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That’s the title of a new working paper which my PhD student Lindsey Novak and I have just finished working on this past week, and in which we ask whether smallholder participation in agricultural value chains via contract farming leads to better food security.

In case you are not familiar with contract farming, it is the economic institution wherein a processing firm contracts the production of some agricultural commodity out to a grower (in developing countries, growers are typically smallholder households). In the literature, contract farming agreements are also known as grower-processor contracts, or as outgrower schemes, and because it is halfway between spot markets (i.e., growers selling their output at market after harvest) and vertical integration (i.e., processors growing, transporting, processing, and so on), contract farming has been referred to as a vertical coordination contract (i.e., it allows coordinating the actions of agents upstream and downstream).

There is now a good amount of evidence that participation in contract farming increases the income of smallholders who choose to participate as growers. I myself published an article in World Development in 2012 in which I asked whether participation in contract farming improved welfare via increased incomes.

In this paper, we use the same data I used in my 2012 article to look at a longer causal chain and ask whether participation in contract farming leads to improved food security in the form of shorter hungry seasons (i.e., the length of time a household goes without eating three meals a day). Why wouldn’t increased incomes not necessarily lead to shorter hungry seasons? Because the income from participating in contract farming materializes immediately around harvest time, and the hungry season occurs in the months leading to harvest, i.e., almost one year after harvest. Because it is not always possible to save, and because of self-control problems, it is not immediately obvious that a greater income will improve food security almost a year later.

I spent a few days last week attending the annual meetings of the Agricultural and Applied Economics Association (AAEA) in San Francisco as well as a one-day pre-conference on agricultural value chains in developing countries. At that pre-conference, I happened to be sitting with Ben Wood, who co-manages 3ie’s replication program, and in light of his experience with replication in economics, he suggested I write a post about data cleaning.

Why data cleaning? Because most students will typically have very little experience with that thankless task, which happens because most econometrics classes usually present students with nice, picture-perfect data sets for applied problem sets (and that’s when those classes actually have students estimate stuff instead of just memorizing the properties of various estimators).

A very nice new article titled “The Effect of Food Deserts on the Body Mass Index of Elementary Schoolchildren” by Thomsen et al. in the American Journal of Agricultural Economics, with emphasis added:

Families in low-income neighborhoods sometimes lack access to supermarkets that provide a broad range of healthy foods. We investigate whether these so called “food deserts” play a role in childhood obesity using a statewide panel data set of Arkansas elementary schoolchildren. We use fixed-effects panel data regression models to estimate the average food desert effect. We next compare children who left (entered) food deserts to children who were always (never) in food deserts and homogenize samples for those whose food desert status changed as a result of a change in residence and those whose status changed only as a consequence of the entry or exit of a supermarket. We present evidence that exposure to food deserts is associated with higher z-scores for body mass index. On average, this is in the neighborhood of 0.04 standard deviations. The strongest evidence and largest association is among urban students and especially those that transition into food deserts from non-deserts. Our food desert estimates are similar in magnitude to findings reported in earlier work on diet and lifestyle interventions targeting similarly aged schoolchildren. That said, we are unable to conclude that the estimated food desert effect is causal because many of the transitions into or out of food deserts result from a change in residence, an event that is endogenous to the child’s household. However, there is evidence that food deserts are a risk indicator and that food desert areas may be obesogenic in ways that other low-income neighborhoods are not.

This is the kind of article I really like, and for my money, the AJAE–the flagship journal of my professional association, the Agricultural and Applied Economics Association–is at its best when it offers such topical, policy-relevant contributions.