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For those of you who (i) are thinking of going to graduate school, (ii) have an interest in food security, and (iii) happen to be US citizens, I am happy to announce that my colleague Tim Beatty and I were recently awarded a $262,500 grant from the National Institute of Food and Agriculture‘s (NIFA) National Needs Graduate Fellowship program.

This grant will fund three PhD students, providing each of them with a three-year fellowship. The theme of the grant is food security broadly defined. So for example, a fellow could study any aspect of food security, from undernutrition in sub-Saharan Africa to food stamps in the US, and everything else in between. That said, for students interested in international development, the grant does include some money for international travel–not enough to fund data collection, but enough to fund exploratory field visits.

On the Worthwhile Canadian Initiative blog, Frances Woolley had a good post about why beginner econometricians get so worked up about the wrong things:

[I]t is rare that I will have someone come to my office hours and ask “Have I chosen my sample appropriately?” Instead, year after year, students are obsessed about learning how to use probit or logit models, as if their computer would explode, or the god of econometrics would smite them down, if they were to try to explain a 0-1 dependent variable by running an ordinary least squares regression.

I try to explain: “Look, it doesn’t matter. It doesn’t make much difference to your results. It’s hard to come up with an intuitive interpretation of what logit and probit coefficients mean, and it’s a hassle to calculate the marginal effects. You can run logit or probit if you want, but run a linear probability model as well, so I can tell whether or not anything weird is going on with the regression.”

But they just don’t believe me.

Continue readingRookie Mistakes in Empirical Analysis

One of the most famous papers in development microeconomics is Chris Udry’s 1996 JPE article, in which he finds on average, within the same household and after controlling for a number of possible explanations, women remain less productive on their own plots than men are on their plots. That finding is at odds with economic theory, which dictates that productivity should be equal across all the plots owned by a given household. Here is the abstract of Udry (1996):

Virtually all models of the household assume that the allocation of resources is Pareto efficient. Within many African households, agricultural production occurs on many plots controlled by different members of the household. Pareto efficiency implies that factors should be allocated efficiently across these plots. I find, in contrast, that plots controlled by women are farmed much less intensively than similar plots within the household controlled by men. The estimates imply that about 6 percent of output is lost because of inefficient factor allocation within the household. The paper suggests a new approach to modeling intrahousehold allocation consistent with the empirical results.

Ever since then, the gender gap in African agriculture has generated a great deal of discussion in development research and policy circles. All that has culminated a few weeks ago with the publication of a joint World Bank/ONE Campaign report on the gender gap, which discusses possible policy interventions aimed at eliminating the gender gap: