Full Recovery by 2018, says the CBO

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Twice each year, the Congressional Budget Office publishes a "Budget and Economic Outlook" for the next 10 years. The just-released August version offers a timeline for the eventual recovery of the U.S. economy to its pre-recession path of economic growth, and some worries about the budget fights that are scheduled to erupt later this year.

On the subject of eventual full recovery, the CBO regularly estimates the "potential GDP" of the U.S. economy: that is, what the U.S. economy would produce if unemployment was down to a steady-state level of about 5.5% and steady growth was occurring. During recessions, of course, the economy produces below its potential GDP. During booms (like the end of the dot-com period in the early 2000s and the top of the housing price bubble in about 2005-2006), it's possible for an economy to produce more than its potential GDP, but only for a short-term and unsustainable period. Here's the CBO graph comparing actual and potential GDP since 2000. The shallowness of how much the recession in 2001 caused actual GDP to fall below potential, compared to the depth and length of how much actual GDP has fallen below potential in the aftermath of the Great Recession, is especially striking. 

This scenario in which the U.S. economy returns to potential GDP in 2018 requires a period in which the U.S. economy shows some rapid growth. Here's a graph showing the growth rate of the U.S. economy vs. that of the average of major U.S. trading partners (weighted by how much trade the U.S. economy does with each of them). "[T]he trading partners are Australia, Brazil, Canada, China, Hong Kong, Japan, Mexico, Singapore, South Korea, Switzerland, Taiwan, the United Kingdom, and countries in the euro zone." Notice that the prediction is for a substantial burst of growth around 2014, and lasting for a couple of years.


However, the eagle-eyed reader will note that these growth predictions from the CBO also show a period of negative growth--that is, a recession--in the near future. Similarly, the earlier figure showing a gap between actual and potential GDP shows that gap widening in the near future, before it starts to close. Why? The CBO is required by law to make baseline projections that reflect the laws that are actually on the books. And currently, "sharp increases in federal taxes and reductions in federal spending that are scheduled under current law to begin in calendar year 2013 are likely to
interrupt the recent economic progress. ... The increases in federal taxes and reductions in federal
spending, totaling almost $500 billion, that are projected to occur in fiscal year 2013 represent an amount of deficit reduction over the course of a single year that has not occurred (as a share of GDP) since 1969." These changes mean that the baseline CBO projection is for a recession in 2013.

The currently changes in taxes and spending can be changed, of course, and along with its baseline estimate, the CBO estimate an alternative scenario for comparison. "Of course, the tax and spending policies that are scheduled to take effect under current law may be delayed or modified. To illustrate how some changes to current law would affect the economy over the next decade, CBO analyzed an alternative fiscal scenario that would maintain many policies that have been in place for several
years. Specifically, that scenario incorporates the assumptions that all expiring tax provisions (other than the payroll tax reduction) are extended indefinitely; the alternative minimum tax is indexed for inflation after 2011; Medicare’s payment rates for physicians’ services are held constant at their current level; and the automatic spending reductions required by the Budget Control Act of
2011 (Public Law 112-25) do not occur (although the original caps on discretionary appropriations remain in place) ..."

Other scenarios are possible, of course. But several points seem worth making.

The CBO alternative scenario does not predict a recession in the short-term, and it predicts higher growth in the next few years. But the alternative scenario also means that the budget deficits are reduced by less, which means that growth slows down. The CBO prediction is that by 2022, the U.S. economy would be larger under the baseline scenario--with a recession in 2013--than it would be with the alternative scenario. This is a standard tradeoff in thinking about budget deficits: in the short run, spending cuts and tax increases are always unattractive, but unless a government figures out a way to reduce outsized deficits, long-run economic growth will be hindered. 

The obvious policy conclusion here, it seems to me, is that having all the scheduled changes to taxes and spending hit in 2013 is too much of a burden for an already-struggling U.S. economy, and should be avoided. But it remains tremendously important to get the U.S. budget deficits headed in a downward direction in the medium-term, certainly before the 10-year horizon of these predictions. 

