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Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China

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  • Jun Xu

    (School of Business, Jiangsu Normal University, Xuzhou 221116, China)

  • Yuchen Jiang

    (School of Business, Jiangsu Normal University, Xuzhou 221116, China)

  • Xin Guo

    (School of Business, Jiangsu Normal University, Xuzhou 221116, China)

  • Li Jiang

    (School of Business, Jiangsu Normal University, Xuzhou 221116, China)

Abstract

Industrial waste discharged by heavy pollution industry is one of the main causes of global environmental degradation. Research on the environmental efficiency of high-polluting industry is necessary to tackle the problem of global environmental pollution. Using panel data of 19 sub-industries in China’s heavy pollution industry from 2001 to 2015, this article employs Data Envelopment Analysis (DEA) and Malmquist index (MI) to measure the environmental efficiency of heavy pollution industry from both the dynamic and static perspectives. The results show that the environmental efficiency of China’s heavy pollution industry maintains an upward trend but did not reach the optimal level. The general trend shows a phased trend of increasing first and then decreasing. Besides, there are inter-industry differences in the environmental efficiency across the examined sub-industries. Based on the research findings, this article proposes a set of corresponding countermeasures to solve the global pollution problem, such as reducing energy inputs and minimizing the volumes of the main categories of emissions in high-polluting industry, as well as improving the production management in the group of high environmental efficiency and strengthening technical capabilities in the group of low environmental efficiency.

Suggested Citation

  • Jun Xu & Yuchen Jiang & Xin Guo & Li Jiang, 2021. "Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China," IJERPH, MDPI, vol. 18(11), pages 1-17, May.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5761-:d:563540
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    1. Yigang Wei & Yan Li & Meiyu Wu & Yingbo Li, 2020. "Progressing sustainable development of “the Belt and Road countries”: Estimating environmental efficiency based on the Super‐slack‐based measure model," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 521-539, July.
    2. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    3. 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.
    4. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model☆," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    5. Färe, Rolf & Margaritis, Dimitris & Rouse, Paul & Roshdi, Israfil, 2016. "Estimating the hyperbolic distance function: A directional distance function approach," European Journal of Operational Research, Elsevier, vol. 254(1), pages 312-319.
    6. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    7. Li Xie & Chunlin Chen & Yihua Yu, 2019. "Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach," Sustainability, MDPI, vol. 11(8), pages 1-22, April.
    8. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    9. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    10. Qingxian An & Xiangyang Tao & Bo Dai & Jinlin Li, 2020. "Modified Distance Friction Minimization Model with Undesirable Output: An Application to the Environmental Efficiency of China’s Regional Industry," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1047-1071, April.
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