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The Regional Economist January 2007 n www.stlouisfed.org President’s Message “ The council members also give us a better idea of what lies ahead than can the formal data, which primarily tell us about the recent past.” William Poole President and CEO, Federal Reserve Bank of St. Louis Industry Councils Bring Firsthand Insights to Our Regional Economic Outlook I suspect that when most people think about a meeting of the Federal Open Market Committee (FOMC), they picture a room full of economists toiling over stacks of data and picking out statistics with a finetooth comb. There is some truth in that, but there is another side of monetary policymaking that is far more art than science: collecting and analyzing informal, or anecdotal, information. Among the informal sources regularly used are the economic reports from the directors of the 12 Federal Reserve banks and their branches. The banks also maintain a network of industry contacts that are consulted on a regular basis in advance of FOMC meetings; the acquired information is used to produce the Summary of Commentary on Current Economic Conditions, commonly known as the Beige Book. One new source for this anecdotal information is the St. Louis Fed’s Eighth District Industry Councils. We began this program in June to help us gather the economic insights important to gauging the overall health of the regional economy. We set up four councils, each focusing on an industrial sector that is important to our area. Each council is anchored in a St. Louis Fed office that is a natural fit for that industry. The four councils, along with their “home office,” are: health care (Louisville), transportation (Memphis), agribusiness (Little Rock) and real estate (St. Louis). We recruited top-level executives, busi- ness owners and academics for these councils, 32 members in all. Already, the councils have met twice with me and Fed staff. Hearing reports on trends from the real experts—the people who are making day-to-day business decisions—is extremely useful because such information helps us clearly see what is happening in the economy and helps us understand the fluctuations in formal data. The council members also give us a better idea of what lies ahead than can the formal data, which primarily tell us about the recent past. Because discussion in these meetings is confidential, we can focus on issues that may not have been reported in the mainstream news or accounted for in the formal data. This information from the trenches, so to speak, helps me to identify emerging trends before situations occur and before trends appear in official data. During the most recent Industry Council meetings, for example, I heard some valuable information. I conveyed this information to the FOMC when we met the following week. Although I can’t share the exact nature of the information, I can tell you that similar rumblings were being heard on this matter from other Fed districts. As a result, Fed economists across the country are polling executives in the affected industry for more information. Although the main reason industry experts serve on our councils is to [3] help us steer the economy, they get something for themselves out of their service. They meet other leaders in the same industry and find out what they are doing. As Bert Greenwalt, a member of the Agribusiness Council, notes, “It is always interesting to compare the similarities and differences among the group.” In addition, council members learn a good deal about the Fed and what makes the economy tick. “Presentations by the Fed staff and president increase council members’ understanding of macroeconomic issues and help us explain the Fed’s mission and tools to our friends and industry colleagues,” says the farmer and Arkansas State University professor. The efforts of our council members reflect the importance of the Fed’s public-private partnership, in which a federal agency—the Fed’s Board of Governors—and the 12 quasi-public Reserve banks conduct monetary policy together. In forming our outlook for the economy, the Fed gets direct input from public citizens who serve on our boards of directors and on groups such as our Industry Councils. This structure and this public involvement make the Federal Reserve’s decentralized approach to monetary policymaking so effective, as well as unique among the world’s central banks. The Regional Economist January 2007 n www.stlouisfed.org The Taking of Prosperity? Kelo vs. New London and the Economics of Eminent Domain By Thomas A. Garrett and Paul Rothstein The U.S. Supreme Court’s decision in Kelo vs. New London was an unlikely source of public outrage. After all, the court didn’t overturn anything in its June 2005 ruling; it merely affirmed an earlier decision by the Supreme Court of Connecticut. That decision allowed the city of New London, which was officially designated as “distressed,” to use the power of eminent domain to acquire 15 properties, one of which belonged to homeowner Susette Kelo. Although forcing the sale of homes always raises delicate issues, it is not an unusual event. Furthermore, nothing in the court’s decision altered the ability of state legislatures to limit the practice of eminent domain. Viewed in this way, the decision in Kelo should have been one of the lower-profile decisions of the Supreme Court that year. That’s not how things went, however. The reaction against both the court and its decision was swift and furious. The U.S. House of Representatives passed a resolution denouncing the court.1 The House also passed a bill that would withhold federal development funds from states and political subdivisions that use eminent domain in certain ways.2 Since the Kelo decision, 34 states have taken action to limit eminent domain: 26 have passed statutes, five have passed constitutional amendments and an additional three have passed both. (Five of the seven states in the Eighth Federal Reserve District have passed statutes.3) President Bush issued an executive order limiting the grounds on which the federal government can take private property.4 Finally, the Supreme Court of Ohio handed down a ruling in a case that, by the court’s own assessment, raises social and legal issues similar to those in Kelo.5 Drawing upon the reasoning of several [5] dissenting judges in the Kelo case, the Supreme Court of Ohio gave property owners the protection that was denied to Susette Kelo in Connecticut. This brief survey of the response to Kelo suggests that its shock waves are likely to reverberate for some time. Nevertheless, we are far enough beyond the Kelo ruling that we can review the main issues with the knowledge that the most speculative and feared consequences of Kelo—free-for-all takings for economic development—have not yet occurred. A History of Eminent Domain The U.S. Supreme Court has long recognized in the federal government the power to acquire private property for public use. This is true even though the term “eminent domain”does not appear in the Constitution or the amendments.6 The power is limited, however, by two restrictions. First, as with any federal action, the use of eminent domain must be “necessary and proper” in accordance with the congressional powers enumerated in Article 1, Section 8, of the Constitution. Second, the use of eminent domain must obey the final clause of the Fifth Amendment, which states, “Nor shall private property be taken for public use, without just compensation.” The Fifth Amendment did not apply to state governments prior to the 14th Amendment. By the late 19th century, however, the due process clause of the 14th Amendment came to be regarded as requiring the states’ use of eminent domain to be consistent with federal interpretations of public use and just compensation. A state is free to establish a more-restrictive concept of public use than the U.S. Supreme Court finds in the Fifth Amendment, just as a state could require “more than” just compensation for a taking, but not a less-restrictive concept. Although state governments have the legal ability to establish, to some degree, their own laws regarding eminent domain, local governments like that of the city of New London have only those powers granted to them by state constitutions and statutes. Although Susette Kelo’s house was in a distressed city, neither her house nor any of the other properties was in poor condition. Rather, the city acted under the authority of a Connecticut statute that (more or less) explicitly declared that the taking of land for purposes of economic development was a taking for public use. The city’s economic development plan designated the parcels for office space, parking and retail services. This scenario highlights the central issues of the Kelo case: What is a “public use,”and does the answer to this question given by a state legislature matter? [6] Public Use, Public Purpose and Judicial Deference In its majority opinion, the U.S. Supreme Court stated in Kelo that the government can never take property from one private party for the sole purpose of giving it to another, even if just compensation is paid. On the other hand, the government can always do so if the general public acquires some actual use of the property. The court has been defining the ground between these extremes since the late 19th century.7 From the start, “it embraced the broader and more natural interpretation of public use as ‘public purpose,’ ” the court said in Kelo.8 More precisely, the court began to argue in the late 1800s that if property is taken to create a widespread benefit, then it is “put to”a public use and satisfies this requirement.9 At the same time, the court developed the language and rationales for deferring to legislative declarations about public use and purpose. The majority wrote in Kelo, “For more than a century, our public use jurisprudence has wisely eschewed rigid formulas and intrusive scrutiny in favor of affording legislatures broad latitude in determining what public needs justify the use of the takings power.”10 