Moreover, it would be useful for the U.S. economy, in the sense of reducing uncertainty, if the political system would stop gaming the budget process. That is, stop the ongoing cycle of having taxes that are scheduled to rise in a few years, or spending that it scheduled to be cut in a few years. Sure, writing down projections that show higher taxes or lower spending in a few years makes the 10-year deficit projections look better, but it also leads to waves of uncertainty cascading through the economy as these policies perpetually are hitting their expiration dates. 

Are CEO's Overpaid?

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Are CEO's Overpaid? I confess that my knee-jerk answer to this question is "YES"! But Steve Kaplan makes a strong case for a more nuanced answer in Executive Compensation and Corporate Governance in the U.S.: Perceptions, Facts and Challenges," published in July as Chicago Booth working paper 12-42. Here's a sketch of some of  his arguments and graphs.

 First, just as a matter of getting the facts straight, CEO pay relative to household income did spike back in the go-go days of the dot-com boom in the late 1990s, but since then, it is relatively lower. Kaplan argues that there are two valid ways to measure executive pay. One measure looks at actual pay received, which he argues is useful for seeing whether top executives are paid for performance. The other measure looks at "estimated" pay, which is the amount that financial pay packages would have been expected to be worth at the time were granted. This calculation requires putting a value on stock options, restricted stock grants, and the like, and estimating what these were worth at the time the pay package was given. Kaplan argues that this measure is the appropriate one for looking at what corporate boards meant to do when they agreed on a compensation package.

Here's one figure showing actual average and median pay totals for S&P 500 CEOs from 1993 to 2010. Average pay is above median pay, which tells you that there are some very high-paid execs at the top pulling up the average.  Also, average CEO pay spikes when the stock market is high, as in 2000 and around 2006 an  2007. Median realized pay seems to have crept up over time. 
Here's a figure showing estimated pay--that is, the value of the pay packages when they were granted. But this time, instead of showing dollar amounts, this graph shows average and median CEO pay as a multiple of median household income. Average pay again spikes at the time of the dot-com boom. Kaplan emphasizes that estimated CEO pay is on average lower than in 2000 and that the median hasn't risen much. My eye is drawn to the fact that median pay for CEOs goes from something like 60 times median household income back in 1993 to about 170 times median household income by 2010.

An obvious question is whether these pay levels are distinctive for CEOs, or whether they are just one manifestation of widening income inequality across a range of highly-paid occupations. Kaplan makes a solid case that it is the latter. For example, here's a graph showing the average pay of the top 0.1% of the income distribution compared with the average pay of a large company CEO.Again, the story is that CEO pay really did spike in the 1990s, but by this measure, CEO pay relative to the top 0.1% is now back to the levels common in the the 1950s.

  

Kaplan also points out that the pay of those at the top of other highly-paid occupations has grown dramatically as well, like lawyers, athletes, and hedge fund managers. Here's a figure showing the pay of top hedge fund managers relative to that of CEOs in the last decade. Kaplan writes: "The top 25 hedge fund managers as a group regularly earn more than all 500 CEOs in the S&P 500. In other words, while public company CEOs are highly paid, other groups with similar backgrounds and talents have done at least equally well over the last fifteen years to twenty years. If one uses evidence of higher CEO pay as evidence of managerial power or capture, one must also explain why the other professional groups have had a similar or even higher growth in pay. A more natural interpretation is that the market for talent has driven a meaningful portion of the increase in pay at the top."   

Kaplan also compiles evidence that CEOs of companies with better stock market performance tend to be paid more than those with poor stock market performance, and that CEOs have shorter job tenures. He writes: Turnover levels since 1998 have been higher than in work that has studied previous periods. In any given year, one out of 6 Fortune 500 CEOs lose their jobs. This compares to one out of 10 in the 1970s. CEOs can expect to be CEOs for less time than in the past. If these declines in expected CEO tenures since 1998 are factored in, the effective decline in CEO pay since then is larger than reported above."And the CEO turnover is related to poor firm stock performance ..."

