Measuring Changes in the Duration of Unemployment

In “The Folly of Subsidizing Unemployment,” Robert Barro attributes an increase in the observed duration of unemployment during the Great Recession to the extension of unemployment benefits from 26 to 99 weeks.  He supports his hypothesis by observing that the current recession is the only one in which benefits have been extended and that the duration of unemployment has been much greater.
A second method for measuring the impact of extending unemployment benefits on the duration of unemployment exists if states are allowed to follow different rules when awarding benefits.  Have any states declined to extend benefits, reduced the benefits over time or offered bonuses to the unemployed if they find work quickly?  If so, we can compare the duration of unemployment conditioned on the generosity of the state’s unemployment programs.  States with more generous programs should experience higher duration of unemployment if Barro is correct. 

The second method does have flaws.  The logic of the argument might reverse causality.  Perhaps the states with the longest duration of unemployment are the ones that extended benefits.  If this were the case and states can vary in allocation unemployment, then we would expect states with the longest duration to have increased the generosity of benefits.

Any thoughts?
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Barro On Extending Unemployment Benefits

I am dedicating a second post to Robert Barro’s article, “The Folly of Subsidizing Unemployment,” a rare occurrence.  The first post, “Barro on Obama’s Policy Objectives,” discussed a tangential point in Barro’s article.  The second will discuss his main point, that subsidizing long-term unemployment by extending benefits from 26 weeks to as much as 99 weeks is folly.  He begins by noting the tradeoff between efficiency and equity.

The unemployment-insurance program involves a balance between compassion—providing for persons temporarily without work—and efficiency. The loss in efficiency results partly because the program subsidizes unemployment, causing insufficient job-search, job-acceptance and levels of employment. A further inefficiency concerns the distortions from the increases in taxes required to pay for the program.

Peak Unemployment Rate	Nov-Dec 82	Oct 09
Unemployment Rate	10.8%	10.1%
Mean Duration (Weeks)	17.6	27.2
Long-term Share	20.4%	36.0%

Peak Mean Duration (Weeks)	Jul 83	June 10
Unemployment Rate	9.4%	9.5%
Mean Duration (Weeks)	21.2	35.2
Long-term Share	24.5%	46.2%

When considering the tradeoff, it would be nice to know the size of the efficiency loss.  Barro compares the current recession to that of 1982.  I have placed the data he discusses into two tables.  The first is a snapshot of long-term unemployment statistics when the unemployment rate peaked during the 1982 recession and the current recession.  The second looks at these statistics when the average weeks of unemployment peaked.    Barro notes that long-term unemployment is a more prominent feature of this recession and that unemployment benefits were not extended in the 1982 recession but were extended from 26 weeks to 99 weeks during the current recession.  He offers the extension of unemployment benefits as a possible explanation, he considers no others.  He asks what the world might be like if the benefits were not extended and assumes that peak unemployment would have held at 24.5% of unemployed as it did in 1983, then total unemployment would have been 10.4 million rather than 14.6 and the unemployment rate would have been 6.8% rather than 9.5%.

This is a “back of the envelope” calculation that Barro calls “rough.”  I would consider two other factors if I were to attempt a more sophisticated model.  I would control for the age of the labor force, which has gotten older.  As another blogger, Calculated Risk, observed in “Older, more educated workers, have highest length of unemployment” in a tell-all title, older, more educated workers have the highest length of unemployment.  This raises an issue of causality.  Is the job search for these workers inherently longer than in the past or do they take longer to search for a perfect fit job because unemployment benefits have been extended?  Both may be true.  The latter explanation supports Barro’s hypothesis.

A second issue of note is that the unemployment rate, which is found by dividing the number of unemployed by the labor force participation rate, may influence the number of labor force participants.  High levels of unemployment discourage workers who drop out of the labor force.  As the economy improves, these workers may reenter the labor force keeping the unemployment rate higher than it would have been if the labor force remained constant through the recovery.  Barro assumes that the labor force participation rate does not change. 
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The Government, Computes and Reverse Causality

Peter Orszag, Director of the Office of Management and Budget, has committed the error of reverse causality arguing that the government is inefficient and ineffective because it has a technology gap with the private sector.  The gap exists because government is inefficient and ineffective relative to the private sector.  Ian Swanson writes in the Hill's technology blog, Hillicon Valley ("White House budget director blames old computers for ineffective government") that Peter Orszag believes that a technology gap is responsible for ineffective and inefficient government.

The public is getting a bad return on its tax dollars because government workers are operating with outdated technologies, Orszag said in a statement that kicked off a summit between Obama and dozens of corporate CEOs.

“Twenty years ago, people who came to work in the federal government had better technology at work than at home,” said Orszag, director of the Office of Management and Budget. “Now that’s no longer the case.

“The American people deserve better service from their government, and better return for their tax dollars.”

The White House release that included Orszag’s comments said one “specific source” of ineffective and inefficient government is the huge technology gap between the public and private sectors that results in billions of dollars in waste, slow and inadequate customer service and a lack of transparency about how dollars are spent.