In particular, if a state declares that the removal of blight serves a public purpose or land redistribution does the same, then the court would not subject those claims to close scrutiny.11 Thus, following this line of thought, the court essentially declared that it would defer to legislative declarations about public use unless, in a particular application, they were transparently covering up a purely private transfer of property. The court decided this was not the case in Kelo. The Economics of Kelo Economist Patricia Munch provides an analysis of the economics of eminent domain. In her model, a land developer needs to assemble contiguous parcels of property. All parcels have identical characteristics, and there is nothing special about any particular location. The lowest price a property owner will accept (his “reservation price”) for his property differs across property owners. Munch assumes that each developer offers all owners the same price for their properties and that this price is the (expected) maximum reservation price of all property owners. Munch then argues that the full additional cost of adding a parcel to a development is likely to be larger than just the cost of that parcel. The reason is that, if the developer only needs a few parcels, then he can easily find a cluster in which the maximum reservation price is low. Since the developer (by The Regional Economist January 2007 n assumption) pays the maximum reservation price to each owner, it follows that the cost of each parcel is relatively low. The larger the number of parcels the developer needs to assemble, however, the more difficult it is to find a cluster with a low maximum reservation price. The general result is that, as long as the developer can do a little searching, the per-parcel cost will be strictly increasing with the number of parcels. It is not hard to see that the result is likely to be inefficiently little land assembly. As in the standard single buyer story (what economists term a monopsony), assembling more parcels requires the developer to offer each homeowner the same (high) price. Assembly stops when the cost to the developer of adding a parcel equals the benefit to him from adding it. In other words, assembly stops when there is no additional profit from adding parcels. The problem, however, is that if the developer could offer different sellers different amounts of money (i.e., he could price discriminate), he could probably offer them prices at which they willingly sell and at which he makes a larger profit. One could argue that the sellers and the buyer should figure this out, but it is expensive for the developer to deal individually with homeowners, and homeowners are reluctant to sell at prices below recent offers. As long as all parcels must sell for the same price, there are likely to be willing sellers whose homes are not purchased. Now suppose the developer has the power of eminent domain. This makes the reservation prices irrelevant: Every homeowner is paid the market price for his home. Now, land assembly stops when the market price equals the benefit to the developer from adding the parcel. The problem in this case is that the market price is below the reservation price for some of these sellers. In other words, they are unwilling sellers. The result is too much land assembly under eminent domain. Munch notes that the assumption that the developer is a single buyer is central to the analysis. If there is competition among developers, then some will develop better techniques for determining seller reservation prices. If communities choose these developers, then more-efficient land assembly will result. Munch also briefly discusses the “holdout”problem. She notes that there is no inefficiency when the owner of a parcel that has some unique value (perhaps as a location) tries to benefit financially from its uniqueness. The only genuine holdout problem she considers occurs if some sellers believe that other sellers did not capture all the rents that were possible to them in their transactions with the www.stlouisfed.org Select U.S. Eminent Domain Laws and Court Rulings 1) Fifth Amendment to the U.S. Constitution (1791) “Nor shall private property be taken for public use, without just compensation.” This statement is commonly referred to as the “takings clause.” Most courts have equated just compensation with a property’s fair market value. Narrowly defined, “public use” requires that the taken property be used by the public at large— what economists call a public good. 2) Fallbrook Irrigation Dist. vs. Bradley, 164 U.S. 112 (1896) In a case concerning the requirement that a group of property owners pay for the building of an irrigation ditch, the U.S. Supreme Court ruled that the irrigation of arid land served a public purpose and the water used was “put to” a public use. This is an important early case in the development of the public purpose doctrine. 3) Berman vs. Parker, 348 U.S. 26 (1954) The U.S. Supreme Court ruled that taking private property (and paying just compensation) to remove blight served a public purpose and met the requirements of the Fifth Amendment. This was true even though the seized property was sold to private interests and would not necessarily have a wide use by the public. 4) Hawaii Housing Authority vs. Midkiff, 467 U.S. 229 (1984) The U.S. Supreme Court ruled that a state could use eminent domain to take land from private landowners and allocate it to others. The case was based on the state of Hawaii’s complaint that a vast majority of the privately held land in Hawaii was in the hands of a few landowners, thus limiting competition in land and property markets. Berman vs. Parker served as precedent for the ruling. 5) Kelo vs. New London, 545 U.S. ____ (2005) The U.S. Supreme Court ruled that eminent domain could be used to take land from one private landowner and give it to another for the sake of economic development. Berman vs. Parker and Hawaii Housing Authority vs. Midkiff served as precedent for the ruling. Critics of the Kelo ruling argue that the court misinterpreted the Fifth Amendment by further broadening “public use” to mean “public purpose.” More information on these cases can be found at www.findlaw.com/ casecode/supreme.html. Other eminent domain cases can be searched at http://caselaw.lp.findlaw.com/casesummary. [7] developer. Misinformation and speculation along these lines could, once again, prevent willing buyers and willing sellers from reaching a transaction. The Public Good vs. Public Goods Although the work by Munch suggests eminent domain can improve upon market outcomes under certain conditions, her analysis fails to address several economic issues involving eminent domain that have broader implications for economic development and growth. Specifically, any economic analysis of eminent domain as it relates to the Kelo decision must recognize the tradeoffs inherent in giving local governments this kind of power over local economic development. Those who approve of eminent domain as it was used in Kelo fail to recognize the difference between what economists call“private goods”and “public goods.” They also fail to see the inefficiencies often generated from government intervention in private markets. An understanding of the differences between a public good and a private good and the ineffectiveness of governments in providing a private good reveals the incorrect premise behind the Kelo decision.12 Private goods are both “rival in consumption”and excludable. Rival in consumption means that one person’s consumption of a private good denies others the opportunity to enjoy the good. The price of a private good is essentially a result of the good’s scarcity— as additional resources are employed to produce more of the good, the opportunity cost and, thus, the marginal costs, of producing the private good rises. This increasing opportunity cost increases the price and, as a result, some individuals will be excluded from consuming the good because they are not willing to pay the higher price. Unlike a private good, a public good is both non-rival in consumption and nonexcludable. The textbook example of a pure public good is national defense; other examples of similar goods include parks and highways.13 One person’s consumption of a public good does not deny others from consuming the good, and people can use the public good without paying for it. As a result, the marginal cost of an additional user of a public good is zero, and this suggests a market price of zero. Economists justify public (government) provision of public goods because too little of the good would be available (given a market price of zero) if production of the good was left to the private market. Government provision of public goods and, thus, the taking of private property to provide these goods, can be justified under the narrow definition of public use, i.e., used by the community as a whole. [8] However, the taking of private property from one person and giving it to another for economic development, even if one considers the holdout problem and payment of just compensation, is unlikely to create a net benefit to society. It is more likely to create economic inefficiencies and to reduce economic growth.14 Historical anecdotal information and formal academic research show that, in general, countries with less government involvement in private markets experience greater levels of economic growth.15 The only possible exceptions in recent times are the Asian Tigers (e.g., South Korea, Taiwan and now China), but even there, markets are used extensively, and the strategies used by those governments have been difficult to replicate elsewhere. When governments interfere in the private market, whether it be a market for apples, cars or property, the likely result is greater economic inefficiency and less economic growth. The reason is that even the most well-intentioned policymaker cannot comprehend or replicate the complex interactions of buyers and sellers that occur in free markets. Of course, there will be certain groups