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Unity and Plurality of the European Cycle

This paper aims to apply the methodology of uni- and multivariate Structural Unobserved Components Time Series Models developed by Andrew Harvey to the study of European growth trends and cycles. The multivariate dimension enables to search similar or, more strongly, common components among national series. Common factors models are an interesting way to study the relations between trends and cycles of several series. The first section presents the general methodology of the paper. The second section presents uni- and multivariate structural time series models more accurately. It presents explicitly the multivariate form of the models in the trivariate case. The trivariate dimension is convenient to understand the logic of these models. The trivariate case remains simple enough to be written explicitly without using systematically matrix presentation and it is more general than the bivariate case, which is too particular to illustrate the general features of multivariate models. Sections 3 to 5 present and comment the application of this methodology to the study of European growth trends and cycles. Data covering all the decades 1960 to 1990 are extracted from the quarterly national accounts collected in the BSDB database of OECD (Business Sector Data Base). The application uses the software STAMP (Koopman, Harvey, Doornik and Shephard, 2000), which was specially built to implement the multivariate structural time series models. Three successive ways to exhibit the European cycle are used: the direct split of the European aggregate GDP, compared to the US split in a bivariate model; the aggregation of the national cycles of the member countries; the search for common components between these national cycles. The results of these ways are compared. Convergence between the results of these approaches is satisfactory. The European aggregate fluctuations reveal two distinct cyclical components, which can be assimilated to the classical Juglar (or decennial) and Kitchin (or triennial) cycles. The European Juglar or decennial cycle exists clearly but it cannot be reduced to a single common component of the national cycles, which would be generated by a single series of shocks. The European Juglar cycle has at least the dimension “three”, i.e. it can be understood as the result of the interference of three elementary and independent sequences of stochastic shocks. These elementary components correspond to current geographical division of Europe. From this point of view, the euro-zone is not yet an optimal currency area, as the shocks generating the European cycles are not completely symmetrical. The national cycles are not yet reducible to the common symmetrical component which shows through the aggregate cycle of the European GDP. This common and symmetrical component contributes approximately only for one third to the whole national cycles. The sixth section uses the sequences of shocks (or innovations) extracted from the uni– and multivariate models to build indicators giving information about the evolution of the symmetrical character of shocks hitting euro-zone countries. The vulnerability of the euro-zone to strong shocks and the asymmetry of these shocks show some decreasing trend during the last ten decades but this trend is neither regular, nor irreversible. The conclusion sums up the main ideas coming from this set of applications. It confirms the practical interest of the specific stochastic models used by this paper and the complexity of the European cycle. The definition of a balanced policy mix should take into account the persistent plurality of the a balanced policy mix should take into account the persistent plurality of the European cycles.