Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/11917
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dc.contributor.authorSilva, J. M. C. Santos-
dc.contributor.authorMurteira, J. M. R.-
dc.date.accessioned2009-11-02T10:25:22Z-
dc.date.available2009-11-02T10:25:22Z-
dc.date.issued2000-
dc.identifier.citationEstudos do GEMF. 5 (2000)en_US
dc.identifier.urihttps://hdl.handle.net/10316/11917-
dc.description.abstractThis 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.en_US
dc.language.isoengen_US
dc.publisherFEUC. Grupo de Estudos Monetários e Financeirosen_US
dc.rightsopenAccessen_US
dc.subjectBeta-binomial distributionen_US
dc.subjectCredit scoringen_US
dc.subjectHurdle modelsen_US
dc.titleEstimation of Default Probabilities Using Incomplete Contracts Dataen_US
dc.typeworkingPaperen_US
item.grantfulltextopen-
item.fulltextCom Texto completo-
item.openairetypeworkingPaper-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.researchunitCeBER – Centre for Business and Economics Research-
crisitem.author.orcid0000-0002-0798-7456-
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