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Marc F. Bellemare Posts

Incentive and Crowding Out Effects of Food Assistance

That’s the title of a new working paper by Munshi Sulaiman, a student at the the London School of Economics, who runs a randomized controlled trial to evaluate the impacts of food assistance in a post-conflict area:

“Food assistance is one of the most common forms of safety net programs in postconflict situations. Besides the humanitarian and promotional roles, there are widespread scepticisms of food assistance regarding its possible influence on disincentive to work and on crowding out of private transfers. While there is a relatively large amount of empirical research on social protection in stable context, it is less researched in post-conflict situations. Based on randomized evaluation of a food-for-training program implemented in Southern Sudan, this paper estimates these effects. We observe a significant negative impact (about 13 per cent) on per capita household income. However, there is no effect on the hours of work or the type of the economic activities of the adult members. The decline in income mostly happened through a reduction in child labor. There is also a positive effect on school enrolment for girls (about 10 percentage points) and an improvement in their housing status. We also do not find any indication of crowding out of private transfers for the participants. This is most likely due to the extent of private transfers being very low to begin with. However, there is a small but significant impact of the transfers given out by the participants.”

In other words, on the positive front, food assistance increases the likelihood that girls within the household are enrolled in school, it increases the quality of the household’s dwelling, it does not reduce the private transfers received by the households, as has often been posited, and it increases the transfers made by the household to others.

On the negative front, food assistance does cause a decrease in household income, but it does so through a reduction in child labor so that depending on your preferences, you may interpret this as good news.

(HT: RepEc’s NEP-DEV listserv.)

Methodological Convergence in the Social Sciences

In a post over at orgtheory.net, Fabio Rojas makes the case for more math in sociology:

“By ‘math’ I mean models and proofs, not statistics. That’s an important distinction. Statistics is using math to test hypotheses (verbal or otherwise) with quantitative data. Math is used to express statistical ideas and prove things about them. However, math can also be used to express sociological ideas and derive ideas through logical proof. By ‘math in sociology,’ I mean ‘writing down equations describing social processes (the models) and proving new things about the models.'”

Fabio then goes on to give six reasons why he thinks sociology needs more mathematical theoretical models.

I fully agree with his assessment and, for me, this is part of the methodological convergence that is currently taking place in the social sciences. Let me explain.