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Convergence and Cluster Structures in EU Area according to Fluctuations in Macroeconomic Indices

Author

Listed:
  • Gligor, Mircea

    (University of Liege)

  • Ausloos, Marcel

    (University of Liege)

Abstract

Cluster analysis methods allow for a comparative study of countries through basic macroeconomic indicator fluctuations. Statistical distances between 15 EU countries are first calculated for various moving time windows. The decrease in time of the mean statistical distance is observed through the correlated fluctuations of typical macroeconomic indicators: GDP, GDP/capita, Consumption and Investments. This empirical evidence can be seen as a mark of globalization. The Moving Average Minimal Length Path algorithm indicates the existence of cluster-like structures both in the hierarchical organization of countries and their relative movements inside the hierarchy. The most strongly correlated countries with respect to GDP fluctuations can be partitioned into stable clusters. Several so correlated countries display strong correlations also in the Final Consumption Expenditure; others are strongly correlated in the Gross Capital Formation. The similarity between the classifications due to GDP and Net Exports fluctuations is pointed out through the squared sum of the correlation coefficients, a so called “country sensitivity”. The structures are robust against changes in time window size. Policy implications concern the economic clusters arising in the presence of Marshallian externalities and the relationships between trade barriers, R&D incentives and growth that must be accounted for in elaborating cluster-promotion policies.

Suggested Citation

  • Gligor, Mircea & Ausloos, Marcel, 2008. "Convergence and Cluster Structures in EU Area according to Fluctuations in Macroeconomic Indices," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 23, pages 297-330.
    • Handle: RePEc:ris:integr:0435
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    Cited by:

    1. Jasna Soldić-Aleksić & Rade Stankić, 2015. "A Comparative Analysis Of Serbia And The Eu Member States In The Context Of The Networked Readiness Index Values," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 60(206), pages 45-86, July - Se.
    2. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    3. Anna Maria D’Arcangelis & Giulia Rotundo, 2016. "Complex Networks in Finance," Lecture Notes in Economics and Mathematical Systems, in: Pasquale Commendatore & Mariano Matilla-García & Luis M. Varela & Jose S. Cánovas (ed.), Complex Networks and Dynamics, pages 209-235, Springer.
    4. Ausloos, Marcel & Saeedian, Meghdad & Jamali, Tayeb & Farahani, S. Vasheghani & Jafari, G. Reza, 2017. "How visas shape and make visible the geopolitical architecture of the planet," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 267-275.
    5. Miguel Carvalho & António Rua, 2014. "Extremal Dependence in International Output Growth: Tales from the Tails," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 605-620, August.
    6. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    7. Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.
    8. Roy Cerqueti & Catherine Deffains‐Crapsky & Saverio Storani, 2023. "Green finance instruments: Exploring minibonds issuance in Italy," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(4), pages 1965-1986, July.
    9. Miśkiewicz, Janusz, 2013. "Power law classification scheme of time series correlations. On the example of G20 group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2150-2162.
    10. de Mattos Neto, Paulo S.G. & Cavalcanti, George D.C. & Madeiro, Francisco & Ferreira, Tiago A.E., 2013. "An ideal gas approach to classify countries using financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 177-183.
    11. Redelico, Francisco O. & Proto, Araceli N. & Ausloos, Marcel, 2009. "Hierarchical structures in the Gross Domestic Product per capita fluctuation in Latin American countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3527-3535.
    12. Ana-Maria HOLOBIUC, 2020. "Assesing The Effects Of The Economic And Financial Crisis On Income Convergence In The Eurozone," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 5(3), pages 134-140.
    13. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2018. "Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective," Papers 1808.05893, arXiv.org.
    14. Marcel Ausloos, 2013. "Econophysics: Comments on a Few Applications, Successes, Methods and Models," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 101-115, July.
    15. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2020. "Simple approaches on how to discover promising strategies for efficient enterprise performance, at time of crisis in the case of SMEs : Voronoi clustering and outlier effects perspective," Papers 2012.14297, arXiv.org.
    16. Li-Wei Dai & Chin-Yi Fang, 2023. "The Role of Corporate Governance in Sustaining the Economy: Examining Its Moderating Effect on Brand Equity and Profitability in Tourism Companies," Sustainability, MDPI, vol. 15(17), pages 1-17, August.
    17. Bongiorno, Christian & Miccichè, Salvatore & Mantegna, Rosario N., 2022. "Statistically validated hierarchical clustering: Nested partitions in hierarchical trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    18. VAN POECK, André, 2009. "One money and fifteen needs inflation and output convergence in the European Monetary Union," Working Papers 2009001, University of Antwerp, Faculty of Business and Economics.

    More about this item

    Keywords

    Statistical distances; Minimal length path; Convergence; Clusteri;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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