The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.
<p>[1] P. Annoni and K. Kozovska, EU Regional Competitiveness Index 2010. Luxembourg: Publica-tion Office of the European Union, 2010. [2] P. Andersen and N.C. Petersen, ÔÇ£A procedure for ranking efficient units in data envelopment analysis, ÔÇØ Management Science, vol. 10, no. 39, pp. 1261-1264, 1993. [3] R. Barrell, G. Mason, and M. O'Mahony, Productivity, Innovation and Economic Growth. Cambridge: Cambridge University Press, 2000. [4] A. Charnes, W. Cooper and E. Rhodes, ÔÇ£Measuring the efficiency of decision making units, ÔÇØ European Journal of Operational Research, vol. 6, no. 2, pp. 429-444, 1978. [5] R. F├ñre et al., Production Frontiers. Cambridge: University Press, 1994. [6] M.J. Farrell, ÔÇ£The measurement of productivity efficiency, ÔÇØ Journal of the Royal Statistical Society, vol. 3, no. 120, pp. 253-290, 1957. [7] J. Han─ìlov├í, ÔÇ£The Effects of Domestics and External Shocks on a Small Open Country: the Evidence from the Czech Economy,ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no 2, pp. 366-375, Feb. 2012. [8] D. Greenaway, H. G├Ârg and R. Kneller, Globalization and Productivity. Cheltenham: Edward Elgar Publishing Limited, 2008. [9] U. Mandl, A. Dierx and F. Ilzkovitz, The effectiveness and efficiency of public spending. Brussels: European Commission-Directorate General for Economic and Financial Affairs, 2008. [10] L. Meleck├¢, ÔÇ£Evaluation of Cohesion in Visegrad Countries in Comparison with Germany and Austria by Multivariate Methods for Disparities Measurement, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no. 8, pp. 979-989, Dec. 2012. [11] L. Meleck├¢ and M. Stan├¡─ìkov├í, ÔÇ£The Competitiveness of Visegrad Four NUTS 2 Regions and its Evaluation by DEA Method Application, ÔÇØ in Proc. 29th Inter. Conf. on Mathematical Methods in Economics, Prague, 2011, pp. 474-479. [12] L. Meleck├¢ and M. Stan├¡─ìkov├í, ÔÇ£National Efficiency Evaluation of Visegrad Countries in Comparison with Austria and Germany by Selected DEA Models, ÔÇØ in Proc. 30th Inter. Conf. on Mathematical Methods in Economics, Karvin├í, 2012, pp. 575-580. [13] D.M. Mihaiu, A. Opreana and M.P. Cristescu, ÔÇ£Efficiency, effectiveness and performance of the public sector, ÔÇØ Romanian Journal of Economic Forecasting, vol. 4, no.1, pp. 132-147, 2010. [14] A. Mohammadi and H. Ranaei, ÔÇ£The application of DEA based Malmquist productivity index in organizational performance analysis, ÔÇØ International Research Journal of Finance and Economics, vol. 62, no. 6, pp. 68-76, 2011 [15] W. Molle, European Cohesion Policy. London: Routledge, 2007. [16] M. Stan├¡─ìkov├í and K. Skokan, ÔÇ£Evaluation of the EU Member States Efficiency by Data Envelopment Analysis Method, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no. 2, pp. 349-357, Feb. 2012. [17] M. Stan├¡─ìkov├í and K. Skokan, ÔÇ£Multidimensional Approach to Assessment of Performance in Selected EU Member States, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 7, no. 1, pp. 1-13, Jan. 2013.</p>
<p>[1] P. Annoni and K. Kozovska, EU Regional Competitiveness Index 2010. Luxembourg: Publica-tion Office of the European Union, 2010. [2] P. Andersen and N.C. Petersen, ÔÇ£A procedure for ranking efficient units in data envelopment analysis, ÔÇØ Management Science, vol. 10, no. 39, pp. 1261-1264, 1993. [3] R. Barrell, G. Mason, and M. O'Mahony, Productivity, Innovation and Economic Growth. Cambridge: Cambridge University Press, 2000. [4] A. Charnes, W. Cooper and E. Rhodes, ÔÇ£Measuring the efficiency of decision making units, ÔÇØ European Journal of Operational Research, vol. 6, no. 2, pp. 429-444, 1978. [5] R. F├ñre et al., Production Frontiers. Cambridge: University Press, 1994. [6] M.J. Farrell, ÔÇ£The measurement of productivity efficiency, ÔÇØ Journal of the Royal Statistical Society, vol. 3, no. 120, pp. 253-290, 1957. [7] J. Han─ìlov├í, ÔÇ£The Effects of Domestics and External Shocks on a Small Open Country: the Evidence from the Czech Economy,ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no 2, pp. 366-375, Feb. 2012. [8] D. Greenaway, H. G├Ârg and R. Kneller, Globalization and Productivity. Cheltenham: Edward Elgar Publishing Limited, 2008. [9] U. Mandl, A. Dierx and F. Ilzkovitz, The effectiveness and efficiency of public spending. Brussels: European Commission-Directorate General for Economic and Financial Affairs, 2008. [10] L. Meleck├¢, ÔÇ£Evaluation of Cohesion in Visegrad Countries in Comparison with Germany and Austria by Multivariate Methods for Disparities Measurement, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no. 8, pp. 979-989, Dec. 2012. [11] L. Meleck├¢ and M. Stan├¡─ìkov├í, ÔÇ£The Competitiveness of Visegrad Four NUTS 2 Regions and its Evaluation by DEA Method Application, ÔÇØ in Proc. 29th Inter. Conf. on Mathematical Methods in Economics, Prague, 2011, pp. 474-479. [12] L. Meleck├¢ and M. Stan├¡─ìkov├í, ÔÇ£National Efficiency Evaluation of Visegrad Countries in Comparison with Austria and Germany by Selected DEA Models, ÔÇØ in Proc. 30th Inter. Conf. on Mathematical Methods in Economics, Karvin├í, 2012, pp. 575-580. [13] D.M. Mihaiu, A. Opreana and M.P. Cristescu, ÔÇ£Efficiency, effectiveness and performance of the public sector, ÔÇØ Romanian Journal of Economic Forecasting, vol. 4, no.1, pp. 132-147, 2010. [14] A. Mohammadi and H. Ranaei, ÔÇ£The application of DEA based Malmquist productivity index in organizational performance analysis, ÔÇØ International Research Journal of Finance and Economics, vol. 62, no. 6, pp. 68-76, 2011 [15] W. Molle, European Cohesion Policy. London: Routledge, 2007. [16] M. Stan├¡─ìkov├í and K. Skokan, ÔÇ£Evaluation of the EU Member States Efficiency by Data Envelopment Analysis Method, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 6, no. 2, pp. 349-357, Feb. 2012. [17] M. Stan├¡─ìkov├í and K. Skokan, ÔÇ£Multidimensional Approach to Assessment of Performance in Selected EU Member States, ÔÇØ International Journal of Mathematical Models and Methods in Applied Sciences, vol. 7, no. 1, pp. 1-13, Jan. 2013.</p>
@article{"International Journal of Business, Human and Social Sciences:49257", author = "M. Staníčková", title = "DEA Method for Evaluation of EU Performance", abstract = "The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.
", keywords = "CCR CRS model, cluster analysis, DEA method, efficiency, EU, Malmquist index, performance.", volume = "7", number = "6", pages = "1337-7", }
