IDEAS home Printed from https://ideas.repec.org/p/oeg/wpaper/2015-02.html
   My bibliography  Save this paper

A parametric frontier model for measuring eco-efficiency

Author

Listed:
  • Orea, Luis
  • Wall, Alan

Abstract

Eco-efficiency has been defined by the OECD as “the efficiency with which ecological resources are used to meet human needs” and can be considered a measure of environmental performance that takes into account both the environmental and economic objectives of firms. Frontier models are an ideal tool for measuring eco-efficiency. While the literature applying frontier models to the empirical measurement of eco-efficiency has been growing steadily in recent years, it has exclusively relied on non-parametric Data Envelopment Analysis (DEA) methods to measure eco-efficiency and its determinants. We propose a parametric Stochastic Frontier (SF) model to measure eco-efficiency, arguing that this has several potential advantages. We provide an empirical application using cross-sectional data from Spanish dairy farms which includes information on environmental and economic indicators as well as a series of potential socio-economic determinants of eco-efficiency.

Suggested Citation

  • Orea, Luis & Wall, Alan, 2015. "A parametric frontier model for measuring eco-efficiency," Efficiency Series Papers 2015/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
  • Handle: RePEc:oeg:wpaper:2015/02
    as

    Download full text from publisher

    File URL: https://www.unioviedo.es/oeg/ESP/esp_2015_02.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Andrés J. Picazo-Tadeo & José A. Gómez-Limón & Ernest Reig-Martínez, 2010. "Assessing farming eco-efficiency: A Data Envelopment Analysis approach," Working Papers 1004, Department of Applied Economics II, Universidad de Valencia.
    2. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    3. Alfons Oude Lansink & Alan Wall, 2014. "Frontier models for evaluating environmental efficiency: an overview," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 43-50.
    4. 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.
    5. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    7. Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
    8. María Pérez Urdiales & Alfons Oude Lansink & Alan Wall, 2016. "Eco-efficiency Among Dairy Farmers: The Importance of Socio-economic Characteristics and Farmer Attitudes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(4), pages 559-574, August.
    9. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    10. Subal Kumbhakar & Frank Asche & Ragnar Tveteras, 2013. "Estimation and decomposition of inefficiency when producers maximize return to the outlay: an application to Norwegian fishing trawlers," Journal of Productivity Analysis, Springer, vol. 40(3), pages 307-321, December.
    11. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    12. Ray, Subhash C., 1988. "Data envelopment analysis, nondiscretionary inputs and efficiency: an alternative interpretation," Socio-Economic Planning Sciences, Elsevier, vol. 22(4), pages 167-176.
    13. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    14. Lauwers, Ludwig, 2009. "Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models," Ecological Economics, Elsevier, vol. 68(6), pages 1605-1614, April.
    15. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    16. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:oeg:wpaper:2015/02. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Luis Orea) or (Alberto Gude). General contact details of provider: http://edirc.repec.org/data/geovies.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.