Does Microfinance Reduce Poverty in Bangladesh? New Evidence from Household Panel Data
The purpose of the present study is to examine whether microfinance reduces poverty in Bangladesh drawing upon the nationally representative household panel data covering 4 rounds from 1997 to 2005. A special attention was drawn to the issue of endogeneity by applying treatment effects model and propensity score matching (PSM) for the participants and non-participants of microfinance programmes. It has been found by treatment effects model applied to panel data that the simple household access to general loans from microfinance institutions (MFIs) did not increase per capita household income significantly, but household access to loans for productive purposes from MFIs significantly increased per capita household income. This suggests that the purpose and monitoring of how clients use the loans is important for increasing household income, and thus decreasing household poverty. However, the application of treatment effects model and PSM to each cross-sectional component of the panel data shows that the poverty reducing effect of MFI on poverty was significantly reduced over the years. This suggests the importance of more attention to the primary purpose of microcredit, that is, poverty reduction, and also to monitoring loan usages in the situations where the profits of MFIs became increasingly squeezed and their activities became more commercialised under severe competitions among MFIs in recent years.
(This abstract was borrowed from another version of this item.)
|Date of creation:||2010|
|Contact details of provider:|| Postal: Manchester M13 9PL|
Phone: (0)161 275 4868
Fax: (0)161 275 4812
Web page: http://www.socialsciences.manchester.ac.uk/subjects/economics/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- A. Smith, Jeffrey & E. Todd, Petra, 2005.
"Does matching overcome LaLonde's critique of nonexperimental estimators?,"
Journal of Econometrics,
Elsevier, vol. 125(1-2), pages 305-353.
- Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20035, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Besley, Timothy & Coate, Stephen, 1995. "Group lending, repayment incentives and social collateral," Journal of Development Economics, Elsevier, vol. 46(1), pages 1-18, February.
- Besley, T. & Coate, S., 1991. "Group Lending, Repayment Incentives And Social Collateral," Papers 152, Princeton, Woodrow Wilson School - Development Studies.
- Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
- Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
- repec:pri:rpdevs:morduch_microfinance_poor is not listed on IDEAS
- Christian Ahlin & RobertM. Townsend, 2007. "Using Repayment Data to Test Across Models of Joint Liability Lending," Economic Journal, Royal Economic Society, vol. 117(517), pages 11-51, 02.
- Christian Ahlin & Robert Townsend, 2002. "Using Repayment Data to Test Across Models of Joint Liability Lending," Vanderbilt University Department of Economics Working Papers 0227, Vanderbilt University Department of Economics.
- Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
- Imai, Katsushi S. & Arun, Thankom & Annim, Samuel Kobina, 2010. "Microfinance and Household Poverty Reduction: New Evidence from India," World Development, Elsevier, vol. 38(12), pages 1760-1774, December.
- Katsushi Imai & Thankom Arun & Samuel Kobina Annim, 2010. "Microfinance and Household Poverty Reduction: New evidence from India," The School of Economics Discussion Paper Series 1008, Economics, The University of Manchester.
- Katsushi S. Imai & Samuel Kobina Annim, 2010. "Microfinance and Household Poverty Reduction: New evidence from India," Discussion Paper Series DP2010-14, Research Institute for Economics & Business Administration, Kobe University.
- David Roodman & Jonathan Morduch, 2014. "The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence," Journal of Development Studies, Taylor & Francis Journals, vol. 50(4), pages 583-604, April.
- David Roodman & Jonathan Morduch, 2009. "The Impact of Microcredit on the Poor in Bangladesh: Revisiting the Evidence," Working Papers 174, Center for Global Development.
- Mark M. Pitt & Shahidur R. Khandker, 1998. "The Impact of Group-Based Credit Programs on Poor Households in Bangladesh: Does the Gender of Participants Matter?," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 958-996, October.
- Shahidur R. Khandker, 2005. "Microfinance and Poverty: Evidence Using Panel Data from Bangladesh," World Bank Economic Review, World Bank Group, vol. 19(2), pages 263-286.
- Khandker, Shahidur R., 2003. "Microfinance and poverty - evidence using panel data from Bangladesh," Policy Research Working Paper Series 2945, The World Bank.
- Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
- Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-161, January.
- Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November. Full references (including those not matched with items on IDEAS)