Alternatives to the new scientism in development economics

When Abhijit Banerjee and Esther Duflo were announced as two of this year’s Nobel Prize winners, it prompted a fresh flurry of public critiques of their work in development economics. From voices as diverse as Oxfam’s Duncan Green and Marginal Revolution’s Alex Tabarrok, many economists and aid experts have cautioned against pinning all our poverty reduction hopes on their findings.

At the heart of the debate is whether randomized-control trials (RCTs), the so-called gold standard of social science research, are ethical and efficacious when it comes to economic and social intervention. On the ethics, most of the issues are somewhat familiar—who wants to willfully withhold treatment from a control group of vulnerable, low-income human subjects, and what does informed consent look like in these acute circumstances? The efficacious question is more complicated. In short, RCT findings in the context of complex developing economies are often not as generalizable as one would hope, meaning you can’t apply the findings at scale in other contexts. This makes them less useful if you are cautious about this fact and very dangerous if you are not.

So what’s the alternative? The question helped to animate a recent full-day academic seminar co-hosted by Atlas Network and Institute for Humane Studies in Ft. Lauderdale, Florida to kick off the Southern Economic Association’s annual meeting. The event, “Poverty, Institutions, and Economic Development,” presented the latest research and insights from a diverse and impressive suite of experts including Dr. Michael Woolcock from Harvard University, Dr. Arvind Panagariya from Columbia University, IHS President Dr. Emily Chamlee-Wright, UFM President Dr. Gabriel Calzada, Dr. Tom Palmer of Atlas Network, and Dr. Peter Boettke of George Mason University, among others.

From left to right: Matt Warner, Emily Chamlee-Wright, Pete Boettke.

A consistent theme among most presenters was the inherent complexity of institution building, a fact that limits the effective influence of outsiders looking to fix systemic problems in local contexts. This message not only challenges traditional foreign aid intervention methodologies but it also lends weight to the evidence presented in Atlas Network’s new book, Poverty & Freedom: Case Studies on Global Economic Development. Using case studies from 12 different countries and contexts, the book demonstrates the role local think tanks can play in accelerating the process of institution building that favors increased prosperity.

In the wake of the widespread criticism, Banerjee and Duflo just released a manifesto-length defense of their work in Foreign Affairs, arguing that not only is growth too crude a proxy for what our global aid should be aiming to achieve, it is unlikely to continue apace, and therefore our philosophies of wealth creation, so to speak, have run out of steam. For them, this should make us more agnostic about what actually works to improve human well-being, an agnosticism that is meant, in their approach, to be slowly mitigated only by results that come from Banerjee-Duflo type experiments in the field. What’s more, the lack of philosophy in their essay becomes most troubling in their conclusion which seems to imply that the role of the state is to pursue human well-being based on their and their colleagues’ latest findings, full stop.

From left to right: Atlas Network’s Tom G. Palmer, Dwight Lee, Adam Smith, Gabriel Calzada.

What a catastrophic implication this promises to be. As far back as 1948 Rockefeller Foundation’s Warren Weaver, writing in American Scientist, argued for making a critically important set of distinctions to prevent mismatching scientific methodologies to their corresponding types of inquiries. He suggests that problems of what he calls “organized complexity,” where large numbers of interdependent factors contribute to something tending towards order, such as is the case with developing economies, call for a “third advance” in scientific approach that looks beyond the aggregate findings useful for problems of “disorganized complexity” such as predicting some probability of mortality for a population of life insurance policyholders. Of course, no one would presume to use actuarial tables to make predictions about a specific person’s final day on earth nor would they draw on those results to prescribe interventions to prevent it.

In F.A. Hayek’s Nobel Prize speech, he warns against the scientism he had observed in the 1970s that led some to believe all that mattered was what could be measured and what could be measured was the sum of all knowledge. The new scientism of Aberjee and Duflo suggests the same. It’s a mistake.