The Impact of Productive Safety Net Program on the Household Food Security: The Case of Kutaber District

The Ethiopian government launched a new social protection program called the Productive Safety Net Program since Poverty and chronic food insecurity have been the main challenges for most of the rural households of the country. The major objective of this study was to examine the impact of PSNP on household food security. The study was conducted in Kutaber district, Amhara National regional state, Ethiopia. A Multistage stage sampling procedure was used to randomly select 116 representative household heads. Both the primary and secondary data were analyzed using descriptive statistics and econometric tools. The propensity score matching (PSM) technique of impact evaluation preferred to overcome the counterfactual problem and selection bias. Participation model result of Estimated Propensity Score showed that among 11 explanatory variables included in the logistic model, 4 of them were significant. The result indicated that the program participation of the households in the area significantly influenced by farmland size, an income of off/non-farm activities, distance to the nearest market center and distance to the nearest agricultural extension office. The program intervention has resulted in a positive and statically significant mean difference between the two groups in terms of the outcomes variables of daily calorie intake and farm and household material. Applying a propensity score matching technique for the study found that the program has increased participating households’ calorie intake and household material by 233.04 calories and 2551.65 ETB, respectively compared to that of non-participating households. The analysis result revealed that the food security of the household has been improved by productive safety net program intervention in the study area. The multiple linear regression model estimated results revealed that the impact of the program on calorie intake was not uniform across the participating households. Therefore, the program should consider the roles of significant variables in the selection of participant households for the desired impact under related locations.