In international cross-country studies, evidence for club convergence has often been found using different methodologies (Baumol 1986; Durlauf and Johnson 1995; Quah 1996a, 1997). In the case ofthe European regions, Ertur and Le Gallo (see Chap. 2) and Le Gallo et al.(see Chap. 3) have shown that the convergence rate among European regions is slow and that GDP disparities seem to be persistent despite the European econornic integration process and higher growth rates of some poorer regions, as highlighted as well in the European Cormnission reports (1996, 1999). Moreover, over the 1980-1995 period, Ertur and Le Gallo (see Chap. 2) found that the geographical distribution of European regions exhibits a persistent polarization pattern between rich regions in the north and poor regions in the south.

These evidences can in fact be linked to several results of new econornic geography theories (Krugman 1991), which show that locations of econornic activities are spatially structured by some agglomerative and cumulative processes. Therefore, we may say that the geographical distribution of areas characterized by high or low econornic activities is spatially dependent and tends to exhibit persistence. Moreover, the econornic surrounding of a region seerns to influence the econornic development perspectives for this region: a poor (respectively rich) region surrounded by poor (respectively rich) regions will stay in this state of econornic development whereas a poor region surrounded by richer regions has more probability to reach a higher state of econornic development. These results are highlighted for European regions by Le Gallo (2001) who analyses the transitional dynarnics of per capita GDP over the 1980-1995 period by means of a spatial Markov chains approach: the results emphasizes a poverty trap since the cluster of the poorest European regions in Southern Europe creates a great disadvantage for these regions.