOT 2004; Kahane 2004). The buckle-up laws of the mid-1980s raised the number of lives saved by wearing seat belts to 6,000 a year by 1988–90, and subsequent increases in belt use raised the annual number of lives saved to more than 15,000 in each year from 2003 to 2007. All together, between 1975 and 2009, seat belt regulations saved an estimated 268,000 lives (Kahane 2004; DOT 2009). (For another example of how benefit-cost analysis works, see Economics Application Box 8-1.) Smart Regulations in Practice Benefit-cost analysis has long been used to evaluate regulations within the Federal Government. For example, the Flood Control Act of 1936 declared that “the Federal Government should improve or participate in the improvement of navigable waters or their tributaries including watersheds thereof, for flood-control purposes if the benefits to whomsoever they may accrue are in excess of the estimated costs, and if the lives and social security of people are otherwise adversely affected.” The use of benefit-cost analysis in evaluating Federal regulations has become widespread since 1981, when President Reagan issued Executive Order 12291, formally requiring that “regulatory action shall not be undertaken unless the potential benefits to society for the regulation outweigh the potential costs to society and that regulatory objectives shall be chosen to maximize the net benefits to society.” President Clinton issued Executive Order 12866, which focused OIRA oversight on “significant” rules and increased transparency. As noted earlier, President Obama issued Executive Order 13563, which reaffirms the principles in Executive Order 12866 and outlines a regulatory strategy to support continued economic growth and job creation. In particular, Executive Order 13563 offers new directions for regulatory review, including a requirement that agencies “use the best available techniques to quantify anticipated present and future benefits and costs as accurately as possible” while authorizing consideration of “values that are 234 | Chapter 8 difficult or impossible to quantify, including equity, human dignity, fairness, and distributive impacts.” Based on the quantified benefits and costs in current regulations, smart regulations are generating the highest level of net benefits for U.S. citizens in the last decade. In calendar year 2011, the Administration completed 740 regulatory reviews, 336 of which were interim final or final rules from executive agencies. Of the interim final and final rules reviewed, 18 percent were “economically significant,” meaning that they are anticipated to have an effect on the economy of more than $100 million in any given year. Those economically significant rules are expected to result in $15 billion in costs and $116 billion in benefits annually (in 2001 dollars). Over the past three calendar years, the annualized net benefits of completed rules have totaled about $155 billion. In 2011 alone, annualized net benefits totaled more than $101 billion. Those figures reflect an estimate of not only purely monetary savings, but also an estimate of the monetary value of prevented deaths, illnesses, and injuries. Figure 8-1 shows the benefits and costs of regulations, which are detailed in the agencies’ Regulatory Impact Assessments for each economically significant rule and summarized annually in OMB’s annual Regulatory-Right-to-Know report to Congress. Data and estimation methods have improved substantially over time, as have modeling tools for projecting a regulation’s effect into the future. For Figure 8-1 Benefits and Costs of Regulations, 2001 ─2011 Billions of 2001 dollars 140 120 Total benefits 100 80 60 40 20 Net benefits Total costs 0 2001 2003 2005 2007 2009 2011 Note: Total benefits, total costs, and net benefits are based on the midpoints of agency estimates for regulations completed during the calendar year. Source: Office of Information and Regulatory Affairs. Improving the Quality of Life through Smart Regulation, | 235 Innovation, Clean Energy, and Public Investment Economics Application Box 8-1: Comparing Benefits and Costs How do policymakers determine whether a regulation is a smart regulation? For example, in 2007, the Department of Transportation (DOT) decided to require that all new passenger vehicles weighing less than 10,000 pounds be equipped with electronic stability control (ESC) systems, which reduce crashes by improving braking in critical situations when the driver is beginning to lose control. This rule will increase the fraction of new vehicles with ESC from 29 percent in 2006 to 100 percent in 2012. How did the DOT decide this was a smart regulation? First, the DOT identified what is arguably a market failure: a relatively affordable technology existed that lowered the risk of a crash, but it was not being offered by some manufacturers and, when offered the choice, many consumers declined. This market failure was caused by asymmetric information (drivers purchasing a vehicle could not fully assess the protection afforded by ESC systems) and by a negative externality (consumers purchasing a car without an ESC system did not fully account for the risks of a crash to others).a Second, the DOT then examined the likely costs and benefits of equipping all passenger cars and light trucks/vans with ESC by model year 2012. Approximately 17 million vehicles will be subject to this regulation; however, DOT estimates that as of 2011, manufacturers would have installed ESC in 71 percent of their fleet absent the rulemaking. Therefore, both the benefits and costs were calculated by raising ESC installation from that baseline of 71 percent to 100 percent. The benefits of the rule include reductions in fatalities, injuries, property damage, and travel delays, all resulting from fewer accidents. To monetize those benefits, the DOT multiplied the total number of loss-of-control crashes by the average effectiveness of ESC systems and found that 67,000– 91,000 crashes would be avoided each year. Using historical accident data, DOT estimated that a decline of 67,000 crashes would reduce total annual fatalities by 1,547 and decrease total annual injuries by 46,896.b The monetary value of those benefits depends on the discount rate, that is, on how much benefits in the future are worth today (a high discount rate implies that people discount the future more and thus any benefits that accrue in the future would be valued less today). At a 7 percent discount rate, the reduction in injuries and fatalities translates into $6.4 billion in benefits; at a 3 percent discount rate, those benefits are $8.0 billion, as the Box Table shows. To determine the noninjury component of benefits, the DOT multiplied the individual unit costs for travel delays and property damage by the 67,000 crashes that would be prevented by the rule, yielding $247 million in benefits at the discount rate of 7 percent. 236 | Chapter 8 Annual Costs and Benefits by Discount Rate Millions of 2005 dollars Injury and fatality benefits Savings from reduced property damage and travel delays 3% discount 7% discount $7,965 $6,360 309 247 Total benefits 8,274 6,607 Vehicle costs 985 985 Fuel costs 27 22 Total costs 1,012 1,007 Net benefits 7,262 5,600 Note: Vehicle costs are not discounted, because they occur when the vehicle is purchased, whereas benefits occur over the vehicle’s lifetime and are discounted back to the time of purchase. Source: Department of Transportation, National Highway Traffic Safety Administration (2007). The DOT determined that production costs would rise by between $111 and $479 for each affected vehicle, depending on whether the vehicle was already equipped with anti-lock braking systems, a necessary component of ESC. The expected costs of the standard above the baseline total $985 million. Because the average weight of passenger cars is expected to increase by 2.1 pounds as a result of the new equipment, the lifetime fuel use of those vehicles is expected to go up by 2.6 gallons. At discount rates of 7 percent and 3 percent, the total additional fuel costs are $21.8 million and $26.8 million, respectively. Summing vehicle and fuel costs gave the total costs of the regulation: about $1.0 billion. Net benefits, then, are the difference between total costs and total benefits, or between $5.6 billion and $7.3 billion each year for the lower range of accident prevention. a For further discussion of market failures and automobile safety standards, see Mannering and Winston (1995), Arnould and Grabowski (1981) and Viscusi and Gayer (2002). b The appropriateness of including private benefits net of private costs in a benefit-cost analysis varies from rule to rule. By including private net benefits— the value of reducing injuries and fatalities of the consumers minus the purchase cost of the technology—the DOT is making the implicit assumption that consumers have made a suboptimal purchasing decision (one of the market failures being addressed by the regulation). However, if consumers do not face an information problem, a traditional approach would assume that consumers have made the purchasing decision that maximizes their welfare. If this were the case, it would be inappropriate to include those private net benefits in the analysis. For further discussion, see Gayer (2011). Improving the Quality of Life through Smart Regulation, | 237 Innovation, Clean Energy, and Public Investment example, the health benefits from reducing different air pollutants over different time periods and populations have been estimated by epidemiologists using air quality monitoring data and various health endpoints (EPA 2011a). Improvements in computing power and data records now allow air quality modelers to forecast the effects of regulatory actions on future air quality under different scenarios. Combining those estimates allows policymakers to weigh the expected health results of a given air quality regulation with the expected costs associated with the controls required by the rule. A peer-reviewed study by the EPA using the Criteria Air Pollutant Modeling System estimated that the Clean Air Act prevented more than 160,000 premature deaths, 54,000 cases of chronic bronchitis, 130,000 nonfatal heart attacks, and 1.7 million cases of asthma exacerbation between 1990 and 2010. Those adverse health outcomes could have led to 86,000 emergency room visits for respiratory problems, 3.2 million lost school days, and 13 million lost work days (EPA 2011b). Some health benefits from Clean Air Act regulations will likely raise economic growth indirectly and over time through intermediate factors. For example, a healthier population will arguably be a more productive one, a change that can be measured in improved labor productivity. A growing consensus has identified certain of those intermediate drivers of growth, including increased human capital, capital investment, research and development, economic competition, physical infrastructure, and good governance. Some evidence strongly suggests that regulations promoting educational attainment may improve human capital accumulation, thereby increasing economic growth over time (for example, see Cohen and Soto 2007). Other studies show a positive link between increased life expectancy and economic growth. A survey of the existing literature on health and economic outcomes (Bloom et al. 2004) finds in cross-country analysis that a one-year increase in life expectancy generates a 4 percent increase in economic output, controlling for other variables. Similarly, Murphy and Topel (2006) find that progress made battling various diseases after 1970 added about $3.2 trillion a year to national wealth. Retrospective Analysis The prospective benefit-cost analysis that goes into crafting smart, efficient regulations is necessarily fraught with uncertainty. Prospective analysis requires that the costs and benefits of a regulation be identified and quantified before (ex-ante) the regulation is implemented. Only after a 238 | Chapter 8 regulation has gone into effect can its actual (ex-post) effects become known (see Data Watch 8-1).1 Changes in technology often make pollution abatement cheaper. For example, the actual costs to utilities of the cap-and-trade system for sulfur dioxide allowances set up by the Clean Air Act Amendments of 1990 were much lower than had been predicted. Scrubbing technologies turned out to be more efficient at removing sulfur dioxide from emissions, and power plants were able to blend a higher percentage of cheaper, low-sulfur coal than had initially been assumed. Moreover, the benefits of reducing sulfur dioxide emissions have since been found to be much larger than originally thought. As a result, subsequent regulations for utilities have tightened controls on those emissions. Similarly, during the 1970s, automobile technologies were improved by new pollution standards. Regulators were phasing lead out of gasoline, and again the costs of the regulation were overestimated and the benefits underestimated. Lead impairs brain development in children and has been linked to serious health problems in adults such as hypertension, heart attacks, and premature death (Lovei 1998). Concern about high blood lead concentrations in the U.S. population led the EPA to begin in 1974 to phase in a stringent standard reducing the amount of lead allowed in the gasoline supply. Subsequent studies found that the annual benefits of banning lead in gasoline would be more than $6 billion (in 1983 dollars), but would cost around $500 million a year (Schwartz 1985). Harrington, Morgenstern, and Nelson (1999) note that those costs may have been overstated, but that it was difficult to disentangle the effects of a phase-out of leaded gasoline from the much larger effect of changes in oil markets around that time. Research also found that the benefits of lowering lead exposure were greater than initially thought. The EPA’s 1985 benefit estimate implied that reducing mean blood lead concentrations in the population by 1 microgram per deciliter (or 1 µg/ dl) was worth at least $3.5 billion a year (Schwartz 1994). By 1994, however, researchers were finding that a reduction of 1 µg/dl in mean blood lead concentrations resulted in much greater benefits than earlier estimates—as high as $17.2 billion a year (1989 dollars) (Schwartz 1994). The phase-out of leaded gasoline was completed in 1995; by then the average blood lead concentration was approximately 2.3 µg/dl, down from more than 15 µg/dl in the early 1970s (Weaver 1999). 1 Retrospective analyses of benefits and costs are also subject to uncertainty, because they require evaluation of a counterfactual scenario in which the rule was not adopted. Identifying that counterfactual is often difficult, in part because changes that occurred due to the rule are difficult to distinguish from changes that the industry would have adopted voluntarily. Improving the Quality of Life through Smart Regulation, | 239 Innovation, Clean Energy, and Public Investment Data Watch 8-1: The Value of Information—the PACE Survey One of the few data sources for benchmarking costs of air and water pollution controls is the Pollution Abatement Costs and Expenditures (PACE) survey, which recently has been funded by the Environmental Protection Agency (EPA) and administered by the Census Bureau. From 1973 to 1994, the PACE survey was administered annually to nearly 20,000 manufacturing and mining facilities and electric utilities. Since 1994, because of resource constraints, the Census Bureau has conducted this survey only twice (for 1999 and 2005). To estimate the overall regulatory burden facing American manufacturers, the PACE survey collects data on overall pollution abatement expenditures by manufacturers for treatment, prevention, recycling, and disposal, rather than trying to allocate costs to specific regulations. It is the only survey that measures environmental compliance costs at both the individual and aggregate levels (Ross et al. 2004). Pollution equipment expenditures have fallen over time, on average accounting for 7 percent of all investments made by manufacturing industries in the early 1990s and 4 percent in 2005. There is considerable variation in spending across industries, but given that pollution levels (and the negative externalities associated with pollution) also vary by industry, that is neither surprising nor necessarily suboptimal. The EPA has used PACE data to estimate the cost of both past and proposed regulations (see for example, Gallaher, Morgan and Shadbegian 2008). Academics have used the data set to investigate the relationship between EPA regulations and economic outcomes. For example, Levinson (1999) used the PACE data to develop a new index of state environmental compliance costs. Similarly, Shadbegian and Gray (2005) examined the relationship between of pollution abatement and productivity. And Becker (2005) found expenditures on environmental compliance for small facilities differ from larger facilities. “Look-Back” Initiative President Obama’s Executive Order 13563, issued in 2011, directed executive agencies to conduct retrospective reviews of their regulations to determine whether any of the agencies’ regulations should be modified, streamlined, expanded, or repealed. This Executive order was followed by Executive Order 13579, which called on independent agencies to conduct such retrospective reviews to the extent possible. Look-back exercises enable regulatory agencies to learn whether they can increase net benefits by modifying existing regulations, expanding regulations, or even eliminating existing regulations that may turn out to be ineffective or duplicative. 240 | Chapter 8 Incorporating ex-post benefits and costs of regulations is the key goal of the new Executive order requiring agencies to conduct retrospective reviews of their regulations. In the past, agencies have undertaken such reviews in certain situations but only on an ad hoc basis. The new Executive order aims to improve regulatory analyses by providing a formalized process for incorporating new information into regulations and for gaining insight into the costs and benefits borne by the private sector in practice. The President’s regulatory look-back initiative has produced more than 500 reform proposals, detailed in 26 agency plans, and monetized savings from this review are likely to exceed $10 billion over the next five years. A number of recent actions eliminate or streamline unjustified or excessive regulations, and the Administration has put in place an improved regulatory system that will generate more current and accurate information on regulatory costs and benefits. Moreover, pursuant to Executive Order 13579, issued in July 2011, some of the major independent regulatory agencies have also issued preliminary retrospective review plans for public comment.2 Five examples illustrate the effectiveness of the look-back initiatives. First, the Occupational Safety and Health Administration (OSHA), has announced a final rule that will eliminate redundant reporting burdens; the regulation is expected to save employers 1.9 million hours and $40 million annually. OSHA also plans to finalize a rule projected to result in more than $585 million in savings each year by making U.S. hazard classifications and labels consistent with other nations. Second, since the 1970s, the EPA has treated milk as “oil” subject to regulations designed to prevent oil spills. In response to feedback from the agriculture community and the President’s Executive order, the EPA recently concluded that the rules placed unjustifiable burdens on dairy farmers and decided to exempt milk from those regulations. That exemption will save the dairy industry, including many small businesses, as much as $148 million per year. Third, to reduce burdens on railroads, the Department of Transportation has proposed to refine its requirements for tracks that are to be equipped with positive train controls. This equipment can automatically control a train in emergency circumstances, reducing the risk of an accident. The potential refinements would eliminate the need for costly wayside components and mitigation measures along as much as 10,000 miles of track where they are not needed for safety. The initial 5-year savings are expected to be as high as $335 million, with total 20-year savings of up to $778 million. 2 Specific retrospective analyses by executive and independent agencies can generally be found on the relevant websites; for example, the Federal Trade Commission provides information on its retrospective review process at http://www.ftc.gov/ftc/regreview/index.shtml. Improving the Quality of Life through Smart Regulation, | 241 Innovation, Clean Energy, and Public Investment Fourth, the EPA has proposed to eliminate a requirement for air pollution vapor recovery systems at local gas stations in many states, on the ground that modern vehicles already have effective air pollution control technologies. The anticipated annual savings from eliminating the requirement are estimated to be as high as $87 million. Fifth, the Health and Human Services Department has proposed or finalized several rules that reduce regulatory burdens and restrictions on doctors and hospitals and that are expected to save more than $5 billion over the next five years. There are many other look-back efforts—in all, the initial round of retrospective proposals is expected to eliminate millions of hours of required paperwork for individuals, businesses, and State and local governments and to save billions of dollars. Improvements in Everyday Life Every time Americans drive a car, take a breath, swim in a lake, or take a medication they are benefiting from regulations. As noted, such improvements in quality of life often show up in national accounts only as a fraction of their total benefit to society. For example, although the growth and size of the pharmaceutical industry are reflected in GDP, the value of assurances given to the U.S. public that the medicines they are taking have been tested and verified to be effective and safe goes far beyond the measured value of that sector to the national economy. Similarly, the Clean Water Act and its associated permitting requirements have reduced effluent discharge into U.S. streams, lakes, and estuaries. Putting a price tag on the benefits of being able to swim, fish, and boat in those bodies of water is difficult. Regardless of the value, some of those benefits (for example, increasing expenditures on fishing equipment and recreation) will show up in a calculation of GDP, while many others (such as reducing the level of fecal coliform in the water) will not. The EPA estimates the benefits of reducing discharge of conventional pollutants to U.S. rivers and streams to be approximately $11 billion annually (Bingham et al. 2000). The EPA’s Superfund program, which identifies, investigates, and cleans the Nation’s most contaminated hazardous waste sites, has also improved public health. Since 1980 the Superfund program has prevented millions of people from being exposed to hazardous substances by requiring protective and containment measures and the removal from industrial sites of many millions of tons of material contaminated with toxic chemicals such as lead, arsenic, mercury, and benzene (EPA 2011c). Studies have shown that Superfund cleanups have lowered the risk of acute poisoning, improved infant health, and decreased the risk of cancer (Currie, Greenstone, and 242 | Chapter 8 Moretti 2011; and EPA 2011c). Those improvements are generally not captured well in GDP for any given year. Even though smart regulations can impose restrictions on the private sector, as Figure 8-2 illustrates, the resulting benefits do not come at the cost of prosperity or sacrifices in U.S. standards of living. Over a period of decades, air quality has improved while the economy has grown; indeed, the demand for clean air and water has risen along with income across countries (see for example, Grossman and Krueger 1995; and World Bank 1992). Even though those benefits do not show up directly in GDP measures, they are consistent with increases in conventional (albeit incomplete) measures of growth. Per capita GDP has shown substantial growth between 1980 and 2010, rising by 65 percent, while at the same time per capita emissions of criteria pollutants (lead, carbon monoxide, sulfur dioxide, nitrogen oxides, particulate matter, and ozone) have declined by nearly 75 percent. Similar achievements have been made in other areas as well. The number of fatalities on U.S. roads per million vehicle miles traveled (VMT) has declined by 67 percent between 1980 and 2010, while VMT per capita increased by 44 percent, reflecting the effectiveness of road and vehicle safety regulations. Innovation Innovation, loosely defined as the introduction of a new or improved product, service, or process, is the primary source of long-run increases in productivity and human welfare (Grossman and Helpman 1991). When new ideas are integrated into the economy, they offer new possibilities for both production and consumption. Innovation comes in two general forms: process and product innovation. Process innovations involve new or improved methods of production or distribution, often as firms seek to reduce costs. The cost savings are reflected in conventional accounting statistics as greater productivity. Over time, rising productivity drives the growth in the amount of output that the economy can produce. By contrast, product innovations introduce new or improved products or services into the marketplace. As noted, consumers benefit from product innovations in ways that conventional accounting statistics do not adequately measure. Although there is no perfect measure of the importance of innovation to an economy, by many measures innovation has played an increasingly important role in the U.S. economy in recent decades. For example, the industries classified by the OECD as “knowledge- and technology-intensive” have steadily increased as a share of the U.S. economy, from 34 percent of GDP in 1992 to 40 percent in 2010, according to the National Science Foundation (2010; 2012). Improving the Quality of Life through Smart Regulation, | 243 Innovation, Clean Energy, and Public Investment Figure 8-2 Economic Growth, Vehicle Safety, and Air Quality, 1980─2010 Percent change from 1980 80 Per capita real GDP 60 40 Per capita VMT 20 0 Per capita emissions of criteria pollutants -20 -40 -60 Fatalities per 100 million VMT -80 -100 1980 1985 1990 1995 2000 2005 2010 Note: VMT is vehicle miles traveled. Criteria emissions are linearly interpolated from 5year interval data between 1980 and 2010. Source: National Highway Traffic Safety Administration; Federal Highway Administration; Environmental Protection Agency; Bureau of Economic Analysis. Private-sector competition is the primary driver of innovation. Firms in innovative industries must continually work to improve their products or increase their efficiency to avoid losing market share to competitors. Businesses that successfully invest in innovations are rewarded in the marketplace. Incentives for businesses to invest in innovation are often less than optimal from the perspective of society as a whole, however, primarily because the innovator may not be able to capture all of the benefits generated by the innovation. The positive spillovers from innovation mean that the private returns from innovation will often be less than the social returns, particularly when it comes to basic research. Private firms have limited incentive to conduct basic scientific research from which they generally can capture only a small fraction of the value that emerges from that research. As a result, private markets may lead to underinvestment in basic science and limited diffusion of scientific advances. Because private incentives to invest in innovation are often inadequate, public-sector support for innovation has important benefits. Government can promote innovation in many ways. By operating a well-functioning system of intellectual property rights, the government can help innovators earn returns commensurate with the social value of their innovations. Government can increase investment in innovation through research and development (R&D) expenditures, both by direct funding and by tax 244 | Chapter 8 incentives. It can facilitate the commercialization of innovations by removing barriers that prevent the private sector from transforming inventions into marketable products. It can provide infrastructure necessary for innovation, for example by allocating spectrum to support the growth of wireless broadband, itself an important platform for innovation in mobile devices, applications, and services. The government can also target innovation initiatives to areas of key public importance, including education, health care, and energy. This section of the chapter discusses these issues and describes some of the Federal Government’s current efforts to promote innovation in the U.S. economy. Measuring Innovation Innovation’s crucial role in economic growth and welfare has prompted efforts to improve the tools to measure it. One longstanding approach to measuring innovation is to infer that any economic growth not attributable to additional capital and labor must be due to some sort of “technical change.” This so-called “Solow residual” approach (Solow 1957), however, leaves unanswered many questions about the nature of the technical change. Data on patenting activity can provide a useful, if imperfect, measure of innovation. Although many innovations are kept secret to preserve competitive advantage, many others are made public through patent filings. The innovations for which patents are granted vary greatly in their significance, however, and a raw count of patents cannot account for these differences. Moreover, increases in patent activity over time may be attributable, at least in part, to more aggressive patenting of marginal innovations rather than increases in innovation itself (Hall and Ziedonis 2001). To address these limitations, studies of innovation have often relied on measures of patent citations. For example, the number of times a firm’s patents are cited by other patent applications is more closely correlated with the firm’s market value than is the raw number of patents it holds (Hall et al. 2001). New measurement efforts have focused on the funds allocated to R&D within the economy. Historically, R&D has been treated as an intermediate input to the production process and is therefore excluded from GDP estimates. Beginning in 2013, the GDP estimates produced by the Bureau of Economic Analysis (BEA) will include R&D under the category of investment, increasing measured GDP. Spending on R&D is large and growing; if the new definition had been in effect earlier, current-dollar GDP in 2007 would have been, on average 2.7, percent higher, and R&D would have accounted for 6.3 percent of real GDP growth between 1998 and 2007. Improving the Quality of Life through Smart Regulation, | 245 Innovation, Clean Energy, and Public Investment In addition, to help improve understanding of the role of R&D in fostering innovation, the Census Bureau and the National Science Foundation (NSF) have introduced the Business R&D and Innovation Survey. This new survey combines firm-level data on R&D expenditures with measures of new or improved products or processes and patenting and licensing activity. The first group of 40,000 for-profit firms was surveyed in 2009, and some preliminary findings have been reported. For example, the NSF reports that companies that invest in R&D exhibit far higher rates of innovation than other firms (Boroush 2010). Measuring innovation is particularly challenging in the growing medical care sector. For example, medical science has established that aspirin—an old and inexpensive product—can substantially reduce heart attack risk. Patients have seen enormous benefits from that scientific advancement, but those benefits are not captured by estimates of GDP. The National Institute on Aging has sponsored research on the development of national health accounts that would gauge the population’s health status and measure how medical care and other factors affect health. Intellectual Property Rights and Patent Reform Innovation is spurred in part by the desire to reap rewards for developing new products and services that people will value. The central purpose of intellectual property (IP) rights, which include patents, trademarks, and copyrights, is to promote innovation by giving IP owners the right to exclude others from making use of their novel product or service. Well-designed IP rights enhance the private returns to innovation and bring them closer to the social returns, thereby increasing the incentives to invest in socially valuable innovation. As President Lincoln famously said, the patent system “added the fuel of interest to the fire of genius” (Edwards 2006).3 The United States has long had a robust system of IP rights. In fact, one of the powers explicitly given Congress in the Constitution is “To promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries.” In recent years, however, many observers have raised concerns about the U.S. patent system. For example, the Federal Trade Commission (FTC 2003) describes concerns that the patent system has failed to keep up with the challenges posed by the growth of the knowledge-based economy. Similarly, the National Academy of Science (NRC 2004) describes unease among academics and practitioners that “the escalation in the number of patents, possibly encouraged by a lowering of the threshold to their 3 President Lincoln was himself an inventor. He was granted patent no. 6469 in 1849 for a flotation system for lifting riverboats stuck on sandbars. 