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Identifying And Interpreting Convergence Clusters Across Europe

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  • Luisa Corrado
  • Ron Martin
  • Melvyn Weeks
Abstract
In this paper we examine the spatial and temporal distribution of per capita income across Europe. We base our analysis on a cluster methodology which allows for an endogenous selection of regional clusters using a multivariate test for stationarity where the number and composition of clusters are determined by the application of pairwise tests of regional contrasts. To circumvent the problem of how to interpret the composition of resulting convergence clusters we construct a number of testable hypotheses based upon orderings consistent with the findings of recent studies on regional growth and convergence. We do this using a set of geographical, socio-demographic and political indicators measuring contiguity and institutional similarity, accessibility, specialisation, region specific levels of agglomeration and regional classification according to the European Union Structural Fund objectives. One of the contributions of our study is a method which facilitates the interpretation of the cluster outcomes on the basis of the factors identified above. Unlike previous studies, we present our results using a geographic representation of regions across Europe.
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Suggested Citation

  • Luisa Corrado & Ron Martin & Melvyn Weeks, 2004. "Identifying And Interpreting Convergence Clusters Across Europe," Royal Economic Society Annual Conference 2004 145, Royal Economic Society.
    • Handle: RePEc:ecj:ac2004:145
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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