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  • Thumbnail for Microeconometric determinants of poverty movement
    Microeconometric determinants of poverty movement by Polk, Stephen William

    This paper analyzes a large data base containing over 18,000 women micro finance clients of the Negros Women for Tomorrow Foundation (NWTF). The data base contains a powerful new poverty impact assessment tool - the Progress Out of Poverty (PPl) Scorecard. The focus of the data analysis performed in this paper was the observable characteristics of actual borrowers and how those factors influence changes in that client's PPI Scorecard Poverty Score. The conclusion of this paper is that micro finance is working in the fight against poverty in the Philippines (average change in poverty score for the population is 28.51 %) but that a small subset of the population sees dramatically greater results. Specifically, clients that receive larger loans from a successful lending branch and employ their loans in non-agriculture/non-fishing industries see on average much greater gains then the rest of the population. Results of the data analysis suggest that the NWTF employs a suboptimal lending strategy. Sixty-six borrowers received abnormally large loans; average loans size for this subset of the population is $63,780 Filipino pesos. On average, these borrowers saw a 55.86% change in pscore. Regression results upon this population yield insignificant results for initial poverty score and years as a client of the NWTF. Loan size among this population has a positive coefficient similar in size to the larger population regression results. The other 17,937 clients of the NWTF received on average a loan $10,205 pesos and saw a 25.63% change in pscore (both sig. at [alpha] =.0I level). Policy suggestions are given in the concluding chapter.

  • Thumbnail for Lending a hand : a quantile regression analysis of micro-lending's poverty impact
    Lending a hand : a quantile regression analysis of micro-lending's poverty impact by xxxx , Johnson, Daniel K. N. , Polk, Stephen William

    This paper analyzes a database of over 18,000 women micro-finance clients of the Negros Women for Tomorrow Foundation (NWTF), a database using the Progress Out of Poverty (PPI) Scorecard as a measure of poverty. Analysis using both OLS and quantile regression models shows how observable characteristics of borrowers affect the ability of clients to reduce their measured poverty. Loan size, duration, and the economic activity supported all have strongly identifiable effects. Moreover, estimates suggest which among the poor are receiving the greatest effective help by the program. Results offer advice to the NWTF and offer insight useful to policymakers and other micro-lenders.