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Generalized Modeling and Estimation of Rating Classes and Default Probabilities Considering Dependencies in Cross and Longitudinal Section

Our sample (Xit; Yit) consists of pairs of variables. The real variable Xit measures the creditworthiness of individual i in period t. The Bernoulli variable Yit is the default indicator of individual i in period t. The objective is to estimate a credit rating system, i.e. to particularly divide the range of the creditworthiness into several rating classes, each with a homogeneous default risk. The field of change point analysis provides a way to estimate the breakpoints between the rating classes. As yet, the literature only considers models without dependencies or with dependence only in cross section. This contribution proposes multi-period models including dependencies in cross section as well as in longitudinal section. Furthermore, estimators for the model parameters are suggested. The estimators are applied to a data set of a German credit bureau.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30253
Date30 March 2017
CreatorsTillich, Daniel
PublisherTechnische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageGerman
Detected LanguageEnglish
Typedoc-type:book, info:eu-repo/semantics/book, doc-type:Text
SourceDresdner Beiträge zu Quantitativen Verfahren
Rightsinfo:eu-repo/semantics/openAccess
Relationurn:nbn:de:bsz:14-qucosa-222671, qucosa:30256

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