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dc.contributor.authorRöhl, Michael C.de
dc.contributor.authorTheis, Winfriedde
dc.contributor.authorWeihs, Clausde
dc.date.accessioned2004-12-06T18:40:35Z-
dc.date.available2004-12-06T18:40:35Z-
dc.date.issued1999de
dc.identifier.urihttp://hdl.handle.net/2003/4961-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15093-
dc.description.abstractWe propose multivariate classification as a statistical tool to describe business cycles. These cycles are often analyzed as a univariate phenomenon in terms of GNP or industrial net production ignoring additional information in other economic variables. Multivariate classification overcomes these limitations by reducing dimension in a way suitable for human perception. Based on a four phase scheme (upswing, upper turning point, downswing, lower turning point) we demonstrate the potential of classification methods by determining the important economic variables (stylized facts) for the German business cycle.en
dc.format.extent284551 bytes-
dc.format.extent910011 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subjectbusiness cycleen
dc.subjectclassificationen
dc.subjectdimension reductionen
dc.subjectsimulated annealingen
dc.subjecttransition structureen
dc.subject.ddc310de
dc.titleMultivariate Classification of Business Phasesen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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