Vulnerability to Food Insecurity of Rural Households in Pakistan: An Empirical Evidence from Climate Change Impact Survey

Abstract

The study primarily focused on dynamic and forward-looking food vulnerability model to estimate the impact of uncertain climate change and risks on vulnerability to food insecurity of rural farm households. The study is based on secondary data from Climate Change Impact Survey [CCIS (2013)], conducted by PIDE university. The vulnerability model to food insecurity takes into account ex-ante risk of a household that its food consumption may fall below the food poverty line in near future. This allows to differentiate between chronic and transient food poor households using cross sectional data. The study employs two-stage least square technique (instrumental variable estimator) to measure the impact of climate change on food security status of household measured as per capita kilo calorie food intake adult equivalent. The expected food consumption and its variance is then used to measure household vulnerability to food insecurity. The empirical findings of the data suggest that changes in temperature and rainfall significantly impact value of agricultural production measure as farm income which them affects household’s food consumption. It has been found that 10 percent increase in farm income will result in almost 1 percent increase in per capita food consumption. In terms of household vulnerability, it has been found that almost 20 percent of the sample households are chronically poor while almost 40 percent of the households are temporary food insecure i.e. they may get out of food poverty status without any external assistance. On the other hand, 16 percent of the households are found to be transient food secure i.e. they are currently food secure but likely to fall into food poverty in near future if no external assistance would be provided. Similarly, almost 25 percent of the households are permanently food secure. Such classification of households is important from policy point of view to improve allocation of resources to target population and to avoid errors of inclusion or exclusion during food policy intervention.