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1 • • • • • • • The Economy in Perspective by Mark Sniderman Democracy is good. I say this because other systems are worse. —Jawaharlal Nehru, Prime Minister of India (January 1961) If you look at the 150 years of modern China’s history since the Opium Wars, then you can’t avoid the conclusion that the last 15 years are the best 15 years in China’s modern history. —J. Stapleton Roy, U.S. ambassador to China, in the New York T imes (September 1, 1994) FRB Cleveland • September 2006 I didn’t think very much about China or India when I was growing up. I knew they were there, of course, on the other side of the globe—large countries with very large populations. I supposed that the people who lived there were poor and tied to the land. India entered my teenage consciousness more tangibly when the Beatles went to commune with the Maharishi Mayesh Yogi, but the country was, to me, still just a large and exotic place. China, what I thought of as the wellspring of the egg roll, appeared as a slightly larger blip on my radar screen when the Vietnam conflict became the Vietnam War. Relative to the United States, China and India are still poor countries with large populations whose livelihoods depend significantly on the land. But these countries—individually and collectively with other countries in Southeast Asia—are remarkably transforming themselves and the global economic order. Today’s young Americans probably will have far different childhood recollections of China and India than I did, and, unless the economic transformations now underway are unexpectedly cut short, that pattern should continue for several generations. To put the pace of change in perspective, consider this mathematical example by Stanley Fischer, Governor of the Bank of Israel.1 Fischer notes that the Chinese economy has been growing in real terms at rates in excess of 10 percent per year for over 25 years. Fischer conjectures that if the U.S. economy grows at its long-term average of about 3 percent per year, China’s economy will equal the size of the U.S. economy in roughly 25 years. The Indian economy has been expanding a bit more slowly than the Chinese economy—8 percent per year—and would take somewhat longer to match the size of the U.S. economy. Certainly it will take more time for the typical Chinese or Indian resident to enjoy the same level of per capita income as the typical U.S. resident, for the populations of China and India are considerably 1Stanley larger than that of the United States. But the trends are unmistakable: According to calculations cited by Fischer, if China and India continue on their current development paths, they, together with the other developing Asian countries, could account for half of the world’s GDP in 2030, up from just a bit more than one-third today. Whether or not these countries can stay on their vigorous growth paths remains to be seen. When people speculate about the bright futures of the Chinese and Indian economies, they often stake their claims on the belief that these nations are doing a superior job in educating their populations: China and India are well-known for turning out very well trained college graduates in science and engineering fields, and they have been able to achieve enrollment rates in their primary education systems of more than 95 percent. But secondary education enrollment lags far behind in both countries, and education generally within the adult populations remains a drawback to better economic performance. Education is not the only challenge facing developing economies. Cross-country comparisons of economic growth strongly conclude that rapid growth depends not only on the quality of human capital, but also on the competitive structure of markets. In an interesting study of Latin America’s subpar economic performance during the past 50 years, the authors conclude that Latin American economies suffered from high costs of starting a business, poorly functioning capital markets, and high costs of adjusting the workforce or building up an experienced workforce.2 Their problems stemmed not from having poorly educated workforces, but from excessive government intrusion into the operation of the economies in the region. The experiences of these nations suggest that China, India, and the other emerging Asian nations will also have to keep transitioning to more competitive markets if they hope to expand per capita income growth. These transitions can often present difficult internal challenges. In the same way that I had a vaguely defined conception of China and India in my youth, I now realize that I had only a hazy grasp of my own country. Most of all, as I look back, I’m struck by how immutable the world seemed then. Things were the way they were, and seemingly would always be so. Such are the follies of youth. Fischer. 2006. “The New Economic Global Geography,” speech delivered at the 2006 Federal Reserve Bank of Kansas City Economic Symposium at Jackson Hole, Wyoming. 2Harold L. Cole, Lee E.Ohanian, Alvaro Riascos, and James A.Schmitz Jr. 2006. “Latin America in the Rearview Mirror,” Federal Reserve Bank of Minneapolis, Quarterly Review, September. 2 • • • • • • • Inflation and Prices 12-month percent change 4.75 CPI AND CPI EXCLUDING FOOD AND ENERGY 4.50 July Price Statistics Percent change, last: a a a 1 mo. 3 mo. 12 mo. 5 yr. 2005 avg. Consumer Price Index 4.25 4.00 3.75 3.50 All items 5.5 4.5 4.1 2.8 3.6 Less food and energy 2.4 3.2 2.7 2.1 2.2 Medianb 4.4 4.4 3.3 2.7 2.5 Less food and energy CPI 3.00 2.75 Producer Price Index All items 3.25 2.50 2.25 2.00 1.5 3.3 4.2 2.9 5.7 –3.0 0.8 1.3 1.1 1.5 1.75 CPI excluding food and energy 1.50 12-month percent change 4.25 TRIMMED-MEAN CPI INFLATION MEASURES 4.00 1.25 1.00 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 12-month percent change 6.00 HOUSEHOLD INFLATION EXPECTATIONS c 5.50 3.75 5.00 3.50 Median CPI b 4.50 3.25 Five to 10 years ahead 3.00 4.00 2.75 3.50 2.50 2.25 3.00 2.00 2.50 1.75 16% trimmed-mean CPI b 2.00 1.50 1.25 One year ahead CPI excluding food and energy 1.00 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 1.50 1.00 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 a. Annualized. b. Calculated by the Federal Reserve Bank of Cleveland. c. Mean expected change as measured by the University of Michigan’s Survey of Consumers. