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The European Business Cycle

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  • Artis, Michael J
  • Krolzig, Hans-Martin
  • Toro, Juan

Abstract

This paper deals with the existence and identification of a common European Growth Cycle. It has recently been argued that the formation of a monetary union creates in itself a tendency for business cycle symmetry to emerge. If this holds for the European monetary Union and the quasi-union of the Exchange Rate Mechanism of the European Monetary System, then we might already expect to be able to find an emergent 'European cycle' which will become more dominant in future years. Univariate Markov switching autoregressions (MS-AR) are used for individual countries in order to detect changes in the mean growth rate of industrial production. The smoothed probabilities obtained from these models give support to the possibility of inferring a common European cycle by jointly modelling the industrial production indices of the nine countries under study. An MS-VAR model is then used to identify the common cycle in Europe and the results confirm the existence of such a cycle. The European business cycle is dated on the basis of the regime probabilities. Two further issues are investigated. First we investigate the contribution of the European Business Cycle to the individual country cycles. Second, we undertake an impulse response analysis where we investigate the response of each individual country to European expansions and recessions. We analyze the response of industrial production in each country due to a change in regime. We focus mainly on two types of shocks, the response of industrial production in individual countries due to a European recession and the effect of an expansionary period in Europe. An appendix includes a similar analysis for GDP.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 2242.

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Date of creation: Sep 1999
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Handle: RePEc:cpr:ceprdp:2242

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Keywords: European Union; International Business Cycles; Markov Switching Structural Breaks; Time Series Analysis;

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References

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