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The paper deals with an application of Data Envelopment Analysis (DEA) method to multicriteria performance evaluation of the Visegrad Four countries (V4) in comparison with selected advanced European Union’s (EU) countries – Austria and Germany. The aim of the paper is to analyse a degree of efficiency achieved in individual countries which is perceived as a reflection of the level of competitive potential in three reference years 2000, 2005 and 2010. The theoretical part of the paper is shortly devoted to the fundamental bases of competitiveness in the context of performance/productivity theory and the methodology of factor and cluster analysis (FA, CA) and DEA method. The multivariate methods, CA and FA, have been used to DEA modelling. The empirical part is aimed at measuring the degree of productivity and level of efficiency changes of evaluated countries by the specialized DEA approach – the Malmquist (Productivity)Index (MI/MPI) measuring the change of technical efficiency and the movement of the frontier in terms of evaluated countries. The final part of the paper offers a comprehensive comparison of results obtained by calculating the MI/MPI.

The aim of the paper is to create an econometric panel data model with techniques using dummy variables for simplification of regional competitiveness evaluation in selected EU 15 countries. The theoretical background of the paper is based on the knowledge of theoretical concept and issues of regional competitiveness and productivity in the context of growth theories. The empirical part of the paper is focused on the application of nonlinear panel data regression model for 35 regions at NUTS level 2 of selected EU15 countries. The level of regional competitiveness is analyzed by selected indicators that evaluate the performance of the objectives of the EU growth strategies. Selection of explanatory variables in the panel data model appropriately reflects the level of competitive potential in NUTS 2 regions of selected EU 15 countries in the reference period 2000 - 2008. The use of econometric panel data model seems to be appropriate, since it better captures the dynamics of changes and the fixed or stochastic effects that have occurred in the proposed explanatory variables. Based on the estimation of the panel data model, econometric and economic verification, the final part of the paper makes a comparison of results for all explanatory variables in NUTS 2 regions, which are cross-sectional and time used to determine the order of influence of each NUTS 2 region of selected EU 15 countries to the overall competitiveness of the European Union. For the purposes of the model, the overall EU competitiveness is approximated with the average volume of GDP per capita in PPS for 271 NUTS 2 regions in EU 27, in accordance with the NUTS 2006 classification methodology.