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Multi-directional efficiency analysis-based regional industrial environmental performance evaluation of China

Author

Listed:
  • Ke Wang
  • Shiwei Yu
  • Mo-Jie Li
  • Yi-Ming Wei

    (Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology)

Abstract
This study evaluates the environmental efficiency of industrial sectors of Chinese major cities. The Multi-directional efficiency analysis (MEA) approach are utilized for evaluation, thus both the integrated MEA efficiency levels and the efficiency patterns, which are represented by the variable specific MEA efficiency according to each type of the industrial pollutant emission or discharge, of Chinese major city are detected. In addition the industrial energy conservation and pollutant reduction potentials are measured and the relationship between environmental pressure and income are explored at the regional level of China. The main findings include: (i) The MEA environmental efficiency increases of the economic less developed cities were faster than the cities in the well-developed region, which indicates that the inequitable nationwide industrial developments of Chinese cities have started to alleviate. (ii) Although some Chinese cities show similar environmental efficiency levels, the undesirable output variable specific efficiency patterns of these cities are diversified, and according to the variable specific efficiency, the most possible efficiency increase potential of each Chinese major city can be identified. (iii) An N-shaped Environmental Kuznets Curve exists in the industrial sectors of Chinese major cities. (iv) Different Chinese cities should have different industrial pollutant reduction priorities, which east China cities should pay more attention on their industrial waste gas emissions and industrial waste water discharges, while west China cities should mainly focus on their industrial soot and dust emissions, and solid waste discharges.

Suggested Citation

  • Ke Wang & Shiwei Yu & Mo-Jie Li & Yi-Ming Wei, 2013. "Multi-directional efficiency analysis-based regional industrial environmental performance evaluation of China," CEEP-BIT Working Papers 47, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:47
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    File URL: http://ceep.bit.edu.cn/docs/2018-10/20181011140052070397.pdf
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    References listed on IDEAS

    as
    1. Peter Bogetoft & Jens Hougaard, 1999. "Efficiency Evaluations Based on Potential (Non-Proportional) Improvements," Journal of Productivity Analysis, Springer, vol. 12(3), pages 233-247, November.
    2. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    3. Jianyi Huang & Yi Liu & Li Ma & Fei Su, 2013. "Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 115-134, January.
    4. Torben Holvad & Jens Hougaard & Dorte Kronborg & Hans Kvist, 2004. "Measuring inefficiency in the Norwegian bus industry using multi-directional efficiency analysis," Transportation, Springer, vol. 31(3), pages 349-369, August.
    5. Hua Liao, 2012. "China Country Report," Chapters, in: Shigeru Kimura (ed.), Analysis on Energy Saving Potential in East Asia, chapter 5, pages 115-130, Economic Research Institute for ASEAN and East Asia (ERIA).
    6. Murty, Sushama & Russell, R. Robert, 2010. "On modeling pollution-generating technologies," The Warwick Economics Research Paper Series (TWERPS) 931, University of Warwick, Department of Economics.
    7. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    8. Yiming Wei & Lancui Liu & Gang Wu & Lele Zou (ed.), 2010. "Energy Economics: CO2 Emissions in China," CEEP-BIT Books, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology, number b1, december.
    9. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    10. Gongbing Bi & Yan Luo & Jingjing Ding & Liang Liang, 2015. "Environmental performance analysis of Chinese industry from a slacks-based perspective," Annals of Operations Research, Springer, vol. 228(1), pages 65-80, May.
    11. Auffhammer, Maximilian & Carson, Richard T., 2008. "Forecasting the path of China's CO2 emissions using province-level information," Journal of Environmental Economics and Management, Elsevier, vol. 55(3), pages 229-247, May.
    12. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    13. Hua, Zhongsheng & Bian, Yiwen & Liang, Liang, 2007. "Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach," Omega, Elsevier, vol. 35(5), pages 578-587, October.
    14. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    15. Song, Tao & Zheng, Tingguo & Tong, Lianjun, 2008. "An empirical test of the environmental Kuznets curve in China: A panel cointegration approach," China Economic Review, Elsevier, vol. 19(3), pages 381-392, September.
    16. Dinda, Soumyananda, 2004. "Environmental Kuznets Curve Hypothesis: A Survey," Ecological Economics, Elsevier, vol. 49(4), pages 431-455, August.
    17. Mette Asmild & Jens Hougaard & Dorte Kronborg & Hans Kvist, 2003. "Measuring Inefficiency Via Potential Improvements," Journal of Productivity Analysis, Springer, vol. 19(1), pages 59-76, January.
    18. Asmild, Mette & Matthews, Kent, 2012. "Multi-directional efficiency analysis of efficiency patterns in Chinese banks 1997–2008," European Journal of Operational Research, Elsevier, vol. 219(2), pages 434-441.
    19. Mette Asmild & Torben Holvad & Jens Hougaard & Dorte Kronborg, 2009. "Railway reforms: do they influence operating efficiency?," Transportation, Springer, vol. 36(5), pages 617-638, September.
    20. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
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    2. Qianwen Li & Ruyin Long & Hong Chen & Feiyu Chen & Xiu Cheng, 2019. "Chinese urban resident willingness to pay for green housing based on double-entry mental accounting theory," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 129-153, January.
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    5. Jia-Yin Yin & Yun-Fei Cao & Bao-Jun Tang, 2019. "Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 343-362, January.

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    More about this item

    Keywords

    Environmental performance; Industrial sector; Pollutant reduction potential; Multi-directional Efficiency Analysis (MEA);
    All these keywords.

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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