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Distinguishing Weak and Strong Disposability among Undesirable Outputs in DEA: The Example of the Environmental Efficiency of Chinese Coal-Fired Power Plants

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Abstract

Different from traditional efficiency research and previous studies considering undesirable outputs, this paper proposes models which distinguish weak and strong disposability features among various undesirable outputs based on the technical nature of the undesirable outputs. The paper illustrates the approach using a research sample covering 582 base-load Chinese coal-fired power plants in 2002. Our final results show that (1) imposing the technically correct disposability features on undesirable outputs makes a significant difference to the final efficiency evaluation. This suggests the necessity of properly distinguishing disposability features among undesirable outputs in efficiency models; (2) compared to their US and European counterparts, Chinese power plants relatively waste more resources. This suggests a great urgency for the Chinese electricity industry to improve its efficiency in coal-fired electricity generation sector.

Suggested Citation

  • Yang, H. & Pollitt, M., 2007. "Distinguishing Weak and Strong Disposability among Undesirable Outputs in DEA: The Example of the Environmental Efficiency of Chinese Coal-Fired Power Plants," Cambridge Working Papers in Economics 0741, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0741
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    File URL: http://www.electricitypolicy.org.uk/pubs/wp/eprg0717.pdf
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    References listed on IDEAS

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    1. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
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    4. 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.
    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. Pittman, Russell W, 1983. "Multilateral Productivity Comparisons with Undesirable Outputs," Economic Journal, Royal Economic Society, vol. 93(372), pages 883-891, December.
    7. Patrick L. Brockett & Boaz Golany, 1996. "Using Rank Statistics for Determining Programmatic Efficiency Differences in Data Envelopment Analysis," Management Science, INFORMS, vol. 42(3), pages 466-472, March.
    8. 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.
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    Cited by:

    1. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    2. 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.
    3. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    4. Kaneko, Shinji & Fujii, Hidemichi & Sawazu, Naoya & Fujikura, Ryo, 2010. "Financial allocation strategy for the regional pollution abatement cost of reducing sulfur dioxide emissions in the thermal power sector in China," Energy Policy, Elsevier, vol. 38(5), pages 2131-2141, May.

    More about this item

    Keywords

    Economics: input-output analysis; Environment; Government: energy policies; Industries: electric; Statistics: nonparametric.;

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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