246 | Chapter 8 acquisition, was creating thickets of rights that could impede innovation.” Shapiro (2008) sees the core problem as being that, in some circumstances, “the patent system predictably provides excessive rewards to patent holders.” The opportunity for excessive returns can arise when patents are issued for technologies that are not genuinely novel or when a patent covers a small component of a complex product that allows the patent’s owner to extract royalties disproportionate to the incremental value of the component. Some empirical evidence suggests that, at least in certain industries, greater patenting activity has in fact led to reduced R&D intensity (Hunt and Bessen 2004). To address concerns about the performance of the patent system, President Obama, on September 16, 2011, signed into law the America Invents Act, the most significant reform of U.S. patent law since 1952. By allowing third parties to provide the patent office with additional information that may be helpful in assessing the novelty of an invention for which a patent application has been filed, the new law will reduce the number of improperly issued patents and thus increase “patent quality.” The law will also reduce unnecessary litigation by creating new ways of resolving patent disputes more quickly and cheaply, allowing inventors to invest with more confidence in the validity of their IP rights while reducing the drag on innovation caused by improperly granted patents. The law will also reduce wait times for patent applicants by giving the U.S. Patent and Trademark Office more resources to reduce the backlog of applications and by creating a “fast-track option” for time-sensitive patent applications such as those from fast-growing startups or entrepreneurs seeking venture capital. Last, the new law will harmonize the American patent system with patent systems in the rest of the world by adopting a “first inventor to file” system. This change will make the U.S. system more efficient and predictable, allowing innovative entrepreneurs to market their products more easily in the United States while simultaneously exporting them abroad. Private and Public Investments in R&D R&D is a critical driver of innovation. Investments aimed at creating new knowledge or applying existing knowledge in new ways are often a necessary precursor to developing new or improved products or processes or entire new industries. Although innovative activities extend far beyond conventional R&D, and innovations arise in industries that perform little R&D as such, investing in R&D is generally an important element of innovative activity. A large body of research confirms that investments in R&D increase productivity growth (CBO 2005). Other research demonstrates that the social returns to R&D investment are generally substantially greater than Improving the Quality of Life through Smart Regulation, | 247 Innovation, Clean Energy, and Public Investment the private returns. For example, Nordhaus (2004) concludes that “only a minuscule fraction of the social returns from technological advances over the 1948–2001 period was captured by producers, indicating that most of the benefits of technological change are passed on to consumers.” (See also Hall, Mairesse, and Mohnen 2009; Bloom, Schankerman, and Van Reenen 2010; and Jones and Williams 1998.) These findings support the conclusion that R&D investments often have important positive spillover effects that prevent private firms from fully capturing the benefits of their innovations, thus giving them inadequate incentives to invest in R&D. In addition, Hall (2002) finds evidence that capital market imperfections may lead to underinvestment in R&D even in the absence of these spillovers. In short, economics research provides persuasive support for a robust government role in promoting R&D. The United States is a world leader in R&D investments. With an estimated $400 billion in public and private expenditures in 2009, the United States invested more in R&D than China, Japan, and Germany combined. Moreover, R&D spending as a share of the U.S. economy has been increasing in recent years, with the ratio of R&D spending to GDP reaching nearly 2.9 percent in 2009, the highest since the 1960s. During that interval, however, the composition of U.S. R&D spending shifted dramatically. During the 1950s and 1960s, the majority of total R&D expenditures was federally funded; today nonfederal sources predominate. Private industry investments have consistently accounted for about 90 percent of all nonfederal R&D expenditures. Despite the increasing role of private-sector investment in R&D, public support for R&D remains critically important, particularly in basic research, which aims to expand scientific knowledge and thus does not generally have immediate commercial applications. Private firms can thus find it especially difficult to capture the benefits that stem from this research, and the positive spillover effects of basic research can be especially large. For example, NSF-funded basic research into the principle of nuclear magnetic resonance ultimately led to the development of magnetic resonance imaging (MRI) machines, a medical imaging technology that has significantly improved diagnosis for cancer and other conditions. Not surprisingly, the Federal Government is a strong supporter of basic research. In 2008, while the Federal Government accounted for only 15 percent of U.S. development expenditures and less than one-third of applied research expenditures, it accounted for nearly 60 percent of the Nation’s basic research expenditures. Overall, the Federal Government provides substantial support for R&D. In 2009, when the Recovery Act helped Federal R&D spending reach 1.18 percent of GDP, the U.S. Government invested a greater share of GDP 248 | Chapter 8 in R&D than did the government of any other OECD country. Even in other years, the U.S. Government’s R&D investments relative to GDP have substantially exceeded the OECD average. Although this largely reflects U.S. dominance in military R&D (national defense has historically accounted for more than half of Federal R&D expenditures), many defense-related innovations ultimately have significant benefits in the private sector. Research into communications networks by the Defense Advanced Research Projects Agency, for example, ultimately led to the emergence of the Internet. Recognizing the importance of R&D for innovation, in April 2009, the President set the goal of devoting more than 3 percent of GDP to R&D, both public and private—a share that surpasses the record of almost 2.9 percent set in 1964 at the height of the space race. In its effort to reach this goal, the Administration has supported large increases in Federal R&D funding. The Recovery Act’s investment of $18.3 billion in research funding was part of the largest annual increase in R&D funding in U.S. history. The President’s Fiscal Year 2013 Budget has proposed additional support for science and basic research, making progress toward the goal of doubling funding for three key basic research agencies—the National Science Foundation, the Office of Science in the Department of Energy, and the National Institute of Standards and Technology. A particular success story is the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (SBTT) programs, competitive programs that provide about $2.5 billion annually to the most promising research projects at small firms. From 2002 to 2006, about one-fourth of the “top 100” innovations selected by R&D Magazine came from companies that had received an SBIR grant at some point in their history. Recognizing the importance of continuing these successes, on December 31, 2011, President Obama signed a bill reauthorizing the SBIR and SBTT programs for the next six years. In addition to direct Federal funding for R&D, the Administration has promoted incentives to support private R&D investment. The Research and Experimentation tax credit, for example, enacted in 1981, provides a tax credit based on qualified research expenses to encourage businesses to increase their investments. Subsidizing this activity through the tax system allows the private sector, rather than the government, to choose the research projects and the method for conducting the research. Recent studies show that the credit is a cost-effective way to encourage research spending (U.S. Treasury 2011). On September 8, 2010, the President proposed to expand and simplify the credit and to make it permanent; that proposal is also included in the President’s FY 2013 Budget. The proposal will further enhance private firms’ incentives to invest in research and will provide Improving the Quality of Life through Smart Regulation, | 249 Innovation, Clean Energy, and Public Investment businesses with assurance that the credit will be available for the duration of long-term research projects. Commercialization An important stage in the process of innovation is commercialization of new technologies. New inventions and new knowledge alone will have little effect on economic welfare unless they are converted into marketable products or processes that change how firms do business. One obstacle to realizing the economic benefits of innovation is the difficulty in transferring new ideas from universities and Federal laboratories to the marketplace. For example, recent empirical studies point to substantial frictions attributable to licensing costs and show large gains in innovation when these frictions are reduced (Williams 2010). Other researchers have found that universities often adopt technology transfer policies that constrain the volume of innovations brought into the marketplace (Litan, Mitchell, and Reddy 2007). As the President announced in January 2011, one of the goals of the Administration’s “Startup America” campaign is to foster innovation by increasing the rate of technology transfer. Since then, the Administration has announced a number of initiatives in support of this goal. In October 2011, the President issued a Presidential Memorandum directing the heads of Executive departments and agencies to take action to accelerate technology transfer and commercialization of Federal research in support of high-growth businesses. The National Center for Advancing Translational Sciences at the National Institutes of Health assists biomedical entrepreneurs by identifying barriers to commercialization and speeding development of new drugs and diagnostics. The Administration’s National Bioeconomy Blueprint lays out a number of steps designed to advance biological research innovations, including reforms to speed commercialization and open new markets. The NSF’s Innovation Corps program is a public-private partnership that will connect NSF-funded researchers with private-sector mentors who will help to transform the results of scientific research into commercially successful technologies. The Department of Energy (DOE) launched a program called “America’s Next Top Energy Innovator,” which offers startup companies low-cost and streamlined procedures for licensing new energy technologies patented by DOE labs. Together, the Administration’s “lab-to-market” initiatives will encourage universities and government research centers to streamline their technology transfer procedures, support additional government-industry collaboration, and encourage the commercialization of novel technologies flowing from research programs—in short, they will facilitate the commercialization phase of the process of innovation. 250 | Chapter 8 Wireless Broadband and Spectrum Policy Information and communication technology (ICT) is vitally important to the U.S. economy. A large body of research has linked economic growth in recent decades with ICT expansion. For example, Roller and Waverman (2001) estimate that one-third of the growth in per capita GDP in 21 developed economies from 1970 to 1990 is attributable to investments in telecommunications infrastructure. Similarly, Bloom, Sadun, and van Reenen (2007) note that the great majority of growth in U.S. productivity since the mid-1990s has been in sectors that either intensively use or produce information technologies.4 Wireless broadband is a form of ICT that can transform many different areas of the American economy by providing a platform for innovation, in areas ranging from media-rich consumer products to health care and education technologies. Much of the investment necessary to realize the potential of wireless broadband will come from the private sector. According to the Census Bureau, total capital spending by wireless telecommunications carriers has exceeded $20 billion in each year since 2000 (U.S. Census Bureau 2011). Public support is necessary in some important areas, including developing a nationwide wireless broadband network for public safety and extending wireless broadband services into rural communities, both of which are discussed in this chapter in the section on infrastructure. Another important way that the government can help to support the growth of wireless broadband is by making more spectrum available, both for licensed and unlicensed use. With the proliferation of smartphones, tablets, and other mobile devices with Internet access, mobile data traffic has been growing tremendously, more than doubling between 2009 and 2010, and industry forecasters expect data traffic to continue to grow rapidly (Cisco 2011). To accommodate this surging demand, wireless carriers will need access to additional spectrum. In early 2011, President Obama introduced his National Wireless Initiative. The proposal aims to nearly double the spectrum available for wireless broadband in the next 10 years by freeing up 500 megahertz (MHz) of spectrum currently allocated to other uses. Some of this spectrum will be shifted away from Federal Government uses, in part by finding ways to make more efficient use of the remaining Federal and shared spectrum. Any changes in the use of Federal spectrum will be designed to ensure that there is no harmful interference with public safety needs or other critical public uses of the spectrum. Doubling the spectrum for wireless broadband will 4 Jorgenson et al. (2008) estimate that ICT accounted for 59 percent of productivity growth during 1995–2000 and 38 percent during 2000–2006. Most recently, Brynjolfsson and Saunders (2010) conclude that most U.S. productivity growth since 1995 can be attributed to ICT. Improving the Quality of Life through Smart Regulation, | 251 Innovation, Clean Energy, and Public Investment also require changes in commercially licensed spectrum. Shifting to wireless broadband a portion of the spectrum now licensed for over-the-air television broadcasting will yield substantial economic benefits. To ensure that commercially held spectrum is reallocated efficiently and that the economic benefits are widely shared, the Administration supports using “voluntary incentive auctions” to guide the reallocation. These auctions will allow existing licensees to receive a portion of the auction proceeds in exchange for voluntarily making their spectrum available for wireless broadband. The auctions will also generate substantial revenues for the U.S. Treasury, providing support for important goals, including deficit reduction, R&D for emerging wireless technologies, and a nationwide interoperable wireless broadband network for public safety. Clean & Secure Energy In his State of the Union address, President Obama, noted that, “This country needs an all-out, all-of-the-above strategy that develops every available source of American energy. A strategy that’s cleaner, cheaper, and full of new jobs.” The President has outlined goals that will set the United States on a path toward lowering its dependence on oil and developing cleaner domestic energy sources that reduce emissions of air pollutants. Those include goals to continue focusing on increasing responsible domestic oil and gas production, to reduce foreign oil imports by a third by 2025, and to increase the share of electricity generated from clean energy sources— including nuclear power, natural gas, clean coal, and renewables like wind and solar—to 80 percent by 2035. The President has outlined a Blueprint for a Secure Energy Future to guide the Nation’s transition to a clean and secure energy economy. While the market provides key signals that greatly influence energy production and consumption decisions, energy markets are subject to market failures, so the government has an important role to play in guiding the mix of energy supplies and uses that is best for the Nation. The government also has a role to play in increasing energy security, reducing air pollution, promoting clean energy through investments in innovation and infrastructure, and establishing rules of the road that promote a cleaner and more secure energy future. Enhancing Energy Security The short-run demand for energy is relatively inelastic, so consumers will bear the brunt of sudden, unexpected energy supply disruptions in the form of price increases, causing them to reduce their consumption of other goods and services, or reduce savings. Elevated global energy prices can, 252 | Chapter 8 in turn, slow economic growth. Promoting the development of alternative energies and energy-efficient technologies reduces the economy’s vulnerability to international energy supply shocks and improves energy security. Oil consumption per thousand dollars of real GDP has fallen by about half since 1980 (from almost one barrel per thousand dollars of GDP in 1980 to about 0.5 barrel per thousand dollars of GDP in 2010). Despite progress in reducing the “petroleum intensity” of the economy, vulnerability to increases in the global market price of crude oil remains. We can improve energy security by lowering demand for petroleum and by increasing the supply of domestic conventional and alternative energy. Reducing Demand During the past year, the Administration has pursued a course that reduces demand for petroleum. In November, EPA and DOT proposed new fuel economy standards for vehicle model years 2017–2025, building on the successful programs for the 2011 and 2012–2016 model years. These standards will save consumers money at the pump, dramatically reduce the Nation’s dependence on oil, and increase investment in new technologies and new manufacturing here in the United States. Under the proposed rules, fuel economy standards from the DOT, greenhouse gas (GHG) emission standards from the EPA, and State of California regulations will be harmonized and auto companies will be able to rely on well-defined regulatory targets to help steer their investments in producing advanced vehicles. Annualized costs of the rule are expected to be between $6.4 billion and $10.6 billion; annualized fuel savings are expected to range between $20.3 billion and $26.7 billion (2009 dollars). Additional annualized benefits from improved health, greater energy security, and lower GHG emissions are expected to range between $5.4 billion and $6.4 billion. Taken together, the fuel economy standards proposed for model years 2011–2025 are projected to reduce oil consumption by over 2.2 million barrels per day by 2025, and save consumers $1.7 trillion in fuel costs. The President has also proposed a new tax incentive to offset half of the incremental cost of dedicated alternative-fuel commercial vehicles, such as natural gas and electric trucks, for a five-year period. In addition, the President has proposed transforming the individual tax credit for consumers who purchase advanced vehicles into a rebate. Increasing Domestic Energy Supplies The Nation has pursued strategies to safely increase domestic energy sources. As part of this focus, the President is committed to advancing the responsible production of domestic oil and natural gas resources. Thanks Improving the Quality of Life through Smart Regulation, | 253 Innovation, Clean Energy, and Public Investment to higher domestic production and lower imports, dependence on foreign oil is being reduced. In 2010, for the first time in over a decade, the United States relied on net imports for less than half of the oil we consumed; in 2011, import dependence declined even further, to 45 percent. Since 2007, the United States has been the leading natural gas producer in the world. To help ensure safe and responsible development of abundant natural gas resources, the Administration is taking a number of steps, including: exploring home grown technologies and methods to improve safety and environmental performance of shale gas production; encouraging greater use of natural gas in transportation; and requiring disclosure of chemicals used in hydraulic fracturing on public lands. As Box 8-1 describes, the development of unconventional oil and gas deposits across the United States illustrates how American enterprise and innovation in horizontal drilling and hydraulic fracturing, combined with government-supported research, have unlocked vast new domestic oil and gas resources. The United States has also increased the amount of ethanol and biodiesel blended into the nation’s fuel supply. In 2011, ethanol and biodiesel production in the United States were estimated by the U.S. Energy Information Administration (EIA) to be roughly 14 billion gallons and 920 million gallons, respectively (EIA 2012). That represented about 10 percent of U.S. gasoline demand and 2 percent of diesel demand for 2011. In March 2011, the President set the goal of breaking ground on at least four commercial-scale cellulosic or advanced bio-refineries over the next two years, and we are on track to exceed that goal. In addition, the Administration announced a partnership between the Departments of Agriculture, Energy and the Navy to invest in multiple domestic commercial or pre-commercial scale bio-refineries to produce advanced “drop-in” biofuels, substitutes for diesel and jet fuel. Reducing Emissions The Administration has taken historic steps to address air pollution from stationary sources such as aging coal-fired power plants. The Mercury and Air Toxics Standard (MATS) regulation announced by the EPA in December, for example, will reduce emissions of sulfur dioxide, mercury and other toxic air pollution and generate between $27 billion and $80 billion in net benefits annually by improving people’s health. In addition, to create a market for innovative technologies that will encourage the deployment of clean energy and the benefits that come with it, such as reduced emissions of air pollutants and greenhouse gases, the President has proposed a Clean Energy Standard (CES). 254 | Chapter 8 A CES works by giving electric power plants clean energy credits for electricity they generate from clean energy. Utilities that serve retail customers are responsible for making sure they have enough clean energy credits to meet their target. Utilities that generate more clean energy than needed to meet their target can bank their extra credits for later use, or sell them to other companies. Under the President’s proposal, the target would increase over time, so that by 2035, 80 percent of the country’s electricity would be generated from clean sources. This flexible approach would harness privatesector incentives to minimize the cost of generating electricity from clean energy sources. Because of cleaner power plants, greater use of alternative fuels, and more energy-efficient vehicles, buildings, and appliances, EIA (2012) expects per capita emissions of carbon dioxide in the United States to fall over time, by an average of 0.8 percent a year between 2010 and 2035. Supporting Clean Energy R&D and Infrastructure Public investments in innovation and infrastructure are critical to solving the twin objectives of increasing energy security and reducing GHG emissions. Private-sector investment in energy R&D and infrastructure will be less than optimal because the positive externalities from such investments prevent private firms from fully capturing the benefits. Support for innovation is a key piece of the Blueprint strategy, which involves creating markets for clean technologies that are ready to deploy and funding cutting-edge research to deliver the next generation of technologies. In addition, investments in modernizing the energy infrastructure with advanced technologies will help to increase efficiency and reduce waste. Innovation and adoption of new technologies will be critical to improving energy efficiency and shifting the Nation’s energy use toward low-carbon energy generation. Among the DOE offices that provide support for clean energy innovation is the Advanced Research Projects Agency-Energy (ARPA-E), an organization modeled after the Defense Advanced Research Projects Agency. ARPA-E provides funds to develop advanced energy technologies that reduce energy-related emissions and increase energy efficiency, focusing on transformational energy research that the private sector by itself is unlikely to support. The Obama Administration funded ARPA-E for the first time with $400 million as part of the Recovery Act. This funding, along with subsequent appropriations, has been used to support about 180 projects, including technologies for plug-in electric vehicles, batteries that convert wind power into a steady power source, and microorganisms that produce liquid biofuels from sunlight and carbon dioxide. The President’s Fiscal Year 2013 Budget proposes $350 million in new funding for ARPA-E to continue Improving the Quality of Life through Smart Regulation, | 255 Innovation, Clean Energy, and Public Investment Box 8-1: Developing Domestic Energy: Shale Gas and Shale Oil Shale gas and shale oil (also known as “tight” oil) are deposits trapped inside formations of fine-grained sedimentary rocks, or shale. As recently as a decade ago many of these deposits were viewed as uneconomical to extract. Now they are being profitably extracted, leading to a boom in production from these unconventional oil and gas deposits. The President has been clear about the importance of domestic oil and gas production, including the central role responsible natural gas development will play in our energy future, increasing energy independence, and supporting jobs. The percent of new wells directed to shale gas and oil deposits surged from 13 percent in 2005 to 57 percent in 2011. That dramatic increase is in large part due to rising energy prices in the early 2000s, which made it profitable for oil and gas companies to pursue higher cost reserves. But it is also due in part to R&D investments made by the Department of Energy (DOE). Between 1978 and 1992, the DOE invested about $137 million in the Eastern Gas Shale program, which helped develop and demonstrate directional and horizontal drilling technology. Horizontal drilling allows multiple wells to be completed from one drilling pad by drilling vertically for several thousand feet and then drilling horizontally. Hydraulic fracturing pumps water, chemicals and sand into the well to fracture the surrounding rock, releasing trapped natural gas and oil, allowing more gas and oil to be captured (see figure). From 2006 through 2010 the average annual growth rate of shale gas production was 48 percent. By 2035 shale gas is expected to make up 49 percent of total U.S. natural gas production, up from 23 percent in 2010 (EIA 2012). Increased supply has caused wholesale natural gas prices to fall more than 75 percent from their peak in October 2005 through October 2011. This led to a 67 percent drop in prices charged for natural gas used to generate electricity and a 34 percent decline in residential natural gas prices. Domestic oil production also grew in 2009 and 2010, in part due to horizontal drilling methods. That growth helped improve America’s energy security. We reduced our imports of crude oil, from 10.1 million barrels per day in 2005 to an estimated 8.9 million barrels per day in 2011. EIA (2012) projects that domestic oil production will continue to increase through 2020. We are also exporting more refined petroleum products than ever: between the first half of 2009 and the first half of 2011, exports of mineral fuels and oils jumped 150 percent, an increase valued at more than $35 billion (see Chapter 5). In addition, the United States is at the forefront of exporting extraction technologies and related services to other countries interested in tapping their own unconventional oil and gas reserves. 256 | Chapter 8 This expansion of natural gas and oil production has also supported jobs for thousands of Americans. Bureau of Labor Statistics (BLS) data show that oil and gas extraction and drilling services jobs have grown by 100,000 between 2005 and 2010, with much of that increase tied to horizontal drilling for shale gas and oil. The industry also indirectly supports many more jobs, including jobs associated with the transportation, processing, and distribution of oil and natural gas products. Furthermore, downstream industries, such as the chemical and plastics sectors that use natural gas as an important input, benefit from the expanded supply of natural gas. Such tremendous growth also comes with the responsibility to develop these new resources safely. A number of concerns have been raised regarding the potential adverse environmental impacts associated with current shale gas extraction practices, particularly the use of hydraulic fracturing. The Obama Administration is taking a number of steps to ensure that the United States can realize the economic benefits of its natural gas resources in a an environmentally responsible way. An important part of this effort consists of targeted research coordinated between the DOE, the Department of the Interior, and the Environmental Protection Agency to assess and address potential impacts of natural gas and oil development using hydraulic fracturing and to identify innovative ways to reduce adverse environmental impacts. For example, the DOE is actively involved in research exploring improved methods to treat the water used in shale gas extraction so it can be reused or disposed of safely. The Administration is committed to ensuring that natural gas and oil extraction will be pursued in a prudent manner that is safe for the environment. Horizontal Well (A) vs. Vertical Well (B) Source: EIA (1993). Improving the Quality of Life through Smart Regulation, | 257 Innovation, Clean Energy, and Public Investment to support breakthrough clean energy research in areas such as solar energy, energy storage, carbon capture and storage, and advanced biofuels. An important part of the effort to transition to a clean energy future is the “SunShot Initiative” announced by the DOE in February 2011. This initiative supports innovation to reduce the cost of solar energy by 75 percent by 2020, making unsubsidized solar energy cost-competitive with other forms of energy. Achieving the goal will require major innovations in the ways solar technologies are conceived, designed, manufactured, and installed. SunShot is investing in solar technology and manufacturing improvements and working to reduce installation and permitting costs. According to DOE (2011) analysis, by reducing the cost of solar electricity to about six cents per kilowatt hour, SunShot has the potential to increase the share of electricity generation from solar photovoltaics to 15 percent by 2030. As the United States transitions to a clean energy future, an important way to improve energy efficiency, reliability, and security is to upgrade the electricity transmission and distribution infrastructure to make greater use of advanced technology and to incorporate real-time communications, monitoring, and control systems. Transforming the electricity infrastructure into a “smart grid” could lead to substantial cost savings and efficiencies, help avoid blackouts, and improve the integration of renewable energy sources on the grid. The Recovery Act included $4.5 billion in grid modernization investments, matched by contributions of more than $5.5 billion from the private sector. Building on these investments, the Administration announced a number of new initiatives to support the development and deployment of smart-grid technologies, including $250 million in loans to deploy smart-grid technology in rural areas under the Rural Utility Service. In June 2011, the White House released a report by the National Science and Technology Council, “A Policy Framework for the 21st Century Grid: Enabling Our Secure Energy Future,” outlining policy recommendations that build on existing smart-grid investments to foster continued modernization of electricity infrastructure. In addition to efforts to support smart grid development, the Administration has announced efforts to improve Federal coordination and ensure timely review of proposed renewable energy projects and transmission lines through the formation of two interagency Rapid Response Teams, one for transmission and one for renewables. The Rapid Response Team for Transmission is focused on seven pilot project transmission lines which cross through 12 states. These projects were selected from lists produced through independent stakeholder processes. When built, these seven pilot projects will help increase electric reliability and integrate renewable energy into the grid. The agencies participating in the Renewable Energy Rapid 258 | Chapter 8 Response Team have all made significant strides toward the deployment of renewable energy through the development of better government processes to issue permits for renewable energy projects. Infrastructure As emphasized, energy infrastructure is critical for developing our domestic clean energy potential. Infrastructure also includes transportation systems like roads, railways, ports and airports; information and communications networks; and schools, parks, and other public facilities. As economic activity grows, the infrastructure that supports it must grow as well. Moreover, physical infrastructure deteriorates over time and requires ongoing investment for maintenance. If investments to maintain, upgrade, and expand infrastructure do not keep pace with the growth in demand, the result is congestion: too many hours sitting in traffic or in an airplane stalled on the tarmac, too many dropped calls, slow Internet connections. Such disruptions impose substantial economic costs through wasted time and resources and diminished quality of life. As a result, efficient infrastructure investments can have a significant positive impact on economic welfare. The State of the Nation’s Infrastructure The value of the U.S. transportation capital stock steadily increased from 2004 to 2009, reaching more than $6 trillion in 2009 (the most recently reported year). The greatest percentage increase in mileage for any mode of transportation from 2004 to 2009 was in light transit rail track, which increased by 24 percent, followed by commuter rail track, which increased by 10 percent. At the same time, the overall condition of many parts of the Nation’s transportation infrastructure remained disappointing. In 2008, nearly 21 percent of urban interstate highways and 35 percent of urban collector roads were in poor or mediocre condition, according to the Bureau of Transportation Statistics. Moreover, in 2009 nearly 71,200 bridges—more than 10 percent of all U.S. bridges—were rated as structurally deficient. The current disappointing state of transportation infrastructure is partly reflected in rising levels of congestion on many parts of the transportation system, particularly urban roadways. According to the Texas Traffic Institute’s (TTI) Urban Mobility Report, traffic congestion in urban areas in 2010 accounted for 4.8 billion hours of travel delay and 1.9 billion gallons of wasted fuel, for an aggregate congestion cost of more than $100 billion, an increase of more than 25 percent over 2000 in constant (inflation-adjusted) dollars (Schrank, Lomax, and Eisele 2011). If current trends continue, TTI projects that the total cost of congestion in U.S. urban areas could grow by Improving the Quality of Life through Smart Regulation, | 259 Innovation, Clean Energy, and Public Investment a further 32 percent in real terms by 2015. These estimates likely understate the real effects of congestion on welfare because they do not take into account the reduction in quality of life that results from additional time spent commuting. Studies of how individuals experience the activities of daily life have found that commuting is among the least enjoyable and most stressful (Kahneman et al. 2004, Stutzer and Frey 2004). The U.S. electricity grid is also showing signs of strain, with investment in capacity generally lagging behind growth in demand. According to the DOE (2008), growth in peak demand for electricity has exceeded transmission growth by almost 25 percent every year since 1982. Power outages and interruptions have become more frequent and are now affecting more consumers. The DOE reported that 41 percent more outages affected 50,000 or more consumers in the second half of the 1990s than in the first half, and the average outage affected 15 percent more consumers. By 2008, power outages and interruptions cost Americans an estimated $150 billion each year. Broadband is another important category of infrastructure where the United States faces significant investment needs. Described by the Federal Communications Commission as “the great infrastructure challenge of the early 21st century” (FCC 2010), broadband’s growth over the past decade has been substantial. Thanks to significant investments by telecommunications and cable companies, 95 percent of the U.S. population had access to wired broadband service in 2010, and industry analysts project that by 2013, wireless providers will offer such service to about 94 percent of the population. (Atkinson et al. 2011). At the same time, many households, particularly in rural areas, continue to have Internet access only at much slower speeds. As discussed, perhaps the most significant challenge to the Nation’s broadband infrastructure is the threat of growing congestion on wireless networks. Overall, evidence is growing that the United States has been underinvesting in many kinds of infrastructure. For example, the Nation invests annually approximately 2 percent of GDP on infrastructure, compared with 9 percent and 5 percent, respectively, for China and Europe. In addition, compared with other OECD countries, Americans are relatively dissatisfied with their local public infrastructure systems, according to the Gallup World Poll. Americans’ satisfaction with public transit ranks 25th out of 32 OECD nations, and satisfaction with roads and highways ranks 17th out of 32. Many observers, including the American Society of Civil Engineers (2009), have concluded that the United States faces a substantial need for infrastructure investment over the next five years. Although the optimal level of infrastructure investment is difficult to quantify precisely, the evidence strongly suggests that the United States has not been investing adequately to meet future infrastructure needs. 