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Estimation of Default Probabilities Using Incomplete Contracts Data

  • J. M. R. Murteira

    (Universidade de Coimbra)

  • Joao M. C. Santos Silva

    (Universidade Tecnica de Lisboa)

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The model is based on the beta-binomial distribution, which is found to be particularly adequate to describe this sort of data. A well known data set on personal loans granted by a Spanish bank is used to illustrate the application of the proposed model.

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Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1121.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:1121
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  1. 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.
  2. Roszbach, Kasper, 2003. "Bank Lending Policy, Credit Scoring and the Survival of Loans," Working Paper Series 154, Sveriges Riksbank (Central Bank of Sweden).
  3. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-24, January.
  4. 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.
  5. Guillen, Montserrat & Manuel Artis, 1994. "Count Data Models For A Credit Scoring System," Working Papers 021, Risk and Insurance Archive.
  6. James J. Heckman & Robert J. Willis, 1975. "A Beta-Logistic Model for the Analysis of Sequential Labor Force Participation by Married Women," NBER Working Papers 0112, National Bureau of Economic Research, Inc.
  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. Carling, Kenneth & Jacobson, Tor & Roszbach, Kasper, 1998. "Duration of Consumer Loans and Bank Lending Policy: Dormancy Versus Default Risk," Working Paper Series 70, Sveriges Riksbank (Central Bank of Sweden).
  9. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
  10. 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.
  11. 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 935-55, November.
  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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