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; Federal Reserve Bank of Cleveland; and University of Michigan. The broad-based rise in retail prices, which began in March, was still evident in July. The Consumer Price Index (CPI) rose 5.5%; the core CPI, which excludes the presumably more volatile food and energy prices, rose a more modest 2.4% (annualized rate). The median CPI, which attempts to isolate inflation trends by focusing on the middle of the monthly price-change distribution, rose a brisk 4.4% (annualized rate). Longer-term growth trends in the core retail price measures inched up a bit further in July and are now 1/2 to 1 percentage point higher than in mid2005. The 12-month growth rate in the CPI excluding food and energy and the median CPI ticked up to 2.7% and 3.3%, respectively. The 12-month growth rate in the 16% trimmed-mean CPI remained at 2.9%. Meanwhile, short-term household inflation expectations have crept back to their highest levels since the months after Hurricane Katrina. Survey data from U.S. households in early August indicate that retail prices over the next 12 months are expected to rise 4.9%. On the other hand, longerterm expectations remain fairly steady, with households anticipating that prices will rise 3.5% annually over the next five to 10 years. One indicator of potential inflation pressure in the economy is unit labor costs: Higher labor costs, the theory goes, induce producers to raise (continued on next page) 3 • • • • • • • Inflation and Prices (cont.) Four-quarter percent change 6 UNIT LABOR COSTS Four-quarter percent change 9 COMPENSATION AND PRODUCTIVITY 5 8 7 4 Compensation per hour 6 3 5 2 4 1 3 0 2 Output per hour –1 1 –2 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 12-month percent change 3.50 CORE CPI AND FORECASTS, 12-MONTH GROWTH RATE IN DECEMBER a 3.25 Top 10 average 3.00 Bottom 10 average 2.75 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Average annual percent change 3.50 NONFARM BUSINESS PRODUCTIVITY GROWTH AND FORECAST a 3.25 Top 10 average 3.00 2.50 2.50 2.25 2.25 2.00 2.00 1.75 1.75 1.50 1.50 1.25 1.25 1.00 Bottom 10 average 2.75 1.00 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 1971– 1975 1976– 1980 1981– 1985 1986– 1990 1991– 1995 1996– 2000 2001– 2005 2006– 2010 FRB Cleveland • September 2006 a. Blue Chip panel of economists. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; and Blue Chip Financial Forecasts, September 1, 2006. prices. Growth in unit labor costs, defined as compensation growth adjusted for productivity growth, doubled from 1.6% in December 2005 to 3.2% in June 2006. This jump resulted primarily from accelerated compensation growth (which recently hit 5.7%, its highest four-quarter growth rate in more than five years), not a slowdown in productivity gains. The Blue Chip panel of economists anticipates that core CPI inflation will rise to about 23/4% this year—almost a full percentage point above its 2002–05 average—before moderating to a 2.4% rate in 2007. One factor that is likely to weigh heavily in this outlook is the future behavior of unit labor costs. Economists expect nonfarm business productivity to remain relatively strong over the next five years, growing at an average annual rate of 21/2%, which could help to keep unit labor costs in check. But the range of opinion concerning the core inflation outlook is pretty wide and may depend on the performance of compensation growth relative to productivity growth. If labor compensation growth slows significantly, or productivity growth accelerates, the inflation outlook is likely to be much improved. But of course, should the opposite occur—if labor compensation growth were to accelerate further or productivity growth to wane—the more pessimistic inflation scenario would gain credibility. 4 • • • • • • • Monetary Policy Percent 8 RESERVE MARKET RATES 7 Percent, daily 100 IMPLIED PROBABILITIES OF ALTERNATIVE TARGET FEDERAL FUNDS RATES, SEPTEMBER MEETING OUTCOME c 90 Effective federal funds rate a August 16: CPI August 4: employment report 80 6 70 5.25% 5 60 Intended federal funds rate b 4 50 5.50% Primary credit rate b 40 3 30 2 20 Discount rate b 1 5.75% 10 0 0 2000 2001 2002 2003 2004 2005 6/29 2006 Percent, daily 100 IMPLIED PROBABILITIES OF ALTERNATIVE TARGET FEDERAL FUNDS RATES, OCTOBER MEETING OUTCOME d 90 August 16: CPI August 14: PPI 7/06 7/13 7/20 8/03 7/27 2006 8/17 8/10 8/24 Percent 5.6 IMPLIED YIELDS ON FEDERAL FUNDS FUTURES e 5.5 June 30, 2006 f 80 5.25% 5.4 August 9, 2006 f 70 5.3 60 August 18, 2006 5.2 50 May 11, 2006 f 40 5.1 5.50% 30 5.0 20 5.75% 4.9 10 4.8 0 8/01 8/05 8/09 8/13 2006 8/17 8/21 May June July Aug. Sept. 2006 Oct. Nov. Dec. Jan. Feb. 2007 Mar. FRB Cleveland • September 2006 a. Weekly average of daily figures. b. Daily observations. c. Probabilities are calculated using trading-day closing prices from options on September 2006 federal funds futures that trade on the Chicago Board of Trade. d. Probabilities are calculated using trading-day closing prices from options on October 2006 federal funds futures that trade on the Chicago Board of Trade. e. All yields are from constant-maturity series. f. One day after the FOMC meeting. