How disaggregated should information be for a sound food security policy?

This study aimed to answer the question whether disaggregating micro data on food security conditions yielded sufficient new information to improve food security policies. To answer this question, we proposed and implemented a conceptual model that comprised three successive levels of disaggregation. The model was implemented for the Punjab province of Pakistan for which primary data was collected from 1,152 rural households. To measure the food security status of households, the Dietary Intake Assessment (DIA) method was used. Furthermore, the determinants of food security were identified using a Logit Regression model. Comparing the results of this model suggested that disaggregation yields sufficient new information to warrant the extra effort. We found that food security of different household categories and micro-regions were statistically different from each other; moreover, household categories differed in their food security status even within regions. Basing potential policies on analysis of too aggregated data a level can lead to biased conclusions. An implication is that a blanket policy for ensuring rural household food security, as currently implemented in Pakistan, is not an efficient approach.