Differentiated determinants of risk in portfolio at risk of the microfinance institutions in Mexico (2007-2012)

• Roberto Alejandro Ramírez Silva ^[1] ; Salvador Cruz Aké ^[1] ; Francisco Venegas Martínez ^[1]
  1. [1] Instituto Politécnico Nacional

     Instituto Politécnico Nacional

     México

     
• Localización: Contaduría y administración, ISSN 0186-1042, ISSN-e 2448-8410, Vol. 60, Nº. Extra 1, 2015, págs. 175-194
• Idioma: inglés
• DOI: 10.1016/j.cya.2015.08.007
• Títulos paralelos:
  • Determinantes diferenciados de riesgo en la cartera en riesgo de las instituciones microfinancieras en México (2007-2012)
• Enlaces
  • Texto completo (pdf)
• Dialnet Métricas: 1 Cita
• Resumen
  • español

    Esta investigación examina el riesgo de crédito que asumen las Instituciones Microfi-nancieras (IMFs) a través de sus tamaños, márgenes y costos para una muestra de 13 IMFs en México durante el período 2007-2012. También estudiamos los efectos diferenciados de estos factores de riesgo a través del tiempo y entre IMFs utilizando metodologías de regre-sión cuantílica. Se encuentra que la hipótesis de normalidad en el análisis tradicional sesga los resultados cuando las variables estudiadas no son normalmente distribuidas diluyendo el percentil 0.75 (la parte más heterogénea de la muestra). Por último, al utilizar un panel de datos cuantílico con efectos fijos se encuentra que las IMFs sólo tienen en cuenta para la gestión del riesgo de crédito el ingreso que pueden alcanzar.

  • English

    This paper is aimed at examining the credit risk assumed by the Micro Finance Insti-tutions (MFIs) through their sizes, margins and costs for a sample of 13 Mexican MFIs during the 2007-2012 period. We also study the differentiated effects of those risk fac-tors on the MFIs credit risk through time and between MFIs by using quantile regression methodologies. We find that the use of the normality assumption on the traditional panel analysis biases the results when the studied variables are not normal by diluting the 0.75 percentile sample characteristics (the most heterogeneous part of the sample). Finally, by using quantile panel data with fixed effects, we find that for credit risk management the MFIs only consider the income they can attain.

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