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Expanding Medicaid Reduces Death Rates

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:

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.

The Paradox of Choice Meets the Decline Effect

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.

Cutting Tax Breaks to Pay for Lower Rates Isn’t Easy

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.

How Behavioral Science Can Improve Tax Policy

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.

Weak Employment in One Chart

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.

Merle Hazard Goes Surfing on the Fiscal Cliff

Remember Merle Hazard? You know, the brains behind “Inflation or Deflation?” and “Bailout”?

Now he’s back with a surf-music take on the looming Fiscal Cliff.

Let’s hope we don’t wipe out.

On Orbitz, Windows Users Steered to Cheaper Hotels

The fun economics story of the day is that Orbitz sometimes looks at your computer’s operating system to decide what hotel options to show you. Dana Mattioli breaks the story over at the Wall Street Journal:

Orbitz Worldwide Inc. has found that people who use Apple Inc.’s Mac computers spend as much as 30% more a night on hotels, so the online travel agency is starting to show them different, and sometimes costlier, travel options than Windows visitors see.

The Orbitz effort, which is in its early stages, demonstrates how tracking people’s online activities can use even seemingly innocuous information—in this case, the fact that customers are visiting Orbitz.com from a Mac—to start predicting their tastes and spending habits.

Orbitz executives confirmed that the company is experimenting with showing different hotel offers to Mac and PC visitors, but said the company isn’t showing the same room to different users at different prices. They also pointed out that users can opt to rank results by price.

Here are examples from the WSJ’s experiments:

The WSJ emphasizes that Mac users see higher-priced hotels. For example, Mattioli’s article is headlined: “On Orbitz, Mac Users Steered to Pricier Hotels.”

My question: Would you feel any different if, instead, the WSJ emphasized that Windows users are directed to lower-priced hotels? For example, Windows users are prompted about the affordable lodgings at the Travelodge in El Paso, Texas. (Full disclosure: I think I once stayed there.)

As Mattioli notes, it’s important to keep in mind that Orbitz isn’t offering different prices, it’s just deciding which hotels to list prominently. And your operating system is just one of many factors that go into this calculation. Others include deals (hotels offering deals move up the rankings), referring site (which can reveal a lot about your preferences), return visits (Orbitz learns your tastes), and location (folks from Greenwich, CT probably see more expensive hotels than those from El Paso).

Will September Bring Another Banking Crisis?

Over at the Economist, Greg Ip points us to a new IMF working paper that surveys all the systemic banking crises–147 in all–since 1970. As Greg notes, one of Luc Laeven and Fabian Valencia’s most striking findings is that banking crises disproportionately begin in the second half of the year, with a particular spike in September:

So let’s enjoy what few days of June remain.

P.S. Theories to explain this pattern are appreciated. Or maybe it’s a spurious correlation, at Tyler Cowen hints.

Update: Joshua Hedlund at PostLibertarian crunches the underlying data and finds that (a) the authors provided a date for only 63 of the crises and (b) that 22 of the 25 in September happened in 2008. ht: Tyler Cowen

Financial Repression and China’s Extractive Elite

Financial repression and extractive institutions are two of the big memes in international economics today.

Financial repression occurs when governments intervene in financial markets to channel cheap funds to themselves. With sovereign debts skyrocketing, for example, governments may try to force their citizens, banks, and others to finance those debts at artificially low interest rates.

Extractive institutions are policies that attempt to redirect resources to politically-favored elites. Classic examples are the artificial monopolies often granted by governments in what would otherwise be structurally competitive markets. Daron Acemoglu and James Robinson have recently argued that such institutions are a key reason Why Nations Fail. Inclusive institutions, in contrast, promote widely-shared prosperity.

Over at Bronte Capital, John Hempton brings these two ideas together in an argument that Chinese elites are using financial repression to extract wealth from state-owned enterprises. In a nutshell, he believes Chinese authorities have artificially lowered the interest rates that regular Chinese citizens earn on their savings (that’s the repression), and have directed these cheap funds to finance “staggeringly unprofitable” state enterprises that nonetheless manage to spin out vast wealth for connected elites and their families.

I don’t have the requisite first-hand knowledge to judge his hypothesis myself. But both his original post and recent follow-up addressing feedback are worth a close read.

One Idea from Rio+20: Investing in Green Infrastructure

Twenty years ago, world leaders gathered in Rio de Janeiro to grapple with climate change, biological diversity, and other environmental challenges. Today they are back again, but with much less fanfare. If my Twitter feed is any indication, Rio+20 is getting much less attention that the original Earth Summit.

One item that deserves attention is greater emphasis on getting business involved in protecting the environment. For example, two dozen leading businesses–from Alcoa to Xerox–teamed up with The Nature Conservancy on a vision for The New Business Imperative: Valuing Natural Capital (interactive, pdf).

The report lays out the business case that natural resources have real economic value, even if they aren’t traded in markets, and that protecting them can sometimes reduce costs, maintain supplies, soften the blow of future regulation, and build goodwill with customers, communities, and workers. All kind of obvious, at one level, but nonetheless useful to see in print with examples and commitments.

One item that caught my eye is the potential for “green” infrastructure to replace “gray”:

Strong, reliable manmade (“gray”) infrastructure undergirds a healthy marketplace, and most companies depend heavily on it to operate effectively and efficiently. Yet increasingly, companies are seeing the enormous potential for “natural infrastructure” in the form of wetlands and forests, watersheds and coastal habitats to perform many of the same tasks as gray infrastructure — sometimes better and more cheaply.

For instance, investing in protection of coral reefs and mangroves can provide a stronger barrier to protect coastal operations against flooding and storm surge during extreme weather, while inland flooding can be reduced by strategic investments in catchment forests, vegetation and marshes. Forests are also crucial for maintaining usable freshwater sources, as well as for naturally regulating water flow.

Putting funds into maintaining a wetland near a processing or manufacturing plant can be a more cost- effective way of meeting regulatory requirements than building a wastewater treatment facility, as evidenced by the Dow Chemical Seadrift, Texas facility, where a 110-acre constructed wetland provides tertiary wastewater treatment of five million gallons a day. While the cost of a traditional “gray”treatment installation averages >$40 million, Dow’s up-front costs were just $1.4 million.

For companies reliant on agricultural systems, improved land management of forests and ecosystems along field edges and streams, along with the introduction of more diversified and resilient sustainable agriculture systems, can minimize dependency on external inputs like artificial fertilizers, pesticides and blue irrigation water.

To encourage such investments, where they make sense, lawmakers and regulators need to focus on performance–is the wastewater getting clean?–rather than the use of specific technologies or construction.