To me, Kaplan makes a couple of especially persuasive points: the run-up in CEO salaries was especially extreme during the 1990s, and less  so since then (depending on how you measure it); and the run-up in CEO salaries reflects the rise in inequality across a wider swath of professions. While I believe the arguments that job tenure can be shorter for the modern CEO, especially if a company isn't performing well, it seems to me that most former CEO's don't plummet too many percentiles down the income distribution in their next job, so my sympathy for them is rather limited on that point.

In this paper, Kaplan doesn't seek to address the deeper question of why the pay for those at the very top, CEOs included, has risen so dramatically.  While the demand for skills at the very top of the income distribution is surely part of the answer, I find it hard to believe that these rewards for skill increased so sharply in the 1990s--just coincidentally during a stock market boom. It seems likely to me that
  cozy institutional arrangements for many of those at the very top of the income distribution--CEOs, hedge fund managers, lawyers, and athletes and entertainers--also plays an important role.  

Labor's Smaller Share

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Margaret Jacobson and Filippo Occhino have been investigating the fact that labor has been receiving a declining share of total economic output over the last few decades. I posted on their work last February in "Labor's Declining Share of Total Income."  Now they have written "Labor’s Declining Share of Income and Rising Inequality," which is "Economic Commentary" 2012-13 published by the Federal Reserve Bank of Cleveland.


The starting point is to look at labor income relative to the size of the economy. The top line in the figure shows labor income as a share of GDP, as measured in the national income and product accounts from the U.S. Bureau of Economic Analysis. The lower line in the figure shows the ratio of compensation to output for the nonfarm business sector, as measured by the U.S. Bureau of Labor Statistics. The measures are not identical, nor would one expect them to be, but they show the same trend: that is, with some ups and downs as the economy has fluctuated, the labor share of income has been falling for decades, and is now at an historically low figure.

 This fact lies behind much of the rise in inequality of incomes over this time. The income that is not being earned by labor is being earned by capital--and capital income is much more concentrated than is labor income. Jacobsen and Occhino offer an intriguing figure that measures the inequality of labor income and the inequality of capital income. The measure used here is a Gini coefficient, which "ranges between 0 and 1, with 0 indicating an equal distribution of income and 1 indicating unequal income." (Here's an earlier post with an explanation of Gini coefficients.)
The figure has two main takeaways. First, labor income has become more unequally distributed over time, but since the early 1990s, the big shift in income inequality is because capital income is more unequally distributed. Second, capital income tends to rise during booms and to fall in recessions. Thus, it seems plausible that the inequality of capital income has dropped in the last few years of the Great Recession and its aftermath, but will rise again as economic growth recovers.

What has caused the long-run decline of the labor share of income? Jacobson and Occhino explain this way: "[W]e begin by looking at what determines the labor share in the long run. The main factor is the technology available to produce goods and services. In competitive markets, labor and
capital are compensated in proportion to their marginal contribution to production, so the most important factor behind the labor and capital shares is the marginal productivities of labor and capital, which are determined by technology. In fact, one important cause of the post-1980 long-run decline in the labor share was a technological change, connected with advances in information and
communication technologies, which made capital more productive relative to labor, and raised the return to capital relative to labor compensation. Other factors that have played a role in the long-run decline in the labor share are increased globalization and trade openness, as well as changes in
labor market institutions and policies."

There is no particular reason to believe that these trends will continue--or that they won't. But the declining share of income going to labor suggests the importance of finding ways to increase the marginal product of labor, especially for workers of low and medium skills, perhaps by focusing on the kind of training and networking that might help them make greater use of the advances in information and communication technology to improve their own productivity.

What's Up With the Dodd-Frank Legislation?

