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Synchronization patterns in the European Union

Author

Listed:
  • Mattia Guerini

  • Duc Thi Luu
  • Mauro Napoletano

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

In this paper, we quantify business cycles synchronization in the European Union by combining Principal Component Analysis (PCA) with a Random Matrix Theory (RMT) model. We employ a balanced panel of industrial production indexes over the 2000–2017 period and we track the evolution of the European synchronization, as measured by the largest and statistically significant principal component. Using the information contained in the eigenvector associated to it, we then identify the dynamics of synchronization clusters. Our results suggest that the degree of synchronization has increased since the introduction of the common currency and until the Great Recession, but decreased thereafter. In addition, our results point to the evolution of synchronization clusters over the past decades. Whereas western and eastern countries had divergent business cycles at the beginning of the 21st century, they have become more synchronized over the analysed period. However, since the dawn of the European sovereign debt crisis, the synchronization divide has become more apparent between northern and southern economies.

Suggested Citation

  • Mattia Guerini & Duc Thi Luu & Mauro Napoletano, 2022. "Synchronization patterns in the European Union," Sciences Po Economics Publications (main) hal-04531116, HAL.
    • Handle: RePEc:hal:spmain:hal-04531116
    DOI: 10.1080/00036846.2022.2101607
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-04531116v1
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    Cited by:

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    2. Claudio Barbieri & Mattia Guerini & Mauro Napoletano, 2021. "The anatomy of government bond yields synchronization in the Eurozone," Sciences Po Economics Publications (main) hal-03373853, HAL.
    3. Lucio Biggiero & Roberto Urbani, 2022. "Testing the convergence hypothesis: a longitudinal and cross-sectional analysis of the world trade web through social network and statistical analyses," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 713-777, July.
    4. Agnieszka Gehringer & Jörg König, 2021. "Recent Patterns of Economic Alignment in the European (Monetary) Union," JRFM, MDPI, vol. 14(8), pages 1-23, August.
    5. Emanuele De Meo & Giacomo Tizzanini, 2021. "GDP‐network CoVaR: A tool for assessing growth‐at‐risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(2), July.
    6. Pereira, Filipe & Aguiar-Conraria, Luís, 2025. "Eurozone Inflation Convergence: Deceptive Appearances," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 343-352.
    7. Pangallo, Marco, 2025. "Synchronization of endogenous business cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 229(C).
    8. Mattia Guerini & Fabio Vanni & Mauro Napoletano, 2025. "E pluribus, quaedam. Gross Domestic Product out of a Dashboard of Indicators," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 11(1), pages 1-16, March.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • F45 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Macroeconomic Issues of Monetary Unions

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