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15; Chicago Board of Trade; and Bloomberg Financial Information Services. On August 8, the Federal Open Market Committee (FOMC) voted to leave the federal funds rate at 5.25%, the first pause since June 2004. Its statement cited slower economic growth and cooling in the housing market as the main reasons. Although “readings on core inflation have been elevated in recent months,” the FOMC is confident that “inflation pressures seem likely to moderate over time.” The statement’s wording suggests that the path of future monetary policy is data dependent: “The extent and timing of any additional firming that may be needed to address these risks will depend on the evolution of the outlook for both inflation and economic growth, as implied by incoming information.” On August 3, participants in the federal funds options market placed the probability of no rate change at the September meeting at nearly 49%. The next day, after the employment report was released, that probability rose to almost 72%. By August 22, it had soared above 86%. The implied probabilities for the October 24 meeting have remained fairly constant since the August 16 CPI release: 72% odds of a 5.25% outcome and roughly 25% odds of a 25 basis point (bp) hike. Recent implied yields on federal funds futures echo this belief in a continued pause. The August 9 and August 18 implied yields are very similar, indicating a constant policy stance well into the first quarter of next year. (continued on next page) 5 • • • • • • • Monetary Policy (cont.) Percent 6.4 IMPLIED YIELDS ON EURODOLLAR FUTURES Percent 6 REAL FEDERAL FUNDS RATE b,c 6.2 5 May 11, 2006 a 6.0 4 3 5.8 June 30, 2006 a 2 5.6 August 9, 2006 a 5.4 1 August 18, 2006 5.2 0 5.0 –1 4.8 2005 2007 2009 2011 2013 2015 –2 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Percent, quarterly 8 TAYLOR RULE e Percent 10 PENNACCHI MODEL d 7 8 Effective federal funds rate 6 30-day Treasury Bill 6 5 Inflation target: 1% f f 4 4 3 2 Inflation target: 3% g 2 Estimated expected inflation rate 0 1 Estimated real interest rate –2 1990 0 1992 1994 1996 1998 2000 2002 2004 2006 1998 1999 2000 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 a. One day after FOMC meeting. b. Defined as the effective federal funds rate deflated by the core PCE. c. Shaded bars represent periods of recession. d. The estimated expected inflation rate and the estimated real interest rate are calculated using the Pennacchi model of inflation estimation and the median forecast for the GDP implicit price deflator from the Survey of Professional Forecasters. Monthly data are used. e. The formula for the implied funds rate is taken from the Federal Reserve Bank of St. Louis, Monetary Trends, January 2002, which is adapted from John B. Taylor, “Discretion versus Policy Rules in Practice,” Carnegie-Rochester Conference Series on Public Policy, vol. 39 (1993), pp.195–214. f. Assumes an interest rate of 2.5% and an inflation target of 1%. g. Assumes an interest rate of 1.5% and an inflation target of 3%. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15; Federal Reserve Bank of Philadelphia; and Bloomberg Financial Information Services. The implied yields on Eurodollar futures, which provide a longer-run gauge of expected monetary policy, are consistent with the federal funds rate pause indicated by the implied probabilities for the September meeting. However, long-term expectations suggest that the federal funds rate target will drop from 5.25% to 5.00% later in 2007. Real yields provide another policy gauge. The real federal funds rate, the effective rate deflated by the core personal consumption expenditures (PCE) price index, stands at roughly 2.5%. During the most recent tightening cycle, the real federal funds rate increased by roughly 360 bp. This movement in the real funds rate is corroborated by the Pennacchi model, which adjusts for inflation statistically, using survey expectations and estimates for both the expected inflation rate and the estimated real funds rate. The latter, at 2.5%, is the same as the estimate given by the PCE deflator and is 1 bp shy of 3% for the year ahead. The Taylor rule, which views the funds rate as reacting to a weighted average of inflation, target inflation, and economic growth, indicates the appropriateness of current monetary policy. According to this model, the current stance is consistent with an inflation target between 1% and 3%. 6 • • • • • • • Money and Financial Markets Percent, weekly average 5.5 YIELD CURVE Percent, weekly 7 SHORT-TERM INTEREST RATES 5.4 6 5.3 June 30, 2006 a Target federal funds rate 5 May 12, 2006 a 5.2 4 5.1 August 11, 2006 a Three-month Treasury bill b 3 One-year Treasury bill b 5.0 2 4.9 August 25, 2006 Six-month Treasury bill b 1 4.8 0 4.7 0 5 10 15 Years to maturity 20 1998 25 Percent, weekly 9 LONG-TERM INTEREST RATES 1999 2000 2001 2002 2003 2004 2005 2006 2005 2006 Percent, daily 12 YIELD SPREADS: CORPORATE BONDS MINUS THE 10-YEAR TREASURY NOTE c 10 8 Conventional mortgage 8 7 High yield 6 6 4 BBB 5 2 20-year Treasury bond b 4 AA 0 10-year Treasury note b 3 –2 1998 1999 2000 2001 2002 2003 2004 2005 2006 1998 1999 2000 2001 2002 2003 2004 FRB Cleveland • September 2006 a. The Friday after the FOMC meeting. b. Yields from constant-maturity series. c. Merrill Lynch AA, BBB, and High Yield Master II indexes, each minus the yield on the 10-year Treasury note. SOURCES: Board of Governors of the Federal Reserve System, “Selected Interest Rates,” Federal Reserve Statistical Releases, H.15; and Bloomberg Financial Information Services. Throughout the summer, the 10-year Treasury note yield has been below that of the one-year Treasury bill, implying an inverted yield curve in that range of maturities. In recent weeks, the gap between the two yields has increased to nearly 20 basis points (bp). Short-term rates have risen in step with increases in the federal funds rate. Since the current round of policy tightening began in June 2004, the 90-day Treasury bill rate has increased nearly 380 bp. Nominal yields on long-term Treasury securities rose by about 80 bp during the first half of the year, but have since fallen back about 30 bp. After rising more than one full percentage point from September 2005 through mid-July 2006, long-term rates on conventional mortgages also drifted downward nearly 30 bp during the last month. The earlier mortgage rate increases have taken a toll on sales of new and existing homes in the last several months. The strength and liquidity of corporate balance sheets have kept risk premiums on their debt at historically low levels. Since early 2004, risk spreads on AA- and BBB-rated corporate debt have remained fairly flat, but risk premiums on lower-rated corporate debt have been more volatile. From mid-May to mid-July, the risk spread on high-yield corporate bonds increased more than 60 