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Data Envelopment Analysis for Measuring of Economic Growth in Terms of Welfare Beyond GDP

Author

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  • Martin Lábaj

    (University of Economics in Bratislava, Faculty of National Economy, Department of Economic Policy)

  • Mikuláš Luptáèik

    (University of Economics in Bratislava, Faculty of National Economy, Department of Economic Policy)

  • Eduard Nežinský

    (University of Economics in Bratislava, Faculty of National Economy, Department of Economic Policy)

Abstract

Recent discussions on the definition of growth in terms of welfare beyond GDP suggest that it is of urgent need to develop new approaches for measuring the economic performance of the firms and national economies. The new concepts should take into account simultaneously economic as well as social and environmental goals. We first discuss several approaches to productivity measures. Then we extend the Data Envelopment Analysis models for environment to measure the so called eco-efficiency and for social indicators to take into account the social performance. For an illustration, we perform the analysis of 30 European countries in the year 2010. In the last section we discuss the possibilities of inter-temporal analysis of proposed models and of their use in ex-ante evaluation of different policy scenarios.

Suggested Citation

  • Martin Lábaj & Mikuláš Luptáèik & Eduard Nežinský, 2013. "Data Envelopment Analysis for Measuring of Economic Growth in Terms of Welfare Beyond GDP," Department of Economic Policy Working Paper Series 002, Department of Economic Policy, Faculty of National Economy, University of Economics in Bratislava.
    • Handle: RePEc:brt:depwps:002
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    1. Daniel Dujava, 2012. "Príčiny zaostávania nových členských krajín EÚ: empirická analýza na základe Montgomeryho dekompozície [Causes of Lagging Behind of New Member States of EU: Empirical Analysis by Montgomery Decompo," Politická ekonomie, Prague University of Economics and Business, vol. 2012(2), pages 222-244.
    2. Mahlberg, Bernhard & Luptacik, Mikulas & Sahoo, Biresh K., 2011. "Examining the drivers of total factor productivity change with an illustrative example of 14 EU countries," Ecological Economics, Elsevier, vol. 72(C), pages 60-69.
    3. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    4. Thijs ten Raa & Pierre Mohnen, 2009. "Neoclassical Growth Accounting and Frontier Analysis: A Synthesis," World Scientific Book Chapters, in: Input–Output Economics: Theory And Applications Featuring Asian Economies, chapter 19, pages 347-370, World Scientific Publishing Co. Pte. Ltd..
    5. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    6. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    7. Fare, Rolf & Grosskopf, Shawna & Tyteca, Daniel, 1996. "An activity analysis model of the environmental performance of firms--application to fossil-fuel-fired electric utilities," Ecological Economics, Elsevier, vol. 18(2), pages 161-175, August.
    8. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    9. 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.
    10. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    11. Zvi Griliches, 1996. "The Discovery of the Residual: A Historical Note," Journal of Economic Literature, American Economic Association, vol. 34(3), pages 1324-1330, September.
    12. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    13. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    14. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    15. Bosetti, Valentina & Buchner, Barbara, 2009. "Data Envelopment Analysis of different climate policy scenarios," Ecological Economics, Elsevier, vol. 68(5), pages 1340-1354, March.
    16. Daniel Tyteca, 1997. "Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results," Journal of Productivity Analysis, Springer, vol. 8(2), pages 183-197, May.
    17. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    18. Sarkis, Joseph & Cordeiro, James J., 2001. "An empirical evaluation of environmental efficiencies and firm performance: Pollution prevention versus end-of-pipe practice," European Journal of Operational Research, Elsevier, vol. 135(1), pages 102-113, November.
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    More about this item

    Keywords

    eco-efficiency; data envelopment analysis; beyond GDP;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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