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During the past two decades, something unexpected happened in the field of development economics. Researchers got out from behind their desks to figure out why, after billions of dollars had been spent on foreign aid, so many poor people were no less poor. They began talking with those they were trying to help: the parents whose babies were dying from contaminated water. The farmers who were eking out an existence. The teachers in communities where children remained illiterate.
These economists figured they could do better than the failed policies put forth by past generations of development experts. By rolling up their sleeves and running experiments, they were going to figure out what worked and what didn’t. And through that, they were going to find cures for poverty.
The work of these "randomistas," so called because of their use of randomized control trials, or RCTs, took off with the creation of research centers that provided the infrastructure, financing, and networks to make more experiments possible. Many projects were designed by eager young graduates of doctoral programs, excited by the immediacy of the work. Innovations for Poverty Action, a Connecticut-based nonprofit organization founded by the Yale economist Dean Karlan, has a staff of more than 900 and projects in 48 countries. The Center for Effective Global Action, based at the University of California at Berkeley, includes a network of 50 researchers.
But some economists argue that this kind of work doesn’t fit in their field. "We’ve always tried to develop and test models about human behavior," says Lant Pritchett, a professor of the practice of international development at Harvard University’s Kennedy School of Government. "But looking down latrines in order to know whether their construction is effective or not is not what economists have done or should do."
"I don’t think we should understate the importance of the approach. They’ve helped clarify deep problems with the way systems work," says Nancy Birdsall, president of the Center for Global Development. Where she thinks the work falls short is in its assumption that a simple scientific method can fix real-world problems: "The notion that we could bring more rigor and expertise to a complex and adaptive system doesn’t seem right to me."