IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i9p3879-d355928.html
   My bibliography  Save this article

Measurement and Influencing Factors Research of the Energy and Power Efficiency in China: Based on the Supply-Side Structural Reform Perspective

Author

Listed:
  • Xiaohua Song

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Caiping Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Jingjing Han

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Qi Zhang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Jinpeng Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Yuanying Chi

    (School of Economics and Management, Beijing University of Technology, Beijing 100022, China)

Abstract

China’s supply-side structural reforms are facing bottlenecks in the energy and power sector, and improving energy and power efficiency and advancing reforms are urgent. To promote sustainable development, based on panel data from 30 provinces and cities in China from 2009 to 2017, this paper uses the super-efficiency DEA method to measure energy and power efficiency; explores the trend of energy and power efficiency changes before and after reform; uses the Tobit model to identify key efficiency factors; and provides policy recommendations to achieve reform goals. The research shows that China’s efficiency level takes the supply-side structural reform as the turning point and presents a volatile upward trend; from the situation of the country, technological progress, the economic development level, and the opening up level are positively correlated with the energy and power efficiency, among which the correlation coefficient between technological progress and efficiency is the highest. The study can offer a reference for the sustainable comprehensive utilization of China’s energy and power, and provide empirical evidence for other countries to improve the energy and power efficiency from the perspectives of theory and policies.

Suggested Citation

  • Xiaohua Song & Caiping Zhao & Jingjing Han & Qi Zhang & Jinpeng Liu & Yuanying Chi, 2020. "Measurement and Influencing Factors Research of the Energy and Power Efficiency in China: Based on the Supply-Side Structural Reform Perspective," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:9:p:3879-:d:355928
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/9/3879/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/9/3879/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    2. She, Zhen-Yu & Meng, Gang & Xie, Bai-Chen & O'Neill, Eoghan, 2020. "The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective," Applied Energy, Elsevier, vol. 264(C).
    3. Fan, Ying & Liao, Hua & Wei, Yi-Ming, 2007. "Can market oriented economic reforms contribute to energy efficiency improvement? Evidence from China," Energy Policy, Elsevier, vol. 35(4), pages 2287-2295, April.
    4. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    5. Yingnan Liu & Ke Wang, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA-based decomposition analysis," CEEP-BIT Working Papers 83, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    6. Zhu, Lin & Wang, Yong & Shang, Peipei & Qi, Lin & Yang, Guangchun & Wang, Ying, 2019. "Improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China: Based on an improved nonradial multidirectional efficiency analysis," Energy Policy, Elsevier, vol. 133(C).
    7. Fisher-Vanden, Karen & Jefferson, Gary H. & Jingkui, Ma & Jianyi, Xu, 2006. "Technology development and energy productivity in China," Energy Economics, Elsevier, vol. 28(5-6), pages 690-705, November.
    8. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    9. Wang, Ke & Wei, Yi-Ming, 2014. "China’s regional industrial energy efficiency and carbon emissions abatement costs," Applied Energy, Elsevier, vol. 130(C), pages 617-631.
    10. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    11. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    12. Xie, Bai-Chen & Shang, Li-Feng & Yang, Si-Bo & Yi, Bo-Wen, 2014. "Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countrie," Energy, Elsevier, vol. 74(C), pages 147-157.
    13. 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.
    14. 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.
    15. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    16. Elena Stefana & Paola Cocca & Filippo Marciano & Diana Rossi & Giuseppe Tomasoni, 2019. "A Review of Energy and Environmental Management Practices in Cast Iron Foundries to Increase Sustainability," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    17. Joakim Haraldsson & Maria T. Johansson, 2019. "Barriers to and Drivers for Improved Energy Efficiency in the Swedish Aluminium Industry and Aluminium Casting Foundries," Sustainability, MDPI, vol. 11(7), pages 1-27, April.
    18. Apriani Soepardi & Pratikto Pratikto & Purnomo Budi Santoso & Ishardita Pambudi Tama & Patrik Thollander, 2018. "Linking of Barriers to Energy Efficiency Improvement in Indonesia’s Steel Industry," Energies, MDPI, vol. 11(1), pages 1-22, January.
    19. Tao Yi & Ling Tong & Mohan Qiu & Jinpeng Liu, 2019. "Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China," Energies, MDPI, vol. 12(3), pages 1-15, January.
    20. M. A. Graña-López & A. García-Diez & A. Filgueira-Vizoso & J. Chouza-Gestoso & A. Masdías-Bonome, 2019. "Study of the Sustainability of Electrical Power Systems: Analysis of the Causes that Generate Reactive Power," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    21. Huang, Jin-ping, 1993. "Industry energy use and structural change : A case study of The People's Republic of China," Energy Economics, Elsevier, vol. 15(2), pages 131-136, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Honglei Liu & Qiang Wu & Jianxin Chen & Mingjun Wang & Di Zhao & Cheng Duan, 2021. "Environmental Impacts Related to Closed Mines in Inner Mongolia," Sustainability, MDPI, vol. 13(23), pages 1-19, December.
    2. Wei Wei & Shuangying Ding & Silin Zheng & Jingjing Ma & Tong Niu & Jinkai Li, 2021. "Environmental Efficiency Evaluation of China’s Power Industry Based on the Two-Stage Network Slack-Based Measure Model," IJERPH, MDPI, vol. 18(23), pages 1-21, November.
    3. Si-Si Dong & Liang-Qun Qi & Jia-Quan Li, 2022. "Evaluation of the Implementation Effect of China’s Industrial Sector Supply-Side Reform: From the Perspective of Energy and Environmental Efficiency," Energies, MDPI, vol. 15(9), pages 1-17, April.
    4. Jungseok Choi & Woohyoung Kim & Seokkyu Choi, 2022. "The Economic Effect of the Steel Industry on Sustainable Growth in China—A Focus on Input–Output Analysis," Sustainability, MDPI, vol. 14(7), pages 1-12, March.
    5. Sungsig Bang, 2020. "Performance Evaluation of Energy Research Projects Using DEA Super-Efficiency," Energies, MDPI, vol. 13(20), pages 1-19, October.
    6. Runqun Yu & Zhuoyang Luo, 2023. "Research on the Influence Mechanism of Factor Misallocation on the Transformation Efficiency of Resource-Based Cities Based on the Optimization Direction Function Calculation Method," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

