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Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach

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  • Ke Wang
  • Zhifu Mi
  • Yi‐Ming Wei

Abstract

Previous studies of the efficiency of Chinese electricity industry have been limited in providing insights regarding policy implications of inherent trade‐offs of economic and environmental outcomes. This study proposes a modified data envelopment analysis method combined with materials balance principle to estimate ecological and cost efficiency in the Chinese electricity industry. The economic cost and ecological impact of energy input reallocation strategies for improving efficiency are identified. The possible impacts of pollution taxes upon the levels of sulfur dioxide (SO2) emissions are assessed. Estimation results show that (1) both energy input costs and SO2 could be reduced through increasing technical efficiency. (2) It is possible to adjust energy input mix to attain ecological efficiency, and, correspondingly, SO2 would be reduced by 15%. (3) The Chinese electricity industry would reduce its unit cost by 9% if optimal ecological efficiency is attained and reduce its unit pollution by 13% if optimal cost efficiency is attained, implying that there are positive ecological synergy effects associated with energy cost savings and positive economic synergy effects associated with SO2 pollution reductions. (4) Estimated shadow costs of SO2 reduction are very high, suggesting that, in the short term, the Chinese electricity industry should pursue cost efficiency instead of ecological efficiency, since alternative abatement activities are less costly and some of the abatement cost could be further offset by energy input cost savings. (5) There would be no significant difference between the impacts of pollution discharge fees and pollution taxes on SO2 emissions levels because of the relatively low pollution tax rate.

Suggested Citation

  • Ke Wang & Zhifu Mi & Yi‐Ming Wei, 2019. "Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach," Journal of Industrial Ecology, Yale University, vol. 23(2), pages 389-401, April.
    • Handle: RePEc:bla:inecol:v:23:y:2019:i:2:p:389-401
    DOI: 10.1111/jiec.12740
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    Cited by:

    1. Yuanhong Hu & Sheng Sun & Yixin Dai, 2021. "Environmental regulation, green innovation, and international competitiveness of manufacturing enterprises in China: From the perspective of heterogeneous regulatory tools," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-28, March.
    2. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    3. Wang, Ke & Wang, Jiayu & Wei, Yi-Ming & Zhang, Chi, 2018. "A novel dataset of emission abatement sector extended input-output table for environmental policy analysis," Applied Energy, Elsevier, vol. 231(C), pages 1259-1267.
    4. Boqiang Lin & Yongjing Xie, 2025. "How does digital finance drive energy transition? A green investment-based perspective," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-23, December.
    5. Weiwei Zhuang & Jiayu Zhang & Taisheng Zhang & Xiang Chen, 2025. "Evaluating energy cost performance in China's thermal power industry: A global cost Malmquist approach," Natural Resources Forum, Blackwell Publishing, vol. 49(1), pages 197-221, February.
    6. Xian, Yujiao & Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2019. "Would China’s power industry benefit from nationwide carbon emission permit trading? An optimization model-based ex post analysis on abatement cost savings," Applied Energy, Elsevier, vol. 235(C), pages 978-986.
    7. Zhou, Dequn & Wu, Changsong & Wang, Qunwei & Zha, Donglan, 2019. "Response of scale and leverage of thermal power enterprises to renewable power enterprises in China," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Lin, Boqiang & Xie, Yongjing, 2023. "Does digital transformation improve the operational efficiency of Chinese power enterprises?," Utilities Policy, Elsevier, vol. 82(C).
    9. Ke Wang & Jiayu Wang & Klaus Hubacek & Zhifu Mi & Yi‐Ming Wei, 2020. "A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 564-576, June.
    10. Jiasen Sun & Guo Li & Ming K. Lim, 2025. "China’s power supply chain sustainability: an analysis of performance and technology gap," Annals of Operations Research, Springer, vol. 349(2), pages 849-877, June.
    11. Zhongfei Chen & Stavros Kourtzidis & Panayiotis Tzeremes & Nickolaos Tzeremes, 2022. "A robust network DEA model for sustainability assessment: an application to Chinese Provinces," Operational Research, Springer, vol. 22(1), pages 235-262, March.
    12. Yunfei An & Dequn Zhou & Qunwei Wang, 2022. "Carbon emission reduction potential and its influencing factors in China’s coal-fired power industry: a cost optimization and decomposition analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3619-3639, March.
    13. Chu, Junfei & Shao, Caifeng & Emrouznejad, Ali & Wu, Jie & Yuan, Zhe, 2021. "Performance evaluation of organizations considering economic incentives for emission reduction: A carbon emission permit trading approach," Energy Economics, Elsevier, vol. 101(C).
    14. Hua, Cheng & Wang, Ke, 2023. "Multi-factor productivity growth with natural capital and undesirable output: A measurement for OECD and G20 countries," Innovation and Green Development, Elsevier, vol. 2(2).
    15. Ying Feng & Ching-Cheng Lu & I-Fang Lin & An-Chi Yang & Po-Chun Lin, 2022. "Total Factor Energy Efficiency of China’s Thermal Power Industry," Sustainability, MDPI, vol. 14(1), pages 1-16, January.
    16. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    17. Yujiao Xian & Ke Wang & Yi-Ming Wei & Zhimin Huang, 2018. "Would China¡¯s power industry benefit from nationwide carbon emission permit trading? An optimization model-based ex post analysis on abatement cost savings," CEEP-BIT Working Papers 121, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    18. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.

    More about this item

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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