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Convergence of European Business Cycles: A Complex Networks Approach

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  • Theophilos Papadimitriou
  • Periklis Gogas
  • Georgios Sarantitis

Abstract

We examine the co-movement patterns of European business cycles during the period 1986–2011, with an obvious focal point the year 1999 that marked the introduction of the common currency, the euro. The empirical analysis is performed within the context of Graph Theory where we apply a rolling window approach in order to dynamically analyze the evolution of the network that corresponds to the GDP growth rate cross-correlations of 22 European economies. The main innovation of our study is that the analysis is performed by introducing what we call the threshold-minimum dominating set (T-MDS). We provide evidence at the network level and analyze its structure and evolution by the metrics of total network edges, network density, isolated nodes and the cardinality of the T-MDS set. Next, focusing on the country level, we analyze each individual country’s neighborhood set (economies with similar growth patterns) in the pre- and post-euro era in order to assess the degree of convergence to the rest of the economies in the network. Our empirical results indicate that despite a few economies’ idiosyncratic behavior, the business cycles of the European countries display an overall increased degree of synchronization and thus convergence in the single currency era. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Theophilos Papadimitriou & Periklis Gogas & Georgios Sarantitis, 2016. "Convergence of European Business Cycles: A Complex Networks Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 97-119, February.
  • Handle: RePEc:kap:compec:v:47:y:2016:i:2:p:97-119
    DOI: 10.1007/s10614-014-9474-3
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    Cited by:

    1. Zhiping Qiu & Sichao Mai, 2022. "Topological characteristics of international business cycle synchronization: A network analysis of the BRI economies," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-17, June.
    2. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    3. Antonakakis, Nikolaos & Gogas, Periklis & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2016. "International business cycle synchronization since the 1870s: Evidence from a novel network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 286-296.
    4. Gogas, Periklis & Gupta, Rangan & Miller, Stephen M. & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2017. "Income inequality: A complex network analysis of US states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 423-437.
    5. Mao Takongmo, Charles-O. & Touré, Adam, 2023. "Trade openness and connectedness of national productions: Do financial openness, economic specialization, and the size of the country matter?," Economic Modelling, Elsevier, vol. 125(C).
    6. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2019. "A re-evaluation of the Feldstein-Horioka puzzle in the Eurozone," Journal of Risk & Control, Risk Market Journals, vol. 6(1), pages 19-35.
    7. Amalia Repele & Sébastien Waelti, 2021. "Mapping the Global Business Cycle Network," Open Economies Review, Springer, vol. 32(4), pages 739-760, September.
    8. Plakandaras, Vasilios & Tiwari, Aviral Kumar & Gupta, Rangan & Ji, Qiang, 2020. "Spillover of sentiment in the European Union: Evidence from time- and frequency-domains," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 105-130.
    9. Luis à ngel Hierro & Antonio José Garzón & Helena Domínguez-Torres, 2019. "20 Years of European Monetary Policy. From Doctrinarism to Realpolitik," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 66(3), pages 149-172, December.
    10. Matesanz, David & Ortega, Guillermo J., 2016. "On business cycles synchronization in Europe: A note on network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 287-296.

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