that do benefit from the taking of private property, such as developers, property managers and local politicians. Developers and property managers will gain income from developing the property. Many local politicians favor targeted economic development because of what they see as the immediate benefits from development, such as increased employment and tax revenue. These economic benefits also translate into political benefits for those politicians who pledge to improve local economic development. Not realized, however, is that the supposed immediate and tangible benefits from taking private property for economic development are outweighed by the greater economic costs of government intervention in private markets. Local Governments and Economic Development The use of eminent domain for economic development as established by Kelo complements already existing economic development tools such as TIFs (tax increment financing), tax breaks, local development grants, etc. Local governments use all of these options to target specific projects in their area because of a perception, whether real or imaginary, that the local area suffers from a lack of growth. All of these economic development tools, however, are unlikely to lead to an overall increase in societal welfare because each tool simply involves a transfer of income from one group to another, often resulting in a zero-sum gain. The Regional Economist January 2007 n A simple example can illustrate the point. Suppose a local government takes $10,000 from Peter and gives it to Paul, who plans to open a business. Paul then uses the $10,000 to open his business, which creates tax revenue and jobs. From a social welfare point of view, Peter loses $10,000 and the savings or consumption benefits of his $10,000, Paul gains $10,000 to open a business, and jobs are created. By taking the $10,000 from Peter and giving it to Paul, the local government is essentially saying that Paul can create greater societal wealth with Peter’s $10,000 than Peter can. The same would be true if local governments paid Peter for his house and then gave the property to Paul for development purposes. Of course, it is impossible for local governments to know if greater wealth would have been created by allowing Peter to keep his $10,000 rather than giving it to Paul. Economic theory tells us that in the absence of incomplete information or externalities, free markets will result in the most efficient allocation of resources and greater economic growth. By replicating the above scenario across thousands or millions of individuals, the likely result is that the costs and benefits will average out to be the same, thus creating a zero-sum gain. Thus, the same level of economic development would have likely occurred if Peter kept his original $10,000. There is reason to believe, however, that a zero-sum gain is not the worst case outcome. In the face of a policy decision like eminent domain, individuals and interest groups on both sides of the issue will expend resources (e.g., campaign contributions, the cost of one’s time in campaigning for an issue, etc.) to ensure that the policy decision will favor their respective position. This rent-seeking by opposing groups results in a net economic loss because both groups will expend resources to ensure a particular outcome, but only one outcome will occur. In the above example, even if the transfer of $10,000 from Peter to Paul created a zero-sum gain, the resources Peter and Paul expended to influence the policy outcome will result in a total economic loss for society rather than a zero-sum gain. Most likely, the policy outcome will be that desired by the interest group that has expended the greatest resources. As Justice Sandra Day O’Connor states in her dissent to Kelo, “The beneficiaries (of eminent domain) are likely to be those citizens with disproportionate influence and power in the political process, including large corporations and development firms.”16 What can governments do to promote economic development that yields positive economic growth? Rather than use eminent domain or other tools to target individual economic development projects, local governments should ask the fundamental question as to why the desired level of economic growth is not occurring in the local area without significant economic development incentives. For example, are taxes too high, thus creating a disincentive for business to locate to the local area? Do current regulations stifle business creation and expansion? All of the targeted economic development in the world will not compensate for a poor business environment. From a regional perspective, local governments should focus on creating a business environment conducive to risk-taking, entry and expansion rather than attempting targeted economic development through eminent domain or other means.17 Indeed, there is some risk for local communities that use eminent domain for economic development. One requirement for a well-functioning private market is secure property rights. Research has shown that without property rights, individuals will no longer face the incentive to make the best economic use of their property, be it a business or home, and economic growth will be limited.18 The Kelo decision essentially says that individuals can lose their property if the local government believes it needs the property to generate greater economic benefits. Potential residents and businesses may avoid communities that have a record of taking private property for economic development because of a greater uncertainty about losing their property to eminent domain. Conclusion The Kelo decision by the U.S. Supreme Court was met by great opposition from the public and many local government officials. Numerous public opinion polls taken immediately following the ruling revealed that the vast majority of Americans disagreed with the court’s ruling.19 Supporters of Kelo argue that using eminent domain for private development will spur economic growth. Although a lack of sufficient data currently prevents empirically testing the economic effects of eminent domain described in this article, economic theory certainly suggests that eminent domain used for private economic development will likely result in a zero-sum gain and may actually hinder economic development in the local areas, as well as the region, rather than help. Thomas A. Garrett is a research officer and economist at the Federal Reserve Bank of St. Louis. Paul Rothstein is an associate professor of economics and associate director of the Weidenbaum Center on the Economy, Government, and Public Policy at Washington University in St. Louis. [9] www.stlouisfed.org ENDNOTES 1 H.RES 340, 109th Congress. 2 HR 4128, 109th Congress. 3 Indiana, Illinois, Kentucky, Tennessee, and Missouri have enacted statutes. The National Council of State Legislatures is keeping track of these activities. See www.ncsl.org/programs/natres/ EMINDOMAIN.htm. 4 “Executive Order: Protecting the Property Rights of the American People,” June 23, 2006. 5 Norwood vs. Horney, Ohio St. 3d, 2006Ohio-3799, paragraphs 7 and 76. 6 In Kohl vs. United States, 91 U.S. 367, 372373 (1876), the Supreme Court wrote, “The Constitution itself contains an implied recognition of it [eminent domain] beyond what may justly be implied from the express grants. The Fifth Amendment contains a provision that private property shall not be taken for public use without just compensation. What is that but an implied assertion, that, on making just compensation, it [private property for public use] may be taken?” 7 More detailed citations are available by request. 8 Kelo vs. New London, 545 U.S. ____, ____ (2005) (Court slip op., at 9). 9 Fallbrook Irrigation Dist. vs. Bradley, 164 U.S. 112, 164 (1896). 10 Kelo vs. New London, 545 U.S.____, ____ (2005) (Court slip op., 12-13). 11 Berman vs. Parker, 348 U.S. 26 (1954) and Hawaii Housing Authority vs. Midkiff, 467 U.S. 229 (1984), respectively. 12 Cornes and Sandler (1996). 13 Highways and parks are called near public goods because they are subject to congestion, which limits consumption. 14 Davies (2006) and Rolnick and Davies (2006) discuss the costs of Kelo. 15 See Gwartney et al. (2004). 16 Kelo vs. New London, 545 U.S.____, ____ (2005) (O’Connor slip op., 12-13). 17 Bauer (1972). 18 Knack and Keefer (1995). 19 See www.castlecoalition.org/resources/ kelo_polls.html. REFERENCES Bauer, Peter T. Dissent on Development: Studies and Debates in Economic Development. Cambridge, Mass.: Harvard University Press, 1972. Cornes, Richard; and Sandler, Todd. The Theory of Externalities, Public Goods, and Club Goods. NewYork: Cambridge University Press, 1996. Davies, Phil. “Condemned Prosperity.” Fedgazette, Federal Reserve Bank of Minneapolis, March 2006, Vol. 18, No. 2, pp. 14-17. Gwartney, James; Holcombe, Randall; and Lawson, Robert. “Economic Freedom, Institutional Quality, and Cross-County Differences in Income and Growth.” Cato Journal, Fall 2004, Vol. 24, No. 3, pp. 205-33. Knack, Stephen; and Keefer, Philip. “Institutions and Economic Performance: Cross-Country Tests Using Alternative Institutional Measures.” Economics and Politics, November 1995, Vol. 7, No. 3, pp. 207-27. Munch, Patricia. “An Economic Analysis of Eminent Domain.” Journal of Political Economy, June 1976, Vol. 84, No. 3, pp. 473-97. Rolnick, Art; and Davies, Phil. “The Cost of Kelo.” The Region, Federal Reserve Bank of Minneapolis, June 2006, Vol. 20, No. 2, pp. 12-17, 42-45. A mericans appear to be working less. Numerous economic studies suggest that the number of hours that the average American works in a year has fallen by about 550 hours from 1900 to 2005.1 The cut in hours worked presumably comes with the benefit of increased time devoted to leisure. Or does it? In two separate studies, economists Mark Aguiar and Erik Hurst and economists Valerie Ramey and Neville Francis found conflicting evidence on the trends in leisure time for Americans. What accounts for these differences? Is it simply alternative definitions of leisure, and, if so, which