260 | Chapter 8 Government and Private Sector Roles in Infrastructure In the United States some kinds of infrastructure, including most roadways and public transit systems, are typically owned and financed by government; other kinds, such as freight railways and telecommunications networks, are largely privately owned. In part, these patterns of ownership reflect historical accident. In choosing how much public support for infrastructure to provide and how to finance it, the United States, like other nations, faces questions about how best to balance the roles of the public and private sectors in infrastructure investment. Two key economic principles are whether it is costly or difficult for a private owner or investor to earn a return by monetizing access to the network, through tolls or user fees, and whether important positive spillover benefits from infrastructure investment would prevent private investors from fully capturing the overall economic benefit, even if there were a dedicated revenue stream from users. The most important potential positive spillover effect is that many infrastructure investments improve economic efficiency, increase productivity, and promote rapid economic growth. Through these effects, as a large body of research has shown, investments in infrastructure can substantially improve the long-run performance of an economy. For example, Munnell (1992) reviews the evidence on infrastructure investment and economic growth and concludes that, “in addition to providing immediate economic stimulus, public infrastructure investment has a significant positive effect on output and growth.” Gramlich’s (1994) review of the same research cautions that the rates of return on investments vary widely across different types of infrastructure and highlights the need for policies that direct public investment toward projects with the highest social return. More recent studies have found further evidence that public infrastructure investment often offers considerable returns, in some cases higher than those from private capital investment. This research is reviewed in a U.S. Treasury-CEA report (2010). In addition to their long-run benefits on economic growth and productivity, investments in infrastructure can also provide short-run benefits during times when economic resources are underutilized, by supporting employment in construction and in materials production. These short-run effects depend on the state of the overall economy. When the economy is operating at or close to its full potential, the new employment generated by infrastructure projects generally requires diverting workers from other productive activities, and the expenditure of public funds may similarly divert funds from other investment opportunities. Certain infrastructure investments may still be justified during such times, but the opportunity costs of Improving the Quality of Life through Smart Regulation, | 261 Innovation, Clean Energy, and Public Investment diverting economic resources from other activities reduce the net benefits of such investments. By contrast, today the economy is gradually recovering from the most serious economic crisis since the Great Depression and is operating significantly below its full potential, with unemployment still unacceptably high. In 2011, over 1.8 million workers in the construction industry were jobless, with an industry unemployment rate of 16.4 percent. In these circumstances, public infrastructure projects create net jobs for workers. With excess capacity widely available in the economy, increased public spending on construction materials and increased private spending by newly hired workers are unlikely to divert goods or materials from other uses. Similarly, with interest rates exceptionally low, there is little risk that Federal investment will crowd out private investment, and more infrastructure investments will yield a positive rate of return. Moreover, State and local governments, which typically fund a significant portion of infrastructure spending, have been forced to cut back on spending because of revenue shortfalls since the recession of 2007–09. Recent macroeconomic research confirms the intuition that the expansionary effect of Federal investment spending is likely to be significantly greater during times of substantial slack in the economy. For example, Auerbach and Gorodnichenko (2010) find that expansionary fiscal policy is substantially more effective during recessions than during expansions. Overall, with so many resources sitting idle, the opportunity costs of using those resources for infrastructure investment are greatly reduced. Moreover, postponing necessary infrastructure investments until after the economy has rebounded would have the undesirable effect of occupying productive resources just when the private sector needs them most. Financing Infrastructure Investments Government funding for infrastructure draws on a number of different sources, including Federal disbursements of Highway Trust Fund revenues and State and local issues of municipal bonds. Recent years have seen increased interest in alternative financing mechanisms that may expand the pool of available capital and improve the efficiency of project selection. A common theme in these alternative approaches is the goal of attracting more private capital for direct or indirect investment in transportation infrastructure. Increased reliance on the private sector to finance transportation infrastructure investments can help increase funding for those investments and may also improve the efficiency of project selection and drive greater returns on investment. For example, to attract private financing, many projects incorporate a dedicated revenue stream, often from user fees or other forms of usage-based pricing. Because these revenue streams 262 | Chapter 8 link investment returns directly to user demand, they can help to guide capital toward the most efficient projects. In general, innovative financing mechanisms can engage the private sector in infrastructure investments with important public benefits. In particular, this chapter considers three innovative approaches to private-sector engagement: public-private partnerships, particularly in the area of rail freight; Build America Bonds (BABs) as an alternative to municipal bonds that can attract new sources of private funding into the market for financing infrastructure projects; and a National Infrastructure Bank that has the potential to leverage private capital into projects of national significance. Public-Private Partnerships. In the United States, most investment in freight railway infrastructure is privately financed, because it is largely owned by the rail carriers themselves. However, even in a network based on private ownership, important public benefits can be realized through investments that improve the flow of freight across the railway network. The benefits of diverting freight efficiently from trucks to rails, for example, include reduced highway congestion, greater safety, and reduced pollution. Public-private partnerships between State and Federal agencies and the rail carriers can be an efficient way to promote such investments. For example, the Chicago Region Environmental and Transportation Efficiency program is a public-private partnership between the U.S. Department of Transportation, the State of Illinois, the City of Chicago, Metra commuter rail, and Class I railroad companies. The partnership, formed to develop and implement a set of multimodal infrastructure improvements to untangle congestion choke points in the Chicago transportation hub, involves significant financial cooperation between the private railroad industry and public government entities. Build America Bonds. Introduced in 2009, BABs are taxable bonds for which the U.S. Treasury Department pays a direct subsidy to the issuer to offset borrowing costs for public capital infrastructure projects. These bonds can function as an attractive alternative to municipal bonds, which deliver a borrowing subsidy only indirectly through the Federal tax exemption to investors for interest earnings. BABs appeal to a broader class of investors than tax-exempt municipal bonds, including nonprofits, pension funds, and many other institutional investors. Since the inception of the program in April 2009, BABs have had a very strong reception from both issuers and investors. They have supported more than $181 billion of financing, in 2,275 transactions in all 50 states, the District of Columbia, and two territories, for new public capital infrastructure projects such as schools, bridges, and hospitals. An empirical study by the Treasury Department (2011) found that State and local governments that issued BABs realized considerable savings Improving the Quality of Life through Smart Regulation, | 263 Innovation, Clean Energy, and Public Investment relative to the cost of issuing tax-exempt bonds. The study also found that expanding the BABs program would lead to continued savings on borrowing costs for State and local governments. Although the initial program expired at the end of December 2010, the President’s Fiscal Year 2013 Budget has proposed extending the program for two years at a subsidy rate of 30 percent and extending it permanently thereafter at a revenue-neutral subsidy rate of 28 percent. The Administration has also proposed expanding the program to include a broader range of eligible municipal projects. National Infrastructure Bank. Another new approach to increasing private-sector participation in infrastructure investment is a National Infrastructure Bank, as President Obama has proposed as part of the American Jobs Act. The proposed bank would help increase overall investment in infrastructure by attracting private capital to co-invest in specific infrastructure projects and would help improve the efficiency of infrastructure investment by relying on a merit-based selection process for projects. To ensure substantial leverage of private capital, the bank would finance no more than 50 percent of the total costs of any project. It would fill in an important gap in the Nation’s infrastructure funding system by focusing on projects of national or regional significance, whose effects cross over state and jurisdictional lines. Such projects are often at a disadvantage under current financing mechanisms, including state-level infrastructure banks and bonds issued by State and local governments. As a result, the National Infrastructure Bank would be a valuable complement to existing sources of funding and would improve the efficiency of U.S. infrastructure investment. Recent and Current Federal Infrastructure Initiatives Infrastructure investment has been an important priority throughout the Obama Administration. As discussed above, the modernization of the electricity grid is a key element of the effort to transition to a clean energy future. This subsection reviews some of the Administration’s other recent and current initiatives to support infrastructure investment. Transportation. The Recovery Act of 2009 provided over $48 billion to fund transportation infrastructure investments. In 2010, the Federal Highway Administration announced that it had finished obligating more than $26 billion of that amount for 12,000 road, highway, and bridge projects, and in June 2010, President Obama visited Columbus, Ohio, to commemorate the breaking of ground on the 10,000th such project. The Recovery Act also provided funds for investments in the Nation’s air and sea transportation infrastructure, including $1.3 billion to construct new runways and improve air traffic control facilities and equipment, as well as more than $18 billion to support transit and high-speed rail. Many of these 264 | Chapter 8 and other recently completed transportation infrastructure investments have already produced substantial economic benefits for the American people, including increased flows of traffic in congested areas, improved highway safety, expansion of public transit service into new communities, and rehabilitation and maintenance of aging infrastructure. Despite these substantial achievements, there is still a pressing need to revitalize America’s infrastructure networks. Recognizing this need, President Obama has proposed $50 billion in immediate investments in transportation infrastructure as part of the American Jobs Act. The proposal includes investments to speed up the permitting process, to make highways safer and more efficient, to repair and modernize public transit systems, to improve intercity passenger rail service and airports, to develop high-speed rail corridors, to support innovative multi-modal transportation programs, and to modernize the air traffic system by investing in the Next Generation Air Transportation System, or NextGen. The President also supports a robust renewal of surface transportation programs, now scheduled to expire on March 31, 2012, to keep existing and planned transportation projects moving forward. Broadband. The Recovery Act provided $7.2 billion to upgrade the Nation’s broadband infrastructure, including $4.7 billion for broadband infrastructure programs at the Department of Commerce’s National Telecommunications and Information Administration (NTIA) and $2.5 billion for the Department of Agriculture’s Rural Utilities Service (RUS) to expand broadband access in rural areas. These two programs together received more than 3,800 applications requesting more than $52 billion in support for potential projects in all 50 states and territories. When the final awards were announced in September 2010, NTIA had awarded approximately $4 billion for 233 projects throughout the country. The funds will support the construction or upgrade of approximately 120,000 miles of broadband infrastructure and will improve broadband access for approximately 24,000 community institutions, including schools, libraries, and health care facilities. In addition, RUS has awarded more than $3.5 billion in grants and loans for 320 broadband projects, which will provide broadband access for 2.8 million households and 364,000 businesses in rural areas. As part of the National Wireless Initiative, the President has called for investment in a state-of-the-art nationwide wireless broadband network for public safety communications. Developing and deploying such a system would help enable interoperability at the national level, making first responders more effective when they are called on to cross jurisdictional lines. An interoperable network would also reduce the costs of the assorted interoperability measures now being used, ranging from swapping radios to Improving the Quality of Life through Smart Regulation, | 265 Innovation, Clean Energy, and Public Investment using Internet-based gateways to patch together noninteroperable systems. Moreover, deploying a single nationwide network would realize important scale economies, eliminating duplicative operating and maintenance costs and enabling public safety entities to obtain commercially supplied devices and equipment at substantially lower cost than they can today. Finally, with clear, nationwide standards that help make public safety communication systems interoperable across jurisdictions and vendors, software and hardware developers will find it more economical to invest in innovative public safety devices and applications, further enhancing the effectiveness of first responders. Conclusion Through smart regulation, innovation, promotion of clean domestic energy, and public investment, the Federal Government helps Americans every day, improving safety and health, laying the groundwork for technological breakthroughs, and putting into place the infrastructure that facilitates commerce and travel and raises productivity. The benefits of these activities are not fully reflected in standard measures of economic activity such as GDP, but they do significantly improve the quality of life and our economy. Jan Tinbergen (1976), the first winner of the Nobel Prize in economics, commented that, “progress in our understanding can only be based on our push for measurement of phenomena previously thought to be nonmeasurable.” Spurred by the creation of new measurement techniques and the need to improve conventional measures of well-being, several recent official efforts have aimed at expanding the boundaries of measurement of the quality of life. 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Washington: Economic Policy Institute. July. OMB (Office of Management and Budget). 2012a. “Budget of the United States Government, Fiscal Year 2013.” _____. 2012b. “Analytical Perspectives, Budget of the United States, Fiscal Year 2013.” Reinhart, Carmen M., and Kenneth S. Rogoff. 2010. “Growth in a Time of Debt.” American Economic Review 100, no. 2: 573–78. Ruffing, Kathy, and James R. Horney. 2011. “Economic Downturn and Bush Policies Continue to Drive Large Projected Deficits.” Washington: Center on Budget and Policy Priorities. May. 272 | References Chapter 4 Stabilizing and Healing the Housing Market Agarwal, Sumit, John Driscoll, and David Laibson. 2007. “Optimal Mortgage Refinancing: A Closed Form Solution.” Working Paper 13487. Cambridge, MA: National Bureau of Economic Research. October. Agarwal, Sumit, Chunlin Liu, and Nicholas Souleles. 2007. “The Reaction of Consumer Spending and Debt to Tax Rebates: Evidence from Consumer Credit Data.” Journal of Political Economy 115, no. 6: 986–1019. Agarwal, Sumit, et al. 2011. “The Role of Securitization in Mortgage Renegotiation.” Journal of Financial Economics 102, no. 3: 559–78. Bajari, Patrick, Chenghuan Chu, and Minjung Park. 2010. “An Empirical Model of Subprime Mortgage Default from 2000 to 2007.” Working Paper 14625. Cambridge, MA: National Bureau of Economic Research. December. Bhutta, Neil, Jane Dokko, and Hui Shan. 2010. “The Depth of Negative Equity and Mortgage Default Decisions.” Washington: Federal Reserve Board. May. Bracha, Anat, and Julian C. Jamison. 2011. “Shifting Confidence in Home Ownership: The Great Recession.” Federal Reserve Bank of Boston. October. Campbell, John, Stefano Giglio, and Parag Pathak. 2011. “Forced Sales and House Prices.” American Economic Review 101, no. 5: 2108–31. Case, Karl, John Quigley, and Robert Shiller. 2005. “Comparing Wealth Effects: The Stock Market versus the Housing Market.” Advances in Macroeconomics 5, no. 1, article 1. _____. 2011. “Wealth Effects Revisited 1978–2009.” Working Paper 16848. Cambridge, MA: National Bureau of Economic Research. March. Department of the Treasury. 2011. “November 2011 Making Home Affordable Report” (www.treasury.gov/initiatives/financial-stability/results/ MHA-Reports/Documents/FINAL_Nov%202011%20MHA%20 Report.pdf). Doms, Mark, Wendy Dunn, and Daniel Vine. 2008. “Changes in Housing Wealth and Consumption: Did the Linkage Increase in the 2000s?” Working Paper. Washington: Federal Reserve System. October. References | 273 Elul, Ronel, et al. 2010. “What ‘Triggers’ Mortgage Default?” Federal Reserve Bank of Philadelphia. April. Federal Reserve Board of Governors. 2012. “The U.S. Housing Market: Current Conditions and Policy Considerations.” Washington. January. 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New York: Oxford University Press. 292 | References A P P E N D I X A REPORT TO THE PRESIDENT ON THE ACTIVITIES OF THE COUNCIL OF ECONOMIC ADVISERS DURING 2011 letter of transmittal Council of Economic Advisers Washington, D.C., December 31, 2011 Mr. President: The Council of Economic Advisers submits this report on its activities during calendar year 2011 in accordance with the requirements of the Congress, as set forth in section 10(d) of the Employment Act of 1946 as amended by the Full Employment and Balanced Growth Act of 1978. Sincerely, Alan B. Krueger, Chairman Katharine G. Abraham, Member Carl Shapiro, Member Activities of the Council of Economic Advisers During 2011 | 295 Council Members and Their Dates of Service Name Position Oath of office date Separation date Edwin G. Nourse Leon H. Keyserling Chairman Vice Chairman Acting Chairman Chairman Member Vice Chairman Member Member Chairman Member Member Member Chairman Member Member Member Member Chairman Member Member Member Chairman Member Member Member Chairman Member Member Member Chairman Member Member Chairman Member Member Member Member Chairman Member Member Chairman Member Member Member Member August 9, 1946 August 9, 1946 November 2, 1949 May 10, 1950 August 9, 1946 May 10, 1950 June 29, 1950 September 8, 1952 March 19, 1953 September 15, 1953 December 2, 1953 April 4, 1955 December 3, 1956 May 2, 1955 December 3, 1956 November 1, 1958 May 7, 1959 January 29, 1961 January 29, 1961 January 29, 1961 August 3, 1962 November 16, 1964 May 17, 1963 September 2, 1964 November 16, 1964 February 15, 1968 February 2, 1966 February 15, 1968 July 1, 1968 February 4, 1969 February 4, 1969 February 4, 1969 January 1, 1972 September 9, 1971 March 13, 1972 July 23, 1973 October 31, 1973 September 4, 1974 June 13, 1975 July 22, 1975 January 22, 1977 March 18, 1977 March 18, 1977 June 6, 1979 August 20, 1980 November 1, 1949 John D. Clark Roy Blough Robert C. Turner Arthur F. Burns Neil H. Jacoby Walter W. Stewart Raymond J. Saulnier Joseph S. Davis Paul W. McCracken Karl Brandt Henry C. Wallich Walter W. Heller James Tobin Kermit Gordon Gardner Ackley John P. Lewis Otto Eckstein Arthur M. Okun James S. Duesenberry Merton J. Peck Warren L. Smith Paul W. McCracken Hendrik S. Houthakker Herbert Stein Ezra Solomon Marina v.N. Whitman Gary L. Seevers William J. Fellner Alan Greenspan Paul W. MacAvoy Burton G. Malkiel Charles L. Schultze William D. Nordhaus Lyle E. Gramley George C. Eads Stephen M. Goldfeld 296 | Appendix A January 20, 1953 February 11, 1953 August 20, 1952 January 20, 1953 December 1, 1956 February 9, 1955 April 29, 1955 January 20, 1961 October 31, 1958 January 31, 1959 January 20, 1961 January 20, 1961 November 15, 1964 July 31, 1962 December 27, 1962 February 15, 1968 August 31, 1964 February 1, 1966 January 20, 1969 June 30, 1968 January 20, 1969 January 20, 1969 December 31, 1971 July 15, 1971 August 31, 1974 March 26, 1973 August 15, 1973 April 15, 1975 February 25, 1975 January 20, 1977 November 15, 1976 January 20, 1977 January 20, 1981 February 4, 1979 May 27, 1980 January 20, 1981 January 20, 1981 Council Members and Their Dates of Service Name Position Oath of office date Separation date Murray L. Weidenbaum William A. Niskanen Jerry L. Jordan Martin Feldstein William Poole Beryl W. Sprinkel Thomas Gale Moore Michael L. Mussa Michael J. Boskin John B. Taylor Richard L. Schmalensee David F. Bradford Paul Wonnacott Laura D’Andrea Tyson Alan S. Blinder Joseph E. Stiglitz Chairman Member Member Chairman Member Chairman Member Member Chairman Member Member Member Member Chair Member Member Chairman Member Member Chair Member Member Chairman Member Member Chairman Member Member Chairman Member Member Chairman Chairman Member Member Chairman Member Chair Member Chairman Member Member Member Chairman February 27, 1981 June 12, 1981 July 14, 1981 October 14, 1982 December 10, 1982 April 18, 1985 July 1, 1985 August 18, 1986 February 2, 1989 June 9, 1989 October 3, 1989 November 13, 1991 November 13, 1991 February 5, 1993 July 27, 1993 July 27, 1993 June 28, 1995 June 30, 1995 January 29, 1996 February 18, 1997 April 23, 1997 October 22, 1998 August 12, 1999 August 12, 1999 May 31, 2000 May 11, 2001 July 25, 2001 November 30, 2001 May 29, 2003 November 21, 2003 November 21, 2003 February 23, 2005 June 21, 2005 November 18, 2005 November 18, 2005 February 27, 2006 July 17, 2008 January 29, 2009 March 11, 2009 September 10, 2010 March 11, 2009 April 19, 2011 April 19, 2011 November 7, 2011 August 25, 1982 March 30, 1985 July 31, 1982 July 10, 1984 January 20, 1985 January 20, 1989 May 1, 1989 September 19, 1988 January 12, 1993 August 2, 1991 June 21, 1991 January 20, 1993 January 20, 1993 April 22, 1995 June 26, 1994 Martin N. Baily Alicia H. Munnell Janet L. Yellen Jeffrey A. Frankel Rebecca M. Blank Martin N. Baily Robert Z. Lawrence Kathryn L. Shaw R. Glenn Hubbard Mark B. McClellan Randall S. Kroszner N. Gregory Mankiw Kristin J. Forbes Harvey S. Rosen Ben S. Bernanke Katherine Baicker Matthew J. Slaughter Edward P. Lazear Donald B. Marron Christina D. Romer Austan D. Goolsbee Cecilia Elena Rouse Katharine G. Abraham Carl Shapiro Alan B. Krueger February 10, 1997 August 30, 1996 August 1, 1997 August 3, 1999 March 2, 1999 July 9, 1999 January 19, 2001 January 12, 2001 January 19, 2001 February 28, 2003 November 13, 2002 July 1, 2003 February 18, 2005 June 3, 2005 June 10, 2005 January 31, 2006 July 11, 2007 March 1, 2007 January 20, 2009 January 20, 2009 September 3, 2010 August 5, 2011 February 28, 2011 Activities of the Council of Economic Advisers During 2011 | 297 Report to the President on the Activities of the Council of Economic Advisers During 2011 The Council of Economic Advisers was established by the Employment Act of 1946 to provide the President with objective economic analysis and advice on the development and implementation of a wide range of domestic and international economic policy issues. The Council is comprised of a Chairman and two members appointed by the President and confirmed by the United States Senate. The Chairman of the Council Alan B. Krueger was nominated as Chairman of the Council by the President on August 29, 2011. He was confirmed by the Senate on November 3, 2011. Chairman Krueger is on leave of absence from Princeton University, where he is the Bendheim Professor of Economics and Public Affairs. He previously served as the Assistant Secretary for Economic Policy and Chief Economist at the U.S Department of the Treasury. The Chairman is a member of the President’s Cabinet and is responsible for communicating the Council’s views on economic matters directly to the President through personal discussions and written reports. Chairman Krueger represents the Council at Presidential economic briefings, daily White House senior staff meetings, budget meetings, Cabinet meetings, a variety of inter-agency meetings, and other formal and informal meetings with the President, the Vice President, and other senior government officials. He also meets frequently with members of Congress well as with business, academic and labor leaders to discuss economic policy issues. Austan D. Goolsbee resigned as Chairman on August 5, 2011 to return to the University of Chicago, where he is the Robert P. Gwinn Professor of Economics at the Booth School of Business. Activities of the Council of Economic Advisers During 2011 | 299 The Members of the Council Katharine G. Abraham was confirmed by the U.S. Senate as a Member of the Council on April 14, 2011. Dr. Abraham is on a leave of absence from the University of Maryland, where she is a faculty associate in the Maryland Population Research Center and a professor in the Joint Program in Survey Methodology. Dr. Abraham served as the Commissioner of the Bureau of Labor Statistics from 1993 to 2001. Carl Shapiro was confirmed by the U.S. Senate as a Member of the Council on April 14, 2011. Dr. Shapiro is on leave from the University of California at Berkeley, where he is the Transamerica Professor of Business Strategy at the Haas School of Business and Professor of Economics in the Department of Economics. Dr. Shapiro served from 2009 to 2011 as Deputy Assistant Attorney General for Economics at the Antitrust Division of the United States Department of Justice. Cecilia E. Rouse resigned as Member of the Council on February 28 to return to Princeton University, where she is the Lawrence and Shirley Katzman and Lewis and Anna Ernst Professor in the Economics of Education and Professor of Economics and Public Affairs. Areas of Activities A central function of the Council is to advise the President on all economic issues and developments. In the past year, as with the two prior years, advising the President on targeted policies to spur job creation and evaluating the effects of the policies on the economy have been a priority. The Council works closely with various government agencies, including the National Economic Council, the Office of Management and Budget, White House senior staff, and other officials and engages in discussions on numerous policy matters. In the area of international economic policy, the Council coordinates with other units of the White House, the Treasury Department, the State Department, the Commerce Department, and the Federal Reserve on matters related to the global financial system. Among the specific economic policy areas that received attention in 2011 were: housing policies, including foreclosure mitigation and prevention and refinancing; implementation of the Affordable Care Act; income inequality; individual and corporate taxation; college affordability; small business lending; regional development; intellectual property and innovation; infrastructure investment; regulatory measures; trade policies; unemployment insurance; job training; and policies to promote the international competitiveness of American manufacturing companies. The Council 300 | Appendix A also worked on several issues related to the quality of the data available for assessing economic conditions. The Council prepares for the President, the Vice President, and the White House senior staff a daily economic briefing memo analyzing current economic developments, and almost-daily memos on key economic data releases. Chairman Krueger has also been preparing monthly briefings on the state of the economy. The Council, the Department of Treasury, and the Office of Management and Budget—the Administration’s economic “troika”— are responsible for producing the economic forecasts that underlie the Administration’s budget proposals. The Council initiates the forecasting process twice each year, consulting with a wide variety of outside sources, including leading private sector forecasters and other government agencies. The Council was an active participant in the trade policy process, participating in the Trade Policy Staff Committee and the Trade Policy Review Group. The Council provided analysis and opinions on a range of trade-related issues involving the enforcement of existing trade agreements, reviews of current U.S. trade policies, and consideration of future policies. The Council also participated on the Trade Promotion Coordinating Committee, helping to examine the ways in which exports may support economic growth in the years to come. In the area of investment and security, the Council participated on the Committee on Foreign Investment in the United States (CFIUS), reviewing individual cases before the committee. Council Members and staff regularly met with economists, policy officials, and government officials from other countries to discuss issues relating to the global economy. The Council’s role also included policy development and planning for the G-20 Summit in Los Cabos, Mexico, and the G-8 Summit in Chicago. The Council is a leading participant in the Organisation for Economic Co-operation and Development (OECD), an important forum for economic cooperation among high-income industrial economies. The Council coordinated and oversaw the OECD’s review of the U.S. economy. Dr. Krueger is chairman of the OECD’s Economic Policy Committee, and Council members and staff participate actively in working-party meetings on macroeconomic policy and coordination and contribute to the OECD’s research agenda. The Council issued a series of reports in 2011. Quarterly reports to Congress on the effects of the Recovery Act on overall economic activity were issued in March, July, and December. In June, the Council released a report on U.S. Inbound Foreign Direct Investment. The Council was also the primary contributor to White House reports released on educational Activities of the Council of Economic Advisers During 2011 | 301 technology in September and two more reports related to education in October—one on the effect the American Jobs Act would have on teaching jobs and another on college affordability. In November, the Council led the preparation of a White House report on the economic benefits of infrastructure. In December, the Council was the primary contributor to a White House report issued on the effects of temporary unemployment insurance extensions on the U.S. economy. The Council continued its efforts to improve the public’s understanding of economic developments and of the Administration’s economic policies through briefings with the economic and financial press, speeches, discussions with outside economists, presentations to outside organizations, and regular updates on major data releases on the CEA blog. The Chairman and Members also regularly met to exchange views on the economy with the Chairman and Members of the Board of Governors of the Federal Reserve System. Public Information The Council’s annual Economic Report of the President is an important vehicle for presenting the Administration’s domestic and international economic policies. It is available for purchase through the Government Printing Office, and is viewable on the Internet at www.gpo.gov/erp. The Council prepared numerous reports in 2011, and the Chairman and Members gave numerous public speeches. The reports, texts of speeches, and written statements accompanying testimony are available at the Council’s website, www.whitehouse.gov/cea. Finally, the Council publishes the monthly Economic Indicators, which is available on-line at www.gpo.gov/economicindicators. The Staff of the Council of Economic Advisers The staff of the Council consists of the senior staff, senior economists, staff economists, research economists, research assistants, and the administrative and support staff. The staff at the end of 2011 was: Senior Staff David P. Vandivier �������������������������������Chief of Staff Judith K. Hellerstein ����������������������������Chief Economist Steven N. Braun ������������������������������������Director of Macroeconomic Forecasting Adrienne Pilot ��������������������������������������Director of Statistical Office 302 | Appendix A Senior Economists Gene Amromin ������������������������������������Housing, Public Finance Lee G. Branstetter ��������������������������������International Trade and Investment, Innovation, and Manufacturing Thomas C. Buchmueller ��������������������Health Lisa D. Cook ������������������������������������������International Finance, Entrepreneurship, Innovation and Development Benjamin H. Harris ������������������������������Tax, Budget and Retirement Robert Johansson ��������������������������������Energy, Environment, Agriculture, Regulation Craig T. Peters ��������������������������������������Industrial Organization, Infrastructure, Innovation, Regulation Charles R. Pierret ��������������������������������Labor and Education Daniel J. Vine ���������������������������������������Macroeconomics Staff Economists Jeffrey A. Borowitz ������������������������������Housing, Labor, Education Andres Bustamante �����������������������������International Finance, Development, Entrepreneurship Colleen M. Carey ����������������������������������Health, Industrial Organization, Public Finance David Cho ����������������������������������������������Macroeconomics Judd N. L. Cramer ��������������������������������Labor and Immigration Reid B. Stevens ��������������������������������������Energy, Environment, Regulation Research Economists Pedro Spivakovsky-Gonzalez ��������������International Economics and Trade Julia H. Yoo ��������������������������������������������Public Finance, Housing, Macroeconomics Research Assistants Matthew L. Aks ������������������������������������Macroeconomics Sandra M. Levy ��������������������������������������Energy, Environment, Regulation Carter Mundell ��������������������������������������Education, Labor, Health Seth H. Werfel ��������������������������������������International Finance and Innovation Activities of the Council of Economic Advisers During 2011 | 303 Statistical Office The Statistical Office gathers, administers, and produces statistical information for the Council. Duties include preparing the statistical appendix to the Economic Report of the President and the monthly publication Economic Indicators. The staff also creates background materials for economic analysis and verifies statistical content in Presidential memoranda. The Office serves as the Council’s liaison to the statistical community. Brian A. Amorosi ����������������������������������Statistical Analyst Lindsay M. Kuberka ����������������������������Statistical Analyst Ms. Kuberka is on detail from the Census Bureau. Administrative Office The Administrative Office provides general support for the Council’s activities. This includes financial management, ethics compliance, human resource management, travel, operations of facilities, security, information technology, and telecommunications management support. Archana A. Snyder ��������������������������������Director of Finance and Administration Doris T. Searles ��������������������������������������Information Management Specialist Office of the Chairman Andres Bustamante ������������������������������Special Assistant to the Chairman and Staff Economist Paige Shevlin ������������������������������������������Special Assistant to the Chairman Michael P. Bourgeois ����������������������������Special Assistant to the Members Staff Support Sharon K. Thomas ��������������������������������Administrative Support and Executive Assistant to the Chief Economist, Senior Economists Interns Student interns provide invaluable help with research projects, dayto-day operations, and fact-checking. Interns during the year were: Noam Angrist, Dan Aloisio, David Bard, Obafemi Elegbede, Rahul Garabadu, Jeanne Jeong, Juliette Lu, Suril Kantaria, Sarah McGhee, Jeremy Patashnik, Benjamin Pyle, Clare Quinn, Sid Shankar, Daniel Seder, Alex T. Stein, Elizabeth Sundheim, and Lucas Zucker. 