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Archive for July, 2012

Politicians and pundits constantly debate the size of government. Is it big or small? Growing or shrinking?

You might hope these simple questions have simple answers. But they don’t. Measuring government size is not as easy as it sounds. For example, official statistics track two different measures of government spending. And those measures tell different stories:

The blue line shows how much federal, state, and local governments directly contribute to economic activity, measured as a share of overall gross domestic product (GDP). If you’ve ever taken an intro economics class, you know that contribution as G, shorthand for government spending. G represents all the goods and services that governments provide, valued at the cost of producing them. G thus includes everything from buying aircraft carriers to paying teachers to housing our ambassador in Zambia.

At 19.5 percent of GDP, G is down from the 21.5 percent it hit in the worst days of the Great Recession. As Catherine Rampell of the New York Times pointed out last week, it’s also below the 20.3 percent average of the available data back to 1947. For most of the past 65 years, federal, state, and local governments had a larger direct economic role producing goods and services than they do today.

There’s one notable exception: today’s government consumption and investment spending is notably larger than it was during the economic boom and fiscal restraint of the late 1990s and early 2000s. From mid-1996 to mid-2001, government accounted for less than 18 percent of GDP. Relative to that benchmark, government is now noticeably larger.

The orange line shows a broader measure that captures all the spending in government budgets—all of G plus much more. Governments pay interest on their debts. More important, they make transfer payments through programs like Social Security, Medicare, Medicaid, food stamps, unemployment insurance, and housing vouchers. Transfer spending does not directly contribute to GDP and thus is not part of G. Instead, it provides economic resources to people (and some businesses) that then show up in other GDP components such as consumer spending and private investment.

This broader measure of government spending is much larger than G alone. In 2011, for example, government spending totaled $5.6 trillion, about 37 percent of GDP. But only $3.1 trillion (20 percent of GDP) went for goods and services. The other $2.5 trillion (17 percent) covered transfers and interest.

Like G, this broader measure of government has declined since the (official) end of the Great Recession. Since peaking at 39 percent in the second quarter of 2009, it has fallen to 36 percent in the second quarter of 2012.

Also like G, this measure has grown since the boom of the late 1990s and early 2000s. In the middle of 2000, government spending totaled just 30 percent of GDP, a full 6 percentage points less than today.

The two measures thus agree on recent history: government has shrunk over the past three years as the economy has slowly recovered from the Great Recession and government policy responses have faded. But government spending is still notably larger than at the turn of the century.

The story changes, however, if we look further back in time. Although governments spent more on goods and services in the past, total spending was almost always lower. Since 1960, when data on the broader measure begin, total government spending has averaged about 32 percent. It never reached today’s 36 percent until 2008, when the financial crisis began in earnest.

Much of the recent increase in overall spending is due to the severity of the downturn. But that’s not the only factor. Government’s economic role has changed. As recently as the early 1960s, federal, state, and local governments devoted most of their efforts to providing public goods and services. Now they devote large portions of their budgets to helping people through cash and in-kind transfers—programs like Medicare and Medicaid that were created in 1965 and account for much of the growth in the gap between the orange and blue lines.

Government thus has gotten bigger. But it’s also gotten smaller. It all depends on the time period you consider and the measure you use.

P.S. Keep in mind that this discussion focuses on a relative measure of government size—the ratio of government spending to the overall economy—not an absolute one. Government thus expands if government spending grows faster than the economy and contracts if the reverse is true.

P.P.S. Measuring government size poses other challenges. Eric Toder and I discuss several in our paper “How Big is the Federal Government?” Perhaps most important is that governments now do a great deal of spending through the tax code. Traditional spending numbers thus don’t fully reflect the size or trend in government spending. For more, see this earlier post.

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Saving Bear Cubs

For my animal-loving readers, here are Shirley and Tom Schenk executing a perfect rescue of three bear cubs trapped in a dumpster in New Mexico (h/t: the Awl).

For more bear action, check out the live cam at Brooks Falls in Alaska.

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The economy grew at a tepid 1.5% annual rate in the second quarter, according to the latest BEA estimates. That’s far below the pace we need to reduce unemployment.

Weak growth was driven by a slowdown in consumer spending and continued cuts in government spending (mostly at the state and local level), which overshadowed rapid growth in investment spending on housing–yes, housing–and equipment and software:

Housing investment expanded at almost a 10% rate in the second quarter, its fifth straight quarter of growth. Government spending declined at a 1.4% rate, its eighth straight quarter of decline.

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Arizona, Maine, and New York significantly expanded Medicaid coverage in the early 2000s. That expansion appears to have reduced death rates, according to a new study in the New England Journal of Medicine.

Benjamin Sommers, Katherine Baicker, and Arnold Epstein, all of the Harvard School of Public Health, compared mortality in those states to four neighboring states (Nevada and New Mexico; New Hampshire; and Pennsylvania) that didn’t expand Medicaid coverage. They found that mortality fell in the three states that expanded coverage even as it increased in the neighbors:

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The authors use the usual battery of statistical techniques to try to tease our whether some other factors, perhaps changing economic fortunes or demographics, might explain the mortality differences. After all that, their best guess is that the reduction in death rates is real: on average, one death was averted each year for every 176 extra adults covered by Medicaid.

