IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/32934.html
   My bibliography  Save this paper

Measuring regional environmental efficiency: A directional distance function approach

Author

Listed:
  • Halkos, George
  • Tzeremes, Nickolaos

Abstract

This paper by applying a directional distance function approach measures the UK regions’ municipality waste performance. In addition the paper constructs conditional stochastic kernels trying to determine nonparametrically the association of regions’ GDP per capita levels with their calculated regional environmental efficiencies. There are evidences of regional environmental inefficiencies for the majority of UK regions regardless their regional GDP per capita levels.

Suggested Citation

  • Halkos, George & Tzeremes, Nickolaos, 2011. "Measuring regional environmental efficiency: A directional distance function approach," MPRA Paper 32934, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:32934
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/32934/1/MPRA_paper_32934.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rolf Färe & Shawna Grosskopf, 2007. "A Comment on Weak Disposability in Nonparametric Production Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(2), pages 535-538.
    2. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    3. Susmita Dasgupta & Benoit Laplante & Hua Wang & David Wheeler, 2002. "Confronting the Environmental Kuznets Curve," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 147-168, Winter.
    4. 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.
    5. Jeffrey Racine, 2008. "Nonparametric econometrics: a primer (in Russian)," Quantile, Quantile, issue 4, pages 7-56, March.
    6. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    7. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    8. Racine, Jeffrey S., 2008. "Nonparametric Econometrics: A Primer," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(1), pages 1-88, March.
    9. Zofio, Jose L. & Prieto, Angel M., 2001. "Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries," Resource and Energy Economics, Elsevier, vol. 23(1), pages 63-83, January.
    10. Timo Kuosmanen & Victor Podinovski, 2008. "Weak Disposability in Nonparametric Production Analysis: Reply to Färe and Grosskopf," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(2), pages 539-545.
    11. 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.
    12. Valentin Zelenyuk & Vitaliy Zheka, 2006. "Corporate Governance and Firm’s Efficiency: The Case of a Transitional Country, Ukraine," Journal of Productivity Analysis, Springer, vol. 25(1), pages 143-157, April.
    13. Fotopoulos, Georgios, 2006. "Nonparametric analysis of regional income dynamics: The case of Greece," Economics Letters, Elsevier, vol. 91(3), pages 450-457, June.
    14. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    15. 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.
    16. Rolf Färe & Shawna Grosskopf, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1070-1074.
    17. Atakelty Hailu, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1075-1077.
    18. Poletti Laurini, Márcio & Valls Pereira, Pedro L., 2009. "Conditional stochastic kernel estimation by nonparametric methods," Economics Letters, Elsevier, vol. 105(3), pages 234-238, December.
    19. 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.
    Full references (including those not matched with items on IDEAS)

    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. George Halkos & Nickolaos Tzeremes, 2012. "Measuring German regions’ environmental efficiency: a directional distance function approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(1), pages 7-16, March.
    2. Halkos, George & Tzeremes, Nickolaos, 2011. "Regional environmental efficiency and economic growth: NUTS2 evidence from Germany, France and the UK," MPRA Paper 33698, University Library of Munich, Germany.
    3. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    4. Halkos, George & Tzeremes, Nickolaos, 2011. "Kuznets curve and environmental performance: evidence from China," MPRA Paper 34312, University Library of Munich, Germany.
    5. George Halkos & Nickolaos Tzeremes, 2013. "National culture and eco-efficiency: an application of conditional partial nonparametric frontiers," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 15(4), pages 423-441, October.
    6. George Halkos & George Papageorgiou, 2016. "Spatial environmental efficiency indicators in regional waste generation: a nonparametric approach," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(1), pages 62-78, January.
    7. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    8. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "Public sector transparency and countries’ environmental performance: A nonparametric analysis," Resource and Energy Economics, Elsevier, vol. 38(C), pages 19-37.
    9. Halkos, George & Sundström, Aksel & Tzeremes, Nickolaos, 2013. "Environmental performance and quality of governance: A non-parametric analysis of the NUTS 1-regions in France, Germany and the UK," MPRA Paper 48890, University Library of Munich, Germany.
    10. George Halkos & Nickolaos Tzeremes, 2014. "Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO 2 emissions: an application of conditional full frontiers," Journal of Productivity Analysis, Springer, vol. 41(3), pages 367-382, June.
    11. Halkos, George & Tzeremes, Nickolaos, 2012. "Regional economic growth and environmental efficiency in greenhouse emissions: A conditional directional distance function approach," MPRA Paper 40015, University Library of Munich, Germany.
    12. Halkos, George & Tzeremes, Nickolaos, 2013. "An additive two-stage DEA approach creating sustainability efficiency indexes," MPRA Paper 44231, University Library of Munich, Germany.
    13. 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.
    14. Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier modelling for analyzing environmental efficiency and economic growth," MPRA Paper 32839, University Library of Munich, Germany.
    15. Makiko Nakano & Shunsuke Managi, 2012. "Waste generations and efficiency measures in Japan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 14(4), pages 327-339, October.
    16. 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.
    17. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    18. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.
    19. Skevas, Theodoros & Lansink, Alfons Oude & Stefanou, Spiro E., 2012. "Measuring technical efficiency in the presence of pesticide spillovers and production uncertainty: The case of Dutch arable farms," European Journal of Operational Research, Elsevier, vol. 223(2), pages 550-559.
    20. Halkos, George & Polemis, Michael, 2016. "The good, the bad and the ugly? Balancing environmental and economic impacts towards efficiency," MPRA Paper 72132, University Library of Munich, Germany.

    More about this item

    Keywords

    Regional environmental performance; Directional distance function; Conditional stochastic kernel;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:32934. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.