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IMPACT OF SOCIAL SAFETY NETS ON POVERTY REDUCTION A CASE STUDY OF SINDH PROVINCE - PAKISTAN

Journal: International Journal of Management (IJM) (Vol.11, No. 11)

Publication Date:

Authors : ;

Page : 1073-1088

Keywords : Social Safety Nets; Poverty; Probit model.;

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Abstract

Government intervention in form of social protection towards poverty reduction has remained in question around the world. Studying the impact of these initiatives has become very critical in order to understand the effectiveness of these interventions. This will provide answers to some of the questions that social safety net programs have been properly designed or whether it is targeting the vulnerable and poorest of the households. The objective of the study is to assess the impact of Social safety nets on the poverty alleviation and wellbeing of households. This study uses cross sectional data of PSLM 2014-15 for the empirical analysis. Poverty is considered as dependent variable whereas, provision of social safety net, literacy, employment, family size, non-agricultural income and agricultural income are used as explanatory variables. Other control variables include gender, age, marital status, rural-urban and district dummies. The empirical analysis is presented in two steps; Descriptive and Inferential analysis. Descriptive analysis includes, frequency tables, cross tabs, bar charts and pie charts by computing mean and median of continuous variables and dichotomous variables. Since the dependent variable is binary, the Probit model has been employed to study its relationship with explanatory variables. The results suggest that higher is the provision of social safety nets, lower will be the probability of being poor. The estimates suggest that one unit increase in social safety nets will reduce the predicted probability of poverty by 0.2 units if all other variables remain constant at their respective mean. The results are consistent with the international studies of social safety nets by Heltberg and Niels (2009), Honoratietal. (2015), Coudouel and Dickinson (2014), Monchuk (2013), Kjellgren et al. (2014), Silvaetal. (2016), World Bank (2017)

Last modified: 2021-02-24 22:19:14