The study does have limitations, as the authors carefully note. For example, it relies on mortality data for counties. What you’d really like, of course, are data for individuals, so you could track the impacts of Medicaid enrollment person-by-person.

For further discussion, see this NYT article by Pam Belluck.

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Does your brain freeze when offered too many options? Do you put off repainting your bathroom because you can’t bear to select among fifty shades of white (or, for the more adventurous, grey)?

If so, take heart. A famous experiment by psychologists Mark Lepper and Sheena Iyengar, published in 2000, suggests that you are not alone. In supermarket tests, they documented what’s known as the Paradox of Choice. Customers offered an array of six new jam varieties were much more likely to buy one than those offered a choice of 24.

That makes no sense in the narrow sense of rationality often used in simple economic models. More choice should always lead to more sales, since the odds are greater that a shopper will find something they want. But it didn’t. On those days, in those supermarkets, with those jams, more choice meant less buying.

This result resonates with many people. I certainly behave that way occasionally. With limited time and cognitive energy, I sometimes avoid or defer choices that I don’t absolutely need to make … like buying a new jam. Making decisions is hard. Just as consumers have financial budget constraints, so too do we have decision-making budget constraints.

Today’s TED Blog provides links and, naturally, videos for a series of studies documenting similar challenges of choice, from retirement planning to health care to spaghetti sauce. All well worth a view.

But how general are these results? Perhaps not as much as we’d think from the TED talks. A few years ago, Tim Harford, the Financial Times’ Undercover Economist, noted that some subsequent studies in the jam tradition failed to find this effect:

It is hard to find much evidence that retailers are ferociously simplifying their offerings in an effort to boost sales. Starbucks boasts about its “87,000 drink combinations”; supermarkets are packed with options. This suggests that “choice demotivates” is not a universal human truth, but an effect that emerges under special circumstances.

Benjamin Scheibehenne, a psychologist at the University of Basel, was thinking along these lines when he decided (with Peter Todd and, later, Rainer Greifeneder) to design a range of experiments to figure out when choice demotivates, and when it does not.

But a curious thing happened almost immediately. They began by trying to replicate some classic experiments – such as the jam study, and a similar one with luxury chocolates. They couldn’t find any sign of the “choice is bad” effect. Neither the original Lepper-Iyengar experiments nor the new study appears to be at fault: the results are just different and we don’t know why.

After designing 10 different experiments in which participants were asked to make a choice, and finding very little evidence that variety caused any problems, Scheibehenne and his colleagues tried to assemble all the studies, published and unpublished, of the effect.

The average of all these studies suggests that offering lots of extra choices seems to make no important difference either way. There seem to be circumstances where choice is counterproductive but, despite looking hard for them, we don’t yet know much about what they are. Overall, says Scheibehenne: “If you did one of these studies tomorrow, the most probable result would be no effect.”

In short, the Paradox of Choice is experiencing the infamous Decline Effect. As Jonah Lehrer noted in the New Yorker in late 2010, sometimes what seems to be scientific truth “wears off” over time. And not just in “soft” sciences like the intersection of psychology and economics, but in biology and medicine as well.

Some of that decline reflects selection pressures in research and publishing … and invitations to give TED talks. It’s easy to get a paper published if it documents a new a paradox or anomaly. Only after that claim has gained some mindshare does the marketplace then open to research showing null results of no paradox.

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Broader base, lower rates.

That’s the bumper sticker for most tax reform proposals. To varying degrees, everyone from President Obama to Governor Romney to Bowles-Simpson has embraced it. Whatever your revenue goal, you can get there with lower tax rates if you are willing to slash tax breaks and thus broaden the tax base.

But cutting tax breaks to pay for lower tax rates is harder than it sounds. There may be more than $1 trillion in annual tax breaks out there, but that doesn’t mean there’s that much easy revenue available to policymakers.

In a new paper today, my Tax Policy Center colleagues Hang Nguyen, James Nunns, Eric Toder, and Roberton Williams document four particular challenges in cutting tax breaks to pay for lower rates:

1. Lower rates reduce the value of most tax preferences. Nearly all tax expenditures are in the form of deductions, exclusions, exemptions, deferrals, or preferential rates, all of which are valuable only to the extent they allow taxpayers to avoid regular statutory tax rates. If tax rates are cut, the value of these tax preferences goes down as well. Thus, cutting tax rates reduces the amount of offsetting revenue that cutting tax preferences can raise.

2. Some tax preferences may be hard to curtail for political or administrative reasons. For example, cutting back widely used and popular preferences such as the deductions for mortgage interest and charitable contributions may be politically difficult. And it would be administratively impractical to require homeowners to include in their income each year the rental value of their homes, although leaving that income untaxed is a tax expenditure (with a sizable cost associated with it). If such preferences can’t be curtailed as part of a realistic tax reform, it becomes harder to find the revenue needed to pay for lower tax rates.

