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New tools for studying scientists

In the 1990s, a few labor economists (including MIT’s Joshua Angrist) discovered new ways to conduct “natural experiments,” studies that mimic laboratory-style randomized trials. They began using historical data to pinpoint the impact a single difference makes between two otherwise equivalent groups of workers. At the same time, detailed Internet citation databases began cropping up, giving economists a source of hard data for natural experiments that assessed the influence, productivity, and teamwork of equivalent groups of scientists. These developments enabled economists to study scientists closely for the first time, says Scott Stern of Kellogg, a former MIT economist and a prominent figure in the analysis of science.

Azoulay and his colleagues put these new tools to work to study the widely held belief that working with the top people in a given field makes other scientists more productive. The project began in 2002, when Azoulay, a voluble native of France, gave a talk about the biotechnology industry and discovered an audience member who was equally knowledgeable about the subject: Joshua Graff Zivin, an economist at the University of California, San Diego. Soon the two were studying the effect of “superstar” scientists on their colleagues. They found that scientists who worked alongside these leading lights indeed had more impressive publication records than those who did not.

But after presenting some findings to the NBER in 2004, they recognized that they had an unresolved problem. Were the collaborators more productive because they worked in the orbit of their fields’ stars? Or did they get the opportunity to work with the stars because they were more capable scientists in the first place?

Going back to the drawing board, Azoulay and Graff Zivin found the answer by examining the performance of laboratories whose star researchers had died suddenly. After combing through obituaries in such publications as the New York Times, the economists compiled a list of 161 such scientists and then scrutinized the records of more than 8,000 researchers who had coauthored papers with them. The result? The productivity of the collaborators dropped 5 to 8 percent after the superstars died. The finding, which they published this year with MIT PhD candidate Jialan Wang in the Quarterly Journal of Economics, quantifies the extent to which top scientists infuse their fields with new ideas and research topics.

The freedom to fail

Natural experiments also allow economists to study how different types of grants affect scientists. For instance, it turns out that scientists whose funding affords them unusual long-term freedom in the lab are more likely to generate breakthroughs, according to a November 2009 working paper by Azoulay, Graff Zivin, and Gustavo Manso, an assistant professor at Sloan.

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Credit: by Marc Rosenthal

Tagged: Computing

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