IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v221y2021ics0360544221000128.html
   My bibliography  Save this article

Measurement and influential factors of the efficiency of coal resources of China’s provinces: Based on Bootstrap-DEA and Tobit

Author

Listed:
  • Xue, Liming
  • Zhang, Wenjie
  • Zheng, Zhixue
  • Liu, Zhe
  • Meng, Shuo
  • Li, Huaqing
  • Du, Yulin

Abstract

A more efficient use of China’s coal resources is key to rapidly promoting the growth of the country’s industrializing economy. As such, it is essential that an effective approach for measuring and evaluating the current efficiency of coal resources is developed. This paper measures the efficiency of coal resources in 30 provinces in China from 2000 to 2015 using an improved DEA model of Bootstrap, and it uses Tobit regression to analyze the influencing factors on the efficiency of coal resources. The results illustrate that: 1) The proposed approach could significantly improve upon the accuracy of the measurement of the traditional DEA model. 2) The efficiency of coal resources shows an uptrend of fluctuation for the research period. With respect to the influential factors, total coal consumption has the least influence on the efficiency of coal resources. In contrast, local financial science and technology expenditures have greatest influence on the efficiency of coal resources. Among all the influential factors, local financial science and technology expenditures have the greatest negative impact on energy efficiency of coal resources and it is very critical that the government increases investment in scientific and technological investment in the mining industry.

Suggested Citation

  • Xue, Liming & Zhang, Wenjie & Zheng, Zhixue & Liu, Zhe & Meng, Shuo & Li, Huaqing & Du, Yulin, 2021. "Measurement and influential factors of the efficiency of coal resources of China’s provinces: Based on Bootstrap-DEA and Tobit," Energy, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:energy:v:221:y:2021:i:c:s0360544221000128
    DOI: 10.1016/j.energy.2021.119763
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221000128
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.119763?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Delu & Wan, Kaidi & Song, Xuefeng & Liu, Yun, 2019. "Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness," Energy Economics, Elsevier, vol. 78(C), pages 109-128.
    2. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    3. Wu, Peng & Wang, Yiqing & Chiu, Yung-ho & Li, Ying & Lin, Tai-Yu, 2019. "Production efficiency and geographical location of Chinese coal enterprises - undesirable EBM DEA," Resources Policy, Elsevier, vol. 64(C).
    4. Zhao, Haoran & Guo, Sen & Zhao, Huiru, 2019. "Provincial energy efficiency of China quantified by three-stage data envelopment analysis," Energy, Elsevier, vol. 166(C), pages 96-107.
    5. Li, Chong-Mao & Cui, Tao & Nie, Rui & Lin, Han & Shan, Yuli, 2019. "Does diversification help improve the performance of coal companies? Evidence from China's listed coal companies," Resources Policy, Elsevier, vol. 61(C), pages 88-98.
    6. Wang, Wensheng & Zhang, Chengyi, 2018. "Evaluation of relative technological innovation capability: Model and case study for China's coal mine," Resources Policy, Elsevier, vol. 58(C), pages 144-149.
    7. Pan, Xiongfeng & Guo, Shucen & Han, Cuicui & Wang, Mengyang & Song, Jinbo & Liao, Xianchun, 2020. "Influence of FDI quality on energy efficiency in China based on seemingly unrelated regression method," Energy, Elsevier, vol. 192(C).
    8. Chai, Jian & Du, Mengfan & Liang, Ting & Sun, Xiaojie Christine & Yu, Ji & Zhang, Zhe George, 2019. "Coal consumption in China: How to bend down the curve?," Energy Economics, Elsevier, vol. 80(C), pages 38-47.
    9. Jung, Samuel Moon & Vijverberg, Chu-Ping C., 2019. "Financial development and income inequality in China – A spatial data analysis," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 295-320.
    10. Wu, Ya & Su, JingRong & Li, Ke & Sun, Chuanwang, 2019. "Comparative study on power efficiency of China's provincial steel industry and its influencing factors," Energy, Elsevier, vol. 175(C), pages 1009-1020.
    11. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    12. 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.
    13. 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.
    14. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Regional heterogeneity of China's energy efficiency in “new normal”: A meta-frontier Super-SBM analysis," Energy Policy, Elsevier, vol. 134(C).
    15. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    16. Qiao, Hui & Chen, Siyu & Dong, Xiucheng & Dong, Kangyin, 2019. "Has China's coal consumption actually reached its peak? National and regional analysis considering cross-sectional dependence and heterogeneity," Energy Economics, Elsevier, vol. 84(C).
    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. Zhang, Wei & Wang, Yaru & Fan, Fengchun, 2023. "How does coordinated development of two-way foreign direct investment affect natural resources Utilization?——Spatial analysis based on China's coal resource utilization efficiency," Resources Policy, Elsevier, vol. 85(PA).
    2. Ji, Zhengsen & Niu, Dongxiao & Li, Wanying & Wu, Gengqi & Yang, Xiaolong & Sun, Lijie, 2022. "Improving the energy efficiency of China: An analysis considering clean energy and fossil energy resources," Energy, Elsevier, vol. 259(C).
    3. Song, Haoran & Zhong, Zheng & Lin, Baiquan, 2023. "Mechanical degradation model of porous coal with water intrusion," Energy, Elsevier, vol. 278(C).
    4. Huang, Zhian & Yu, Rongxia & Ding, Hao & Wang, Hongsheng & Quan, Sainan & Song, Donghong & Lei, Yukun & Gao, Yukun & Zhang, Yinghua & Wang, Pengfei, 2023. "Preparation and properties of tea polyphenol nanofoamed gel for preventing coal spontaneous combustion," Energy, Elsevier, vol. 284(C).