bp. Since mid-2005, the U.S. personal saving rate has resided in negative territory. As of 2006:IIQ, it stood at (continued on next page) 7 • • • • • • • Money and Financial Markets (cont.) Ratio 7 HOUSEHOLD FINANCIAL POSITION Percent of income 15 Four-quarter percent change 24 OUTSTANDING DEBT 21 Revolving consumer credit 18 10 6 Personal saving rate Home mortgages 15 12 9 5 5 6 3 Wealth-to-income ratio a 0 4 0 –3 Nonrevolving consumer credit –6 3 –5 1980 1985 1990 1995 2000 –9 1991 2005 1993 1995 1997 1999 2001 2003 Index, 1985 = 100 155 CONSUMER ATTITUDES Percent of average loan balances 13 DELINQUENCY RATES 2005 Index, 1966:IQ = 100 115 12 Consumer sentiment, University of Michigan b 11 135 105 115 95 95 85 75 75 10 Commercial real estate loans 9 8 7 6 Commercial and industrial loans Credit cards 5 4 3 2 Consumer confidence, Conference Board Residential real estate loans 1 0 1991 55 1993 1995 1997 1999 2001 2003 2005 65 2000 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 a. Wealth is defined as household net worth; income is defined as personal disposable income. b. Data are not seasonally adjusted. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; Board of Governors of the Federal Reserve System, “Flow of Funds Accounts of the United States,” Federal Reserve Statistical Releases, Z.1; University of Michigan; and the Conference Board. –1.5%. For the last 25 years, the saving rate has displayed a significant downward trend. Whereas the personal saving rate averaged 9% in the 1980s, its average from 2000 to the present was only 1.5%. Counterbalancing this is an upward trend in the wealth-to-income ratio over the same period. Higher levels of wealth have supported a higher level of spending relative to income. Since 2002:IQ, mortgage debt has grown at annual rates exceeding 10%. Outstanding home mortgage debt grew at a year-to-year rate of nearly 15% in 2006:IQ, partly because households extracted their accumulated gains in home equity. This has slowed consumer credit growth. Despite high levels of consumer debt, delinquency rates on residential mortgages remain subdued by historical standards. The Conference Board’s Index of Consumer Confidence rose modestly in July. Most of the increase came from a rise in the expectations component of the index, although the present- conditions component also posted an increase. In the survey, consumers viewed labor markets as strong and indicated a greater propensity to buy homes and autos in the coming months. The University of Michigan’s Consumer Sentiment Index remained basically unchanged in July, but its preliminary August value shows marked deterioration. The expectations component, which dominated this decline, reached its lowest level since 1992. 8 • • • • • • • The U.S. Trade Balance Billions of dollars –70 BALANCE OF TRADE Billions of dollars 200 IMPORTS AND EXPORTS 180 –65 160 –60 Imports 140 –55 120 –50 100 Exports –45 80 –40 60 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June 2005 2006 1996 1997 1998 1999 2000 Index, March 1973 = 100 Billions of dollars 0 BALANCE OF TRADE AND REAL BROAD DOLLAR INDEX 120 –10 115 Balance of trade –20 2001 2002 2003 2004 2005 2006 Billions of dollars 60 IMPORTS AND EXPORTS OF GOODS Exports Imports 50 110 40 –30 105 30 –40 100 –50 95 20 Real Broad Dollar Index –60 90 –70 85 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 10 0 North America Europe Africa Pacific Rim East Asia South Central and Asia South America FRB Cleveland • September 2006 SOURCES: U.S. Department of Commerce, Census Bureau; and Board of Governors of the Federal Reserve System, “Foreign Exchange Rates,” Federal Reserve Statistical Releases, H.10. The nominal U.S. trade deficit reached an all-time high of $66.6 billion in October 2005. Many believe that Hurricane Katrina caused imports and exports—which generally move in the same direction—to diverge as imports increased and exports decreased, creating a sizable jump in the trade deficit. The deficit remains far above its pre-Katrina level, although it has fallen in four of the last eight months. In June, it narrowed slightly from $65.0 billion to $64.8 billion. While $0.2 billion is not a substantial one-month decrease, in real terms the June deficit is down more than 4% from its peak. The June deficit decrease occurred because export growth (2.0%) exceeded import growth (1.2%). Export growth, which fell after Katrina, has strengthened again, attaining an average monthly rate of nearly 1.3%. This rate is strong in the sense that export growth over the past 10 years has averaged only 0.5% a month. In contrast, import growth following Katrina has been close to its trend of the past 10 years: Since last September, import growth has averaged 0.8% per month, compared to the 10-year average of 0.7%. From 2002 through 2004, the dollar depreciated sharply. At the same time, the U.S. trade deficit continued to widen. This may seem counterintuitive: One would expect that as the dollar’s value falls relative to other currencies, foreign demand for U.S. (continued on next page) 9 • • • • • • • The U.S. Trade Balance (cont.) JUNE 1996 EXPORTS JUNE 2006 EXPORTS Capital goods 28.8% Capital goods 28.7% Automotive 7.6% Industrial supplies 17.0% Automotive 7.4% Industrial supplies 19.5% Consumer goods 8.1% Consumer goods 8.9% Food 6.7% Services 27.6% Services 28.1% Food 4.7% Other goods 2.8% Other goods 4.3% JUNE 1996 IMPORTS JUNE 2006 IMPORTS Capital goods 23.9% Automotive 13.9% Industrial supplies 21.7% Food 3.8% Services 15.8% Capital goods 18.7% Industrial supplies 28.1% Automotive 11.9% Consumer goods 19.9% Consumer goods 18.1% Food 3.3% Services 15.5% Other goods 2.7% Other goods 2.8% FRB Cleveland • September 2006 SOURCE: U.S. Department of Commerce, Census Bureau. goods would increase and U.S. demand for foreign goods would decrease. One possible explanation for a growing trade deficit during a period of dollar depreciation is that the U.S.’s strong economic growth stimulated foreigners’ appetite for our assets. Holding all else constant, an increase in foreigners’ holdings of U.S. assets would worsen the trade balance. In June, the Pacific Rim region was the largest exporter of goods to the U.S., with Europe and the North American region not far behind. On the other hand, the largest importer of U.S. goods was the North American region, while Europe and the Pacific Rim were virtually tied for imports of U.S. goods. Interestingly enough, the composition of our export products has not shifted significantly in the last 10 years. Aside from a decrease in food and other goods as a percent of exports and an increase in industrial supplies, little has changed. Imports have been slightly more dynamic over the last 10 years. Industrial supplies and consumer goods have increased substantially as a share of total imports, whereas capital goods and automotive imports have declined. Still, considering how much the U.S. economy has changed in the last 10 years, it is surprising that the overall makeup of our imports and exports has changed so little. 