304 | Appendix A Departures in 2011 Jay C. Shambaugh left his position as Chief Economist of the Council in June, and he is presently on faculty at Georgetown University’s McDonough School of Business. In October, Nan Gibson left her position as Executive Director and Adam Hitchcock left his position as Chief of Staff in August. The senior economists who resigned in 2011(with the institutions to which they returned after leaving the Council in parentheses) were: Chad Bown (World Bank); Aaron Chatterji (Duke Fuqua School of Business); Thomas Davidoff (Sauder School of Business, UBC); Benjamin F. Jones (Northwestern University, Kellogg School); Lisa Kahn (Yale School of Management); Arik Levinson (Georgetown University); Helen Levy (University of Michigan School of Public Health); Matthew Magura (Department of Justice); Nicholas Mastronardi (US Air Force Academy); and Paul Smith (Federal Reserve Board). The staff economists who departed in 2011 were Douglas Campbell, Hoan Soo Lee, Sayeh Nikpay, James O’Brien, Jamin Speer, and Owen Zidar. Those who served as research assistants at the Council and resigned were Ravi Deedwania, Nicholas Hagerty, and Kia McLeod. Brittany Heyd, Meryl Holt, Eric Lesser, and Matthew Tully all served in the Office of the Chairman and resigned in 2011 to pursue other endeavors. Several long-term staff members departed as well. Dagmara Mocala Mathews left her position as Program Analyst after almost 10 dedicated years of service in the Statistical Office. There were two retirements at the Council in 2011. They are Rosemary M. Rogers, who served as the Administrative Officer and Lisa D. Branch who served as Executive Assistant to the Members. Mrs. Rogers devoted 30 years to working in the Executive Branch, with almost 20 of those years at the Council. Ms. Branch devoted 34 years to working in the Executive Branch, with 25 of those years at the Council. Their dedication, loyalty and diligence in serving the Council, Chairs, Members, staff and the people of the United States will be missed tremendously. Activities of the Council of Economic Advisers During 2011 | 305 A P P E N D I X B STATISTICAL TABLES RELATING TO INCOME, EMPLOYMENT, AND PRODUCTION C O N T E N T s National Income or Expenditure B–1. Page Gross domestic product, 1963–2011������������������������������������������������������������������������ 316 B–2. Real gross domestic product, 1963–2011���������������������������������������������������������������� 318 B–3. Quantity and price indexes for gross domestic product, and percent changes, 1963–2011������������������������������������������������������������������������������������������������������������������� 320 B–4. Percent changes in real gross domestic product, 1963–2011�������������������������������� 321 B–5. Contributions to percent change in real gross domestic product, 1963–2011��� 322 B–6. Chain-type quantity indexes for gross domestic product, 1963–2011���������������� 324 B–7. Chain-type price indexes for gross domestic product, 1963–2011���������������������� 326 B–8. Gross domestic product by major type of product, 1963–2011��������������������������� 328 B–9. Real gross domestic product by major type of product, 1963–2011�������������������� 329 B–10. Gross value added by sector, 1963–2011����������������������������������������������������������������� 330 B–11. Real gross value added by sector, 1963–2011���������������������������������������������������������� 331 B–12. Gross domestic product (GDP) by industry, value added, in current dollars and as a percentage of GDP, 1980–2010������������������������������������������������������������������ 332 B–13. Real gross domestic product by industry, value added, and percent changes, 1980–2010������������������������������������������������������������������������������������������������������������������� 334 B–14. Gross value added of nonfinancial corporate business, 1963–2011��������������������� 336 B–15. Gross value added and price, costs, and profits of nonfinancial corporate business, 1963–2011��������������������������������������������������������������������������������������������������� 337 B–16. Personal consumption expenditures, 1963–2011��������������������������������������������������� 338 B–17. Real personal consumption expenditures, 1995–2011������������������������������������������ 339 B–18. Private fixed investment by type, 1963–2011���������������������������������������������������������� 340 B–19. Real private fixed investment by type, 1995–2011������������������������������������������������� 341 B–20. Government consumption expenditures and gross investment by type, 1963–2011������������������������������������������������������������������������������������������������������������������� 342 B–21. Real government consumption expenditures and gross investment by type, 1995–2011������������������������������������������������������������������������������������������������������������������� 343 B–22. Private inventories and domestic final sales by industry, 1963–2011������������������ 344 B–23. Real private inventories and domestic final sales by industry, 1963–2011���������� 345 B–24. Foreign transactions in the national income and product accounts, 1963–2011������������������������������������������������������������������������������������������������������������������� 346 309 National Income or Expenditure—Continued B–25. Real exports and imports of goods and services, 1995–2011������������������������������� 347 B–26. Relation of gross domestic product, gross national product, net national product, and national income, 1963–2011������������������������������������������������������������� 348 B–27. Relation of national income and personal income, 1963–2011���������������������������� 349 B–28. National income by type of income, 1963–2011���������������������������������������������������� 350 B–29. Sources of personal income, 1963–2011������������������������������������������������������������������ 352 B–30. Disposition of personal income, 1963–2011����������������������������������������������������������� 354 B–31. Total and per capita disposable personal income and personal consumption expenditures, and per capita gross domestic product, in current and real dollars, 1963–2011������������������������������������������������������������������������������������������������������ 355 B–32. Gross saving and investment, 1963–2011���������������������������������������������������������������� 356 B–33. Median money income (in 2010 dollars) and poverty status of families and people, by race, selected years, 1998–2010������������������������������������������������������������� 358 Population, Employment, Wages, and Productivity B–34. Population by age group, 1939–2011����������������������������������������������������������������������� 359 B–35. Civilian population and labor force, 1929–2011���������������������������������������������������� 360 B–36. Civilian employment and unemployment by sex and age, 1965–2011���������������� 362 B–37. Civilian employment by demographic characteristic, 1965–2011����������������������� 363 B–38. Unemployment by demographic characteristic, 1965–2011��������������������������������� 364 B–39. Civilian labor force participation rate and employment/population ratio, 1965–2011������������������������������������������������������������������������������������������������������������������� 365 B–40. Civilian labor force participation rate by demographic characteristic, 1972–2011������������������������������������������������������������������������������������������������������������������� 366 B–41. Civilian employment/population ratio by demographic characteristic, 1972–2011������������������������������������������������������������������������������������������������������������������� 367 B–42. Civilian unemployment rate, 1965–2011����������������������������������������������������������������� 368 B–43. Civilian unemployment rate by demographic characteristic, 1972–2011����������� 369 B–44. Unemployment by duration and reason, 1965–2011��������������������������������������������� 370 B–45. Unemployment insurance programs, selected data, 1980–2011�������������������������� 371 B–46. Employees on nonagricultural payrolls, by major industry, 1967–2011������������� 372 B–47. Hours and earnings in private nonagricultural industries, 1965–2011 �������������� 374 B–48. Employment cost index, private industry, 1997–2011������������������������������������������� 375 B–49. Productivity and related data, business and nonfarm business sectors, 1962–2011������������������������������������������������������������������������������������������������������������������� 376 B–50. Changes in productivity and related data, business and nonfarm business sectors, 1962–2011����������������������������������������������������������������������������������������������������� 377 310 | Appendix B Production and Business Activity B–51. Industrial production indexes, major industry divisions, 1963–2011����������������� 378 B–52. Industrial production indexes, market groupings, 1963–2011����������������������������� 379 B–53. Industrial production indexes, selected manufacturing industries, 1968–2011������������������������������������������������������������������������������������������������������������������� 380 B–54. Capacity utilization rates, 1963–2011���������������������������������������������������������������������� 381 B–55. New construction activity, 1967–2011��������������������������������������������������������������������� 382 B–56. New private housing units started, authorized, and completed and houses sold, 1965–2011���������������������������������������������������������������������������������������������������������� 383 B–57. Manufacturing and trade sales and inventories, 1970–2011��������������������������������� 384 B–58. Manufacturers’ shipments and inventories, 1970–2011���������������������������������������� 385 B–59. Manufacturers’ new and unfilled orders, 1970–2011��������������������������������������������� 386 Prices B–60. Consumer price indexes for major expenditure classes, 1968–2011������������������� 387 B–61. Consumer price indexes for selected expenditure classes, 1968–2011���������������� 388 B–62. Consumer price indexes for commodities, services, and special groups, 1968–2011������������������������������������������������������������������������������������������������������������������� 390 B–63. Changes in special consumer price indexes, 1968–2011��������������������������������������� 391 B–64. Changes in consumer price indexes for commodities and services, 1940–2011������������������������������������������������������������������������������������������������������������������� 392 B–65. Producer price indexes by stage of processing, 1965–2011����������������������������������� 393 B–66. Producer price indexes by stage of processing, special groups, 1974–2011�������� 395 B–67. Producer price indexes for major commodity groups, 1965–2011���������������������� 396 B–68. Changes in producer price indexes for finished goods, 1972–2011��������������������� 398 Money Stock, Credit, and Finance B–69. Money stock and debt measures, 1972–2011���������������������������������������������������������� 399 B–70. Components of money stock measures, 1972–2011���������������������������������������������� 400 B–71. Aggregate reserves of depository institutions and the monetary base, 1982–2011������������������������������������������������������������������������������������������������������������������� 402 B–72. Bank credit at all commercial banks, 1974–2011��������������������������������������������������� 403 B–73. Bond yields and interest rates, 1940–2011�������������������������������������������������������������� 404 B–74. Credit market borrowing, 2003–2011���������������������������������������������������������������������� 406 B–75. Mortgage debt outstanding by type of property and of financing, 1954–2011������������������������������������������������������������������������������������������������������������������� 408 B–76. Mortgage debt outstanding by holder, 1954–2011������������������������������������������������� 409 B–77. Consumer credit outstanding, 1960–2011�������������������������������������������������������������� 410 Contents | 311 Government Finance B–78. Federal receipts, outlays, surplus or deficit, and debt, fiscal years, 1945–2013�� 411 B–79. Federal receipts, outlays, surplus or deficit, and debt, as percent of gross domestic product, fiscal years 1939–2013��������������������������������������������������������������� 412 B–80. Federal receipts and outlays, by major category, and surplus or deficit, fiscal years 1945–2013��������������������������������������������������������������������������������������������������������� 413 B–81. Federal receipts, outlays, surplus or deficit, and debt, fiscal years 2008–2013��� 414 B–82. Federal and State and local government current receipts and expenditures, national income and product accounts (NIPA), 1963–2011�������������������������������� 415 B–83. Federal and State and local government current receipts and expenditures, national income and product accounts (NIPA), by major type, 1963–2011������ 416 B–84. Federal Government current receipts and expenditures, national income and product accounts (NIPA), 1963–2011��������������������������������������������������������������������� 417 B–85. State and local government current receipts and expenditures, national income and product accounts (NIPA), 1963–2011������������������������������������������������ 418 B–86. State and local government revenues and expenditures, selected fiscal years, 1946–2009������������������������������������������������������������������������������������������������������������������� 419 B–87. U.S. Treasury securities outstanding by kind of obligation, 1973–2011�������������� 420 B–88. Maturity distribution and average length of marketable interest-bearing public debt securities held by private investors, 1973–2011��������������������������������� 421 B–89. Estimated ownership of U.S. Treasury securities, 1998–2011������������������������������� 422 Corporate Profits and Finance B–90. Corporate profits with inventory valuation and capital consumption adjustments, 1963–2011�������������������������������������������������������������������������������������������� 423 B–91. Corporate profits by industry, 1963–2011��������������������������������������������������������������� 424 B–92. Corporate profits of manufacturing industries, 1963–2011���������������������������������� 425 B–93. Sales, profits, and stockholders’ equity, all manufacturing corporations, 1970–2011������������������������������������������������������������������������������������������������������������������� 426 B–94. Relation of profits after taxes to stockholders’ equity and to sales, all manufacturing corporations, 1962–2011���������������������������������������������������������������� 427 B–95. Historical stock prices and yields, 1949–2003�������������������������������������������������������� 428 B–96. Common stock prices and yields, 2000–2011��������������������������������������������������������� 429 Agriculture B–97. Farm income, 1950–2011������������������������������������������������������������������������������������������ 430 B–98. Farm business balance sheet, 1952–2011���������������������������������������������������������������� 431 B–99. Farm output and productivity indexes, 1950–2009����������������������������������������������� 432 B–100. Farm input use, selected inputs, 1950–2011������������������������������������������������������������ 433 312 | Appendix B AGRICULTURE—Continued B–101. Agricultural price indexes and farm real estate value, 1975–2011����������������������� 434 B–102. U.S. exports and imports of agricultural commodities, 1950–2011��������������������� 435 International Statistics B–103. U.S. international transactions, 1953–2011������������������������������������������������������������� 436 B–104. U.S. international trade in goods by principal end-use category, 1965–2011����� 438 B–105. U.S. international trade in goods by area, 2003–2011�������������������������������������������� 439 B–106. U.S. international trade in goods on balance of payments (BOP) and Census basis, and trade in services on BOP basis, 1983–2011������������������������������������������ 440 B–107. International investment position of the United States at year-end, 2004–2010������������������������������������������������������������������������������������������������������������������� 441 B–108. Industrial production and consumer prices, major industrial countries, 1985–2011������������������������������������������������������������������������������������������������������������������� 442 B–109. Civilian unemployment rate, and hourly compensation, major industrial countries, 1985–2011������������������������������������������������������������������������������������������������� 443 B–110. Foreign exchange rates, 1992–2011�������������������������������������������������������������������������� 444 B–111. International reserves, selected years, 1992–2011�������������������������������������������������� 445 B–112. Growth rates in real gross domestic product, 1993–2012������������������������������������� 446 Contents | 313 General Notes Detail in these tables may not add to totals because of rounding. Because of the formula used for calculating real gross domestic product (GDP), the chained (2005) dollar estimates for the detailed components do not add to the chained-dollar value of GDP or to any intermediate aggregate. The Department of Commerce (Bureau of Economic Analysis) no longer publishes chained-dollar estimates prior to 1995, except for selected series. Unless otherwise noted, all dollar figures are in current dollars. Symbols used: p Preliminary. ... Not available (also, not applicable). Data in these tables reflect revisions made by the source agencies through January 27, 2012. In particular, tables containing national income and product accounts (NIPA) estimates reflect revisions released by the Department of Commerce in July 2011. General Notes | 315 National Income or Expenditure Table B–1. Gross domestic product, 1963–2011 [Billions of dollars, except as noted; quarterly data at seasonally adjusted annual rates] Personal consumption expenditures Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product 617.8 663.6 719.1 787.7 832.4 909.8 984.4 1,038.3 1,126.8 1,237.9 1,382.3 1,499.5 1,637.7 1,824.6 2,030.1 2,293.8 2,562.2 2,788.1 3,126.8 3,253.2 3,534.6 3,930.9 4,217.5 4,460.1 4,736.4 5,100.4 5,482.1 5,800.5 5,992.1 6,342.3 6,667.4 7,085.2 7,414.7 7,838.5 8,332.4 8,793.5 9,353.5 9,951.5 10,286.2 10,642.3 11,142.2 11,853.3 12,623.0 13,377.2 14,028.7 14,291.5 13,939.0 14,526.5 15,087.7 14,273.9 14,415.5 14,395.1 14,081.7 13,893.7 13,854.1 13,920.5 14,087.4 14,277.9 14,467.8 14,605.5 14,755.0 14,867.8 15,012.8 15,176.1 15,294.3 Fixed investment Total 382.7 411.5 443.8 480.9 507.8 558.0 605.1 648.3 701.6 770.2 852.0 932.9 1,033.8 1,151.3 1,277.8 1,427.6 1,591.2 1,755.8 1,939.5 2,075.5 2,288.6 2,501.1 2,717.6 2,896.7 3,097.0 3,350.1 3,594.5 3,835.5 3,980.1 4,236.9 4,483.6 4,750.8 4,987.3 5,273.6 5,570.6 5,918.5 6,342.8 6,830.4 7,148.8 7,439.2 7,804.1 8,270.6 8,803.5 9,301.0 9,772.3 10,035.5 9,866.1 10,245.5 10,722.6 10,018.5 10,126.5 10,135.8 9,861.3 9,781.7 9,781.6 9,911.1 9,990.0 10,103.7 10,184.8 10,276.6 10,417.1 10,571.7 10,676.0 10,784.5 10,858.1 See next page for continuation of table. 316 | Appendix B Gross private domestic investment Goods 198.2 212.3 229.7 249.6 259.0 284.6 304.7 318.8 342.1 373.8 416.6 451.5 491.3 546.3 600.4 663.6 737.9 799.8 869.4 899.3 973.8 1,063.7 1,137.6 1,195.6 1,256.3 1,337.3 1,423.8 1,491.3 1,497.4 1,563.3 1,642.3 1,746.6 1,815.5 1,917.7 2,006.8 2,110.0 2,290.0 2,459.1 2,534.0 2,610.0 2,728.0 2,892.1 3,076.7 3,224.7 3,363.9 3,381.7 3,197.5 3,387.0 3,645.2 3,422.3 3,466.9 3,456.1 3,181.4 3,130.7 3,143.6 3,245.6 3,270.0 3,338.1 3,340.1 3,386.5 3,483.4 3,592.2 3,622.7 3,661.2 3,704.5 Services 184.6 199.2 214.1 231.3 248.8 273.4 300.4 329.5 359.5 396.4 435.4 481.4 542.5 604.9 677.4 764.1 853.2 956.0 1,070.1 1,176.2 1,314.8 1,437.4 1,580.0 1,701.1 1,840.7 2,012.7 2,170.7 2,344.2 2,482.6 2,673.6 2,841.2 3,004.3 3,171.7 3,355.9 3,563.9 3,808.5 4,052.8 4,371.2 4,614.8 4,829.2 5,076.1 5,378.5 5,726.8 6,076.3 6,408.3 6,653.8 6,668.7 6,858.5 7,077.4 6,596.2 6,659.6 6,679.7 6,679.9 6,651.0 6,638.0 6,665.5 6,720.1 6,765.6 6,844.7 6,890.1 6,933.7 6,979.4 7,053.3 7,123.2 7,153.6 Total 93.8 102.1 118.2 131.3 128.6 141.2 156.4 152.4 178.2 207.6 244.5 249.4 230.2 292.0 361.3 438.0 492.9 479.3 572.4 517.2 564.3 735.6 736.2 746.5 785.0 821.6 874.9 861.0 802.9 864.8 953.3 1,097.3 1,144.0 1,240.2 1,388.7 1,510.8 1,641.5 1,772.2 1,661.9 1,647.0 1,729.7 1,968.6 2,172.3 2,327.1 2,295.2 2,087.6 1,546.8 1,795.1 1,913.6 2,185.7 2,165.4 2,086.3 1,913.0 1,620.1 1,493.8 1,481.2 1,592.2 1,702.3 1,809.7 1,850.5 1,818.0 1,853.1 1,895.3 1,906.6 1,999.7 Nonresidential Total 88.1 97.2 109.0 117.7 118.7 132.1 147.3 150.4 169.9 198.5 228.6 235.4 236.5 274.8 339.0 412.2 474.9 485.6 542.6 532.1 570.1 670.2 714.4 739.9 757.8 803.1 847.3 846.4 803.3 848.5 932.5 1,033.5 1,112.9 1,209.4 1,317.7 1,447.1 1,580.7 1,717.7 1,700.2 1,634.9 1,713.3 1,903.6 2,122.3 2,267.2 2,266.1 2,128.7 1,707.6 1,728.2 1,866.4 2,205.2 2,183.7 2,130.5 1,995.5 1,799.6 1,694.3 1,678.3 1,658.3 1,658.0 1,731.6 1,743.8 1,779.3 1,791.1 1,841.7 1,905.8 1,927.1 Total 56.0 63.0 74.8 85.4 86.4 93.4 104.7 109.0 114.1 128.8 153.3 169.5 173.7 192.4 228.7 280.6 333.9 362.4 420.0 426.5 417.2 489.6 526.2 519.8 524.1 563.8 607.7 622.4 598.2 612.1 666.6 731.4 810.0 875.4 968.6 1,061.1 1,154.9 1,268.7 1,227.8 1,125.4 1,135.7 1,223.0 1,347.3 1,505.3 1,637.5 1,656.3 1,353.0 1,390.1 1,529.2 1,689.3 1,689.0 1,665.9 1,580.9 1,430.6 1,351.9 1,324.3 1,305.1 1,318.7 1,377.1 1,416.5 1,447.9 1,460.5 1,506.0 1,568.7 1,581.5 EquipStructures ment and software 21.2 23.7 28.3 31.3 31.5 33.6 37.7 40.3 42.7 47.2 55.0 61.2 61.4 65.9 74.6 93.6 117.7 136.2 167.3 177.6 154.3 177.4 194.5 176.5 174.2 182.8 193.7 202.9 183.6 172.6 177.2 186.8 207.3 224.6 250.3 275.1 283.9 318.1 329.7 282.8 281.9 306.7 351.8 433.7 524.9 586.3 449.9 374.4 407.8 570.9 589.6 594.7 590.0 527.4 461.4 424.8 386.1 361.2 370.2 376.6 389.6 379.5 405.2 424.8 421.7 34.8 39.2 46.5 54.0 54.9 59.9 67.0 68.7 71.5 81.7 98.3 108.2 112.4 126.4 154.1 187.0 216.2 226.2 252.7 248.9 262.9 312.2 331.7 343.3 349.9 381.0 414.0 419.5 414.6 439.6 489.4 544.6 602.8 650.8 718.3 786.0 871.0 950.5 898.1 842.7 853.8 916.4 995.6 1,071.7 1,112.6 1,070.0 903.0 1,015.7 1,121.4 1,118.4 1,099.4 1,071.2 990.9 903.2 890.5 899.5 918.9 957.5 1,006.9 1,039.9 1,058.3 1,081.0 1,100.8 1,143.9 1,159.9 Residential 32.1 34.3 34.2 32.3 32.4 38.7 42.6 41.4 55.8 69.7 75.3 66.0 62.7 82.5 110.3 131.6 141.0 123.2 122.6 105.7 152.9 180.6 188.2 220.1 233.7 239.3 239.5 224.0 205.1 236.3 266.0 302.1 302.9 334.1 349.1 385.9 425.8 449.0 472.4 509.5 577.6 680.6 775.0 761.9 628.7 472.4 354.7 338.1 337.2 515.9 494.6 464.6 414.6 369.0 342.4 353.9 353.2 339.3 354.5 327.3 331.3 330.6 335.7 337.0 345.6 Change in private inventories 5.6 4.8 9.2 13.6 9.9 9.1 9.2 2.0 8.3 9.1 15.9 14.0 –6.3 17.1 22.3 25.8 18.0 –6.3 29.8 –14.9 –5.8 65.4 21.8 6.6 27.1 18.5 27.7 14.5 –.4 16.3 20.8 63.8 31.2 30.8 71.0 63.7 60.8 54.5 –38.3 12.0 16.4 64.9 50.0 60.0 29.1 –41.1 –160.8 66.9 47.2 –19.5 –18.3 –44.1 –82.5 –179.5 –200.5 –197.1 –66.1 44.3 78.1 106.7 38.7 62.0 53.6 .8 72.6 Table B–1. Gross domestic product, 1963–2011—Continued [Billions of dollars, except as noted; quarterly data at seasonally adjusted annual rates] Net exports of goods and services Government consumption expenditures and gross investment Year or quarter Federal Net exports Exports Imports 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� 4.9 6.9 5.6 3.9 3.6 1.4 1.4 4.0 .6 –3.4 4.1 –.8 16.0 –1.6 –23.1 –25.4 –22.5 –13.1 –12.5 –20.0 –51.7 –102.7 –115.2 –132.5 –145.0 –110.1 –87.9 –77.6 –27.0 –32.8 –64.4 –92.7 –90.7 –96.3 –101.4 –161.8 –262.1 –382.1 –371.0 –427.2 –504.1 –618.7 –722.7 –769.3 –713.1 –709.7 –391.5 –516.9 –578.2 –742.3 –746.1 –756.9 –593.7 –383.5 –338.3 –406.7 –437.6 –495.8 –531.2 –540.3 –500.2 –571.3 –597.1 –562.3 –582.1 31.1 35.0 37.1 40.9 43.5 47.9 51.9 59.7 63.0 70.8 95.3 126.7 138.7 149.5 159.4 186.9 230.1 280.8 305.2 283.2 277.0 302.4 302.0 320.3 363.8 443.9 503.1 552.1 596.6 635.0 655.6 720.7 811.9 867.7 954.4 953.9 989.3 1,093.2 1,027.7 1,003.0 1,041.0 1,180.2 1,305.1 1,471.0 1,661.7 1,846.8 1,583.0 1,839.8 2,087.6 1,819.3 1,922.8 1,933.8 1,711.1 1,522.2 1,520.8 1,590.3 1,699.0 1,749.5 1,813.8 1,860.6 1,935.3 2,024.1 2,085.3 2,119.2 2,121.6 26.1 28.1 31.5 37.1 39.9 46.6 50.5 55.8 62.3 74.2 91.2 127.5 122.7 151.1 182.4 212.3 252.7 293.8 317.8 303.2 328.6 405.1 417.2 452.9 508.7 554.0 591.0 629.7 623.5 667.8 720.0 813.4 902.6 964.0 1,055.8 1,115.7 1,251.4 1,475.3 1,398.7 1,430.2 1,545.1 1,798.9 2,027.8 2,240.3 2,374.8 2,556.5 1,974.6 2,356.7 2,665.8 2,561.6 2,668.9 2,690.6 2,304.8 1,905.7 1,859.1 1,997.0 2,136.5 2,245.3 2,345.0 2,400.9 2,435.5 2,595.4 2,682.4 2,681.6 2,703.6 Total 136.4 143.2 151.4 171.6 192.5 209.3 221.4 233.7 246.4 263.4 281.7 317.9 357.7 383.0 414.1 453.6 500.7 566.1 627.5 680.4 733.4 796.9 878.9 949.3 999.4 1,038.9 1,100.6 1,181.7 1,236.1 1,273.5 1,294.8 1,329.8 1,374.0 1,421.0 1,474.4 1,526.1 1,631.3 1,731.0 1,846.4 1,983.3 2,112.6 2,232.8 2,369.9 2,518.4 2,674.2 2,878.1 2,917.5 3,002.8 3,029.7 2,812.0 2,869.6 2,929.8 2,901.1 2,875.5 2,916.9 2,935.0 2,942.7 2,967.7 3,004.6 3,018.7 3,020.2 3,014.4 3,038.6 3,047.3 3,018.6 Total 76.9 78.4 80.4 92.4 104.6 111.3 113.3 113.4 113.6 119.6 122.5 134.5 149.0 159.7 175.4 190.9 210.6 243.7 280.2 310.8 342.9 374.3 412.8 438.4 459.5 461.6 481.4 507.5 526.6 532.9 525.0 518.6 518.8 527.0 531.0 531.0 554.9 576.1 611.7 680.6 756.5 824.6 876.3 931.7 976.3 1,080.1 1,142.7 1,222.8 1,232.7 1,042.7 1,066.0 1,100.6 1,111.2 1,105.3 1,137.2 1,157.7 1,170.6 1,195.2 1,224.5 1,237.5 1,234.3 1,219.9 1,237.1 1,248.9 1,225.0 National Nondefense defense 61.0 60.2 60.6 71.7 83.4 89.2 89.5 87.6 84.6 86.9 88.1 95.6 103.9 111.1 120.9 130.5 145.2 168.0 196.2 225.9 250.6 281.5 311.2 330.8 350.0 354.7 362.1 373.9 383.1 376.8 363.0 353.8 348.8 354.8 349.8 346.1 361.1 371.0 393.0 437.7 497.9 550.8 589.0 624.9 662.3 737.8 774.9 819.2 824.8 706.0 724.7 758.4 762.1 747.7 771.6 789.0 791.4 803.5 818.0 831.3 823.9 809.0 830.6 844.0 815.6 15.9 18.2 19.8 20.8 21.2 22.0 23.8 25.8 29.1 32.7 34.3 39.0 45.1 48.6 54.5 60.4 65.4 75.8 83.9 84.9 92.3 92.7 101.6 107.6 109.6 106.8 119.3 133.6 143.4 156.1 162.0 164.8 170.0 172.2 181.1 184.9 193.8 205.0 218.7 242.9 258.5 273.9 287.3 306.8 314.0 342.3 367.8 403.6 407.9 336.7 341.3 342.1 349.0 357.7 365.7 368.6 379.2 391.6 406.5 406.2 410.3 410.9 406.5 404.9 409.4 State and local 59.5 64.8 71.0 79.2 87.9 98.0 108.2 120.3 132.8 143.8 159.2 183.4 208.7 223.3 238.7 262.7 290.2 322.4 347.3 369.7 390.5 422.6 466.1 510.9 539.9 577.3 619.2 674.2 709.5 740.6 769.8 811.2 855.3 894.0 943.5 995.0 1,076.3 1,154.9 1,234.7 1,302.7 1,356.1 1,408.2 1,493.6 1,586.7 1,697.9 1,798.0 1,774.8 1,780.0 1,797.0 1,769.3 1,803.7 1,829.2 1,789.9 1,770.1 1,779.7 1,777.3 1,772.1 1,772.6 1,780.1 1,781.2 1,786.0 1,794.4 1,801.5 1,798.5 1,793.7 Final sales of domestic product Gross domestic purchases 1 Addendum: Gross national product 2 612.1 658.8 709.9 774.1 822.6 900.8 975.3 1,036.3 1,118.6 1,228.8 1,366.4 1,485.5 1,644.0 1,807.5 2,007.8 2,268.0 2,544.2 2,794.5 3,097.0 3,268.1 3,540.4 3,865.5 4,195.6 4,453.5 4,709.2 5,081.9 5,454.5 5,786.0 5,992.5 6,326.0 6,646.5 7,021.4 7,383.5 7,807.7 8,261.4 8,729.8 9,292.7 9,896.9 10,324.5 10,630.3 11,125.8 11,788.3 12,573.0 13,317.3 13,999.6 14,332.7 14,099.8 14,459.6 15,040.5 14,293.4 14,433.8 14,439.2 14,164.2 14,073.3 14,054.6 14,117.6 14,153.5 14,233.6 14,389.8 14,498.8 14,716.3 14,805.8 14,959.2 15,175.3 15,221.7 612.8 656.7 713.5 783.8 828.9 908.5 983.0 1,034.4 1,126.2 1,241.3 1,378.2 1,500.3 1,621.7 1,826.2 2,053.2 2,319.1 2,584.8 2,801.2 3,139.4 3,273.2 3,586.3 4,033.6 4,332.7 4,592.6 4,881.3 5,210.5 5,570.0 5,878.1 6,019.1 6,375.1 6,731.7 7,177.9 7,505.3 7,934.8 8,433.7 8,955.3 9,615.6 10,333.5 10,657.2 11,069.5 11,646.3 12,471.9 13,345.7 14,146.5 14,741.7 15,001.3 14,330.5 15,043.4 15,665.9 15,016.2 15,161.5 15,151.9 14,675.4 14,277.3 14,192.4 14,327.2 14,525.0 14,773.7 14,999.0 15,145.8 15,255.2 15,439.1 15,609.9 15,738.4 15,876.3 622.2 668.6 724.4 792.8 837.8 915.9 990.5 1,044.7 1,134.4 1,246.4 1,394.9 1,515.0 1,650.7 1,841.4 2,050.4 2,315.3 2,594.2 2,822.3 3,159.8 3,289.7 3,571.7 3,967.2 4,244.0 4,477.7 4,754.0 5,123.8 5,508.1 5,835.0 6,022.0 6,371.4 6,698.5 7,109.2 7,444.3 7,870.1 8,355.8 8,810.8 9,381.3 9,989.2 10,338.1 10,691.4 11,210.9 11,944.5 12,720.1 13,449.6 14,151.9 14,460.7 14,091.2 14,715.9 ������������� 14,452.5 14,596.8 14,594.0 14,199.5 14,026.4 13,994.4 14,084.2 14,259.8 14,447.4 14,664.0 14,812.8 14,939.4 15,094.9 15,274.0 15,443.4 ������������� Percent change from preceding period Gross Gross domes- domestic tic purproduct chases 1 5.5 7.4 8.4 9.5 5.7 9.3 8.2 5.5 8.5 9.9 11.7 8.5 9.2 11.4 11.3 13.0 11.7 8.8 12.1 4.0 8.7 11.2 7.3 5.8 6.2 7.7 7.5 5.8 3.3 5.8 5.1 6.3 4.7 5.7 6.3 5.5 6.4 6.4 3.4 3.5 4.7 6.4 6.5 6.0 4.9 1.9 –2.5 4.2 3.9 .6 4.0 –.6 –8.4 –5.2 –1.1 1.9 4.9 5.5 5.4 3.9 4.2 3.1 4.0 4.4 3.2 5.4 7.2 8.6 9.9 5.7 9.6 8.2 5.2 8.9 10.2 11.0 8.9 8.1 12.6 12.4 13.0 11.5 8.4 12.1 4.3 9.6 12.5 7.4 6.0 6.3 6.7 6.9 5.5 2.4 5.9 5.6 6.6 4.6 5.7 6.3 6.2 7.4 7.5 3.1 3.9 5.2 7.1 7.0 6.0 4.2 1.8 –4.5 5.0 4.1 1.9 3.9 –.3 –12.0 –10.4 –2.4 3.9 5.6 7.0 6.2 4.0 2.9 4.9 4.5 3.3 3.6 1 Gross domestic product (GDP) less exports of goods and services plus imports of goods and services. 2 GDP plus net income receipts from rest of the world. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 317 Table B–2. Real gross domestic product, 1963–2011 [Billions of chained (2005) dollars, except as noted; quarterly data at seasonally adjusted annual rates] Personal consumption expenditures Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product 3,204.0 3,389.4 3,607.0 3,842.1 3,939.2 4,129.9 4,258.2 4,266.3 4,409.5 4,643.8 4,912.8 4,885.7 4,875.4 5,136.9 5,373.1 5,672.8 5,850.1 5,834.0 5,982.1 5,865.9 6,130.9 6,571.5 6,843.4 7,080.5 7,307.0 7,607.4 7,879.2 8,027.1 8,008.3 8,280.0 8,516.2 8,863.1 9,086.0 9,425.8 9,845.9 10,274.7 10,770.7 11,216.4 11,337.5 11,543.1 11,836.4 12,246.9 12,623.0 12,958.5 13,206.4 13,161.9 12,703.1 13,088.0 13,313.4 13,266.8 13,310.5 13,186.9 12,883.5 12,663.2 12,641.3 12,694.5 12,813.5 12,937.7 13,058.5 13,139.6 13,216.1 13,227.9 13,271.8 13,331.6 13,422.4 Fixed investment Total 1,989.0 2,107.5 2,240.8 2,367.9 2,438.8 2,579.6 2,676.2 2,738.9 2,843.3 3,018.1 3,167.7 3,141.4 3,212.6 3,391.5 3,534.3 3,690.1 3,777.8 3,764.5 3,821.6 3,874.9 4,096.4 4,313.6 4,538.3 4,722.4 4,868.0 5,064.3 5,207.5 5,313.7 5,321.7 5,503.2 5,698.6 5,916.2 6,076.2 6,288.3 6,520.4 6,862.3 7,237.6 7,604.6 7,810.3 8,018.3 8,244.5 8,515.8 8,803.5 9,054.5 9,262.9 9,211.7 9,037.5 9,220.9 9,421.1 9,289.1 9,285.8 9,196.0 9,076.0 9,040.9 8,998.5 9,050.3 9,060.2 9,121.2 9,186.9 9,247.1 9,328.4 9,376.7 9,392.7 9,433.5 9,481.3 See next page for continuation of table. 318 | Appendix B Gross private domestic investment Goods ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 1,896.0 1,980.9 2,075.3 2,215.5 2,392.0 2,518.2 2,597.3 2,702.9 2,827.2 2,953.3 3,076.7 3,178.9 3,273.5 3,192.9 3,098.0 3,230.7 3,351.9 3,249.0 3,252.7 3,187.9 3,082.0 3,082.6 3,064.3 3,120.7 3,124.6 3,173.3 3,202.9 3,240.8 3,306.0 3,344.4 3,331.2 3,342.7 3,389.2 Services ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 4,208.5 4,331.7 4,465.3 4,662.1 4,853.1 5,093.6 5,219.1 5,318.5 5,418.2 5,562.7 5,726.8 5,875.6 5,990.2 6,017.0 5,935.5 5,991.8 6,075.4 6,039.7 6,032.9 6,006.5 5,988.8 5,953.5 5,928.6 5,926.8 5,932.9 5,947.4 5,984.3 6,008.1 6,027.5 6,039.1 6,067.0 6,096.1 6,099.4 Total 353.0 382.1 435.7 474.1 452.4 478.7 506.6 473.4 527.3 589.8 658.9 610.3 502.2 603.7 694.9 778.7 803.5 715.2 779.6 670.3 732.8 948.7 939.8 933.5 962.2 984.9 1,024.4 989.9 909.4 983.1 1,070.9 1,216.4 1,254.3 1,365.3 1,535.2 1,688.9 1,837.6 1,963.1 1,825.2 1,800.4 1,870.1 2,058.2 2,172.3 2,231.8 2,159.5 1,939.8 1,454.2 1,714.9 1,795.2 2,055.7 2,024.0 1,934.7 1,744.6 1,490.4 1,397.2 1,407.3 1,522.0 1,630.0 1,728.3 1,766.8 1,734.5 1,750.9 1,778.4 1,784.2 1,867.4 Residential Change in private inventories ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 456.1 492.5 501.8 540.4 574.2 580.0 583.3 613.8 664.3 729.5 775.0 718.2 584.2 444.4 345.6 330.8 326.2 481.3 462.8 437.8 395.8 354.9 334.3 348.2 344.8 330.8 348.2 321.1 323.1 321.1 324.4 325.4 333.9 ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ ������������������ 32.1 31.2 77.4 71.6 68.5 60.2 –41.8 12.8 17.3 66.3 50.0 59.4 27.7 –36.3 –144.9 58.8 35.6 –12.5 –14.2 –38.1 –80.3 –161.6 –183.0 –178.7 –56.5 39.9 64.6 92.3 38.3 49.1 39.1 –2.0 56.0 Nonresidential Total ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 1,231.2 1,341.6 1,465.4 1,624.4 1,775.5 1,906.8 1,870.7 1,791.5 1,854.7 1,992.5 2,122.3 2,172.7 2,130.6 1,978.6 1,606.3 1,648.4 1,757.8 2,066.4 2,039.1 1,973.5 1,835.4 1,665.5 1,589.8 1,592.6 1,577.5 1,582.0 1,654.0 1,663.5 1,693.9 1,699.0 1,736.7 1,790.4 1,805.0 Total ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 787.9 861.5 965.5 1,081.4 1,194.3 1,311.3 1,274.8 1,173.7 1,189.6 1,263.0 1,347.3 1,455.5 1,550.0 1,537.6 1,263.2 1,319.2 1,432.4 1,589.1 1,580.0 1,539.2 1,442.3 1,312.9 1,257.6 1,247.0 1,235.2 1,253.3 1,308.0 1,343.6 1,371.9 1,378.9 1,413.2 1,465.6 1,471.9 EquipStructures ment and software ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 342.0 361.4 387.9 407.7 408.2 440.0 433.3 356.6 343.0 346.7 351.8 384.0 438.2 466.4 367.3 309.1 321.8 463.8 474.4 469.9 457.5 415.3 375.4 354.9 323.7 301.5 306.9 310.1 318.0 305.9 321.9 332.9 326.7 ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 489.4 541.4 615.9 705.2 805.0 889.2 860.6 824.2 850.0 917.3 995.6 1,071.1 1,106.8 1,059.4 889.7 1,019.4 1,124.1 1,117.2 1,094.6 1,056.8 969.0 883.7 874.2 888.0 912.9 958.8 1,010.1 1,044.1 1,064.5 1,086.9 1,103.5 1,145.7 1,160.3 Table B–2. Real gross domestic product, 1963–2011—Continued [Billions of chained (2005) dollars, except as noted; quarterly data at seasonally adjusted annual rates] Net exports of goods and services Government consumption expenditures and gross investment Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Federal Net exports Exports Imports ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� –98.8 –110.7 –139.8 –252.5 –356.4 –451.3 –471.8 –548.5 –603.7 –687.9 –722.7 –729.4 –648.8 –494.8 –358.8 –421.8 –412.3 –550.2 –486.2 –464.6 –478.0 –404.2 –331.8 –352.4 –346.9 –376.8 –437.4 –458.7 –414.2 –424.4 –416.4 –402.8 –405.8 111.4 124.5 128.0 136.9 140.0 151.0 158.3 175.3 178.3 191.7 227.8 245.8 244.3 255.0 261.1 288.6 317.2 351.4 355.7 328.5 320.1 346.2 356.7 384.1 425.4 493.5 550.2 599.7 639.5 683.5 705.9 767.4 845.1 915.3 1,024.3 1,047.7 1,093.4 1,187.4 1,120.8 1,098.3 1,116.0 1,222.5 1,305.1 1,422.1 1,554.4 1,649.3 1,494.0 1,663.2 1,776.3 1,643.9 1,693.9 1,678.7 1,580.6 1,451.1 1,449.4 1,497.3 1,578.3 1,606.2 1,645.0 1,684.8 1,716.8 1,749.6 1,765.0 1,785.2 1,805.6 130.0 996.1 ������������� 136.9 1,018.0 ������������� 151.5 1,048.7 ������������� 174.0 1,141.1 ������������� 186.7 1,228.7 ������������� 214.5 1,267.2 ������������� 226.7 1,264.3 ������������� 236.4 1,233.7 ������������� 249.0 1,206.9 ������������� 277.0 1,198.1 ������������� 289.9 1,193.9 ������������� 283.3 1,224.0 ������������� 251.8 1,251.6 ������������� 301.1 1,257.2 ������������� 334.0 1,271.0 ������������� 362.9 1,308.4 ������������� 369.0 1,332.8 ������������� 344.5 1,358.8 ������������� 353.5 1,371.2 ������������� 349.1 1,395.3 ������������� 393.1 1,446.3 ������������� 488.8 1,494.9 ������������� 520.5 1,599.0 ������������� 565.0 1,696.2 ������������� 598.4 1,737.1 ������������� 621.9 1,758.9 ������������� 649.3 1,806.8 ������������� 672.6 1,864.0 ������������� 671.6 1,884.4 ������������� 718.7 1,893.2 ������������� 780.8 1,878.2 ������������� 873.9 1,878.0 ������������� 943.9 1,888.9 704.1 1,026.0 1,907.9 696.0 1,164.1 1,943.8 689.1 1,300.2 1,985.0 681.4 1,449.9 2,056.1 694.6 1,638.7 2,097.8 698.1 1,592.6 2,178.3 726.5 1,646.8 2,279.6 779.5 1,719.7 2,330.5 831.1 1,910.4 2,362.0 865.0 2,027.8 2,369.9 876.3 2,151.5 2,402.1 894.9 2,203.2 2,434.2 906.1 2,144.0 2,497.4 971.1 1,852.8 2,539.6 1,029.5 2,085.0 2,556.8 1,075.9 2,188.7 2,502.0 1,054.7 2,194.1 2,473.9 943.8 2,180.1 2,484.5 955.1 2,143.3 2,510.7 982.0 2,058.6 2,520.5 1,003.5 1,855.3 2,509.6 995.2 1,781.2 2,546.0 1,029.2 1,849.7 2,554.2 1,043.9 1,925.2 2,548.5 1,049.6 1,983.0 2,540.6 1,056.9 2,082.4 2,564.0 1,079.4 2,143.5 2,570.3 1,087.8 2,131.0 2,552.1 1,079.6 2,173.9 2,513.9 1,053.3 2,181.4 2,508.2 1,058.3 2,187.9 2,507.6 1,063.7 2,211.5 2,478.5 1,043.7 Total Total National Nondefense defense ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� 476.8 470.4 457.2 447.5 455.8 453.5 470.7 505.3 549.2 580.4 589.0 598.4 611.8 657.7 695.6 718.3 701.4 634.7 643.1 669.7 683.2 669.9 695.7 709.5 707.3 708.2 718.6 728.6 717.7 694.0 705.9 714.6 691.1 ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� ������������� 227.5 225.7 231.9 233.7 238.7 244.4 255.5 273.9 281.7 284.6 287.3 296.6 294.2 313.3 333.8 357.7 353.3 309.1 312.1 312.0 320.2 325.3 333.4 334.3 342.2 348.7 360.8 359.2 361.9 359.4 352.4 349.0 352.6 State and local ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ 1,183.6 1,211.1 1,254.3 1,303.8 1,361.8 1,400.1 1,452.3 1,500.6 1,499.7 1,497.1 1,493.6 1,507.2 1,528.1 1,528.1 1,514.2 1,487.0 1,453.4 1,530.9 1,530.5 1,530.8 1,520.1 1,517.2 1,520.7 1,514.9 1,503.9 1,489.2 1,490.8 1,488.9 1,478.9 1,466.4 1,456.1 1,450.4 1,440.7 AddenFinal Gross dum: sales of domestic Gross domespurnational tic 1 prodproduct chases uct 2 3,199.9 3,390.8 3,587.6 3,803.4 3,920.0 4,115.8 4,245.0 4,284.3 4,403.6 4,636.7 4,884.0 4,870.0 4,922.1 5,115.9 5,340.3 5,634.9 5,836.2 5,873.6 5,954.4 5,918.2 6,167.6 6,490.0 6,833.1 7,092.7 7,289.9 7,601.3 7,860.8 8,025.8 8,027.9 8,277.2 8,508.0 8,801.7 9,065.4 9,404.4 9,774.2 10,208.3 10,706.5 11,158.0 11,382.0 11,533.6 11,820.5 12,181.3 12,573.0 12,899.3 13,177.5 13,200.5 12,852.7 13,028.9 13,281.8 13,277.8 13,325.9 13,225.6 12,972.9 12,836.0 12,830.0 12,875.1 12,869.5 12,895.9 12,992.2 13,046.0 13,181.6 13,182.8 13,236.2 13,340.9 13,367.4 3,246.0 3,423.4 3,656.1 3,907.0 4,014.8 4,222.1 4,355.0 4,348.3 4,503.1 4,751.8 4,987.0 4,922.1 4,867.9 5,184.8 5,459.8 5,758.4 5,898.3 5,784.8 5,939.7 5,860.4 6,203.1 6,739.7 7,039.4 7,297.2 7,512.1 7,752.2 7,984.2 8,097.8 8,027.8 8,302.7 8,585.7 8,968.5 9,181.3 9,534.0 9,984.4 10,531.1 11,131.8 11,671.6 11,815.8 12,097.5 12,444.7 12,935.5 13,345.7 13,688.1 13,855.3 13,653.1 13,051.6 13,500.4 13,717.2 13,818.0 13,794.5 13,646.5 13,353.3 13,057.0 12,964.0 13,035.7 13,149.6 13,304.1 13,486.8 13,589.6 13,621.2 13,644.2 13,679.9 13,725.3 13,819.5 3,230.1 3,417.5 3,636.4 3,869.8 3,967.7 4,160.6 4,288.0 4,295.8 4,442.2 4,678.9 4,960.3 4,939.8 4,917.2 5,186.8 5,429.1 5,728.4 5,925.2 5,908.3 6,047.3 5,934.0 6,197.1 6,634.1 6,888.0 7,110.4 7,335.9 7,643.9 7,917.3 8,075.0 8,048.8 8,319.4 8,556.0 8,893.0 9,121.7 9,463.1 9,873.4 10,295.3 10,802.9 11,259.2 11,395.0 11,597.1 11,909.9 12,341.6 12,720.1 13,028.3 13,322.0 13,316.9 12,843.2 13,261.0 ������������� 13,431.7 13,476.6 13,367.4 12,991.9 12,785.6 12,770.7 12,844.9 12,971.6 13,092.9 13,238.4 13,328.9 13,383.9 13,432.2 13,504.2 13,567.9 ������������� Percent change from preceding period Gross Gross domes- domestic tic purproduct chases 1 4.4 5.8 6.4 6.5 2.5 4.8 3.1 .2 3.4 5.3 5.8 –.6 –.2 5.4 4.6 5.6 3.1 –.3 2.5 –1.9 4.5 7.2 4.1 3.5 3.2 4.1 3.6 1.9 –.2 3.4 2.9 4.1 2.5 3.7 4.5 4.4 4.8 4.1 1.1 1.8 2.5 3.5 3.1 2.7 1.9 –.3 –3.5 3.0 1.7 –1.8 1.3 –3.7 –8.9 –6.7 –.7 1.7 3.8 3.9 3.8 2.5 2.3 .4 1.3 1.8 2.8 4.2 5.5 6.8 6.9 2.8 5.2 3.1 –.2 3.6 5.5 5.0 –1.3 –1.1 6.5 5.3 5.5 2.4 –1.9 2.7 –1.3 5.8 8.7 4.4 3.7 2.9 3.2 3.0 1.4 –.9 3.4 3.4 4.5 2.4 3.8 4.7 5.5 5.7 4.8 1.2 2.4 2.9 3.9 3.2 2.6 1.2 –1.5 –4.4 3.4 1.6 –2.1 –.7 –4.2 –8.3 –8.6 –2.8 2.2 3.5 4.8 5.6 3.1 .9 .7 1.0 1.3 2.8 1 Gross domestic product (GDP) less exports of goods and services plus imports of goods and services. 