    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. Liu, Haomin & Zhang, Zaixu & Zhang, Tao & Wang, Liyang, 2020. "Revisiting China’s provincial energy efficiency and its influencing factors," Energy, Elsevier, vol. 208(C).
    2. Zhang, Caiqing & Chen, Panyu, 2022. "Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries," Energy, Elsevier, vol. 241(C).
    3. Guo, Qiu-tong & Dong, Yong & Feng, Biao & Zhang, Hao, 2023. "Can green finance development promote total-factor energy efficiency? Empirical evidence from China based on a spatial Durbin model," Energy Policy, Elsevier, vol. 177(C).
    4. Zhang, Weike & Meng, Jia & Tian, Xiaoli, 2020. "Does de-capacity policy enhance the total factor productivity of China's coal companies? A Regression Discontinuity design," Resources Policy, Elsevier, vol. 68(C).
    5. Ping Han & Ziyu Zhou, 2023. "The Harmonious Relationship between Energy Utilization Efficiency and Industrial Structure Development under Carbon Emission Constraints: Measurement, Quantification, and Identification," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    6. Gao, Da & Li, Ge & Yu, Jiyu, 2022. "Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities," Energy, Elsevier, vol. 247(C).
    7. Wang, Xipan & Song, Junnian & Duan, Haiyan & Wang, Xian'en, 2021. "Coupling between energy efficiency and industrial structure: An urban agglomeration case," Energy, Elsevier, vol. 234(C).
    8. Mushtaq, Zulqarnain & Wei, Wei & Jamil, Ihsan & Sharif, Maimoona & Chandio, Abbas Ali & Ahmad, Fayyaz, 2022. "Evaluating the factors of coal consumption inefficiency in energy intensive industries of China: An epsilon-based measure model," Resources Policy, Elsevier, vol. 78(C).
    9. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    10. 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.
    11. 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.
    12. Xiangxiang Sun & Lawrence Loh, 2019. "Sustainability Governance in China: An Analysis of Regional Ecological Efficiency," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    13. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    14. Shuangjie Li & Hongyu Diao & Liming Wang & Chunqi Li, 2021. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    15. Wang, Xipan & Song, Junnian & Xing, Jiahao & Duan, Haiyan & Wang, Xian'en, 2022. "System nexus consolidates coupling of regional water and energy efficiencies," Energy, Elsevier, vol. 256(C).
    16. Wei, Jing & Zhang, Jianjun & Wu, Xia & Song, Zeyu, 2022. "Governance in mining enterprises: An effective way to promote the intensification of resources—Taking coal resources as an example," Resources Policy, Elsevier, vol. 76(C).
    17. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    18. Teng, Xiangyu & Liu, Fan-peng & Chiu, Yung-ho, 2021. "The change in energy and carbon emissions efficiency after afforestation in China by applying a modified dynamic SBM model," Energy, Elsevier, vol. 216(C).
    19. Shao, Jun & Wang, Lianghu, 2023. "Can new-type urbanization improve the green total factor energy efficiency? Evidence from China," Energy, Elsevier, vol. 262(PB).
    20. 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).

    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:eee:energy:v:221:y:2021:i:c:s0360544221000128. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.