10 • • • • • • • Economic Activity Annualized percent change 8 REAL GDP a Annualized percent change 10 NOMINAL GDP a 7 9 Revised 8 6 7 5 Vintage 4 6 Vintage 5 3 Revised 4 2 3 1 0 2 2002 2003 2004 2005 Annualized percent change 11 PRODUCTIVITY a 2002 2003 2004 2005 Annual percent change 3.0 CORE PCE b 10 9 Revised Vintage before 2006 revision Vintage before 2005 revision 2.5 8 7 2.0 6 Revised Vintage 5 1.5 4 3 1.0 2 1 0.5 0 –1 2002 0 2003 2004 2005 2003 2004 2005 FRB Cleveland • September 2006 a. “Vintage” refers to the series before the July 2006 BEA revisions; “revised” designates the current series values. b. The 2006 vintage series was revised July 2006 by the BEA and the 2005 vintage was revised July 2005. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; and Haver Analytics. Sometimes it’s what you thought you knew that hurts the most. On July 28, the Bureau of Economic Analysis released one of its regular revisions in the National Income and Product Accounts, a data series that includes the most comprehensive available estimates of U.S. economic activity. The revisions cover the years 2003 through 2005, and the first quarter of 2006. The most recent revision did not much change the view of nominal GDP growth—the change in the dollar value of production growth. Before the revision, the data were telling us that quarterly growth from 2002:IVQ through 2006:IQ averaged about 6.6%. The July revisions, which “incorporate source data that are more complete, more detailed, and otherwise more reliable than those previously available,” barely changed that number. The changes in estimates of real, or inflation-adjusted, GDP growth were a bit more substantial. The estimated average quarterly growth fell by about 1/ 4 of a percentage point, from 3.83% to 3.59%. Labor productivity growth fell by a comparable amount, from a prerevision estimate of 3.44% per quarter (annualized) to 3.15%, which represents the truth as we know it now. The July revision marks the second time in two years that the Personal Consumption Expenditure price index has changed. Just as revisions have lowered our guesses about real growth in the past several years, so have they raised our estimates of the pace at which prices have been rising. If only it were the other way around. 11 • • • • • • • Housing Markets Units per thousand people 3.3 EXISTING HOME SALES ADJUSTED FOR POPULATION a,b,c Units per thousand people 6.5 NEW HOME SALES ADJUSTED FOR POPULATION a,b,c 6.0 3.1 5.5 5.0 2.9 4.5 4.0 2.7 3.5 3.0 2.5 2.5 2.3 1999 2000 2001 2002 2003 2004 2005 2006 Thousands of dollars 270 MEDIAN PRICE OF HOUSING a,d 2.0 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Thousands of units 1,800 INVENTORY OF UNSOLD HOMES a,d 250 1,600 230 New home sales 210 1,400 190 170 1,200 Existing home sales 150 130 2000 1,000 2001 2002 2003 2004 2005 2006 2000 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 a. Shaded bars indicate recessions. b. Adjustment based on civilian non-institutional population 16 years and older. c. Seasonally adjusted at annual rates. d. Quarterly data. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; U.S. Census Bureau; and U.S. Department of Labor, Bureau of Labor Statistics. In case you haven’t heard, the Great Housing Boom of the Early Millennium appears to be over. Certainly the July data for both existing and new home sales disappointed most expectations, which were modest to begin with. As reported by the National Association of Realtors, total existing home sales—which include single-family homes, town houses, condominiums, and co-ops—fell 4.1% in July relative to June and 11.2% relative to July 2005. The U.S. Census Bureau reported that sales of new single-family homes in July 2006 were 4.3% below the June rate and 21.6% below the July 2005 estimate. The softening of the housing market has resulted in second-quarter prices that were up modestly for existing homes and down slightly for new ones. Despite clear signals that residential housing markets have cooled off after the torrid pace of the last several years, unit sales remain above their pre-boom levels, and significant generalized price declines have yet to materialize. In the historical context, activity thus far continues at a reasonably solid pace. Nonetheless, the trend in sales is clearly negative, and builders’ confidence is on the wane: In August, the Wells Fargo/National Association of Home Builders index fell to its lowest level since early 1991. Furthermore, the inventory of unsold homes has been climbing steadily since the beginning of 2005, which may well indicate that the bottom of the market has yet to be found. 12 • • • • • • • Labor Markets Change, thousands of workers 450 AVERAGE MONTHLY NONFARM EMPLOYMENT CHANGE Labor Market Conditions 400 Average monthly change (thousands of employees, NAICS) Revised 350 Preliminary estimate 300 Payroll employment 250 Goods producing Construction Manufacturing Durable goods Nondurable goods 200 150 Service providing Retail trade Financial activitiesa PBSb Temporary help svcs. Education & health svcs. Leisure & hospitality Government 100 50 0 –50 Jan.