Non-Parametric, Unconditional Quantile Estimation of Efficiency in Microfinance Institutions

We apply the non-parametric, unconditional, hyperbolic order-α quantile estimator to appraise the relative efficiency of Microfinance Institutions in Africa in terms of outreach. Our purpose is to verify if these institutions, which must constantly try to strike a compromise between their social role and financial sustainability are operationally efficient. Using data on African MFIs extracted from the Microfinance Information eXchange (MIX) database and covering the 2004 to 2006 periods, we find that more efficient MFIs are also the most profitable. This result is in line with the view that social performance is not in contradiction with the pursuit of excellent financial performance. Our results also show that large MFIs in terms of asset and those charging the highest fees are not necessarily the most efficient.

Authors:

• Komlan Sedzro

Keywords:

• Data envelopment analysis
• microfinance institutions
• quantile estimation of efficiency
• social and financial performance.

References:

[1] J. E. Stiglitz, La grande désillusion. Paris : Fayard, 2002.
[2] M. Robinson, “Addressing some keys questions on finance and
poverty,” Journal of International Development 8: 153-161, 1996.
[3] P. Honohan, “Household financial assets in the process of
development,” World Bank Policy Research Working Paper 3965, 2006.
[4] T. Beck, A. Demirguc-Kunt and M.S. Martinez Peria, “Reaching out:
Access to and use of banking services across countries” Journal of
Financial Economics 85: 234-266, 2007.
[5] M. Schreiner, “Scoring: The next breakthrough in microfinance?”
Occasional Paper, Consultative Group to Assist the Poorest,
Washington, D.C. 2002.
[6] M. Zeller and M. Sharma, “Many borrow, more save, and all insure:
Implication for food and microfinance policy” Food policy 25: 143-167,
2000.
[7] B. A. DeAghion and J. Morduch, The Economics of Microfinance. MIT
Press, 2005.
[8] G. Barboza and H. Barreto, “Learning by Association: Micro Credit in
Chiapas. Contemporary Economic Policy,” Mexico 24: 316-331, 2006.
[9] S. Boyé, J Hajdenberg and C. Poursat, Le guide de la microfinance:
Microcrédit et épargne pour le développement. Edition d'Organisation.
2006.
[10] J. Morduch, “Sibling Rivalry in Africa,” American Economic Review
90: 405-409, 2000.
[11] M. Tucker and G. Miles, “Financial performance of microfinance
institutions: A comparison to performance of regional commercial banks
by geographic region,” Journal of Microfinance 6: 41-54. 2004.
[12] Koveos P and Randhawa D (2004). Financial service for the poor:
assessing microfinance institutions. Managerial Finance 30: 70-95.
[13] A. D. Athanassopoulos and J. A. Ballantine, “Ratio and frontier analysis
for assessing corporate performance: Evidence from the grocery industry
in the UK,” Journal of the Operational Research Society 46: 427-440,
1995.
[14] G. Gregoriou, J. Messier and K. Sedzro “Assessing the relative
efficiency of Credit Union Branches Using Data Envelopment
Analysis,” INFOR 42: 281-297, 2005.
[15] H. Sherman and F. Gold, “Bank branch operating efficiency: evaluation
with data envelopment analysis,” Journal of Banking and Finance 9:
297-315. 1985.
[16] B. Gutiérrez-nieto, C. Serrano-cinca and C. Mar Molinero C, “Social
efficiency in microfinance institutions,” The Journal of the Operational
Research Society 60: 104-119, 2009.
[17] B. Gutiérrez-nieto, C. Serrano-cinca and C. Mar Molinero C,
“Microfinance institutions and efficiency,” OMEGA The International
Journal of Management Science 35: 131-142, 2007.
[18] L. Simar and P. W. Wilson, “A general methodology for bootstrapping
in non-parametric frontier models,” Journal of Applied Statistics 27:
779-802. 2000a.
[19] L. Simar “Detecting outliers in frontier models: A simple approach,”
Journal of Productivity Analysis 20: 391–424, 2003.
[20] D. C. Wheelock and P. W. Wilson, “Non-parametric, unconditional
quantile estimation for efficiency analysis with an application to Federal
Reserve check processing operations,” Journal of Econometrics 145:
209-225.
[21] Wheelock D C and Wilson P W (2009 «Robust nonparametric quantile
estimation of efficiency and productivity change in U.S. commercial
banking, 1985-2004. Journal of Business & Economic Statistics 27: 354-
368.
[22] L. Simar and P. W. Wilson, “Statistical inference in nonparametric
frontier models: The state of the art” Journal of Productivity Analysis
13: 49-78. 2000b.
[23] R. W. Shephard, Theory of Cost and Production Functions, Princeton
University Press. 1970.
[24] R. Färe and S. Grosskopf, New directions: efficiency and productivity,
Springer Verlag 2005.
[25] C. Cazals, J. P. Florens and L. Simar, “Nonparametric frontier
estimation: A robust approach,” Journal of Econometrics 106: 1-25,
2002.
[26] C. Daraio and L. Simar, “Introducing environmental variables in