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Back in July 2010, President Obama signed into law the Dodd-Frank Wall Street Reform and Consumer Protection Act. The difficulty with the law has always been that while it was fairly clear on its goals, it did not specify how to reach those goals--instead turning over that task to current and newly-created regulatory agencies.  If you're looking for an update on how the law is proceeding, a good starting point is the Third Quarter 2012 issue of Economic Perspectives, published by the Federal Reserve Bank of Chicago, which has six articles on the Dodd-Frank legislation.

Douglas D. Evanoff and William F. Moeller offer an overview of the goals and approach of the law in their opening piece (footnotes and citations omitted):

"The stated goals of the act were to provide for financial regulatory reform, to protect consumers
and investors, to put an end to too-big-to-fail, to regulate the over-the-counter (OTC) derivatives markets, to prevent another financial crisis, and for other purposes. ... Implementation of Dodd–Frank requires the development of some 250 new regulatory rules and various mandated studies. There is also the need to introduce and staff a number of new entities (bureaus, offices, and councils) with responsibility to study, evaluate, and  promote consumer protection and financial stability. Additionally, there is a mandate for regulators to identify and increase regulatory scrutiny of systemically important institutions.  ... Two years into the implementation of the act, much has been done, but much remains to be done."

How are those rules coming along? The law firm of Davis Polk & Wardwell publishes a regular Dodd-Frank report. The September 2012 edition summarizes:

• "As of September 4, 2012, a total of 237 Dodd-Frank rulemaking requirement deadlines have
  passed. This is 59.5% of the 398 total rulemaking requirements, and 84.6% of the 280
  rulemaking requirements with specified deadlines.
• "Of these 237 passed deadlines, 145 (61.2%) have been missed and 92 (38.8%) have been
  met with finalized rules. Regulators have not yet released proposals for 31 of the 145 missed
  rules.
• "Of the 398 total rulemaking requirements, 131 (32.9%) have been met with finalized rules and
  rules have been proposed that would meet 135 (33.9%) more. Rules have not yet been
  proposed to meet 132 (33.2%) rulemaking requirements.

The July 2010 Davis Polk update--the two-year anniversary of the legislation--offers some additional detail: "The two years since Dodd-Frank’s passage have seen 848 pages of statutory text expand to 8,843 pages of regulations. Already at almost a 1:10 page ratio, this staggering number represents
only 30% of required rulemaking contained within Dodd-Frank, affecting every area of the financial markets and involving over a dozen Federal agencies."

It's important to  recognize that writing a new regulation isn't as simple as, well, just writing it. Instead, there is often first an in-house study, followed by a draft regulation, which then is open to public comments, and then can revised, and eventually at some point a new regulation is created. It's not unusual for a regulation to get dozens or hundreds of detailed public comments.

This blizzard of evolving rules has to create considerable uncertainty in the financial sector. Matthew Richardson discusses the complexities of one particular issue in his contribution to the Chicago Fed publication. He picks one example: the problem that many banks made very low-quality subprime mortgage loans. What does the Dodd-Frank legislation do about this basic issue? As he describes, the act: 1) Sets up a Consumer Finance Protection Bureau in title X to deal with misleading products; 2)
Imposes particular underwriting standards for residential mortgages; 3) Requires firms performing securitization to retain at least 5 percent of the credit risk; and 4) Iincreases regulation of credit rating agencies. Each of these tasks requires detailed rulemaking. And as Richardson points out, "with all of these new provisions, the act does not even address what we at NYU Stern consider to be a primary fault for the poor quality of loans—namely, the mispriced government guarantees in the system that led to price distortions and an excessive buildup of leverage and risky credit."

I'm skeptical of anyone who has strong opinions about the Dodd-Frank legislation, because here we are more than two years later, less than halfway toward figuring out what rules the legislation will actually put in place. Wayne A. Abernethy of the American Bankers Association is one of the authors in the Chicago Fed symposium. Yes, he is speaking for the bankers' point of view. But his judgement about the overall process seems fair to me:

"At least in the financial regulatory history of the United States, there has never been anything like it. I have seen no definitive count of the number of regulations that the Dodd–Frank Act calls forth. The numbers seem to range between 250 and 400—numbers so large that they are numbing. It all defies hyperbole. The Fair and Accurate Credit Transactions Act, adopted in 2003, astonished the financial industry with more than a dozen significant new regulations to be written. ...

