Evaluating the Impact of Microfinance on Savings and Income in Sri Lanka:Quasi-experimental Approach Using Propensity Score Matching

Abstract

The study applied recent advances in propensity score matching methods to assess the impact of microfinance on household income and savings. Results suggest that overall programme participants’ benefit incidence is indeed pro-poor. With respect to both household per capita income and savings, programme participation definitely has a positive impact for all low-income households. Consequently, this article’s findings have several important policy implications. The large positive impact of participating in microfinance programmes on household income and savings suggest that microfinance programmes may improve household status in terms of wealth. The regressive effect on household per capita income suggests that poorer households do not feel as much the effects of the intervention compared to richer households. The policy implication of this regressive effect might be that for the poorest programme participants, the availability of programme loans and savings schemes may be not sufficient to become highly productive in income-generating activities. The finding of participation in microfinance programmes not being highly effective in terms of savings for richer households highlights the importance of a robust and accurate targeting mechanism for the microfinance programme in Sri Lanka. Against the backdrop of these findings, policy planners and microfinance practitioners could re-examine the targeting approach of microfinance in Sri Lanka. Finally, the principal message that emerges from the study is: there are quantitatively non-negligible, average gains from microfinance on household savings and income, especially for the poor.

JEL Classification: O16, C14, C21, G21

Keywords

Microfinance Propensity Score Matching Quasi-experimental Treatment Effects Sri Lanka

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References

Bryson

Dorsett

Purdon

(2002). The use of propensity score matching in evaluation of labour market policies. Working paper No. 4, Department for Work and Pensions.

Coleman

(1999). The impact of group lending in northeast Thailand. Journal of Development Economics, 60, 105–41.

Coleman

(2002). Microfinance in Northeast Thailand: Who benefits and how much? Asian Development Bank, Economics and Research Department Working paper No. 9, April.

Consultative Group to Assist the Poor (CGAP). (2006). Sri Lanka CLEAR Review. Washington, DC: CGAP.

Dawid

A.P.

(1979). Conditional independence in statistical theory (with discussion). Journal of the Royal Statistical Society. B, 41(1), 1–31.

Dehejia

Wahba

(2002). Propensity score matching methods for non-experimental casual studies. The Review of Economics and Statistics, 84(1), 151–61.

De Mel

McKenzie

Woodruff

(2007). Who does microfinance fail to reach? Experimental evidence on gender and microenterprise returns. Washington, DC: World Bank.

Goldberger

(1983). Abnormal selection bias. In Amemiya

Olkin

(Eds), Studies in econometrics, time series and multivariate statistics. San Diego, London, and Toronto: Academic Press.

Goldberge

(2005). Measuring the impact of microfinance: Taking stock of what we know. Grameen foundation, USA Publication Series.

10.

GTZ-ProMiS. (2010). Impact assessment of microfinance in Sri Lanka.

11.

GTZ-ProMiS. (2010). Microfinance industry report Sri Lanka.

12.

Gunatilaka

De Silva

(2010). Microfinance and women’s empowerment. Colombo: Center for Women’s Research.

13.

Heckman

J.J.

Ichimura

Todd

P.E.

(1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. Review of Economic Studies, 64, 605–54.

14.

Heckman

J.J.

Ichimura

Todd

P.E.

(1998). Matching as an econometric evaluation estimator. Review of Economic Studies, 65, 261–94.

15.

Hossain

(1988). Credit for the alleviation of rural poverty: The Grameen Bank in Bangladesh. IFPRI, Research Report No. 65, Washington, DC.

16.

Hulme

(2000). Impact assessment methodologies for microfinance: Theory, experience and better practice. World Development, 28(1), 79–98.

17.

Khandker

(2005). Microfinance and poverty: Evidence using panel data from Bangladesh. World Bank Economic Review,19(2), 263–86.

18.

Microfinance Information Exchange (MIX). (2009). Asia microfinance analysis and bench-marking report 2008, Washington DC, USA: Microfinance Information Exchange, Inc. Available at http://www.themix.org/publications/mix-microfinance-world/2009/03/2008-asia-microfinance-analysis-and-benchmarking-report.

19.

Pitt

Khandker

(1998). The impact of group-based credit programmes on poor households in Bangladesh: Does the gender of participants matter? Journal of Political Economy, 106(5), 958–96.

20.

Puhani

(2000). The Heckman correction for sample selection and its critique—A short survey. Journal of Economic Surveys, 14, 53–68.

21.

Rosenbaum

P.R.

Rubin

D.B.

(1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.

22.

Rosenbaum

P.R.

Rubin

D.B.

(1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Biometrica, 70, 41–50.

23.

Rubin

Thomas

(1996). Matching using estimated propensity score: Relating theory to practice. Biometrics, 52, 249–64.

24.

Tilakaratna

Wickramasinghe

Kumara

(2005). Microfinance in Sri Lanka: A household-level analysis of outreach and impact on poverty. Colombo: Institute of Policy Studies.

25.

World Bank. (1990). The World Bank Annual Report 1990. Washington, DC: The World Bank.

26.

World Bank. (1996). A worldwide inventory of microfinance institutions, sustainable banking with the poor. July, Washington, DC: World Bank.

27.

World Bank. (1997). Introducing savings in microcredit institutions: When and how? Consultative Group to Assist the Poorest, CGAP Note No. 8, April, Washington, DC.

28.

World Bank. (1998). Public expenditures for poverty alleviation in northeast Brazil: Promoting growth and improving services. World Bank LAC Report.

29.

Zeller

Meyer

(2002). The triangle of microfinance: Financial sustainability, outreach and impact. Baltimore: John Hopkins for the International Food Policy Research Institute.