2 GDP plus net income receipts from rest of the world. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 319 Table B–3. Quantity and price indexes for gross domestic product, and percent changes, 1963–2011 [Quarterly data are seasonally adjusted] Percent change from preceding period 1 Index numbers, 2005=100 Gross domestic product (GDP) Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Real GDP GDP (chain-type chain-type quantity price index index) 25.382 26.851 28.575 30.437 31.206 32.717 33.733 33.798 34.932 36.788 38.920 38.705 38.623 40.695 42.566 44.940 46.345 46.217 47.390 46.470 48.570 52.060 54.214 56.092 57.887 60.266 62.420 63.591 63.442 65.595 67.466 70.214 71.980 74.672 78.000 81.397 85.326 88.857 89.816 91.445 93.769 97.021 100.000 102.658 104.622 104.270 100.635 103.684 105.470 105.101 105.447 104.468 102.064 100.319 100.145 100.567 101.509 102.494 103.450 104.093 104.699 104.792 105.140 105.614 106.334 19.290 19.589 19.945 20.511 21.142 22.040 23.130 24.349 25.567 26.670 28.148 30.695 33.606 35.535 37.796 40.447 43.811 47.817 52.326 55.514 57.705 59.874 61.686 63.057 64.818 67.047 69.579 72.274 74.826 76.602 78.288 79.935 81.602 83.154 84.627 85.580 86.840 88.724 90.731 92.192 94.134 96.784 100.000 103.237 106.231 108.565 109.732 111.000 113.307 107.623 108.282 109.107 109.247 109.709 109.589 109.662 109.969 110.370 110.770 111.162 111.699 112.390 113.091 113.811 113.935 GDP implicit price deflator 19.281 19.580 19.936 20.502 21.133 22.031 23.119 24.338 25.554 26.657 28.136 30.690 33.591 35.519 37.783 40.435 43.798 47.791 52.270 55.459 57.652 59.817 61.628 62.991 64.819 67.046 69.577 72.262 74.824 76.598 78.290 79.940 81.606 83.159 84.628 85.584 86.842 88.723 90.727 92.196 94.135 96.786 100.000 103.231 106.227 108.582 109.729 110.992 113.327 107.591 108.302 109.162 109.300 109.717 109.594 109.658 109.943 110.358 110.793 111.156 111.644 112.398 113.118 113.836 113.946 Personal consumption expenditures (PCE) PCE Real GDP GDP PCE food (chain-type chain-type chain-type lessenergy quantity price index price index and price index index) 19.254 19.536 19.819 20.322 20.834 21.645 22.626 23.685 24.692 25.536 26.913 29.716 32.198 33.966 36.171 38.705 42.137 46.663 50.833 53.640 55.948 58.065 59.965 61.427 63.618 66.151 69.025 72.180 74.789 76.989 78.679 80.302 82.078 83.864 85.433 86.246 87.636 89.818 91.530 92.778 94.658 97.121 100.000 102.723 105.499 108.943 109.169 111.112 113.815 107.852 109.052 110.218 108.650 108.194 108.703 109.513 110.265 110.774 110.864 111.136 111.673 112.747 113.666 114.324 114.524 1 Quarterly percent changes are at annual rates. Source: Department of Commerce (Bureau of Economic Analysis). 320 | Appendix B 19.788 20.091 20.345 20.805 21.442 22.362 23.412 24.510 25.664 26.493 27.505 29.687 32.174 34.130 36.320 38.749 41.569 45.377 49.342 52.526 55.247 57.541 59.724 61.974 64.331 67.120 69.889 72.872 75.709 78.256 80.106 81.875 83.761 85.386 87.022 88.284 89.597 91.154 92.783 94.390 95.823 97.815 100.000 102.265 104.631 107.020 108.691 110.208 111.790 106.208 106.844 107.384 107.644 107.913 108.475 108.888 109.488 109.796 110.147 110.353 110.534 110.963 111.585 112.156 112.454 Personal consumption expenditures (PCE) Gross domestic product (GDP) 4.4 5.8 6.4 6.5 2.5 4.8 3.1 .2 3.4 5.3 5.8 –.6 –.2 5.4 4.6 5.6 3.1 –.3 2.5 –1.9 4.5 7.2 4.1 3.5 3.2 4.1 3.6 1.9 –.2 3.4 2.9 4.1 2.5 3.7 4.5 4.4 4.8 4.1 1.1 1.8 2.5 3.5 3.1 2.7 1.9 –.3 –3.5 3.0 1.7 –1.8 1.3 –3.7 –8.9 –6.7 –.7 1.7 3.8 3.9 3.8 2.5 2.3 .4 1.3 1.8 2.8 1.1 1.6 1.8 2.8 3.1 4.2 4.9 5.3 5.0 4.3 5.5 9.0 9.5 5.7 6.4 7.0 8.3 9.1 9.4 6.1 3.9 3.8 3.0 2.2 2.8 3.4 3.8 3.9 3.5 2.4 2.2 2.1 2.1 1.9 1.8 1.1 1.5 2.2 2.3 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 2.5 2.5 3.1 .5 1.7 –.4 .3 1.1 1.5 1.5 1.4 1.9 2.5 2.5 2.6 .4 GDP implicit price deflator 1.1 1.6 1.8 2.8 3.1 4.2 4.9 5.3 5.0 4.3 5.5 9.1 9.5 5.7 6.4 7.0 8.3 9.1 9.4 6.1 4.0 3.8 3.0 2.2 2.9 3.4 3.8 3.9 3.5 2.4 2.2 2.1 2.1 1.9 1.8 1.1 1.5 2.2 2.3 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 2.4 2.7 3.2 .5 1.5 –.4 .2 1.0 1.5 1.6 1.3 1.8 2.7 2.6 2.6 .4 PCE chain-type price index 1.2 1.5 1.4 2.5 2.5 3.9 4.5 4.7 4.3 3.4 5.4 10.4 8.4 5.5 6.5 7.0 8.9 10.7 8.9 5.5 4.3 3.8 3.3 2.4 3.6 4.0 4.3 4.6 3.6 2.9 2.2 2.1 2.2 2.2 1.9 1.0 1.6 2.5 1.9 1.4 2.0 2.6 3.0 2.7 2.7 3.3 .2 1.8 2.4 3.9 4.5 4.3 –5.6 –1.7 1.9 3.0 2.8 1.9 .3 1.0 1.9 3.9 3.3 2.3 .7 PCE less food and energy price index 1.3 1.5 1.3 2.3 3.1 4.3 4.7 4.7 4.7 3.2 3.8 7.9 8.4 6.1 6.4 6.7 7.3 9.2 8.7 6.5 5.2 4.2 3.8 3.8 3.8 4.3 4.1 4.3 3.9 3.4 2.4 2.2 2.3 1.9 1.9 1.5 1.5 1.7 1.8 1.7 1.5 2.1 2.2 2.3 2.3 2.3 1.6 1.4 1.4 2.5 2.4 2.0 1.0 1.0 2.1 1.5 2.2 1.1 1.3 .8 .7 1.6 2.3 2.1 1.1 Table B–4. Percent changes in real gross domestic product, 1963–2011 [Percent change from preceding period; quarterly data at seasonally adjusted annual rates] Personal consumption expenditures Year or quarter 1963 ��������������������� 1964 ��������������������� 1965 ��������������������� 1966 ��������������������� 1967 ��������������������� 1968 ��������������������� 1969 ��������������������� 1970 ��������������������� 1971 ��������������������� 1972 ��������������������� 1973 ��������������������� 1974 ��������������������� 1975 ��������������������� 1976 ��������������������� 1977 ��������������������� 1978 ��������������������� 1979 ��������������������� 1980 ��������������������� 1981 ��������������������� 1982 ��������������������� 1983 ��������������������� 1984 ��������������������� 1985 ��������������������� 1986 ��������������������� 1987 ��������������������� 1988 ��������������������� 1989 ��������������������� 1990 ��������������������� 1991 ��������������������� 1992 ��������������������� 1993 ��������������������� 1994 ��������������������� 1995 ��������������������� 1996 ��������������������� 1997 ��������������������� 1998 ��������������������� 1999 ��������������������� 2000 ��������������������� 2001 ��������������������� 2002 ��������������������� 2003 ��������������������� 2004 ��������������������� 2005 ��������������������� 2006 ��������������������� 2007 ��������������������� 2008 ��������������������� 2009 ��������������������� 2010 ��������������������� 2011 p ������������������� 2008: I ����������������� II ���������������� III ��������������� IV ��������������� 2009: I ����������������� II ���������������� III ��������������� IV ��������������� 2010: I ����������������� II ���������������� III ��������������� IV ��������������� 2011: I ����������������� II ���������������� III ��������������� IV p ������������ Gross domestic product 4.4 5.8 6.4 6.5 2.5 4.8 3.1 .2 3.4 5.3 5.8 –.6 –.2 5.4 4.6 5.6 3.1 –.3 2.5 –1.9 4.5 7.2 4.1 3.5 3.2 4.1 3.6 1.9 –.2 3.4 2.9 4.1 2.5 3.7 4.5 4.4 4.8 4.1 1.1 1.8 2.5 3.5 3.1 2.7 1.9 –.3 –3.5 3.0 1.7 –1.8 1.3 –3.7 –8.9 –6.7 –.7 1.7 3.8 3.9 3.8 2.5 2.3 .4 1.3 1.8 2.8 Gross private domestic investment Exports and imports of goods and services Government consumption expenditures and gross investment Exports Imports Total 7.2 11.8 2.8 6.9 2.3 7.9 4.8 10.7 1.7 7.5 18.9 7.9 –.6 4.4 2.4 10.5 9.9 10.8 1.2 –7.6 –2.6 8.2 3.0 7.7 10.8 16.0 11.5 9.0 6.6 6.9 3.3 8.7 10.1 8.3 11.9 2.3 4.4 8.6 –5.6 –2.0 1.6 9.5 6.7 9.0 9.3 6.1 –9.4 11.3 6.8 5.5 12.7 –3.5 –21.4 –29.0 –.5 13.9 23.5 7.2 10.0 10.0 7.8 7.9 3.6 4.7 4.7 2.7 5.3 10.6 14.9 7.3 14.9 5.7 4.3 5.3 11.3 4.6 –2.3 –11.1 19.6 10.9 8.7 1.7 –6.6 2.6 –1.3 12.6 24.3 6.5 8.5 5.9 3.9 4.4 3.6 –.2 7.0 8.6 11.9 8.0 8.7 13.5 11.7 11.5 13.0 –2.8 3.4 4.4 11.1 6.1 6.1 2.4 –2.7 –13.6 12.5 5.0 1.4 –2.5 –6.6 –14.9 –34.0 –15.0 16.3 17.4 12.5 21.6 12.3 –2.3 8.3 1.4 1.2 4.4 Nonresidential fixed Total 4.1 6.0 6.3 5.7 3.0 5.8 3.7 2.3 3.8 6.1 5.0 –.8 2.3 5.6 4.2 4.4 2.4 –.4 1.5 1.4 5.7 5.3 5.2 4.1 3.1 4.0 2.8 2.0 .2 3.4 3.6 3.8 2.7 3.5 3.7 5.2 5.5 5.1 2.7 2.7 2.8 3.3 3.4 2.9 2.3 –.6 –1.9 2.0 2.2 –1.0 –.1 –3.8 –5.1 –1.5 –1.9 2.3 .4 2.7 2.9 2.6 3.6 2.1 .7 1.7 2.0 Goods 4.0 6.0 7.1 6.3 2.0 6.2 3.1 .8 4.2 6.5 5.2 –3.6 .7 7.0 4.3 4.1 1.6 –2.5 1.2 .7 6.4 7.2 5.3 5.6 1.8 3.7 2.5 .6 –2.0 3.2 4.2 5.3 3.0 4.5 4.8 6.8 8.0 5.3 3.1 4.1 4.6 4.5 4.2 3.3 3.0 –2.5 –3.0 4.3 3.8 –5.6 .5 –7.7 –12.6 .1 –2.3 7.6 .5 6.4 3.8 4.8 8.3 4.7 –1.6 1.4 5.7 Services 4.2 6.0 5.5 5.0 4.1 5.3 4.5 3.9 3.5 5.8 4.7 1.9 3.8 4.3 4.1 4.7 3.1 1.5 1.8 1.9 5.2 3.9 5.2 3.0 4.0 4.2 3.0 3.0 1.5 3.6 3.2 3.0 2.5 2.9 3.1 4.4 4.1 5.0 2.5 1.9 1.9 2.7 3.0 2.6 1.9 .4 –1.4 .9 1.4 1.5 –.5 –1.7 –1.2 –2.3 –1.7 –.1 .4 1.0 2.5 1.6 1.3 .8 1.9 1.9 .2 Total 5.6 11.9 17.4 12.5 –1.3 4.5 7.6 –.5 .0 9.2 14.5 .8 –9.9 4.9 11.3 15.0 10.1 –.3 5.7 –3.8 –1.3 17.6 6.6 –2.9 –.1 5.2 5.6 .5 –5.4 3.2 8.7 9.2 10.5 9.3 12.1 12.0 10.4 9.8 –2.8 –7.9 1.4 6.2 6.7 8.0 6.5 –.8 –17.8 4.4 8.6 –.8 –2.3 –9.9 –22.9 –31.3 –15.8 –3.3 –3.7 6.0 18.6 11.3 8.7 2.1 10.3 15.7 1.7 Structures 1.2 10.4 15.9 6.8 –2.5 1.4 5.4 .3 –1.6 3.1 8.2 –2.2 –10.5 2.4 4.1 14.4 12.7 5.9 8.0 –1.6 –10.8 13.9 7.1 –11.0 –2.9 .7 2.0 1.5 –11.1 –6.0 –.6 1.8 6.4 5.7 7.3 5.1 .1 7.8 –1.5 –17.7 –3.8 1.1 1.4 9.2 14.1 6.4 –21.2 –15.8 4.1 .8 9.4 –3.7 –10.2 –32.1 –33.3 –20.1 –30.8 –24.7 7.5 4.2 10.5 –14.3 22.6 14.4 –7.2 Residential fixed Equipment and software 8.4 12.8 18.3 16.0 –.7 6.2 8.8 –1.0 1.0 12.9 18.3 2.6 –9.5 6.3 15.1 15.2 8.7 –3.6 4.3 –5.2 5.4 19.8 6.4 1.9 1.4 7.5 7.3 .0 –2.6 7.3 12.5 11.9 12.0 10.6 13.8 14.5 14.1 10.5 –3.2 –4.2 3.1 7.9 8.5 7.6 3.3 –4.3 –16.0 14.6 10.3 –1.7 –7.9 –13.1 –29.3 –30.8 –4.2 6.4 11.7 21.7 23.2 14.1 8.1 8.7 6.2 16.2 5.2 11.8 5.8 –2.9 –8.9 –3.1 13.6 3.0 –6.0 27.4 17.8 –.6 –20.6 –13.0 23.5 21.5 6.3 –3.7 –21.2 –8.0 –18.2 41.4 14.8 1.6 12.3 2.0 –1.0 –3.0 –8.6 –9.6 13.8 8.2 9.7 –3.3 8.0 1.9 7.7 6.3 1.0 .6 5.2 8.2 9.8 6.2 –7.3 –18.7 –23.9 –22.2 –4.3 –1.4 –28.5 –14.5 –20.0 –33.2 –35.4 –21.3 17.8 –3.8 –15.3 22.8 –27.7 2.5 –2.4 4.2 1.3 10.9 2.6 2.2 3.0 8.8 7.7 3.1 –.2 –2.4 –2.2 –.7 –.4 2.5 2.3 .4 1.1 2.9 1.9 1.9 .9 1.8 3.7 3.4 7.0 6.1 2.4 1.3 2.7 3.2 1.1 .5 –.8 .0 .6 1.0 1.9 2.1 3.6 2.0 3.8 4.7 2.2 1.4 .3 1.4 1.3 2.6 1.7 .7 –2.1 3.1 1.7 4.3 1.6 –1.7 5.9 1.3 –.9 –1.2 3.7 1.0 –2.8 –5.9 –.9 –.1 –4.6 Federal 0.1 –1.3 .0 11.1 10.0 .8 –3.4 –7.4 –7.7 –4.1 –4.2 .9 .3 .0 2.1 2.5 2.4 4.7 4.8 3.9 6.6 3.1 7.8 5.7 3.6 –1.6 1.6 2.0 –.2 –1.8 –3.9 –3.8 –2.7 –1.2 –1.0 –1.1 1.9 .5 4.1 7.3 6.6 4.1 1.3 2.1 1.2 7.2 6.0 4.5 –2.0 9.7 4.9 11.7 9.1 –3.3 14.4 5.9 2.2 2.8 8.8 3.2 –3.0 –9.4 1.9 2.1 –7.3 State and local 6.0 6.8 6.7 6.3 5.1 5.9 3.4 2.8 3.1 2.2 2.9 3.8 3.7 .7 .4 3.3 1.5 –.1 –2.0 .0 1.2 3.6 6.2 6.4 1.4 3.7 3.7 4.1 2.1 2.2 1.5 2.6 2.7 2.3 3.6 3.9 4.5 2.8 3.7 3.3 –.1 –.2 –.2 .9 1.4 .0 –.9 –1.8 –2.3 –.6 –.1 .1 –2.8 –.8 .9 –1.5 –2.9 –3.9 .4 –.5 –2.7 –3.4 –2.8 –1.6 –2.6 Note: Percent changes based on unrounded data. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 321 Table B–5. Contributions to percent change in real gross domestic product, 1963–2011 [Percentage points, except as noted; quarterly data at seasonally adjusted annual rates] Personal consumption expenditures Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product (percent change) 4.4 5.8 6.4 6.5 2.5 4.8 3.1 .2 3.4 5.3 5.8 –.6 –.2 5.4 4.6 5.6 3.1 –.3 2.5 –1.9 4.5 7.2 4.1 3.5 3.2 4.1 3.6 1.9 –.2 3.4 2.9 4.1 2.5 3.7 4.5 4.4 4.8 4.1 1.1 1.8 2.5 3.5 3.1 2.7 1.9 –.3 –3.5 3.0 1.7 –1.8 1.3 –3.7 –8.9 –6.7 –.7 1.7 3.8 3.9 3.8 2.5 2.3 .4 1.3 1.8 2.8 Fixed investment Total 2.56 3.69 3.91 3.50 1.82 3.51 2.29 1.44 2.37 3.81 3.08 –.52 1.40 3.51 2.66 2.77 1.48 –.22 .95 .86 3.65 3.43 3.32 2.62 2.01 2.64 1.86 1.34 .10 2.27 2.37 2.57 1.81 2.35 2.48 3.50 3.68 3.44 1.85 1.85 1.97 2.30 2.35 1.98 1.60 –.39 –1.32 1.44 1.53 –.70 –.08 –2.67 –3.53 –1.02 –1.28 1.66 .33 1.92 2.05 1.85 2.48 1.47 .49 1.24 1.45 See next page for continuation of table. 322 | Appendix B Gross private domestic investment Goods 1.29 1.91 2.26 2.02 .62 1.92 .95 .24 1.27 1.97 1.57 –1.12 .20 2.08 1.28 1.22 .47 –.74 .34 .19 1.74 1.97 1.41 1.49 .48 .98 .66 .16 –.51 .78 1.02 1.29 .73 1.09 1.16 1.61 1.90 1.29 .77 .99 1.12 1.09 1.01 .80 .71 –.59 –.69 .99 .87 –1.37 .12 –1.89 –3.04 .05 –.52 1.70 .12 1.45 .87 1.09 1.87 1.10 –.38 .33 1.34 Services 1.27 1.78 1.66 1.48 1.21 1.59 1.34 1.19 1.10 1.84 1.51 .60 1.20 1.43 1.38 1.56 1.02 .52 .62 .67 1.91 1.47 1.90 1.13 1.53 1.66 1.20 1.18 .61 1.49 1.35 1.27 1.08 1.26 1.33 1.90 1.78 2.15 1.09 .86 .85 1.22 1.34 1.18 .89 .21 –.63 .46 .66 .67 –.20 –.78 –.49 –1.07 –.76 –.04 .21 .47 1.18 .75 .61 .36 .87 .90 .10 Total 1.00 1.25 2.16 1.44 –.76 .90 .90 –1.04 1.67 1.87 1.96 –1.31 –2.98 2.84 2.43 2.16 .61 –2.12 1.55 –2.55 1.45 4.63 –.17 –.12 .51 .39 .64 –.53 –1.20 1.07 1.21 1.94 .48 1.35 1.95 1.65 1.50 1.19 –1.24 –.22 .60 1.57 .93 .47 –.56 –1.66 –3.61 1.96 .58 –2.02 –.94 –2.63 –5.59 –7.76 –2.84 .35 3.51 3.25 2.92 1.14 –.91 .47 .79 .17 2.35 Nonresidential Total 1.08 1.37 1.50 .87 –.28 .99 .90 –.31 1.10 1.81 1.47 –1.04 –1.71 1.42 2.18 2.04 1.02 –1.21 .39 –1.21 1.17 2.68 .89 .20 .09 .53 .47 –.32 –.94 .79 1.14 1.30 .94 1.33 1.41 1.70 1.52 1.24 –.32 –.70 .54 1.15 1.05 .40 –.33 –1.15 –2.77 .32 .79 –1.36 –.80 –1.91 –4.05 –5.09 –2.26 .13 –.42 .15 2.12 .28 .88 .15 1.07 1.52 .41 Total 0.50 1.07 1.65 1.29 –.15 .46 .78 –.06 .00 .93 1.50 .09 –1.14 .52 1.19 1.69 1.23 –.03 .74 –.50 –.17 2.05 .82 –.36 –.01 .58 .61 .05 –.57 .31 .83 .91 1.08 1.01 1.33 1.38 1.24 1.20 –.35 –.94 .14 .63 .69 .86 .73 –.09 –2.05 .42 .82 –.10 –.25 –1.18 –2.84 –3.90 –1.66 –.29 –.33 .56 1.62 1.04 .82 .20 .98 1.49 .18 EquipStructures ment and software 0.04 .36 .57 .27 –.10 .05 .20 .01 –.06 .12 .31 –.09 –.43 .09 .15 .54 .53 .27 .40 –.09 –.57 .60 .32 –.50 –.11 .02 .07 .05 –.39 –.18 –.02 .05 .17 .16 .21 .16 .00 .24 –.05 –.58 –.10 .03 .04 .27 .46 .24 –.85 –.51 .11 .03 .37 –.14 –.41 –1.47 –1.41 –.71 –1.07 –.76 .18 .10 .26 –.40 .54 .37 –.21 0.46 .71 1.07 1.02 –.05 .41 .58 –.07 .07 .81 1.19 .18 –.70 .43 1.04 1.15 .71 –.30 .34 –.42 .41 1.45 .50 .15 .10 .55 .54 .00 –.18 .50 .85 .86 .91 .85 1.12 1.22 1.24 .96 –.30 –.36 .24 .60 .65 .59 .26 –.34 –1.20 .93 .71 –.13 –.63 –1.04 –2.43 –2.43 –.25 .42 .74 1.32 1.45 .94 .56 .60 .44 1.12 .39 Residential 0.58 .30 –.15 –.43 –.13 .53 .13 –.26 1.10 .89 –.04 –1.13 –.57 .90 .99 .35 –.21 –1.17 –.35 –.71 1.33 .64 .07 .55 .10 –.05 –.14 –.37 –.37 .47 .31 .39 –.14 .33 .08 .32 .28 .05 .03 .24 .40 .52 .36 –.46 –1.05 –1.05 –.72 –.11 –.03 –1.26 –.55 –.73 –1.21 –1.19 –.60 .42 –.10 –.41 .50 –.76 .06 –.06 .09 .03 .23 Change in private inventories –0.08 –.13 .66 .58 –.49 –.10 .00 –.73 .58 .06 .50 –.27 –1.27 1.41 .25 .12 –.41 –.91 1.16 –1.34 .29 1.95 –1.06 –.32 .42 –.14 .17 –.21 –.26 .29 .07 .63 –.46 .02 .54 –.05 –.02 –.05 –.92 .48 .06 .42 –.13 .07 –.23 –.51 –.84 1.64 –.20 –.66 –.14 –.73 –1.54 –2.66 –.58 .21 3.93 3.10 .79 .86 –1.79 .32 –.28 –1.35 1.94 Table B–5. Contributions to percent change in real gross domestic product, 1963–2011—Continued [Percentage points, except as noted; quarterly data at seasonally adjusted annual rates] Government consumption expenditures and gross investment Net exports of goods and services Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Net exports 0.24 .36 –.30 –.29 –.22 –.30 –.04 .34 –.19 –.21 .82 .75 .89 –1.08 –.72 .05 .66 1.68 –.15 –.60 –1.35 –1.58 –.42 –.30 .16 .82 .52 .43 .64 –.05 –.57 –.43 .11 –.15 –.32 –1.18 –.99 –.85 –.20 –.65 –.45 –.66 –.27 –.06 .62 1.21 1.11 –.51 .05 .38 2.00 .79 –.12 2.44 2.21 –.59 .15 –.97 –1.94 –.68 1.37 –.34 .24 .43 –.11 Exports Total 0.35 .59 .15 .36 .12 .41 .25 .56 .10 .42 1.12 .58 –.05 .37 .20 .82 .82 .97 .12 –.73 –.22 .63 .23 .54 .77 1.24 .99 .81 .63 .68 .32 .85 1.03 .90 1.30 .26 .47 .91 –.61 –.20 .15 .90 .67 .93 1.03 .73 –1.18 1.31 .88 .65 1.56 –.47 –2.97 –3.82 –.02 1.49 2.51 .86 1.19 1.21 .98 1.01 .48 .64 .64 Goods 0.29 .52 .02 .27 .02 .30 .20 .44 –.02 .43 1.01 .46 –.16 .31 .08 .68 .77 .86 –.09 –.67 –.19 .46 .20 .26 .56 1.04 .75 .56 .46 .52 .23 .67 .85 .68 1.11 .18 .29 .82 –.48 –.25 .12 .56 .52 .68 .75 .53 –1.04 1.12 .68 .75 1.21 –.22 –2.75 –3.25 –.20 1.48 2.01 .96 .97 .75 .79 .94 .24 .48 .48 Imports Services 0.06 .07 .13 .09 .10 .10 .05 .12 .11 –.01 .11 .12 .10 .05 .11 .15 .06 .11 .21 –.06 –.03 .17 .02 .28 .21 .20 .24 .26 .16 .16 .10 .19 .19 .22 .19 .08 .18 .08 –.13 .05 .03 .34 .15 .25 .28 .20 –.13 .19 .20 –.10 .35 –.24 –.21 –.57 .18 .01 .49 –.10 .23 .46 .18 .07 .24 .16 .16 Total –0.12 –.23 –.45 –.65 –.34 –.71 –.29 –.22 –.29 –.63 –.29 .18 .94 –1.45 –.92 –.78 –.16 .71 –.27 .12 –1.13 –2.21 –.65 –.84 –.61 –.43 –.48 –.38 .02 –.72 –.90 –1.28 –.92 –1.04 –1.62 –1.43 –1.45 –1.76 .41 –.46 –.60 –1.55 –.95 –.98 –.40 .47 2.29 –1.82 –.82 –.28 .44 1.25 2.84 6.26 2.24 –2.08 –2.36 –1.83 –3.13 –1.89 .39 –1.35 –.24 –.21 –.75 Goods –0.12 –.19 –.41 –.49 –.17 –.68 –.20 –.15 –.33 –.57 –.34 .17 .87 –1.35 –.84 –.67 –.14 .67 –.18 .20 –1.01 –1.83 –.52 –.82 –.39 –.36 –.38 –.26 –.04 –.78 –.85 –1.18 –.86 –.94 –1.44 –1.21 –1.31 –1.52 .39 –.42 –.56 –1.29 –.87 –.81 –.37 .57 2.19 –1.74 –.79 .05 .31 1.47 2.98 5.63 2.15 –1.98 –2.36 –1.71 –3.05 –1.58 .08 –1.29 –.23 –.08 –.60 Federal Services 0.00 –.04 –.04 –.16 –.16 –.03 –.09 –.07 .04 –.06 .05 .00 .07 –.10 –.07 –.11 –.02 .04 –.09 –.08 –.13 –.39 –.13 –.02 –.22 –.07 –.09 –.13 .05 .06 –.05 –.10 –.06 –.10 –.17 –.22 –.14 –.24 .02 –.04 –.04 –.26 –.07 –.18 –.04 –.10 .10 –.08 –.03 –.33 .13 –.21 –.14 .63 .09 –.10 .00 –.12 –.08 –.31 .31 –.06 –.01 –.13 –.15 Total 0.58 .49 .65 1.87 1.68 .73 –.05 –.55 –.50 –.16 –.08 .52 .48 .10 .23 .60 .37 .38 .19 .35 .76 .70 1.41 1.27 .51 .26 .55 .64 .22 .10 –.16 .00 .11 .19 .34 .38 .63 .36 .67 .84 .42 .26 .06 .26 .25 .50 .34 .14 –.45 .58 .34 .85 .35 –.33 1.21 .28 –.18 –.26 .77 .20 –.58 –1.23 –.18 –.02 –.93 Total 0.01 –.17 –.01 1.24 1.17 .10 –.42 –.86 –.85 –.42 –.41 .08 .03 .00 .19 .22 .20 .39 .42 .35 .63 .30 .74 .55 .35 –.16 .14 .18 –.02 –.16 –.33 –.30 –.20 –.08 –.07 –.07 .12 .03 .24 .44 .43 .28 .09 .15 .09 .50 .45 .37 –.17 .66 .35 .84 .69 –.25 1.09 .48 .18 .23 .71 .26 –.26 –.82 .16 .17 –.62 National defense Nondefense –0.25 –.39 –.19 1.21 1.19 .16 –.49 –.83 –.97 –.60 –.39 –.05 –.06 –.02 .07 .05 .17 .25 .38 .48 .50 .35 .60 .47 .35 –.03 –.03 .00 –.07 –.32 –.31 –.27 –.19 –.06 –.13 –.09 .07 –.02 .14 .28 .36 .26 .07 .07 .11 .36 .30 .18 –.13 .38 .27 .85 .44 –.40 .84 .45 –.07 .03 .33 .31 –.34 –.74 .37 .27 –.73 0.26 .23 .19 .03 –.02 –.06 .06 –.03 .12 .18 –.02 .13 .09 .03 .12 .16 .03 .14 .04 –.13 .13 –.05 .14 .08 .00 –.12 .17 .18 .05 .16 –.02 –.04 –.01 –.02 .06 .02 .04 .05 .09 .15 .07 .02 .02 .07 –.02 .15 .16 .19 –.03 .28 .09 –.01 .25 .15 .25 .03 .25 .21 .38 –.05 .09 –.08 –.22 –.10 .11 State and local 0.57 .65 .66 .63 .51 .63 .37 .31 .36 .26 .33 .44 .45 .09 .04 .38 .17 –.01 –.23 .01 .13 .40 .67 .71 .17 .42 .41 .46 .24 .26 .17 .30 .30 .27 .41 .45 .51 .33 .43 .40 –.01 –.02 –.03 .11 .17 .00 –.11 –.23 –.28 –.08 –.01 .01 –.34 –.08 .12 –.19 –.37 –.49 .05 –.06 –.33 –.41 –.34 –.19 –.32 Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 323 Table B–6. Chain-type quantity indexes for gross domestic product, 1963–2011 [Index numbers, 2005=100; quarterly data seasonally adjusted] Personal consumption expenditures Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product 25.382 26.851 28.575 30.437 31.206 32.717 33.733 33.798 34.932 36.788 38.920 38.705 38.623 40.695 42.566 44.940 46.345 46.217 47.390 46.470 48.570 52.060 54.214 56.092 57.887 60.266 62.420 63.591 63.442 65.595 67.466 70.214 71.980 74.672 78.000 81.397 85.326 88.857 89.816 91.445 93.769 97.021 100.000 102.658 104.622 104.270 100.635 103.684 105.470 105.101 105.447 104.468 102.064 100.319 100.145 100.567 101.509 102.494 103.450 104.093 104.699 104.792 105.140 105.614 106.334 Fixed investment Total 22.593 23.939 25.453 26.897 27.703 29.301 30.399 31.112 32.297 34.283 35.982 35.683 36.492 38.525 40.146 41.916 42.912 42.761 43.410 44.015 46.531 48.998 51.551 53.642 55.297 57.525 59.152 60.359 60.450 62.511 64.731 67.203 69.021 71.429 74.066 77.950 82.213 86.382 88.718 91.080 93.650 96.731 100.000 102.850 105.218 104.637 102.657 104.741 107.015 105.515 105.478 104.458 103.096 102.696 102.215 102.803 102.915 103.608 104.355 105.038 105.962 106.511 106.693 107.156 107.699 See next page for continuation of table. 324 | Appendix B Gross private domestic investment Goods 21.701 22.994 24.623 26.184 26.697 28.350 29.216 29.447 30.679 32.685 34.378 33.124 33.349 35.684 37.215 38.753 39.373 38.376 38.830 39.101 41.589 44.586 46.931 49.556 50.448 52.322 53.643 53.975 52.904 54.571 56.838 59.836 61.623 64.383 67.453 72.010 77.745 81.847 84.417 87.848 91.890 95.988 100.000 103.322 106.394 103.776 100.693 105.006 108.944 105.599 105.719 103.615 100.171 100.190 99.597 101.430 101.555 103.139 104.100 105.333 107.452 108.700 108.272 108.646 110.157 Services 22.543 23.885 25.204 26.453 27.541 29.009 30.303 31.487 32.574 34.458 36.091 36.783 38.164 39.802 41.447 43.375 44.700 45.389 46.203 47.103 49.568 51.508 54.173 55.784 58.007 60.469 62.301 64.151 65.110 67.431 69.589 71.666 73.488 75.640 77.973 81.409 84.744 88.944 91.134 92.870 94.611 97.134 100.000 102.599 104.599 105.067 103.644 104.628 106.087 105.465 105.344 104.884 104.576 103.958 103.524 103.493 103.599 103.853 104.496 104.912 105.250 105.453 105.941 106.449 106.506 Total 16.249 17.589 20.058 21.825 20.827 22.039 23.323 21.791 24.275 27.150 30.331 28.097 23.120 27.791 31.989 35.846 36.989 32.926 35.886 30.859 33.733 43.672 43.266 42.971 44.295 45.337 47.156 45.569 41.862 45.254 49.299 55.998 57.743 62.851 70.672 77.747 84.592 90.371 84.023 82.879 86.090 94.749 100.000 102.742 99.412 89.296 66.944 78.945 82.642 94.633 93.176 89.061 80.314 68.610 64.317 64.782 70.067 75.037 79.562 81.333 79.848 80.600 81.869 82.135 85.964 Nonresidential Total 16.306 17.882 19.708 20.838 20.453 21.881 23.242 22.754 24.477 27.420 29.926 28.055 25.042 27.511 31.465 35.274 37.265 34.844 35.623 33.125 35.541 41.543 43.729 44.237 44.480 45.947 47.328 46.340 43.335 45.904 49.839 54.500 58.010 63.213 69.045 76.537 83.658 89.843 88.142 84.412 87.390 93.880 100.000 102.375 100.390 93.228 75.688 77.667 82.822 97.363 96.078 92.989 86.480 78.473 74.910 75.041 74.327 74.541 77.935 78.380 79.812 80.052 81.829 84.362 85.046 Total 12.247 13.701 16.088 18.100 17.856 18.654 20.070 19.963 19.964 21.797 24.968 25.177 22.689 23.800 26.486 30.450 33.517 33.429 35.333 34.003 33.563 39.486 42.103 40.901 40.870 43.008 45.409 45.633 43.186 44.565 48.456 52.915 58.478 63.940 71.658 80.264 88.640 97.327 94.614 87.112 88.290 93.740 100.000 108.027 115.039 114.125 93.755 97.913 106.314 117.944 117.269 114.238 107.050 97.447 93.341 92.556 91.678 93.023 97.081 99.725 101.822 102.342 104.889 108.782 109.244 Structures 51.986 57.399 66.553 71.109 69.313 70.299 74.096 74.300 73.082 75.359 81.520 79.755 71.355 73.073 76.079 87.058 98.098 103.837 112.161 110.325 98.404 112.125 120.095 106.935 103.859 104.539 106.616 108.187 96.150 90.354 89.768 91.405 97.235 102.744 110.280 115.911 116.049 125.101 123.191 101.377 97.514 98.571 100.000 109.180 124.578 132.595 104.426 87.883 91.497 131.860 134.869 133.594 130.057 118.078 106.721 100.894 92.013 85.704 87.261 88.169 90.399 86.974 91.511 94.631 92.874 Equipment and software 6.476 7.303 8.641 10.024 9.958 10.578 11.513 11.399 11.512 12.997 15.381 15.774 14.272 15.164 17.449 20.106 21.861 21.075 21.971 20.829 21.950 26.303 27.974 28.504 28.895 31.074 33.351 33.361 32.504 34.873 39.226 43.904 49.158 54.383 61.861 70.837 80.857 89.320 86.438 82.789 85.377 92.138 100.000 107.590 111.168 106.411 89.367 102.393 112.909 112.220 109.945 106.148 97.330 88.760 87.812 89.194 91.700 96.309 101.463 104.873 106.925 109.174 110.839 115.077 116.546 Residential 32.142 34.011 33.017 30.063 29.117 33.086 34.063 32.026 40.808 48.061 47.752 37.895 32.975 40.740 49.486 52.602 50.672 39.949 36.747 30.075 42.524 48.836 49.608 55.696 56.807 56.231 54.524 49.819 45.032 51.263 55.450 60.840 58.850 63.550 64.751 69.732 74.092 74.834 75.258 79.204 85.712 94.130 100.000 92.667 75.379 57.345 44.587 42.681 42.091 62.104 59.721 56.484 51.072 45.790 43.133 44.932 44.495 42.680 44.933 41.427 41.684 41.428 41.855 41.991 43.090 Table B–6. Chain-type quantity indexes for gross domestic product, 1963–2011—Continued [Index numbers, 2005=100; quarterly data seasonally adjusted] Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Exports of goods and services Imports of goods and services Total Goods Total Goods 8.535 9.540 9.807 10.487 10.728 11.572 12.131 13.435 13.663 14.689 17.458 18.837 18.718 19.536 20.006 22.115 24.307 26.925 27.256 25.173 24.524 26.526 27.331 29.429 32.594 37.815 42.161 45.954 49.005 52.370 54.086 58.802 64.755 70.133 78.490 80.281 83.785 90.985 85.880 84.160 85.514 93.677 100.000 108.969 119.108 126.376 114.479 127.444 136.112 125.966 129.793 128.631 121.112 111.191 111.058 114.728 120.941 123.074 126.049 129.101 131.551 134.061 135.240 136.789 138.358 8.074 9.180 9.228 9.870 9.916 10.701 11.262 12.546 12.497 13.840 17.020 18.371 17.944 18.796 19.042 21.170 23.671 26.492 26.205 23.837 23.151 24.982 25.903 27.233 30.252 35.953 40.237 43.623 46.633 50.122 51.756 56.790 63.436 69.031 78.955 80.717 83.788 93.080 87.318 84.176 85.687 92.995 100.000 109.425 120.090 127.691 112.417 128.564 138.256 127.394 131.666 130.878 120.825 108.530 107.723 113.062 120.352 123.835 127.341 130.096 132.984 136.363 137.206 138.874 140.579 6.411 6.752 7.471 8.581 9.206 10.578 11.181 11.658 12.280 13.662 14.296 13.972 12.419 14.848 16.471 17.898 18.195 16.987 17.433 17.214 19.386 24.105 25.669 27.863 29.511 30.671 32.022 33.168 33.118 35.440 38.505 43.098 46.547 50.595 57.409 64.119 71.500 80.813 78.540 81.213 84.806 94.212 100.000 106.099 108.652 105.733 91.372 102.821 107.934 108.203 107.511 105.698 101.518 91.492 87.838 91.215 94.941 97.789 102.695 105.708 105.091 107.207 107.573 107.897 109.058 5.035 5.367 6.127 7.093 7.466 9.009 9.502 9.874 10.702 12.158 13.016 12.654 11.059 13.560 15.213 16.577 16.861 15.610 15.931 15.531 17.641 21.908 23.279 25.665 26.855 27.943 29.146 29.995 30.130 32.971 36.270 41.114 44.817 49.018 56.082 62.727 70.549 80.018 77.464 80.341 84.302 93.637 100.000 105.920 108.674 104.500 88.174 101.248 107.118 107.516 106.907 104.396 99.182 88.340 84.079 87.919 92.357 95.522 101.199 104.206 104.065 106.464 106.875 107.020 108.113 Government consumption expenditures and gross investment Federal Services 9.605 10.180 11.215 11.986 12.932 13.925 14.442 15.729 16.942 16.835 18.025 19.432 20.626 21.236 22.606 24.496 25.250 26.826 29.683 28.860 28.380 30.911 31.279 35.820 39.390 42.939 47.375 52.372 55.505 58.496 60.437 64.275 68.316 73.101 77.436 79.303 83.857 86.102 82.534 84.115 85.107 95.237 100.000 107.935 116.885 123.395 119.041 125.030 131.392 122.720 125.544 123.540 121.774 117.044 118.392 118.433 122.297 121.464 123.262 126.961 128.433 128.977 130.926 132.204 133.463 Services 14.943 15.328 15.779 17.783 19.957 20.315 21.596 22.722 22.075 23.011 22.235 22.210 21.247 22.714 23.846 25.546 25.897 25.319 26.778 28.205 30.483 38.126 41.026 41.488 46.378 47.954 50.278 53.564 52.173 50.768 52.124 54.901 56.556 59.514 64.687 71.721 76.569 84.955 84.292 85.837 87.474 97.252 100.000 107.059 108.539 112.488 108.576 111.742 112.937 111.891 110.696 112.908 114.459 108.490 107.816 108.940 109.060 110.303 111.197 114.282 111.185 111.798 111.918 113.243 114.788 Total 42.032 42.958 44.250 48.149 51.844 53.472 53.347 52.059 50.926 50.556 50.379 51.648 52.812 53.049 53.630 55.210 56.241 57.337 57.860 58.876 61.027 63.078 67.471 71.573 73.300 74.220 76.240 78.655 79.514 79.885 79.253 79.245 79.705 80.507 82.020 83.759 86.761 88.519 91.917 96.192 98.336 99.668 100.000 101.359 102.713 105.381 107.161 107.886 105.577 104.391 104.838 105.941 106.356 105.895 107.431 107.779 107.537 107.205 108.193 108.457 107.691 106.076 105.837 105.812 104.582 Total 60.526 59.725 59.697 66.303 72.903 73.491 70.969 65.738 60.677 58.197 55.748 56.243 56.426 56.453 57.647 59.092 60.519 63.390 66.420 68.989 73.561 75.829 81.771 86.407 89.477 88.010 89.379 91.185 91.000 89.351 85.842 82.555 80.353 79.423 78.641 77.758 79.270 79.661 82.901 88.953 94.839 98.710 100.000 102.127 103.399 110.819 117.479 122.782 120.363 107.703 108.996 112.058 114.518 113.570 117.445 119.128 119.772 120.614 123.177 124.138 123.197 120.195 120.769 121.385 119.101 National defense 72.838 69.951 68.481 78.306 88.567 90.001 85.556 77.800 68.981 63.588 60.061 59.595 59.030 58.828 59.511 60.019 61.845 64.541 68.628 73.814 79.110 82.971 90.002 95.766 100.301 99.826 99.335 99.305 98.214 93.351 88.401 84.072 80.936 79.856 77.618 75.978 77.386 76.986 79.908 85.782 93.243 98.535 100.000 101.588 103.867 111.649 118.090 121.942 119.076 107.756 109.173 113.693 115.975 113.724 118.106 120.457 120.073 120.233 121.992 123.698 121.846 117.822 119.841 121.311 117.332 Nondefense 36.946 40.157 42.878 43.320 42.913 41.897 43.019 42.567 44.575 47.722 47.429 49.891 51.594 52.085 54.324 57.700 58.309 61.573 62.396 59.402 62.471 61.279 64.900 67.130 67.081 63.499 68.795 74.465 76.170 81.218 80.687 79.525 79.207 78.577 80.737 81.374 83.095 85.066 88.945 95.357 98.071 99.067 100.000 103.237 102.420 109.081 116.200 124.508 123.004 107.602 108.640 108.622 111.459 113.237 116.062 116.365 119.137 121.391 125.618 125.038 125.985 125.111 122.665 121.494 122.745 State and local 30.552 32.626 34.813 36.998 38.868 41.168 42.557 43.738 45.077 46.068 47.381 49.164 50.970 51.346 51.532 53.216 53.998 53.958 52.873 52.898 53.514 55.444 58.879 62.669 63.575 65.933 68.340 71.112 72.585 74.156 75.244 77.197 79.247 81.090 83.980 87.291 91.179 93.744 97.236 100.473 100.408 100.234 100.000 100.910 102.311 102.310 101.378 99.557 97.308 102.501 102.473 102.490 101.776 101.583 101.817 101.424 100.689 99.704 99.814 99.689 99.020 98.177 97.488 97.107 96.461 Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 325 Table B–7. Chain-type price indexes for gross domestic product, 1963–2011 [Index numbers, 2005=100, except as noted; quarterly data seasonally adjusted] Personal consumption expenditures Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product 19.290 19.589 19.945 20.511 21.142 22.040 23.130 24.349 25.567 26.670 28.148 30.695 33.606 35.535 37.796 40.447 43.811 47.817 52.326 55.514 57.705 59.874 61.686 63.057 64.818 67.047 69.579 72.274 74.826 76.602 78.288 79.935 81.602 83.154 84.627 85.580 86.840 88.724 90.731 92.192 94.134 96.784 100.000 103.237 106.231 108.565 109.732 111.000 113.307 107.623 108.282 109.107 109.247 109.709 109.589 109.662 109.969 110.370 110.770 111.162 111.699 112.390 113.091 113.811 113.935 Fixed investment Total 19.254 19.536 19.819 20.322 20.834 21.645 22.626 23.685 24.692 25.536 26.913 29.716 32.198 33.966 36.171 38.705 42.137 46.663 50.833 53.640 55.948 58.065 59.965 61.427 63.618 66.151 69.025 72.180 74.789 76.989 78.679 80.302 82.078 83.864 85.433 86.246 87.636 89.818 91.530 92.778 94.658 97.121 100.000 102.723 105.499 108.943 109.169 111.112 113.815 107.852 109.052 110.218 108.650 108.194 108.703 109.513 110.265 110.774 110.864 111.136 111.673 112.747 113.666 114.324 114.524 See next page for continuation of table. 