At the migration session, Marieke Kleemans presented a thoughtful paper on labor market changes in response to immigration, using weather shocks as an instrument for internal migration in Indonesia. Her discussant, Michael Clemens from the CGD gave some insightful comments in return, including one that posited that weather stations (the source of her climate data) might actually be located somewhere between the source town and the destination city that drives migration. This called into question the exogeneity of her instrumental variable, and potentially the entire identification. It also led to the appropriately sarcastic exclamation from a frustrated economist: "Great. Even rainfall isn't exogenous anymore."
And this leads me to frustration number three: the elusive quest for exogeneity. In order to be able to discuss the causal effect of X on Y, it is imperative that you ensure both a) that Y doesn't cause X and b) that unobservable factors don't affect both X and Y systematically. Exogeneity is crucial to identifying an unbiased causal effect. However, my concern is that the exogeneity bar (likely due to the gold standard of randomized controlled trials) has been raised so high that our focus on exogeneity as the primary objective can consequently side-line development research objectives.
It certainly isn't the case that research with a great exogenous variable necessarily overlooks development altogether, but my fear is that switching the objective of the research to exogeneity limits the set of development questions we might even ask. Additionally, my concern does not go so far as to call into question the legitimacy and effectiveness of using randomized controlled trials to study development, although Angus Deaton has written about this (a fantastic video summarizing his views through a review of Poor Economics is available here). However, I do want to re-emphasize that the objective of good economic development research should be informing and shedding light on development.
It seems to me that an obvious source of good development questions is from practitioners working in developing countries and communities of stakeholders, but this is actually fairly uncommon in economics research. In a nice World Bank working paper, "Evaluation in the Practice of Development," Martin Ravallion point out that "Academic researchers draw the bulk of their ideas from the work of other academic researchers. To be useful, evaluative research [in development] needs to draw more heavily on inputs from non-researchers actively involved in making and thinking about policy in developing countries." Also interestingly, Ravallion will be the keynote speaker next year at the Midwest International Economic Development Conference in Madison, WI.
Last week, Dean Yang, gave a talk at at our APEC Development Seminar on experimental results in Malawi of updating prior savings choices. Since he does a lot of migration research (where the exogeneity challenge is ever present), I asked him about this. And although he said that he would officially place himself in a camp of high value on identification, that the concern of limiting the set of research to causally identifiable effects is an important and potentially controversial meta-level question. And he added that, in terms of publication, research on correlations (that bypass problem of exogeneity) are still relevant and important, especially if you bring a policy-relevant and unique dependent variable to the table. Perhaps 'unique dependent variable' is an economists way of cautiously saying: tell me why I should care.
Hat tips: ALD, DY, CBT