Clustering techniques for the detection of Business Cycles

dc.contributor.author	Theis, W.	de
dc.contributor.author	Weihs, C.	de
dc.date.accessioned	2004-12-06T18:39:49Z
dc.date.available	2004-12-06T18:39:49Z
dc.date.issued	1999	de
dc.description.abstract	In this paper business cycles are considered as a multivariate phenomenon and not as a univariate one determined e.g. by the GNP. The subject is to look for the number of phases of a business cycle, which can be motivated by the number of clusters in a given dataset of macro-economic variables. Different approaches to distances in the data are tried in a fuzzy cluster analysis to pursue this goal.	en
dc.format.extent	202234 bytes
dc.format.extent	897846 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/4927
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-15027
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	business cycles	en
dc.subject	cluster analysis	en
dc.subject	fuzzy clustering	en
dc.subject.ddc	310	de
dc.title	Clustering techniques for the detection of Business Cycles	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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