326 | Appendix B Gross private domestic investment Goods 29.689 30.013 30.328 30.996 31.542 32.642 33.907 35.200 36.258 37.186 39.404 44.322 47.903 49.777 52.435 55.653 60.916 67.737 72.769 74.753 76.102 77.541 78.785 78.417 80.939 83.072 86.268 89.801 91.996 93.106 93.915 94.870 95.757 96.809 96.696 95.237 95.735 97.655 97.563 96.563 96.492 97.929 100.000 101.441 102.764 105.912 103.209 104.837 108.750 105.356 106.609 108.437 103.248 101.575 102.597 104.007 104.657 105.196 104.286 104.497 105.367 107.412 108.752 109.530 109.304 Services 14.305 14.572 14.845 15.276 15.785 16.467 17.324 18.285 19.284 20.102 21.077 22.866 24.834 26.556 28.558 30.777 33.350 36.802 40.555 43.709 46.429 48.846 51.049 53.375 55.409 58.123 60.840 63.808 66.581 69.236 71.294 73.200 75.365 77.473 79.812 81.689 83.509 85.818 88.422 90.801 93.686 96.688 100.000 103.414 106.981 110.584 112.353 114.465 116.493 109.211 110.386 111.204 111.536 111.715 111.964 112.463 113.269 113.758 114.380 114.682 115.037 115.574 116.260 116.852 117.286 Total 26.560 26.710 27.136 27.692 28.424 29.485 30.883 32.190 33.794 35.206 37.107 40.797 45.833 48.366 51.994 56.235 61.323 67.080 73.422 77.180 76.987 77.538 78.332 80.029 81.561 83.424 85.418 87.064 88.302 87.993 88.997 90.157 91.173 90.786 90.449 89.435 89.315 90.283 91.080 91.451 92.483 95.633 100.000 104.302 106.313 107.501 106.401 104.743 106.432 106.487 106.815 107.447 109.254 108.646 106.872 105.274 104.811 104.507 104.510 104.755 105.199 105.755 106.342 106.646 106.983 Nonresidential Total 25.485 25.640 26.077 26.626 27.372 28.472 29.877 31.162 32.731 34.135 36.020 39.568 44.525 47.106 50.803 55.094 60.088 65.710 71.816 75.747 75.628 76.070 77.028 78.870 80.332 82.415 84.410 86.125 87.404 87.152 88.163 89.352 90.393 90.149 89.921 89.085 89.029 90.083 90.888 91.261 92.374 95.543 100.000 104.347 106.360 107.587 106.305 104.843 106.161 106.687 107.048 107.912 108.699 108.062 106.595 105.410 105.154 104.818 104.693 104.826 105.035 105.412 106.039 106.433 106.759 Total 33.971 34.142 34.532 35.047 35.939 37.203 38.740 40.571 42.479 43.914 45.605 50.008 56.893 60.048 64.157 68.453 74.013 80.541 88.316 93.181 92.350 92.127 92.850 94.427 95.275 97.392 99.435 101.339 102.906 102.048 102.100 102.592 102.811 101.612 100.326 98.125 96.704 96.750 96.317 95.889 95.471 96.837 100.000 103.425 105.645 107.717 107.106 105.373 106.734 106.261 106.846 108.183 109.578 108.968 107.525 106.238 105.694 105.237 105.293 105.424 105.536 105.909 106.560 107.027 107.442 Structures 11.636 11.801 12.143 12.580 12.973 13.621 14.518 15.473 16.664 17.863 19.247 21.910 24.534 25.741 27.973 30.675 34.238 37.421 42.567 45.927 44.757 45.147 46.219 47.106 47.863 49.895 51.848 53.522 54.491 54.502 56.103 58.089 60.601 62.141 64.516 67.480 69.559 72.298 76.087 79.292 82.174 88.441 100.000 112.922 119.780 125.706 122.490 121.117 126.597 123.025 124.220 126.538 129.041 127.209 123.194 120.003 119.555 119.947 120.647 121.399 122.475 123.982 125.835 127.565 129.008 Equipment and software 53.975 53.952 54.001 54.144 55.344 56.831 58.411 60.560 62.360 63.112 64.184 68.917 79.100 83.754 88.730 93.412 99.335 107.819 115.524 120.030 120.284 119.234 119.090 120.976 121.637 123.155 124.695 126.310 128.112 126.605 125.322 124.604 123.163 120.199 116.639 111.454 108.195 106.893 104.364 102.240 100.450 99.900 100.000 100.049 100.525 101.000 101.496 99.634 99.745 100.070 100.396 101.313 102.222 102.182 101.851 101.295 100.657 99.860 99.677 99.595 99.406 99.446 99.743 99.838 99.953 Residential 12.901 13.003 13.372 13.857 14.339 15.100 16.144 16.666 17.632 18.703 20.359 22.460 24.547 26.124 28.759 32.281 35.902 39.789 43.036 45.340 46.380 47.713 48.944 50.994 53.079 54.913 56.680 58.011 58.771 59.486 61.890 64.069 66.403 67.828 69.557 71.412 74.151 77.415 80.994 83.002 86.953 93.297 100.000 106.081 107.612 106.296 102.637 102.214 103.367 107.250 106.941 106.196 104.799 104.023 102.451 101.643 102.430 102.568 101.784 101.941 102.563 102.958 103.479 103.551 103.482 Table B–7. Chain-type price indexes for gross domestic product, 1963–2011—Continued [Index numbers, 2005=100, except as noted; quarterly data seasonally adjusted] Exports and imports of goods and services Government consumption expenditures and gross investment Federal Year or quarter Exports Imports Total Total 1963 ����������������� 1964 ����������������� 1965 ����������������� 1966 ����������������� 1967 ����������������� 1968 ����������������� 1969 ����������������� 1970 ����������������� 1971 ����������������� 1972 ����������������� 1973 ����������������� 1974 ����������������� 1975 ����������������� 1976 ����������������� 1977 ����������������� 1978 ����������������� 1979 ����������������� 1980 ����������������� 1981 ����������������� 1982 ����������������� 1983 ����������������� 1984 ����������������� 1985 ����������������� 1986 ����������������� 1987 ����������������� 1988 ����������������� 1989 ����������������� 1990 ����������������� 1991 ����������������� 1992 ����������������� 1993 ����������������� 1994 ����������������� 1995 ����������������� 1996 ����������������� 1997 ����������������� 1998 ����������������� 1999 ����������������� 2000 ����������������� 2001 ����������������� 2002 ����������������� 2003 ����������������� 2004 ����������������� 2005 ����������������� 2006 ����������������� 2007 ����������������� 2008 ����������������� 2009 ����������������� 2010 ����������������� 2011 p ��������������� 2008: I ������������� II ������������ III ����������� IV ����������� 2009: I ������������� II ������������ III ����������� IV ����������� 2010: I ������������� II ������������ III ����������� IV ����������� 2011: I ������������� II ������������ III ����������� IV p �������� 27.898 28.128 29.023 29.900 31.045 31.723 32.796 34.053 35.310 36.956 41.816 51.517 56.781 58.645 61.033 64.752 72.545 79.903 85.810 86.204 86.544 87.347 84.674 83.406 85.516 89.945 91.443 92.063 93.283 92.904 92.879 93.914 96.070 94.799 93.174 91.042 90.477 92.069 91.696 91.322 93.282 96.539 100.000 103.440 106.900 111.975 105.959 110.617 117.546 110.731 113.584 115.264 108.320 104.944 104.967 106.249 107.674 108.955 110.295 110.461 112.757 115.725 118.182 118.747 117.529 20.102 20.526 20.812 21.297 21.379 21.704 22.270 23.587 25.035 26.789 31.446 44.989 48.734 50.201 54.624 58.482 68.483 85.301 89.886 86.855 83.601 82.879 80.157 80.154 85.008 89.074 91.021 93.630 92.848 92.922 92.210 93.075 95.625 93.958 90.691 85.809 86.311 90.027 87.824 86.846 89.851 94.164 100.000 104.131 107.785 119.237 106.571 113.032 121.774 116.791 122.490 125.623 112.045 102.793 104.443 108.027 111.019 113.252 112.610 111.994 114.271 119.370 122.949 122.543 122.236 13.690 14.070 14.444 15.044 15.671 16.520 17.517 18.945 20.421 21.989 23.594 25.977 28.586 30.469 32.583 34.670 37.575 41.669 45.768 48.775 50.717 53.319 54.974 55.977 57.541 59.074 60.924 63.405 65.606 67.276 68.949 70.819 72.753 74.488 75.854 76.879 79.337 82.513 84.764 87.003 90.650 94.531 100.000 104.842 109.863 115.245 114.883 117.445 121.093 113.673 115.506 116.698 115.103 114.581 114.572 114.908 115.470 116.812 117.182 117.444 118.341 119.910 121.146 121.523 121.794 14.506 14.995 15.379 15.914 16.386 17.287 18.226 19.699 21.383 23.471 25.080 27.315 30.158 32.302 34.742 36.888 39.727 43.900 48.165 51.434 53.218 56.358 57.635 57.938 58.642 59.884 61.504 63.548 66.070 68.101 69.830 71.725 73.717 75.763 77.047 77.931 79.886 82.524 84.201 87.318 91.024 95.335 100.000 104.107 107.753 111.225 111.000 113.653 116.878 110.488 111.605 112.080 110.726 111.065 110.502 110.898 111.537 113.080 113.444 113.759 114.331 115.827 116.902 117.413 117.372 National Nondefense defense 14.209 14.620 15.024 15.535 15.994 16.834 17.757 19.116 20.810 23.209 24.911 27.223 29.880 32.057 34.486 36.908 39.853 44.179 48.542 51.953 53.775 57.603 58.696 58.642 59.236 60.326 61.882 63.917 66.222 68.522 69.712 71.438 73.161 75.431 76.517 77.328 79.225 81.821 83.484 86.624 90.659 94.895 100.000 104.421 108.249 112.187 111.402 114.046 117.593 111.240 112.696 113.251 111.561 111.610 110.902 111.202 111.892 113.455 113.834 114.093 114.802 116.576 117.672 118.119 118.005 15.037 15.798 16.104 16.708 17.215 18.327 19.284 21.143 22.746 23.892 25.231 27.245 30.505 32.549 34.993 36.514 39.100 42.906 46.917 49.825 51.501 52.779 54.574 55.915 56.953 58.679 60.497 62.568 65.672 67.034 70.002 72.267 74.830 76.406 78.095 79.120 81.188 83.907 85.612 88.689 91.774 96.234 100.000 103.468 106.743 109.240 110.188 112.860 115.456 108.936 109.353 109.654 109.017 109.961 109.690 110.285 110.817 112.321 112.655 113.083 113.380 114.333 115.367 116.011 116.115 State and local 13.028 13.293 13.662 14.334 15.137 15.945 17.013 18.411 19.720 20.896 22.495 24.970 27.410 29.114 31.005 33.042 35.976 40.002 43.975 46.786 48.857 51.034 53.002 54.577 56.849 58.621 60.654 63.474 65.443 66.856 68.494 70.351 72.252 73.806 75.219 76.320 79.036 82.482 85.019 86.810 90.425 94.062 100.000 105.276 111.112 117.666 117.214 119.704 123.646 115.571 117.848 119.496 117.750 116.666 117.030 117.326 117.835 119.030 119.404 119.627 120.757 122.372 123.721 123.997 124.494 Final sales of domestic product 19.141 19.440 19.798 20.363 20.996 21.898 22.988 24.203 25.415 26.516 27.992 30.519 33.418 35.350 37.614 40.266 43.614 47.598 52.074 55.280 57.464 59.624 61.466 62.856 64.607 66.865 69.397 72.102 74.655 76.436 78.123 79.775 81.449 83.024 84.522 85.516 86.795 88.698 90.709 92.168 94.123 96.774 100.000 103.240 106.238 108.576 109.703 110.981 113.242 107.647 108.309 109.171 109.179 109.637 109.544 109.652 109.979 110.375 110.761 111.140 111.647 112.315 113.021 113.754 113.876 Gross domestic purchases 1 Total 18.887 19.191 19.524 20.071 20.654 21.526 22.582 23.798 25.021 26.134 27.647 30.484 33.328 35.238 37.617 40.286 43.833 48.448 52.909 55.906 57.865 59.904 61.605 63.000 64.978 67.215 69.765 72.601 74.980 76.788 78.404 80.029 81.743 83.220 84.468 85.034 86.377 88.537 90.198 91.498 93.584 96.415 100.000 103.354 106.402 109.858 109.803 111.438 114.186 108.703 109.893 110.982 109.852 109.340 109.472 109.913 110.485 111.057 111.190 111.456 112.048 113.147 114.081 114.642 114.873 Percent change 2 Less food and energy Gross domestic product �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� 55.408 57.569 59.704 61.577 63.464 65.506 67.900 70.346 73.043 75.539 77.520 79.228 80.947 82.722 84.077 85.344 86.171 87.463 89.243 90.851 92.384 94.214 96.779 100.000 103.127 105.938 108.719 109.580 110.898 112.874 107.751 108.576 109.291 109.256 109.249 109.424 109.592 110.056 110.490 110.783 110.991 111.326 111.987 112.734 113.239 113.535 1.1 1.6 1.8 2.8 3.1 4.2 4.9 5.3 5.0 4.3 5.5 9.0 9.5 5.7 6.4 7.0 8.3 9.1 9.4 6.1 3.9 3.8 3.0 2.2 2.8 3.4 3.8 3.9 3.5 2.4 2.2 2.1 2.1 1.9 1.8 1.1 1.5 2.2 2.3 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 2.5 2.5 3.1 .5 1.7 –.4 .3 1.1 1.5 1.5 1.4 1.9 2.5 2.5 2.6 .4 Gross domestic purchases 1 Total 1.2 1.6 1.7 2.8 2.9 4.2 4.9 5.4 5.1 4.4 5.8 10.3 9.3 5.7 6.8 7.1 8.8 10.5 9.2 5.7 3.5 3.5 2.8 2.3 3.1 3.4 3.8 4.1 3.3 2.4 2.1 2.1 2.1 1.8 1.5 .7 1.6 2.5 1.9 1.4 2.3 3.0 3.7 3.4 2.9 3.2 –.1 1.5 2.5 4.1 4.5 4.0 –4.0 –1.9 .5 1.6 2.1 2.1 .5 1.0 2.1 4.0 3.3 2.0 .8 Less food and energy �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� �������������� 3.9 3.7 3.1 3.1 3.2 3.7 3.6 3.8 3.4 2.6 2.2 2.2 2.2 1.6 1.5 1.0 1.5 2.0 1.8 1.7 2.0 2.7 3.3 3.1 2.7 2.6 .8 1.2 1.8 3.4 3.1 2.7 –.1 .0 .6 .6 1.7 1.6 1.1 .8 1.2 2.4 2.7 1.8 1.0 1 Gross domestic product (GDP) less exports of goods and services plus imports of goods and services. 2 Quarterly percent changes are at annual rates. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 327 Table B–8. Gross domestic product by major type of product, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Goods Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product Final sales of domestic product 617.8 663.6 719.1 787.7 832.4 909.8 984.4 1,038.3 1,126.8 1,237.9 1,382.3 1,499.5 1,637.7 1,824.6 2,030.1 2,293.8 2,562.2 2,788.1 3,126.8 3,253.2 3,534.6 3,930.9 4,217.5 4,460.1 4,736.4 5,100.4 5,482.1 5,800.5 5,992.1 6,342.3 6,667.4 7,085.2 7,414.7 7,838.5 8,332.4 8,793.5 9,353.5 9,951.5 10,286.2 10,642.3 11,142.2 11,853.3 12,623.0 13,377.2 14,028.7 14,291.5 13,939.0 14,526.5 15,087.7 14,273.9 14,415.5 14,395.1 14,081.7 13,893.7 13,854.1 13,920.5 14,087.4 14,277.9 14,467.8 14,605.5 14,755.0 14,867.8 15,012.8 15,176.1 15,294.3 612.1 658.8 709.9 774.1 822.6 900.8 975.3 1,036.3 1,118.6 1,228.8 1,366.4 1,485.5 1,644.0 1,807.5 2,007.8 2,268.0 2,544.2 2,794.5 3,097.0 3,268.1 3,540.4 3,865.5 4,195.6 4,453.5 4,709.2 5,081.9 5,454.5 5,786.0 5,992.5 6,326.0 6,646.5 7,021.4 7,383.5 7,807.7 8,261.4 8,729.8 9,292.7 9,896.9 10,324.5 10,630.3 11,125.8 11,788.3 12,573.0 13,317.3 13,999.6 14,332.7 14,099.8 14,459.6 15,040.5 14,293.4 14,433.8 14,439.2 14,164.2 14,073.3 14,054.6 14,117.6 14,153.5 14,233.6 14,389.8 14,498.8 14,716.3 14,805.8 14,959.2 15,175.3 15,221.7 Change in private inventories 5.6 4.8 9.2 13.6 9.9 9.1 9.2 2.0 8.3 9.1 15.9 14.0 –6.3 17.1 22.3 25.8 18.0 –6.3 29.8 –14.9 –5.8 65.4 21.8 6.6 27.1 18.5 27.7 14.5 –.4 16.3 20.8 63.8 31.2 30.8 71.0 63.7 60.8 54.5 –38.3 12.0 16.4 64.9 50.0 60.0 29.1 –41.1 –160.8 66.9 47.2 –19.5 –18.3 –44.1 –82.5 –179.5 –200.5 –197.1 –66.1 44.3 78.1 106.7 38.7 62.0 53.6 .8 72.6 Total Total Final sales 258.5 277.8 304.3 337.1 345.4 370.8 397.6 408.7 432.6 472.0 547.1 588.0 628.6 706.6 773.5 872.6 977.2 1,035.2 1,167.3 1,148.8 1,226.9 1,402.2 1,452.8 1,491.2 1,570.7 1,703.7 1,851.9 1,923.1 1,943.5 2,031.5 2,124.2 2,290.7 2,379.5 2,516.3 2,701.2 2,819.2 2,990.1 3,124.5 3,077.6 3,101.2 3,170.7 3,333.8 3,475.7 3,663.7 3,844.1 3,758.6 3,617.0 4,009.9 4,256.0 3,825.3 3,847.5 3,789.8 3,571.9 3,539.7 3,567.3 3,617.4 3,743.7 3,909.7 3,953.8 4,050.0 4,126.1 4,193.8 4,199.4 4,262.2 4,368.7 252.9 273.0 295.1 323.5 335.5 361.7 388.4 406.7 424.4 462.9 531.2 574.0 634.8 689.5 751.2 846.8 959.2 1,041.5 1,137.5 1,163.7 1,232.6 1,336.8 1,431.0 1,484.7 1,543.6 1,685.2 1,824.2 1,908.5 1,943.9 2,015.1 2,103.4 2,226.9 2,348.3 2,485.5 2,630.2 2,755.5 2,929.3 3,070.0 3,115.9 3,089.1 3,154.3 3,268.9 3,425.8 3,603.7 3,815.0 3,799.7 3,777.8 3,943.0 4,208.8 3,844.8 3,865.8 3,833.9 3,654.4 3,719.2 3,767.8 3,814.5 3,809.8 3,865.4 3,875.8 3,943.4 4,087.4 4,131.8 4,145.8 4,261.4 4,296.1 Durable goods Change in private inventories 5.6 4.8 9.2 13.6 9.9 9.1 9.2 2.0 8.3 9.1 15.9 14.0 –6.3 17.1 22.3 25.8 18.0 –6.3 29.8 –14.9 –5.8 65.4 21.8 6.6 27.1 18.5 27.7 14.5 –.4 16.3 20.8 63.8 31.2 30.8 71.0 63.7 60.8 54.5 –38.3 12.0 16.4 64.9 50.0 60.0 29.1 –41.1 –160.8 66.9 47.2 –19.5 –18.3 –44.1 –82.5 –179.5 –200.5 –197.1 –66.1 44.3 78.1 106.7 38.7 62.0 53.6 .8 72.6 Final sales 108.6 119.3 131.6 145.4 150.0 162.8 175.7 178.6 186.7 208.4 243.6 262.4 293.2 330.9 374.6 424.9 483.9 512.3 554.8 552.5 592.3 665.9 727.9 758.3 785.3 863.3 939.7 973.2 967.6 1,010.7 1,072.9 1,149.8 1,225.9 1,321.0 1,430.7 1,524.2 1,633.8 1,734.4 1,731.5 1,678.9 1,699.3 1,759.3 1,873.8 1,973.4 2,087.3 2,043.1 1,911.4 2,006.0 2,153.6 2,101.3 2,090.2 2,058.1 1,922.8 1,900.3 1,903.4 1,929.6 1,912.4 1,953.1 1,982.2 2,015.0 2,073.6 2,094.1 2,119.9 2,184.5 2,215.9 Change in private inventories 1 2.6 3.8 6.2 10.0 4.8 4.5 6.0 –.2 2.9 6.4 13.0 10.9 –7.5 10.8 9.5 18.2 12.8 –2.3 7.3 –16.0 2.5 41.4 4.4 –1.9 22.9 22.7 20.0 7.7 –13.6 –3.0 17.1 35.7 33.6 19.1 40.0 39.3 37.4 35.6 –44.4 17.7 13.0 37.3 35.2 25.9 11.2 –23.1 –113.6 45.5 32.3 –16.0 –34.2 –7.1 –35.1 –142.1 –144.1 –118.8 –49.4 32.4 62.8 69.2 17.7 42.7 34.2 34.2 18.2 Nondurable goods Final sales 144.3 153.7 163.5 178.0 185.5 198.9 212.7 228.2 237.7 254.5 287.6 311.7 341.6 358.6 376.6 422.0 475.3 529.2 582.6 611.2 640.3 670.9 703.1 726.4 758.3 821.9 884.5 935.3 976.3 1,004.4 1,030.4 1,077.1 1,122.4 1,164.5 1,199.5 1,231.3 1,295.5 1,335.6 1,384.4 1,410.3 1,455.0 1,509.6 1,552.0 1,630.3 1,727.7 1,756.6 1,866.4 1,937.0 2,055.2 1,743.5 1,775.6 1,775.8 1,731.6 1,818.9 1,864.4 1,884.9 1,897.4 1,912.3 1,893.6 1,928.4 2,013.8 2,037.7 2,025.9 2,076.9 2,080.2 Change in private inventories 1 3.0 1.0 3.0 3.6 5.0 4.5 3.2 2.2 5.3 2.7 2.9 3.1 1.2 6.3 12.8 7.6 5.2 –4.0 22.5 1.1 –8.2 24.0 17.4 8.4 4.2 –4.3 7.7 6.8 13.2 19.3 3.7 28.1 –2.4 11.7 31.0 24.4 23.4 19.0 6.2 –5.6 3.3 27.6 14.7 34.0 17.9 –18.0 –47.2 21.4 14.9 –3.5 15.9 –37.0 –47.5 –37.4 –56.4 –78.3 –16.7 11.9 15.3 37.5 21.0 19.3 19.4 –33.4 54.4 Services 2 286.6 307.4 330.1 362.6 397.5 439.1 478.6 519.9 565.8 619.0 672.2 745.8 842.4 926.8 1,029.9 1,147.2 1,271.7 1,431.6 1,606.9 1,759.9 1,939.1 2,102.9 2,305.9 2,488.7 2,668.0 2,881.7 3,101.2 3,343.9 3,548.6 3,788.1 3,985.1 4,187.2 4,396.7 4,625.5 4,882.5 5,159.7 5,485.1 5,878.0 6,208.7 6,535.5 6,891.2 7,304.9 7,783.8 8,260.8 8,751.8 9,174.0 9,211.9 9,508.6 9,811.8 9,074.1 9,185.5 9,240.1 9,196.2 9,148.1 9,172.4 9,217.8 9,309.2 9,382.1 9,491.3 9,549.1 9,612.1 9,684.1 9,800.4 9,877.2 9,885.4 Structures 72.7 78.4 84.7 88.0 89.6 100.0 108.3 109.7 128.4 146.9 162.9 165.6 166.7 191.2 226.8 273.9 313.3 321.3 352.6 344.5 368.7 425.8 458.7 480.1 497.6 515.0 529.0 533.5 499.9 522.7 558.1 607.3 638.5 696.7 748.6 814.5 878.2 949.0 999.9 1,005.7 1,080.4 1,214.5 1,363.4 1,452.7 1,432.8 1,359.0 1,110.1 1,008.0 1,020.0 1,374.6 1,382.4 1,365.2 1,313.6 1,205.9 1,114.4 1,085.4 1,034.6 986.1 1,022.7 1,006.4 1,016.8 989.9 1,013.0 1,036.7 1,040.2 1 Estimates for durable and nondurable goods for 1996 and earlier periods are based on the Standard Industrial Classification (SIC); later estimates are based on the North American Industry Classification System (NAICS). 2 Includes government consumption expenditures, which are for services (such as education and national defense) produced by government. In current dollars, these services are valued at their cost of production. Source: Department of Commerce (Bureau of Economic Analysis). 328 | Appendix B Table B–9. Real gross domestic product by major type of product, 1963–2011 [Billions of chained (2005) dollars; quarterly data at seasonally adjusted annual rates] Goods Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product Final sales of domestic product Change in private inventories 3,204.0 3,389.4 3,607.0 3,842.1 3,939.2 4,129.9 4,258.2 4,266.3 4,409.5 4,643.8 4,912.8 4,885.7 4,875.4 5,136.9 5,373.1 5,672.8 5,850.1 5,834.0 5,982.1 5,865.9 6,130.9 6,571.5 6,843.4 7,080.5 7,307.0 7,607.4 7,879.2 8,027.1 8,008.3 8,280.0 8,516.2 8,863.1 9,086.0 9,425.8 9,845.9 10,274.7 10,770.7 11,216.4 11,337.5 11,543.1 11,836.4 12,246.9 12,623.0 12,958.5 13,206.4 13,161.9 12,703.1 13,088.0 13,313.4 13,266.8 13,310.5 13,186.9 12,883.5 12,663.2 12,641.3 12,694.5 12,813.5 12,937.7 13,058.5 13,139.6 13,216.1 13,227.9 13,271.8 13,331.6 13,422.4 3,199.9 3,390.8 3,587.6 3,803.4 3,920.0 4,115.8 4,245.0 4,284.3 4,403.6 4,636.7 4,884.0 4,870.0 4,922.1 5,115.9 5,340.3 5,634.9 5,836.2 5,873.6 5,954.4 5,918.2 6,167.6 6,490.0 6,833.1 7,092.7 7,289.9 7,601.3 7,860.8 8,025.8 8,027.9 8,277.2 8,508.0 8,801.7 9,065.4 9,404.4 9,774.2 10,208.3 10,706.5 11,158.0 11,382.0 11,533.6 11,820.5 12,181.3 12,573.0 12,899.3 13,177.5 13,200.5 12,852.7 13,028.9 13,281.8 13,277.8 13,325.9 13,225.6 12,972.9 12,836.0 12,830.0 12,875.1 12,869.5 12,895.9 12,992.2 13,046.0 13,181.6 13,182.8 13,236.2 13,340.9 13,367.4 20.3 17.3 32.9 47.1 33.9 30.8 30.3 5.6 25.0 25.7 39.0 29.1 –12.8 34.3 43.1 45.6 28.0 –9.3 39.0 –19.7 –7.7 78.3 25.4 8.5 33.2 21.9 30.6 16.6 –1.4 17.9 22.3 69.3 32.1 31.2 77.4 71.6 68.5 60.2 –41.8 12.8 17.3 66.3 50.0 59.4 27.7 –36.3 –144.9 58.8 35.6 –12.5 –14.2 –38.1 –80.3 –161.6 –183.0 –178.7 –56.5 39.9 64.6 92.3 38.3 49.1 39.1 –2.0 56.0 Total Total 673.0 718.1 778.4 846.0 848.3 882.2 912.6 905.0 931.8 995.5 1,101.4 1,090.8 1,063.5 1,147.0 1,202.1 1,282.9 1,335.9 1,324.2 1,384.0 1,312.8 1,369.5 1,539.3 1,576.1 1,622.2 1,687.5 1,792.5 1,894.4 1,914.2 1,881.9 1,958.7 2,034.1 2,177.1 2,257.1 2,380.4 2,566.0 2,714.7 2,905.1 3,046.9 2,997.7 3,049.9 3,160.3 3,324.4 3,475.7 3,659.1 3,819.6 3,789.7 3,566.6 3,984.2 4,162.9 3,862.0 3,905.1 3,822.0 3,569.6 3,471.1 3,502.7 3,569.9 3,722.8 3,903.4 3,941.5 4,016.9 4,075.1 4,124.5 4,118.1 4,140.6 4,268.4 Durable goods Nondurable goods Final sales Change in private inventories Final sales Change in private inventories 1 Final sales Change in private inventories 1 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� 2,234.2 2,356.6 2,502.1 2,654.8 2,847.0 2,993.5 3,034.2 3,038.0 3,142.4 3,259.1 3,425.8 3,599.9 3,792.1 3,834.7 3,732.1 3,921.9 4,131.4 3,877.2 3,924.9 3,867.0 3,669.9 3,661.8 3,710.8 3,769.3 3,786.6 3,859.9 3,871.2 3,916.6 4,040.1 4,078.0 4,082.0 4,154.6 4,211.0 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� 32.1 31.2 77.4 71.6 68.5 60.2 –41.8 12.8 17.3 66.3 50.0 59.4 27.7 –36.3 –144.9 58.8 35.6 –12.5 –14.2 –38.1 –80.3 –161.6 –183.0 –178.7 –56.5 39.9 64.6 92.3 38.3 49.1 39.1 –2.0 56.0 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� 1,017.9 1,105.4 1,216.7 1,334.8 1,469.2 1,582.7 1,606.7 1,588.8 1,658.0 1,750.4 1,873.8 1,989.5 2,133.1 2,129.9 1,994.5 2,128.4 2,302.9 2,176.0 2,189.4 2,150.2 2,004.0 1,974.0 1,979.3 2,020.1 2,004.6 2,061.4 2,100.9 2,140.2 2,211.2 2,240.2 2,266.6 2,334.2 2,370.7 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� 31.4 17.9 40.2 40.6 39.5 37.7 –46.4 18.1 13.5 38.1 35.2 25.2 10.8 –21.1 –105.9 41.5 28.2 –14.8 –30.5 –5.8 –33.3 –132.6 –135.1 –110.3 –45.6 30.0 57.1 62.6 16.4 37.4 29.8 29.8 15.9 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� 1,259.3 1,286.0 1,309.2 1,333.6 1,384.2 1,411.0 1,427.4 1,451.0 1,485.2 1,508.8 1,552.0 1,610.6 1,660.7 1,704.8 1,730.4 1,789.9 1,833.7 1,702.8 1,736.3 1,717.0 1,663.1 1,682.6 1,723.9 1,742.6 1,772.6 1,790.9 1,766.6 1,774.4 1,827.5 1,837.6 1,819.0 1,828.6 1,849.5 ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� ��������������� –3.3 12.5 36.1 29.5 27.7 21.4 7.3 –6.4 3.6 28.1 14.7 34.1 16.9 –15.5 –41.2 18.6 9.1 1.6 13.8 –30.8 –46.4 –32.2 –50.6 –70.0 –12.0 11.1 9.6 31.5 22.3 13.9 11.1 –27.2 38.7 Services 2 2,090.5 2,189.6 2,299.2 2,441.1 2,577.0 2,712.9 2,801.0 2,858.4 2,927.0 3,034.9 3,125.7 3,194.8 3,309.3 3,400.4 3,517.3 3,651.8 3,740.4 3,811.4 3,887.6 3,957.1 4,120.4 4,234.4 4,449.0 4,635.5 4,785.6 4,961.7 5,115.1 5,269.7 5,363.4 5,522.0 5,648.3 5,781.5 5,902.9 6,045.7 6,208.7 6,422.2 6,664.0 6,919.2 7,095.8 7,276.1 7,415.9 7,598.2 7,783.8 7,961.0 8,131.5 8,216.6 8,173.1 8,261.2 8,339.6 8,226.7 8,231.0 8,211.6 8,197.3 8,159.3 8,168.7 8,169.7 8,194.8 8,201.4 8,253.9 8,284.5 8,305.0 8,303.5 8,341.0 8,366.7 8,347.2 Structures 591.7 631.5 663.1 663.9 654.2 694.5 703.3 673.0 735.5 790.2 807.1 723.4 657.6 719.2 787.2 862.8 887.4 823.0 811.9 742.6 796.3 903.9 951.0 965.1 969.3 967.6 961.0 941.9 869.1 902.4 930.5 978.4 988.9 1,053.1 1,097.8 1,155.1 1,202.2 1,245.3 1,254.1 1,223.2 1,263.6 1,325.6 1,363.4 1,341.1 1,267.0 1,169.9 971.9 886.5 869.0 1,196.0 1,196.5 1,170.9 1,116.3 1,031.6 973.7 964.2 918.1 872.0 902.9 884.3 886.6 856.0 866.5 878.8 874.8 1 Estimates for durable and nondurable goods for 1996 and earlier periods are based on the Standard Industrial Classification (SIC); later estimates are based on the North American Industry Classification System (NAICS). 2 Includes government consumption expenditures, which are for services (such as education and national defense) produced by government. In current dollars, these services are valued at their cost of production. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 329 Table B–10. Gross value added by sector, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Business 1 Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Gross domestic product 617.8 663.6 719.1 787.7 832.4 909.8 984.4 1,038.3 1,126.8 1,237.9 1,382.3 1,499.5 1,637.7 1,824.6 2,030.1 2,293.8 2,562.2 2,788.1 3,126.8 3,253.2 3,534.6 3,930.9 4,217.5 4,460.1 4,736.4 5,100.4 5,482.1 5,800.5 5,992.1 6,342.3 6,667.4 7,085.2 7,414.7 7,838.5 8,332.4 8,793.5 9,353.5 9,951.5 10,286.2 10,642.3 11,142.2 11,853.3 12,623.0 13,377.2 14,028.7 14,291.5 13,939.0 14,526.5 15,087.7 14,273.9 14,415.5 14,395.1 14,081.7 13,893.7 13,854.1 13,920.5 14,087.4 14,277.9 14,467.8 14,605.5 14,755.0 14,867.8 15,012.8 15,176.1 15,294.3 Total 488.0 524.9 570.7 624.3 653.6 713.5 769.1 802.2 868.3 957.1 1,077.4 1,164.5 1,265.8 1,420.7 1,590.0 1,809.4 2,028.5 2,186.1 2,454.0 2,514.9 2,741.1 3,065.5 3,283.9 3,461.5 3,662.0 3,940.2 4,235.7 4,453.9 4,558.6 4,829.2 5,084.1 5,425.2 5,677.8 6,030.2 6,442.8 6,810.8 7,249.0 7,715.5 7,913.6 8,132.8 8,502.8 9,070.1 9,680.1 10,262.4 10,738.3 10,787.8 10,338.8 10,879.1 11,381.8 10,842.8 10,926.9 10,869.0 10,512.6 10,316.8 10,259.2 10,312.2 10,467.1 10,646.1 10,820.7 10,950.7 11,098.9 11,188.9 11,315.1 11,462.7 11,560.5 Nonfarm 1 469.5 507.5 550.7 603.5 633.5 693.0 746.3 778.5 842.9 927.5 1,030.6 1,120.3 1,220.1 1,377.7 1,546.5 1,758.7 1,968.4 2,134.7 2,389.0 2,454.5 2,696.2 3,001.3 3,220.5 3,402.1 3,600.5 3,879.4 4,162.0 4,376.6 4,488.0 4,748.9 5,012.7 5,341.3 5,608.7 5,936.9 6,354.9 6,731.6 7,177.8 7,641.9 7,837.4 8,060.5 8,410.4 8,951.9 9,578.0 10,169.4 10,623.4 10,657.4 10,225.7 10,746.5 11,230.4 10,699.7 10,791.9 10,746.2 10,391.9 10,206.7 10,146.7 10,198.5 10,350.9 10,524.4 10,697.1 10,809.6 10,954.7 11,038.0 11,161.4 11,307.4 11,414.7 Households and institutions Farm 18.5 17.3 19.9 20.8 20.1 20.5 22.8 23.7 25.4 29.7 46.8 44.2 45.6 43.0 43.5 50.7 60.1 51.4 65.0 60.4 44.9 64.2 63.4 59.5 61.5 60.7 73.8 77.3 70.6 80.4 71.4 83.9 69.1 93.3 87.9 79.2 71.2 73.6 76.2 72.3 92.4 118.3 102.0 93.1 114.9 130.5 113.1 132.6 151.4 143.2 135.1 122.8 120.7 110.1 112.6 113.7 116.2 121.7 123.6 141.1 144.1 150.9 153.6 155.3 145.8 Total 54.3 57.7 61.8 66.6 71.8 77.5 85.4 92.6 102.2 111.4 121.7 133.6 147.5 160.5 175.5 196.9 220.8 253.5 287.5 319.3 348.2 380.3 410.1 442.3 482.8 529.7 574.2 624.0 665.9 711.1 752.1 800.0 852.1 897.0 949.2 1,010.1 1,082.9 1,157.2 1,232.9 1,298.0 1,347.2 1,423.8 1,506.4 1,602.9 1,685.8 1,805.7 1,836.0 1,838.4 1,867.5 1,764.9 1,802.3 1,816.0 1,839.6 1,828.4 1,832.6 1,839.2 1,843.6 1,833.9 1,835.2 1,843.9 1,840.5 1,851.9 1,861.6 1,871.5 1,884.8 Households 39.1 41.2 43.6 46.2 49.1 51.9 56.0 59.8 65.5 70.8 76.5 83.0 90.8 98.7 107.9 121.3 136.0 156.5 177.8 196.7 212.5 231.0 250.3 268.0 288.0 313.1 337.2 363.3 383.7 405.3 428.3 461.3 492.2 519.8 550.9 583.9 628.4 673.5 719.5 746.0 762.7 806.0 864.4 924.8 968.1 1,042.8 1,046.9 1,033.6 1,037.3 1,016.1 1,045.6 1,050.1 1,059.2 1,050.3 1,043.9 1,049.8 1,043.5 1,039.3 1,033.0 1,031.5 1,030.6 1,035.1 1,036.7 1,035.9 1,041.6 Nonprofit institutions serving households 2 15.2 16.5 18.2 20.4 22.7 25.6 29.4 32.8 36.7 40.5 45.2 50.6 56.7 61.8 67.6 75.6 84.8 97.0 109.7 122.7 135.6 149.3 159.8 174.3 194.8 216.6 237.0 260.6 282.2 305.9 323.8 338.7 359.9 377.2 398.3 426.3 454.5 483.7 513.4 552.1 584.5 617.7 642.0 678.1 717.8 762.9 789.1 804.8 830.1 748.7 756.7 765.9 780.4 778.1 788.7 789.5 800.1 794.7 802.3 812.4 810.0 816.8 824.9 835.6 843.2 General government 3 Total 75.5 81.1 86.6 96.8 107.0 118.8 130.0 143.5 156.4 169.4 183.2 201.3 224.5 243.5 264.6 287.5 313.0 348.5 385.3 419.0 445.4 485.1 523.4 556.3 591.5 630.6 672.2 722.7 767.6 801.9 831.2 859.9 884.8 911.3 940.3 972.5 1,021.6 1,078.8 1,139.6 1,211.4 1,292.2 1,359.3 1,436.5 1,512.0 1,604.6 1,698.0 1,764.1 1,809.1 1,838.5 1,666.2 1,686.2 1,710.0 1,729.6 1,748.5 1,762.2 1,769.1 1,776.8 1,797.9 1,811.9 1,810.9 1,815.6 1,827.0 1,836.1 1,841.9 1,849.0 Federal 38.4 40.7 42.4 47.2 51.5 56.3 59.9 64.0 67.7 71.5 73.9 79.6 87.3 93.8 102.0 109.7 117.6 131.2 147.4 161.2 171.2 192.1 205.0 212.6 223.3 234.8 246.4 258.8 274.8 282.0 285.2 285.2 283.6 287.6 290.0 292.2 300.4 315.1 324.9 351.8 382.9 412.0 438.7 460.6 486.0 517.7 553.2 589.6 608.6 506.9 514.6 521.9 527.4 543.9 550.5 555.8 562.6 580.9 592.2 591.3 593.8 601.9 607.2 611.0 614.2 State and local 37.1 40.4 44.2 49.6 55.5 62.5 70.0 79.5 88.6 97.9 109.3 121.8 137.2 149.7 162.6 177.8 195.4 217.3 237.9 257.7 274.1 293.1 318.4 343.7 368.2 395.8 425.8 463.9 492.8 519.9 546.0 574.7 601.2 623.7 650.3 680.3 721.2 763.7 814.7 859.6 909.3 947.3 997.7 1,051.3 1,118.6 1,180.3 1,210.9 1,219.5 1,230.0 1,159.3 1,171.7 1,188.0 1,202.2 1,204.6 1,211.6 1,213.3 1,214.2 1,217.0 1,219.8 1,219.6 1,221.8 1,225.2 1,228.9 1,231.0 1,234.8 Addendum: Gross housing value added 48.9 51.6 54.9 58.2 62.1 65.9 71.3 76.7 83.9 91.1 98.3 106.8 117.2 126.6 140.5 155.5 172.9 199.8 228.8 255.7 277.7 301.3 333.1 359.7 385.5 415.3 443.4 477.8 508.1 538.6 562.9 602.6 640.7 671.3 708.6 745.3 798.3 849.9 904.4 932.5 938.2 988.7 1,054.0 1,130.8 1,200.6 1,299.7 1,321.2 1,314.5 1,330.3 1,262.6 1,299.3 1,310.3 1,326.8 1,319.8 1,317.6 1,325.9 1,321.4 1,319.6 1,313.5 1,312.8 1,312.3 1,321.5 1,327.4 1,330.4 1,341.7 1 Gross domestic business value added equals gross domestic product excluding gross value added of households and institutions and of general government. Nonfarm value added equals gross domestic business value added excluding gross farm value added. 2 Equals compensation of employees of nonprofit institutions, the rental value of nonresidential fixed assets owned and used by nonprofit institutions serving households, and rental income of persons for tenant-occupied housing owned by nonprofit institutions. 3 Equals compensation of general government employees plus general government consumption of fixed capital. Source: Department of Commerce (Bureau of Economic Analysis). 330 | Appendix B Table B–11. Real gross value added by sector, 1963–2011 [Billions of chained (2005) dollars; quarterly data at seasonally adjusted annual rates] Business 1 Year or quarter Gross domestic product Total Nonfarm 1 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� 3,204.0 3,389.4 3,607.0 3,842.1 3,939.2 4,129.9 4,258.2 4,266.3 4,409.5 4,643.8 4,912.8 4,885.7 4,875.4 5,136.9 5,373.1 5,672.8 5,850.1 5,834.0 5,982.1 5,865.9 6,130.9 6,571.5 6,843.4 7,080.5 7,307.0 7,607.4 7,879.2 8,027.1 8,008.3 8,280.0 8,516.2 8,863.1 9,086.0 9,425.8 9,845.9 10,274.7 10,770.7 11,216.4 11,337.5 11,543.1 11,836.4 12,246.9 12,623.0 12,958.5 13,206.4 13,161.9 12,703.1 13,088.0 13,313.4 13,266.8 13,310.5 13,186.9 12,883.5 12,663.2 12,641.3 12,694.5 12,813.5 12,937.7 13,058.5 13,139.6 13,216.1 13,227.9 13,271.8 13,331.6 13,422.4 2,186.8 2,325.4 2,489.6 2,658.0 2,708.9 2,843.7 2,930.7 2,930.0 3,042.6 3,238.5 3,465.5 3,413.7 3,381.8 3,605.2 3,805.8 4,045.6 4,179.9 4,132.8 4,247.7 4,119.1 4,341.0 4,717.9 4,937.0 5,121.2 5,289.8 5,516.6 5,720.9 5,808.8 5,757.9 5,985.1 6,178.1 6,481.0 6,663.3 6,966.8 7,327.5 7,693.8 8,123.7 8,491.4 8,559.5 8,726.8 9,001.6 9,363.0 9,680.1 9,974.0 10,172.5 10,038.4 9,550.3 9,923.9 10,153.1 10,182.9 10,189.0 10,049.3 9,732.3 9,518.9 9,493.9 9,535.7 9,652.6 9,773.3 9,886.9 9,977.9 10,057.5 10,065.9 10,107.9 10,175.1 10,263.4 2,152.8 2,297.1 2,459.8 2,635.6 2,681.0 2,821.6 2,907.6 2,904.4 3,014.8 3,215.2 3,450.9 3,400.3 3,344.8 3,579.3 3,778.7 4,027.9 4,155.0 4,110.3 4,197.8 4,062.4 4,323.6 4,679.3 4,880.9 5,070.4 5,239.3 5,478.3 5,671.7 5,753.4 5,700.5 5,914.6 6,121.3 6,407.0 6,610.4 6,901.6 7,253.2 7,624.8 8,051.5 8,408.3 8,482.3 8,646.1 8,910.5 9,265.1 9,578.0 9,874.6 10,082.1 9,934.2 9,430.8 9,804.7 10,055.7 10,077.1 10,087.5 9,952.9 9,619.4 9,402.3 9,375.7 9,408.3 9,537.0 9,657.6 9,766.6 9,851.7 9,942.8 9,964.0 10,009.6 10,079.2 10,169.8 Households and institutions Farm 25.7 24.9 26.5 25.5 27.6 26.6 27.5 28.3 29.8 29.8 29.5 28.8 34.3 32.7 34.5 33.3 36.3 35.2 46.5 48.8 31.9 43.3 52.9 50.8 51.3 45.6 52.3 56.0 56.9 66.2 57.8 70.5 56.4 65.3 72.5 69.4 72.8 83.5 77.7 81.2 91.6 97.9 102.0 99.1 90.3 101.7 117.1 116.5 99.3 102.5 99.4 95.0 110.0 114.0 115.6 126.2 112.5 112.6 117.3 123.2 112.7 102.4 99.9 98.2 96.8 Total 384.0 399.9 419.7 438.9 457.1 480.1 501.2 510.2 531.7 554.8 574.6 597.7 617.9 628.2 637.5 666.4 695.3 730.9 754.1 778.9 801.0 826.8 841.2 863.4 895.8 937.2 974.8 1,009.6 1,038.5 1,071.4 1,106.9 1,140.0 1,175.5 1,199.8 1,240.5 1,280.2 1,325.5 1,376.2 1,407.0 1,417.3 1,417.8 1,457.4 1,506.4 1,539.8 1,571.9 1,628.6 1,623.0 1,630.6 1,635.2 1,603.9 1,634.4 1,636.9 1,639.3 1,623.4 1,615.9 1,625.6 1,627.1 1,630.3 1,632.1 1,630.2 1,629.8 1,633.7 1,638.4 1,633.4 1,635.4 Nonprofit institutions serving households 2 Households 226.9 236.0 246.9 256.8 267.1 274.6 285.9 292.6 305.9 319.1 330.6 345.0 354.2 360.9 365.0 387.4 405.0 430.6 444.1 452.1 460.5 476.4 487.4 493.7 506.8 525.7 542.0 555.7 572.0 589.0 603.5 631.9 651.3 665.4 687.6 703.7 740.3 774.1 793.1 789.9 787.1 821.7 864.4 898.0 914.2 954.8 944.8 943.2 934.5 938.1 961.0 958.7 961.3 947.0 939.4 946.5 946.5 947.0 946.1 941.6 938.1 940.1 940.0 929.2 928.7 152.6 159.4 168.6 178.5 186.6 204.9 214.9 216.7 224.5 234.4 242.7 251.0 262.5 265.8 271.3 276.7 287.8 297.1 306.8 324.3 338.5 348.3 351.2 368.0 388.0 411.1 432.9 454.9 467.4 483.5 504.9 508.7 524.8 535.0 553.5 577.8 585.3 601.8 613.4 627.7 631.1 635.9 642.0 642.0 657.8 674.2 678.3 687.2 699.8 666.1 673.9 678.6 678.4 676.6 676.6 679.2 680.7 683.3 686.0 688.3 691.2 693.1 697.7 702.9 705.4 General government 3 Total 742.8 768.4 794.2 843.9 888.7 923.6 947.2 950.8 952.4 950.6 954.9 974.4 990.1 998.7 1,009.2 1,028.5 1,039.5 1,054.4 1,060.2 1,071.0 1,077.9 1,091.3 1,122.5 1,150.1 1,175.3 1,205.8 1,234.6 1,266.2 1,279.4 1,283.7 1,286.5 1,286.8 1,287.7 1,289.8 1,299.6 1,314.3 1,326.3 1,349.4 1,373.7 1,401.4 1,418.2 1,426.8 1,436.5 1,445.0 1,462.5 1,492.3 1,520.1 1,527.9 1,522.6 1,479.6 1,486.1 1,498.0 1,505.4 1,511.5 1,521.2 1,522.9 1,524.9 1,526.7 1,533.1 1,526.7 1,525.1 1,524.6 1,522.5 1,520.9 1,522.3 Federal 396.7 400.7 403.4 429.9 457.9 465.7 467.1 447.1 426.5 405.8 390.7 389.4 387.3 387.9 389.0 393.9 393.5 399.7 405.9 412.5 422.0 431.6 443.9 451.8 463.6 469.3 475.1 483.8 486.7 476.5 467.4 452.2 435.1 423.2 415.2 410.4 407.1 410.5 412.1 420.2 431.5 435.8 438.7 438.4 441.8 459.0 485.9 503.7 508.9 449.6 454.5 462.2 469.9 475.1 485.6 489.7 493.2 498.5 507.0 504.3 505.0 507.4 508.4 508.7 511.0 State and local 356.1 377.5 400.5 424.2 442.1 468.6 490.0 511.7 532.5 550.9 570.2 590.9 608.9 616.9 626.4 641.0 652.4 661.2 660.9 665.2 662.5 666.4 685.6 705.4 719.0 743.6 766.4 789.2 799.4 813.0 824.2 838.5 855.1 868.4 885.6 904.6 919.5 939.0 961.3 980.9 986.7 991.0 997.7 1,006.5 1,020.8 1,033.3 1,034.6 1,025.0 1,014.6 1,030.1 1,031.5 1,035.8 1,035.7 1,036.7 1,036.0 1,033.7 1,032.3 1,028.9 1,026.8 1,023.2 1,020.9 1,018.1 1,014.9 1,013.1 1,012.2 Addendum: Gross housing value added 278.9 291.6 307.1 320.9 335.6 348.3 364.6 376.6 393.6 412.5 427.8 448.5 462.2 469.3 481.2 503.2 523.0 555.0 576.7 592.3 605.4 624.6 649.1 661.1 676.8 696.4 712.2 730.2 754.6 776.7 789.1 821.7 846.9 860.4 885.6 900.9 942.3 977.8 997.8 988.5 969.3 1,008.4 1,054.0 1,098.6 1,132.4 1,183.9 1,184.6 1,189.5 1,187.3 1,161.3 1,188.5 1,189.7 1,196.1 1,182.2 1,178.0 1,187.9 1,190.2 1,192.9 1,192.4 1,188.4 1,184.4 1,189.2 1,192.3 1,183.1 1,184.6 1 Gross domestic business value added equals gross domestic product excluding gross value added of households and institutions and of general government. Nonfarm value added equals gross domestic business value added excluding gross farm value added. 2 Equals compensation of employees of nonprofit institutions, the rental value of nonresidential fixed assets owned and used by nonprofit institutions serving households, and rental income of persons for tenant-occupied housing owned by nonprofit institutions. 3 Equals compensation of general government employees plus general government consumption of fixed capital. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 331 Table B–12. Gross domestic product (GDP) by industry, value added, in current dollars and as a percentage of GDP, 1980–2010 [Billions of dollars; except as noted] Private industries Year Gross domestic product Total private industries Agriculture, forestry, fishing, and hunting Manufacturing Mining Construction Total manufacturing Durable goods Nondurable goods Utilities Wholesale trade Retail trade Value added 1980 ����������� 1981 ����������� 1982 ����������� 1983 ����������� 1984 ����������� 1985 ����������� 1986 ����������� 1987 ����������� 1988 ����������� 1989 ����������� 1990 ����������� 1991 ����������� 1992 ����������� 1993 ����������� 1994 ����������� 1995 ����������� 1996 ����������� 1997 ����������� 1998 ����������� 1999 ����������� 2000 ����������� 2001 ����������� 2002 ����������� 2003 ����������� 2004 ����������� 2005 ����������� 2006 ����������� 2007 ����������� 2008 ����������� 2009 ����������� 2010 ����������� 2,788.1 3,126.8 3,253.2 3,534.6 3,930.9 4,217.5 4,460.1 4,736.4 5,100.4 5,482.1 5,800.5 5,992.1 6,342.3 6,667.4 7,085.2 7,414.7 7,838.5 8,332.4 8,793.5 9,353.5 9,951.5 10,286.2 10,642.3 11,142.2 11,853.3 12,623.0 13,377.2 14,028.7 14,291.5 13,939.0 14,526.5 2,404.8 2,701.6 2,791.4 3,041.7 3,393.0 3,634.6 3,840.4 4,077.9 4,395.3 4,729.7 4,994.3 5,133.2 5,442.0 5,735.9 6,119.9 6,420.0 6,812.6 7,271.0 7,694.4 8,199.6 8,736.1 9,010.8 9,289.3 9,706.9 10,345.6 11,037.1 11,709.4 12,268.8 12,437.1 12,018.1 12,558.0 62.1 75.6 71.6 57.2 77.0 76.6 73.7 78.8 78.1 91.6 95.7 88.3 99.3 90.6 105.6 91.3 114.2 108.4 100.3 92.8 95.6 98.6 94.4 115.5 142.7 127.1 122.5 144.5 159.4 140.0 157.0 90.8 121.5 118.5 102.8 107.2 106.2 70.3 73.1 74.1 78.6 88.4 79.5 73.6 74.4 75.9 76.7 90.0 94.8 81.0 82.0 108.9 119.3 109.5 134.9 159.3 192.3 229.8 254.5 319.2 213.4 239.5 86.3 86.4 85.8 86.1 86.3 86.2 86.1 86.1 86.2 86.3 86.1 85.7 85.8 86.0 86.4 86.6 86.9 87.3 87.5 87.7 87.8 87.6 87.3 87.1 87.3 87.4 87.5 87.5 87.0 86.2 86.4 2.2 2.4 2.2 1.6 2.0 1.8 1.7 1.7 1.5 1.7 1.6 1.5 1.6 1.4 1.5 1.2 1.5 1.3 1.1 1.0 1.0 1.0 .9 1.0 1.2 1.0 .9 1.0 1.1 1.0 1.1 3.3 3.9 3.6 2.9 2.7 2.5 1.6 1.5 1.5 1.4 1.5 1.3 1.2 1.1 1.1 1.0 1.1 1.1 .9 .9 1.1 1.2 1.0 1.2 1.3 1.5 1.7 1.8 2.2 1.5 1.6 Percent 1980 ����������� 1981 ����������� 1982 ����������� 1983 ����������� 1984 ����������� 1985 ����������� 1986 ����������� 1987 ����������� 1988 ����������� 1989 ����������� 1990 ����������� 1991 ����������� 1992 ����������� 1993 ����������� 1994 ����������� 1995 ����������� 1996 ����������� 1997 ����������� 1998 ����������� 1999 ����������� 2000 ����������� 2001 ����������� 2002 ����������� 2003 ����������� 2004 ����������� 2005 ����������� 2006 ����������� 2007 ����������� 2008 ����������� 2009 ����������� 2010 ����������� 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 131.5 133.1 131.0 139.6 160.7 177.0 197.2 210.1 226.5 238.6 243.6 228.8 233.2 250.4 277.2 294.2 320.9 346.7 383.7 428.4 467.3 490.5 494.3 516.1 554.2 612.5 651.0 653.8 614.2 541.9 511.6 558.3 619.6 606.5 657.5 731.8 751.4 777.4 823.1 900.2 950.2 968.9 976.7 1,016.7 1,058.9 1,127.3 1,180.9 1,208.5 1,277.3 1,326.7 1,368.1 1,415.6 1,343.9 1,355.5 1,374.3 1,482.7 1,569.3 1,648.4 1,698.0 1,628.5 1,540.2 1,701.9 339.2 376.2 359.2 385.5 451.0 458.6 468.4 492.5 537.9 562.4 558.9 554.2 574.5 603.0 650.2 675.4 705.0 748.9 781.2 802.4 839.1 758.8 767.8 766.4 822.0 878.3 921.3 939.9 904.1 800.4 914.5 219.2 243.4 247.3 272.0 280.7 292.8 308.9 330.6 362.2 387.7 410.1 422.5 442.2 456.0 477.1 505.5 503.5 528.3 545.6 565.6 576.5 585.2 587.8 607.9 660.6 691.0 727.1 758.1 724.4 739.8 787.4 61.0 72.0 83.2 94.4 105.7 113.0 117.5 125.8 125.1 138.2 145.5 153.8 159.7 164.3 171.2 175.3 173.4 169.9 165.1 172.7 173.9 177.6 181.0 192.0 208.0 205.9 236.0 248.6 257.7 258.3 264.9 186.3 206.2 206.6 222.4 249.8 269.2 279.3 285.6 314.3 335.7 347.7 362.6 380.1 402.5 444.5 460.2 492.5 524.9 557.3 579.1 617.7 613.3 614.9 638.1 684.2 725.5 769.7 816.7 824.1 768.5 797.3 198.3 218.0 226.9 255.3 286.8 309.1 331.4 345.7 366.8 390.7 400.4 407.9 430.0 462.9 500.5 525.0 556.8 589.9 626.9 653.4 686.2 703.9 731.2 769.5 795.1 837.6 875.8 887.9 848.6 837.2 884.9 2.2 2.3 2.6 2.7 2.7 2.7 2.6 2.7 2.5 2.5 2.5 2.6 2.5 2.5 2.4 2.4 2.2 2.0 1.9 1.8 1.7 1.7 1.7 1.7 1.8 1.6 1.8 1.8 1.8 1.9 1.8 6.7 6.6 6.4 6.3 6.4 6.4 6.3 6.0 6.2 6.1 6.0 6.1 6.0 6.0 6.3 6.2 6.3 6.3 6.3 6.2 6.2 6.0 5.8 5.7 5.8 5.7 5.8 5.8 5.8 5.5 5.5 7.1 7.0 7.0 7.2 7.3 7.3 7.4 7.3 7.2 7.1 6.9 6.8 6.8 6.9 7.1 7.1 7.1 7.1 7.1 7.0 6.9 6.8 6.9 6.9 6.7 6.6 6.5 6.3 5.9 6.0 6.1 Industry value added as a percentage of GDP (percent) 4.7 4.3 4.0 3.9 4.1 4.2 4.4 4.4 4.4 4.4 4.2 3.8 3.7 3.8 3.9 4.0 4.1 4.2 4.4 4.6 4.7 4.8 4.6 4.6 4.7 4.9 4.9 4.7 4.3 3.9 3.5 20.0 19.8 18.6 18.6 18.6 17.8 17.4 17.4 17.6 17.3 16.7 16.3 16.0 15.9 15.9 15.9 15.4 15.3 15.1 14.6 14.2 13.1 12.7 12.3 12.5 12.4 12.3 12.1 11.4 11.0 11.7 12.2 12.0 11.0 10.9 11.5 10.9 10.5 10.4 10.5 10.3 9.6 9.2 9.1 9.0 9.2 9.1 9.0 9.0 8.9 8.6 8.4 7.4 7.2 6.9 6.9 7.0 6.9 6.7 6.3 5.7 6.3 7.9 7.8 7.6 7.7 7.1 6.9 6.9 7.0 7.1 7.1 7.1 7.1 7.0 6.8 6.7 6.8 6.4 6.3 6.2 6.0 5.8 5.7 5.5 5.5 5.6 5.5 5.4 5.4 5.1 5.3 5.4 1 Consists of agriculture, forestry, fishing, and hunting; mining; construction; and manufacturing. 2 Consists of utilities; wholesale trade; retail trade; transportation and warehousing; information; finance, insurance, real estate, rental, and leasing; professional and business services; educational services, health care, and social assistance; arts, entertainment, recreation, accommodation, and food services; and other services, except government. Note: Data shown in Tables B–12 and B–13 are consistent with the 2011 flexible annual revision of the industry accounts released in December 2011. For details see Survey of Current Business, December 2011. See next page for continuation of table. 