3. Cutting back on tax preferences may alter the distribution of the tax burden in ways that are deemed unacceptable. Finding a combination of lower rates and cutbacks in tax preferences with acceptable distributional effects can prove quite difficult.

4. A tax reform that includes wholesale, immediate repeal of a significant portion of tax preferences would significantly disrupt existing economic arrangements in ways that might be deemed unfair. Instead, some preferences might be only partially curtailed, and some cutbacks might phase in, possibly over an extended period of time. In addition, taxpayers would likely change their behavior to lessen the impact of these cutbacks. All of these “real world” effects would likely reduce, perhaps substantially, the revenue gains from cutting tax preferences.

The chart above illustrates the first of these points. It shows how big tax breaks are in three scenarios: current law (in which all expiring tax cuts actually expire), current policy (most get extended), and current policy with reduced rates (rates get reduced by another 20 percent). The top income tax rate in 2015 under these scenarios is thus 39.6 percent, 35 percent, and 28 percent, respectively (before accounting for Medicare taxes and the health reform tax on investment income).

Most official estimates of tax preferences use the tax rates in current law. Under those rates, TPC estimates that the value of most deductions, fringe benefits, and small credits in 2015 is $590 billion. Under the lower rates of current policy, however, those preferences are worth only $525 billion. And under the still lower rates of current policy with reduced rates, they are worth only $446 billion.

Cutting tax rates thus materially reduces the amount of  money available from rolling back tax breaks.

For more, see Howard Gleckman’s take on the report.

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In Sunday’s New York Times, Richard Thaler laments that “as a general rule, the United States government is run by lawyers who occasionally take advice from economists.”

That makes for better policy than a tyranny of lawyers alone. But it certainly isn’t enough. Policy is ultimately about changing the way people behave. And to do that, you need to understand more than just economics (as an increasing number of economists, Thaler foremost among them, already recognize).

Thaler thus makes two important suggestions: First, he argues that behavioral scientists deserve a greater formal role in the policy process, perhaps even a Council of Behavioral Science Advisers that would advise the White House in parallel with the Council of Economic Advisers. Second, he urges government to engage in more experimentation so it can learn just what policy choices best drive behavior, and how.

As an example, he cites the efforts of Britain’s Behavioral Insights Team, which was created when David Cameron’s coalition government came to office in 2010.

As its name implies, the team (which he advises) works with government agencies to explore how behavioral insights can make policy more effective. Tax compliance is one example.

Each year, Britain sends letters to certain taxpayers—primarily small businesses and individuals with non-wage income—directing them to make appropriate tax payments within six weeks. If they fail to do so, the government follows up with more costly measures. Enter the Behavioral Insights Team:

The tax collection authority wondered whether this letter might be improved. Indeed, it could.

The winning recipe comes from Robert B. Cialdini, an emeritus professor of psychology and marketing at Arizona State University, and author of the book “Influence: The Psychology of Persuasion.”

People are more likely to comply with a social norm if they know that most other people comply, Mr. Cialdini has found. (Seeing other dog owners carrying plastic bags encourages others to do so as well.) This insight suggests that adding a statement to the letter that a vast majority of taxpayers pay their taxes on time could encourage others to comply. Studies showed that it would be even better to cite local data, too

Letters using various messages were sent to 140,000 taxpayers in a randomized trial. As the theory predicted, referring to the social norm of a particular area (perhaps, “9 out of 10 people in Exeter pay their taxes on time”) gave the best results: a 15-percentage-point increase in the number of people who paid before the six-week deadline, compared with results from the old-style letter, which was used as a control condition.

Rewriting the letter thus materially improved tax compliance. That’s an important insight, and I hope it scales if and when Britain’s tax authority applies it more broadly.

But there’s a second lesson as well: the benefit of running policy experiments. Policymakers have no lack for theories about how people will respond to various policy changes. What they often do lack, however, is evidence about which theory is correct or how big the potential effects are. Governments on both sides of the Atlantic should look for opportunities to run such controlled experiments so that, to paraphrase Thaler, evidence-based policies can be based on actual evidence.

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Another weak jobs report with payrolls up only 80,000, unemployment stuck at 8.2 percent, and underemployment ticking up to 14.9 percent.

But the real news continues to be how far employment has fallen. As recently as 2006, more than 63 percent of adults had a job. Today, that figure is less than 59 percent:

With the exception of the past several years, you’ve got to go back almost three decades to find the last time that so few Americans were employed (as a share of the adult population).

The stunning decline in the employment-to-population ratio (epop to its friends) reflects two related factors. First, the unemployment rate has increased from less than 5 percent to more than 8 percent. That accounts for roughly half the fall in epop. The other half reflects lower labor force participation. Slightly more than 66 percent of adults were in the labor force back them, but now it’s less than 64 percent.

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