Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/69740 
Erscheinungsjahr: 
2013
Schriftenreihe/Nr.: 
FZID Discussion Paper No. 64-2013
Verlag: 
Universität Hohenheim, Forschungszentrum Innovation und Dienstleistung (FZID), Stuttgart
Zusammenfassung: 
This article proposes a new multivariate method to construct business cycle indicators. The method is based on a decomposition into trend-cycle and irregular. To derive the cycle, a multivariate band-pass filter is applied to the estimated trend-cycle. The whole procedure is fully model-based. Using a set of monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. They are represented by the smoothed cycles of real GDP and the industrial production index. Both indicators are able to reproduce previous recessions very well. Series contributing to the construction of both indicators are allowed to be leading, lagging or coincident relative to the business cycle. Their behavior is assessed by means of the phase angle and the mean phase angle after cycle estimation. The proposed multivariate method can serve as an attractive tool for policy making, in particular due to its good forecasting performance and quite simple setting. The model ensures reliable realtime forecasts even though it does not involve elaborate mechanisms that account for, e.g., changes in volatility.
Schlagwörter: 
business cycle
multivariate structural time series model
univariate band-pass filter
forecasts
phase angle
JEL: 
E32
E37
C18
C32
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
412.74 kB





Publikationen in EconStor sind urheberrechtlich geschützt.