EURECONProject ID: 514913
Regional convergence clusters across Europe: methodological issues and empirical evidence
Total cost:EUR 0
EU contribution:EUR 177 970
Coordinated in:United Kingdom
Call for proposal:FP6-2002-MOBILITY-5See other projects for this call
Funding scheme:EIF - Marie Curie actions-Intra-European Fellowships
The identification of regional convergence clubs is in the research agenda of economists and policy-makers. In general, it is widely recognized (see, for example, Bertola, 1993; Durlauf and Johnson, 1995) that inter-regional interactions and co-dependence in growth over time produce multiple convergence paths at the regional level The aim of the project is to develop research to support the anedoctical evidence on the presence of these different poles of attraction by focussing upon the distribution of regional per capita income across Europe. We base the 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 is determined by the application of pairwise tests on regional contrasts.
The methodology is based on the following two steps:
(i) generating regional clusters based upon the statistical-based method just described;
(ii) testing the cluster pattern against one or more hypothesised cluster patterns based upon geographic, socio-demographic and politico-institutional factors along the lines of regional economic 'theory'.
We wish to construct these testable hypotheses on the basis of a set of indicators on the region specific level of agglomeration (population growth and settlement structure), accessibility (length of transportation), contiguity and institutional similarity (geographic location of regions), specialisation (level of agricultural intensification). We also wish to analyse the interaction between the observed outcomes and the set of structural funds used by the European Community to promote the development and structural adjustment of European Community regions.
This approach is particularly useful for policy analysis since it gives a richer set of information on the temporal distribution and composition of the convergence clubs. The next step of my research is to further analyse the nature of cross-sectional dependence.