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 the case of selected EU Visegrad Four (V4) countries. 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 linear panel data regression model for

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... 5 regions at NUTS level 2 of selected V4 countries. The level of regional competitiveness is analysed by selected indicators evaluating the performance of the EU growth strategies objectives. Selection of explanatory variables in the panel data model appropriately reflects the level of competitive potential in NUTS 2 regions of the selected EU V4 countries in the reference period 2000 -2008. The use of econometric panel data model seems to be appropriate, since it marks the better capture of the dynamics of changes and fixed or random 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 includes 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 the selected V4 countries to the overall competitiveness of the European Union. The basic hypothesis assumes that the average value of EU 27 GDP per capita is considered as an ideal region, i.e., the most competitive region. In the paper, we have observed contributions of each statistically significant V4 NUTS 2 region to the average level of the whole EU 27 performance approximated by GDP per inhabitant in PPS. For the model purposes, the overall EU competitiveness is approximated with the average volume of GDP per capita in PPS for 271 NUTS 2 regions in the EU 27, according to the NUTS 2008 -2011 classification methodology.