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Scoring Bank Loans that may go wrong: A Case Study

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Author Info
J.S. Cramer () (University of Amsterdam)

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Abstract

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

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Publisher 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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This paper has been announced in the following NEP Reports: Cited by:
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  1. Annemiek van VUren & Daniël van Vuuren, 2005. "Financial incentives in disability insurance in the Netherlands," CPB Discussion Papers 45, CPB Netherlands Bureau for Economic Policy Analysis. [Downloadable!]
    Other versions:
  2. J.S. Cramer, 2005. "Omitted Variables and Misspecified Disturbances in the Logit Model," Tinbergen Institute Discussion Papers 05-084/4, Tinbergen Institute. [Downloadable!]
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