definition more accurately reflects what Americans view as leisure? The New Leisure The presumption that labor and leisure are inversely related is the foundation of many economic models. Time not spent at work must, by definition, be spent on leisure. An innovation of the two studies cited above is that they allow for non-market labor, i.e., hours spent outside the office performing chores not considered leisure. These activities include cleaning, cooking, commuting, etc. Although non-market labor activities might seem straight forward to define, in practice some activities, such as child-rearing, may be difficult to classify. In their 2006 study, Aguiar and Hurst examined changes in the time allocated to market work, non-market work and leisure from 1965-2003 for working-age adults—those aged 21-65. The accompanying table shows the changes for the whole sample, as well as the changes broken down by gender. According to the authors, total time devoted to the market sector per week (paid hours plus commuting, breaks and meals) declined by 3.2 hours for all workers.2 However, the trends for men and women were vastly different; the decline in men’s total weekly market work was over three times larger than the increase in women’s weekly hours. Similarly, total weekly non-market work (housework plus time spent obtaining goods and services and other home production) fell by 4.6 hours for all workers between 1965 and 2003. In this case, the decline in women’s total weekly non-market work was three times larger than the increase in men’s weekly hours. Thus, total weekly work (market plus non-market) decreased Working Hard or Hardly Working? The Evolution of Leisure in the United States By Kristie M. Engemann and Michael T. Owyang by 7.8 hours, with men and women experiencing similar overall declines. Rather than defining leisure simply as the amount of time not spent on market and non-market work, Aguiar and Hurst defined four alternative measures of leisure. The first accounts for time spent on activities such as socializing, relaxing, active recreation and recreational child care (e.g., playing games with children). Overall, working-age adults spent 5.1 more hours on these activities in 2003 than in 1965 on a weekly basis. The authors’ second measure, adding sleeping, eating and personal care to their first measure, increased by 5.6 hours during the sample period. Their third measure, which includes all previous activities plus primary and educational child care, increased by 6.9 hours. [10] Finally, their last measure of leisure is simply the residual from total work. The authors claimed that adults spent 7.8 more hours a week on leisure in 2003 using this last definition. Based on each of these measures then, adults have more leisure time than they did in 1965. 20th Century Trends in Per Capita Leisure The 2006 study by Ramey and Francis provides another perspective, yielding seemingly different results. Rather than examining the allocation of time for working-age adults, the authors used the entire population to estimate changes in market work, home production and leisure from 1900-2004. In addition to the three components The Regional Economist January 2007 n used by Aguiar and Hurst, Ramey and Francis estimated the time allocated to school for their sample period. The authors estimated that the average employed person worked 55 hours per week in 1900 but only 37 hours per week in 2004. Because school and homework are aimed at enhancing the productivity of future market work, Ramey and Francis included time spent on those activities as non-leisure. They found that school hours for those aged 5-22 rose from 330 to nearly 900 hours annually.3 After including commuting, time spent on market work and schooling per year declined by only 40 hours between 1900 and 2004. For home production, Ramey and Francis included typical housework (meals, cleaning, laundry, etc.) plus basic child care and helping with school work. They found that the typical non-employed woman aged 18-64 spent 56 hours per week on housework in the early 1900s but only 45 hours per week since 1975. For employed women aged 18-64, home production hours remained steady—about 25 hours per week—throughout the entire period. Employed men aged 18-64, on the other hand, saw an increase in housework from 2-3 hours per week in the 1920s to 16 hours per week in 2004. For the entire population, annual hours on home production increased by 67 hours during the sample period.4 In their study, Ramey and Francis defined leisure time as time spent on activities that provide direct enjoyment. Hence, leisure is time not spent on market work, school work, commuting or housework. The authors found that the average person spent similar time on leisure in 1900 (6,657 hours) and in 2004 (6,634 hours). These translate into 128 hours and 127.6 hours of leisure per week in 1900 and 2004, respectively. During the same period studied by Aguiar and Hurst, Ramey and Francis’ estimate of leisure time actually showed a slight decline in 2003 from the 1965 level. www.stlouisfed.org Discussion Are Americans enjoying more free time than they used to? Not if you ask them. Social scientists John Robinson and Geoffrey Godbey found that in surveys conducted in various years between 1965 and 1995, Americans increasingly felt rushed. In 1965, 24 percent of respondents aged 18-64 “always felt rushed”; this percentage climbed to 38 percent in 1992, but then dropped to 33 percent in 1995. Moreover, the percentage of respondents who “almost never felt rushed” fell from 27 percent to 17 percent between 1971 and 1995. Economists Daniel Hamermesh and Jungmin Lee offered a different interpretation. The authors studied people’s perception of their time stress, finding that people who make more money—but did not work more hours—reported that they felt more stressed for time.5 Hence, the authors attributed at least part of the time stress simply to having too much money to spend, given the amount of time left after working. These conflicting studies leave open this question of whether today’s Americans actually have more leisure time than past generations had. The salient difference in these studies’ conclusions appears to stem from what one considers leisure and who is being asked. Focusing only on working-age adults, as do Aguiar and Hurst, suggests that Americans enjoy more leisure now than in the mid-1960s. On the other hand, when school and work by children and retirees are included, Americans work about the same amount of time now as they did in both 1900 and 1965. However, no matter which definition of leisure is preferred, the broad conclusion is that Americans’ leisure time is, at worst, the same now as it ever was—regardless of perception. Kristie M. Engemann is a senior research associate, and Michael T. Owyang is a research officer, both at the Federal Reserve Bank of St. Louis Changes in Weekly Hours (1965-2003) From study by Mark Aguiar and Erik Hurst All Total market work (paid work, commute, breaks, meals) Men Women –3.2 –11.6 Total non-market work (housework, time obtaining goods and services, other) –4.6 Total work (total market + total non-market) 3.4 3.7 –11.1 –7.8 –7.9 –7.7 Leisure 1 (socializing, relaxing, recreation) 5.1 6.3 3.8 Leisure 2 (Leisure 1 + sleeping, eating, personal care) 5.6 6.4 4.9 Leisure 3 (Leisure 2 + primary and educational child care) 6.9 7.9 6.0 Leisure 4 (total hours possible minus total work) 7.8 7.9 7.7 [11] ENDNOTES 1 Total hours worked in business divided by the civilian non-institutional population aged 16 and older (Ramey and Francis 2006). 2 Aguiar and Hurst’s results control for age, education, the day of the week that the survey was taken and family composition. 3 The results for school were due to both higher enrollment and more days attended. 4 The authors noted that the increase is due to changes in the composition of the population (e.g., retired people now make up a larger percentage). 5 Hamermesh and Lee controlled for health and various demographic characteristics (e.g., family composition, age and location). REFERENCES Aguiar, Mark; and Hurst, Erik. “Measuring Trends in Leisure: The Allocation of Time over Five Decades.” Working Paper No. 06-2, Federal Reserve Bank of Boston, January 2006. Hamermesh, Daniel S.; and Lee, Jungmin. “Stressed Out on Four Continents: Time Crunch or Yuppie Kvetch?” Review of Economics and Statistics, forthcoming 2007. Ramey, Valerie A.; and Francis, Neville. “A Century of Work and Leisure.” Manuscript, University of California, San Diego, May 2006. Robinson, John P.; and Godbey, Geoffrey. Time for Life: The Surprising Ways Americans Use Their Time. Second Edition. University Park, Penn.: The Pennsylvania State University Press, 1999. Barnyard Boon or Bust? The National Animal Identification System (NAIS) By Michael R. Pakko producers could choose their level of participation in the program.6 Agriculture Department officials envision the identification system as a “public/private partnership.” However, the lack of a clear division of costs among various levels of government and producers has created uncertainty. Benefits and Costs C ity residents might not have heard much about it, but a program to identify and track U.S. farm animals has many farmers and ranchers angry and suspicious. Now being implemented by the U.S. Department of Agriculture (USDA), the National Animal Identification System (NAIS) calls for registering all premises involved with animal agriculture, tagging all farm animals and tracking these animals through a system of producer-reporting and state-managed databases. Opponents of NAIS worry about data security and cite objections to the program on constitutional and religious grounds.1 Small farmers, in particular, oppose the program, because they say it will cost too much.2 About the NAIS According to the USDA, the plan will enable the federal government to trace, within 48 hours, the origin of any animal in the food chain found to be infected by disease. Working groups comprised of industry and government representatives