The paper examines economic growth in old and new member countries of the European Union (EU-15 and EU-12) during the years of 1994-2000 and 2001-2008 mainly due to changes in information and communication technology (ICT) capital development. The first group EU-15 is presented by old EU countries and the second group EU-12 is presented by new member countries that joined the EU in 2004-2007. The threefactor Cobb-Douglas production function is estimated through the panel general least squares method. The input factors that might influence the economic growth are labour, ICT capital services and non-ICT capital services. Since ICT capital growth data are not available for all selected economies, the groups of countries were reduced to EU-14 and EU-7. The estimated panel production functions confirmed that the average growth of GDP in the EU-7 countries was supported by the stable growth of labour quantity and ICT-capital and increasing total factor productivity. A short-term drop in non-ICT capital growth with follow-up stagnation was caused rather by lower labour productivity. The research discovered that the drop in GDP growth in the EU-14 countries was a result of the slower growth of non-ICT capital and total factor productivity and the stagnated growth of ICT capital with low elasticity, and showed that even the compensation of growth in labour quality did not prevent a decrease in total factor productivity and economic growth.

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Background: The paper focusses on the efficiency evaluation of the EU-28 NUTS 2 regions production process according to the concept of the Regional Competitiveness Index 2013. Objectives: Production units are divided into four groups using the factors of regional competitiveness. Production technology also enables reduction of the undesirable outputs (a negative impact on health and long-term unemployment). Based on the analysis of distance of the production units from the efficiency frontiers, a directional output distance function assuming a constant return to scale is used. This approach thus respects the heterogeneity among the groups of regions. Methods/Approach: The nonparametric meta-frontier Data Envelopment Analysis approach was used in two steps. Firstly, the efficiency evaluation within each group of regions is provided and in the second step the meta-frontier is set down. For the measurement of the gap between the group-frontier and the meta-frontier, the technology gap ratios are provided. The paper also analyses environmental inefficiencies. Results: The obtained results indicate that a significant improvement of meta-technology ratio holds within the European context. Conclusions: The combination of empirical findings, with respect to technology gaps and environmental technology gaps, supports the evidence that traditional differences of technological frontiers formation are more significant in comparison to group frontiers constitution.

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