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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

Author

Listed:
  • Hongliang Yang

    (Judge Business School, University of Cambridge)

  • Michael Pollitt

    (Judge Business School, University of Cambridge)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hongliang Yang & Michael Pollitt, 2007. "Distinguishing Weak and Strong Disposability among Undesirable Outputs in DEA: The Example of the Environmental Efficiency of Chinese Coal-Fired Power Plants," Working Papers EPRG 0717, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg0717
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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. 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.
    3. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    4. 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.
    5. 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.
    6. Ather Hassan Dar & Somesh Kumar Mathur & Sila Mishra, 2021. "The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 653-701, December.
    7. Grebel, Thomas & Islam, Rohidul, 2022. "Endogenous cap reduction in Emission Trading Systems," Ilmenau Economics Discussion Papers 169, Ilmenau University of Technology, Institute of Economics.
    8. 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.

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    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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