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Evaluating the Synchronisation of the Eurozone Business Cycles using Multivariate Coincident Macroeconomic Indicators

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Abstract

This paper offers an insight into the optimality of the European Economic and Monetary Union (EMU) and its common monetary policies by evaluating the degree of business cycle synchronisation among the EMU member states with respect to the Eurozone aggregate. Business cycles for each country, defined by turning points, are extracted from multivariate coincident macroeconomic variables by using both classical and modern business cycle dating procedures, including the Bry-Boschan Quarterly (BBQ) algorithm, the multivariate dynamic-factor model and the multivariate dynamic-factor Markov-switching (DFMS) model. The degree of cycle synchronisation between the EMU members and the Eurozone aggregate is measured using the index of concordance, the mean corrected index of concordance and correlation-coefficients. The inference provided by the pairwise correlation-coefficients of the smoothed recession probabilities in the dynamic-factor Markov-switching model is also used to indicate cycle corrections. Overall, close cycle correlations are found between the Eurozone aggregate and the core EMU countries. A catching-up process of cycle convergence is observed in some of the peripheral countries (Spain and Finland), perhaps as a result of participating in the ERM and the EMU. To date there have been few studies measuring cycle synchronisation using business cycles extracted from multivariate coincident macroeconomic indicators for the EMU countries. This paper contributes to this area.

Suggested Citation

  • Xiaoshan Chen, 2007. "Evaluating the Synchronisation of the Eurozone Business Cycles using Multivariate Coincident Macroeconomic Indicators," Discussion Paper Series 2007_27, Department of Economics, Loughborough University, revised Nov 2007.
  • Handle: RePEc:lbo:lbowps:2007_27
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    File URL: http://www.lboro.ac.uk/departments/ec/RePEc/lbo/lbowps/XChen2007.pdf
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    Cited by:

    1. Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.

    More about this item

    Keywords

    Business Cycle Turning Point; Markov-Switching; Dynamic-factor model;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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