are developing implementation plans for cattle, swine, sheep, goats, horses, poultry, bison, deer, elk, llamas and alpacas. For example, the cattle working group has recommended radio frequency identification (RFID) ear tags to identify cattle.3 The plan has three phases: • Premises identification: The first phase, under way in most states, calls for the registration of all premises housing farm animals. Each location will get a unique seven-digit premises identification number. • Animal identification: The second phase calls for assigning a 15-digit animal identification number to each farm animal. Methods of identifying animals may differ from one species to another, with species working groups establishing the standards. Animals that move through the production chain as a group (e.g., swine and poultry) may get 13-digit group identification numbers. • Animal tracking: When the program is fully operational, all animal movements that involve possible commingling will be reported and stored in standardized databases that will be run by state governments and industry groups. The Agriculture Department’s draft strategic plan originally called for the system to become mandatory in 2008.4 Responding to criticism of this timetable, the USDA has backed away from mandatory features of the program and has begun emphasizing voluntary participation. An implementation plan published in October 2006 set milestones and benchmarks, envisioning a fully functional system in operation by January 2009. The plan noted that “allowing market forces … to drive producer participation in the NAIS is preferable to mandatory federal regulations.”5 A newly released User’s Guide, published in November 2006, emphasized voluntary participation even further, describing how individual [12] When evaluating public policy issues, a fundamental benchmark of analysis is a cost/benefit study. The principle is simple: It is worthwhile to implement or expand a program as long as the benefits exceed the costs. In practice, these costs and benefits can be difficult to quantify. Nevertheless, policies should not be implemented without a general consideration of this criterion. With NAIS, no formal cost/benefit analysis has been undertaken, although work is under way on such a project. The User’s Guide sketches out the general considerations. The benefits of the program should be calculated as the saving made possible by improved trace-back of disease outbreaks. For example, if improved tracking allows for only 2,000 animals to be isolated and tested, rather than 20,000, the lower cost should be considered a net benefit. The nature of the issue makes this exercise, in part, an analysis of risk. The relevant calculations should include the probability of specific disease scenarios, estimates of the costs of these scenarios and estimates of the savings that improved tracking procedures could provide.7 The cost of identifying every U.S. farm animal has been the focus of much critical attention. Agriculture Department officials foresee state governments and producers paying for much of the program. Federal funding for the program was only $18.8 million in 2004, with $33 million per year in subsequent years. This funding level has been sufficient to pay for initial administration costs and to provide support to states for setting up premises identification. States and producers will pay for the remaining costs, which are likely to be substantial.8 Having established criteria for uniform The Regional Economist January 2007 n record-keeping, the Agriculture Department is authorizing private database managers to collect animal tracking information and is authorizing particular manufacturers to provide official identification tags. Individual states may allocate some funding, but individual producers probably will pay for a large share of tagging and tracking animals. Researchers at Kansas State University developed a spreadsheet that estimates how much producers will have to pay to implement RFID technology for cattle. As the figure shows, the cost per head of implementing the system varies in proportion to herd size. The authors point out that not all the costs included in their analysis would necessarily be associated with NAIS.9 In particular, some smaller producers would probably not have to buy chip-reading equipment and computers for data management. Nevertheless, the technology itself is not scale-neutral: Fixed costs raise the cost per animal for small farmers, while economies of scale help keep the unit cost down for larger operations. Herd sizes in the U.S. beef and dairy industry tend to be fairly small. According to the 2002 Census of Agriculture, the median number of cattle and calves per farm is fewer than 50.10 Opposition to a national animal identification system tends to come from these smaller producers. Ranches with more than 50 head represent only one-third of all farms, but account for 87 percent of all cattle and calves. Additional Considerations One important feature of risk analysis is the general principle of diminishing returns. As in many economic analyses, the mitigation of some risk can be relatively inexpensive, but the cost can increase as more risk is addressed. It is often cost-effective to follow policies that mitigate some risk, but rarely can risk be totally eliminated. In this particular exam- ple, efforts to include the smaller producers face this escalating cost schedule. Supporters of NAIS sometimes argue that the benefits of an animal identification system include improved management tools for producers, as well as enhanced opportunities in domestic and international markets. This may be the case, but these benefits would largely accrue to the producers directly and would not necessarily justify the NAIS program itself. These considerations are relevant to the cost-benefit analysis of individual farmers, but not necessarily to the ID system as a whole. Nevertheless, these factors are relevant for evaluating the voluntary nature of current plans. Large-scale producers are far more likely to reap benefits from improving their inventory and marketing technologies and are likely to find it economical to participate voluntarily in the NAIS. With benefits of animal tracking technology increasing and costs decreasing for larger herds, there is likely to be a threshold level where participation in NAIS provides a net benefit. The distribution of herd sizes suggests that even a fairly low level of participation among producers could cover a large proportion of the nation’s animals. Broader participation in the program could be encouraged by program design to keep down the costs. As the most recent User’s Guide indicates, this level of voluntary participation is likely to be far more economically efficient than the original plan of mandatory 100 percent participation. Indeed, much criticism about the NAIS has focused on the high cost of the initial mandatory proposals. Assuming that the overall benefits of the program make its costs worthwhile, a system based on voluntary participation is far more likely to result in an efficient distribution of costs than a mandatory program. Michael Pakko is a research officer at the Federal Reserve Bank of St. Louis. ENDNOTES 1 See, for example, Zanoni (2006). 2 A recent article in USA Today describes the intensity of opposition that has arisen in some parts of the country, Hall (2006). 3 This article focuses on cattle as an example, but many of the points likely carry over to other species groups covered under the plan. 4 USDA (2005). 5 USDA (2006a), p. 2. Although the program is voluntary at the federal level, some individual states are requiring compliance with premises identification. 6 USDA (2006b). 7 An example of methodology is already established: Disney et al. (2001) showed how to evaluate both the costs of animal tracking systems and the benefits of trace-back after a disease outbreak. Although details of the study did not reflect some specific features of the NAIS proposals, it did find that a tracking program may or may not be cost-effective, depending on the assumed risks of disease outbreak and the cost of technologies used. 8 Tagging 40 million new calves born each year at a cost of $2.50 per tag, the cost of identifying cattle alone could exceed $100 million annually. 9 The costs include electronic tags, a wand/stick reader, a laptop computer and software, and other costs (including labor for implementing the technology). The costs do not include labor costs for the maintenance of centralized NAIS databases. 10 The average (mean) herd size nationwide is 94. For Missouri, the average is 69. REFERENCES Disney, W.T.; Green, J.W.; Forsythe, K.W.; Wiemers, J.F.; and Weber, S. “Benefitcost analysis of animal identification for disease prevention and control.” Rev. sci. tech. Off. Int. Epiz., August 2001, Vol. 20, No. 2, pp. 385-405. Dhuyvetter, Kevin C.; and Blasi, Dale. “A spreadsheet to estimate the economic costs of a radio frequency identification (RFID) system.” Kansas State University, 2006. See www.agmanager. info/livestock/budgets/production/ beef/RFID%20costs.xls. Hall, Mimi. “Animal ID plan angers some farmers.” USA Today, Oct. 27, 2006. See www.usatoday.com/news/nation/ 2006-10-26-animal-id_x.htm. “Tracking animals with RFID.” RFID Gazette, Nov. 26, 2005. See www. rfidgazette.org/healthcare/index.html. U.S. Department of Agriculture. Animal and Plant Health Inspection Service. “National Animal Identification System (NAIS) Draft Strategic Plan 2005 to 2009.” April 25, 2005. Total Annual Cost of Radio Frequency Identification System 25 $/head www.stlouisfed.org 20 ___. “National Animal Identification System (NAIS): Strategies for the Implementation of NAIS.” October 2006a. 15 ___. “National Animal Identification System (NAIS): A User Guide.” November 2006b. Zanoni, Mary. “The ‘National Animal Identification System’: A New Threat to Rural Freedom.” Countryside & Small Stock Journal, January/February 2006. See www.countrysidemag.com/ issues/1_2006.htm#article4. 