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Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs

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  • Shi, Guang-Ming
  • Bi, Jun
  • Wang, Jin-Nan
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    Abstract

    Data envelopment analysis (DEA) has recently become a popular method in measuring energy efficiency at the macro-economy level. However, previous studies are limited in that they failed to consider the issues of undesirable outputs and minimisation of energy consumption. Thus, this study considers both factors in measuring Chinese industrial energy efficiency and investigates the maximum energy-saving potential in 28 administrative regions in China. The results show that industries in the east area have the best average energy efficiency for the period 2000-2006, followed by the central area. Further, after comparing the industrial energy overall efficiency, pure technical efficiency (IEPTE), and scale efficiency of the 28 administrative regions examined, the study finds that in most regions of this study, the two main reasons causing the wastage of a large amount of energy during the industrial production process are that the industrial structure of most regions still relies on the massive use of energy in order to support the industrial-based economy and the IEPTE is too low. Based on these findings, this paper correspondingly proposes some policies to improve regional industrial energy efficiency.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 38 (2010)
    Issue (Month): 10 (October)
    Pages: 6172-6179

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    Handle: RePEc:eee:enepol:v:38:y:2010:i:10:p:6172-6179

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    Web page: http://www.elsevier.com/locate/enpol

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    Keywords: Chinese industrial energy efficiency Undesirable outputs Minimising energy consumption;

    References

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    Cited by:
    1. Hu, Jin-Li & Lio, Mon-Chi & Yeh, Fang-Yu & Lin, Cheng-Hsun, 2011. "Environment-adjusted regional energy efficiency in Taiwan," Applied Energy, Elsevier, vol. 88(8), pages 2893-2899, August.
    2. Jin, Jingliang & Zhou, Dequn & Zhou, Peng, 2014. "Measuring environmental performance with stochastic environmental DEA: The case of APEC economies," Economic Modelling, Elsevier, vol. 38(C), pages 80-86.
    3. Yuyu Liu & Caizhi Sun & Shiguo Xu, 2013. "Eco-Efficiency Assessment of Water Systems in China," Water Resources Management, Springer, vol. 27(14), pages 4927-4939, November.
    4. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, vol. 112(C), pages 1403-1415.
    5. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    6. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    7. Halkos, George & Tzeremes, Nickolaos, 2012. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from the UK regions," MPRA Paper 38147, University Library of Munich, Germany.
    8. Zhou, Yan & Xing, Xinpeng & Fang, Kuangnan & Liang, Dapeng & Xu, Chunlin, 2013. "Environmental efficiency analysis of power industry in China based on an entropy SBM model," Energy Policy, Elsevier, vol. 57(C), pages 68-75.
    9. Weibin Lin & Jin Yang & Bin Chen, 2011. "Temporal and Spatial Analysis of Integrated Energy and Environment Efficiency in China Based on a Green GDP Index," Energies, MDPI, Open Access Journal, vol. 4(9), pages 1376-1390, September.
    10. Ke Wang & Yi-Ming Wei & Xian Zhang, 2011. "A comparative analysis of China's regional energy and emission performance: Which is the better way to deal with undesirable outputs?," CEEP-BIT Working Papers 24, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    11. Wang, H. & Zhou, P. & Zhou, D.Q., 2013. "Scenario-based energy efficiency and productivity in China: A non-radial directional distance function analysis," Energy Economics, Elsevier, vol. 40(C), pages 795-803.
    12. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.
    13. Yang, Mian & Yang, Fu-Xia & Chen, Xing-Peng, 2011. "Effects of substituting energy with capital on China's aggregated energy and environmental efficiency," Energy Policy, Elsevier, vol. 39(10), pages 6065-6072, October.
    14. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    15. Fang, Chin-Yi & Hu, Jin-Li & Lou, Tze-Kai, 2013. "Environment-adjusted total-factor energy efficiency of Taiwan's service sectors," Energy Policy, Elsevier, vol. 63(C), pages 1160-1168.
    16. Bian, Yiwen & He, Ping & Xu, Hao, 2013. "Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach," Energy Policy, Elsevier, vol. 63(C), pages 962-971.
    17. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    18. Chang, Ming-Chung, 2014. "Energy intensity, target level of energy intensity, and room for improvement in energy intensity: An application to the study of regions in the EU," Energy Policy, Elsevier, vol. 67(C), pages 648-655.

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