"One of the most common criticisms of Dodd–Frank implementation has been a lack of order and coordination in the regulatory process. Instead, the Dodd–Frank Act has succeeded in replacing the financial crisis with a regulatory crisis.  ... As agencies are grappling with impossible rulemaking tasks, most of them are also engaged in major structural reorganizations and shifts in the areas of responsibility. ... Nothing like this has ever been tried before in the history of the United States. Writing 400 financial regulations of the highest significance and the greatest complexity in a couple of years has clearly been too much to expect. ... Getting on with the work to end our self-inflicted regulatory crisis should be among the highest priorities."

 I'm someone who believes that financial regulation needed shaking up. Many of the broad goals of the Dodd-Frank legislation make sense to me: rethinking bank and regulation to deal with macroeconomic risk, not just the risk of an individual institution going broke; figuring out better ways to shut down even large financial institutions when needed; and better regulation of certain financial instruments like credit default swaps and repo agreements; a closer look at technologies that allow ultra-high-speed financial trading; and others.

The Dodd-Frank legislation is almost not a law in the conventional meaning of the term, because it mostly isn't about actual specific activities that are prohibited. Instead, it's about handing over the difficult problems to regulators and telling them to fix it. I'm not sure there was an easy alternative to this regulatory approach: the idea of Congress trying to debate, say, appropriate regulation of the over-the-counter swaps market is not an encouraging thought. But stating a goal is not the same as solving a problem. The passage of Dodd-Frank, in and of  itself, didn't solve any problems.

Expanding U.S. Exports of Services

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When I'm asked (usually with deep suspicion) about how globalization benefits the U.S. economy, I of course have my pre-packaged explanation about comparative advantage, specialization, and gains from trade. But I've found that another answer is often more powerful. The main growth in the world economy in the next few decades is, by all accounts, most likely to be in nations like China, India, Brazil, and others. The U.S. economy should be looking for ways to hitch itself to this growth locomotive--and globalization is one name for this process.
Pedro Amaral and Margaret Jacobson offer some encouraging recent news about U.S. exports in a short article in  Economic Trends from the Federal Reserve Bank of Cleveland. "In fact, despite the recovery’s frustratingly slow growth, exports have averaged 8 percent yearly growth since the beginning of 2010 and continue to reach record levels in terms of total nominal and real dollars. The ratio of exports to GDP has been growing at a far faster rate in the current recovery than in an average one." They point to strong demand from abroad--and it's not from high-incomne countries like Europe or Japan!--as well as to a lower foreign exchange rate of the U.S. dollar as driving the rise in exports.



But how can the high-wage U.S. economy hope to compete in the lower-wage world economy? J. Bradford Jenson offers a nice discussion of "Opportunities for U.S. Exports of Business Services" in some recent Congressional testimony that I ran across at the website of the Peterson Institute for International Economics.

I liked Jenson's discussion because it pushes all of us to see international trade and the U.S. economy as it operates today, not through a gauzy nostalgia for the role played by manufacturing in the U.S. economy of a  half-century ago.  He writes :

"When we think of trade, most of us envision wheat, copper, crude oil, and manufactured goods such as clothing, furniture, consumer electronics, cars, and jet aircraft. We need only visit a port, border crossing, or big-box superstore to find an abundance of such goods from virtually every country in the world. By contrast, many believe the service sector is largely insulated from the international economy. Because many services require face-to-face interaction between buyer and seller, the prevailing assumption is that most services are not tradable. This belief has always been a misconception, and in today’s economy, it is an increasingly inappropriate one. The falling costs of travel and increased ease of communications, thanks to the Internet, have vastly expanded opportunities for services to be traded across long distances, including across borders."