– July August 2006 2006 142 128 2003 9 2004 175 2005 165 –42 10 –51 –32 –19 28 26 0 9 –9 22 25 –6 1 –7 20 13 2 6 –4 10 17 –11 –8 –3 51 –4 7 23 12 30 19 –4 147 17 8 40 13 33 26 13 143 13 12 41 14 31 21 14 122 –11 14 35 –3 32 23 13 118 –14 10 26 3 60 10 17 Average for period (percent) –100 Civilian unemployment rate –150 2002 2003 2004 2005 IIIQ IVQ 2005 IQ IIQ June 2006 6.0 5.5 5.1 4.7 4.7 July August 2006 Percent 65.0 LABOR MARKET INDICATORS Percent 6.5 Percent 90 LABOR MARKET PARTICIPATION c,d 85 Employment-to-population ratio Male (16-44) 64.5 6.0 80 Male (total) 75 5.5 64.0 70 Female (16-44) 65 63.5 5.0 60 55 Male (45 and older) Female (total) 63.0 4.5 50 45 4.0 62.5 Female (45 and older) 40 Civilian unemployment rate 35 3.5 62.0 1995 1997 1999 2001 2003 2005 30 1980 1984 1988 1992 1996 2000 2004 FRB Cleveland • September 2006 a. Financial activities include the finance, insurance, and real estate sector and the rental and leasing sector. b. Professional and business services include professional, scientific, and technical services, management of companies and enterprises, administrative and support, and waste management and remediation services. c. Seasonally adjusted. d. Shaded bars represent recessions. SOURCE: U.S. Department of Labor, Bureau of Labor Statistics. Nonfarm payrolls increased by 128,000 in August, a number identical to the three-month average of 128,000. Service-producing industries drove the increase, adding 118,000 jobs. Health and education services accounted for almost half of the increase (60,000), largely from an addition of 34,800 jobs in health care. Manufacturing’s job losses lessened from –24,000 in July to –11,000 in August, contributing to the overall improvement in employment. The biggest drag on employment was retail trade, which decreased by 13,500 jobs. Temporary help services, often considered an indicator of the labor market’s future condition, continues to show little or no growth. This steady growth is boosting employment by just over 1% per year. Because the U.S. population is also increasing by just over 1% annually, this growth absorbs new workers as long as the participation rate stays fixed. Indeed, the civilian unemployment rate was essentially unchanged (creeping from 4.8% to 4.7%), and the labor force participation rate held at 66.2%. The employment-to-population ratio remained almost unchanged at 63.1%. Labor participation rates have been stable recently, but there have been some important shifts within demographic groups. Young men and women have both been participating at significantly lower rates since the 2001 recession. In contrast, older workers of both sexes have increased their labor force participation. The future path of these supply trends will be an important determinant of how much employment growth will occur from month to month. 13 • • • • • • • Labor Utilization Four-quarter percent change 8 COMPONENTS OF COMPENSATION Percent 12 UNEMPLOYMENT RATES BY INDUSTRY Benefits c 10 Leisure and hospitality Construction 6 8 PBS a Total compensation c 4 6 All occupations b Manufacturing Wages and salaries c 4 2 Education and health services 2 0 0 2000 2001 2002 2003 2004 2005 2006 2000 2001 2002 2003 2004 2005 Four-quarter percent change 7 COMPENSATION IN GOODS-PRODUCING INDUSTRIES Four-quarter percent change 7 COMPENSATION IN SERVICE-PROVIDING INDUSTRIES 6 6 Construction Manufacturing 2006 Education and health services 5 5 All service-providing industries 4 4 3 3 All goods-producing industries Leisure and hospitality 2 2 PBS a 1 2000 2001 2002 2003 2004 2005 2006 1 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 NOTE: All data are seasonally adjusted. a. Professional and business services. b. All civilian workers. c. Private industry workers in constant dollars SOURCE: U.S. Department of Labor, Bureau of Labor Statistics. At its August 8 meeting, the Federal Open Market Committee (FOMC) expressed concern that “high levels of resource utilization” could potentially sustain inflation. Growing labor utilization is reflected in falling unemployment rates. Although the most recent monthly data show a slight increase in the unemployment rate (from 4.6% in June to 4.8% in July), this measure has been trending downward for several years, as more and more workers are re-absorbed into the labor force. Nevertheless, unemployment rates can vary considerably across industries. For several years, rates in construction, leisure and hospitality, and professional and business services have all been above the all-industry average. By contrast, the manufacturing sector’s unemployment rate has been about average, while the rate in education and health services was below average. Despite the general increase in labor utilization, workers’ compensation gains, as measured by the Employment Cost Index, have been trending down in recent years because of dramatic declines in benefit gains. As of 2006:IIQ, the index was up 2.8% from a year earlier; this compares to annual increases on the order of 41/2% in 2000. Goods producers have generally seen sharper reductions in compensation gains than their service-providing counterparts. The exception was professional and business services, where compensation gains began to tumble in 2004, though this trend has reversed in recent quarters. 14 • • • • • • • Fourth District Employment Percent 8.5 UNEMPLOYMENT RATES, 1990–2006 a Percent 8 UNEMPLOYMENT RATES, 2000–2006 a,c 8.0 7.5 7 Kentucky 7.0 Ohio 6.5 6 6.0 Pennsylvania U.S. 5.5 5 5.0 Fourth District b 4.5 4 West Virginia 4.0 3.5 3 1990 1993 1996 1999 2002 2005 CHANGE IN UNEMPLOYMENT, JUNE TO JULY 2006 b 2000 2001 2002 2003 2004 2005 2006 TOTAL WAGE BILL FOR TRANSPORTATION EQUIPMENT MANUFACTURING, 2005 Unemployment increased by at least 1,000 people At least $200 million FRB Cleveland • September 2006 a. Shaded bars represent recessions. b. Seasonally adjusted using the Census Bureau’s X-11 procedure. c. Seasonally adjusted. