Financing and Managing Poverty Reduction in Rural Pakistan: A Case of DG Khan and Rajanpur Districts.
Poverty remains an essential global issue in this new century as well, despite the number of global and domestic initiatives undertaken by governments and international agencies. Pakistan, being a developing country, has been facing the realities of poverty, where a number of programmes developed at state and civil society level to respond to poverty
In an attempt to alleviate poverty in the Pakistan, financial resources are provided by microfinance institutions to poor and vulnerable people to engage in income generating activity on soft term and conditions. Zakat Institution and BISP provide free cash to needy and poor as living allowances. ZI, PBM and NGOs provide financing for human capital development through education and training to manage the poverty reduction. These institutions facilitate the poor segment directly to manage the poverty reduction on sustainable basis.
The research presented in this study, hence, aims to explore and evaluate the financial dimensions of managing poverty reduction in rural Pakistan through a micro level study to evaluate the outcome and effectiveness of poverty reduction programmes in Pakistan by focusing on the impact of such programmes in DG Khan and Rajanpur Districts.
In fulfilling the aim of this study, primary data were collected through a questionnaire survey to measure the perceptions of the households, in the form beneficiaries and non beneficiaries, on the outcome and efficiency of the poverty reduction programmes in the DG Khan and Rajanpur.
In terms of analysis, this study used non-parametric (Kruskal Wallis and Mean U Whitney tests) and parametric inferential statistics, such as logit model, to draw the result for research questions.
In terms of findings from the non-parametric test, institution, employment, marital status, working female members, working male members, assets like land, livestock, business assets, savings and loan are significant and ranked at 1 for income related questions. Training, education, gender, age, child dependency and district variables are also significant and causing for poverty but ranking at second number.
In addition, Logit model helped to draw conclusion that beneficiaries and households are statically significant and positively correlated with probability of being poor. It also concluded that education, institution, gender, age, employment, working male member, and working female member as variables are statically significant and negatively correlated with probability of being poor
In Logit regression, as forward conditional method is applied to measure the impact of efficiency of institutions for financing and managing the poverty reduction. The model draws result from the data for ZI that it contributed in working male member and change in income. Working male members are found to be statically significant and negatively correlated with probability of being poor. It was also found that BISP did not contributed in determinant for managing the poverty reduction, while PBM contributed in working male member, which is significant and negatively correlated with probability of being poor. In addition, the findings indicate that MFI contributed in education and change in income, which are negatively correlated with probability of being poor. Furthermore, this study established that NGOs contributed in change in income for managing the poverty reduction.
It is concluded from the analysis that financial capital and human capital development is essential element for financing and managing the poverty reduction in rural Pakistan. But it should be noted that coordination of different poverty reduction program is essential of such an effective strategy. Although it is very difficult task to eliminate the poverty in society due to being multidimensional, yet it can be managed through effective planning and coordination of poverty reduction institution.