332 | Appendix B Table B–12. Gross domestic product (GDP) by industry, value added, in current dollars and as a percentage of GDP, 1980–2010—Continued [Billions of dollars; except as noted] Private industries—Continued Year Transportation and warehousing Information Finance, insurance, real estate, rental, and leasing Professional and business services Educational services, health care, and social assistance Arts, entertainment, recreation, accommodation, and food services Private goodsOther Government producing services, industries 1 except government Private servicesproducing industries 2 Value added 1980 ������������� 1981 ������������� 1982 ������������� 1983 ������������� 1984 ������������� 1985 ������������� 1986 ������������� 1987 ������������� 1988 ������������� 1989 ������������� 1990 ������������� 1991 ������������� 1992 ������������� 1993 ������������� 1994 ������������� 1995 ������������� 1996 ������������� 1997 ������������� 1998 ������������� 1999 ������������� 2000 ������������� 2001 ������������� 2002 ������������� 2003 ������������� 2004 ������������� 2005 ������������� 2006 ������������� 2007 ������������� 2008 ������������� 2009 ������������� 2010 ������������� 102.6 110.1 106.3 118.0 131.4 137.1 147.0 152.6 161.4 166.3 172.8 182.3 192.0 206.4 223.7 231.7 241.3 261.8 275.6 287.1 301.4 302.6 302.4 319.8 347.0 369.5 394.0 404.9 415.0 391.7 402.5 108.3 123.5 135.3 152.5 160.0 176.4 185.6 197.4 205.4 222.4 235.6 244.3 260.5 279.6 299.4 311.5 338.6 349.4 386.1 438.5 417.8 451.1 499.7 506.6 558.8 586.5 590.6 635.5 636.8 615.4 623.5 446.8 502.8 544.7 611.6 677.5 739.4 804.0 850.3 915.7 981.0 1,049.2 1,109.8 1,192.1 1,259.3 1,321.6 1,405.7 1,490.3 1,610.6 1,696.8 1,834.0 1,997.7 2,154.8 2,222.3 2,316.5 2,400.4 2,598.8 2,765.3 2,857.0 2,916.6 2,964.5 3,007.2 1980 ������������� 1981 ������������� 1982 ������������� 1983 ������������� 1984 ������������� 1985 ������������� 1986 ������������� 1987 ������������� 1988 ������������� 1989 ������������� 1990 ������������� 1991 ������������� 1992 ������������� 1993 ������������� 1994 ������������� 1995 ������������� 1996 ������������� 1997 ������������� 1998 ������������� 1999 ������������� 2000 ������������� 2001 ������������� 2002 ������������� 2003 ������������� 2004 ������������� 2005 ������������� 2006 ������������� 2007 ������������� 2008 ������������� 2009 ������������� 2010 ������������� 3.7 3.5 3.3 3.3 3.3 3.3 3.3 3.2 3.2 3.0 3.0 3.0 3.0 3.1 3.2 3.1 3.1 3.1 3.1 3.1 3.0 2.9 2.8 2.9 2.9 2.9 2.9 2.9 2.9 2.8 2.8 3.9 4.0 4.2 4.3 4.1 4.2 4.2 4.2 4.0 4.1 4.1 4.1 4.1 4.2 4.2 4.2 4.3 4.2 4.4 4.7 4.2 4.4 4.7 4.5 4.7 4.6 4.4 4.5 4.5 4.4 4.3 16.0 16.1 16.7 17.3 17.2 17.5 18.0 18.0 18.0 17.9 18.1 18.5 18.8 18.9 18.7 19.0 19.0 19.3 19.3 19.6 20.1 20.9 20.9 20.8 20.3 20.6 20.7 20.4 20.4 21.3 20.7 173.1 197.3 213.2 242.4 280.9 316.3 352.4 384.5 424.3 470.4 516.5 524.0 566.6 600.9 639.7 687.3 756.5 842.1 927.0 1,010.2 1,116.8 1,170.7 1,198.3 1,260.0 1,347.5 1,460.2 1,567.2 1,697.6 1,783.2 1,678.1 1,782.8 134.1 152.9 169.2 189.7 207.1 225.4 245.2 277.7 301.5 337.4 376.7 413.4 452.9 476.4 500.2 523.9 545.4 571.4 601.2 638.5 678.0 729.2 789.8 847.1 906.1 953.5 1,015.3 1,076.9 1,153.9 1,210.4 1,272.3 83.0 92.9 100.0 111.5 120.8 132.0 144.0 152.3 168.8 184.0 199.6 205.9 219.0 230.9 242.3 255.3 272.8 300.3 321.1 355.4 381.6 391.2 411.1 427.8 458.7 485.4 512.4 549.0 537.3 517.6 555.8 68.5 76.0 78.3 86.8 96.3 105.3 115.3 121.1 133.0 144.8 153.9 155.9 166.3 178.3 190.7 200.7 211.2 223.8 245.6 259.3 277.6 264.2 285.0 288.8 300.8 313.0 331.6 343.8 342.7 340.8 356.8 383.3 425.2 461.8 492.9 537.9 582.9 619.7 658.4 705.1 752.4 806.2 858.9 900.3 931.4 965.3 994.6 1,025.9 1,061.3 1,099.1 1,153.9 1,215.4 1,275.4 1,353.0 1,435.3 1,507.7 1,585.9 1,667.8 1,759.9 1,854.4 1,920.9 1,968.5 842.8 949.9 927.7 957.1 1,076.7 1,111.2 1,118.6 1,185.0 1,278.8 1,358.9 1,396.5 1,373.2 1,422.8 1,474.3 1,586.1 1,643.1 1,733.6 1,827.2 1,891.7 1,971.3 2,087.4 2,052.3 2,053.7 2,140.8 2,338.9 2,501.2 2,651.6 2,750.9 2,721.2 2,435.5 2,610.1 1,562.0 1,751.7 1,863.7 2,084.6 2,316.3 2,523.4 2,721.8 2,892.9 3,116.5 3,370.8 3,597.7 3,760.0 4,019.2 4,261.6 4,533.8 4,776.9 5,079.0 5,443.8 5,802.7 6,228.3 6,648.7 6,958.5 7,235.6 7,566.1 8,006.6 8,535.8 9,057.8 9,517.9 9,715.9 9,582.6 9,948.0 13.7 13.6 14.2 13.9 13.7 13.8 13.9 13.9 13.8 13.7 13.9 14.3 14.2 14.0 13.6 13.4 13.1 12.7 12.5 12.3 12.2 12.4 12.7 12.9 12.7 12.6 12.5 12.5 13.0 13.8 13.6 30.2 30.4 28.5 27.1 27.4 26.3 25.1 25.0 25.1 24.8 24.1 22.9 22.4 22.1 22.4 22.2 22.1 21.9 21.5 21.1 21.0 20.0 19.3 19.2 19.7 19.8 19.8 19.6 19.0 17.5 18.0 56.0 56.0 57.3 59.0 58.9 59.8 61.0 61.1 61.1 61.5 62.0 62.8 63.4 63.9 64.0 64.4 64.8 65.3 66.0 66.6 66.8 67.6 68.0 67.9 67.5 67.6 67.7 67.8 68.0 68.7 68.5 Industry value added as a percentage of GDP (percent) 6.2 6.3 6.6 6.9 7.1 7.5 7.9 8.1 8.3 8.6 8.9 8.7 8.9 9.0 9.0 9.3 9.7 10.1 10.5 10.8 11.2 11.4 11.3 11.3 11.4 11.6 11.7 12.1 12.5 12.0 12.3 4.8 4.9 5.2 5.4 5.3 5.3 5.5 5.9 5.9 6.2 6.5 6.9 7.1 7.1 7.1 7.1 7.0 6.9 6.8 6.8 6.8 7.1 7.4 7.6 7.6 7.6 7.6 7.7 8.1 8.7 8.8 3.0 3.0 3.1 3.2 3.1 3.1 3.2 3.2 3.3 3.4 3.4 3.4 3.5 3.5 3.4 3.4 3.5 3.6 3.7 3.8 3.8 3.8 3.9 3.8 3.9 3.8 3.8 3.9 3.8 3.7 3.8 2.5 2.4 2.4 2.5 2.4 2.5 2.6 2.6 2.6 2.6 2.7 2.6 2.6 2.7 2.7 2.7 2.7 2.7 2.8 2.8 2.8 2.6 2.7 2.6 2.5 2.5 2.5 2.5 2.4 2.4 2.5 Note (cont’d): Value added is the contribution of each private industry and of government to GDP. Value added is equal to an industry’s gross output minus its intermediate inputs. Current-dollar value added is calculated as the sum of distributions by an industry to its labor and capital, which are derived from the components of gross domestic income. Value added industry data shown in Tables B–12 and B–13 are based on the 2002 North American Industry Classification System (NAICS). Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 333 Table B–13. Real gross domestic product by industry, value added, and percent changes, 1980–2010 Private industries Year Gross domestic product Total private industries Agriculture, forestry, fishing, and hunting Manufacturing Mining Construction Total manufacturing Durable goods Nondurable goods Utilities Wholesale trade Retail trade Chain-type quantity indexes for value added (2005=100) 1980 ����������� 1981 ����������� 1982 ����������� 1983 ����������� 1984 ����������� 1985 ����������� 1986 ����������� 1987 ����������� 1988 ����������� 1989 ����������� 1990 ����������� 1991 ����������� 1992 ����������� 1993 ����������� 1994 ����������� 1995 ����������� 1996 ����������� 1997 ����������� 1998 ����������� 1999 ����������� 2000 ����������� 2001 ����������� 2002 ����������� 2003 ����������� 2004 ����������� 2005 ����������� 2006 ����������� 2007 ����������� 2008 ����������� 2009 ����������� 2010 ����������� 46.217 47.390 46.470 48.570 52.060 54.214 56.092 57.887 60.266 62.420 63.591 63.442 65.595 67.466 70.214 71.980 74.672 78.000 81.397 85.326 88.857 89.816 91.445 93.769 97.021 100.000 102.658 104.622 104.270 100.635 103.684 44.227 45.387 44.282 46.325 49.753 51.961 53.470 55.466 58.098 60.243 61.264 61.161 63.537 65.296 68.374 70.112 73.146 76.840 80.541 84.778 88.667 89.792 91.300 93.464 96.945 100.000 102.980 104.953 103.909 99.343 102.877 38.449 48.384 51.011 36.388 47.087 55.753 54.881 56.750 50.675 56.742 60.074 60.756 67.964 58.983 70.448 59.555 66.286 71.591 69.837 73.031 81.603 78.861 82.079 90.644 96.510 100.000 100.756 93.149 101.279 112.225 108.774 115.603 114.882 109.757 104.252 114.545 121.137 116.810 122.364 136.911 132.276 130.787 133.113 129.022 131.161 142.428 143.474 133.682 138.097 148.848 137.847 121.027 136.785 138.414 120.511 119.237 100.000 108.435 111.427 107.236 129.626 121.680 1980 ����������� 1981 ����������� 1982 ����������� 1983 ����������� 1984 ����������� 1985 ����������� 1986 ����������� 1987 ����������� 1988 ����������� 1989 ����������� 1990 ����������� 1991 ����������� 1992 ����������� 1993 ����������� 1994 ����������� 1995 ����������� 1996 ����������� 1997 ����������� 1998 ����������� 1999 ����������� 2000 ����������� 2001 ����������� 2002 ����������� 2003 ����������� 2004 ����������� 2005 ����������� 2006 ����������� 2007 ����������� 2008 ����������� 2009 ����������� 2010 ����������� –0.3 2.5 –1.9 4.5 7.2 4.1 3.5 3.2 4.1 3.6 1.9 –.2 3.4 2.9 4.1 2.5 3.7 4.5 4.4 4.8 4.1 1.1 1.8 2.5 3.5 3.1 2.7 1.9 –.3 –3.5 3.0 –0.6 2.6 –2.4 4.6 7.4 4.4 2.9 3.7 4.7 3.7 1.7 –.2 3.9 2.8 4.7 2.5 4.3 5.1 4.8 5.3 4.6 1.3 1.7 2.4 3.7 3.2 3.0 1.9 –1.0 –4.4 3.6 –1.2 25.8 5.4 –28.7 29.4 18.4 –1.6 3.4 –10.7 12.0 5.9 1.1 11.9 –13.2 19.4 –15.5 11.3 8.0 –2.5 4.6 11.7 –3.4 4.1 10.4 6.5 3.6 .8 –7.5 8.7 10.8 –3.1 10.4 –.6 –4.5 –5.0 9.9 5.8 –3.6 4.8 11.9 –3.4 –1.1 1.8 –3.1 1.7 8.6 .7 –6.8 3.3 7.8 –7.4 –12.2 13.0 1.2 –12.9 –1.1 –16.1 8.4 2.8 –3.8 20.9 –6.1 75.146 68.529 60.546 62.785 70.655 75.849 77.499 79.148 82.976 85.326 84.779 78.616 80.403 82.649 87.293 88.224 92.982 95.170 98.277 103.607 106.961 104.536 100.882 101.161 101.134 100.000 96.982 91.606 85.547 74.474 72.127 43.142 45.199 41.913 45.226 49.545 51.109 51.078 54.843 58.683 59.359 58.575 57.674 59.597 61.987 66.078 68.798 70.997 75.261 79.022 83.268 88.584 84.499 86.606 89.347 96.658 100.000 104.159 107.847 101.545 92.000 102.328 33.516 34.438 31.046 33.064 38.389 39.540 39.836 42.637 46.870 47.610 46.726 45.243 46.187 48.129 51.830 55.832 59.253 64.194 70.550 75.962 84.443 79.298 82.246 85.053 93.004 100.000 106.663 110.655 108.932 92.746 108.529 61.448 66.320 64.152 70.536 70.782 73.192 72.251 77.950 80.123 80.544 80.093 80.651 84.672 87.853 92.380 91.805 91.157 93.699 92.120 94.101 93.958 91.571 92.420 95.052 101.453 100.000 101.069 104.394 93.038 90.535 95.142 59.058 58.963 57.737 60.798 66.262 70.538 74.025 82.732 82.022 90.437 95.576 96.834 97.689 96.434 99.397 102.620 101.716 97.108 95.007 104.692 108.309 93.854 97.378 100.904 104.815 100.000 100.539 104.004 108.818 96.381 99.554 28.963 30.726 30.871 32.224 34.845 36.656 40.323 39.192 41.306 43.307 42.692 44.438 48.490 49.957 53.134 52.901 57.783 64.068 74.157 78.059 83.510 87.671 88.479 93.901 98.912 100.000 102.995 108.619 107.416 92.866 96.473 34.293 35.287 35.240 38.504 42.183 44.468 47.777 46.100 50.726 52.973 53.825 53.661 56.467 59.225 63.523 66.714 72.881 79.185 84.195 86.596 89.942 92.731 95.770 97.961 97.982 100.000 102.176 102.473 96.613 94.284 103.764 –5.0 7.9 –3.3 10.0 .3 3.4 –1.3 7.9 2.8 .5 –.6 .7 5.0 3.8 5.2 –.6 –.7 2.8 –1.7 2.2 –.2 –2.5 .9 2.8 6.7 –1.4 1.1 3.3 –10.9 –2.7 5.1 –6.7 –.2 –2.1 5.3 9.0 6.5 4.9 11.8 –.9 10.3 5.7 1.3 .9 –1.3 3.1 3.2 –.9 –4.5 –2.2 10.2 3.5 –13.3 3.8 3.6 3.9 –4.6 .5 3.4 4.6 –11.4 3.3 –0.7 6.1 .5 4.4 8.1 5.2 10.0 –2.8 5.4 4.8 –1.4 4.1 9.1 3.0 6.4 –.4 9.2 10.9 15.7 5.3 7.0 5.0 .9 6.1 5.3 1.1 3.0 5.5 –1.1 –13.5 3.9 –5.6 2.9 –.1 9.3 9.6 5.4 7.4 –3.5 10.0 4.4 1.6 –.3 5.2 4.9 7.3 5.0 9.2 8.6 6.3 2.9 3.9 3.1 3.3 2.3 .0 2.1 2.2 .3 –5.7 –2.4 10.1 Percent change from year earlier –5.6 –8.8 –11.6 3.7 12.5 7.4 2.2 2.1 4.8 2.8 –.6 –7.3 2.3 2.8 5.6 1.1 5.4 2.4 3.3 5.4 3.2 –2.3 –3.5 .3 .0 –1.1 –3.0 –5.5 –6.6 –12.9 –3.2 –5.2 4.8 –7.3 7.9 9.5 3.2 –.1 7.4 7.0 1.2 –1.3 –1.5 3.3 4.0 6.6 4.1 3.2 6.0 5.0 5.4 6.4 –4.6 2.5 3.2 8.2 3.5 4.2 3.5 –5.8 –9.4 11.2 –5.3 2.8 –9.8 6.5 16.1 3.0 .7 7.0 9.9 1.6 –1.9 –3.2 2.1 4.2 7.7 7.7 6.1 8.3 9.9 7.7 11.2 –6.1 3.7 3.4 9.3 7.5 6.7 3.7 –1.6 –14.9 17.0 1 Consists of agriculture, forestry, fishing, and hunting; mining; construction; and manufacturing. 2 Consists of utilities; wholesale trade; retail trade; transportation and warehousing; information; finance, insurance, real estate, rental, and leasing; professional and business services; educational services, health care, and social assistance; arts, entertainment, recreation, accommodation, and food services; and other services, except government. See next page for continuation of table. 334 | Appendix B Table B–13. Real gross domestic product by industry, value added, and percent changes, 1980–2010—Continued Private industries—Continued Year Transportation and warehousing Information Finance, insurance, real estate, rental, and leasing Educational services, health care, and social assistance Professional and business services Arts, entertainment, recreation, accommodation, and food services Private goodsOther Government producing services, industries 1 except government Private servicesproducing industries 2 Chain-type quantity indexes for value added (2005=100) 1980 ������������� 1981 ������������� 1982 ������������� 1983 ������������� 1984 ������������� 1985 ������������� 1986 ������������� 1987 ������������� 1988 ������������� 1989 ������������� 1990 ������������� 1991 ������������� 1992 ������������� 1993 ������������� 1994 ������������� 1995 ������������� 1996 ������������� 1997 ������������� 1998 ������������� 1999 ������������� 2000 ������������� 2001 ������������� 2002 ������������� 2003 ������������� 2004 ������������� 2005 ������������� 2006 ������������� 2007 ������������� 2008 ������������� 2009 ������������� 2010 ������������� 41.818 40.790 38.832 43.831 45.938 46.619 46.696 48.989 50.432 52.397 55.147 57.664 61.325 64.042 69.180 71.236 75.138 79.006 78.063 80.801 86.201 83.090 81.948 86.133 93.911 100.000 104.049 105.231 106.182 93.455 96.695 30.378 32.049 31.956 34.198 33.874 34.821 34.983 37.356 38.579 41.288 42.649 43.057 45.429 47.837 50.285 52.034 55.321 56.402 62.107 70.528 67.832 72.885 80.958 82.501 92.679 100.000 101.530 109.310 111.156 107.166 110.347 48.277 48.938 49.393 50.583 52.452 53.847 54.648 56.560 58.607 60.088 61.497 62.438 64.388 66.268 67.851 69.615 71.251 74.419 76.667 81.686 87.064 92.351 92.155 93.538 94.519 100.000 104.035 105.125 104.357 105.553 105.311 34.690 35.550 35.428 37.922 42.010 45.365 48.917 51.538 54.138 57.635 60.141 58.046 59.787 61.282 63.418 65.656 70.179 75.051 79.327 82.819 86.923 89.035 89.688 92.228 95.440 100.000 103.229 106.140 110.288 102.660 106.587 1980 ������������� 1981 ������������� 1982 ������������� 1983 ������������� 1984 ������������� 1985 ������������� 1986 ������������� 1987 ������������� 1988 ������������� 1989 ������������� 1990 ������������� 1991 ������������� 1992 ������������� 1993 ������������� 1994 ������������� 1995 ������������� 1996 ������������� 1997 ������������� 1998 ������������� 1999 ������������� 2000 ������������� 2001 ������������� 2002 ������������� 2003 ������������� 2004 ������������� 2005 ������������� 2006 ������������� 2007 ������������� 2008 ������������� 2009 ������������� 2010 ������������� –2.3 –2.5 –4.8 12.9 4.8 1.5 .2 4.9 2.9 3.9 5.2 4.6 6.3 4.4 8.0 3.0 5.5 5.1 –1.2 3.5 6.7 –3.6 –1.4 5.1 9.0 6.5 4.0 1.1 .9 –12.0 3.5 8.4 5.5 –.3 7.0 –.9 2.8 .5 6.8 3.3 7.0 3.3 1.0 5.5 5.3 5.1 3.5 6.3 2.0 10.1 13.6 –3.8 7.5 11.1 1.9 12.3 7.9 1.5 7.7 1.7 –3.6 3.0 5.0 1.4 .9 2.4 3.7 2.7 1.5 3.5 3.6 2.5 2.3 1.5 3.1 2.9 2.4 2.6 2.4 4.4 3.0 6.5 6.6 6.1 –.2 1.5 1.0 5.8 4.0 1.0 –.7 1.1 –.2 2.6 2.5 –.3 7.0 10.8 8.0 7.8 5.4 5.0 6.5 4.3 –3.5 3.0 2.5 3.5 3.5 6.9 6.9 5.7 4.4 5.0 2.4 .7 2.8 3.5 4.8 3.2 2.8 3.9 –6.9 3.8 56.112 57.200 57.034 59.229 60.919 62.423 63.597 67.638 68.238 70.866 73.463 75.173 77.453 77.728 78.052 79.293 80.204 81.559 82.657 84.776 86.688 88.822 92.487 95.460 98.332 100.000 103.265 104.978 109.833 110.915 114.020 44.619 46.189 47.380 51.042 53.218 55.848 59.483 59.082 62.454 64.701 66.671 64.814 67.092 69.166 71.235 73.630 76.742 80.225 82.504 87.572 91.104 89.691 91.313 93.634 97.751 100.000 102.563 105.614 100.271 92.642 99.866 75.952 73.651 70.878 74.147 78.074 80.627 82.446 83.865 87.958 91.973 93.971 91.234 93.331 96.564 101.126 103.010 103.940 102.674 108.399 109.304 110.957 99.325 102.420 100.428 100.685 100.000 101.704 101.659 97.388 92.399 94.327 74.868 75.162 75.297 75.976 76.794 78.818 80.650 82.216 84.340 86.397 88.511 88.991 89.513 89.512 89.780 89.719 90.120 91.101 92.284 93.395 95.142 95.941 97.802 98.749 99.445 100.000 100.437 101.209 103.008 103.940 104.525 50.611 52.361 48.901 50.241 55.880 58.708 58.664 62.184 65.702 66.909 66.431 64.989 67.163 68.816 73.841 75.400 78.077 82.210 85.786 89.880 94.368 91.430 92.368 94.040 99.161 100.000 102.528 103.194 97.973 91.739 96.834 42.038 42.951 42.869 45.236 47.804 49.789 51.881 53.341 55.673 58.155 59.704 60.060 62.511 64.309 66.769 68.566 71.717 75.282 79.023 83.304 87.019 89.318 90.987 93.288 96.307 100.000 103.112 105.471 105.673 101.586 104.683 0.9 –3.0 –3.8 4.6 5.3 3.3 2.3 1.7 4.9 4.6 2.2 –2.9 2.3 3.5 4.7 1.9 .9 –1.2 5.6 .8 1.5 –10.5 3.1 –1.9 .3 –.7 1.7 .0 –4.2 –5.1 2.1 1.7 .4 .2 .9 1.1 2.6 2.3 1.9 2.6 2.4 2.4 .5 .6 .0 .3 –.1 .4 1.1 1.3 1.2 1.9 .8 1.9 1.0 .7 .6 .4 .8 1.8 .9 .6 –3.6 3.5 –6.6 2.7 11.2 5.1 –.1 6.0 5.7 1.8 –.7 –2.2 3.3 2.5 7.3 2.1 3.6 5.3 4.3 4.8 5.0 –3.1 1.0 1.8 5.4 .8 2.5 .6 –5.1 –6.4 5.6 1.1 2.2 –.2 5.5 5.7 4.2 4.2 2.8 4.4 4.5 2.7 .6 4.1 2.9 3.8 2.7 4.6 5.0 5.0 5.4 4.5 2.6 1.9 2.5 3.2 3.8 3.1 2.3 .2 –3.9 3.0 Percent change from year earlier 3.6 1.9 –.3 3.8 2.9 2.5 1.9 6.4 .9 3.9 3.7 2.3 3.0 .4 .4 1.6 1.1 1.7 1.3 2.6 2.3 2.5 4.1 3.2 3.0 1.7 3.3 1.7 4.6 1.0 2.8 –3.6 3.5 2.6 7.7 4.3 4.9 6.5 –.7 5.7 3.6 3.0 –2.8 3.5 3.1 3.0 3.4 4.2 4.5 2.8 6.1 4.0 –1.6 1.8 2.5 4.4 2.3 2.6 3.0 –5.1 –7.6 7.8 Note: Data are based on the 2002 North American Industry Classification System (NAICS). See Note, Table B–12. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 335 Table B–14. Gross value added of nonfinancial corporate business, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Net value added Year or quarter Gross value Conadded sumpof nonfinancial tion of corpofixed rate capital business 1 1963 ������������� 329.9 1964 ������������� 356.1 1965 ������������� 391.2 1966 ������������� 429.0 1967 ������������� 451.2 1968 ������������� 497.8 1969 ������������� 540.5 1970 ������������� 558.3 1971 ������������� 603.0 1972 ������������� 669.4 1973 ������������� 750.8 1974 ������������� 809.8 1975 ������������� 876.7 1976 ������������� 989.7 1977 ������������� 1,119.4 1978 ������������� 1,272.7 1979 ������������� 1,414.4 1980 ������������� 1,534.5 1981 ������������� 1,742.2 1982 ������������� 1,802.6 1983 ������������� 1,929.1 1984 ������������� 2,161.4 1985 ������������� 2,293.9 1986 ������������� 2,383.2 1987 ������������� 2,551.0 1988 ������������� 2,765.4 1989 ������������� 2,899.2 1990 ������������� 3,035.2 1991 ������������� 3,104.1 1992 ������������� 3,241.1 1993 ������������� 3,398.4 1994 ������������� 3,677.6 1995 ������������� 3,888.0 1996 ������������� 4,119.4 1997 ������������� 4,412.5 1998 ������������� 4,668.3 1999 ������������� 4,955.5 2000 ������������� 5,279.4 2001 ������������� 5,252.5 2002 ������������� 5,307.7 2003 ������������� 5,503.7 2004 ������������� 5,877.5 2005 ������������� 6,302.8 2006 ������������� 6,740.3 2007 ������������� 6,946.0 2008 ������������� 6,991.4 2009 ������������� 6,592.0 2010 ������������ 6,902.0 2011 p ����������� ������������� 2008: I ��������� 6,955.8 II �������� 6,964.7 III ������� 7,094.8 IV ������� 6,950.5 2009: I ��������� 6,650.3 II �������� 6,534.6 III ������� 6,533.4 IV ������� 6,649.7 2010: I ��������� 6,811.1 II �������� 6,876.6 III ������� 6,953.9 IV ������� 6,966.5 2011: I ��������� 7,078.3 II �������� 7,216.5 III ������� 7,269.9 IV p ���� ������������� 25.6 27.0 29.1 31.9 35.2 38.7 42.9 47.5 52.0 56.5 63.1 74.2 88.6 97.8 110.1 125.1 144.3 166.7 192.4 212.8 219.3 228.8 244.0 258.0 270.0 287.3 303.9 321.0 336.1 344.1 359.0 380.1 408.3 435.1 466.9 499.9 539.3 590.1 632.0 654.5 669.0 695.6 743.0 800.9 840.1 864.3 862.2 856.8 890.1 852.2 858.8 869.6 876.6 874.2 864.5 856.4 853.8 850.3 853.9 857.7 865.4 873.4 885.4 896.3 905.5 Addenda Net operating surplus Total 304.3 329.0 362.1 397.1 416.0 459.1 497.5 510.8 551.1 613.0 687.6 735.7 788.0 892.0 1,009.2 1,147.5 1,270.2 1,367.8 1,549.8 1,589.8 1,709.8 1,932.6 2,049.9 2,125.2 2,280.9 2,478.1 2,595.3 2,714.2 2,768.0 2,897.0 3,039.3 3,297.5 3,479.7 3,684.4 3,945.6 4,168.5 4,416.3 4,689.4 4,620.5 4,653.1 4,834.7 5,181.9 5,559.8 5,939.4 6,106.0 6,127.1 5,729.8 6,045.2 ������������� 6,103.6 6,105.9 6,225.2 6,073.8 5,776.1 5,670.1 5,677.0 5,796.0 5,960.7 6,022.6 6,096.2 6,101.1 6,205.0 6,331.1 6,373.6 ������������� Taxes Comon pensa- production tion and of imports employ- less ees subsidies 210.1 225.7 245.4 272.9 291.1 321.9 357.1 376.5 399.4 443.9 502.2 552.2 575.5 651.4 735.3 845.1 958.4 1,047.2 1,157.6 1,200.4 1,263.1 1,400.0 1,496.1 1,575.4 1,678.4 1,804.7 1,905.7 2,005.5 2,044.8 2,152.9 2,244.0 2,382.1 2,511.5 2,631.3 2,814.6 3,049.7 3,256.5 3,541.8 3,559.4 3,544.2 3,651.3 3,786.7 3,976.3 4,182.3 4,361.0 4,441.2 4,178.2 4,263.0 4,440.7 4,456.3 4,450.2 4,445.9 4,412.3 4,210.8 4,178.9 4,156.0 4,167.0 4,188.9 4,247.5 4,299.8 4,315.9 4,386.5 4,426.3 4,450.5 4,499.7 31.7 33.9 36.0 37.0 39.3 45.5 50.2 54.2 59.5 63.7 70.1 74.4 80.2 86.7 94.6 102.7 108.8 121.5 146.7 152.9 168.0 185.0 196.6 204.6 216.8 233.8 248.2 263.5 285.7 302.5 318.0 347.8 354.2 365.6 381.0 393.1 414.6 439.4 434.5 461.9 484.2 517.7 558.4 593.3 607.7 615.2 587.4 614.3 639.8 613.4 620.5 619.9 606.9 584.5 586.5 581.6 597.1 607.3 612.3 617.1 620.7 633.2 641.2 640.9 644.0 Total Net interest Business and current miscel- transfer laneous paypayments ments 62.5 4.7 69.5 5.2 80.7 5.8 87.2 7.0 85.6 8.4 91.7 9.7 90.3 12.7 80.1 16.6 92.1 17.6 105.4 18.6 115.4 21.8 109.1 27.5 132.4 28.4 153.9 26.0 179.3 28.5 199.7 33.4 203.0 41.8 199.1 54.2 245.5 67.2 236.5 77.4 278.7 77.0 347.5 86.0 357.2 91.5 345.2 98.5 385.6 95.9 439.6 107.9 441.5 133.9 445.2 143.1 437.5 139.6 441.6 114.2 477.3 99.8 567.5 98.8 614.0 112.7 687.5 112.1 750.0 124.7 725.7 146.8 745.1 164.5 708.2 192.8 626.7 197.7 647.1 163.7 699.2 147.9 877.5 134.4 1,025.1 148.2 1,163.7 164.0 1,137.4 232.3 1,070.8 257.7 964.2 243.7 1,167.8 130.9 ������������ ������������� 1,033.9 251.5 1,035.2 248.7 1,159.4 254.5 1,054.6 275.9 980.7 286.2 904.7 255.2 939.4 228.3 1,031.8 205.2 1,164.5 166.7 1,162.8 135.5 1,179.4 114.9 1,164.6 106.5 1,185.3 106.6 1,263.6 103.0 1,282.1 104.5 ������������ ������������� 1.7 2.0 2.2 2.7 2.8 3.1 3.2 3.3 3.7 4.0 4.7 4.1 5.0 7.0 9.0 9.5 9.5 10.2 11.4 8.8 10.5 11.7 16.1 27.3 29.9 27.4 24.0 25.4 26.6 31.3 30.1 35.3 30.7 38.0 39.2 35.2 47.1 47.9 58.9 56.3 65.2 65.5 79.3 75.8 69.1 58.1 78.3 85.4 87.1 57.9 54.6 54.1 65.7 74.6 83.4 75.8 79.4 84.5 84.8 86.7 85.5 86.3 87.5 86.7 87.9 Corporate profits with inventory valuation and capital consumption adjustments Total Taxes on corporate income Profits after tax 2 Profits before tax Inven- Capital tory convalua- sumption tion adjustadjustment ment 56.1 22.8 33.4 49.7 0.1 62.4 23.9 38.5 55.9 –.5 72.7 27.1 45.5 66.1 –1.2 77.5 29.5 48.0 71.4 –2.1 74.4 27.8 46.5 67.6 –1.6 78.9 33.5 45.4 74.0 –3.7 74.4 33.3 41.0 71.2 –5.9 60.2 27.3 32.9 58.5 –6.6 70.8 30.0 40.8 67.4 –4.6 82.8 33.8 49.0 79.5 –6.6 88.9 40.4 48.5 99.5 –19.6 77.5 42.8 34.6 110.2 –38.2 98.9 41.9 57.0 110.7 –10.5 121.0 53.5 67.5 138.2 –14.1 141.9 60.6 81.3 159.5 –15.7 156.8 67.6 89.2 183.7 –23.7 151.8 70.6 81.2 197.2 –40.1 134.7 68.2 66.5 184.1 –42.1 166.8 66.0 100.8 185.0 –24.6 150.2 48.8 101.5 140.0 –7.5 191.2 61.7 129.5 163.4 –7.4 249.8 75.9 173.9 197.6 –4.0 249.6 71.1 178.6 173.5 .0 219.5 76.2 143.2 149.7 7.1 259.9 94.2 165.7 213.5 –16.2 304.3 104.0 200.3 264.1 –22.2 283.5 101.2 182.3 243.1 –16.3 276.7 98.5 178.3 243.3 –12.9 271.3 88.6 182.7 226.8 4.9 296.1 94.4 201.7 258.6 –2.8 347.5 108.0 239.5 308.7 –4.0 433.5 132.4 301.1 391.9 –12.4 470.6 140.3 330.3 431.2 –18.3 537.4 152.9 384.5 471.3 3.1 586.2 161.4 424.8 506.8 14.1 543.7 158.7 385.1 460.5 15.7 533.5 171.4 362.1 468.6 –4.0 467.5 170.2 297.3 432.5 –16.8 370.1 111.2 258.8 315.1 8.0 427.2 97.1 330.1 342.3 –2.6 486.1 132.9 353.2 425.9 –11.3 677.5 187.0 490.6 662.1 –34.3 797.6 271.9 525.8 957.1 –30.7 923.9 307.6 616.2 1,117.9 –38.0 835.9 293.8 542.2 1,042.0 –47.2 755.0 227.4 527.7 831.2 –44.5 642.1 175.0 467.1 693.5 .6 951.5 229.3 722.3 942.8 –39.1 ������������� ������������� ������������ ������������� ������������� 724.5 248.0 476.5 884.8 –131.3 731.8 252.8 479.1 916.5 –155.4 850.9 255.3 595.5 957.1 –72.7 713.0 153.5 559.5 566.2 181.6 619.9 164.6 455.4 607.9 76.5 566.1 156.7 409.4 604.2 15.9 635.2 169.8 465.4 701.9 –20.7 747.2 209.0 538.2 859.9 –69.3 913.3 233.4 680.0 976.6 –28.4 942.5 232.0 710.5 984.3 –5.6 977.8 239.4 738.3 961.5 –32.0 972.6 212.4 760.2 848.9 –90.3 992.3 238.5 753.8 974.8 –116.0 1,073.1 252.2 821.0 1,006.3 –60.4 1,091.0 250.1 840.9 1,013.4 –45.5 ������������� ������������� ������������ ������������� ������������� 6.4 7.0 7.8 8.1 8.3 8.6 9.1 8.3 8.0 9.9 9.0 5.5 –1.2 –3.2 –1.9 –3.2 –5.3 –7.2 6.5 17.8 35.2 56.2 76.2 62.7 62.6 62.3 56.7 46.3 39.6 40.3 42.9 54.0 57.6 63.0 65.3 67.5 68.9 51.8 47.0 87.5 71.5 49.7 –128.8 –156.0 –158.8 –31.7 –52.0 47.8 126.3 –29.1 –29.3 –33.5 –34.8 –64.4 –54.0 –46.0 –43.4 –34.9 –36.2 48.3 214.1 133.6 127.2 123.1 121.4 1 Estimates for nonfinancial corporate business for 2000 and earlier periods are based on the Standard Industrial Classification (SIC); later estimates are based on the North American Industry Classification System (NAICS). 2 With inventory valuation and capital consumption adjustments. Source: Department of Commerce (Bureau of Economic Analysis). 336 | Appendix B Table B–15. Gross value added and price, costs, and profits of nonfinancial corporate business, 1963–2011 [Quarterly data at seasonally adjusted annual rates] Price per unit of real gross value added of nonfinancial corporate business (dollars) 1, 2 Gross value added of nonfinancial corporate business (billions of dollars) 1 Year or quarter Current dollars 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� 329.9 356.1 391.2 429.0 451.2 497.8 540.5 558.3 603.0 669.4 750.8 809.8 876.7 989.7 1,119.4 1,272.7 1,414.4 1,534.5 1,742.2 1,802.6 1,929.1 2,161.4 2,293.9 2,383.2 2,551.0 2,765.4 2,899.2 3,035.2 3,104.1 3,241.1 3,398.4 3,677.6 3,888.0 4,119.4 4,412.5 4,668.3 4,955.5 5,279.4 5,252.5 5,307.7 5,503.7 5,877.5 6,302.8 6,740.3 6,946.0 6,991.4 6,592.0 6,902.0 6,955.8 6,964.7 7,094.8 6,950.5 6,650.3 6,534.6 6,533.4 6,649.7 6,811.1 6,876.6 6,953.9 6,966.5 7,078.3 7,216.5 7,269.9 Chained (2005) dollars 1,277.9 1,368.1 1,481.8 1,588.1 1,630.9 1,736.7 1,806.9 1,792.4 1,866.3 2,009.0 2,132.7 2,099.0 2,068.2 2,237.2 2,402.9 2,560.2 2,640.4 2,613.4 2,717.8 2,653.0 2,781.1 3,027.7 3,157.9 3,235.5 3,402.5 3,599.1 3,658.8 3,713.1 3,695.4 3,804.9 3,905.0 4,155.3 4,349.0 4,588.6 4,887.8 5,167.3 5,452.4 5,745.7 5,637.8 5,675.5 5,818.1 6,085.1 6,302.8 6,543.2 6,606.4 6,515.9 6,036.5 6,329.5 6,557.3 6,538.7 6,585.9 6,381.8 6,035.2 5,966.1 6,006.1 6,138.4 6,288.7 6,329.3 6,361.5 6,338.4 6,407.9 6,504.1 6,491.6 Total 0.258 .260 .264 .270 .277 .287 .299 .311 .323 .333 .352 .386 .424 .442 .466 .497 .536 .587 .641 .679 .694 .714 .726 .737 .750 .768 .792 .817 .840 .852 .870 .885 .894 .898 .903 .903 .909 .919 .932 .935 .946 .966 1.000 1.030 1.051 1.073 1.092 1.090 1.061 1.065 1.077 1.089 1.102 1.095 1.088 1.083 1.083 1.086 1.093 1.099 1.105 1.110 1.120 Compensation of employees (unit labor cost) 0.164 .165 .166 .172 .178 .185 .198 .210 .214 .221 .235 .263 .278 .291 .306 .330 .363 .401 .426 .452 .454 .462 .474 .487 .493 .501 .521 .540 .553 .566 .575 .573 .577 .573 .576 .590 .597 .616 .631 .624 .628 .622 .631 .639 .660 .682 .692 .674 .680 .681 .675 .691 .698 .700 .692 .679 .666 .671 .676 .681 .685 .681 .686 Corporate profits with inventory valuation and capital consumption adjustments 4 Unit nonlabor cost Total 0.050 .050 .050 .049 .053 .056 .061 .067 .071 .071 .075 .085 .098 .098 .101 .106 .116 .135 .154 .170 .171 .169 .173 .182 .180 .183 .194 .203 .214 .208 .207 .207 .209 .207 .208 .208 .214 .222 .235 .235 .234 .232 .243 .249 .264 .276 .293 .267 .270 .272 .273 .285 .301 .300 .290 .282 .272 .266 .264 .265 .265 .264 .266 ConinterTaxes on Net sumption production est and of misceland fixed laneous imports 3 payments capital 0.020 .020 .020 .020 .022 .022 .024 .026 .028 .028 .030 .035 .043 .044 .046 .049 .055 .064 .071 .080 .079 .076 .077 .080 .079 .080 .083 .086 .091 .090 .092 .091 .094 .095 .096 .097 .099 .103 .112 .115 .115 .114 .118 .122 .127 .133 .143 .135 .130 .131 .132 .137 .145 .145 .143 .139 .135 .135 .135 .137 .136 .136 .138 0.026 .026 .026 .025 .026 .028 .030 .032 .034 .034 .035 .037 .041 .042 .043 .044 .045 .050 .058 .061 .064 .065 .067 .072 .073 .073 .074 .078 .085 .088 .089 .092 .089 .088 .086 .083 .085 .085 .088 .091 .094 .096 .101 .102 .102 .103 .110 .111 .102 .103 .102 .105 .109 .112 .109 .110 .110 .110 .111 .111 .112 .112 .112 0.004 .004 .004 .004 .005 .006 .007 .009 .009 .009 .010 .013 .014 .012 .012 .013 .016 .021 .025 .029 .028 .028 .029 .030 .028 .030 .037 .039 .038 .030 .026 .024 .026 .024 .026 .028 .030 .034 .035 .029 .025 .022 .024 .025 .035 .040 .040 .021 .038 .038 .039 .043 .047 .043 .038 .033 .027 .021 .018 .017 .017 .016 .016 Total 0.044 .046 .049 .049 .046 .045 .041 .034 .038 .041 .042 .037 .048 .054 .059 .061 .057 .052 .061 .057 .069 .083 .079 .068 .076 .085 .077 .075 .073 .078 .089 .104 .108 .117 .120 .105 .098 .081 .066 .075 .084 .111 .127 .141 .127 .116 .106 .150 .110 .112 .129 .112 .103 .095 .106 .122 .145 .149 .154 .153 .155 .165 .168 Taxes on corporate income 0.018 .017 .018 .019 .017 .019 .018 .015 .016 .017 .019 .020 .020 .024 .025 .026 .027 .026 .024 .018 .022 .025 .023 .024 .028 .029 .028 .027 .024 .025 .028 .032 .032 .033 .033 .031 .031 .030 .020 .017 .023 .031 .043 .047 .044 .035 .029 .036 .038 .039 .039 .024 .027 .026 .028 .034 .037 .037 .038 .034 .037 .039 .039 Profits after tax 5 0.026 .028 .031 .030 .029 .026 .023 .018 .022 .024 .023 .016 .028 .030 .034 .035 .031 .025 .037 .038 .047 .057 .057 .044 .049 .056 .050 .048 .049 .053 .061 .072 .076 .084 .087 .075 .066 .052 .046 .058 .061 .081 .083 .094 .082 .081 .077 .114 .073 .073 .090 .088 .075 .069 .077 .088 .108 .112 .116 .120 .118 .126 .130 1 Estimates for nonfinancial corporate business for 2000 and earlier periods are based on the Standard Industrial Classification (SIC); later estimates are based on the North American Industry Classification System (NAICS). 2 The implicit price deflator for gross value added of nonfinancial corporate business divided by 100. 3 Less subsidies plus business current transfer payments. 4 Unit profits from current production. 5 With inventory valuation and capital consumption adjustments. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 337 Table B–16. Personal consumption expenditures, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Goods Durable Personal consumption expenditures Year or quarter 1963 �������������� 1964 �������������� 1965 �������������� 1966 �������������� 1967 �������������� 1968 �������������� 1969 �������������� 1970 �������������� 1971 �������������� 1972 �������������� 1973 �������������� 1974 �������������� 1975 �������������� 1976 �������������� 1977 �������������� 1978 �������������� 1979 �������������� 1980 �������������� 1981 �������������� 1982 �������������� 1983 �������������� 1984 �������������� 1985 �������������� 1986 �������������� 1987 �������������� 1988 �������������� 1989 �������������� 1990 �������������� 1991 �������������� 1992 �������������� 1993 �������������� 1994 �������������� 1995 �������������� 1996 �������������� 1997 �������������� 1998 �������������� 1999 �������������� 2000 �������������� 2001 �������������� 2002 �������������� 2003 �������������� 2004 �������������� 2005 �������������� 2006 �������������� 2007 �������������� 2008 �������������� 2009 �������������� 2010 �������������� 2011 p ������������ 2008: I ���������� II ��������� III �������� IV �������� 2009: I ���������� II ��������� III �������� IV �������� 2010: I ���������� II ��������� III �������� IV �������� 2011: I ���������� II ��������� III �������� IV p ����� 382.7 411.5 443.8 480.9 507.8 558.0 605.1 648.3 701.6 770.2 852.0 932.9 1,033.8 1,151.3 1,277.8 1,427.6 1,591.2 1,755.8 1,939.5 2,075.5 2,288.6 2,501.1 2,717.6 2,896.7 3,097.0 3,350.1 3,594.5 3,835.5 3,980.1 4,236.9 4,483.6 4,750.8 4,987.3 5,273.6 5,570.6 5,918.5 6,342.8 6,830.4 7,148.8 7,439.2 7,804.1 8,270.6 8,803.5 9,301.0 9,772.3 10,035.5 9,866.1 10,245.5 10,722.6 10,018.5 10,126.5 10,135.8 9,861.3 9,781.7 9,781.6 9,911.1 9,990.0 10,103.7 10,184.8 10,276.6 10,417.1 10,571.7 10,676.0 10,784.5 10,858.1 Total Total 1 198.2 212.3 229.7 249.6 259.0 284.6 304.7 318.8 342.1 373.8 416.6 451.5 491.3 546.3 600.4 663.6 737.9 799.8 869.4 899.3 973.8 1,063.7 1,137.6 1,195.6 1,256.3 1,337.3 1,423.8 1,491.3 1,497.4 1,563.3 1,642.3 1,746.6 1,815.5 1,917.7 2,006.8 2,110.0 2,290.0 2,459.1 2,534.0 2,610.0 2,728.0 2,892.1 3,076.7 3,224.7 3,363.9 3,381.7 3,197.5 3,387.0 3,645.2 3,422.3 3,466.9 3,456.1 3,181.4 3,130.7 3,143.6 3,245.6 3,270.0 3,338.1 3,340.1 3,386.5 3,483.4 3,592.2 3,622.7 3,661.2 3,704.5 54.2 59.6 66.4 71.7 74.0 84.8 90.5 90.0 102.4 116.4 130.5 130.2 142.2 168.6 192.0 213.3 226.3 226.4 243.9 253.0 295.0 342.2 380.4 421.4 442.0 475.1 494.3 497.1 477.2 508.1 551.5 607.2 635.7 676.3 715.5 780.0 857.4 915.8 946.3 992.1 1,019.9 1,072.9 1,123.4 1,155.0 1,188.4 1,108.9 1,029.6 1,085.5 1,161.9 1,163.0 1,146.6 1,106.6 1,019.3 1,020.1 1,009.5 1,050.1 1,038.8 1,058.0 1,071.7 1,087.5 1,124.7 1,154.5 1,143.8 1,158.3 1,190.9 Services Household consumption expenditures Nondurable Motor vehicles and parts 24.2 25.8 29.6 29.9 29.6 35.4 37.4 34.5 43.2 49.4 54.4 48.2 52.6 68.2 79.8 89.2 90.2 84.4 93.0 100.0 122.9 147.2 170.1 187.5 188.2 202.2 207.8 205.1 185.7 204.8 224.7 249.8 255.7 273.5 293.1 320.2 350.7 363.2 383.3 401.3 401.0 403.9 408.2 394.8 399.9 339.3 316.5 340.1 378.3 378.9 354.1 332.6 291.5 303.0 303.5 339.2 320.5 323.1 330.6 339.6 367.1 383.0 363.4 368.7 397.9 Total 1 143.9 152.7 163.3 177.9 185.0 199.8 214.2 228.8 239.7 257.4 286.1 321.4 349.2 377.7 408.4 450.2 511.6 573.4 625.4 646.3 678.8 721.5 757.2 774.2 814.3 862.3 929.5 994.2 1,020.3 1,055.2 1,090.8 1,139.4 1,179.8 1,241.4 1,291.2 1,330.0 1,432.6 1,543.4 1,587.7 1,617.9 1,708.1 1,819.3 1,953.4 2,069.8 2,175.5 2,272.8 2,167.8 2,301.5 2,483.3 2,259.4 2,320.3 2,349.4 2,162.2 2,110.6 2,134.1 2,195.5 2,231.1 2,280.1 2,268.3 2,299.0 2,358.7 2,437.8 2,478.9 2,503.0 2,513.6 Food and beverages Gasoline purand chased other for offenergy premises goods consumption 65.9 69.5 74.4 80.6 82.6 88.8 95.4 103.5 107.1 114.5 126.7 143.0 156.6 167.3 179.8 196.1 218.4 239.2 255.3 267.1 277.0 291.1 303.0 316.4 324.3 342.8 365.4 391.2 403.0 404.5 413.5 432.1 443.7 461.9 474.8 486.5 513.6 537.5 559.7 569.6 587.5 613.0 644.5 674.2 711.2 746.4 746.0 766.4 809.0 732.5 749.2 757.1 746.7 741.3 743.8 746.4 752.6 761.5 759.4 766.4 778.2 792.0 806.7 815.8 821.5 16.9 17.7 19.1 20.7 21.9 23.2 25.0 26.3 27.6 29.4 34.3 43.8 48.0 53.0 57.8 61.5 80.4 101.9 113.4 108.4 106.5 108.2 110.5 91.2 96.4 99.9 110.4 124.2 121.1 125.0 126.9 129.2 133.4 144.7 147.7 133.4 148.8 188.8 183.6 174.6 209.5 249.4 303.8 335.2 364.8 410.5 299.4 354.1 427.4 418.3 444.0 466.9 312.6 261.4 275.5 321.5 339.3 359.5 337.0 345.9 374.1 420.2 431.5 434.5 423.5 Total Total 1 184.6 199.2 214.1 231.3 248.8 273.4 300.4 329.5 359.5 396.4 435.4 481.4 542.5 604.9 677.4 764.1 853.2 956.0 1,070.1 1,176.2 1,314.8 1,437.4 1,580.0 1,701.1 1,840.7 2,012.7 2,170.7 2,344.2 2,482.6 2,673.6 2,841.2 3,004.3 3,171.7 3,355.9 3,563.9 3,808.5 4,052.8 4,371.2 4,614.8 4,829.2 5,076.1 5,378.5 5,726.8 6,076.3 6,408.3 6,653.8 6,668.7 6,858.5 7,077.4 6,596.2 6,659.6 6,679.7 6,679.9 6,651.0 6,638.0 6,665.5 6,720.1 6,765.6 6,844.7 6,890.1 6,933.7 6,979.4 7,053.3 7,123.2 7,153.6 178.6 192.5 206.9 223.5 240.4 264.0 290.4 318.4 347.2 382.8 420.7 465.0 524.4 584.9 655.6 739.6 825.4 924.1 1,033.9 1,136.1 1,271.9 1,389.8 1,529.7 1,645.8 1,782.1 1,946.0 2,099.0 2,264.5 2,398.4 2,581.3 2,746.6 2,901.9 3,064.6 3,240.2 3,451.6 3,677.5 3,907.4 4,205.9 4,428.6 4,624.2 4,864.8 5,169.1 5,515.1 5,836.3 6,154.4 6,369.3 6,388.4 6,578.3 6,791.9 6,325.0 6,377.8 6,389.2 6,385.1 6,366.9 6,361.3 6,386.7 6,438.7 6,484.0 6,562.3 6,610.9 6,656.0 6,700.0 6,771.6 6,834.4 6,861.5 Housing and utilities 68.2 72.1 76.6 81.2 86.3 92.7 101.0 109.4 120.0 131.2 143.5 158.6 176.5 194.7 217.8 244.3 273.4 311.8 352.0 387.0 421.2 458.3 500.7 535.7 571.8 614.5 655.6 696.4 735.5 771.2 814.5 866.5 913.8 961.2 1,009.9 1,065.2 1,125.0 1,198.6 1,287.7 1,334.8 1,393.9 1,462.4 1,582.6 1,686.2 1,756.2 1,831.0 1,871.6 1,893.2 1,921.2 1,802.0 1,825.2 1,838.6 1,858.4 1,867.2 1,866.7 1,872.1 1,880.3 1,883.6 1,887.1 1,900.8 1,901.1 1,901.7 1,913.3 1,937.7 1,932.0 Health care 21.0 24.2 26.0 28.7 31.9 36.6 42.1 47.7 53.7 59.8 67.2 76.1 89.0 101.8 115.7 131.2 148.8 171.7 201.9 225.2 253.1 276.5 302.2 330.2 366.0 410.1 451.2 506.2 555.8 612.8 648.8 680.5 719.9 752.1 790.9 832.0 863.6 918.4 996.6 1,082.9 1,148.2 1,228.5 1,308.9 1,373.7 1,457.7 1,532.6 1,604.2 1,667.4 1,728.8 1,513.0 1,526.5 1,539.0 1,552.0 1,571.8 1,596.2 1,615.4 1,633.5 1,632.9 1,659.1 1,677.1 1,700.4 1,708.1 1,729.5 1,734.4 1,743.2 Addendum: Personal consumption expendiFinancial tures services excludand ing insurfood ance and energy 2 15.9 17.7 19.4 21.3 22.8 25.8 28.5 31.1 34.1 38.3 41.5 45.9 54.0 59.3 67.8 80.6 87.6 95.6 102.0 116.3 145.9 156.6 180.5 196.7 207.1 219.4 235.7 253.2 282.0 311.8 341.0 349.0 364.7 393.6 431.3 469.6 514.2 570.0 562.8 576.2 602.5 651.7 698.4 732.6 790.3 807.0 747.8 780.2 804.6 817.0 819.7 807.7 783.6 753.8 744.3 741.9 751.2 770.5 788.6 779.2 782.7 795.7 803.1 811.9 807.6 1 Includes other items not shown separately. 2 Food consists of food and beverages purchased for off-premises consumption; food services, which include purchased meals and beverages, are not classified as food. Source: Department of Commerce (Bureau of Economic Analysis). 