Regional differentiation, agglomeration and clusters within the EU

The European integration process is constantly deepening. In the 90s of the last century the project of the internal market was completed and then Member States started to implement the provisions of a monetary union. Coordination proceeds also in terms of fiscal, structural and to some extent and social policies. Nevertheless, the European Union is quite a heterogeneous as a whole. Individual economies are different both in absolute and relative economic indicators, the economic and social disparities of the member base is even more marked after the recently realized enlargement of the original Fifteen by the twelve new member states. European Union is chracterized by significant concentration of economic activities, both sectoral and spatial. The goal of this paper is to clarify regional differentiation and agglomeration within the European union. We will use quantitative analises of empirical statistical data from Eurostat databases and the European Cluster Observatory. To monitor regional differences in economic level, gross domestic product per capita expressed in purchasing power parity is used as an indicator which is also suitable for international comparisons, since it addresses issues of the effects of price levels and exchange rates. A substantial issue in the assessment of regional disparities represents a selection of examined territorial units. In cluster analyses we will come out, for reasons of comparability, from the unified classification of territorial regions of the European Union, which divides the territory of all member countries into the so-called NUTS regions. Specifically, we will follow namely the units at NUTS 2 level, only in certain evaluation we enter the regions at the level of the NUTS 3. In our analysis, we use data from a database of European Cluster Observatory, which represents the most comprehensive European source. The database contains comparative data for all 27 EU member countries and focuses only on clusters of high quality levels. Clusters are identified based on regional employment. Geographical dimension is observed at the NUTS 2 regions. To determine the quality of industrial specialization and agglomeration is used in so-called Star classification under which the cluster can take one, two or three stars. Three stars are seen as the highest achievable rating.