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Weihs, Claus
Röhl, Michael C.
Theis, Winfried
Year of Publication: 
Series/Report no.: 
Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 1999,26
We 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.
Business cycle
dimension reduction
simulated annealing
transition structure
Document Type: 
Working Paper

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