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Scoring Bank Loans that may go wrong: A Case Study

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  • J.S. Cramer

    ()
    (University of Amsterdam)

Abstract

A bank employs logistic regression with state-dependent sample selection to identify loans thatmay go wrong. Inspection shows that the logit model is inappropriate. A bounded logit model witha ceiling of (far) less than 1 fits the data much better.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 00-090/4.

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Date of creation: 10 Nov 2000
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Handle: RePEc:dgr:uvatin:20000090

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Web page: http://www.tinbergen.nl

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Cited by:
  1. J.S. Cramer, 2005. "Omitted Variables and Misspecified Disturbances in the Logit Model," Tinbergen Institute Discussion Papers 05-084/4, Tinbergen Institute.
  2. J.S. Cramer, 2005. "Omitted Variables and Misspecified Disturbances in the Logit Model," Tinbergen Institute Discussion Papers 05-084/4, Tinbergen Institute.
  3. Annemiek Vuren & Daniel Vuuren, 2007. "Financial Incentives in Disability Insurance in the Netherlands," De Economist, Springer, vol. 155(1), pages 73-98, March.
  4. Medema, Lydian & Koning, Ruud H. & Lensink, Robert, 2009. "A practical approach to validating a PD model," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 701-708, April.

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