IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v6y2014i8p5476-5492d39508.html
   My bibliography  Save this article

Energy Efficiency and Energy Saving Potential in China: A Directional Meta-Frontier DEA Approach

Author

Listed:
  • Qunwei Wang

    () (School of Business, Soochow University, No. 50 Donghuan Road, Suzhou 215021, China
    Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, No. 29 Jiangjun Avenue, Nanjing 210016, China)

  • Peng Zhou

    () (Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, No. 29 Jiangjun Avenue, Nanjing 210016, China)

  • Zengyao Zhao

    () (School of Business, Soochow University, No. 50 Donghuan Road, Suzhou 215021, China)

  • Neng Shen

    () (School of Business, Soochow University, No. 50 Donghuan Road, Suzhou 215021, China)

Abstract

Increasing energy efficiency and exploiting energy saving potential are two important practices that can help to ensure future energy security in China. This paper proposes a new total factor energy efficiency indicator, based on the directional meta-frontier data envelopment analysis (DEA) approach, to account for the heterogeneity of production technology among provinces in China. This indicator considers both energy savings and economic development, and can also decompose the energy saving potential. An empirical research study conducted on 29 Chinese provinces indicates that the differences in energy efficiency and production technology among the Chinese regions are quite significant. Most eastern coastal provinces maintain high-energy efficiency and advanced production technology, while energy efficiency in the west is typically lower. As a rule, improvements in technical and management factors are needed to exploit energy saving potentials. However, the emphasis on these two factors in each province should differ. China’s general energy efficiency is relatively low; the absolute amount of nationwide energy saving potential is on the rise.

Suggested Citation

  • Qunwei Wang & Peng Zhou & Zengyao Zhao & Neng Shen, 2014. "Energy Efficiency and Energy Saving Potential in China: A Directional Meta-Frontier DEA Approach," Sustainability, MDPI, Open Access Journal, vol. 6(8), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:6:y:2014:i:8:p:5476-5492:d:39508
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/6/8/5476/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/6/8/5476/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    2. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    3. Ghali, Khalifa H. & El-Sakka, M. I. T., 2004. "Energy use and output growth in Canada: a multivariate cointegration analysis," Energy Economics, Elsevier, vol. 26(2), pages 225-238, March.
    4. Zhang, Ming & Li, Huanan & Zhou, Min & Mu, Hailin, 2011. "Decomposition analysis of energy consumption in Chinese transportation sector," Applied Energy, Elsevier, vol. 88(6), pages 2279-2285, June.
    5. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    6. 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.
    7. Ang, B.W., 2006. "Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index," Energy Policy, Elsevier, vol. 34(5), pages 574-582, March.
    8. 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.
    9. 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.
    10. Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," European Journal of Operational Research, Elsevier, vol. 80(3), pages 474-499, February.
    11. 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.
    12. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    13. 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.
    14. 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.
    15. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    16. R. Ramanathan, 2002. "Combining indicators of energy consumption and CO 2 emissions: a cross-country comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 214-227.
    17. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    18. Chu Wei & Jinlan Ni & Manhong Shen, 2009. "Empirical Analysis of Provincial Energy Efficiency in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 17(5), pages 88-103, September.
    19. 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.
    20. Hu, Jin-Li & Kao, Chih-Hung, 2007. "Efficient energy-saving targets for APEC economies," Energy Policy, Elsevier, vol. 35(1), pages 373-382, January.
    21. 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.
    22. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    2. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    3. 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.
    4. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    5. Zhou, D.Q. & Wang, Qunwei & Su, B. & Zhou, P. & Yao, L.X., 2016. "Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis," Applied Energy, Elsevier, vol. 166(C), pages 201-209.
    6. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    7. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    8. Kounetas, Konstantinos & Stergiou, Eirini, 2019. "Technology heterogeneity in European industries' energy efficiency performance. The role of climate, greenhouse gases, path dependence and energy mix," MPRA Paper 92314, University Library of Munich, Germany.
    9. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    10. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    11. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    12. Li, Ke & Lin, Boqiang, 2015. "Metafroniter energy efficiency with CO2 emissions and its convergence analysis for China," Energy Economics, Elsevier, vol. 48(C), pages 230-241.
    13. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    14. Li, Jianglong & Lin, Boqiang, 2017. "Ecological total-factor energy efficiency of China's heavy and light industries: Which performs better?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 83-94.
    15. 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.
    16. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    17. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    18. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    19. Zhencheng Xing & Jigan Wang & Jie Zhang, 2017. "CO 2 Emission Performance, Mitigation Potential, and Marginal Abatement Cost of Industries Covered in China’s Nationwide Emission Trading Scheme: A Meta-Frontier Analysis," Sustainability, MDPI, Open Access Journal, vol. 9(6), pages 1-17, June.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:6:y:2014:i:8:p:5476-5492:d:39508. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (XML Conversion Team). General contact details of provider: https://www.mdpi.com/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.