It’s not enough to compare lifetime wages of people who did and didn’t serve, because they might be systematically different from each other in other hard-to-detect ways. Let’s say you want to figure out the effect of serving in the military during the Vietnam War on earnings later in life. That’s one example of an ingenious tool that this year's Nobel laureates advanced. So they exploited the fact that seasonal effects in eastern Pennsylvania are similar to those in New Jersey, effectively using Pennsylvania as the “control” group. If Card and Krueger had looked only at employment in New Jersey, they would have had trouble disentangling the effect of the higher minimum wage from the effect of seasonal changes in fast-food employment. Contrary to accepted wisdom, the economists found “no indication that the rise in the minimum wage reduced employment.” Fast-food restaurants on either side of the border between New Jersey and eastern Pennsylvania were similar in every important respect except how much they had to pay workers, since New Jersey had raised its minimum wage. Card and his fellow economist Alan Krueger famously exploited a variation in the state minimum wage between New Jersey and Pennsylvania to see whether raising the minimum wage kills jobs. As a fallback, economists look for “natural experiments”: real-life situations that, because of a quirk of nature or government policy or some other source, resemble designed experiments.Ĭard, Angrist and Imbens are clever at identifying and learning from natural experiments. You can’t randomly assign certain people to be smokers or drop out of college, for instance. More often, though, proper experiments are impossible. The 2019 Nobel in economics went to Abhijit Banerjee, Esther Duflo and Michael Kremer for such experiments, which were aimed at alleviating global poverty. Sometimes economists can run proper experiments, where certain randomly chosen people are “treated” (experimented on) and the rest serve as a “control” group. We will never know for sure if taking an aspirin is what cured your headache, but we can measure the average effect of aspirin across thousands of headache sufferers who did or didn’t take a tablet. interview with unmatched socks), it’s possible to find the average effect by doing experiments on multiple people. While it’s impossible to rewind the clock to observe both possibilities for a single individual (interview with matched socks vs. And you can’t test the hypothesis by rerunning the interview with matched socks.Įconomists call this “the fundamental problem of causal inference.” Luckily, there’s a way around it. Just because you wore mismatched socks to a job interview and didn’t get the job doesn’t prove the hypothesis that the wardrobe malfunction was what killed your chances. The problem that econometrics deals with is that correlation does not imply causation. These tools are powerful yet easily graspable, like a good pair of pliers. I want to focus instead on the tools that the three developed. A lot of excellent articles about the Nobel have focused on how these scholars upset conventional economic wisdom on topics such as the minimum wage and immigration. That said, I am pretty excited by the awarding of the prize to Angrist, of the Massachusetts Institute of Technology Card, of the University of California, Berkeley and Imbens, of Stanford University. I’m only on, so the T-shirt remains in the dresser.
To wear the T-shirt, one really ought to complete the book. I got it in 2015 as a promotional tie-in with a review copy of a book on econometrics called “Mastering ’Metrics: The Path From Cause to Effect,” co-written by Joshua Angrist, who on Monday received the Nobel Memorial Prize in Economic Sciences along with David Card and Guido Imbens. It says “Master of ’Metrics” on the back. I have a T-shirt that I have never put on because I don’t deserve to wear it.
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