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Poverty Targeting and Impact of a Governmental Micro-credit Program in Vietnam

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  • Nguyen Viet Cuong
  • Minh Thu Pham
  • Nguyet Pham Minh
  • Vu Thieu
  • Duong Toan

Abstract

It is argued that without collateral the poor often face binding borrowing constraints in the formal credit market. This justifies a micro-credit program, which is operated by the Vietnam Bank for Social Policies to provide the poor with preferential credit. This paper examines poverty targeting and impact of the micro-credit program. It is found that the program is not very pro-poor in terms of targeting. Among the participants, the non-poor account for a larger proportion of loans. The non-poor also tend to receive larger amounts of credit compared to the poor. However, the program has positive impact on poverty reduction of the participants. This positive impact is found for all the three Foster-Greer-Thorbecke poverty measures.

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Bibliographic Info

Paper provided by PEP-PMMA in its series Working Papers PMMA with number 2007-29.

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Date of creation: 2007
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Handle: RePEc:lvl:pmmacr:2007-29

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Related research

Keywords: Micro-credit; poverty; poverty targeting; impact evaluation; instrumental variables; fixed-effect model;

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References

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  1. Hentschel, Jesko, et al, 2000. "Combining Census and Survey Data to Trace the Spatial Dimensions of Poverty: A Case Study of Ecuador," World Bank Economic Review, World Bank Group, vol. 14(1), pages 147-65, January.
  2. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Working Papers 11259, National Bureau of Economic Research, Inc.
  3. Coleman, Brett E., 1999. "The impact of group lending in Northeast Thailand," Journal of Development Economics, Elsevier, vol. 60(1), pages 105-141, October.
  4. Jonathan Conning & Christopher Udry, 2005. "Rural Financial Markets in Developing Countries," Working Papers 914, Economic Growth Center, Yale University.
  5. Khandker, Shahidur R. & Faruqee, Rashidur R., 2001. "The impact of farm credit in Pakistan," Policy Research Working Paper Series 2653, The World Bank.
  6. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  7. Alastair Hall & Fernanda P. M. Peixe, 2000. "A Consistent Method for the Selection of Relevant Instruments," Econometric Society World Congress 2000 Contributed Papers 0790, Econometric Society.
  8. 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.
  9. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April.
  10. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
  11. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
  12. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
  13. Diagne, Aliou & Zeller, Manfred, 2001. "Access to credit and its impact on welfare in Malawi:," Research reports 116, International Food Policy Research Institute (IFPRI).
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Cited by:
  1. Li, Xia & Gan, Christopher & Hu, Baiding, 2011. "The welfare impact of microcredit on rural households in China," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(4), pages 404-411, August.

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