Food security and wheat prices in Afghanistan : a distribution-sensitive analysis of household-level impacts / Anna Dandrsquo;Souza, Dean Joliffe.

Abstract

This paper investigates the impact of increases in wheat flour prices on household food security using unique nationally-representative data collected in Afghanistan from 2007 to 2008. It uses a new estimator, the Unconditional Quantile Regression estimator, based on influence functions, to examine the marginal effects of price increases at different locations on the distributions of several food security measures. The estimates reveal that the negative marginal effect of a price increase on food consumption is two and a half times larger for households that can afford to cut the value of food consumption (75 th quantile) than for households at the bottom (25 th quantile) of the food-consumption distribution. Similarly, households with diets high in calories reduce intake substantially, but those at This paper is a product of the Economic Policy and Poverty Sector, South Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at adsouza@ers.usda.gov and djolliffe@worldbank.org. the bottom of the calorie distribution (25 th quantile) make very small changes in intake as a result of the price increases. In contrast, households at the bottom of the dietary diversity distribution make the largest adjustments in the quality of their diets, since such households often live at subsistence levels and cannot make large cuts in caloric intake without suffering serious health consequences. These results provide empirical evidence that when faced with staple-food price increases, food-insecure households sacrifice quality (diversity) in order to protect calories. The large differences in behavioral responses of households that lie at the top and bottom of these distributions suggest that policy analyses relying solely on ordinary least squares estimates may be misleading.