10 5 0 0 100 SOURCE: Dhuyvetter, Kevin C.; and Blasi, Dale. 200 300 400 500 Size of Herd [13] 600 Community Profile Tunica Lays Big Bet on the Casino Industry Gamble pays off for Mississippi town after years of struggle C C hi C mp C C me r C C tunica arena & expo center Pr C ed os op I-69 Tunica C = casino tunica airport downtown ILLINOIS INDIANA MISSOURI KENTUCKY EIGHTH FEDERAL RESERVE DISTRICT ARKANSAS By Glen Sparks S to s sis mis s C i ve ir ip p TENNESSEE MISSISSIPPI Tunica, Miss. BY THE NUMBERS Population . .........................................City 1,089 (2005) County 10,321 (2005) County Labor Force...........................4,469 (June 2006) County Unemployment Rate.......8.5 percent (June 2006) County Per Capita Income...................$19,567 (2004) Top Employers in Tunica County Grand Casino............................................................2,556 Horseshoe Casino....................................................2,500 Sam’s Town Casino..................................................1,561 Gold Strike Casino...................................................1,547 Fitzgerald’s Casino...................................................1,130 The bright lights of the Grand Casino (above) contrast sharply with a pastoral scene several miles west of downtown. igns of prosperity pop up across the flat land of Tunica: nine flashy casinos, an expo center, a new golf course, an outlet mall, a recreation center and other attractions. Long-time residents like to brag about the “Tunica miracle.” The old Tunica, the Tunica of the 1980s and early ’90s, seems like a long time ago. Or does it? “There’s no way to forget,” says Clifton Johnson, the Tunica County administrator and a life-long Tunica resident. “I remember when there was nothing here.” Flash back to the “old Tunica.” Residents had depended for decades on the cotton industry for jobs; the introduction of high-tech farming tools cut the need for actual farmers, however. In 1991, the year before the first casino opened, Tunica County had 15.7 percent unemployment, the highest in Mississippi and 6.8 percentage points higher than the state average. Now, about 12 million people try their luck every year at casinos here, making Tunica the largest casino market in the Eighth District and the fifth largest in the United States, according to the American Gaming Association. Gamblers can choose from more than 14,000 slots and 400 table games and stay in one of more than 6,300 hotel rooms. The Tunica casino industry employs about 15,000 workers, most of them getting on-the-job training. “The bottom line is that people have jobs,” Johnson says. “Before, people weren’t working.” The average annual salary of a Tunica County resident has gone from $12,700 in the early 1990s to $26,000 in 2004, according to the Mississippi Employment Security Commission. The county had just 2,000 jobs in 1992 and almost 17,000 jobs in 2005, according to the security commission. Unemployment is about one-half what it was in the pre-casino days. Casino development also has had dramatic implications for local government finance. Through the first [14] 10 months of 2006, the 26 casinos in Mississippi had generated almost $245 million in tax revenue for state and local governments, according to the Mississippi Gaming Commission. In 2005, tax revenue totaled about $254 million, despite Hurricane Katrina knocking out the Gulf Coast casinos for nearly four months. Tunica gaming revenue is subject to a 12 percent tax: 8 percent from the state and 4 percent from Tunica County. The Tunica County Board of Supervisors decides how to spend the local money. County officials say that Tunica has benefited from millions of dollars in capital projects since 1992, including: • the 48,000-square-foot Tunica Arena and Expo Center, which attracts more than 200,000 visitors every year for trade shows and other events. Built in 2001, this $24 million venue already is undergoing a $5 million expansion; • Tunica RiverPark, which includes a museum, aquarium, nature trails and a deck overlooking the Mississippi River. The $26 million RiverPark has attracted more than 100,000 visitors over the past two years; • the Tunica Airport, which completed a $38 million expansion in 2000. Charter flights carry passengers to Tunica from at least 12 states; • the Tunica County Library, which has doubled in size at a cost of $1.5 million; • the Tunica National Golf and Tennis Center, which opened in March 2004; and • the G.W. Henderson Sr. Recreation Complex, which features a 38,700-square-foot county sports The Regional Economist January 2007 n www.stlouisfed.org complex with an eight-lane swimming pool, basketball courts, a boxing ring and a workout facility. “We wouldn’t have been able to do any of this without gaming,” Johnson says. In 1997, Tunica County cut property taxes by 25 percent. Since the first casino opened, the county has allocated more than $100 million to road construction and improvement, $40.8 million to school improvements, $28.2 million to water and sewer upgrades, $13.2 million to police and fire protection, and $5 million to housing rehabilitation and support services for the elderly and disabled. “There’s a feeling among some critics that if you make gambling legal, the entire town will go to ruin,” says St. Louis Fed economist Tom Garrett, who has written about the gambling industry. “That just isn’t the case.” State lawmakers in 1990 made casino gambling legal for Mississippi counties that lie along the Gulf Coast and on major waterways, such as the Mississippi River. The first Tunica casino, Splash, opened in 1992. Lady Luck opened 11 months later, and other casinos followed: Harrah’s in 1993; Treasure Bay, Hollywood, Circus Circus (now Gold Strike) and Fitzgerald’s in 1994; and so on. Gold Strike added a 31-story hotel, the tallest building in Mississippi, in 1997. The Horseshoe Casino opened in 1995 and completed a $40 million expansion in 2000. Casino owners built all this on their own, without a penny of tax increment financing or other subsidies. “That’s the interesting thing, that in this age of subsidies and companies making all these demands, the casino industry has traditionally received fewer economic development incentives than other industries,” Garrett says. “Of course, usually, there is a segment of the local population that doesn’t support gambling, and the gambling industry is just glad to be there.” “There has been a real vision” Why don’t more towns—especially struggling ones, as Tunica was—open casinos, build golf courses and outlet malls and then sit back and wait for prosperity? Well, for one thing, it isn’t that easy. What Tunica did is more complicated than just legalizing the lottery or putting a few hundred slot machines on a riverboat. Tunica, about 30 miles south of Memphis, built a destination resort. It did it in just a few years, and it did it from scratch. Bob McQueen, the general manger of Fitzgerald’s Casino, credits forward-thinking public officials for helping to pull off the “Tunica Miracle” that the county likes to advertise. John Osborne, the general manager of Hollywood Casino, agrees: “There has been a real vision if you look at the investment on infrastructure. Look at it all—the school improvements, the recreation centers, the museums, everything.” The casinos continue to invest in Tunica. Fitzgerald’s plans to renovate its hotel lobby and guest rooms, and add suites throughout the hotel; the Horseshoe hopes to put in a Starbucks coffee shop; Resorts Casino is renovating its exterior; and the Sheraton will open a showroom to attract variety acts. The next phase in the Tunica transformation will be in the area of residential construction. Ask Matt McCraw, the president of Covenant Bank in downtown Tunica, whether Tunica is just a southern suburb of Memphis and he smiles. “Tunicans don’t think so,” he says. “But it’s coming this way.” Over the next five years, Johnson says 3,000 housing units will be built in Tunica County. The additional housing may help bring more retail stores and chain restaurants to Tunica, McCraw said. Along with housing, and possibly more retail, Tunica hopes to attract more manufacturing jobs to the area. In late 2005, the county designated a 2,200-acre site for industrial development, on a cotton field near Casino Row and the intersection of highways 61 and 304. Johnson says the county wants to land an automobile assembly plant on the site. In some ways, the old Tunica really does seem like a long time ago. Farming, once the lifeblood of Tunica, is just a $70 million business—a fraction of what gambling generates. “Some people don’t like gambling,” Johnson says, “but it has given people here some hope. It is responsible for providing many people with a better life.” Glen Sparks is an editor at the Federal Reserve Bank of St. Louis. [15] Downtown Tries To Hit the Jackpot, Too D owntown Tunica sits about 10 miles south of the nearest casino. That doesn’t mean, however, that downtown doesn’t reap the benefits of all the glitter and glamour that have made Tunica famous over the past decade. Since 1994, the city of Tunica has spent nearly $9 million in tax revenue from casino gambling to build a new police station, post office, market place, playground, Veterans’ Memorial Park and more. “The downtown area has made tremendous progress over the last several years,” says Matt McCraw, president of Covenant Bank in downtown Tunica. Tunica Mainstreet, a local improvement group, offers 50/50 façade improvement grants of up to $2,000 to local business owners. Twenty-two of the 70 downtown businesses have taken part in the program. Now, downtown business owners hope more tourists begin stopping by the other side of Tunica. “You have 50,000 people coming to Tunica every day to gamble and not enough come to downtown,” says Frank Scaggs, a former steel fabricator in Memphis who opened Poore Frank’s Antiques and Collectibles two years ago. “It’d be great just to get 10 percent of these folks.” Downtown averages about 1,000 tourists every month. TOP: Although casinos are king now in Tunica, there’s still