Broader message for India to focus on data in policy

It is a rare and joyous moment when your three most influential advisers and mentors win a Nobel Prize together – and Monday was that day! Abhijit Banerjee, Michael Kremer, and Esther Duflo have just received the Nobel Memorial Prize in economics for their pioneering work in the use of randomized field experiments to study the effectiveness of policies and programs at improving human well-being.

Abhijit Banerjee is an extraordinarily broad and deep development economist, with seminal contributions in several areas. Abhijit’s special genius is in how he has reinvented himself multiple times as a scholar to continue producing top-quality new research at a pace that would put those half his age to shame. In the eighties and early nineties, when data was limited, the most insightful ways to think about development were theoretical and his earliest classics were pure theory papers. These covered topics such as how people learn new facts and ideas, and the relationship between wealth distribution, occupational choice, and development. With the onset of personal computers and greater access to better quality of data in the mid-nineties, his work evolved to combining elegant applied theory with data to study fundamental questions in development economics such as the impact of land reforms on agricultural productivity. Finally, with the increasing use of randomized experiments in development economics (more below), he has written highly-influential empirical papers that study the impacts of specific policies to improve development outcomes including education, health, and reduction in poverty.

Abhijit’s transition to more empirical work and randomized experiments in particular, was in turn influenced by his association with Michael Kremer, when they were both on the faculty at MIT in the mid-nineties. Similar to Abhijit, Michael’s early classics and professional recognition came from his theoretical work. However, Michael had also spent three years before his PH.D. teaching in rural schools in Kenya and formed an early appreciation for how little data and evidence there was to test various programs and policies that claimed to improve the lives of the poor. When he won a Macarthur “genius” award, Michael used these funds to start running randomized field experiments in Kenya to test the effectiveness of specific policies to improve education and health outcomes.

The key idea behind a randomized control trial (or RCT) is that a program is first provided to some participants chosen by a random lottery (a “treatment” group) while others get the program later and serve as a “control” group. Since these groups are identical on average and treatment is assigned by lottery, comparing outcomes over time allows researchers to credibly study the impact of specific policies. While RCTS have their limitations, they are often considered the “gold standard” of evidence, and are the standard method used in testing and approving new medicines around the world. RCT’S were not a new idea, but Michael’s main contribution was to systematically start using them to evaluate development interventions. As he once mentioned to me, “a new medication goes through the rigour of an RCT even when it only affects a few hundred thousand people; so it’s crazy that we spend billions of dollars on policies and programs affecting hundreds of millions of people with nothing close to the same level of evidence on effectiveness or lack thereof”.

Finally, the person perhaps most responsible for the RCT revolution in development economics is Esther Duflo – the youngest ever winner of the Nobel Prize in Economics. A force of nature, Esther was a student of Abhijit’s and Michael’s at MIT and co-founded the Jameel Poverty Action Lab (or JPAL). Under her leadership, JPAL has, in just fifteen years, transformed the field of development economics from being mainly theoretical to predominantly empirical and informed by high-quality evidence on the causal impact of programs and policies. JPAL now has over 180 affiliated researchers, and has nearly a 1000 completed and ongoing RCTS in sectors ranging from education, health, credit, savings, and governance.

Of course, many important questions are not amenable to RCTS, but many others have benefited enormously from this body of evidence. Taken together, these studies have built a rich set of facts that have informed and transformed how we think about many topics in development economics. In particular, the evidence shows that there is large variation in the impact and cost-effectiveness of policies and thus, shifting public (and donor) spending from less to more cost-effective programs and policies can significantly improve outcomes within a given budget.

The broader message for India in this prize is that solving complex development challenges requires careful attention to data and evidence. Companies and products face a “market test” where they receive rapid feedback on whether a product is working or not. In contrast, it is possible for governments to spend taxpayer money badly for a long time without facing the consequences. This magnifies the importance of evaluation of major programs, and improving the quality of public expenditure. The economic slowdown is a good occasion to appreciate and institutionalize a more systematic focus on data, evidence, and value for money in policy.

THE MESSAGE FOR INDIA IN THIS PRIZE IS THAT SOLVING COMPLEX DEVELOPMENT CHALLENGES REQUIRES CAREFUL ATTENTION TO DATA AND EVIDENCE