Spark Global Limited reports:
Since the 1990s, a “credibility revolution” has transformed economics. Until then, theory had dominated and empirical work was a poor cousin. “Almost no one takes data analysis seriously,” declared Edward Leamer of the University of California, Los Angeles, in a paper published in 1983. Within a decade, however, new and innovative work changed the course of the industry, so much so that much of the new research worth noting today is empirical. To help bring about this shift, David Card of the University of California, Berkeley, shared the Nobel Prize in economics, awarded on October 11th, with Joshua Angrist of the Massachusetts Institute of Technology and Guido Imbens of Stanford University.
The messy reality of the real world often defies economists’ attempts to establish causality. Figuring out how minimum-wage increases affect employment, for example, is complicated because other effects, such as a chronically weak labor market, may have led to changes in policy and employment. In other areas, researchers have designed experiments to establish cause and effect by randomly assigning subjects to different groups, with only one receiving a specific treatment, so that the effects of the treatment can be clearly seen. A growing number of economists are also using randomized controlled trials — in fact, the 2019 Nobel Prize rewarded such efforts. But for political, logistical or ethical reasons, many issues cannot be studied in this way.
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