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Demasking the impact of microfinance

  • Helke Waelde

    ()

    (KfW Entwicklungsbank, Frankfurt am Main, Germany)

We reconsider data from a randomized control trial study in India. The data reveal the impact of a microloan program. We extend the often used randomized impact evaluation and di¤erence-in-di¤erence approach by quantile regression and the consideration of the quantile treatment effects. The use of additional, more advanced, evaluation methods allows a more detailed consideration of borrowers at the lower and at the upper end of the wealth distribution. We find a strong negative and signi.cant time-trend. Furthermore, we observe a negative impact of the provi- sion of microfinance loans such that the overall impact is even more negative. This is particularly well seen for entrepreneurs in the lower and in the higher quantiles. As we learn that poor entrepreneurs use microloans for consumption, we doubt that micro.nance is the right instrument for them. The data suggest that providing microloans for average entrepreneurs, who can hire very poor entrepreneurs, might be an effective solution for that dilemma.

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File URL: http://www.macro.economics.uni-mainz.de/RePEc/pdf/Discussion_Paper_1115.pdf
File Function: First version, 2011
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Paper provided by Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz in its series Working Papers with number 1115.

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Length: 33 pages
Date of creation: 09 Nov 2011
Date of revision: 09 Nov 2011
Handle: RePEc:jgu:wpaper:1115
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  1. Hilary W. Hoynes & Marianne P Bitler & Jonah B. Gelbach, 2005. "Distributional Impacts of the Self-Sufficiency Project," Working Papers 530, University of California, Davis, Department of Economics.
  2. Markus Frölich & Blaise Melly, 2013. "Unconditional Quantile Treatment Effects Under Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 346-357, July.
  3. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, 01.
  4. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, 2010. "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693.
  5. Shahidur R. Khandker & Zaid Bakht & Gayatri B. Koolwal, 2009. "The Poverty Impact of Rural Roads: Evidence from Bangladesh," Economic Development and Cultural Change, University of Chicago Press, vol. 57(4), pages 685-722, 07.
  6. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2007. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program," NBER Working Papers 12831, National Bureau of Economic Research, Inc.
  7. Abrevaya, Jason & Dahl, Christian M, 2008. "The Effects of Birth Inputs on Birthweight," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 379-397.
  8. Ghatak, Maitreesh, 1999. "Group lending, local information and peer selection," Journal of Development Economics, Elsevier, vol. 60(1), pages 27-50, October.
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