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The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence

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  • David Roodman
  • Jonathan Morduch

Abstract

The most-noted studies on the impact of microcredit on households are based on a survey fielded in Bangladesh in the 1990s. Contradictions among them have produced lasting controversy and confusion. Pitt and Khandker (PK, 1998) apply a quasi-experimental design to 1991–92 data; they conclude that microcredit raises household consumption, especially when lent to women. Khandker (2005) applies panel methods using a 1999 resurvey; he concurs and extrapolates to conclude that microcredit helps the extremely poor even more than the moderately poor. But using simpler estimators than PK, Morduch (1999) finds no impact on the level of consumption in the 1991–92 data, even as he questions PK’s identifying assumptions. He does find evidence that microcredit reduces consumption volatility. Partly because of the sophistication of PK’s Maximum Likelihood estimator, the conflicting results were never directly confronted and reconciled. We end the impasse. A replication exercise shows that all these studies’ evidence for impact is weak. As for PK’s headline results, we obtain opposite signs. But we do not conclude that lending to women does harm. Rather, all three studies appear to fail in expunging endogeneity. We conclude that for non-experimental methods to retain a place in the program evaluator’s portfolio, the quality of the claimed natural experiments must be high and demonstrated.

Suggested Citation

  • David Roodman & Jonathan Morduch, 2009. "The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence," Working Papers 174, Center for Global Development.
  • Handle: RePEc:cgd:wpaper:174
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    File URL: http://www.cgdev.org/content/publications/detail/1422302
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    References listed on IDEAS

    as
    1. Phillips, Peter C.B., 2006. "A Remark On Bimodality And Weak Instrumentation In Structural Equation Estimation," Econometric Theory, Cambridge University Press, vol. 22(05), pages 947-960, October.
    2. Orazio Attanasio & Britta Augsburg & Ralph De Haas & Emla Fitzsimons & Heike Harmgart, 2011. "Group lending or individual lending? Evidence from a randomised field experiment in Mongolia," IFS Working Papers W11/20, Institute for Fiscal Studies.
    3. Angelucci, Manuela & Karlan, Dean & Zinman, Jonathan, 2013. "Win Some Lose Some? Evidence from a Randomized Microcredit Program Placement Experiment by Compartamos Banco," Working Papers 117, Yale University, Department of Economics.
    4. Manuela Angelucci, Dean Karlan, Jonathan Zinman, 2013. "Win Some Lose Some? Evidence from a Randomized Microcredit Program Placement Experiment by Compartamos Banco-Working Paper 330," Working Papers 330, Center for Global Development.
    5. Abhijit Banerjee & Esther Duflo & Rachel Glennerster & Cynthia Kinnan, 2015. "The Miracle of Microfinance? Evidence from a Randomized Evaluation," American Economic Journal: Applied Economics, American Economic Association, vol. 7(1), pages 22-53, January.
    6. repec:pri:rpdevs:morduch_microfinance_poor is not listed on IDEAS
    7. Jonathan Morduch, 1998. "Does Microfinance Really Help the Poor? New Evidence from Flagship Programs in Bangladesh," Working Papers 198, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
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    More about this item

    Keywords

    microcredit; impact evaluation; Grameen Bank; Bangladesh; replication; mixed-process models;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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