Showing papers in "The Regional Economist in 2013"

Why are corporations holding so much cash

Abstract: U.S. corporations are holding record-high amounts of cash. One reason has to do with taxes—both the uncertainty about future taxes and the reality of today’s tax rules. The second reason has to do with the rise of research and development; because of its uncertain nature, this sort of work requires access to high levels of cash.

How Low Can You Go? Negative Interest Rates and Investors' Flight to Safety

Abstract: It is not uncommon to observe negative interest rates during uncertain times, when investors flee to safety. But the existence of negative market yields provides no support for policies in which central banks set negative interest rates on deposits held at a central bank.

Financial markets: an engine for economic growth

Abstract: Do developed financial markets lead to economic growth or result from it? While some economists argue for the latter, the author maintains that financial markets—despite their shortcomings of late—are an essential ingredient for an economy to grow in the long run.

A closer look at the decline in the labor force participation rate

Abstract: The labor force participation rate has fallen from over 67 percent in 2000 to almost 63 percent today. Among the reasons are the downward trends in the percentages of women and young people in the labor force.

Banks and credit unions: competition not going away

Abstract: Has the competitive balance tilted away from banks and toward credit unions, given the latter’s tax exemption and more-recent ability to draw members from wider pools? Whether it has or not, both industries have seen similar trend growth over the past 15 years—and, in fact, have come to resemble each other in many ways.

Output and unemployment: how do they relate today?

Abstract: Fifty years ago, Arthur Okun examined the relationship between output growth and the unemployment rate. The empirical relationship of the resulting “Okun’s law” has remained largely intact since then, including during the Great Recession. However, while the law does fit our intuition about economic relationships, it should not necessarily be taken to be causal.

Job polarization leaves middle-skilled workers out in the cold

Abstract: The economy has increased its demand for high-skilled (high-wage) workers, while opportunities for middle-skilled (middle-wage) jobs have declined. This “job polarization” may require a shift in the sort of training that is encouraged for American workers.

Exploring the link between drug use and job status in the U.S

Abstract: What is the relationship between drug abuse and job status in the United States? This is a complex question involving two directions of causality. Does drug abuse lead someone to become or stay jobless, or does unemployment lead to drug abuse? On the one hand, drug abuse can reduce a person’s employment prospects, both by reducing productivity and by decreasing the chance of getting a job in the first place, especially if an employer tests applicants for illegal drug consumption. On the other hand, those who are unemployed or otherwise out of the labor force may face financial hardship or simply have more unstructured time, either of which can result in a higher propensity to consume these substances, everything else held constant. If so, it would only be natural to think that a national increase in unemployment—such as during the Great Recession—could lead to increased drug abuse and persistent drug addiction issues. This article provides a quick glance at this relationship, using data about legal and illegal drug use from 2005 to 2011 from the annual National Survey on Drug Use and Health, conducted by the U.S. Department of Health and Human Services.1 Caffeine, alcohol and nicotine are by far the most popular addictive substances in the U.S., partly because they are not illegal and partly because their negative health effects are thought to be mild if consumed in moderation. In 2011, 13.5 percent of respondents reported having smoked a cigarette every day during the past month, and 18 percent reported having drunk alcohol more than 100 times in the previous 12 months. Figure 1 shows the fraction of the population reporting having consumed illegal substances in the month prior to questioning.2 The figure reveals that marijuana was by far the most popular illegal substance, with 7 percent of the population reporting having consumed it in the previous month. Pain relievers and tranquilizers follow marijuana in popularity and were reportedly consumed by 1.5 and 0.7 percent of the population, respectively. Substances such as crack, heroin and sedatives were consumed by 0.1 percent of the population. At first glance, the rates at which traditionally illegal substances are consumed appear inversely related to their addictive potential and to measures of their associated health risks. On the one hand, a medical study on addiction shows that heroin and some stimulants (methamphetamines) are the most addictive drugs, and, as Figure 1 shows, they are used by only a small portion of the population. On the other hand, another study, which focuses on the risk of acute reaction and death, shows that the least hazardous drugs are hallucinogens and marijuana, the latter of which is the most widely consumed, according to Figure 1.3 These are interesting facts for discussing theories of addiction.

