Tuesday, January 18

Nobel Prize winners in economics showed economists how to turn the real world into their laboratory

The Nobel committee’s decision to award its 2021 economics prize to David Card, Josh Angrist and Guido Imbens marks the culmination of a revolution in the way economists approach the world that began more than 30 years ago. Until the 1980s, experiments were rare in economics. Most economists who worked on the applied side of the field relied on data from surveys (such as the census) or administrative sources (such as social security).

Towards the end of the 1980s, labor economists in particular began to think deeply about how best to estimate the effects of phenomena such as immigration or the minimum wage. Similar to how, say, pharmaceutical companies test a new drug, they wanted to rule out other variables that could be causing the same effects. Along with this came a new focus on data and the measurement of people and their behavior.

It is no accident that Card (1983) and Angrist (1989) completed their PhDs at Princeton. They both had Orley Ashenfelter as their Ph.D. advisor, and Ashenfelter deserves substantial credit along with Card for pushing labor economics and empirical economics toward mimicking the traditional sciences.

David Card and the Real World Laboratory

Economists knew there was a problem trying to understand the exact relationship between two economic variables, say, education and wages. Just because, on average, those with higher levels of education also earn higher wages does not mean that the higher wages are caused by higher education. Other factors, such as a privileged family environment or greater innate ability, could also be associated with higher levels of education and higher wages.

In a drug test, you can isolate the effects of the drug as opposed to other potential effects through a random experiment: you divide the people participating in your test into two groups at random, giving the drug to one group and giving the another group a placebo, but without telling anyone if they are taking the real drug.

Ashenfelter and Card saw the potential to do something similar in economics using “natural experiments,” which are real-life economic phenomena that only happen to some people. By comparing two groups in which only one has experienced a phenomenon, so to speak at random, the researchers would get a clearer picture of cause and effect.

Two of David Card’s most influential articles used natural experiments to great effect. In the first, published in 1990, examined how more than 120,000 migrants who left the port of Mariel in Cuba during a period in 1980 affected Miami’s job market.

A simple “before and after” comparison of wages and unemployment in Miami would have ignored the fact that the US economy was booming in 1979 and sinking in 1981 for reasons that had nothing to do with these migrants. Card’s response was to analyze the average change in wages and unemployment between the late 1970s and 1980s in Atlanta, Houston, Los Angeles, and Tampa-St. Petersburg.

Nobel Prize winners in economics David Card, Josh Angrist, and Guido Imbens.
Nobel Prize winners in economics David Card, Josh Angrist, and Guido Imbens.
Nobel Committee

This provided the so-called “counterfactual outcome,” that is, what would likely have happened in Miami without the influx of immigrants. By subtracting this change from the change in job market outcomes in Miami, Card was (possibly) able to calculate the effect of the influx of immigrants on wages and unemployment in the city.

Card found, surprisingly, that this influx had virtually no effect on the wages of the less-skilled non-Cubans in Miami, and neither did it increase unemployment among blacks or non-Cubans. This result was controversial 31 years ago and remains controversial today, but Card’s approach remains highly influential.

The second of Card’s most important articles was a collaboration with the late Alan Krueger, Card and Ashenfelter’s colleague at Princeton, who tragically died at age 58 in 2019. 1993 work examined the effect of the minimum wage on employment, testing the idea of ​​standard economic theory that imposing a minimum wage should, in general, have a negative effect on employment.

Aware that New Jersey would increase its minimum wage from $ 4.25 to $ 5.05 an hour on April 1, 1992, they collected data from fast food restaurants in New Jersey and, as a counterfactual, Pennsylvania, before and after the change. in New Jersey. Jersey minimum wage. This revealed that employment actually increased at New Jersey fast food restaurants relative to Pennsylvania, meaning that raising the minimum wage increased employment.

Josh Angrist and schooling

Josh Angrist is another product of the fertile environment in the labor relations section at Princeton of the 1980s. The Nobel Prize quotes Angrist’s work on econometrics – the application of statistical methods to explain economic phenomena, although his work on the economics of education is equally important. One of Angrist’s most influential contributions is a 1991 paper with Alan Krueger, who indisputably would have shared this award if he were still alive.

In trying to unravel the effect of education on income, Angrist and Krueger needed to rule out other factors, such as an individual’s innate ability or family background. These could have been correlated with the level of schooling of the students, but there was no data available to verify.

School kids holding hands
Josh Angrist brought new insights to education policy.
Syda Productions

Instead, Angrist and Krueger observed that US law said that students had to start school in the calendar year in which they turned six years old, but could drop out as soon as they turned 16. This meant that a student born on December 31 would have to spend a year longer than one born on January 1, for example.

Angrist and Krueger then used when individuals were born in the year to predict how much education they would get. Because when it is born in the year it is presumed that it is not related to their family history or innate ability, this allowed them to eliminate the influence of these things in the analysis.

What they found when they looked at a large cohort was as surprising as the work of Card and Krueger: They estimated that the effect of education on income was actually greater than previous estimates using conventional methods. There is still some controversy as to whether these results are fully reliable, but Angrist and Krueger’s article unquestionably set the standard for this type of analysis.

Guido Imbens and methodology

Guido Imbens, who did his PhD at Brown University (1991), has refined the tools that academics use to estimate causal effects, or to know when there are limits to how they can interpret their results. This has had an enormous influence on the definition of how we evaluate policy options.

Imbens’ most influential role, from 1996, he co-authored with Angrist and Donald Rubin, a Harvard statistician who could easily have shared this Nobel. It establishes a framework that helps us evaluate policies when some people reject an intervention and some people always accept it, for example, the effect of a job training program on wages.

In other extremely influential role, Angrist and Imbens define exactly for whom the causal estimates are valid. For example, Angrist and Krueger’s results on schooling are relevant only to those who were forced to stay in school until age 16, but would have left earlier if they could, and this may actually explain why the results they were different from previous estimates.

For Card, Angrist, and Imbens, the “credibility revolution” in economics consists in providing defensible estimates of causal effects, even if those estimates run counter to conventional economic theory. They fundamentally believe that “real world” data will reveal the truth and have developed methods to show us that truth.The conversation

David A Jaeger, Professor of Economics, St Andrews University

This article is republished from The conversation under a Creative Commons license. Read the Original article.


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