Reject inference in consumer credit scoring with nonignorable missing data

dc.contributor.author	Bücker, Michael
dc.contributor.author	Krämer, Walter
dc.date.accessioned	2011-03-02T11:34:50Z
dc.date.available	2011-03-02T11:34:50Z
dc.date.issued	2011-03-02
dc.description.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.	en
dc.identifier.uri	http://hdl.handle.net/2003/27636
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-1123
dc.language.iso	en	de
dc.relation.replaces	http://hdl.handle.net/2003/27554
dc.subject	Credit scoring	en
dc.subject	Logistic regression	en
dc.subject	Missing data	en
dc.subject	Reject inference	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Reject inference in consumer credit scoring with nonignorable missing data	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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