It was a moment of great happiness when news came that the Nobel Prize in Economic Sciences for 2019 has been awarded to Abhijit Banerjee, Esther Duflo and Michael Kremer for “their experimental approach to alleviating global poverty”. Their seminal and pioneering work in development economics using randomised evaluations (similar to clinical trials used in medicine) to test the effectiveness of social programmes and policies with the objective of reducing poverty marks a definite shift in discerning development from an entirely theoretical perspective.
Evidence from randomised evaluations can yield insights and conclusions into questions at the heart of controversial policy debates. Since the past decade or so, evidence-based policy-making has gained traction, with some governments and NGOs having institutionalised processes for rigorously evaluating innovations and incorporating evidence into decision-making.
One of the chief proponents of evidence-based policy-making is the Abdul Latif Jameel Poverty Action Lab (J-PAL) at the Massachusetts Institute of Technology (MIT) established by Professors Abhijit Banerjee and Esther Duflo in 2003. The path-breaking approach that they follow is popularly known as randomised control trial (RCT), which is used to test the effect of small interventions on individual behaviour. The lab has transformed the field of development economics from being mainly theoretical to empirical with high-quality evidence that has influenced piloting, testing, and scaling of effective policies around the globe. For example, with support from J-PAL and IPA, the Ministry of Education in Peru formed a dedicated unit to identify, test and scale low-cost interventions to improve educational outcomes.
J-PAL is promoting the scale-up and replication of effective programmes. Randomised evaluations allow researchers to learn not only about the impact of a particular programme but also to draw out the mechanisms behind its success to help derive general lessons that can be applied in the same context. But this requires adapting and scaling a programme taking into account local conditions and implementation capacity so that a programme that is effective at improving outcomes in one context may help in other places where the key problems and underlying reasons for the problems are similar.
For example, from randomised evaluations in India, Ghana and Kenya, researchers learnt why children are behind in school and thereby built a range of cost-effective strategies based on the insight of regrouping students by their current learning level rather than by their age group. On the other hand, the Government of Zambia has been able to apply the general idea of “Teaching at the Right Level” (TaRL, an approach developed by Indian NGO Pratham) to inform the design of its own remedial programs. This has significantly improved the learning opportunities in both India and Africa.
Evidence-based policy-making (EBP) assists in making decisions about projects, programmes and policies, by placing the best available evidence from research conducted at the heart of policy development and implementation. It also makes explicit what is known through scientific evidence. In contrast to opinion-based policy-making, evidence-based policy-making needs an evidence base at all stages in the policy cycle to define issues, shape agendas, make choices of action, identify options, deliver them, and monitor their impact and outcomes. Basically, it is a set of methods which informs the policy process, rather than aiming to directly affect the eventual objectives of the policy. Thereby, EBP advocates a more systematic, rational and rigorous approach to produce better outcomes.
The pre-requisite for evidence-based policy is that the data must be trustworthy, and it depends upon the quality of the data and the quality of the professional statisticians. Credible statistics is important for good governance and decision-making in all sectors of society. Therefore, policy-makers are more likely to use evidence in decision-making if that evidence is unbiased, rigorous, substantive, relevant, timely, actionable, easy to understand, cumulative and easy to explain to constituents. In developing nations, EBP approaches can dramatically help reduce poverty and improve economic performance.
Two cases that highlight the value of EBP in developing nations: one where evidence-based policies transformed lives and the other where the lack of an evidence-based response has caused widespread death. First, the Government of Tanzania has implemented various health service reforms informed by the results of household disease surveys. This EBP contributed to over 40% reductions in infant mortality in two pilot districts. Second, the AIDS/HIV crisis has aggravated in some countries because respective governments have ignored the evidence of what causes the disease and how to prevent it from spreading further.
Impact evaluations of social programmes have emerged as an important tool to guide social policy in developing polities as they allow for accurate measurement and attribution of impact can help policy-makers identify programmes that work and those that do not work, so that effective and performing programmes can be promoted and ineffective ones can be discontinued. J-PAL has shown how complex development challenges can be solved with data and evidence.
All Indians are proud of Professor Banerjee’s achievements. But as India is facing an economic slowdown, it is high time the government ensured that policy was driven by evidence and reasoning, and research was translated into action. The EBP has the potential for high-impact change that we shouldn’t ignore. Thereby, systemic institutionalisation of EBP is the way forward in the fight to eradicate poverty and to improve economic performance, education, health care and social assistance for millions of people.