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; U.S. Department of Labor, Bureau of Labor Statistics and Employment and Training Administration; Kentucky Office of Employment and Training, Workforce Kentucky; Ohio Department of Job and Family Services, Bureau of Labor Market Information; Ohio Department of Job and Family Services, Worker Adjustment Retraining Notification Act; Pennsylvania Department of Labor and Industry, Center for Workforce Information and Analysis; and West Virginia Bureau of Employment Programs, Workforce West Virginia. The Fourth District’s unemployment rate was 5.7% in July, up sharply from 5.1% a month earlier. Although the District is still below its recent peak of 6.5% in June 2003, the jump of 0.6 percentage point (pp) is its largest one-month increase on record. By comparison, the U.S. unemployment rate was 4.8% in July, up 0.2 pp from June. Over the month, the District’s employment fell 0.4%, the labor force increased 0.1%, and unemployment rose 11.5%. Unemployment rates went up in all Fourth District states, substantially in some. Pennsylvania’s rate was nearly stable (up just 0.1 pp to 4.8%), but rates in West Virginia and Kentucky each rose 0.5 pp over the month, reaching 5.4% and 6.3%, respectively. Ohio’s unemployment rate, still more dramatically, leaped 0.7 pp to 5.8%. Although local labor force data can be volatile and subject to revision, for Ohio, at least, there is other evidence to substantiate the unemployment increase shown in that data. First, Ohio unemployment claims jumped substantially in early July, which the U.S. Department of Labor attributed to “layoffs in the automobile and transportation equipment industries.” Second, the state’s Worker Adjustment Retraining Notification system, which lists employers that plan to lay off 50 workers or more, showed many such layoffs scheduled for late June and early July. Finally, the counties posting the steepest unemployment increases have large assembly plants or auto parts suppliers. In Ohio, the surge in the unemployment rate does seem to result from recent layoffs and spillover in the auto industry. 15 • • • • • • • The Dayton Metropolitan Statistical Area Index, March 2001 = 100 104 PAYROLL EMPLOYMENT SINCE MARCH 2001 b LOCATION QUOTIENTS, 2005 DAYTON MSA/U.S. a Natural resources, mining, and construction 102 U.S. Manufacturing Trade, transportation, and utilities 100 Information Financial activities 98 Professional and business services Ohio Education and health services 96 Leisure and hospitality Dayton MSA Other services 94 Government 92 0 0.5 1.0 1.5 2001 Percent change 2 COMPONENTS OF EMPLOYMENT GROWTH, DAYTON MSA c 2002 2003 2004 2005 PAYROLL EMPLOYMENT GROWTH Total nonfarm 2006 Dayton MSA U.S. U.S. 1 Goods-producing Manufacturing Natural resources, mining, and construction 0 Service-providing Trade, transportation, and utilities –1 Information Dayton MSA Financial activities Professional and business services Financial, information, and business services Education, health, leisure, government, and other services Retail and wholesale trade Manufacturing –2 –3 Educational and health services Leisure and hospitality Other services Natural resources, mining, and construction Government Transportation, warehousing, and utilities –4 2001 2002 2003 2004 2005 –4 –3 –2 0 –1 1 2 12-month percent change, July 2006 3 4 FRB Cleveland • September 2006 NOTE: The Dayton metropolitan statistical area (MSA) consists of Greene, Miami, Montgomery, and Preble counties. a. The location quotient is the simple ratio between two locations of a given industry’s employment share. b. Seasonally adjusted. c. Lines represent total employment growth for the U.S. and the Dayton MSA. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; and the Dayton Area Chamber of Commerce. Like many other Fourth District metropolitan areas, Dayton is more focused on manufacturing than the U.S.: The metro area has proportionately more manufacturing workers. And with over 35 institutions of higher learning, Dayton’s share of total employment in the educational and health services industry is also greater than the nation’s. Since the last business cycle peak, in March 2001, Dayton has shed 6% of its jobs. Whereas Ohio and the nation started experiencing employment growth toward the end of 2003, Dayton’s employment base continued to erode. A look at the components of employment growth suggests the reasons: Manufacturing has been a drag on total employment growth in each of the last five years. To a lesser extent, retail and wholesale trade also subtracted from employment growth during that period. By contrast, education, health, leisure, government, and other services made positive contributions in four of the last five years. Since July 2005, Dayton has lost 0.5% of its jobs, compared to the nation’s gain of 1.3%. The metro area’s manufacturing, trade, transportation and utilities, information, and financial activities industries all posted sizeable declines in the number of jobs over the past year. In only three industries (leisure and hospitality, other services, and government) did Dayton outpace the nation’s annual employment growth. (continued on next page) 16 • • • • • • • The Dayton Metropolitan Statistical Area (cont.) Index, 1990:QI = 100 9 UNEMPLOYMENT RATES a,b Percent 2 POPULATION GROWTH 8 U.S. U.S. 7 1 Ohio 6 5 0 Ohio Dayton MSA c 4 Dayton MSA 3 1990 1992 1994 1996 1998 2000 2002 2004 2006 1985 1990 1995 2000 2005 Thousands of dollars 40 PER CAPITA PERSONAL INCOME Selected Demographics, 2005 U.S. Dayton MSA Ohio U.S. 0.8 11.2 288.3 White Black Other 82.8 15.4 1.8 85.7 12.3 2.0 76.3 12.8 10.9 0–19 years 20–34 years 35–64 years 65 or older 26.6 18.8 41.2 13.4 27.0 19.3 40.8 12.8 27.9 20.1 40.0 12.1 Percent with bachelor’s degree or higher 24.0 23.3 27.2 Median age 38.6 37.6 36.4 Total population (millions) –1 1980 30 U.S. metropolitan areas Dayton MSA 20 Ohio 10 1980 1985 1990 1995 2000 2005 FRB Cleveland • September 2006 NOTE: The Dayton metropolitan statistical area (MSA) consists of Greene, Miami, Montgomery, and Preble counties. a. Shaded areas represent recessions. b. Seasonally adjusted. c. The July unemployment rate for Dayton is calculated by the Federal Reserve Bank of Cleveland and based on county unemployment and labor force data. SOURCES: U.S. Department of Commerce, Bureau of the Census; and Bureau of Economic Analysis; U.S. Department of Labor, Bureau of Labor Statistics; and Ohio Department of Job and Family Services, Office of Workforce Development. Throughout