For those old enough to remember interacting with the government twenty years ago, were they more efficient and ineffective relative to the private sector? 
The private sector has been and remains more efficient than the government because it generally has superior incentives, most importantly profits.  If a business believes that a new technology will increase profits, they employ it or risk adaptation by a competitor that will cannibalize their profits and market share.  The government has no such incentive.  They may know that a new technology will improve efficiency but there is no profit motive to encourage adaptation.  They may or may not make the investment.  If they don't make it we get the same service.

Orszag wants to improve government, a laudable goal.  A first step is to recognize government's shortcomings and limit its scope to areas in which the private sector has poor incentives relative to the public sector.  The government should provide national defense, a judicial system to protect people and property, city roads, and perhaps a few other services.  Policy makers can improve the effectiveness and efficiency of the government by turning over functions to the private sector.
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Barro and Redlick on Multipliers

The financial crisis that deepened in September 2008 re-ignited a debate about the efficacy of fiscal stimulus.  Robert Barro, a professor of economics at Harvard, and Charles Redlick, a graduate of Harvard add to our knowledge that they describe as "thin" in their Wall Street Journal article, "Stimulus Spending Doesn't Work."  The article summarizes their recently completed research published by the National Bureau of Economic Research.  They divided fiscal policy into three types: war induced spending, peacetime spending, and tax cuts.  On war spending, they write 

For annual data that start in 1939 or earlier (and, thereby, include World War II), the defense-spending multiplier that applies at the average unemployment rate of 5.6% is in a range of 0.6-0.7. A multiplier less than one means that, overall, other components of GDP fell when defense spending rose. Empirically, our research shows that most of the fall was in private investment, with personal consumer expenditure changing little.

Our research also shows that greater weakness in the economy raises the estimated multiplier: It increases by around 0.1 for each two percentage points by which the unemployment rate exceeds its long-run median of 5.6%. Thus the estimated multiplier reaches 1.0 when the unemployment rate gets to about 12%.

In a weak economy, with unemployment exceeding 12%, war spending might help the economy if you don't suffer high casualties and a country's physical capital remains intact.  For my students, that reads like something that I wrote here.  Thankfully, our economy was not quite that weak, but that means that the stimulus hurt a little.Barro and Redlick assert that economists have reversed causality of the impact of peacetime spending on GDP.  Spending does not increase GDP, but GDP growth does increase spending. 

To evaluate typical fiscal-stimulus packages, however, nondefense government spending multipliers are more important. Estimating these multipliers convincingly from U.S. time series is problematical, however, because the movements in nondefense government purchases (dominated since the 1960s by state and local outlays) are closely intertwined with the business cycle. Thus the explanation for much of the positive association between nondefense spending and GDP is that government spending increased in response to growing GDP, rather than the reverse.

The authors find that tax cuts are good, but the results may not be robust.

The effects of tax rates on GDP growth can be analyzed from a time series we've constructed on average marginal income-tax rates from federal and state income taxes and the Social Security payroll tax. Since 1950, the largest declines in the average marginal rate from the federal individual income tax occurred under Ronald Reagan (to 21.8% in 1988 from 25.9% in 1986 and to 25.6% in 1983 from 29.4% in 1981), George W. Bush (to 21.1% in 2003 from 24.7% in 2000), and Kennedy-Johnson (to 21.2% in 1965 from 24.7% in 1963). Tax rates rose particularly during the Korean War, the 1970s and the 1990s. The average marginal tax rate from Social Security (including payments from employees, employers and the self-employed) expanded to 10.8% in 1991 from 2.2% in 1971 and then remained reasonably stable.

For data that start in 1950, we estimate that a one-percentage-point cut in the average marginal tax rate raises the following year's GDP growth rate by around 0.6% per year. However, this effect is harder to pin down over longer periods that include the world wars and the Great Depression.

Barro and Redlick conclude,

The bottom line is this: The available empirical evidence does not support the idea that spending multipliers typically exceed one, and thus spending stimulus programs will likely raise GDP by less than the increase in government spending. Defense-spending multipliers exceeding one likely apply only at very high unemployment rates, and nondefense multipliers are probably smaller. However, there is empirical support for the proposition that tax rate reductions will increase real GDP.

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Sowell on Causation and Correlation

(Edited Sept 17, 2009) In his most recent book, "The Housing Boom and Bust," Thomas Sowell quotes the Millennial Housing Commission which wrote

Decent and affordable housing has a demonstrable impact on family stability and the life outcomes of children. Decent housing is an indispensable building block of healthy neighborhoods, and thus shapes the quality of community life...Better housing can lead to better outcomes for individuals, communities, and American society as a whole.

Sowell argues that the authors confused causality with correlation, writing

It is certainly true that neighborhoods with better housing also usually have more stable families, better educated children and lower crime rates. But statisticians have long pointed out that correlation is not causation, though that may be the most often ignored lesson statistics.