He focuses in particular on "business services." "This group includes the information, finance and insurance, real estate, professional, scientific, and technical industries; management, administrative support, and waste remediation industry groups; and industries such as software, engineering services, architectural services, and satellite-imaging services. ... The business service sector accounts for about 25 percent of the US labor force—two and a half times the size of the manufacturing sector. Moreover, the business service sector is growing. Over the past decade or so, manufacturing sector
employment has decreased by about 20 percent, while business services have increased by about 30 percent. And business service jobs are good jobs: Average wages in business services are more than 20 percent higher than average wages in manufacturing.

"Many people hold an outdated view of the US economy. Just as an example, consider the relative size of one service industry, engineering services, relative to two important manufacturing industries: the automotive industry (including assembly and parts) and the aerospace industry. It might surprise you to learn that engineering services is the largest in terms of employment. Engineering services (NAICS 541330) employed 980,000 people in 2007—more than the automotive industry (910,000), and more than twice as many as aerospace (440,000), according to the most recent economic census. Average earnings in engineering services ($73,000) are significantly higher than in auto production ($52,000) or even in aerospace ($68,000)."

Here's a figure from the ever-useful FRED website at the St. Louis Fed showing the trade surplus that the U.S. economy has been running in the service sector as a whole.  The figure shows monthly data, so the U.S. trade surplus in services has been was running about about $5-6 billion per month for much of the 1990s and first half of the 2000s--call it $60-$72 billion per year. But since early 2011, the monthly trade surplus in services has been more like $15 billion per month--call it a services trade surplus of $180 billion per year.



Jensen's testimony focuses in particular on how world trade talks could bring down barriers to exports of U.S business services, and while that is important, I suspect it is at least as important that U.S. business services providers have been orienting themselves more toward international markets. As the U.S. government and economy struggles to get its debt burdens under control in the years to come, export growth in services is one of the most promising sources of additional demand for U.S.-made output.

Presidential Predictions From Economic Data

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The performance of the economy clearly has an influence on presidential elections. What are such models saying about the like outcome of an Obama-Romney election? Here are three examples: from Ray Fair, from Douglas Hibbs, and from the team of Michael Berry and Kenneth Bickers.

For some years now, Ray Fair has been experimenting with different relationships between economic variables and the outcome of national elections. For example, my own Journal of Economic Perspectives published an article he authored on this subject back in the Summer 1996 issue.  Just after the results of the November 2010 elections were known, he published "Presidential and Congressional Vote-Share Equations: November 2010 Update." Based on the fit of the past  historical data, he offers this equation:


VP = 48.39 + .672*G - .654*P + 0.990*Z

VP is the Democratic share of the two-party presidential vote in 2012. G is the growth rate of real per capita GDP in the first 3 quarters of 2012. P is the growth rate of the GDP deflator in the first 15 quarters of the Obama administration. And Z is the number of quarters in the first 15 quarters of theObama administration in which the growth rate of real per capita GDP is greater than 3.2 percent at an annual rate.

Obviously, the third quarter GDP of 2012 GDP numbers will not be officially announced until after the election--although one can argue that they will be perceived by people in the economy as they happen. Just for the sake of argument, if one plugs in a 1.5% growth rate for real per capita GDP in the first three quarters of 2012, a 1.5% growth rate for the GDP deflator (a measure of inflation) and 2 quarter of real per capita GDP growth above 3.2% (that is, fourth quarter 2009 and fourth quarter 2011), then Fair's equation says that Obama will get 50.4% of the two-party vote--and thus (assuming not too much weirdness in the Electoral College) would narrowly win re-election.


An obvious question about Fair's equation is that it doesn't t include a separate variable for the unemployment rate. Why not? The answer is that researchers like Fair have experimenting with a wide variety of different kinds of economics data. For Fair, the equation given above is the one that predicts best over the elections from 1916 up through 2008. It's worth remembering that presidents have often been re-elected with a fairly high unemployment rate, like Franklin Roosevelt during the Great Depression, or Ronald Reagan when the unemployment rate was 7.4% in October 2004.

