The future of development economics is random

This first posted on the IPA blog.

Chris Blattman notes that this Summer’s edition of the Journal of Economic Perspectives is focused on development economics. What he doesn’t note is that the articles are heavily focused upon the role of randomized controlled trials within development economics, taking perspectives that are both positive and constructively critical.

Banerjee and Duflo make the case that it is advances in empirical testing that have revolutionized the entire field.

After a period of relative marginalization, development economics has now reemerged into the mainstream of most economics departments, attracting some of the brightest talents  in  the field … We believe that one of the reasons for the field’s vitality is the opportunity it offers to integrate theoretical thinking and empirical testing, and the rich dialogue that  can  potentially  take  place  between  the  two … In the last few years, field experiments have emerged as an attractive new tool in this effort to elaborate our understanding of economic  issues  relevant  to poor countries and poor people … Much of this paper illustrates the power of this interplay between experimental and  theoretical  thinking.

Angus Deaton, one of the elder statesmen of micro-econometrics, and randomista-critic, argues that experimental and quasi-experimental methods answer the what question but not the how or the why.

Instrumental variables and randomized trials can play a role in uncovering the mechanisms of development. Randomized trials have a powerful ability to isolate one mechanism from another; in particular, an experiment will often allow us to short circuit the often difficult process of developing theoretical mechanisms  to  the  point  where  they  can  be  convincingly  tested  on nonexperimental data. At the same time, the routine use of instrumental variable methods and of randomized controlled trials for project evaluation is often uninformative about why the results are what they are, and in such cases, nothing is learned about mechanisms that can be applied elsewhere.

Daron Acemoglu raises an important concern for scale-up, which is the question of how the effects of a project tested on a small scale, may have different impacts on a larger scale. He advocates the careful use of economic theory to help alleviate these concerns.

General equilibrium and political economy issues often create challenges for this type of external validity…General equilibrium and political economy considerations are important because partial equilibrium estimates that ignore responses from both sources will not give the appropriate answer to counterfactual exercises.

How do we  convince others  and ourselves  that our  estimates have  external validity and can be used  for policy analysis or  for  testing  theories? This is where economic theory becomes particularly useful.

And finally Dani Rodrik makes the case for his particular brand of theory; the diagnostic approach, as a tool to be used in conjunction with randomized experiments for helping to overcome the problem of external validity and deciding which interventions are likely to be most powerful in which contexts.

Ideally, diagnostics and randomized experiments should be complementary; in particular, diagnostics should guide the choice of which random experiments are worth undertaking.  Any developmental failure has hundreds of potential causes. If the intervention that is evaluated is not a candidate for remedying the most important of these causes, it does not pass a simple test of relevance. Yet the tools of diagnostics remain surprisingly underresearched.