    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. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    2. 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.
    3. Kai He & Nan Zhu & Wu Jiang & Chuanjin Zhu, 2022. "Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    4. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    5. Tengfei Huo & Hong Ren & Weiguang Cai & Wei Feng & Miaohan Tang & Nan Zhou, 2018. "The total-factor energy productivity growth of China’s construction industry: evidence from the regional level," 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. 92(3), pages 1593-1616, July.
    6. Zhou, D.Q. & Wu, F. & Zhou, X. & Zhou, P., 2016. "Output-specific energy efficiency assessment: A data envelopment analysis approach," Applied Energy, Elsevier, vol. 177(C), pages 117-126.
    7. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    8. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Energy and Environmental Efficiency in Different Chinese Regions," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    9. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    10. Liao, Hua & Fan, Ying & Wei, Yi-Ming, 2007. "What induced China's energy intensity to fluctuate: 1997-2006?," Energy Policy, Elsevier, vol. 35(9), pages 4640-4649, September.
    11. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.
    12. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    13. Chen, Xiude & Qin, Quande & Wei, Y.-M., 2016. "Energy productivity and Chinese local officials’ promotions: Evidence from provincial governors," Energy Policy, Elsevier, vol. 95(C), pages 103-112.
    14. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    15. Jiang, Xuemei & Zhu, Kunfu & Green, Christopher, 2015. "The energy efficiency advantage of foreign-invested enterprises in China and the role of structural differences," China Economic Review, Elsevier, vol. 34(C), pages 225-235.
    16. Huaming Chen & Jia Liu & Ying Li & Yung-Ho Chiu & Tai-Yu Lin, 2019. "A Two-stage Dynamic Undesirable Data Envelopment Analysis Model Focused on Media Reports and the Impact on Energy and Health Efficiency," IJERPH, MDPI, vol. 16(9), pages 1-23, April.
    17. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    18. Xu, Xin & Cui, Qiang, 2017. "Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure," Energy, Elsevier, vol. 122(C), pages 274-286.
    19. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "The Impact of Economic Growth and Air Pollution on Public Health in 31 Chinese Cities," IJERPH, MDPI, vol. 16(3), pages 1-26, January.
    20. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.

    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:12:y:2020:i:9:p:3879-:d:355928. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.