Social Efficiency in Peruvian Microfinance Institutions: a Semi-Parameter Approach
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2013
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Pontificia Universidad Católica del Perú. Departamento de Economía
Abstract
Este estudio tiene como objetivo evaluar la eficiencia social de las instituciones microfinancieras (IMF) peruanas —reguladas y no reguladas—. La eficiencia social está referida a la capacidad de las IMF de producir más output social (cantidad de clientes pobres atendidos) sin emplear más recursos productivos. La metodología del Análisis de la Envolvente de Datos (DEA) es empleada para llevar acabo el análisis de eficiencia. Adicionalmente, se analizan los potenciales determinantes de la eficiencia social de las IMF a través de un análisis de regresión Tobit en el contexto de datos de panel, a fin de indagar si las diferencias relacionadas a la naturaleza institucional de los operadores microfinancieros explican las diferencias en la eficiencia social alcanzada por ellos. El periodo de estudio cubre los años del 2007 al 2011. Los resultados muestran que las IMF no reguladas conforman en su mayoría el segmento de instituciones socialmente más eficientes. Por el contrario, aquellas IMF que se encuentran dentro del esquema regulatorio muestran, en la mayoría de los casos, posiciones lejanas a la frontera de eficiencia. Del análisis de regresión se desprende que el ser una IMF regulada afecta negativa y significativamente los niveles de eficiencia social mientras una mayor presencia en el medio rural afectaría positivamente los niveles de eficiencia social. Aun cuando, existe evidencia de que la rentabilidad financiera podría relacionarse positivamente con la eficiencia social; este resultado no parecería ser tan robusto y exigiría una investigación adicional centrada específicamente en el tema. En el otro extremo, la tecnología crediticia parecería no ser relevante para explicar la eficiencia social de las IMF.
This study aims to assess the social efficiency of microfinance institutions (MFIs) —regulated and non-regulated— in Peru. Social efficiency is referred to the capacity of MFIs to produce more social outputs —number of poor clients and women served— without using more resources. The Data Envelopment Analysis methodology is used to carry on efficiency analysis. Additionally, we analyze the potential determinants of social efficiency of MFIs through a Tobit regression analysis in the context of panel data, in order to investigate whether differences related to the institutional nature of MFIs explain differences in social efficiency achieved by them. The study period covers the years from 2007 to 2011. The results show that non-regulated MFIs are socially more efficient. On the contrary, those MFIs which are within regulatory scheme, shown in most cases, distant positions to the efficient frontier. Regression analysis shows that being a regulated MFI negatively affects social efficiency levels, a greater presence in rural area positively affect social efficiency levels. Although there is evidence that financial returns could relate positively to social efficiency, this result does not seem to be as robust. At the other extreme, the lending technology does not seem to be relevant to explain social efficiency.
This study aims to assess the social efficiency of microfinance institutions (MFIs) —regulated and non-regulated— in Peru. Social efficiency is referred to the capacity of MFIs to produce more social outputs —number of poor clients and women served— without using more resources. The Data Envelopment Analysis methodology is used to carry on efficiency analysis. Additionally, we analyze the potential determinants of social efficiency of MFIs through a Tobit regression analysis in the context of panel data, in order to investigate whether differences related to the institutional nature of MFIs explain differences in social efficiency achieved by them. The study period covers the years from 2007 to 2011. The results show that non-regulated MFIs are socially more efficient. On the contrary, those MFIs which are within regulatory scheme, shown in most cases, distant positions to the efficient frontier. Regression analysis shows that being a regulated MFI negatively affects social efficiency levels, a greater presence in rural area positively affect social efficiency levels. Although there is evidence that financial returns could relate positively to social efficiency, this result does not seem to be as robust. At the other extreme, the lending technology does not seem to be relevant to explain social efficiency.
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Microfinanzas, Eficiencia social, Análisis de la envolvente de datos
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