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Technical Efficiency and Productivity Change in the European Union with Undesirable Output Considered

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  • Djula Borozan

    (Faculty of Economics in Osijek, Josip Juraj Strossmayer University of Osijek, Gajev trg 7, 31000 Osijek, Croatia)

Abstract

Global competition and climate change are changing the nature of economic activity and impose the urgent need to have environmentally sensitive productivity growth. The paper addresses both desirable and undesirable output to assess technical efficiency and productivity changes, as well as evaluate the importance of an energy input in the production function and productivity change differentials in the European Union (EU) over the period 2000–2018. To that end, it uses output-oriented data envelopment analysis and Malmquist productivity analysis. The results reveal that the EU is facing significant challenges due to a decreasing trend in technical efficiency and slow productivity growth. The absence of major improvements in human resource performance has reduced the benefits of technological innovations which are the main source of productivity growth. Additionally, the results show that energy use did not critically influence efficiency and productivity.

Suggested Citation

  • Djula Borozan, 2021. "Technical Efficiency and Productivity Change in the European Union with Undesirable Output Considered," Energies, MDPI, vol. 14(16), pages 1-15, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4937-:d:613030
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    1. 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.
    2. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    3. Kortelainen, Mika, 2008. "Dynamic environmental performance analysis: A Malmquist index approach," Ecological Economics, Elsevier, vol. 64(4), pages 701-715, February.
    4. Gu, Wulong & Willox, Michael & Hussain , Jakir, 2019. "Environmentally Adjusted Multifactor Productivity Growth for the Canadian Manufacturing Sector," Analytical Studies Branch Research Paper Series 2019013e, Statistics Canada, Analytical Studies Branch.
    5. 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.
    6. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    7. Marian Chertow & Weslynne Ashton & Juan Espinosa, 2008. "Industrial Symbiosis in Puerto Rico: Environmentally Related Agglomeration Economies," Regional Studies, Taylor & Francis Journals, vol. 42(10), pages 1299-1312.
    8. Agnieszka Gehringer & Inmaculada Martinez-Zarzoso & Felicitas Nowak.Lehmann Danziger, 2013. "The Determinants of Total Factor Productivity in the EU: Insights from Sectoral Data and Common Dynamic Processes," EcoMod2013 5343, EcoMod.
    9. Shen, Zhiyang & Boussemart, Jean-Philippe & Leleu, Hervé, 2017. "Aggregate green productivity growth in OECD’s countries," International Journal of Production Economics, Elsevier, vol. 189(C), pages 30-39.
    10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    11. Bruce Morley, 2012. "Empirical evidence on the effectiveness of environmental taxes," Applied Economics Letters, Taylor & Francis Journals, vol. 19(18), pages 1817-1820, December.
    12. Nela Vlahinic Lenz & Alemka egota & Dario Maradin, 2018. "Total-factor Energy Efficiency in EU: Do Environmental Impacts Matter?," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 92-96.
    13. Woo, Chungwon & Chung, Yanghon & Chun, Dongphil & Seo, Hangyeol & Hong, Sungjun, 2015. "The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 367-376.
    14. Djula Borozan, 2018. "Efficiency of Energy Taxes and the Validity of the Residential Electricity Environmental Kuznets Curve in the European Union," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    15. Jiayu Wang & Ke Wang & Xunpeng Shi & Yi-Ming Wei, 2019. "Spatial heterogeneity and driving forces of environmental productivity growth in China: Would it help to switch pollutant discharge fees to environmental taxes?," CEEP-BIT Working Papers 123, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    16. Hasneen Jahan & Tiho Ancev, 2017. "Environmentally adjusted efficiency of shrimp farming in Bangladesh," Chapters, in: Tihomir Ancev & M. A.S. Azad & Francesc Hernández-Sancho (ed.), New Directions in Productivity Measurement and Efficiency Analysis, chapter 12, pages 249-274, Edward Elgar Publishing.
    17. Evangelia Desli, 2009. "Convergence and efficiency: evidence from the EU-15," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 31(3), pages 403-430, April.
    18. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    19. David I. Stern and Astrid Kander, 2012. "The Role of Energy in the Industrial Revolution and Modern Economic Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    20. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    21. Duman, Yavuz Selman & Kasman, Adnan, 2018. "Environmental technical efficiency in EU member and candidate countries: A parametric hyperbolic distance function approach," Energy, Elsevier, vol. 147(C), pages 297-307.
    22. Sun, Huaping & Kporsu, Anthony Kwaku & Taghizadeh-Hesary, Farhad & Edziah, Bless Kofi, 2020. "Estimating environmental efficiency and convergence: 1980 to 2016," Energy, Elsevier, vol. 208(C).
    23. 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.
    24. Nela Vlahinic-Dizdarevic & Alemka Segota, 2012. "Total-factor energy efficiency in the EU countries," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 30(2), pages 247-265.
    25. Lozano, Sebastián & Gutiérrez, Ester, 2008. "Non-parametric frontier approach to modelling the relationships among population, GDP, energy consumption and CO2 emissions," Ecological Economics, Elsevier, vol. 66(4), pages 687-699, July.
    26. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    27. Jin-chi Hsieh & Ching-cheng Lu & Ying Li & Yung-ho Chiu & Ya-sue Xu, 2019. "Environmental Assessment of European Union Countries," Energies, MDPI, vol. 12(2), pages 1-18, January.
    28. Zhongsheng Hua & Yiwen Bian, 2007. "DEA with Undesirable Factors," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 103-121, Springer.
    29. Tiho Ancev & M.A. Samad Azad & Mahmuda Akter, 2017. "Environmentally adjusted productivity and efficiency: a review of concepts, methods and empirical work," Chapters, in: Tihomir Ancev & M. A.S. Azad & Francesc Hernández-Sancho (ed.), New Directions in Productivity Measurement and Efficiency Analysis, chapter 2, pages 9-58, Edward Elgar Publishing.
    30. Parmeter, Christopher F. & Kumbhakar, Subal C., 2014. "Efficiency Analysis: A Primer on Recent Advances," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(3-4), pages 191-385, December.
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    Cited by:

    1. Djula Borozan & Dubravka Pekanov Starcevic, 2021. "Analysing the Pattern of Productivity Change in the European Energy Industry," Sustainability, MDPI, vol. 13(21), pages 1-14, October.

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