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dc.contributor.authorBehl, Peter-
dc.contributor.authorDette, Holger-
dc.contributor.authorFrondel, Manuel-
dc.contributor.authorTauchmann, Harald-
dc.date.accessioned2011-07-04T12:12:08Z-
dc.date.available2011-07-04T12:12:08Z-
dc.date.issued2011-07-04-
dc.identifier.urihttp://hdl.handle.net/2003/28900-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-1850-
dc.description.abstractIn contrast to conventional model selection criteria, the Focused Information Criterion (FIC) allows for purpose-specific choice of models. This accommodates the idea that one kind of model might be highly appropriate for inferences on a particular parameter, but not for another. Ever since its development, 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 classical example and data for 35 U. S. industry sectors (1960-2005), this paper provides for an illustration of the FIC and a demonstration of its usefulness in empirical applications.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;22/2011en
dc.subjectCross-Price Elasticitiesen
dc.subjectInformation Criteriaen
dc.subjectTranslog Cost Functionen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleBeing focuseden
dc.title.alternativeWhen the purpose of inference matters for model selectionen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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