CONTRACT DESIGN STRATEGIES FOR GROUP LOANS LIMITING LATE REPAYMENT IN MICROFINANCE INSTITUTIONS (MFIS)

Author: Ntieche Adamou

ABSTRACT

The objective of this paper is to show how the components of a debt contract optimize the loan repayment terms of borrowers (BEPs) at MFIs. The results of the bivariate probit model censored from a database of 321 group loan contracts granted over a period from 2007 to 2014 in the different second-tier MFIs show a pre-default of borrowers characterized by late repayment behaviour and/or penalty payments. Our model successfully predicts being a pre-default borrower by 70.75%, while being a non-pre-default borrower will be successfully predicted by 69.54%. The results also show that the model correctly classifies 70.09% of the sample observations. Our results show that the sector of activity, the nature of the project and the presence of other MFIs in the area have a significant effect on reducing the risk of pre-default. Similarly, we note that the interest rates applied to group loans and loan rationing significantly increase the potential for group default.

Keywords: Group loan; Contract; Late repayment; MFI

BIBLIOGRAPHIC REFERENCES 

  • Armendariz de Aghion B., Gollier C., 1997, “Peer group formation in an adverse selection model.”, University College, Department of Economics, London.
  • Armendariz de Aghion B., Morduch J., 2005, “The Economics of Microfinance”, MIT Press, p. 346.
  • Ash, D., Meester, S., 2002, “Best Practicing in Reject Inferencing on Credit Risk Modeling and Decisioning”,in Conference Presentation. Available from Internet: <http://fic.wharton.upenn.edu/fic/ash.pdf>.
  • Boyes William J. D,. ; Hoffman L,. Stuart A.Low., 1989, “An econometric analysis of the bank credit scoring problem”, Journal of Econometrics Vol. 40, Issue 1, pp. 3-14.
  • Crook, J Banasik J., 2004, “Does reject inference really improve the performance of application scoring models? “Journal of Banking & Finance, – Elsevier.
  • Diamond D. W. , 1996, “Financial intermediation as delegated monitoring: a simple example”, Economic Quaterly, vol. 82/3, pp. 51-65.
  • Ghatak M., 2000, “Screening by the company you keep: Joint liability lending and the peer selection effect”, The Economic Journal, 110 , pp. 601-631
  • Godquin. M.,2004, “Microfinance Repayment Performance in Bangladesh: How to Improve the group lending”, Economic of Transition, vol. 8, Issue 2, pp. 401-420
  • Heckman James J, 1978, “Dummy Endogenous Variables in a Simultaneous Equation System”, Econometrica ,Vol. 46, No. 4, pp. 931-959
  • Holmstrom B., 1979, “Moral hazard and observability”, The Bell Journal of Economics, vol. 10 Issue 1, pp. 74-91.
  • Holmstrom, B., Tirole. J, 2000, “Liquidity and Risk Management”, Journal of Money, Credit and Banking, 32 (3): pp. 295-319.
  • Jensen M.C. and Meckling W.H. 1976, “Theory of The Firm: Managerial Behavior, Agency Costs and Ownership Structure”, Journal of Financial Economics, vol.3, pp. 305-360.
  • Karlan, D., 2007, “Social connections and group banking”, Economic Journal, vol. 117, pp. 52
  • Laffont J.-J., Guessan T N. 2000, “Group lending with adverse selection”, European Economic Review, vol. 44, pp. 773-784.
  • Le Saout, E., & Daher, L. , 2016, “The efficiency of listed microfinance Institutions Computational” Economics and Finance, Paris.
  • Ledgerwood J. and White V., 2006, “Transforming Microfiannce Institutions”, Washnigton, The World Bank and The Microfinance Network.
  • Lelart M., 2007, “les mutations dans la microfinance: l’expérience du Benin”, Doc de recherches 15, LEO, Université d’Orleans.
  • Mayoukou C., 2000, “La microfinance en Afrique Centrale: état des lieux et perspectives de développement”, Techniques financières et développement, n°59-60.
  • Modigliani F., Miller M. (1963), “Corporate Income Taxes and the Cost of Capital: A Correction”, The American Economic Review, Vol. 53, N◦3, pp. 433-443.
  • Morduch J. ,2000, “The Microfinance Schism”, World Development, Vol. 28, Issue 4, April 2000 ,pp .617-629.
  • Yunus M., (1997): “Towards a world without poverty”, LATTES, Paris.
  • Navajas, S. ,2000, “Microcredit and the Poorest of the Poor: Theory and Evidence from Bolivia”, World Development, Vol. 28 No. 2, pp. 333-346.
  • Poirier. D.J. (1980) “Partial observability in bivariate probit models”, Journal of Econometrics, 1980, vol. 12, issue 2, 209-217
  • Rosenberg, E., & Gleit, A.,1994, ‘Quantitative methods in credit management: A survey’, Operations Research, 42(4), 589-613.
  • Sengupta . R., Craig P.A., “The Microfinance Revolution: An Over vie” Federal Reserve Bank of St. Louis Review, January/February 2008, 90 (1), pp. 9-30.
  • Servet J-M, (2006), “Banquiers aux pieds nus: la Microfinance”, Odile jacob, pp.495.
  • Sharma. M., Zelle M., 1997, ‘Repayment performance in group-based credit programs in Bangladesh: An empirical analysis’ World Development, Vol. 25, Issue 10, pp 1731-1742
  • Sharpe, S.A. (1990), “Asymmetric Information, Bank Lending and Implicit Contracts: a Stylized
  • Stewart C. (1984), “Corporate financing and investment decisions when firms have information that investors do not have” Journal of Financial Economics, Vol. 13, Issue 2, pp. 187-221
  • Stiglitz . J, 1990, “Peer Monitoring and Credit Markets”, World Bank Economic Review, vol. 4, pp351-366.
  • Stiglitz. J., Weiss A., 1981, “Credit Rationing in Markets with Imperfect Information”, The American Economic Review, Vol. 71, n° 3, pp393-410.
  • Tedeschi A. G., 2006, “Here today, gone tomorrow: can dynamic incentives make microfinance more flexible?”, Journal of development economics, vol. 80, pp.84-105.
  • Van Maanen, 2005, “Proceedings of the Eighth International Workshop on Trust in Agent Societies (Trust 2005)”, Utrecht, The Netherlands.