However, my guess is that in the context of 2012, Fair's equation will tend to overstate Obama's changes. I think the sustained high rates of unemployment will be more salient in the 2012 election than they may have been in some past elections. Also, Fair's equation is that it gives Obama credit for the low rate of inflation during his term of office--but it's not clear that in 2012, the low rate of overall inflation is getting Obama a lot of political credit. Fair's equation gives Obama extra credit for the two good quarters of economic growth during his presidency--and I'm not sure that in the broader context of a slow recovery, Obama will get much political credit for those two quarters.

Douglas Hibbs takes a related but different approach to economic variables and presidential election outcomes in his "Bread and Peace" model. He starts off by using the average of per capita real economic growth over the incumbent president's term, and uses that to predict the incumbent's share of the two-party vote. The result, as shown in the best-fit line in the figure below, is that some of the years where the incumbent did much worse than expected were years with a large number of military fatalities, like 1952 and 1968.



Thus, Hibbs added a second explanatory variable, military fatalities, and with the addition of that extra factor most of the points showing actual voting shares fall closer to best-fit line.  As the figure shows, based on economic data through the end of 2012, Obama would receive 45.5% of the two-party vote. The Hibbs equation doesn't give Obama credit for a low inflation rate.

 

Like Fair, Hibbs doesn't include an unemployment variable. But of course, these sorts of disputes over what should be included in drawing connections from economic data to election results just illustrates a broader point: every election has unique characteristics, starting with the actual candidates. In the 1996 election, Bill Clinton did better than would have been expected based on Hibbs formula. In the 2000, Al Gore (who was from the "incumbent" party), did considerably worse than would have been expected. Public perceptions of the candidates, non-economic policies, and the actual events during the campaign clearly matter as well.

Michael Berry and Kenneth Bickers take a different approach in "Forecasting the 2012 Presidential Election With State-Level Economic Indicators."  Instead of trying to predict the overall national popular vote, they instead estimate an equation for each of 50 states and the District of Columbia. They also use a more complex set of variables. They emphasize economic variables like the change in each state in real per capita income, the national unemployment rate, the state-level unemployment rate. But they also include variables for the vote received by that party in the previous election, a variable for whether the incumbent is a Democrat or a Republican, and for how many terms in a row the presidency would be held by a particular party. These terms then interact with the economic variables. A variable for the home state of each presidential candidate is also included.

The strength of the Berry/Bickers approach is that with this extra detail, their equation correctly predicts all of presidential elections from 1980 to 2008. The weakness is that if you add enough variables and complexity, you can always create an equation that will match the past data, but your results can be quite sensitive to small tweaks in the variables that you use. Thus, it's hard to have confidence that a complex equation is will be an accurate predictor.  For what it's worth, their equation predicts that Romney will win the 2012 election rather comfortably, with more than 52% of the popular vote. As they point out: "What is striking about our state-level economic indicator forecast is the expectation that Obama will lose almost all of the states currently considered as swing states, including North Carolina, Virginia, New Hampshire, Colorado, Wisconsin, Minnesota, Pennsylvania, Ohio, and Florida."


In terms of narrowly economic influences on the presidential race, there are just two more monthly unemployment reports that will come out before the election in November. There won't be too much new economic data, either. Thus, my suspicion is that the ways in which economic outcomes affect presidential preferences are in large part already being taken into account in the presidential polls, which currently show a tight race.

Are CEO's Overpaid?

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Are CEO's Overpaid? I confess that my knee-jerk answer to this question is "YES"! But Steve Kaplan makes a strong case for a more nuanced answer in Executive Compensation and Corporate Governance in the U.S.: Perceptions, Facts and Challenges," published in July as Chicago Booth working paper 12-42. Here's a sketch of some of  his arguments and graphs.