much of the 1990s, the metro area’s unemployment rate was lower than both the nation’s and the state’s. Since the most recent business cycle peak, however, its unemployment rate has tracked Ohio’s more closely. Like Ohio’s, its rate spiked in July: Dayton’s rate jumped to 6.5% from 5.3% in June. One reason the metro area’s employment rate has followed Ohio’s closely in recent years, even as its employment growth has trailed the state’s, may be the decline in Dayton’s labor force (its negative population growth suggests this as well). Indeed, its population growth has trailed both the state and the nation since 1988. Not surprisingly, Dayton’s social and demographic characteristics are closer to the state’s than to the nation’s. Like Ohio, Dayton has a smaller percentage of minorities than the U.S. has. As for education, its share of residents aged 25 and older with a bachelor’s degree (24.0%) lies between the state’s (23.3%) and the nation’s (27.2%). Dayton’s population is older than both Ohio’s and the nation’s, as evidenced by its larger share of population 65 and older and its higher median age. In 2004, Dayton’s per capita personal income was $31,400, roughly the same as Ohio’s, but well below the average of all U.S. metropolitan areas and the nation as a whole. 17 • • • • • • • Mortgage Lending Percent 80 Billions of dollars 1,400 MORTGAGE ORIGINATIONS Originations 1,200 Percent 20 MORTGAGE AND COMMERCIAL LENDING BY COMMERCIAL BANKS 70 18 60 16 50 14 Refinancing share 1,000 800 One-to-four-family residential mortgages/assets 40 12 30 10 20 8 10 6 Commercial and industrial loans/assets 600 400 Mortgage-backed securities/assets 200 0 1996 0 1999 2002 2005 4 1996 1998 2000 2002 Percent 5.0 SPREAD: EFFECTIVE MORTGAGE RATE OVER COST OF FUNDS ARMs, percent 45 ADJUSTABLE-RATE MORTGAGES 4.5 40 2004 2006 Spread, percent 3.5 3.0 10-year/one-year Treasury spread 35 4.0 2.5 FRM/ARM spread 30 2.0 25 1.5 20 1.0 15 0.5 3.5 3.0 2.5 2.0 10 0 ARMs in originations 1.5 5 1.0 –0.5 –1.0 0 1996 1998 2000 2002 2004 2006 1996 1998 2000 2002 2004 2006 FRB Cleveland • September 2006 SOURCES: U.S. Department of the Treasury, Office of Thrift Supervision; Federal Housing Finance Board; Federal Financial Institutions Examination Council, Quarterly Bank Reports on Condition and Income; Federal Home Loan Mortgage Corporation; and Mortgage Bankers Association. Mortgage bankers originated $590 billion of new mortgages in 2006:IQ and $633 billion in 2006:IIQ, the lowest first- and second-quarter increases since 2002. Rising mortgage rates left little incentive for new refinancings, which constituted 35% of originations in 2006:IIQ, a significant drop from their peak share of 74% in 2002:IVQ. The share of mortgage-related assets (mortgages and mortgage-backed securities) on banks’ balance sheets has tapered off in recent quarters but is still at historically high levels. Currently, mortgage-related assets make up 29% of commercial banks’ assets. Mortgage loan profitability, as approximated by the spread of the effective mortgage rate (interest plus fees) over savings banks’ cost of funds, has been stable at about 3.44% since fall 2003. The cost of funds has risen in step with the increase in the federal funds rate, but banks were able to maintain their lending margins on these loans. Since their peak in popularity, the share of adjustable-rate mortgages (ARMs) in total originations has decreased steadily from 40% in June 2004 to 27% in June 2006. ARMs depend on short-term rates, whereas fixed-rate mortgages (FRMs) depend on long-term rates. ARMs’ drop in popularity resulted primarily from the rise in short-term rates and the decrease in the spread between fixed and adjustable mortgage rates. 18 • • • • • • • FDIC Funds Percent of insured deposits 1.75 FUND RESERVE RATIO 1.70 Billions of dollars 5,000 FDIC-INSURED DEPOSITS 4,500 1.65 4,000 1.60 1.55 3,500 Target 1.50 3,000 1.45 1.40 2,500 1.35 1.30 2,000 1.25 1,500 1.20 1,000 1.15 1.10 500 1.05 1.00 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Number of institutions 40 FAILED INSTITUTIONS Total assets, billions of dollars 3.2 35 2.8 SAIF number BIF assets SAIF assets 30 Number of institutions 280 PROBLEM INSTITUTIONS Total assets, billions of dollars 40 35 240 BIF assets SAIF assets 2.4 30 200 25 2.0 25 160 20 1.6 15 1.2 20 120 15 BIF number 80 10 0.8 5 0.4 10 SAIF number 40 5 BIF number 0 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 0 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 FRB Cleveland • September 2006 SOURCE: Federal Deposit Insurance Corporation, Quarterly Banking Profile, various issues. FDIC-insured deposits grew 3.7% in the first two quarters of 2006. The insurance fund’s reserve-to-deposit ratio fell to 1.23%, partly because insured deposits increased after April 1, when the Federal Deposit Insurance Reform Act of 2005 raised the insurance limit for retirement accounts from $100,000 to $250,000. In addition, the FDIC changed its target for the reserve-to-deposit ratio from 1.25% to a range between 1.15% and 1.50% in 2006; its board of directors can now manage the pace at which the reserve ratio varies within this range. The law also ended the separation between the Bank Insurance Fund and the Savings Association Insurance Fund, merging them into a single Deposit Insurance Fund (DIF). Since 1995, bank failures have been miniscule in terms of both numbers and total assets of failed institutions. No insured institution failed during the first half of 2006; 2006:IIQ was the eighth consecutive quarter without a failure of an FDIC-insured institution, marking the longest failure-free period since the inception of federal deposit insurance. At mid-2006, the number of problem institutions (those with substandard examination ratings) dropped to a historic low of 50, the smallest number in the 36 years for which data are available. Total assets of problem institutions declined from $6.61 billion to $5.50 billion over the same period. The low number of problem institutions and the low value of their assets suggest that the DIF’s losses should remain low in the near future.
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