The Nobel Prize, credibility and the debates on inequality

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The awards Nobel Prize in Economics they are awarded for long-term research, not for economists’ involvement in current debates, so they certainly don’t have much to do with the political moment. It is to be expected that the disconnect will be especially great when the prize is awarded above all for the development of new research methods.

And that is the case with the latest award, awarded on Monday to David Card, Joshua D. Angrist and Guido W. Imbens, leaders of the “credibility revolution”(A change in the way economists use data to evaluate theories), which has proliferated in economics in the last generation.

However, it turns out that the credibility revolution is extremely relevant to current debates. Indeed, studies using the new method have, in many cases, but not all, reinforced the argument in favor of more active government intervention in the fight against inequality.

As I will explain, this is not an accident. But first, what is this revolution about?

In general, economists cannot do controlled experiments: all we can do is observe. And the problem with trying to draw conclusions from economic observations is that a lot is happening at all times and places.

For example, the economy boomed after Bill Clinton raised high income taxes and cut the budget deficit. But were these fiscal policies the cause of the prosperity, or was Clinton lucky to become president during a tech boom?

Before the credibility revolution, economists were essentially trying to isolate the effects of certain policies or other changes by using elaborate statistical methods to control for other factors. In many cases, that is the only thing we can do. But any such attempt depends on how good the controls are, and there is usually an endless margin of controversy over the results.

However, in the 1990s, some economists realized that there was an alternative method, that of exploiting “natural experiments,” situations in which the vagaries of history offer something akin to the kind of controlled trial that researchers they would like to carry out but cannot.

The most famous example is the research that Card conducted with the late Alan Krueger on the effects of minimum wages. Most economists used to believe that raising the minimum wage reduces employment. But is it so? In 1992, the state of New Jersey increased its minimum wage, while one of its neighboring states, Pennsylvania, did not. Card and Krueger found that they could assess the effect of this policy change by comparing job growth in the two states after the wage increase, and use Pennsylvania as a control for the New Jersey experiment.

What they found was that raising the minimum wage had little or no negative effect on the number of jobs, a result that has since been confirmed by examining many other cases. These results not only justify the increase in minimum wages, but also more aggressive attempts to reduce inequality in general.

Another example: How can we assess the effects of social protection programs that help children? Researchers have taken advantage of natural experiments created, among other examples, by the gradual rollout of food stamps in the 1960s and 1970s and several discrete jumps in Medicaid availability in the 1980s. These studies show that children Those who received help became much healthier and more productive adults than those who did not.

These studies also make a strong case for the Joe Biden government’s Rebuild Better initiative, which emphasizes investing in children as well as conventional infrastructure.

Finally, the big changes in unemployment insurance over the course of the pandemic – a huge increase in generosity, then a sudden cut, then a partial reset, and then another cut, in which some states cut benefits earlier than expected. others – provide several natural experiments that allow us to test whether, as conservatives always insist, unemployment insurance deters the unemployed from seeking new jobs.

Well, the data offer a clear answer: although unemployment benefits can have some disincentive effects, they are small.

So overall, the modern data-driven economy tends to support more activist economic policies – raising wages, helping children, and helping the unemployed are better ideas than many politicians seem to believe. But why does the data seem to support a progressive agenda?

The main answer, I would argue, is that in the past many influential people clung to economic arguments that could be used to justify high inequality. We cannot increase the minimum wage because that would end employment; We cannot help the unemployed because that would hurt their incentives to work; And so one after another. In other words, the political use of economic theory tends to have a right-wing bias.

But now we have evidence that can be used to prove these arguments, and some do not hold up. So the empirical revolution in economics undermines the conventional wisdom of the right that had dominated the discourse. In that sense, the evidence turns out to have a liberal bias.

Once again, the research awarded with this Nobel is not political, but it has important political implications. And most of those implications favor a policy move to the left.

We would like to thank the author of this write-up for this amazing material

The Nobel Prize, credibility and the debates on inequality

Hank Gilbert