IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v10y2020i3p2158244020934888.html
   My bibliography  Save this article

Measurement and Structural Factors Influencing China’s Provincial Total-Factor Energy Efficiency Under Resource and Environmental Constraints

Author

Listed:
  • Hongzhang Chen
  • Haiwen Yang

Abstract

We studied the measurement and structural factors influencing China’s provincial total-factor energy efficiency (TFEE) under resource and environmental constraints, using spatial weight matrix analysis, spatial econometric model selection, a generalized spatial econometric model with unknown heteroscedasticity, and a directional distance function global Malmquist–Luenberger (GML) superefficient model. The findings of this empirical research are as follows. Resource and environmental constraints should be considered while measuring TFEE. The results obtained in such cases are more accurate reflections of the actual situation in China. Furthermore, spatial effects should be considered when analyzing the factors influencing provincial TFEE; otherwise, the estimates will be biased. The following conclusions were obtained from the results of the empirical analysis: China’s provincial TFEE continued to decline under resource and environmental constraints, and the trend is not optimistic, implying an undue reliance on coal resources, which reduce TFEE by a considerable extent. Moreover, China’s interprovincial TFEE is affected by a variety of structural factors.

Suggested Citation

  • Hongzhang Chen & Haiwen Yang, 2020. "Measurement and Structural Factors Influencing China’s Provincial Total-Factor Energy Efficiency Under Resource and Environmental Constraints," SAGE Open, , vol. 10(3), pages 21582440209, July.
  • Handle: RePEc:sae:sagope:v:10:y:2020:i:3:p:2158244020934888
    DOI: 10.1177/2158244020934888
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2158244020934888
    Download Restriction: no

    File URL: https://libkey.io/10.1177/2158244020934888?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Honma, Satoshi & Hu, Jin-Li, 2009. "Total-factor energy productivity growth of regions in Japan," Energy Policy, Elsevier, vol. 37(10), pages 3941-3950, October.
    2. Pang, Rui-Zhi & Deng, Zhong-Qi & Hu, Jin-li, 2015. "Clean energy use and total-factor efficiencies: An international comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1158-1171.
    3. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    4. 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.
    5. 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.
    6. Chen, Zhenling & Li, Jinkai & Zhao, Weigang & Yuan, Xiao-Chen & Yang, Guo-liang, 2019. "Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China," Energy Policy, Elsevier, vol. 125(C), pages 122-134.
    7. 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.
    8. Philip Kostov, 2010. "Model Boosting for Spatial Weighting Matrix Selection in Spatial Lag Models," Environment and Planning B, , vol. 37(3), pages 533-549, June.
    9. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    10. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    11. W D Cook & L Liang & Y Zha & J Zhu, 2009. "A modified super-efficiency DEA model for infeasibility," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 276-281, February.
    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. Reema Gh. Alajmi, 2024. "Total-Factor Energy Efficiency (TFEE) and CO 2 Emissions for GCC Countries," Sustainability, MDPI, vol. 16(2), pages 1-14, January.
    2. Chiang-Ping Chen & Ming-Chung Chang & Wei-Che Tsai, 2021. "Dynamic Energy Efficiency, Energy Decoupling Rate, and Decarbonization: Evidence from ASEAN+6," SAGE Open, , vol. 11(3), pages 21582440211, September.

    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. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    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. 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.
    4. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    5. Zuoren Sun & Chao An & Huachen Sun, 2018. "Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-28, July.
    6. Zhang, Yue-Jun & Sun, Ya-Fang & Huang, Junling, 2018. "Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment," Energy Policy, Elsevier, vol. 115(C), pages 119-130.
    7. Nela Vlahinic Lenz & Alemka egota & Dario Maradin, 2018. "Total-factor Energy Efficiency in EU: Do Environmental Impacts Matter?," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 92-96.
    8. Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015. "Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs," Energy Economics, Elsevier, vol. 51(C), pages 45-53.
    9. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    10. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.
    11. Jebali, Eya & Essid, Hédi & Khraief, Naceur, 2017. "The analysis of energy efficiency of the Mediterranean countries: A two-stage double bootstrap DEA approach," Energy, Elsevier, vol. 134(C), pages 991-1000.
    12. Sanzidur Rahman & Basanta Kumar Barmon, 2018. "Total Factor Energy Productivity and Efficiency Changes of the Gher (Prawn-Carp-Rice) Farming System in Bangladesh: A Stochastic Input Distance Function Approach," Energies, MDPI, vol. 11(12), pages 1-17, December.
    13. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(C).
    14. 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).
    15. Chia-Jung Tu & Ming-Chung Chang & Chiang-Ping Chen, 2016. "Progressive Time-Weighted Dynamic Energy Efficiency, Energy Decoupling Rate, and Decarbonization: An Empirical Study on G7 and BRICS," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    16. Qingwei Shi & Hong Ren & Weiguang Cai & Jingxin Gao, 2020. "How to Set the Proper CO 2 Reduction Targets for the Provincial Building Sector of China?," Sustainability, MDPI, vol. 12(24), pages 1-22, December.
    17. Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    18. Lei Wang & Wei Li & Guomin Li & Guozhen Zhang, 2021. "Concept Evolution and Multi-Dimensional Measurement Comparison of Urban Energy Performance from the Perspective of System Correlation: Empirical Analysis of 142 Prefecture Level Cities in China," IJERPH, MDPI, vol. 18(24), pages 1-21, December.
    19. Djula Borozan & Luka Borozan, 2018. "Analyzing total-factor energy efficiency in Croatian counties: evidence from a non-parametric approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 673-694, September.
    20. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.

    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:sae:sagope:v:10:y:2020:i:3:p:2158244020934888. 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: SAGE Publications (email available below). General contact details of provider: .

    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.