Economists Do This Too

The 2019 Nobel Prize in Economics was awarded to Abhijit Banerjee, Esther Duflo and Michael Kremer for “their experimental approach to alleviating global poverty”. Why did this trio receive the prize?

To understand the main reasons behind this decision of the Royal Swedish Academy of Sciences, we should appreciate the nature and path of development economics. This is a difficult field in economics because, despite its noble goal (help poor countries to catch up with rich countries), it is not well defined. Indeed, it is not clear why economics laws should be different for poor and rich countries. We do not have special laws of physics for Uganda and Germany. Why should we have special economics for these two countries? In addition, development economics is neither microeconomics nor macroeconomics because one can help a developing economy via a variety of policies. As a result, development economics has been historically a mix of different disciplines with different methodological approaches. But perhaps the most important challenge for development economics is that no single force is responsible for why a given country is poor. For example, why is Ukraine a poor country? Is it because of hyperinflation in the 1990s? Poor protection of property rights? Oligarchs? Corruption? Lack of oil? Soviet legacy? High consumption of alcohol? There is a myriad of possible explanations and it is hard to establish the contribution of each one.  

Given these challenges, development economics went through many paradigm shifts and much soul searching. For example, a popular theory in development economics was that government intervention is desirable. Many poor countries embraced some form of central planning. Then the consensus view was that markets are better equipped to foster development. As a result, government property was privatized. Some theories emphasized that economic development can be achieved by a “big push” which required significant financing to build e.g. a giant dam (typically this was funded by the World Bank and other external donors). Some suggested focusing on small projects supported by micro-finance. Sadly, it was not clear if any of these ideas really worked. The inability to prove decisively that some theory is working (or not working) generated much disagreement in what we knew and what policies were helpful.

Against this background of utter confusion and bitter disputes, Banerjee, Duflo and Kremer made a transformation of development economics into a science-based field. Their idea was disarmingly simple and powerful. Science is making progress by reducing complicated problems into a set of small problems. The size of these small problems should be such that one can run an experiment and establish how a small problem “works” and whether this small problem can be addressed by some policy. When we have enough evidence to understand small problems, we try to assemble this evidence to understand the big problem. Can we run experiments on humans? Their thought was that if the medical science can do it, economics should be able to do it too.

What was a typical experiment pioneered by this group? Suppose you are interested in long-term effects of providing mosquito nets on economic development. This may seem to be a trivial problem, but malaria is a major death factor in poor African countries. Because malaria reduces life expectancy, people in these countries may be unable to invest in human capital. Indeed, why would anybody spend 20 years in school if life expectancy is only 50 years? The Banerjee-Duflo-Kremer approach is to identify areas plagued by malaria. Suppose you have 100 villages in such an area. Then you randomly split villages in two groups. The first group receives a treatment: every household in this group gets a free mosquito net. The second group receives nothing (control group). Then you observe economic outcomes for these two groups. Note that which village is provided with nets is determined by chance (you can literally flip a coin). As a result, if there is a difference between treated and control villages, you know that this difference is due to the treatment. After you have many experiments like this, you have a lot of hard evidence on causal effects of providing nets to population vulnerable to malaria.

This approach can be adapted to many, many problems. What is the effect of micro-financing on investment? What is the effect of flexible labor markets on local employment? What is the effect of schooling on wages? What is the effect of childcare on female empowerment? These are just some examples of what we can answer with experiments.

Obviously, the Banerjee-Duflo-Kremer approach does not resolve all problems in economics. For example, if everybody is provided a free mosquito net, who should be paying for nets and what should be the right price? General equilibrium effects are typically not well understood with the approach. But the approach allows us to build solid foundations for our theories and policies.

In summary, Banerjee, Duflo, and Kremer turned development economics into a giant laboratory. Thousands of researchers and institutions run experiments to shed new light on a broad range of problems (health, education, discrimination, infrastructure) and to provide evidence-based solutions. As a result, the lives of millions and millions of people have been improved dramatically. This contribution is certainly worthy of Nobel!