Jeff Tollefson :
(From previous issue)
But the randomistas have been accused of succumbing to their own biases. Some fear that their insistence on the RCT has skewed research towards smaller policy questions and given short-shrift to larger, macroeconomic questions. One example comes from Martin Ravallion. An economist at Georgetown University and a former research director at the World Bank, he cites an antipoverty programme in China that received $464 million from the bank in the 1990s. Although the programme involved road construction, housing, education, health and even conditional cash payments for poor families, a study based on data collected in 2005, 4 years after disbursement ended, found minimal average impact on citizens6. “That was the only long-term study of integrated rural development, which is the most common form of development assistance,” Ravallion says.
Yet some families did benefit, and by combining statistics with economic modelling, he and his team showed that the difference lay in basic issues, such as education level. For Ravallion, the message is that aid is best targeted at the literate poor, or more broadly at issues such as literacy. “Governments need to know these things,” he says. “They can’t just know about the subset of things that are amenable to randomization.”
To Alexis Diamond, a former student of Duflo’s who manages project evaluations at the International Finance Corporation, the private-sector development arm of the World Bank in Washington DC, the debate between the randomistas and the old-guard economists is in many ways about status and clout. The latter have spent their careers delving into ever more complex and abstract models, he says. And then “the randomistas came along and said ‘We don’t care about any of that. This is about who has a seat at the table’.”
Diamond says that he tries to strike a balance at his organization, where most evaluations still rely on a mixture of quantitative and qualitative data, including expert judgement.
Duflo shrugs off the debate and says that she is merely trying to provide government officials with the information – and tools – that they need to help them spend their money more wisely. “The best use of international aid money should be to generate evidence and lessons for national governments,” she says.
She points to a anti-pollution programme in industrial plants in the Indian state of Gujarat. Partnering with a group of US researchers, the state ran an experiment in 2009 that divided nearly 500 plants into 2 groups. Those in the control group continued with the conventional system, in which industries hire their own auditors to check compliance with pollution regulations. The others tested a scheme in which independent auditors were paid a fixed price from a common pool. The hope was that this would eliminate auditors’ fear of being black-balled for filing honest reports. And it did: independent auditors were 80% less likely to falsely give plants a passing grade, and many of the industrial plants covered by those audits responded by curbing their pollution. In January, regulators rolled out the programme across the state.
“My hope, in a best-case scenario, is that in the next ten years you are going to have many, many of these projects run as a matter of course by governments in the spaces where they want to learn,” Duflo says.
(Jeff came to Nature from Congressional Quarterly, where he covered energy, climate and the environment for two years.)
