Authors: Bücker, Michael
Krämer, Walter
Title: Reject inference in consumer credit scoring with nonignorable missing data
Language (ISO): en
Abstract: We generalize an empirical likelihood approach to missing data to the case of consumer credit scoring and provide a Hausman test for nonignorability of the missings. An application to recent consumer credit data shows that our model yields parameter estimates which are significantly different (both statistically and economically) from the case where customers who were refused credit are ignored.
Subject Headings: Credit scoring
Logistic regression
Missing data
Reject inference
Issue Date: 2011-03-02
Appears in Collections:Sonderforschungsbereich (SFB) 823

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