At the annual meeting of the American Economic Association, held this year in New Orleans, wonks discussed everything from inflation and technological progress to the economics of crime and the energy transition. Yet those looking for big breakthroughs would have left unsatisfied. Most new work focused on rigorous analysis of data or painstaking theoretical modelling. As one attendee noted, such modelling often fails to produce surprising results, since it tends to reflect the assumptions that go into it.
Evidence for this downsizing of ambition is not purely anecdotal. A recent paper in Nature analyses citation data from 1945 to 2010 to assess the disruptiveness of papers and patents. The authors consider new work to be disruptive if later work that cites it is less likely to also mention its predecessors. The paper concludes that the share of disruptive research in the social sciences has fallen precipitously, even more so than in the actual sciences. As Tyler Cowen of George Mason University puts it: “In the last 30 years the reliability of empirical work and estimations has risen dramatically. Which is good. But few new important ideas have really been generated.”
In New Orleans economics’s biggest names offered ideas that were fresh and interesting, but hardly breakthroughs on the scale of, say, the Nash equilibrium or the idea of asymmetric information. Gita Gopinath, the imf’s chief economist, discussed research on how the economics of international finance has shifted since the seminal work of Robert Mundell and Marcus Fleming in the 1960s. In a seminar on economic growth, Thomas Philippon of New York University argued that growth follows linear trends, rather than being an exponential process. Daron Acemoglu of the Massachusetts Institute of Technology presented work on “distorted innovation”, arguing against the idea that markets tend to get innovation right.
New theories without robust empirical support can be dangerous, as demonstrated by the rise of central planning during the 20th century. And big advances are easier to spot in hindsight. It may even turn out that there were some hidden among the presentations in New Orleans. Some conference attendees were also more optimistic about the present state of affairs. A professor noted that good questions in economics tend to come from real-world events—and the past few years have been tumultuous enough to raise plenty of good questions. Erik Brynjolfsson of Stanford University observes that the use of large datasets, machine learning and field experiments are all “game-changers”. Innovation may therefore simply be shifting from theory to practice. Indeed, the use of high-frequency data, a feature of a presentation by Lisa Cook of the Federal Reserve, has given economists and central bankers a helpful new way to look at the world in their fight against inflation.
Yet the most compelling evidence on the impact of monetary policy on inflation came from Christina Romer of the University of California, Berkeley, who dusted off an old-fashioned method. In her talk, she argued that monetary-policy changes have bigger effects on unemployment than inflation, and that it sometimes takes a few years for their main impact to be felt. The method used by Ms Romer and her husband and co-author, David Romer, was not a new statistical technique or even timelier data, but a “narrative approach”. The Romers combed through transcripts and minutes from meetings held by the Federal Open Market Committee—just as they had when they developed the method in a paper published in 1989. ■
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