plenty of room for cotton, too. The harvest was in full swing last fall in the northern part of the county. BOTTOM: The Schweikert family of Olive Branch, Miss., visits RiverPark, a complex on the Mississippi River that includes a museum, aquarium and nature trails. District Overviews Louisville Zone Louisville’s Job Growth Lags on Many Fronts By Kristie M. Engemann and Howard J. Wall T he number of private nonfarm jobs in the Louisville metro area increased by 0.2 percent—or just 1,200—between October 2005 and October 2006, according to estimates from the Bureau of Labor Statistics. This was a significant slowing of job growth compared to the previous 12-month period, when nearly three times as many jobs were added. The metro area has underperformed the country as a whole, too: Between October 2005 and October 2006, private nonfarm employment in the United States rose by 1.6 percent. On the other hand, in the 2006 calendar year through October, the number of private-sector jobs in the Louisville area rose by 0.7 percent at an annualized rate, indicating that job growth has been accelerating somewhat. As is usually the case, the employment numbers for the metro area as a whole mask significant differences in performance across sectors. For example, in contrast with trends in total employment, the two largest sectors in Louisville—trade, transportation and utilities; and education and health— have been generating more jobs than previously. Also, the rate of job loss in manufacturing has been accelerating, while jobs have continued to be added in all other sectors. The pattern across industries is detailed by the figure. Six of the eight private sectors contributed positively to the employment growth since October 2005. Trade, transportation and utilities— the largest sector in Louisville—grew by 1.6 percent since October 2005. That percentage was larger than the previous year’s growth rate and outpaced the 0.5 percent national-level growth for the sector. Louisville’s second-largest sector, education and health services, continued to have slight positive employment growth since October 2004; the most recent year-over-year growth rate (0.4 percent) was unchanged from the previous 12-month period. This sector lagged significantly behind the rest of the country, which saw 2.6 percent growth from October 2005 to October 2006. Manufacturing employment fell by 5.2 percent from October 2005 to Private Nonfarm Employment in the Louisville Metro Area percent 6 Y/Y% change October ’04 – October ’05 Y/Y% change October ’05 – October ’06 4 2 0 –2 –4 –6 Total Trade, Transportation and Utilities Education and Health Manufacturing Professional and Business Services Leisure and Hospitality Financial Activities Natural Resources, Mining and Construction Information * 25.4% 14.4% 13.8% 13.5% 11.1% 7.6% 6.8% 1.9% SOURCE: Bureau of Labor Statistics and authors’ calculations; data are seasonally adjusted. * The percentage beneath each sector represents its share of employment. October 2006, or more than 4,000 jobs, a sharp worsening over the previous year’s 2.4 percent decrease. In contrast, employment in the U.S. manufacturing sector experienced a decrease of only 0.1 percent over the same period. Professional and business services, the area’s fourth-largest sector, has been one of the strongest sectors since October 2004. From October 2004 to October 2005, the number of jobs rose by 3.8 percent. For the next 12 months, employment in this sector grew by 1.6 percent. In comparison, the U.S. sector grew by 2.7 percent from October 2005 to October 2006; this growth was the largest across all of the U.S. sectors. The fifth-largest sector in Louisville, leisure and hospitality, continued to have gains in employment but at a much slower pace. The year-overyear growth rate in October 2006 was 1 percent, which was half of the previous year-over-year rate. The U.S. sector grew by 2.6 percent since October 2005. The financial activities sector had a similar experience. The most recent year-over-year rate was 0.8 percent, less than one-third of the previous year-over-year rate. For the country, the rate was 1.9 percent for the period from October 2005 until October 2006. Natural resources, mining and construction had larger growth than [16] any other sector in Louisville since October 2005. It is also the only sector to have continuous upward growth since October 2004. The year-overyear growth rate for October 2006 was 3.6 percent, and the pace for the first 10 months of 2006 was 6.3 percent. The U.S. sector had 2.4 percent growth since October 2005. Louisville’s smallest sector, information, experienced no change in employment since October 2005. Employment in the U.S. information sector rose 0.1 percent from October 2005 to October 2006. Kristie M. Engemann is a senior research associate, and Howard J. Wall is an assistant vice president and economist, both at the Federal Reserve Bank of St. Louis. The Regional Economist January 2007 n www.stlouisfed.org memphis Zone There Are Two Sides to Every (Employment Redistribution) Story! By Joshua A. Byrge and Michael R. Pakko T he Memphis zone of the Eighth Federal Reserve District includes two metropolitan statistical areas (MSAs) outside of Memphis itself: Jonesboro, Ark., and Jackson, Tenn. In many ways, these two MSAs are very similar: They are roughly the same size in population with similar employment patterns and industry compositions. They also have followed similar paths of employment growth during the current economic expansion; both Jonesboro and Jackson have exemplified the national shift in employment from goods production to service-providing sectors and have both outperformed their respective states’ rates of employment growth. Nationally, this employment shift is often associated with movement from high-paying jobs to lowpaying jobs. However, this broadly held sentiment belies a mixture of local experiences. Jonesboro has exceeded statewide growth of real personal income per capita, while Jackson has not. During the expansion, both Jonesboro and Jackson have redistributed employment more rapidly than have their respective states. Between November 2001 and October 2006, Jonesboro’s concentration in serviceproviding employment grew by 0.4 percent annually relative to Arkansas’ statewide. Similarly, Jackson’s concentration increased by 0.5 percent when compared with Tennessee’s. In addition, the concentration of goodsproviding employment in both MSAs fell by nearly 1 percent annually relative to their respective states’. This ability to move employment into the expanding service sector has allowed total employment growth in both Jonesboro and Jackson to outpace their respective states’ since the beginning of the expansion. Through October 2006, private nonfarm payroll employment in Jonesboro grew by 1.1 percent annually compared with 0.8 percent statewide. In Jackson, private employment grew by 1.5 percent compared with 1 percent in Tennessee overall. Although both Jonesboro and Jackson have added to their service-providing employment throughout this Nonfarm Employment Growth by Sector Seasonally Adjusted Monthly Data, November 2001 to October 2006 Annualized Growth Rate 3 Professional/Business Leisure /Hospitality 2 Professional/Business Education/Health Leisure /Hospitality 1 Education/Health Trade/Transport/Utilities Trade/Transport/Utilities 0 Other –1 –2 –3 JACKSON JONESBORO Total Goods Producing Government Service Providing SOURCE: Bureau of Labor Statistics/Haver and authors’calculations. expansion, the composition of these additions has differed in important ways. Through October 2006, new service-sector growth in Jonesboro was concentrated in the professional and business services sector, which grew by 7.9 percent annually compared with 4.2 percent from January 1990 through the business cycle peak in March 2001. Professional and business services include professional, scientific and technical services, management of companies and enterprises, and administrative and waste services industries. Nationally, real earnings in these industries averaged $9.55 per hour as of October 2006. (The national average for goods-producing sectors was $8.93 per hour.) In Jackson, new service-sector employment growth occurred mainly in leisure and hospitality services. Employment in these services grew by 4.4 percent annually through October 2006 compared with 2.4 percent from 1990 to March 2001. Leisure and hospitality services include arts, entertainment, recreation, accommodations and food services. In October 2006, real earnings in these industries averaged $4.78 per hour—roughly half the average hourly earnings in professional and business services. Income growth, then, provides the real distinction between the Jonesboro [17] and Jackson areas during the current expansion. Because employment growth in the Jackson metro area has been concentrated in low-wage industries, its income growth has only matched Tennessee’s. From 2001 through 2005, real personal income per capita increased by 1.3 percent annually in Jackson and statewide. The area’s leisure and hospitality employment growth has not been enough to bolster its overall income growth beyond the statewide trend. If Jackson exemplifies the national sentiment regarding employment reallocation, Jonesboro provides a counterexample. Because of the area’s exceptional employment growth in high-wage industries, Jonesboro has outperformed Arkansas in income growth. From 2001 through 2005, real personal income per capita grew by 1.7 percent in Jonesboro compared with 1.5 percent statewide. Although there is fear that the national shift from a goods-producing economy to a service-providing one will produce lower wages, the Jonesboro experience demonstrates the potential for higher standards of living in response to employment reallocations. Joshua Byrge is a research associate and Michael Pakko is a research officer, both in the Research Division of the Federal Reserve Bank of St. Louis. National Overview Below-Trend Growth Is Predicted for Most of 2007 By Kevin L. Kliesen A