Sowell notes that using the logic of the Millennial Housing Commission, early policy makers tore down slums to force people into better neighborhoods. Later, policy makers used kinder methods such as financial incentives and lowered lending standards to entice people into better neighborhoods, As might be expected when you assume causation when only correlation exists, the government actions have had little positive effect.

I think that the Millennial Housing Commission may have reversed causality. More stable families create better neighborhoods and better housing. Perhaps there is an omitted variable that causes both better families and better neighborhoods. What do you think?



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The Nanny State In The Doll House

L.A. Johnson writing for the Pittsburgh Post-Gazette in "West Virginia state lawmaker proposes ban on Barbie just before she turns 50," reports that

West Virginia Democratic Delegate Jeff Eldridge Tuesday proposed a bill to ban the sale of Barbie and similar dolls that promote physical beauty to the detriment of girls' intellectual and emotional development.

There are many things wrong with the proposal. The smallest is that he reversed causality. I doubt many girls, shopping for a new calculator, innocently happen by Barbie and are transformed by her hypnotic beauty into girls obsessed with their own physical imperfection, and drained by their inability to match hers. It is more likely that girls interested in physical beauty and fashion select dolls that match their interests. It is more likely still that the intellectual and emotional development of girls is simply not affected by playing with Barbies.

More significantly, when did anyone begin to believe that we, through our elected representatives, had the right or wisdom to dictate the types of dolls parents purchase for their children? What kind of people could elect a delegate in West Virginia who would make such an arrogant proposal let alone elect a sufficient number of representatives in Montpelier, Vermont to ban Barbie (2006)? I hope that the voters in West Virginian and Montpelier were fooled and that their representatives soon find themselves looking for other employment.

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Kobe and Reverse Causality

Critics of Kobe Bryant often claim that he is a selfish player. They note with glee that the Lakers lose a higher percentage of their games when he takes more than thirty shots than when he shoots less. The same thing was said about Michael Jordan. Reporters claimed that he scored a lot of points before he learned to be a team player, then he won championships.

I offer this hypothesis for your consideration; I believe that have reversed causality. Bryant and Jordan took a more shoots when their teammates couldn't score, and fewer when they could. Their games did not improve, their teammates did.

Reverse causality is a problem that plagues economists. Kevin Grier gives a good example in the Concise Encyclopedia of Economics, in "Empirics of Economic Growth," and writes,

[W]e are seldom sure whether the variables expected to cause growth actually do so or are themselves caused by growth. For example, some economists claim that financial development helps growth, but others argue that economic growth itself causes financial development.

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Treasury Secretary Hank Paulson Blames...

Krishna Guha of the Financial Times reports that is a valedictory interview, Mr. Paulson said that

in the years leading up to the crisis, super-abundant savings from fast-growing emerging nations such as China and oil exporters – at a time of low inflation and booming trade and capital flows – put downward pressure on yields and risk spreads everywhere...Excesses...built up for a long time, [with] investors looking for yield, mis-pricing risk. It could take different forms. For some of the European banks it was eastern Europe. Spain and the UK were much more like the US with housing being the biggest bubble. With Japan it may be banks continuing to invest in equities.

Mr. Paulson said the solution was better global macroeconomic cooperation, better regulation and risk pricing.

I have briefly looked for a transcript of the interview and could not find it. Perhaps in the full text he stated how a need for better regulation springs from the root causes he names, certainly regulators erred in pricing risk as did investors. Hazarding another guess, from a U.S. perspective, perhaps by global macroeconomic cooperation, he means pegging Asian exchange rates differently so as to generate fewer imports, more exports, and less net capital inflows.

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$650 Million Did Not Buy Obama the Election!

A spate of news stories and blogs are declaring that President elect Barak Obama bought the presidency for $650 million, a point I dispute (see Big Money Bought Obama the White House or £500m election fund 'bought Obama victory').

The stories are of two types, by raising so much money Mr. Obama was able to bamboozle voters with tons of TV, radio and other advertising, or that the money was somehow illegally raised. As to the second point, illegally raising money, I will only comment briefly. Mr. Obama should comply with the law no matter how difficult the compliance and stupid the law. Without any evidence, I believe that when all is said and done, Mr. Obama will be shown to have complied with the law about as well as anyone else.

Money and votes seem to be correlated, but the question is one of causality. Does money buy votes or do good candidates raise more money. Steven Levitt and Stephen Dubner answer that question based on Levitt's peer reviewed work in their best seller, Freakonomics, certainly a valuable and entertaining read. Levitt looked at elections in which the same congressional candidates ran against each other in consecutive elections. This happened a lot, over 1,000 times in his sample.

Levitt then compared the votes and money raised in the two elections. He found that a candidate can cut his or her spending in half and only lose about one percent of the votes. Candidate Obama won by a 7.2 percent spread. It wasn't even close. Mr. Obama won because, given the economic and social conditions, he was the better candidate.

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