Abstract:
The main objective of this study was to assess the impact of productive safety net program (PSNP) on household asset accumulation in wera woreda, Halaba zone, south Ethiopia. Both primary and secondary data were used for this study. The primary data were collected through structured questionnaire from 134 PSNP and 126 non PSNP participant sample households of the study area. Propensity score matching (PSM) was used to assess the impact of PSNP on asset accumulation.
The estimated coefficient results indicate that participation in the PSNP was significantly influenced by five explanatory variables. Family size, frequency of development agents (DA) and number of months that the household encountered food security problem prior to the intervention of PSNP were found to have positive and significant influence on participation in PSNP at 10%, 5% and 5% level of significances, respectively. On the other hand, sex of the household head and education of family member were found to have negative and significant effect on the program participation at 5% and 1% level of significances, respectively. As PSM was applied to assess the impact of the program on outcome variables (asset accumulation) for the PSNP participant households, nearest neighbor matching (NN) of neighborhood 4 was selected as best matching algorithm which hold large matched sample size and low Pseudo R2. After matching only 254 matched respondents (132 from participants and 122 from non- participants) were used to come up with the final decision. The ATT estimation result was indicating that participation in PSNP did not lead to strong and significant effect on individual's household's asset accumulations. Therefore. re-thinking or re-evaluating the program objectives at national, regional, and other operational levels is inevitable to actualize desired objectives. It can be recommended that policy makers should be careful in designing and implementing huge social programs such as PSNP in the way that it contributes in asset accumulation of PSNP participant households and improving practices besides household demographic background, socio-economic and institutional factors to bring a positive effect in the study area.
