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Forecasting the Turns of German Business Cycle: Dynamic Bi-Factor Model with Markov Switching

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dc.creator Kholodilin, Konstantin Arkadievich
dc.date 2005
dc.date.accessioned 2013-10-16T06:59:35Z
dc.date.available 2013-10-16T06:59:35Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/18345
dc.identifier ppn:491232934
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/18345
dc.description In this paper a dynamic bi-factor model with Markov switching is proposed to measure and predict turning points of the German business cycle. It estimates simultaneously the composite leading indicator (CLI) and composite coincident indicator (CCI) together with corresponding probabilities of being in recession. According to the bi-factor model, on average, CLI leads CCI by 3 months at both peaks and troughs. The model-derived recession probabilities of CCI and those of CLI with a lag of 2?3 months capture the turning points of the ECRI?s and OECD?s reference cycle much better than the dynamic single-factor model with Markov switching.
dc.language eng
dc.publisher Deutsches Institut für Wirtschaftsforschung (DIW) Berlin
dc.relation DIW-Diskussionspapiere 494
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject C10
dc.subject E32
dc.subject ddc:330
dc.subject Forecasting turning points
dc.subject composite coincident indicator
dc.subject composite leading indicator
dc.subject dynamic bi-factor model
dc.subject Markov-switching
dc.title Forecasting the Turns of German Business Cycle: Dynamic Bi-Factor Model with Markov Switching
dc.type doc-type:workingPaper


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