 First, just as a matter of getting the facts straight, CEO pay relative to household income did spike back in the go-go days of the dot-com boom in the late 1990s, but since then, it is relatively lower. Kaplan argues that there are two valid ways to measure executive pay. One measure looks at actual pay received, which he argues is useful for seeing whether top executives are paid for performance. The other measure looks at "estimated" pay, which is the amount that financial pay packages would have been expected to be worth at the time were granted. This calculation requires putting a value on stock options, restricted stock grants, and the like, and estimating what these were worth at the time the pay package was given. Kaplan argues that this measure is the appropriate one for looking at what corporate boards meant to do when they agreed on a compensation package.

Here's one figure showing actual average and median pay totals for S&P 500 CEOs from 1993 to 2010. Average pay is above median pay, which tells you that there are some very high-paid execs at the top pulling up the average.  Also, average CEO pay spikes when the stock market is high, as in 2000 and around 2006 an  2007. Median realized pay seems to have crept up over time. 
Here's a figure showing estimated pay--that is, the value of the pay packages when they were granted. But this time, instead of showing dollar amounts, this graph shows average and median CEO pay as a multiple of median household income. Average pay again spikes at the time of the dot-com boom. Kaplan emphasizes that estimated CEO pay is on average lower than in 2000 and that the median hasn't risen much. My eye is drawn to the fact that median pay for CEOs goes from something like 60 times median household income back in 1993 to about 170 times median household income by 2010.

An obvious question is whether these pay levels are distinctive for CEOs, or whether they are just one manifestation of widening income inequality across a range of highly-paid occupations. Kaplan makes a solid case that it is the latter. For example, here's a graph showing the average pay of the top 0.1% of the income distribution compared with the average pay of a large company CEO.Again, the story is that CEO pay really did spike in the 1990s, but by this measure, CEO pay relative to the top 0.1% is now back to the levels common in the the 1950s.

  

Kaplan also points out that the pay of those at the top of other highly-paid occupations has grown dramatically as well, like lawyers, athletes, and hedge fund managers. Here's a figure showing the pay of top hedge fund managers relative to that of CEOs in the last decade. Kaplan writes: "The top 25 hedge fund managers as a group regularly earn more than all 500 CEOs in the S&P 500. In other words, while public company CEOs are highly paid, other groups with similar backgrounds and talents have done at least equally well over the last fifteen years to twenty years. If one uses evidence of higher CEO pay as evidence of managerial power or capture, one must also explain why the other professional groups have had a similar or even higher growth in pay. A more natural interpretation is that the market for talent has driven a meaningful portion of the increase in pay at the top."   

Kaplan also compiles evidence that CEOs of companies with better stock market performance tend to be paid more than those with poor stock market performance, and that CEOs have shorter job tenures. He writes: Turnover levels since 1998 have been higher than in work that has studied previous periods. In any given year, one out of 6 Fortune 500 CEOs lose their jobs. This compares to one out of 10 in the 1970s. CEOs can expect to be CEOs for less time than in the past. If these declines in expected CEO tenures since 1998 are factored in, the effective decline in CEO pay since then is larger than reported above."And the CEO turnover is related to poor firm stock performance ..."

To me, Kaplan makes a couple of especially persuasive points: the run-up in CEO salaries was especially extreme during the 1990s, and less  so since then (depending on how you measure it); and the run-up in CEO salaries reflects the rise in inequality across a wider swath of professions. While I believe the arguments that job tenure can be shorter for the modern CEO, especially if a company isn't performing well, it seems to me that most former CEO's don't plummet too many percentiles down the income distribution in their next job, so my sympathy for them is rather limited on that point.

In this paper, Kaplan doesn't seek to address the deeper question of why the pay for those at the very top, CEOs included, has risen so dramatically.  While the demand for skills at the very top of the income distribution is surely part of the answer, I find it hard to believe that these rewards for skill increased so sharply in the 1990s--just coincidentally during a stock market boom. It seems likely to me that
  cozy institutional arrangements for many of those at the very top of the income distribution--CEOs, hedge fund managers, lawyers, and athletes and entertainers--also plays an important role.