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Club performance dynamics at Italian regional level

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Abstract
This paper analyze the dynamic economic performance of the Italian regions during the period 1970-2004. The measure of economic performance is given by the level and the growth rates of per capita GDP. Using the concept of economic regime, we introduce a notion of distance between the dynamical paths of the Italian regions. Afterwards, a Minimal Spanning Tree and a Hierarchical Tree are constructed from time series in order to assess the existence of groups of regions sharing similar economic performance. Two main clusters are identified, representing high performance and low performance regions, alongside other two small clusters displaying regions with similar dynamic behaviour. The high performance cluster comprises mainly regions from the north, showing the presence of agglomeration externalities. Turning to the evolution of clusters, we see a similar path until 1975, after which the two groups start to slightly diverge. Studying the evolution of each cluster's diameter we find substantial convergence within the two groups. Splitting the sample into two periods (1975-1993 and 1994-2005) the hypothesis of two performance clubs is confirmed. The club shift of some regions hints a strong effect on regional economic dynamics of the Italian 1994 crisis. The final analysis of the distance between the two clusters show that in the first period (1975-1993) the distance between the two group was constant, while in the second one (1994-2005) it has increased.

Suggested Citation

  • N. Garrido & F. Mureddu, 2012. "Club performance dynamics at Italian regional level," Working Paper CRENoS 201203, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    • Handle: RePEc:cns:cnscwp:201203
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    Cited by:

    1. BRIDA, Juan Gabriel & GARRIDo, Nicolas & MUREDDU, Francesco, 2014. "Club Performance Dynamics At Italian Regional Level," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 14(1), pages 47-68.
    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. Marco PLATANIA, 2014. "Trade Advantage Of Italian Industrial Districts:Persistence And Change," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 14(2).

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    More about this item

    Keywords

    hierarchical clustering; economic convergence; economic dualism;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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