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Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis

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  • Du, Limin
  • Hanley, Aoife
  • Zhang, Ning

Abstract

In this paper, we propose a new meta-frontier estimation method to investigate the environmental technical efficiency and carbon abatement cost of power plants in China taking the technological heterogeneities into consideration. This study is based on a plant-level cross-sectional data set comprising 648 observations for the year 2008. Results show that, state-owned power plants are least efficient relative to the meta-frontier. A further 44 percent of total CO2 emissions can be cut if all power plants are completely efficient. Additionally, the group of state-owned power plants is faced with the lowest cost to marginal CO2 abatement.

Suggested Citation

  • Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    • Handle: RePEc:eee:resene:v:43:y:2016:i:c:p:14-32
    DOI: 10.1016/j.reseneeco.2015.11.001
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    1. Gale Boyd & George Tolley & Joseph Pang, 2002. "Plant Level Productivity, Efficiency, and Environmental Performance of the Container Glass Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(1), pages 29-43, September.
    2. Zhao, Xiaoli & Ma, Chunbo, 2013. "Deregulation, vertical unbundling and the performance of China's large coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 474-483.
    3. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    4. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    5. 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.
    6. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    7. Barbara Casu & Alessandra Ferrari & Tianshu Zhao, 2013. "Regulatory Reform and Productivity Change in Indian Banking," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 1066-1077, July.
    8. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations," Energy Economics, Elsevier, vol. 40(C), pages 370-382.
    9. Lee, Myunghun & Zhang, Ning, 2012. "Technical efficiency, shadow price of carbon dioxide emissions, and substitutability for energy in the Chinese manufacturing industries," Energy Economics, Elsevier, vol. 34(5), pages 1492-1497.
    10. Víctor Moreira & Boris Bravo-Ureta, 2010. "Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model," Journal of Productivity Analysis, Springer, vol. 33(1), pages 33-45, February.
    11. Du, Limin & He, Yanan & Yan, Jianye, 2013. "The effects of electricity reforms on productivity and efficiency of China's fossil-fired power plants: An empirical analysis," Energy Economics, Elsevier, vol. 40(C), pages 804-812.
    12. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    13. Wei, Chu & Löschel, Andreas & Liu, Bing, 2013. "An empirical analysis of the CO2 shadow price in Chinese thermal power enterprises," Energy Economics, Elsevier, vol. 40(C), pages 22-31.
    14. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    15. M. Murty & Surender Kumar & Kishore Dhavala, 2007. "Measuring environmental efficiency of industry: a case study of thermal power generation in India," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(1), pages 31-50, September.
    16. 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.
    17. Kira R. Fabrizio & Nancy L. Rose & Catherine D. Wolfram, 2007. "Do Markets Reduce Costs? Assessing the Impact of Regulatory Restructuring on US Electric Generation Efficiency," American Economic Review, American Economic Association, vol. 97(4), pages 1250-1277, September.
    18. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    19. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    20. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    21. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "A comparative study among fossil fuel power plants in PJM and California ISO by DEA environmental assessment," Energy Economics, Elsevier, vol. 40(C), pages 130-145.
    22. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    23. Zhang, Ning & Wang, Bing, 2015. "A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case," Energy Economics, Elsevier, vol. 51(C), pages 88-98.
    24. Oh, Dong-hyun, 2010. "A metafrontier approach for measuring an environmentally sensitive productivity growth index," Energy Economics, Elsevier, vol. 32(1), pages 146-157, January.
    25. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    26. Ma, Jinlong, 2011. "On-grid electricity tariffs in China: Development, reform and prospects," Energy Policy, Elsevier, vol. 39(5), pages 2633-2645, May.
    27. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    28. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    29. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    30. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    31. Kumar, Surender & Managi, Shunsuke, 2009. "Energy price-induced and exogenous technological change: Assessing the economic and environmental outcomes," Resource and Energy Economics, Elsevier, vol. 31(4), pages 334-353, November.
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    More about this item

    Keywords

    Chinese power plant; Meta-frontier; Parametric estimation; Environmental technical efficiency; Shadow price;
    All these keywords.

    JEL classification:

    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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