338 | Appendix B 290.0 313.8 339.3 368.1 391.1 432.9 470.8 503.3 550.1 607.9 670.9 722.4 800.6 898.3 1,002.5 1,127.8 1,245.4 1,358.3 1,507.1 1,627.2 1,824.2 2,016.9 2,215.1 2,401.8 2,587.3 2,813.2 3,019.8 3,221.3 3,351.1 3,601.1 3,828.2 4,072.3 4,291.9 4,542.0 4,821.6 5,173.5 5,554.6 5,966.4 6,255.9 6,549.4 6,846.7 7,240.0 7,665.3 8,090.7 8,485.9 8,655.0 8,605.3 8,901.3 9,263.2 8,649.7 8,707.0 8,688.2 8,574.9 8,556.7 8,550.9 8,632.2 8,681.3 8,763.5 8,868.2 8,934.2 9,039.3 9,141.4 9,215.2 9,299.8 9,396.5 Table B–17. Real personal consumption expenditures, 1995–2011 [Billions of chained (2005) dollars; quarterly data at seasonally adjusted annual rates] Goods Durable Year or quarter 1995 �������������� 1996 �������������� 1997 �������������� 1998 �������������� 1999 �������������� 2000 �������������� 2001 �������������� 2002 �������������� 2003 �������������� 2004 �������������� 2005 �������������� 2006 �������������� 2007 �������������� 2008 �������������� 2009 �������������� 2010 �������������� 2011 p ������������ 2008: I ���������� II ��������� III �������� IV �������� 2009: I ���������� II ��������� III �������� IV �������� 2010: I ���������� II ��������� III �������� IV �������� 2011: I ���������� II ��������� III �������� IV p ����� Personal consumption expenditures 6,076.2 6,288.3 6,520.4 6,862.3 7,237.6 7,604.6 7,810.3 8,018.3 8,244.5 8,515.8 8,803.5 9,054.5 9,262.9 9,211.7 9,037.5 9,220.9 9,421.1 9,289.1 9,285.8 9,196.0 9,076.0 9,040.9 8,998.5 9,050.3 9,060.2 9,121.2 9,186.9 9,247.1 9,328.4 9,376.7 9,392.7 9,433.5 9,481.3 Total Total 1 1,896.0 1,980.9 2,075.3 2,215.5 2,392.0 2,518.2 2,597.3 2,702.9 2,827.2 2,953.3 3,076.7 3,178.9 3,273.5 3,192.9 3,098.0 3,230.7 3,351.9 3,249.0 3,252.7 3,187.9 3,082.0 3,082.6 3,064.3 3,120.7 3,124.6 3,173.3 3,202.9 3,240.8 3,306.0 3,344.4 3,331.2 3,342.7 3,389.2 510.5 548.6 593.3 665.6 752.0 818.0 862.4 927.9 989.1 1,060.9 1,123.4 1,174.2 1,232.4 1,171.8 1,108.3 1,188.3 1,284.5 1,218.7 1,209.8 1,170.8 1,088.0 1,094.6 1,083.4 1,134.5 1,120.8 1,147.5 1,169.3 1,194.1 1,242.4 1,277.4 1,260.2 1,277.8 1,322.7 Services Household consumption expenditures Nondurable Motor vehicles and parts 255.6 268.0 286.1 316.0 345.1 356.1 374.3 394.0 404.8 410.4 408.2 394.4 401.4 346.8 322.5 330.1 356.5 381.9 360.7 340.8 303.8 316.2 312.4 344.5 316.7 315.9 321.4 328.0 354.9 368.2 342.1 343.5 372.1 Total 1 1,437.7 1,479.2 1,522.7 1,580.2 1,660.7 1,714.5 1,745.4 1,780.1 1,840.7 1,892.8 1,953.4 2,005.0 2,042.9 2,019.1 1,983.4 2,041.3 2,077.0 2,032.1 2,043.5 2,015.4 1,985.3 1,980.3 1,972.8 1,982.7 1,997.7 2,021.1 2,030.8 2,045.8 2,067.4 2,075.4 2,076.6 2,073.7 2,082.2 Food and beverages Gasoline purand chased other for offenergy premises goods consumption 548.4 553.9 558.8 565.5 587.3 600.5 607.5 608.9 616.5 623.9 644.5 663.0 673.2 666.0 657.3 673.1 683.6 672.9 674.5 666.5 650.2 647.0 654.8 660.8 666.8 671.6 667.2 672.8 680.8 682.1 684.1 683.9 684.1 264.3 268.5 273.9 283.7 292.4 287.1 289.2 294.0 301.9 305.9 303.8 296.9 294.4 280.6 281.1 281.3 269.4 286.3 282.7 273.4 280.0 284.9 281.2 279.3 279.1 281.8 282.1 282.7 278.4 274.2 268.5 267.5 267.2 Total 4,208.5 4,331.7 4,465.3 4,662.1 4,853.1 5,093.6 5,219.1 5,318.5 5,418.2 5,562.7 5,726.8 5,875.6 5,990.2 6,017.0 5,935.5 5,991.8 6,075.4 6,039.7 6,032.9 6,006.5 5,988.8 5,953.5 5,928.6 5,926.8 5,932.9 5,947.4 5,984.3 6,008.1 6,027.5 6,039.1 6,067.0 6,096.1 6,099.4 Total 1 Housing and utilities Health care 4,068.9 4,183.6 4,327.6 4,511.0 4,690.8 4,918.2 5,029.3 5,109.8 5,199.4 5,345.1 5,515.1 5,640.6 5,745.2 5,745.6 5,660.5 5,714.0 5,798.1 5,775.9 5,765.1 5,734.4 5,707.1 5,676.3 5,657.0 5,653.5 5,655.2 5,668.1 5,702.6 5,730.6 5,754.7 5,765.9 5,793.2 5,816.6 5,816.9 1,234.8 1,261.6 1,290.3 1,329.7 1,371.7 1,413.6 1,451.4 1,461.9 1,480.2 1,512.8 1,582.6 1,616.8 1,626.6 1,637.8 1,654.9 1,669.2 1,670.7 1,637.3 1,637.0 1,630.9 1,646.1 1,650.0 1,651.3 1,656.6 1,661.5 1,663.6 1,665.7 1,675.3 1,672.2 1,666.0 1,669.1 1,680.4 1,667.2 947.6 967.2 997.2 1,029.6 1,045.7 1,081.6 1,135.6 1,202.4 1,228.3 1,267.4 1,308.9 1,333.0 1,364.0 1,396.5 1,423.1 1,442.9 1,471.9 1,385.7 1,395.7 1,401.9 1,402.5 1,409.1 1,421.6 1,429.1 1,432.8 1,424.1 1,438.2 1,446.9 1,462.3 1,464.3 1,474.5 1,472.3 1,476.4 Addendum: Personal consumption expendiFinancial tures services excludand ing insurfood ance and energy 2 489.9 508.2 525.7 559.1 606.2 666.0 661.3 658.9 659.2 675.5 698.4 716.4 739.8 732.3 676.1 667.8 678.0 746.3 738.3 732.2 712.5 693.1 679.7 670.6 661.0 667.0 670.8 665.9 667.6 674.7 676.9 682.8 677.7 5,123.9 5,319.4 5,540.7 5,860.1 6,199.5 6,545.5 6,742.5 6,938.6 7,145.2 7,401.8 7,665.3 7,911.5 8,110.4 8,087.2 7,917.2 8,076.8 8,286.3 8,143.9 8,148.9 8,090.4 7,965.7 7,929.2 7,882.9 7,927.7 7,929.1 7,981.7 8,051.4 8,096.2 8,178.0 8,238.4 8,258.7 8,292.0 8,356.0 1 Includes other items not shown separately. 2 Food consists of food and beverages purchased for off-premises consumption; food services, which include purchased meals and beverages, are not classified as food. Note: See Table B–2 for data for total personal consumption expenditures for 1963–94. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 339 Table B–18. Private fixed investment by type, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Nonresidential Residential Equipment and software Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Private fixed investment 88.1 97.2 109.0 117.7 118.7 132.1 147.3 150.4 169.9 198.5 228.6 235.4 236.5 274.8 339.0 412.2 474.9 485.6 542.6 532.1 570.1 670.2 714.4 739.9 757.8 803.1 847.3 846.4 803.3 848.5 932.5 1,033.5 1,112.9 1,209.4 1,317.7 1,447.1 1,580.7 1,717.7 1,700.2 1,634.9 1,713.3 1,903.6 2,122.3 2,267.2 2,266.1 2,128.7 1,707.6 1,728.2 1,866.4 2,205.2 2,183.7 2,130.5 1,995.5 1,799.6 1,694.3 1,678.3 1,658.3 1,658.0 1,731.6 1,743.8 1,779.3 1,791.1 1,841.7 1,905.8 1,927.1 Total nonresidential 56.0 63.0 74.8 85.4 86.4 93.4 104.7 109.0 114.1 128.8 153.3 169.5 173.7 192.4 228.7 280.6 333.9 362.4 420.0 426.5 417.2 489.6 526.2 519.8 524.1 563.8 607.7 622.4 598.2 612.1 666.6 731.4 810.0 875.4 968.6 1,061.1 1,154.9 1,268.7 1,227.8 1,125.4 1,135.7 1,223.0 1,347.3 1,505.3 1,637.5 1,656.3 1,353.0 1,390.1 1,529.2 1,689.3 1,689.0 1,665.9 1,580.9 1,430.6 1,351.9 1,324.3 1,305.1 1,318.7 1,377.1 1,416.5 1,447.9 1,460.5 1,506.0 1,568.7 1,581.5 Information processing equipment and software Structures Total Total 21.2 23.7 28.3 31.3 31.5 33.6 37.7 40.3 42.7 47.2 55.0 61.2 61.4 65.9 74.6 93.6 117.7 136.2 167.3 177.6 154.3 177.4 194.5 176.5 174.2 182.8 193.7 202.9 183.6 172.6 177.2 186.8 207.3 224.6 250.3 275.1 283.9 318.1 329.7 282.8 281.9 306.7 351.8 433.7 524.9 586.3 449.9 374.4 407.8 570.9 589.6 594.7 590.0 527.4 461.4 424.8 386.1 361.2 370.2 376.6 389.6 379.5 405.2 424.8 421.7 34.8 39.2 46.5 54.0 54.9 59.9 67.0 68.7 71.5 81.7 98.3 108.2 112.4 126.4 154.1 187.0 216.2 226.2 252.7 248.9 262.9 312.2 331.7 343.3 349.9 381.0 414.0 419.5 414.6 439.6 489.4 544.6 602.8 650.8 718.3 786.0 871.0 950.5 898.1 842.7 853.8 916.4 995.6 1,071.7 1,112.6 1,070.0 903.0 1,015.7 1,121.4 1,118.4 1,099.4 1,071.2 990.9 903.2 890.5 899.5 918.9 957.5 1,006.9 1,039.9 1,058.3 1,081.0 1,100.8 1,143.9 1,159.9 6.5 7.4 8.5 10.7 11.3 11.9 14.6 16.6 17.3 19.5 23.1 27.0 28.5 32.7 39.2 48.7 58.5 68.8 81.5 88.3 100.1 121.5 130.3 136.8 141.2 154.9 172.6 177.2 182.9 199.9 217.6 235.2 263.0 290.1 330.3 366.1 417.1 478.2 452.5 419.8 430.9 455.3 475.3 505.2 536.6 536.4 504.0 543.8 566.7 550.3 550.2 538.6 506.4 491.9 492.7 507.3 524.2 528.4 539.8 548.0 559.3 557.9 567.6 567.4 573.9 1 Includes other items not shown separately. Source: Department of Commerce (Bureau of Economic Analysis). 340 | Appendix B Structures Computers and peripheral equipment 0.7 .9 1.2 1.7 1.9 1.9 2.4 2.7 2.8 3.5 3.5 3.9 3.6 4.4 5.7 7.6 10.2 12.5 17.1 18.9 23.9 31.6 33.7 33.4 35.8 38.0 43.1 38.6 37.7 44.0 47.9 52.4 66.1 72.8 81.4 87.9 97.2 103.2 87.6 79.7 77.6 80.2 78.9 84.9 87.0 84.9 75.6 93.8 103.6 90.6 90.8 84.1 74.2 71.3 71.6 74.6 84.9 86.6 94.1 95.3 99.3 95.6 103.9 105.1 109.7 Software 0.4 .5 .7 1.0 1.2 1.3 1.8 2.3 2.4 2.8 3.2 3.9 4.8 5.2 5.5 6.3 8.1 9.8 11.8 14.0 16.4 20.4 23.8 25.6 29.0 34.2 41.9 47.6 53.7 57.9 64.3 68.3 74.6 85.5 107.5 126.0 157.3 184.5 186.6 183.0 191.3 205.7 218.0 229.8 245.0 257.2 253.2 257.9 272.5 256.0 258.2 259.5 255.2 250.3 252.3 252.6 257.6 254.8 255.1 258.6 263.2 265.1 270.4 275.5 279.0 Other 5.4 5.9 6.7 8.0 8.2 8.7 10.4 11.6 12.2 13.2 16.3 19.2 20.2 23.1 28.0 34.8 40.2 46.4 52.5 55.3 59.8 69.6 72.9 77.7 76.4 82.8 87.6 90.9 91.5 98.1 105.4 114.6 122.3 131.9 141.4 152.2 162.5 190.6 178.4 157.0 162.0 169.4 178.4 190.6 204.6 194.3 175.2 192.1 190.7 203.6 201.2 195.1 177.0 170.3 168.8 180.0 181.7 187.0 190.5 194.0 196.8 197.3 193.3 186.8 185.2 Industrial equipment Transportation equipment Other equipment 10.0 11.4 13.7 16.2 16.9 17.3 19.1 20.3 19.5 21.4 26.0 30.7 31.3 34.1 39.4 47.7 56.2 60.7 65.5 62.7 58.9 68.1 72.5 75.4 76.7 84.2 93.3 92.1 89.3 93.0 102.2 113.6 129.0 136.5 140.4 147.4 149.1 162.9 151.9 141.7 142.6 142.0 159.6 178.4 193.0 194.5 156.2 168.6 195.9 194.5 196.7 197.5 189.2 162.6 155.2 153.2 153.6 154.5 169.1 172.9 178.0 185.0 186.5 201.2 211.0 9.4 10.6 13.2 14.5 14.3 17.6 18.9 16.2 18.4 21.8 26.6 26.3 25.2 30.0 39.3 47.3 53.6 48.4 50.6 46.8 53.5 64.4 69.0 70.5 68.1 72.9 67.9 70.0 71.5 74.7 89.4 107.7 116.1 123.2 135.5 147.1 174.4 170.8 154.2 141.6 132.9 161.1 181.7 198.2 190.2 146.9 77.8 122.7 156.8 183.6 161.6 138.9 103.6 72.2 79.0 78.8 81.2 104.4 120.7 132.8 133.1 145.4 152.0 163.1 166.7 8.8 9.9 11.0 12.7 12.4 13.0 14.4 15.6 16.3 19.0 22.6 24.3 27.4 29.6 36.3 43.2 47.9 48.3 55.2 51.2 50.4 58.1 59.9 60.7 63.9 69.0 80.2 80.2 70.8 72.0 80.2 88.1 94.7 101.0 112.1 125.4 130.4 138.6 139.5 139.6 147.5 157.9 178.9 189.8 192.8 192.2 165.1 180.5 202.0 190.1 191.0 196.2 191.7 176.4 163.6 160.3 159.9 170.2 177.4 186.3 187.9 192.7 194.6 212.3 208.2 Total residential 1 32.1 34.3 34.2 32.3 32.4 38.7 42.6 41.4 55.8 69.7 75.3 66.0 62.7 82.5 110.3 131.6 141.0 123.2 122.6 105.7 152.9 180.6 188.2 220.1 233.7 239.3 239.5 224.0 205.1 236.3 266.0 302.1 302.9 334.1 349.1 385.9 425.8 449.0 472.4 509.5 577.6 680.6 775.0 761.9 628.7 472.4 354.7 338.1 337.2 515.9 494.6 464.6 414.6 369.0 342.4 353.9 353.2 339.3 354.5 327.3 331.3 330.6 335.7 337.0 345.6 Total 1 31.5 33.6 33.5 31.6 31.6 37.9 41.6 40.2 54.5 68.1 73.6 64.1 60.8 80.4 107.9 128.9 137.8 119.8 118.9 102.0 148.6 175.9 183.1 214.6 227.9 233.2 233.4 218.0 199.4 230.4 259.9 295.9 296.5 327.7 342.8 379.2 418.5 441.2 464.4 501.3 569.1 671.4 765.2 751.6 618.4 462.7 345.9 329.2 328.2 505.9 484.6 454.8 405.3 360.1 333.8 345.3 344.5 330.5 345.5 318.4 322.5 321.7 326.7 327.8 336.3 Single family 16.0 17.6 17.8 16.6 16.8 19.5 19.7 17.5 25.8 32.8 35.2 29.7 29.6 43.9 62.2 72.8 72.3 52.9 52.0 41.5 72.5 86.4 87.4 104.1 117.2 120.1 120.9 112.9 99.4 122.0 140.1 162.3 153.5 170.8 175.2 199.4 223.8 236.8 249.1 265.9 310.6 377.6 433.5 416.0 305.2 185.8 105.3 112.6 106.8 221.3 202.1 174.0 145.7 112.1 92.9 105.0 111.3 114.4 118.7 110.7 106.6 106.9 105.2 106.3 109.0 Table B–19. Real private fixed investment by type, 1995–2011 [Billions of chained (2005) dollars; quarterly data at seasonally adjusted annual rates] Nonresidential Residential Equipment and software Year or quarter 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Private fixed investment 1,231.2 1,341.6 1,465.4 1,624.4 1,775.5 1,906.8 1,870.7 1,791.5 1,854.7 1,992.5 2,122.3 2,172.7 2,130.6 1,978.6 1,606.3 1,648.4 1,757.8 2,066.4 2,039.1 1,973.5 1,835.4 1,665.5 1,589.8 1,592.6 1,577.5 1,582.0 1,654.0 1,663.5 1,693.9 1,699.0 1,736.7 1,790.4 1,805.0 Total nonresidential 787.9 861.5 965.5 1,081.4 1,194.3 1,311.3 1,274.8 1,173.7 1,189.6 1,263.0 1,347.3 1,455.5 1,550.0 1,537.6 1,263.2 1,319.2 1,432.4 1,589.1 1,580.0 1,539.2 1,442.3 1,312.9 1,257.6 1,247.0 1,235.2 1,253.3 1,308.0 1,343.6 1,371.9 1,378.9 1,413.2 1,465.6 1,471.9 Structures Information processing equipment and software Structures 342.0 361.4 387.9 407.7 408.2 440.0 433.3 356.6 343.0 346.7 351.8 384.0 438.2 466.4 367.3 309.1 321.8 463.8 474.4 469.9 457.5 415.3 375.4 354.9 323.7 301.5 306.9 310.1 318.0 305.9 321.9 332.9 326.7 Total Computers and peripheral equipment 1 Software 147.3 176.5 217.6 267.1 327.2 386.2 384.5 373.9 403.7 443.1 475.3 516.3 558.2 569.7 548.3 602.6 638.4 583.0 583.3 571.7 540.7 529.9 535.5 553.7 574.1 581.2 596.1 608.5 624.5 625.0 638.4 640.2 650.0 ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ ������������ 66.9 78.5 101.7 122.8 151.5 172.4 173.7 173.4 185.6 204.6 218.0 227.1 240.9 250.8 249.1 256.1 271.2 251.0 251.4 251.9 248.8 244.8 247.8 249.8 253.9 252.0 252.9 257.2 262.4 263.7 268.9 274.1 277.9 Total 489.4 541.4 615.9 705.2 805.0 889.2 860.6 824.2 850.0 917.3 995.6 1,071.1 1,106.8 1,059.4 889.7 1,019.4 1,124.1 1,117.2 1,094.6 1,056.8 969.0 883.7 874.2 888.0 912.9 958.8 1,010.1 1,044.1 1,064.5 1,086.9 1,103.5 1,145.7 1,160.3 Other 90.1 98.7 107.2 120.7 134.6 162.0 157.0 142.7 155.1 168.1 178.4 192.8 208.4 202.4 186.1 207.3 208.6 211.8 209.8 203.3 184.8 180.0 179.8 190.8 193.7 200.3 204.8 209.9 214.4 215.2 211.5 204.3 203.2 Industrial equipment Transportation equipment Other equipment 145.5 150.9 154.1 160.8 161.8 175.8 162.8 151.9 151.6 147.4 159.6 172.9 179.9 172.9 137.1 146.6 165.4 176.9 175.6 173.1 165.8 142.8 136.5 134.5 134.5 135.1 147.3 150.1 153.7 158.1 157.7 169.0 177.0 131.5 136.8 148.2 162.0 190.3 186.2 169.6 154.2 140.4 162.3 181.7 196.5 185.8 142.7 70.7 119.3 149.4 180.6 158.2 133.6 98.3 65.5 69.8 70.6 76.7 101.8 117.6 129.1 128.9 139.6 144.6 155.2 158.1 110.6 114.8 125.9 138.8 142.4 150.4 149.3 148.2 155.0 164.4 178.9 185.5 184.2 177.8 145.6 162.6 179.5 180.0 181.1 181.9 168.3 154.4 143.5 142.3 142.3 153.8 160.5 167.1 168.9 174.0 173.8 187.9 182.2 Total residential 2 456.1 492.5 501.8 540.4 574.2 580.0 583.3 613.8 664.3 729.5 775.0 718.2 584.2 444.4 345.6 330.8 326.2 481.3 462.8 437.8 395.8 354.9 334.3 348.2 344.8 330.8 348.2 321.1 323.1 321.1 324.4 325.4 333.9 Total 2 450.1 486.8 496.3 534.5 567.5 572.6 575.6 605.9 655.9 720.1 765.2 708.1 574.2 434.9 336.9 321.5 316.5 471.6 453.0 428.3 386.9 346.2 325.9 339.6 336.0 321.7 338.9 311.8 313.6 311.5 314.8 315.7 324.1 Single family 240.2 262.4 261.6 290.1 311.5 315.0 315.4 327.7 362.6 406.1 433.5 391.1 284.0 178.4 105.5 114.7 108.1 209.6 193.2 168.4 142.4 109.8 93.3 106.9 112.2 115.6 121.8 113.1 108.1 108.4 106.7 107.6 109.8 1 Because computers exhibit rapid changes in prices relative to other prices in the economy, the chained-dollar estimates should not be used to measure the component’s relative importance or its contribution to the growth rate of more aggregate series. The quantity index for computers can be used to accurately measure the real growth rate of this series. For information on this component, see Survey of Current Business Table 5.3.1 (for growth rates), Table 5.3.2 (for contributions), and Table 5.3.3 (for quantity indexes). 2 Includes other items not shown separately. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 341 Table B–20. Government consumption expenditures and gross investment by type, 1963–2011 [Billions of dollars; quarterly data at seasonally adjusted annual rates] Government consumption expenditures and gross investment Federal State and local National defense Year or quarter 1963 ���������������������� 1964 ���������������������� 1965 ���������������������� 1966 ���������������������� 1967 ���������������������� 1968 ���������������������� 1969 ���������������������� 1970 ���������������������� 1971 ���������������������� 1972 ���������������������� 1973 ���������������������� 1974 ���������������������� 1975 ���������������������� 1976 ���������������������� 1977 ���������������������� 1978 ���������������������� 1979 ���������������������� 1980 ���������������������� 1981 ���������������������� 1982 ���������������������� 1983 ���������������������� 1984 ���������������������� 1985 ���������������������� 1986 ���������������������� 1987 ���������������������� 1988 ���������������������� 1989 ���������������������� 1990 ���������������������� 1991 ���������������������� 1992 ���������������������� 1993 ���������������������� 1994 ���������������������� 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Total 136.4 143.2 151.4 171.6 192.5 209.3 221.4 233.7 246.4 263.4 281.7 317.9 357.7 383.0 414.1 453.6 500.7 566.1 627.5 680.4 733.4 796.9 878.9 949.3 999.4 1,038.9 1,100.6 1,181.7 1,236.1 1,273.5 1,294.8 1,329.8 1,374.0 1,421.0 1,474.4 1,526.1 1,631.3 1,731.0 1,846.4 1,983.3 2,112.6 2,232.8 2,369.9 2,518.4 2,674.2 2,878.1 2,917.5 3,002.8 3,029.7 2,812.0 2,869.6 2,929.8 2,901.1 2,875.5 2,916.9 2,935.0 2,942.7 2,967.7 3,004.6 3,018.7 3,020.2 3,014.4 3,038.6 3,047.3 3,018.6 Total 76.9 78.4 80.4 92.4 104.6 111.3 113.3 113.4 113.6 119.6 122.5 134.5 149.0 159.7 175.4 190.9 210.6 243.7 280.2 310.8 342.9 374.3 412.8 438.4 459.5 461.6 481.4 507.5 526.6 532.9 525.0 518.6 518.8 527.0 531.0 531.0 554.9 576.1 611.7 680.6 756.5 824.6 876.3 931.7 976.3 1,080.1 1,142.7 1,222.8 1,232.7 1,042.7 1,066.0 1,100.6 1,111.2 1,105.3 1,137.2 1,157.7 1,170.6 1,195.2 1,224.5 1,237.5 1,234.3 1,219.9 1,237.1 1,248.9 1,225.0 Total 61.0 60.2 60.6 71.7 83.4 89.2 89.5 87.6 84.6 86.9 88.1 95.6 103.9 111.1 120.9 130.5 145.2 168.0 196.2 225.9 250.6 281.5 311.2 330.8 350.0 354.7 362.1 373.9 383.1 376.8 363.0 353.8 348.8 354.8 349.8 346.1 361.1 371.0 393.0 437.7 497.9 550.8 589.0 624.9 662.3 737.8 774.9 819.2 824.8 706.0 724.7 758.4 762.1 747.7 771.6 789.0 791.4 803.5 818.0 831.3 823.9 809.0 830.6 844.0 815.6 Consumption expenditures 48.3 48.8 50.6 59.9 69.9 77.1 78.1 76.5 77.1 79.5 79.4 84.5 90.9 95.8 104.2 112.7 123.8 143.7 167.3 191.1 208.7 232.8 253.7 267.9 283.6 293.5 299.4 308.0 319.7 315.2 307.5 300.8 297.0 303.2 304.5 300.3 313.0 321.8 342.0 380.7 435.2 481.2 514.8 543.9 575.4 633.3 664.1 702.1 717.0 614.2 620.9 648.5 649.6 641.9 659.5 674.6 680.5 691.0 701.6 713.1 702.7 701.0 723.4 733.2 710.6 Gross investment Structures 1.6 1.3 1.1 1.3 1.2 1.2 1.5 1.3 1.8 1.8 2.1 2.2 2.3 2.1 2.4 2.5 2.5 3.2 3.2 4.0 4.8 4.9 6.2 6.8 7.7 7.4 6.4 6.1 4.6 5.2 5.3 5.8 6.7 6.3 6.1 5.8 5.4 5.4 5.3 5.8 7.3 7.1 7.5 8.1 10.1 13.7 17.3 17.3 14.8 10.2 13.1 14.9 16.4 16.9 17.0 17.9 17.4 16.6 17.2 18.0 17.5 15.5 14.4 15.9 13.3 Source: Department of Commerce (Bureau of Economic Analysis). 342 | Appendix B Gross investment Nondefense Equipment and software 11.0 10.2 8.9 10.5 12.3 10.9 9.9 9.8 5.7 5.7 6.6 8.9 10.7 13.2 14.4 15.3 18.9 21.1 25.7 30.8 37.1 43.8 51.3 56.1 58.8 53.9 56.3 59.8 58.8 56.3 50.1 47.2 45.1 45.4 39.2 39.9 42.8 43.8 45.6 51.2 55.4 62.4 66.8 72.9 76.9 90.9 93.5 99.8 93.0 81.6 90.7 95.0 96.2 88.9 95.0 96.5 93.5 96.0 99.3 100.2 103.7 92.6 92.9 94.9 91.6 Total 15.9 18.2 19.8 20.8 21.2 22.0 23.8 25.8 29.1 32.7 34.3 39.0 45.1 48.6 54.5 60.4 65.4 75.8 83.9 84.9 92.3 92.7 101.6 107.6 109.6 106.8 119.3 133.6 143.4 156.1 162.0 164.8 170.0 172.2 181.1 184.9 193.8 205.0 218.7 242.9 258.5 273.9 287.3 306.8 314.0 342.3 367.8 403.6 407.9 336.7 341.3 342.1 349.0 357.7 365.7 368.6 379.2 391.6 406.5 406.2 410.3 410.9 406.5 404.9 409.4 Consumption expenditures 12.4 14.0 15.1 15.9 17.0 18.2 20.2 22.1 24.9 28.2 29.4 33.4 38.7 41.4 46.5 50.6 55.1 63.8 71.0 72.1 77.7 77.1 84.7 90.1 90.1 88.3 99.1 111.0 118.6 128.9 133.7 139.9 143.2 143.4 153.0 154.3 160.3 174.2 188.1 209.8 225.1 240.2 251.0 267.1 273.5 298.5 322.5 351.9 355.5 294.4 297.8 297.7 303.9 313.3 321.7 323.2 331.9 342.9 354.4 353.6 356.9 358.1 354.1 351.7 357.9 Gross investment Structures 2.3 2.5 2.8 2.8 2.2 2.1 1.9 2.1 2.5 2.7 3.1 3.4 4.1 4.6 5.0 6.1 6.3 7.1 7.7 6.8 6.7 7.0 7.3 8.0 9.0 6.8 6.9 8.0 9.2 10.3 11.2 10.2 10.8 11.3 9.9 10.8 10.7 8.3 8.1 9.9 10.3 9.1 8.3 9.5 11.1 11.4 12.4 16.3 15.4 10.5 10.9 11.7 12.5 12.1 11.5 12.5 13.6 14.2 17.0 16.7 17.1 16.4 16.0 15.2 14.0 Equipment and software 1.2 1.6 1.9 2.1 1.9 1.7 1.7 1.7 1.7 1.8 1.8 2.2 2.4 2.7 3.0 3.7 4.0 4.9 5.3 6.0 7.8 8.7 9.6 9.5 10.4 11.7 13.4 14.6 15.7 16.9 17.0 14.7 16.0 17.5 18.2 19.9 22.7 22.6 22.5 23.2 23.1 24.6 28.0 30.2 29.4 32.4 32.9 35.4 37.0 31.8 32.6 32.8 32.7 32.3 32.5 32.9 33.8 34.6 35.1 35.8 36.3 36.4 36.3 37.9 37.5 Total Consumption expenditures 59.5 64.8 71.0 79.2 87.9 98.0 108.2 120.3 132.8 143.8 159.2 183.4 208.7 223.3 238.7 262.7 290.2 322.4 347.3 369.7 390.5 422.6 466.1 510.9 539.9 577.3 619.2 674.2 709.5 740.6 769.8 811.2 855.3 894.0 943.5 995.0 1,076.3 1,154.9 1,234.7 1,302.7 1,356.1 1,408.2 1,493.6 1,586.7 1,697.9 1,798.0 1,774.8 1,780.0 1,797.0 1,769.3 1,803.7 1,829.2 1,789.9 1,770.1 1,779.7 1,777.3 1,772.1 1,772.6 1,780.1 1,781.2 1,786.0 1,794.4 1,801.5 1,798.5 1,793.7 41.9 45.8 50.2 56.1 62.6 70.4 79.8 91.5 102.7 113.2 126.0 143.7 165.1 179.5 195.9 213.2 233.3 258.4 282.3 304.9 324.1 347.7 381.8 418.1 441.4 471.0 504.5 547.0 577.5 606.2 634.2 668.2 701.3 730.2 764.5 808.6 870.6 930.6 994.2 1,049.4 1,096.5 1,139.1 1,212.0 1,282.3 1,368.9 1,449.2 1,425.5 1,443.5 1,475.0 1,428.4 1,455.1 1,475.6 1,437.8 1,417.1 1,424.6 1,427.6 1,432.7 1,443.1 1,441.8 1,438.9 1,450.1 1,471.7 1,482.9 1,476.1 1,469.2 Structures 16.0 17.2 19.0 21.0 23.0 25.2 25.6 25.8 27.0 27.1 29.1 34.7 38.1 38.1 36.9 42.8 49.0 55.1 55.4 54.2 54.2 60.5 67.6 74.2 78.8 84.8 88.7 98.5 103.2 104.2 104.5 108.7 117.3 126.8 139.5 143.6 159.7 176.0 192.3 205.8 211.8 220.2 230.8 249.9 268.4 285.0 284.5 270.8 253.8 277.1 284.3 289.1 289.4 289.4 290.7 284.9 273.0 263.7 272.8 276.6 270.0 256.8 250.6 252.9 254.8 Equipment and software 1.5 1.8 1.9 2.1 2.3 2.4 2.7 3.0 3.1 3.5 4.1 4.9 5.5 5.7 5.9 6.6 7.8 8.9 9.5 10.6 12.2 14.4 16.8 18.6 19.6 21.5 26.0 28.7 28.9 30.1 31.2 34.3 36.7 36.9 39.4 42.9 46.1 48.3 48.2 47.5 47.8 48.9 50.8 54.5 60.7 63.8 64.8 65.7 68.3 63.8 64.3 64.5 62.7 63.6 64.5 64.8 66.4 65.8 65.6 65.7 65.8 66.0 68.0 69.5 69.6 Table B–21. Real government consumption expenditures and gross investment by type, 1995–2011 [Billions of chained (2005) dollars; quarterly data at seasonally adjusted annual rates] Government consumption expenditures and gross investment Federal State and local National defense Year or quarter 1995 ���������������������� 1996 ���������������������� 1997 ���������������������� 1998 ���������������������� 1999 ���������������������� 2000 ���������������������� 2001 ���������������������� 2002 ���������������������� 2003 ���������������������� 2004 ���������������������� 2005 ���������������������� 2006 ���������������������� 2007 ���������������������� 2008 ���������������������� 2009 ���������������������� 2010 ���������������������� 2011 p �������������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Total 1,888.9 1,907.9 1,943.8 1,985.0 2,056.1 2,097.8 2,178.3 2,279.6 2,330.5 2,362.0 2,369.9 2,402.1 2,434.2 2,497.4 2,539.6 2,556.8 2,502.0 2,473.9 2,484.5 2,510.7 2,520.5 2,509.6 2,546.0 2,554.2 2,548.5 2,540.6 2,564.0 2,570.3 2,552.1 2,513.9 2,508.2 2,507.6 2,478.5 Total 704.1 696.0 689.1 681.4 694.6 698.1 726.5 779.5 831.1 865.0 876.3 894.9 906.1 971.1 1,029.5 1,075.9 1,054.7 943.8 955.1 982.0 1,003.5 995.2 1,029.2 1,043.9 1,049.6 1,056.9 1,079.4 1,087.8 1,079.6 1,053.3 1,058.3 1,063.7 1,043.7 Total 476.8 470.4 457.2 447.5 455.8 453.5 470.7 505.3 549.2 580.4 589.0 598.4 611.8 657.7 695.6 718.3 701.4 634.7 643.1 669.7 683.2 669.9 695.7 709.5 707.3 708.2 718.6 728.6 717.7 694.0 705.9 714.6 691.1 Consumption expenditures 424.5 418.5 412.2 401.2 407.6 403.9 418.5 445.8 484.1 509.4 514.8 519.1 528.0 559.6 591.5 609.0 602.2 547.3 545.6 567.2 578.4 570.7 590.3 601.9 603.0 602.7 609.8 618.1 605.3 594.0 607.1 613.1 594.7 Gross investment Structures 10.1 9.2 8.7 8.1 7.2 6.9 6.5 7.0 8.5 7.8 7.5 7.5 8.8 11.5 14.6 14.7 12.2 8.7 11.0 12.5 13.7 14.0 14.3 15.2 14.8 14.1 14.7 15.4 14.8 13.0 12.0 13.2 10.9 Gross investment Nondefense Equipment and software 43.7 43.8 38.9 40.1 42.4 43.6 46.3 52.7 57.0 63.3 66.8 71.9 75.1 87.0 89.7 94.9 86.7 78.9 87.0 90.5 91.4 85.3 91.4 92.7 89.5 91.6 94.4 95.5 98.3 86.9 86.6 88.0 85.3 Total 227.5 225.7 231.9 233.7 238.7 244.4 255.5 273.9 281.7 284.6 287.3 296.6 294.2 313.3 333.8 357.7 353.3 309.1 312.1 312.0 320.2 325.3 333.4 334.3 342.2 348.7 360.8 359.2 361.9 359.4 352.4 349.0 352.6 Consumption expenditures 201.2 196.2 203.2 201.2 202.9 212.4 224.2 239.7 247.1 250.2 251.0 257.5 254.7 271.0 289.7 307.5 303.0 268.0 270.0 269.2 276.7 282.3 290.5 289.8 296.1 301.2 310.3 308.3 310.3 308.4 302.1 298.3 303.3 Gross investment Structures 15.7 15.9 13.8 14.5 14.0 10.4 9.8 11.8 11.9 9.9 8.3 8.8 9.8 9.6 10.4 13.7 12.6 9.0 9.3 9.8 10.2 9.9 9.6 10.5 11.5 12.0 14.4 14.1 14.3 13.6 13.2 12.4 11.3 Equipment and software 13.7 15.5 16.6 18.7 21.7 21.5 21.6 22.7 23.0 24.6 28.0 30.3 29.7 33.0 33.7 36.3 37.9 32.3 33.0 33.2 33.3 33.1 33.3 33.9 34.5 35.3 35.9 36.6 37.2 37.3 37.2 38.7 38.4 Total Consumption expenditures 1,183.6 1,211.1 1,254.3 1,303.8 1,361.8 1,400.1 1,452.3 1,500.6 1,499.7 1,497.1 1,493.6 1,507.2 1,528.1 1,528.1 1,514.2 1,487.0 1,453.4 1,530.9 1,530.5 1,530.8 1,520.1 1,517.2 1,520.7 1,514.9 1,503.9 1,489.2 1,490.8 1,488.9 1,478.9 1,466.4 1,456.1 1,450.4 1,440.7 983.0 1,001.0 1,027.7 1,070.8 1,109.5 1,133.7 1,172.6 1,211.3 1,207.5 1,207.4 1,212.0 1,220.7 1,239.8 1,237.1 1,228.9 1,213.0 1,199.0 1,240.7 1,236.6 1,237.2 1,233.9 1,232.6 1,231.7 1,227.1 1,224.3 1,219.1 1,214.8 1,210.8 1,207.4 1,207.4 1,203.2 1,197.2 1,188.4 Structures 175.4 184.3 196.7 196.5 210.9 222.2 234.8 244.2 245.5 241.3 230.8 231.4 227.6 227.9 222.2 210.6 190.4 226.8 230.0 229.9 224.8 222.8 226.1 224.4 215.4 207.0 212.8 214.6 208.1 196.3 189.3 188.6 187.6 Equipment and software 29.1 29.9 33.1 37.7 41.8 44.3 45.3 45.8 47.2 48.6 50.8 55.2 61.6 64.4 64.8 66.2 68.6 64.9 65.2 65.0 62.6 63.4 64.3 64.9 66.7 66.1 65.9 66.1 66.5 66.5 68.3 69.6 69.8 Note: See Table B–2 for data for total government consumption expenditures and gross investment for 1963–94. Source: Department of Commerce (Bureau of Economic Analysis). National Income or Expenditure | 343 Table B–22. Private inventories and domestic final sales by industry, 1963–2011 [Billions of dollars, except as noted; seasonally adjusted] Private inventories 1 Quarter Total 2 Fourth quarter: 1963 ���������������� 1964 ���������������� 1965 ���������������� 1966 ���������������� 1967 ���������������� 1968 ���������������� 1969 ���������������� 1970 ���������������� 1971 ���������������� 1972 ���������������� 1973 ���������������� 1974 ���������������� 1975 ���������������� 1976 ���������������� 1977 ���������������� 1978 ���������������� 1979 ���������������� 1980 ���������������� 1981 ���������������� 1982 ���������������� 1983 ���������������� 1984 ���������������� 1985 ���������������� 1986 ���������������� 1987 ���������������� 1988 ���������������� 1989 ���������������� 1990 ���������������� 1991 ���������������� 1992 ���������������� 1993 ���������������� 1994 ���������������� 1995 ���������������� NAICS: 1996 ���������������� 1997 ���������������� 1998 ���������������� 1999 ���������������� 2000 ���������������� 2001 ���������������� 2002 ���������������� 2003 ���������������� 2004 ���������������� 2005 ���������������� 2006 ���������������� 2007 ���������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Farm Mining, utilities, and construction 2 Manufac- Wholesale turing trade Retail trade Other industries 2 Nonfarm 2 Final sales of domestic business 3 Ratio of private inventories to final sales of domestic business Total Nonfarm 149.9 154.5 169.4 185.6 194.8 208.1 227.4 235.7 253.7 283.6 351.5 405.6 408.5 439.6 482.0 570.9 667.6 739.0 779.1 773.9 796.9 869.0 875.9 858.0 924.2 999.7 1,044.3 1,082.0 1,057.2 1,082.6 1,116.0 1,194.5 1,257.2 44.4 42.2 47.2 47.3 45.7 48.8 52.8 52.4 59.3 73.7 102.2 87.6 89.5 85.3 90.6 119.3 134.9 140.3 127.4 131.3 131.7 131.4 125.8 113.0 119.9 130.7 129.6 133.1 123.2 133.1 132.3 134.5 131.1 ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 55.1 58.6 63.4 73.0 79.9 85.1 92.6 95.5 96.6 102.1 121.5 162.6 162.2 178.7 193.2 219.8 261.8 293.4 313.1 304.6 308.9 344.5 333.3 320.6 339.6 372.4 390.5 404.5 384.1 377.6 380.1 404.3 424.5 19.5 20.8 22.5 25.8 28.1 29.3 32.5 36.4 39.4 43.1 51.7 66.9 66.5 74.1 84.0 99.0 119.5 139.4 148.8 147.9 153.4 169.1 175.9 182.0 195.8 213.9 222.8 236.8 239.2 248.3 258.6 281.5 303.7 23.9 25.2 28.0 30.6 30.9 34.2 37.5 38.5 44.7 49.8 58.4 63.9 64.4 73.0 80.9 94.1 104.7 111.7 123.2 123.2 137.6 157.0 171.4 176.2 199.1 213.2 231.4 236.6 240.2 249.4 268.6 293.6 312.2 7.1 7.7 8.3 8.9 10.1 10.6 12.0 12.9 13.7 14.8 17.7 24.7 25.9 28.5 33.3 38.8 46.6 54.1 66.6 66.8 65.2 66.9 69.5 66.3 69.9 69.5 70.1 71.0 70.5 74.3 76.5 80.6 85.6 105.5 112.2 122.2 138.3 149.1 159.3 174.6 183.3 194.4 209.9 249.4 318.1 319.0 354.2 391.4 451.7 532.6 598.7 651.7 642.6 665.1 737.6 750.2 745.1 804.4 869.1 914.7 948.9 934.0 949.5 983.7 1,060.0 1,126.1 37.9 40.8 44.9 47.4 49.9 55.0 58.7 61.9 67.5 75.7 83.7 89.8 101.1 111.2 124.0 143.6 159.4 174.1 186.7 194.8 215.7 233.6 249.5 264.2 277.7 304.1 322.8 335.9 345.7 370.9 391.4 413.9 436.0 3.95 3.79 3.77 3.92 3.90 3.79 3.88 3.81 3.76 3.74 4.20 4.52 4.04 3.95 3.89 3.98 4.19 4.24 4.17 3.97 3.69 3.72 3.51 3.25 3.33 3.29 3.23 3.22 3.06 2.92 2.85 2.89 2.88 2.78 2.75 2.72 2.92 2.99 2.90 2.98 2.96 2.88 2.77 2.98 3.54 3.16 3.19 3.16 3.15 3.34 3.44 3.49 3.30 3.08 3.16 3.01 2.82 2.90 2.86 2.83 2.82 2.70 2.56 2.51 2.56 2.58 1,284.7 1,327.3 1,341.6 1,432.7 1,524.0 1,447.3 1,489.1 1,545.7 1,681.5 1,804.6 1,917.1 2,077.5 2,146.8 2,232.2 2,203.2 2,024.3 1,949.4 1,901.6 1,863.4 1,883.6 1,926.4 1,938.9 2,001.3 2,084.5 2,189.6 2,211.6 2,225.8 2,246.4 136.6 136.9 120.5 124.3 132.1 126.2 135.9 151.0 157.2 165.2 165.1 188.3 197.8 213.5 206.7 185.4 181.2 176.1 171.1 173.0 183.5 183.4 195.1 214.8 237.7 230.0 234.8 233.0 31.1 33.0 36.6 38.5 42.3 45.3 46.5 54.7 64.1 81.7 90.7 95.6 101.3 111.1 111.3 94.0 88.9 85.6 84.7 83.5 84.2 83.0 82.2 82.3 85.3 88.0 89.0 90.9 421.0 432.0 432.3 457.6 476.5 440.9 443.7 447.6 487.2 531.5 575.7 635.6 670.4 703.0 681.8 604.5 585.3 577.0 572.1 582.1 595.4 595.2 608.6 640.9 680.5 690.7 689.5 701.4 285.1 302.5 312.0 334.8 357.7 335.8 343.2 352.6 388.9 422.8 456.4 497.2 515.8 539.6 537.1 496.9 472.7 457.5 441.2 449.0 457.6 462.7 489.4 515.8 541.6 557.8 566.0 573.4 328.7 335.9 349.2 377.7 400.8 386.0 408.0 425.5 460.9 473.7 491.6 511.8 508.9 509.9 508.3 488.9 471.5 458.0 447.4 448.1 455.9 464.9 475.6 477.3 485.8 484.7 486.3 485.6 82.1 87.1 91.1 99.8 114.6 113.0 111.8 114.3 123.2 129.8 137.7 148.9 152.6 155.1 158.0 154.6 149.8 147.5 146.9 147.8 149.8 149.7 150.3 153.6 158.6 160.4 160.1 162.1 1,148.1 1,190.4 1,221.1 1,308.4 1,391.8 1,321.1 1,353.2 1,394.7 1,524.3 1,639.4 1,752.0 1,889.2 1,949.0 2,018.7 1,996.5 1,838.9 1,768.2 1,725.5 1,692.3 1,710.6 1,742.9 1,755.5 1,806.2 1,869.7 1,951.9 1,981.6 1,991.0 2,013.4 465.6 492.2 525.8 557.2 588.3 603.0 608.5 646.2 683.4 727.5 769.6 807.0 803.4 810.3 804.8 782.5 775.8 769.8 772.8 772.9 777.0 787.0 794.1 812.0 816.5 825.4 840.3 845.8 2.76 2.70 2.55 2.57 2.59 2.40 2.45 2.39 2.46 2.48 2.49 2.57 2.67 2.75 2.74 2.59 2.51 2.47 2.41 2.44 2.48 2.46 2.52 2.57 2.68 2.68 2.65 2.66 2.47 2.42 2.32 2.35 2.37 2.19 2.22 2.16 2.23 2.25 2.28 2.34 2.43 2.49 2.48 2.35 2.28 2.24 2.19 2.21 2.24 2.23 2.27 2.30 2.39 2.40 2.37 2.38 1 Inventories at end of quarter. Quarter-to-quarter change calculated from this table is not the current-dollar change in private inventories component of gross domestic product (GDP). The former is the difference between two inventory stocks, each valued at its respective end-of-quarter prices. The latter is the change in the physical volume of inventories valued at average prices of the quarter. In addition, changes calculated from this table are at quarterly rates, whereas change in private inventories is stated at annual rates. 2 Inventories of construction, mining, and utilities establishments are included in other industries through 1995. 3 Quarterly totals at monthly rates. Final sales of domestic business equals final sales of domestic product less gross output of general government, gross value added of nonprofit institutions, compensation paid to domestic workers, and imputed rental of owner-occupied nonfarm housing. Includes a small amount of final sales by farm and by government enterprises. Note: The industry classification of inventories is on an establishment basis. Estimates through 1995 are based on the Standard Industrial Classification (SIC). Beginning with 1996, estimates are based on the North American Industry Classification System (NAICS). Source: Department of Commerce (Bureau of Economic Analysis). 344 | Appendix B Table B–23. Real private inventories and domestic final sales by industry, 1963–2011 [Billions of chained (2005) dollars, except as noted; seasonally adjusted] Private inventories 1 Quarter Total 2 Fourth quarter: 1963 ���������������� 1964 ���������������� 1965 ���������������� 1966 ���������������� 1967 ���������������� 1968 ���������������� 1969 ���������������� 1970 ���������������� 1971 ���������������� 1972 ���������������� 1973 ���������������� 1974 ���������������� 1975 ���������������� 1976 ���������������� 1977 ���������������� 1978 ���������������� 1979 ���������������� 1980 ���������������� 1981 ���������������� 1982 ���������������� 1983 ���������������� 1984 ���������������� 1985 ���������������� 1986 ���������������� 1987 ���������������� 1988 ���������������� 1989 ���������������� 1990 ���������������� 1991 ���������������� 1992 ���������������� 1993 ���������������� 1994 ���������������� 1995 ���������������� NAICS: 1996 ���������������� 1997 ���������������� 1998 ���������������� 1999 ���������������� 2000 ���������������� 2001 ���������������� 2002 ���������������� 2003 ���������������� 2004 ���������������� 2005 ���������������� 2006 ���������������� 2007 ���������������� 2008: I ������������������ II ����������������� III ���������������� IV ���������������� 2009: I ������������������ II ����������������� III ���������������� IV ���������������� 2010: I ������������������ II ����������������� III ���������������� IV ���������������� 2011: I ������������������ II ����������������� III ���������������� IV p ������������� Farm Mining, utilities, and construction 2 Manufac- Wholesale turing trade Other industries 2 Retail trade Nonfarm 2 Final sales of domestic business 3 Ratio of private inventories to final sales of domestic business Total Nonfarm 540.6 557.9 590.8 637.9 671.8 702.6 732.9 738.5 763.5 789.1 828.1 857.2 844.4 878.7 921.8 967.4 995.4 986.0 1,025.0 1,005.3 997.7 1,075.9 1,101.3 1,109.8 1,143.0 1,164.9 1,195.6 1,212.1 1,210.7 1,228.6 1,250.8 1,320.1 1,352.2 139.0 135.1 137.7 136.3 138.8 142.9 142.9 140.5 144.6 145.0 146.8 142.4 148.2 146.6 153.9 155.9 160.2 153.0 163.1 170.6 153.1 159.4 166.5 164.2 155.1 142.0 142.0 148.6 146.7 153.8 146.3 160.0 147.0 ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� ����������������� 187.8 198.2 212.2 240.6 259.6 271.5 284.1 284.0 280.6 288.3 309.6 333.0 324.6 340.1 349.6 365.6 379.7 380.1 385.2 367.9 367.5 399.4 392.4 388.3 397.6 416.2 431.8 441.6 434.2 429.0 432.9 446.3 461.7 77.5 82.2 87.8 99.5 107.7 111.5 119.7 128.7 135.5 141.6 145.4 158.9 152.1 162.2 175.3 189.3 198.7 204.0 209.8 207.2 206.3 222.8 229.2 237.7 245.4 254.9 258.5 267.2 271.5 280.3 286.5 302.7 316.2 77.0 81.1 89.3 96.6 96.6 104.8 112.1 112.2 127.4 137.3 148.4 146.2 138.8 149.5 158.1 168.7 168.6 163.8 172.8 168.9 182.7 205.0 220.8 224.3 246.1 253.9 268.8 267.2 267.7 272.5 288.3 309.4 321.9 42.1 44.7 46.6 47.9 53.5 55.1 57.9 58.6 60.7 63.7 67.0 71.4 73.3 74.0 79.6 84.4 84.3 82.9 92.3 89.4 88.3 89.7 94.8 98.3 100.8 99.3 94.8 91.2 94.8 97.7 101.2 106.1 108.6 385.5 407.3 437.8 487.9 519.5 545.9 576.8 585.5 606.1 632.8 673.3 712.3 690.9 728.5 764.2 809.1 832.8 832.4 860.6 833.3 844.0 916.3 934.7 945.1 986.2 1,021.6 1,052.4 1,066.4 1,066.8 1,077.7 1,107.6 1,163.4 1,207.7 166.1 176.1 191.3 195.4 200.3 211.2 215.5 218.1 229.3 248.4 257.1 247.5 259.3 272.0 286.4 307.8 315.0 314.7 312.4 311.2 334.7 353.1 369.4 383.3 393.8 414.2 426.4 427.7 427.4 450.6 466.3 484.9 502.7 3.25 3.17 3.09 3.26 3.35 3.33 3.40 3.39 3.33 3.18 3.22 3.46 3.26 3.23 3.22 3.14 3.16 3.13 3.28 3.23 2.98 3.05 2.98 2.90 2.90 2.81 2.80 2.83 2.83 2.73 2.68 2.72 2.69 2.32 2.31 2.29 2.50 2.59 2.58 2.68 2.68 2.64 2.55 2.62 2.88 2.66 2.68 2.67 2.63 2.64 2.65 2.75 2.68 2.52 2.60 2.53 2.47 2.50 2.47 2.47 2.49 2.50 2.39 2.38 2.40 2.40 1,383.4 1,460.8 1,532.4 1,600.9 1,661.1 1,619.4 1,632.1 1,649.5 1,715.8 1,765.8 1,825.2 1,852.9 1,849.8 1,846.2 1,836.7 1,816.6 1,776.3 1,730.5 1,685.8 1,671.7 1,681.7 1,697.8 1,720.9 1,730.5 1,742.8 1,752.6 1,752.1 1,766.1 155.3 159.0 160.6 156.9 155.2 155.3 152.2 152.4 160.3 160.4 156.7 155.9 154.1 155.0 156.3 156.9 156.9 156.7 155.5 155.4 156.5 156.7 155.3 154.0 152.1 149.9 148.4 147.2 47.6 50.1 59.1 57.1 54.3 65.1 61.0 68.2 69.6 73.4 90.3 90.3 88.5 87.2 86.6 81.8 81.7 81.2 79.5 74.8 72.3 72.5 71.0 70.6 70.3 70.9 70.7 72.9 465.7 490.0 507.6 523.8 531.9 505.7 500.5 492.0 498.0 519.0 536.0 551.4 558.0 552.9 544.5 537.3 528.1 517.6 507.1 505.9 509.0 510.2 516.2 526.1 534.5 540.5 543.3 551.9 298.0 324.9 348.6 369.7 390.4 376.8 376.7 376.3 396.8 415.0 428.3 432.8 434.0 440.5 442.5 441.7 425.0 407.1 389.3 387.0 390.5 397.2 409.8 413.9 419.5 429.2 430.9 437.1 335.3 349.5 364.7 390.5 411.1 400.5 424.2 441.5 465.2 469.8 480.6 484.8 476.5 471.8 467.8 458.3 444.8 429.9 417.6 412.5 417.0 425.1 432.2 428.8 428.6 423.5 420.3 417.9 87.6 93.2 99.0 106.6 119.3 119.1 118.0 119.6 126.0 128.3 132.9 137.2 137.4 137.2 137.4 138.8 137.6 135.9 134.8 134.0 134.2 134.1 134.4 134.7 135.7 136.0 135.9 136.6 1,230.9 1,304.4 1,373.9 1,444.7 1,505.9 1,464.4 1,480.0 1,497.2 1,555.6 1,605.4 1,668.6 1,697.3 1,696.1 1,691.6 1,680.5 1,659.7 1,619.1 1,573.4 1,529.9 1,515.9 1,524.8 1,540.8 1,565.5 1,576.6 1,591.6 1,604.3 1,605.7 1,621.6 528.6 550.7 585.4 615.6 638.0 644.2 644.8 676.3 696.6 718.7 744.4 766.1 760.7 764.3 753.1 730.4 719.0 716.0 718.9 717.7 719.6 726.1 730.1 742.9 744.1 747.8 755.4 760.3 2.62 2.65 2.62 2.60 2.60 2.51 2.53 2.44 2.46 2.46 2.45 2.42 2.43 2.42 2.44 2.49 2.47 2.42 2.35 2.33 2.34 2.34 2.36 2.33 2.34 2.34 2.32 2.32 2.33 2.37 2.35 2.35 2.36 2.27 2.30 2.21 2.23 2.23 2.24 2.22 2.23 2.21 2.23 2.27 2.25 2.20 2.13 2.11 2.12 2.12 2.14 2.12 2.14 2.15 2.13 2.13 1 Inventories at end of quarter. Quarter-to-quarter changes calculated from this table are at quarterly rates, whereas the change in private inventories component of gross domestic product (GDP) is stated at annual rates. 2 Inventories of construction, mining, and utilities establishments are included in other industries through 1995. 3 Quarterly totals at monthly rates. Final sales of domestic business equals final sales of domestic product less gross output of general government, gross value added of nonprofit institutions, compensation paid to domestic workers, and imputed rental of owner-occupied nonfarm housing. Includes a small amount of final sales by farm and by government enterprises. Note: The industry classification of inventories is on an establishment basis. Estimates through 1995 are based on the Standard Industrial Classification (SIC). Beginning with 1996, estimates are based on the North American Industry Classification System (NAICS). See Survey of Current Business, Tables 5.7.6A and 5.7.6B, for detailed information on calculation of the chained (2005) doll
@FedFRASER