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A parametric frontier model for measuring eco-efficiency

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  • 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.

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  • 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
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    References listed on IDEAS

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    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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.
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