The aim of the present study has been to outline and refine a coherent approach to identifying and modelling business cycles on various levels of aggregation. A further central task has been to demonstrate its potential and superiority to conventional methods and models by applying it to updated, as well as newly available sources of data. Three central and connected aspects, which are widely neglected issues, though of paramount importance,1 in contemporary business cycle research, have been thoroughly investigated: Description, aggregation and comovement or synchronization of business cycles. Here I briefly summarize the major findings:
Chapter 2 and 3 outlined the methodology for the analysis of cyclical dynamics developed at SEMECON, especially in the latest contributions by C. Hillinger, U. Woitek and M. Reiter, which represent the direct precursors to the present study. I attempted to supplement and refine the existing methods, primarily in the following two respects: (i) definition and application of central volatility and contribution-to-variance measures and (ii) derivation of standard errors for estimated period lengths and moduli of found cyclicalities, based on the AR interpretat ion of ME spectral analysis. In chapter 3 this methodology was applied to a thorough analysis of the G7 and Eurol 5 national and supranational economies. A central finding was the revelation and evidence of classical business cycles with frequencies corresponding to about 2 to 4 and about 7 to 10 years period lengths. Both are reflected in the spectra of the G7 economies and the two supranational economies (G7 and EuroI5 ). Central contributors to cyclic dynamic and volatility terms are the economies of Germany, Japan and the USA. Germany has been found to be predominated by a M/W-cyclical structure and mainly responsible for the secondary peak, corresponding to a classical short cycle, in the spectrum of the Eurol5 supra-economy. An outstanding and robust finding was the identification of the US economy as an economy profoundly and exceptionally dominated by cyclic investment dynamics with an intermediary periodicity of about 5 to 6 years.
KeywordsBusiness Cycle Synchronization Phenomenon Model Business Cycle Central Volatility Volatility Term
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- 1.As recently more frequently claimed in the literature.Google Scholar