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dc.contributor.authorBehl, Peter-
dc.contributor.authorDette, Holger-
dc.contributor.authorFrondel, Manuel-
dc.contributor.authorTauchmann, Harald-
dc.date.accessioned2010-10-27T11:32:01Z-
dc.date.available2010-10-27T11:32:01Z-
dc.date.issued2010-10-27-
dc.identifier.urihttp://hdl.handle.net/2003/27438-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15657-
dc.description.abstractIn contrast to conventional measures, the Focused Information Criterion (FIC) allows the purpose-specific selection of models, thereby reflecting the idea that one kind of model might be appropriate for inferences on a parameter of interest, but not for another. Ever since its introduction, the FIC has been increasingly applied in the realm of statistics, but this concept appears to be virtually unknown in the economic literature. Using a straightforward analytical example, this paper illustrates the FIC and its usefulness in economic applications. JEL classification: C3, D2en
dc.language.isoenen
dc.relation.ispartofseriesDiscussion Paper / SFB 823;42/2010-
dc.subjectAKAIKE Information Criterionen
dc.subjectSCHWARZ Information Criterionen
dc.subjectTranslog Cost Functionen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleChoice is sufferingen
dc.title.alternativea focused information criterion for model selectionen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
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