Category: Uncategorized

I’ve discussed this paper often on this blog (see here, here, here, and here), but here goes one last time: My article on female genital cutting in West Africa with Lindsey Novak and Tara Steinmetz  is now published on the Journal of Development Economics website, and will be published in the November 2015 issue of the journal.

Here is the abstract:

Why does female genital cutting (FGC) persist in certain places but has declined elsewhere? We study the persistence of FGC—proxied for by whether survey respondents are in favor of the practice continuing—in West Africa. We use 38 repeated cross-sectional country-year data sets covering 310,613 women aged 15 to 49 in 13 West African countries for the period 1995–2013. The data exhibit sufficient within-household variation to allow controlling for the unobserved heterogeneity between households, which in turn allows determining how much variation is due to factors at the levels of the individual, household, village, and beyond. Our results show that on average, 87% of the variation in FGC persistence can be attributed to household- and individual-level factors, with contributions from those levels of variation ranging from 71% in Nigeria in 2011 to 93% in Burkina Faso in 2006. Our results also suggest that once invariant factors across women aged 15 to 49 in the same household are accounted for, women who report having undergone FGC in West Africa are on average 16 percentage points more likely to be in favor of the practice.

Once again, here is the key figure from the paper, which shows where support for FGC comes from in West Africa. Note that in most cases, the bulk of support for the practice comes from observed and unobserved factors at the household level which do not vary from one individual to another within the household as well as from individual-level factors, i.e., from levels beyond those of the community:

Simple regression analysis, the method of randomization, and the analysis of big data have been transforming development economics (Banerjee and Duflo 2009; Deaton 2010; Ray 2014; Varian 2014). This is truly welcome and has the potential to leave its mark on human well-being, growth, and development.

There is a risk, however, that this euphoria will once again have us carried away. We are seeing, especially in policy circles, these new empirical findings being quickly waved in front of our noses and treated as ground for doing whatever the policy maker wants to do. What is important to realize is that when we say that policy should be evidence-based, both words are important—“evidence” and “based.”We must not fall into the trap of evidence-waved policy. To see this mistake, consider the commonly heard policy refrain: “Recent data show 90% of jobs were created by the private sector. Therefore, we have to rely on the private sector for creating jobs.” The “therefore” is wrong. If it were not wrong, we would also have to go along with the Soviet economist who having studied Russian data in the 1980 s wrote: “Recent data show 90% of all jobs were created by the state. Therefore, we have to rely on the state for creating jobs.”

This is why we need the discipline of deductive reasoning, economic theory, and also common sense.

That is from Kaushik Basu and Andrew Foster–respectively, chief economist at the World Bank and editor of the World Bank Economic Review (WBER)–in an article titled “Development Economics and Method,” which serves as an introduction of sorts to a special issue of the WBER summarizing this year’s Annual Bank Conference on Development Economics.

I have been saying for a few years now that the pendulum will swing back, that theory will make a comeback in development economics in order to help understand the mechanisms whereby the effects observed in randomized controlled trials occur. It looks like the pendulum is on its way back.

(January 16, 2016 Update: If you came here from the New York Times website, thank you for your visit, and please note that the findings discussed below have changed slightly due to our incorporating two more years of data since this was posted last summer. Our new findings will be presented and discussed in an updated version of the working paper discussed in this post, which I am hoping to release before the end of March 2016. In the meantime, some of those new findings are discussed in the New York Times article.)

When I arrived at the University of Minnesota in the fall of 2013, a few colleagues and I applied for a seed grant from the university’s Healthy Foods, Healthy Lives Institute by submitting a proposal to look at the impact of local and organic foods and food safety.

After working on it for almost two years, I am happy to finally be able to circulate my new paper titled “Farmers Markets and Food-Borne Illness,” coauthored with my colleague Rob King and my student Jenny Nguyen, in which we ask whether farmers markets are associated with food-borne illness in a systematic way. In order to answer that question, we use a US state-level panel data set for the years 2004, 2006, and 2008-2011 (i.e., the years for which we had a full data set).

Here is the abstract:

We study the relationship between farmers markets and food-borne illness in the United States. Using a state-level panel data set for the period 2004-2011, we find a positive relationship between the number of farmers markets per capita on the one hand and, on the other hand, the number of reported (i) outbreaks of food-borne illness, (ii) cases of food-borne illness, (iii) outbreaks of Campylobacter jejuni, and (iv) cases of Campylobacter jejuni. Our estimates indicate that a 1% increase in the number of farmers markets is associated with a 0.7% (3.9%) increase in the total number of reported outbreaks of food-borne illness (Campylobacter jejuni), and a 3.9% (2.1%) increase in the total number of reported cases of food-borne illness (Campylobacter jejuni) in the average state-year. Our estimates also suggest that a doubling of the number of farmers markets in the average state-year would be associated with an economic cost of over $900,000 in additional cases of food-borne illness. When controlling simultaneously for both the number of farmers markets and the number of farmers markets that accept SNAP benefits (i.e., food stamps), we find that they are respectively associated positively and negatively with reported food-borne illness outbreaks and cases. Our results are robust to different specifications and estimators, and falsification and placebo tests indicate that they are unlikely to be spurious.