t first glance, last year’s economic performance was solid but not spectacular. As this article went to press in December 2006, actual year-to-date growth of real GDP and CPI were on track to finish near their January 2006 consensus forecasts of 3.3 and 2.2 percent, respectively. By contrast, through November, the unemployment rate was one-half percentage point better than expectations. A closer inspection reveals that a significant portion of the gains in real GDP growth in 2006 was catalogued in the first quarter, when output rose at a robust 5.6 percent annual rate. Over the following two quarters, real GDP growth slowed to rates of 2.6 percent and 2.2 percent, respectively. If real GDP increases by 1.7 percent in the fourth quarter of 2006, modestly weaker than forecasters expect, then real GDP will have increased by at least 3 percent for the fourth consecutive year. The slowing in real GDP growth over the latter part of last year can be attributed mainly to three developments. First, real short-term interest rates rose by about two percentage points as the Federal Open Market Committee pushed its target for the federal funds rate from 4.25 percent in December 2005 to 5.25 percent in June 2006; this increase helped to slow the demand for interestsensitive consumption goods. Second, oil prices rose unexpectedly to more than $77 per barrel during the summer, pushing retail gasoline prices above $3 per gallon. Higher energy prices not only reduced the purchasing power of household incomes, but also raised operating costs for many firms and contributed to increased financial market uncertainty. Rising gasoline prices also decreased the demand for light trucks and SUVs, causing manufacturers to dramatically cut production. The third and, perhaps, most significant development last year was the widely anticipated slowing in the housing sector, which followed the record-setting performance in 2005. Although conventional 30-year mortgage rates rose by only about 50 basis points over the first seven months of the year and then dropped back to their 2005 year-end levels, housing starts, new home sales and median prices of new homes fell sharply in 2006. With inventories of unsold new homes rising to record levels, builders significantly curtailed new construc- tion. As a result, real residential fixed investment subtracted a little more than 1.75 percentage points from real GDP growth in the second and third quarters of 2006. Strains in the housing sector continue to dominate the economic headlines, but the big picture looks better. Solid labor market conditions and growth of business capital outlays remain healthy, while the prospects for continued strong growth of U.S. exports appear good. Longterm inflation expectations remain relatively low and stable, and crude oil and gasoline prices have fallen significantly since August. Despite these favorable developments, there [18] are some areas of concern. Two stand out. Continued elevated rates of underlying price pressures are the first area of concern. The FOMC noted at its meeting of Oct. 24-25, 2006, that “current rates of core inflation remained undesirably high,” according to the minutes. Although the FOMC expects core inflation to “moderate gradually,” the timing and extent of that moderation is “quite uncertain.” Complicating matters is the recent slowing in labor productivity growth in the face of an upswing in the growth of labor compensation. While worrisome, the consensus forecast is that the CPI will increase 2.5 percent in 2007. Excluding food and energy prices (core), the consensus expects CPI inflation to average 2.4 percent in 2007. The second area of concern is the potential threat of much weaker growth in real GDP. This threat is manifested by the inverted Treasury yield curve, which has preceded every recession since the end of World War II. One well-known model based on the yield curve posits a more-than-50-percent probability of a recession sometime during 2007. Other economists, such as Fed Chairman Ben Bernanke, have argued that global capital flows and a reduced risk from holding longerterm securities have minimized the yield curve’s importance as a business cycle indicator. Although business cycle peaks and troughs remain difficult to predict, most forecasters see a much lower probability of a recession in 2007. Instead, they generally expect below-trend real GDP growth through much of 2007 and, then, trend-like growth (3 to 3.5 percent) over the latter part of 2007 and into 2008. Kevin L. Kliesen is an economist at the Federal Reserve Bank of St. Louis. Joshua A. Byrge provided research assistance. The Regional Economist January 2007 n www.stlouisfed.org National and District Data Selected indicators of the national economy and banking, agricultural and business conditions in the Eighth Federal Reserve District Commercial Bank Performance Ratios third quarter 2006 U.S. Banks by Asset Size ALL $100 million$300 million Return on Average Assets* 1.35 1.25 1.16 1.38 1.27 1.40 1.34 1.36 Net Interest Margin* 3.46 4.34 4.34 4.30 4.32 4.03 4.17 3.19 Nonperforming Loan Ratio 0.74 0.75 0.79 0.64 0.72 0.58 0.65 0.78 Loan Loss Reserve Ratio 1.21 1.25 1.28 1.24 1.26 1.26 1.26 1.19 less than $300 million $300 million$1 billion less than $1 billion $1billion$15 billion Return on Average Assets * Net Interest Margin * 1.23 1.20 1.19 1.18 1.08 1.13 1.06 0.99 1.24 1.29 1.21 1.15 1.24 1.25 1.38 1.24 0 .25 .50 .75 1 1.25 1.50 3.91 3.87 4.14 4.20 3.65 3.74 3.65 3.49 4.08 3.78 4.14 4.13 4.11 3.96 3.42 3.57 Eighth District Arkansas Illinois Indiana Kentucky Mississippi Missouri Tennessee 2 percent 1 Nonperforming Loan Ratio 0.77 0.80 0.85 0.92 0.89 0.90 0.92 2.5 3 Arkansas Illinois Indiana 1.17 Kentucky 0.69 Missouri 0.90 0.96 .75 1 4 4.5 0.94 0.91 Tennessee 1.25 3.5 1.24 1.31 1.38 1.47 1.21 1.24 1.36 1.47 1.17 1.49 1.26 1.36 1.36 1.38 Mississippi 0.58 .5 2 Eighth District 0.44 0.46 .25 1.5 Loan Loss Reserve Ratio 0.78 0.84 0 More less than than $15 billion $15 billion 1.5 Third Quarter 2006 NOTE: Data include only that portion of the state within Eighth District boundaries. SOURCE: FFIEC Reports of Condition and Income for all insured U.S. commercial banks. *Annualized data 0 .25 .50 .75 1 1.25 Third Quarter 2005 For additional banking and regional data, visit our web site at: www.research.stlouisfed.org/fred2/ 1.50 1.75 The Regional Economist January 2007 n www.stlouisfed.org Regional Economic Indicators Nonfarm Employment Growth* year-over-year percent change third quarter 2006 Total Nonagricultural Natural Resources/Mining Construction Manufacturing Trade/Transportation/Utilities Information Financial Activities Professional & Business Services Education & Health Services Leisure & Hospitality Other Services Government united states eighth district arkansas illinois indiana 1.4% 8.8 2.7 0.2 0.3 –0.3 2.3 2.7 2.3 1.9 0.2 0.9 1.0% 3.9 2.4 –1.0 1.2 –0.9 1.3 2.2 1.6 1.6 0.4 0.6 1.2% 5.5 2.0 –1.9 1.1 1.8 1.9 3.9 2.2 2.1 1.7 1.1 1.1% 0.7 2.7 –1.4 1.0 –1.5 1.9 3.3 1.2 2.8 0.2 –0.3 0.5% 1.9 1.1 0.4 0.2 1.4 1.6 0.2 1.0 0.6 0.5 0.2 900 III/2006 II/2006 III/2005 4.7% 5.3 4.6 5.4 5.8 7.4 4.9 5.4 4.6% 5.2 4.7 5.0 5.8 7.4 4.6 5.5 5.0% 4.9 5.7 5.5 6.3 8.3 5.2 5.5 Illinois Indiana Kentucky Mississippi Missouri Tennessee missouri tennessee 1.0% 6.8 1.3 –1.4 1.1 0.0 0.9 2.0 2.0 2.5 -0.4 0.6 1.2% 6.1 9.1 –0.7 2.0 –3.5 –0.6 4.2 2.2 –4.5 1.4 2.0 0.9% –5.6 1.5 –1.6 1.7 –2.9 1.0 1.3 1.7 0.8 0.4 1.3 1.2% 4.0 2.6 –1.3 1.7 0.3 0.6 1.1 2.2 3.2 0.9 0.9 millions of dollars percent Arkansas mississippi Adjusted Gross Casino Revenue* Unemployment Rates United States kentucky Recession as determined by the National Bureau of Economic Research mississippi 800 700 indiana 600 500 illinois 400 missouri 300 SOURCE: State gaming commissions. 200 1999Q3 2000Q3 2001Q3 2002Q3 2003Q3 2004Q3 2005Q3 2006Q3 NOTE: Adjusted Gross Revenue = Total wagers minus player winnings. Native American casino revenue (Mississippi only) is not included. In 2006 dollars. * third quarter second quarter Housing Permits Real Personal Income ‡ year-over-year percent change in year-to-date levels year-over-year percent change –10.8 –10.5 –0.5 –5.2 –21.3 –25.4 United States 7.1 10.1 Arkansas 2.0 Illinois 2.0 Indiana –2.5 24.0 –2.1 –7.1 7.8 0.5 2.9 –35 –30 –25 –20 –15 –10 –5 2006 0 3.8 2.4 2.1 Mississippi 3.2 3.9 2.4 Missouri 3.7 2.3 Tennessee 5 10 15 20 25 30 percent 4.1 1.3 Kentucky –7.8 3.8 2.8 2.9 0 2005 1 2 2006 ‡ 3.4 3 4 5 2005 NOTE: Real personal income is personal income divided by the PCE chained price index. The Regional Economist January 2007 n www.stlouisfed.org Major Macroeconomic Indicators Consumer Price Inflation Real GDP Growth percent percent 8 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 6 4 2 0 –2 01 Additional charts can be found on the web version of The Regional Economist. Go to www.stlouisfed.org/publications/re/2007/a/pdf/01_07_data.pdf. 02 03 04 05 06 NOTE: Each bar is a one-quarter growth rate (annualized); the green line is the 10-year growth rate. all items all items, less food and energy Nov. 01 02 03 04 05 06 NOTE: Percent change from a year earlier Civilian Unemployment Rate Interest Rates percent percent 7 6.5 6 6.0 5 5.5 4 5.0 3 4.5 fed funds target 2 4.0 1 Nov. 3.5 01 02 03 04 05 0 06 NOTE: Beginning in January 2003, household data reflect revised population controls used in the Current Population Survey. Nov. three-month t-bill 01 02 03 04 05 06 NOTE: Except for the fed funds target, which is end-of-period, data are monthly averages of daily data. Farm Sector Indicators U.S. Agricultural Trade Farming Cash Receipts billions of dollars 45 40 35 30 25 20 15 10 5 0 billions of dollars 130 125 120 115 crops 110 livestock 105 100 95 90 Aug. 85 06 01 02 03 04 05 exports imports trade balance Oct. 01 02 04 03 05 06 NOTE: Data are aggregated over the past 12 months. NOTE: Data are aggregated over the past 12 months. U.S. Crop and Livestock Prices index 1990-92=100 145 135 crops 125 115 105 95 livestock 85 75 1992 Nov. 93 94 95 96 97 98 99 [19] 00 01 02 03 04 05 06
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