Uncertainty and the Economy

Abstract: or a while now, comments from financial market participants and business executives have suggested that high levels of uncertainty have been a key reason for the economy's sluggish performance during the current business expansion. If the business and financial community believes the near-term outlook is murkier than usual, then the pace of hiring and outlays for capital spending projects may be unnecessarily constrained, thereby slowing the overall pace of economic activity. Monetary policymakers are also not immune to the challenges posed by rising levels of economic uncertainty. This has been noted in the minutes of several recent meetings of the Federal Open Market Committee (FOMC). Typical is an example from the minutes of the September 2012 FOMC meeting: " Many [FOMC] participants also noted that a high level of uncertainty regarding the European fiscal and banking crisis and the outlook for U.S. fiscal and regulatory policies was weighing on confidence , thereby restraining household and business spending. " This article will discuss the concept of economic uncertainty, how some economists measure it and how rising uncertainty can slow the growth of economic activity. Uncertainty and its effects on commerce (business decision-making) are often studied in the context of decisions to expand—chiefly through increased hiring and additions to the capital stock (fixed investment). These decisions naturally affect the firm's profits. The link between uncertainty and profit was further refined by introducing the concept of risk. To many lay people, risk and uncertainty appear to be the same thing, but to economists there is a subtle distinction. The difference between risk and uncertainty was discussed nearly 100 years ago by the economist Frank Knight. According to Knight: " There is a fundamental distinction between the reward for taking a known risk and that for assuming a risk whose value itself is not known. It is so fundamental, indeed, that … a known risk will not lead to any reward or special payment at all. " 1 What Knight meant is that the unfavorable outcome of a known risk can be insured against during the decision-making process because it has a well-defined distribution of expected probabilities. Life insurance companies, for example, have a reasonably accurate estimate of how many policies will pay off in a given year because of mortality statistics. However, an unknown risk does not have a known distribution of expected probabilities. For example, should a firm devote its scarce resources …

There are two sides to every coin—even to the bitcoin, a virtual currency

Abstract: Central to Bitcoin is its independence from any institution or government, allowing anyone to engage in a direct transaction at a low cost. So, what exactly is it, and how does it work?

The Fed's Strategy for Exiting from Unconventional Policy: Key Principles, Potential Challenges

Abstract: In the wake of the crisis, the Fed’s balance sheet increased from the historical 6 percent of GDP to more than 20 percent. As plans are made to return to normal monetary policy, it’s important to be aware of the challenges and potential pitfalls of this transition.

Student-Loan Debt in the District: Reasons behind the Recent Increase

Abstract: The aggregate value of outstanding debt from student loans in the U.S. has grown to about $1 trillion and is now greater than both credit card debt ($670 billion) and auto debt ($810 billion). This amounts to about $3,185 per capita.1 Recent trends suggest that college-loan balances will continue to expand at a rapid pace. Over the past decade, the college tuition and fees component of the consumer price index increased by 6.4 percent per year, while the broader index increased by only 2.4 percent per year. Over the same period, college enrollment increased by 37 percent,2 and, according to the Project on Student Debt, about two out of every three college graduates had student-loan debt, with an average balance of about $27,000.3 Large student-loan balances may have long-term economic consequences, as new graduates saddled with debt may struggle to make payments, fail to save for down payments on a home or be unable to get a loan to buy a car. On the other hand, the lifetime return on investment (ROI) for higher education tends to be significant, typically measured as higher income and lower levels of unemployment. As long as an ROI for education exists, families may see a benefit in taking on debt to pay for college.4 However, college graduation and a higher-paying job are not guaranteed; as a result, the long-term economic impact of the growing debt for attending college is somewhat unclear. In this article, we look at the growth in student-loan debt in the states that constitute the Federal Reserve’s Eighth District.5 We examine possible factors that may explain why the amount of student-loan debt has expanded, and we consider how differences in tuition growth and college-enrollment growth may cause variation across states.6 The table’s three columns under “Debt Growth” indicate growth in debt per capita of individuals aged 25-34 in each of the Eighth District states, as well as in the United States, between 2005 and 2013.7 Between these two years, average debt per capita in the U.S. grew by 140 percent, to $9,894 as of the first quarter of 2013. On average, the increases in student debt since 2005 were larger for Eighth District states than for the nation. In Kentucky, debt per capita more than tripled, while Missouri experienced the slowest growth, at 120 percent. Debt balances are roughly 25 percent of per capita income in the corresponding states, ranging from $8,430 in Arkansas to $11,236 in Illinois.

Who is concealing earnings and still collecting unemployment benefits

Abstract: Concealed earnings represent the largest source of fraud in the U.S. unemployment insurance system. Individuals with relatively low earnings constitute a larger fraction of those committing such fraud. High-earnings individuals, however, account for larger dollar amounts of this fraud.

Europe May Provide Lessons on Preventing Mortgage Defaults

Abstract: During the last global recession, house prices fell in some European countries almost as much as in some U.S. states. However, mortgage defaults occurred at a much lower rate in Europe. The authors say the difference might be explained by two regulations that apply in Europe but are used on a limited or much less restrictive basis in the U.S.

A view from the fiscal cliff

Abstract: January’s deal on the so-called fiscal cliff only raised projected revenue moderately and continued to push the spending issue forward unresolved. The economy may have been slowed down by such a drawn-out process, as well as by the uncertainty on the future size of government and on the distribution of the tax burden.

