Randomized control trials – why they deserve the Nobel and what should happen next

This year’s Nobel Prize in Economics was awarded to Abhijit Banerjee, Esther Duflo, and Michael Kremer for their experimental approach — randomized control trials (RCTs) — to alleviating global poverty. Thanks to Banerjee, Duflo, and Kremer and their networks, the RCT method, which uses field trials to test development interventions, has come to dominate the field of development economics.

RCTs provide a solution to the data gap

A key challenge in empirical development economics has traditionally been the lack of data of high enough quality to, for example, show true causal impacts of programmes and policies to alleviate poverty. Administering RCTs that include self-collected evaluation data may solve this challenge, in particular when testing specific well-defined research questions on finding out what in the intervention actually works and how.

Therefore, this trio’s commitment to providing new solutions to the challenge of finding reliable evidence of the most cost-effective ways of tackling extreme poverty should be commended.

As a result of their research, more than 5 million children in India have benefitted from remedial tutoring programmes in schools. Furthermore, questions about the cost of deworming pills for parasitic infections have been answered, impacting policy decisions on healthcare. Thanks to Abdul Jameel Poverty Action Lab (J-PAL), founded by Banerjee, Duflo, and Sendhil Mullainathan, over 400 million people have been reached by scale-ups of programmes that were found to be effective.

The RCT debates

Despite the tremendous achievements of the RCT revolution, debates in the development economics field continue on the role of the method within the discipline. Some argue that Banerjee, Duflo, and Kremer’s success shifts attention and funds away from the big questions like, how can policy makers tackle root causes of poverty?

Others criticise the RCT method because it makes publishing research more challenging for those who do not use it. And some say that the people doing RCTs have not addressed the issue of agency thoroughly enough in their experiments — if, for example, some groups may be more responsive to intervention than others.

As a development economist, and someone who has used RCTs in their research, I see merit in these critiques. Much of the critique is useful in improving the appropriate use of the research method by the growing research community employing these methods. Conducting reliable RCTs is not easy, requires a lot of planning, funds, and time. It is natural that the research groups that manage to do them completely right do also get published well.

However, only certain types of research questions in development economics can be studied using RCTs and I remain optimistic that carefully conducted papers with innovative ideas will continue to publish well, irrespective of having an RCT framework or not. 

The next steps to increasingly scale-up effective programmes

The prestige of the Nobel might help direct more funding to poverty alleviation programmes, but the extent to which interventions based on new knowledge from RCTs will be successful depends a lot on how well this knowledge is absorbed by grassroots practitioners.

To ensure that the accumulated experimental evidence has the desired impact on policy, there is a need to strengthen the connections between research and policy to improve the results for the beneficiaries.

The success of scaling up of programmes is highly dependent on how well the correct information regarding how to design, pilot, and manage interventions is getting through to the policy makers and practitioners.

For example, a now well-known study from Banerjee et al. found that when immunization programmes were delivered to camps near to where recipients lived and worked — and small incentives (a bag of lentils and a metal plate) accompanied the offer of free vaccinations — the rate of immunization of children would go up more than sixfold.

If a policy maker or practitioner would, looking at the study, decide that it would be good idea to implement the same process, but with the tiny change of leaving out the cumbersome task to organise lentils and plates, they would not necessarily get the same increase in immunization levels, because the lessons of the research would not have been fully translated to policy action.

This is where a lot more work will need to be done in the future to get the right policies and implementation schemes in place to get the benefit of the research evidence that the RCTs are generating.

The views expressed in this piece are those of the author(s), and do not necessarily reflect the views of the Institute or the United Nations University, nor the programme/project donors.

Reflections on the 2019 Nobel Prize in Economics
Reflections on the 2019 Nobel Prize in Economics
Data for better policies
Thanks to the updated version of the Government Revenue Dataset ( GRD ) we are now able to gain a clear picture of tax and other revenue trends in over 190 countries over the past four decades, now up until 2018...
Data for better policies