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The analysis of convergence process of voivodships’ efficiency in Poland using the DEA metod

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  • Dariusz Wozniak

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  • Piotr Czarnecki
  • Robert Szarota
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    Abstract

    Since 1999 – when the new administrative division in Poland was introduced – it has been possible to measure and compare standard of living between Polish and other European regions (NUTS II). In 2004 Poland has joined the European Union. Since that year voivodships have become main beneficiaries of the EU funds. The essential part of that aid is related to the EU cohesion policy (convergence objective). According to the fifth cohesion report “cohesion policy has made a significant contribution to spreading growth and prosperity across the Union, while reducing economic, social and territorial disparitiesâ€. However, the differences in standard of living still remains significant between countries as well as between regions within one country. In many researches the level of welfare is measured using “classic†indicators (GDP per capita, GNI per capita, unemployment rate, etc.). In this paper the authors focus on the regional economies’ efficiency. The efficiency will be measured using the Data Envelopment Analysis. Due to the method used, the efficiency will be measured as relative in nature, i.e. will be compared between voivodships within the period of research. The goal of the paper is to analyze variety of relative voivodships’ efficiency in order to answer the question if the dispersion in efficiency is increasing or decreasing over time.

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    Bibliographic Info

    Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa11p925.

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    Date of creation: Sep 2011
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    Handle: RePEc:wiw:wiwrsa:ersa11p925

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    1. Andrew T. Young & Matthew J. Higgins & Daniel Levy, 2008. "Sigma Convergence versus Beta Convergence: Evidence from U.S. County-Level Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(5), pages 1083-1093, 08.
    2. Mankiw, N Gregory & Romer, David & Weil, David N, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 407-37, May.
    3. K. M. Matawie & A. Assaf, 2010. "Bayesian and DEA efficiency modelling: an application to hospital foodservice operations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 945-953.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Brockett, P. L. & Charnes, A. & Cooper, W. W. & Huang, Z. M. & Sun, D. B., 1997. "Data transformations in DEA cone ratio envelopment approaches for monitoring bank performances," European Journal of Operational Research, Elsevier, vol. 98(2), pages 250-268, April.
    6. Friedman, Milton, 1992. "Do Old Fallacies Ever Die?," Journal of Economic Literature, American Economic Association, vol. 30(4), pages 2129-32, December.
    7. Mustafa Dinc & Kingsley E. Haynes & Murat Tarimcilar, 2003. "Integrating models for regional development decisions: A policy perspective," The Annals of Regional Science, Springer, vol. 37(1), pages 31-53, 02.
    8. George Petrakos & Andres Rodríguez-Pose & Antonis Rovolis, 2003. "Growth, Integration and Regional Inequality in Europe," ERSA conference papers ersa03p46, European Regional Science Association.
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