IDEAS home Printed from https://ideas.repec.org/a/eee/ecolec/v195y2022ics0921800922000398.html
   My bibliography  Save this article

Heterogeneity, spillovers and eco-efficiency of European industries under different pollutants’ scenarios. Is there a definite direction?

Author

Listed:
  • Stergiou, Eirini
  • Kounetas, Konstantinos

Abstract

Eco-efficiency is the ability to create more goods and services with less impact on the environment while it consists a dominant strategy for the European Union in view of the New Green Deal. In recent years, its assessment, especially for the manufacturing sector, has attracted the interest of policymakers as a strategy in the pursuit of sustainability. However, a clear-cut direction on which industries should follow does not exist. In this applied study, we estimate distinct objectives of economic and ecological performance, introducing diverse scenarios regarding specific environmental pressures, by utilizing directional distance functions under a metafrontier framework. The methodology is implemented to a sample of 14 industries from the manufacturing sector from 27 European countries over the period 1995–2011. Our results reveal that the existence of a unified production technology set causes large differences in the eco-efficiency levels of the manufacturing sector while energy intensive industries can be characterized as the most eco-inefficient. Although the speed of industrial eco-efficiency convergence increases throughout the years, the case of CO2 emissions presents an irregular behavior compared to the other greenhouse gases and air pollutants. Thus, a decomposition analysis of the manufacturing CO2 emissions is considered as a further subject of interest in the study.