nonparametric frontier models: A probabilistic approach,” Journal of
Productivity Analysis 24: 93–121, 2005.
[27] P. W. Wilson, “FEAR 1.0: A software package for frontier efficiency
analysis with R,” Socio-Economic Planning Sciences 42: 247-254, 2008.
[28] D. Deprins, L. Simar and H. Tulkens, “Measuring labor inefficiency in
post offices,” In: Marchand M, Pestieau P, Tulkens H ed. The
Performance of Public Enterprises: Concepts and Measurements. North-
Holland, Amsterdam, pp. 243-267, 1984.
[29] M. J. Farrell, “The measurement of productive efficiency,” Journal of
the Royal Statistical Society 120: 253-281, 1957.
[30] A. Charnes, W. W. Cooper and E. Rhodes “Measuring the efficiency of
decision making units,” European Journal of Operational Research 2:
429-444, 1978.
[31] K. Sedzro, M. Keita and T. Assogbavi, “The Impact of the
organizational structure on the performance of microfinance institutions
using data envelopment analysis,” In: Kenneth DL, Gary K (ed)
Applications in multicriteria decision making, data envelopment
analysis, and finance (Applications of Management Science, Volume 14,
Emerald Group Publishing Limited. pp.293-308, 2010.
[32] M. Haq, M. Skully and S. Pathan, “Efficiency of Microfinance
Institutions: A Data Envelopment Analysis,” Asia-Pacific Financial
Markets 17: 63-97, 2010.
[33] United Nations “National Accounts Main Aggregates Database”
http://unstats.un.org.proxy.bibliotheques.uqam.ca:2048/unsd/snaama/dnl
list.asp. Accessed 15 september 2011.
[34] M. Yunus “Creating a world without poverty: social business and the
future of capitalism” PublicAffairs, 2009.
[35] M. Yunus “Building social business: The new kind of capitalism that
serves humanity's most pressing needs. PublicAffairs, 2011.
[36] C. Kao and S. Liu, “Predicting bank performance with financial
forecasts: A case of Taiwan commercial banks,” Journal of Banking and
Finance 28: 2353-2368, 2004.
[37] A. N. Berger and D. B. Humphrey, “Efficiency of financial institutions:
International survey and directions for future research,” European
Journal of Operational research 98: 175-202, 1997.
[38] Q. J. Yeh, “The application of Data Envelopment Analysis in
Conjunction with financial ratios for bank performance evaluation,”
Journal of Operational Research Society 47: 980-988, 1996.
[39] T. F. Siems and R. S. Barr, “Benchmarking the productive efficiency of
U.S. banks,” Financial industry Studies, Federal Reserve Bank of Dallas
98: 11-24, 1998.
[40] R. S. Barr, K. A. Killgo, T. F. Siems and S. Zimmel, “Evaluating the
productive efficiency and performance of U.S. commercial banks,”
Managerial Finance 28: 3-25, 2002.
[41] S. Navajas, M. Schreiner, R. L. Meyer, C. Gonzalez-Vega, and J.
Rodriguez-Meza, “Micro credit and the Poorest of the Poor: Theory and
Evidence from Bolivia,” World Development 28: 333-346, 2000.
[42] R. Cull, A. Demirgüç-Kunt and J. Morduch, “Financial performance and
outreach: A global analysis of leading microbanks,” Economic Journal
117: 107-133, 2007.
[43] A. González, “Defining responsible financial performance:
understanding efficiency,” Microbanking Bulletin (May 2011): 1-5
[44] J. F. Burgess and P. W. Wilson, “Variation in inefficiency among US
hospitals,” Canadian Journal of Operational Research and Information
Processing, INFOR 36: 84-102, 1998.
[45] K. R. Stanton, “Trends in relationship lending and factors affecting
relationship lending efficiency,” Journal of Banking and Finance 26:
127-152, 2002. [46] C. P. Barros, “Measuring performance in defence-sector companies in a
small NATO member country,” Journal of Economic Studies 31: 112-
128, 2004.
[47] C. C. Okeahalam, “Foreign ownership, performance and efficiency in
the banking sector in Uganda and Botswana,” Journal for Studies in
Economics and Econometrics 28: 89-118, 2004.
[48] A. Alfonso and M. S. Aubyn, “Cross-country efficiency of secondary
education provision: A semi-parametric analysis with non-discretionary
inputs,” Economic Modelling 23: 476-91, 2006.
[49] C. P. Barros and A. Assaf, “Bootstrapped efficiency measures of oil
blocks in Angola” Energy Policy 37: 4098-4103, 2009.
[50] C. P. Barros and P. Garcia-del-Barrio, “Productivity drivers and market
dynamics in the Spanish first division football league,” Journal of
Productivity Analysis 35: 5-13, 2011.
[51] L. Simar and P. W. Wilson, “Estimation and inference in two-stage,
semi-parametric models of productions processes,” Journal of
Econometrics 136: 31-64, 2007.
[52] D. Hulme and P. Mosley, Finance Against Poverty, Volumes 1 and 2,
Routledge, London, 1996.
[53] G. Woller and W. Woodworth, “Microcredit: a Grassroots Policy for
International Development,” Policy Studies Journal 29: 267-282, 2001.
[54] B. Haley, and J. Morduch, “Microfinance et réduction de la pauvreté :
quel est le résultat? ” In : Guerin I and Servet J M. Exclusion et Liens
Financiers-Rapport du Centre Walras 2003, Paris : Economica, 2004. pp
549-560.