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Demasking the impact of microfinance

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  • Helke Waelde

    () (KfW Entwicklungsbank, Frankfurt am Main, Germany)

Abstract

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.

Suggested Citation

  • Helke Waelde, 2011. "Demasking the impact of microfinance," Working Papers 1115, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 09 Nov 2011.
  • Handle: RePEc:jgu:wpaper:1115
    as

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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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    References listed on IDEAS

    as
    1. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    2. Ghatak, Maitreesh, 1999. "Group lending, local information and peer selection," Journal of Development Economics, Elsevier, vol. 60(1), pages 27-50, October.
    3. 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.
    4. 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.
    5. Bitler, Marianne P. & Gelbach, Jonah B. & Hoynes, Hilary W., 2008. "Distributional impacts of the Self-Sufficiency Project," Journal of Public Economics, Elsevier, vol. 92(3-4), pages 748-765, April.
    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 Technical Working Papers 0335, National Bureau of Economic Research, Inc.
    7. 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, July.
    8. Cameron,A. Colin & Trivedi,Pravin K., 2008. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9787111235767, March.
    9. 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.
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    More about this item

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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