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Estimation of default probabilities using incomplete contracts data

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  • Santos Silva, J.M.C.
  • Murteira, J.M.R.

Abstract

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The main advantage of the proposed approach is that it permits a more efficient use of the data, including that for the most recent clients. Moreover, because the probability of default is specified as a function of the age of the contract, the model provides some information on the timing of the defaults. The model is based on the beta-binomial distribution, which is found to be particularly adequate for this purpose. A well-known dataset on personal loans is used to illustrate the application of the proposed model.

Suggested Citation

  • Santos Silva, J.M.C. & Murteira, J.M.R., 2009. "Estimation of default probabilities using incomplete contracts data," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 457-465, June.
  • Handle: RePEc:eee:empfin:v:16:y:2009:i:3:p:457-465
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    1. Johansson, Per & Palme, Marten, 1996. "Do economic incentives affect work absence? Empirical evidence using Swedish micro data," Journal of Public Economics, Elsevier, vol. 59(2), pages 195-218, February.
    2. Heckman, James J & Willis, Robert J, 1977. "A Beta-logistic Model for the Analysis of Sequential Labor Force Participation by Married Women," Journal of Political Economy, University of Chicago Press, vol. 85(1), pages 27-58, February.
    3. Dionne, Georges & Artis, Manuel & Guillen, Montserrat, 1996. "Count data models for a credit scoring system," Journal of Empirical Finance, Elsevier, vol. 3(3), pages 303-325, September.
    4. Carling, Kenneth & Jacobson, Tor & Roszbach, Kasper, 1998. "Duration of consumer loans and bank lending policy: dormancy versus default risk," SSE/EFI Working Paper Series in Economics and Finance 280, Stockholm School of Economics.
    5. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541.
    6. Wooldridge, Jeffrey M, 1992. "Some Alternatives to the Box-Cox Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(4), pages 935-955, November.
    7. Carling, Kenneth & Jacobson, Tor & Roszbach, Kasper, 2001. "Dormancy risk and expected profits of consumer loans," Journal of Banking & Finance, Elsevier, vol. 25(4), pages 717-739, April.
    8. Kasper Roszbach, 2004. "Bank Lending Policy, Credit Scoring, and the Survival of Loans," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 946-958, November.
    9. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    10. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    11. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    12. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
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    Cited by:

    1. José Varejão & Pedro Portugal, 2003. "Why Do Firms Use Fixed-Term Contracts?," CEF.UP Working Papers 0310, Universidade do Porto, Faculdade de Economia do Porto.
    2. Santos Silva, J.M.C. & Tenreyro, Silvana & Wei, Kehai, 2014. "Estimating the extensive margin of trade," Journal of International Economics, Elsevier, vol. 93(1), pages 67-75.
    3. Harald Oberhofer & Michael Pfaffermayr, 2014. "Two-Part Models for Fractional Responses Defined as Ratios of Integers," Econometrics, MDPI, Open Access Journal, vol. 2(3), pages 1-22, September.
    4. repec:esx:essedp:721 is not listed on IDEAS
    5. Marshall, Andrew & Tang, Leilei & Milne, Alistair, 2010. "Variable reduction, sample selection bias and bank retail credit scoring," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 501-512, June.
    6. Enrico De Giorgi, 2002. "An Intensity Based Non-Parametric Default Model for Residential Mortgage Portfolios," Risk and Insurance 0209001, EconWPA, revised 09 Sep 2002.

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