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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.

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.

Data envelopment analysis (DEA) methodology is used in this study for a comparison of the dynamic efficiency of European countries over the last decade. Moreover, efficiency analysis is used to determine where resources are distributed efficiently and/or were used efficiently/inefficiently under factors of competitiveness extracted from factor analysis. DEA measures numerical grades of the efficiency of economic processes within evaluated countries and, therefore, it becomes a suitable tool for setting an efficient/inefficient position of each country. Most importantly, the DEA technique is applied to all (28) European Union (EU) countries to evaluate their technical and technological efficiency within the selected factors of competitiveness based on country competitiveness index in the 2000-2017 reference period. The main aim of the paper is to measure efficiency changes over the reference period and to analyze the level of productivity in individual countries based on the Malmquist productivity index (MPI). Empirical results confirm significant disparities among European countries and selected periods 2000-2007, 2008-2011, and 2012-2017. Finally, the study offers a comprehensive comparison and discussion of results obtained by MPI that indicate the EU countries in which policy-making authorities should aim to stimulate national development and provide more quality of life to the EU citizens. [ABSTRACT FROM AUTHOR]

Economies have always been prone to different kinds of exogenous shocks, which can destabilize the path and pattern of regional economic growth. Regional economy perturbed by a shock may move onto a new growth path by re-establishing economic linkages, both internally and with other regions. The question why one region is more vulnerable to economic shock than other, impelled to analyze notion of resilience in a regional development context. Despite own limitations of quantitative methods, several approaches in the form of composite indices (CIs) have been proposed by the European Union (EU) and the other institutions. The aim of this paper is to throw light on some of the underlying aspects of regional resilience and provide an overview of a notion as well as analysis of research studies on constructing the territorial CIs. The main results of the paper are overview and comparison of regional resilience literature and empirics of existing CIs that lead to measuring the EU NUTS-2 regions resilience based on constructing own index. CIs construction includes several steps that have to be made and corresponding methods have to be chosen. Primarily, selection of sub-indicators, normalizing methods, weighting schemes and aggregation formulas are fundamental. [ABSTRACT FROM AUTHOR]

Research background: The European Union currently provides financial support to the Member States through various financial tools from European Structural and Investment Funds 2014-2020, and previously from the EU Structural Funds. In both terminologies, the funds represent the main instrument of EU Cohesion Policy to sustain territorial development, to increase competitiveness and to eliminate regional disparities. The overall impact of EU Funds depends on the structure of funding and absorption capacity of the country. Purpose of the article: The efficiency of funding across the EU Member States is a fundamental issue for EU development as a whole. The Author considers deter-mining the efficiency of EU Funds as an issue of high importance, and therefore this paper provides a contribution to the debate on the role of EU Cohesion Policy in the Member States. The paper focuses on territorial effects of relevant EU Funds in programming period 2007-2013 in infrastructure through efficiency analysis. Methods: Efficiency analysis is based on data at the country level, originating from ex-post evaluation of Cohesion Policy programmes 2007-2013 and representing the input and output variables to analyse whether the goal of fostering growth in the target countries have been achieved with the funds provided, and whether or not more resources generated stronger growth effects in transport accessibility. The paper deals with comparative cross-country analysis, descriptive analysis of dataset and multiple-criteria approach of Data Envelopment Analysis (DEA) in the form of output-oriented BCC VRS model of efficiency and outputoriented APM VRS subsequently model of super-efficiency. Findings & Value added: The paper aims to test the factors of two inputs and five outputs, trying to elucidate the differences obtained by the Member States in effective use of the European Regional Development Fund and the Cohesion Fund in the transport sector. The paper determines if the countries have been more efficient in increasing their levels of competitive advantages linked with transport. Preliminary results reveal that most countries with a lower amount of funding achieve higher efficiency, especially countries in a group of socalled "old EU Member States", i.e. group EU15. [ABSTRACT FROM AUTHOR]

For centuries, the "Blue Banana", metropolitan axis running from London to Milan, has been Europe's breeding place for innovation and growth. Recently, the "Sunbelt" from Milan to Valencia and the "Yellow Banana" from Paris to Warsaw have been identified as future European growth poles beside or even beyond the Blue Banana. Europe's competitiveness depends on a multiplicity of actions that can optimise the potentials within its territory, especially regions. Nowadays, regions are increasingly becoming the drivers of the economy. All regions possess development opportunities - however, use these options enough and hence the competitiveness of European regions must be efficient enough. It is well-known that there are significant differences among the European Union regions which weaken its competitiveness. What are differences in territorial efficiencies with respect to the structure of Europe's economic-geographical system? The paper is focused on using SBMT VRS DEA model for dividing NUTS 2 regions from geographic models of the European economy into efficient and inefficient ones. The main aim of the paper is to find the efficient frontier and identify optimal benchmark for inefficient regions as a strategy for enhancing their economic structure. [ABSTRACT FROM AUTHOR]