Suggested Citation

  • Stergiou, Eirini & Kounetas, Konstantinos, 2022. "Heterogeneity, spillovers and eco-efficiency of European industries under different pollutants’ scenarios. Is there a definite direction?," Ecological Economics, Elsevier, vol. 195(C).
  • Handle: RePEc:eee:ecolec:v:195:y:2022:i:c:s0921800922000398
    DOI: 10.1016/j.ecolecon.2022.107377
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0921800922000398
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolecon.2022.107377?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    3. Mercedes Beltrán-Esteve & José Gómez-Limón & Andrés Picazo-Tadeo & Ernest Reig-Martínez, 2014. "A metafrontier directional distance function approach to assessing eco-efficiency," Journal of Productivity Analysis, Springer, vol. 41(1), pages 69-83, February.
    4. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    5. Kounetas, Konstantinos Elias, 2018. "Energy consumption and CO2 emissions convergence in European Union member countries. A tonneau des Danaides?," Energy Economics, Elsevier, vol. 69(C), pages 111-127.
    6. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2020. "Fast and efficient computation of directional distance estimators," Annals of Operations Research, Springer, vol. 288(2), pages 805-835, May.
    7. Joachim Schleich & Wolfgang Eichhammer & Ulla Boede & Frank Gagelmann & Eberhard Jochem & Barbara Schlomann & Hans-Joachim Ziesing, 2001. "Greenhouse gas reductions in Germany-lucky strike or hard work?," Climate Policy, Taylor & Francis Journals, vol. 1(3), pages 363-380, September.
    8. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    9. Martin Carree & Luuk Klomp, 1997. "Testing The Convergence Hypothesis: A Comment," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 683-686, November.
    10. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas & Broadstock, David C., 2016. "Spillovers, path dependence and the productive performance of European transportation sectors in the presence of technology heterogeneity," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 261-274.
    11. Eric Bartelsman & John Haltiwanger & Stefano Scarpetta, 2013. "Cross-Country Differences in Productivity: The Role of Allocation and Selection," American Economic Review, American Economic Association, vol. 103(1), pages 305-334, February.
    12. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Efficiency and economies of scale and specialization in European universities: A directional distance approach," Journal of Informetrics, Elsevier, vol. 9(3), pages 430-448.
    13. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    14. Kounetas, Konstantinos, 2015. "Heterogeneous technologies, strategic groups and environmental efficiency technology gaps for European countries," Energy Policy, Elsevier, vol. 83(C), pages 277-287.
    15. Quah, Danny, 1993. "Empirical cross-section dynamics in economic growth," European Economic Review, Elsevier, vol. 37(2-3), pages 426-434, April.
    16. Štreimikienė, Dalia & Balezentis, Tomas, 2016. "Kaya identity for analysis of the main drivers of GHG emissions and feasibility to implement EU “20–20–20” targets in the Baltic States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1108-1113.
    17. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    18. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
    19. Casu, Barbara & Ferrari, Alessandra & Girardone, Claudia & Wilson, John O.S., 2016. "Integration, productivity and technological spillovers: Evidence for eurozone banking industries," European Journal of Operational Research, Elsevier, vol. 255(3), pages 971-983.
    20. 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.
    21. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    22. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    23. Yantuan Yu & Hui Hu & Yun Zhang & Zhujia Yin, 2019. "Metafrontier Eco-Efficiency and Its Convergence Analysis for China: A Multidimensional Heterogeneity Perspective," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(7), pages 1531-1549, May.
    24. Timo Kuosmanen & Mika Kortelainen, 2005. "Measuring Eco‐efficiency of Production with Data Envelopment Analysis," Journal of Industrial Ecology, Yale University, vol. 9(4), pages 59-72, October.
    25. Mariam Camarero & Juana Castillo & Andrés Picazo-Tadeo & Cecilio Tamarit, 2013. "Eco-Efficiency and Convergence in OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(1), pages 87-106, May.
    26. Treffers, D. J. & Faaij, A. P. C. & Spakman, J. & Seebregts, A., 2005. "Exploring the possibilities for setting up sustainable energy systems for the long term: two visions for the Dutch energy system in 2050," Energy Policy, Elsevier, vol. 33(13), pages 1723-1743, September.
    27. Eirini Stergiou and Kostas Kounetas, 2021. "European Industries' Energy Efficiency under Different Technological Regimes: The Role of CO2 Emissions, Climate, Path Dependence and Energy Mix," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 93-128.
    28. Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
    29. 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.
    30. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    31. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    32. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    33. Mika Kortelainen & Timo Kuosmanen, 2004. "Measuring Eco-efficiency of Production: A Frontier Approach," Econometrics 0411006, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stergiou, Eirini & Rigas, Nikos & Kounetas, Konstantinos E., 2023. "Environmental productivity growth across European industries," Energy Economics, Elsevier, vol. 123(C).
    2. Stergiou, Eirini, 2022. "Environmental Efficiency of European Industries across Sectors and Countries," MPRA Paper 114635, University Library of Munich, Germany.
    3. Salman, Muhammad & Long, Xingle & Wang, Guimei & Zha, Donglan, 2022. "Paris climate agreement and global environmental efficiency: New evidence from fuzzy regression discontinuity design," Energy Policy, Elsevier, vol. 168(C).
    4. Sovacool, Benjamin K. & Baum, Chad M. & Low, Sean, 2023. "Beyond climate stabilization: Exploring the perceived sociotechnical co-impacts of carbon removal and solar geoengineering," Ecological Economics, Elsevier, vol. 204(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kounetas, Konstantinos & Stergiou, Eirini, 2020. "European industrial eco-efficiency under different pollutants' scenarios and heterogeneity structures. Is there a definite direction?," MPRA Paper 98583, University Library of Munich, Germany.
    2. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Examining eco-efficiency convergence of European Industries.The existence of technological spillovers within a metafrontier framework," MPRA Paper 94286, University Library of Munich, Germany.
    3. 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.
    4. Picazo-Tadeo, Andrés J. & Castillo-Giménez, Juana & Beltrán-Esteve, Mercedes, 2014. "An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union," Ecological Economics, Elsevier, vol. 100(C), pages 173-182.
    5. Mercedes Beltrán-Esteve & José Gómez-Limón & Andrés Picazo-Tadeo & Ernest Reig-Martínez, 2014. "A metafrontier directional distance function approach to assessing eco-efficiency," Journal of Productivity Analysis, Springer, vol. 41(1), pages 69-83, February.
    6. Bonasia, Mariangela & Kounetas, Konstantinos & Oreste, Napolitano, 2020. "Assessment of regional productive performance of European health systems under a metatechnology framework," Economic Modelling, Elsevier, vol. 84(C), pages 234-248.
    7. Andrés J. Picazo-Tadeo & Juana Castillo & Mercedes Beltrán-Esteve, 2013. "A dynamic approach to measuring ecological-economic performance with directional distance functions: greenhouse gas emissions in the European Union," Working Papers 1304, Department of Applied Economics II, Universidad de Valencia.
    8. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2015. "Assessing environmental performance trends in the transport industry: Eco-innovation or catching-up?," Energy Economics, Elsevier, vol. 51(C), pages 570-580.
    9. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Technology heterogeneity in European industries' energy efficiency performance. The role of climate, greenhouse gases, path dependence and energy mix," MPRA Paper 92314, University Library of Munich, Germany.
    10. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    11. Yu, Yantuan & Huang, Jianhuan & Zhang, Ning, 2019. "Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective," Ecological Modelling, Elsevier, vol. 402(C), pages 1-17.
    12. Nikolaos, Chatzistamoulou & Theodoros, Antonakis & Konstantinos, Kounetas, 2020. "Salary cap and National Basketball Association teams' productive performance. A two stage Data Envelopment Analysis approach under a metatechnology framework," MPRA Paper 98811, University Library of Munich, Germany.
    13. Alfredsson, Eva & Månsson, Jonas & Vikström, Peter, 2016. "Internalising external environmental effects in efficiency analysis," Economic Analysis and Policy, Elsevier, vol. 51(C), pages 22-31.
    14. Xiangxiang Sun & Lawrence Loh, 2019. "Sustainability Governance in China: An Analysis of Regional Ecological Efficiency," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    15. Colesnic, Olga & Kounetas, Konstantinos & Michael, Polemis, 2020. "Estimating risk efficiency in Middle East banks before and after the crisis: A metafrontier framework," Global Finance Journal, Elsevier, vol. 46(C).
    16. Napolitano, Oreste & Foresti, Pasquale & Kounetas, Konstantinos & Spagnolo, Nicola, 2023. "The impact of energy, renewable and CO2 emissions efficiency on countries’ productivity," Energy Economics, Elsevier, vol. 125(C).
    17. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
    18. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    19. Yu, Yantuan & Peng, Chong & Li, Yushuang, 2019. "Do neighboring prefectures matter in promoting eco-efficiency? Empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 456-465.
    20. Nikos Chatzistamoulou & Kounetas Kostas & Antonakis Theodor, 2022. "Salary Cap, Organizational Gap, and Catch-up in the Performance of NBA Teams: A Two-Stage DEA Model Under Heterogeneity," Journal of Sports Economics, , vol. 23(2), pages 123-155, February.

    More about this item

    Keywords

    Industries; Eco-efficiency; Metafrontier; Spillovers; Catch-up; Kaya identity;
    All these keywords.

    JEL classification:

    • D29 - Microeconomics - - Production and Organizations - - - Other
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolec:v:195:y:2022:i:c:s0921800922000398. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolecon .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.