Urban areas host the largest manufacturing and service employers

Abstract: Over the past few decades, manufacturing employment as a share of total employment has declined across the U.S., with most of the manufacturing jobs lost in metropolitan areas. At the same time, cities have become increasingly more service-oriented.1 Despite this general trend, metropolitan areas—and, in particular, large metropolitan areas—still contain the great majority of manufacturing jobs. Similar to those across the U.S., urban areas in the Eighth District host the largest employers in manufacturing; urban areas also host the largest service employers. While service industries naturally thrive near large concentrations of people, manufacturing industries also gain from locating in urban areas, where they are near suppliers and firms in similar or related industries, including firms in related financial, legal and educational services. Cities also provide manufacturing firms potential workers of varying skill levels. Understanding the existing location patterns of both manufacturing and service industries is important because firms’ location choices are in response to not only geographic advantages but also to public policies aimed at promoting employment growth or at developing targeted industries in certain areas.2 This article describes the geographic distribution of the largest (by employment) manufacturing and service industries in the 339 counties in the Eighth District. The best data for analyzing the distribution of industries and establishments across counties come from the County Business Patterns (CBP) statistics of the U.S. Census Bureau. The data are the latest available—as of March 2011.3 The analysis reveals interesting patterns. First, we found that in the Eighth District, both the largest manufacturing and the largest service industries were related to the food industry. Other important manufacturing industries were related to the auto industry, while other important service industries were related to the health-care industry. We also found that manufacturing employment was concentrated in a small number of industries, whereas service employment was spread across a larger number of industries. In addition, the average manufacturing establishment employed about three times as many people as did the average service establishment. Finally, except for a handful of counties in smaller urban areas—such as Tupelo, Miss.; Jasper, Ind.; and Paducah, Ky.—the largest concentrations of manufacturing and service employment and establishments occurred in or around the largest metro areas of the District.

Mortgage borrowing: the boom and bust

Abstract: Also titled as "Mortgage Boom and Bust Affected Different Age Groups Differently" in PDF format.

Changes in the racial earnings gap since 1960

Abstract: Income inequality between races has been a widely used indicator of economic prosperity and opportunity (or the lack thereof) within the diverse population of the U.S. The Civil Rights Act of 1964 prohibited discrimination in public places, provided for the integration of schools and other public facilities, and made employment discrimination illegal, thus improving the quality of education and providing more job opportunities for African-Americans. Nevertheless, disparities remain.

Higher taxes for top earners: can they really increase revenue?

Abstract: re top-income households paying enough taxes? Increasing top income-tax rates in the U.S. would result in larger government revenue, according to a 2011 academic study by Peter Diamond, winner of the Nobel Prize for economics in 2010, and by Emmanuel Saez, winner of the John Bates Clark Medal in 2009.1 Their study argues that households in the top 1 percent of income distribution should pay a marginal tax rate in the range of 54-80 percent. Such a rate would be substantially higher than the current one, which is approximately 42.5 percent.2 The Diamond-Saez proposal has fueled a debate in the blogosphere, in academic circles and in Washington, D.C. One of the reasons is that top income-tax rates of this magnitude can be popular among many voters and, therefore, could become a reality in the future. Recently in France, presidential candidate Francois Hollande promised a 75 percent top income-tax rate during his campaign in order to attract left-wing voters and, according to The Economist, made this tax rate a centerpiece of his budget program.3 Perhaps aided by this promise, Hollande became the first left-wing president of France since Francois Mitterrand (who served from 1981 to 1995). However, the top-tax reform was ultimately rejected by the French parliament near the end of last year. In spite of all the discussion, few people understand the calculations behind the Diamond-Saez recommendation. This article provides a quick introduction to their calculations and concludes with a brief description of some factors that may be important for discussing their recommendation. The Facts behind the Calculations

Why was the decline in U.S. trade larger this time? a global view

Abstract: The decline in U.S. trade during the Great Recession was worse than during previous recessions. But the difference was not merely due to the severity of the U.S. recession.

Population and migration trends in the District differ from nation's

Abstract: Economists who study urban areas argue that cities lead to higher levels of productivity due to agglomeration economies. In other words, the higher the density of individuals, the higher the overall level of productivity within that area. To examine the potential for productivity growth in the Eighth District, we looked at population and population density growth trends between 2000 and 2011. The District, whose population grew 6.5 percent since 2000 and 2.0 percent since 2007,1 experienced significant growth in its metro areas.2 To illustrate, Table 1 indicates that the population in the District’s metro areas grew 9.9 percent since 2000 and 2.9 percent since 2007. During these time periods, three of the four major metro areas in the District grew at rates lower than the nation’s. Specifically, the populations in Louisville, Memphis and St. Louis grew 11.0 percent, 9.7 percent and 4.3 percent, respectively, since 2000 and 3.6 percent, 2.5 percent and 1.3 percent since 2007. Little Rock grew 15.9 percent since 2000 and 5.7 percent since 2007, rates higher than the District’s and the nation’s cities. The District’s largest levels of growth, however, came from some of the smaller metro areas. Of these areas, the fastest growers were Fayetteville-SpringdaleRogers, Ark.-Mo. (35.6 percent since 2000 and 8.5 percent since 2007); Bowling Green, Ky. (22.0 percent since 2000 and 6.9 percent since 2007); Columbia, Mo. (20.3 percent since 2000 and 6.1 percent since 2007); and Springfield, Mo. (19.0 percent since 2000 and 4.0 percent since 2007). Only one area—Pine Bluff, Ark.—showed a population decline (–7.7 percent since 2000 and –2.9 since 2007). TablE 1