IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v251y2022ics0360544222008209.html
   My bibliography  Save this article

Total factor productivity of high coal-consuming industries and provincial coal consumption: Based on the dynamic spatial Durbin model

Author

Listed:
  • Zhao, Mingxuan
  • Lv, Lianhong
  • Wu, Jing
  • Wang, Shen
  • Zhang, Nan
  • Bai, Zihan
  • Luo, Hong

Abstract

To promote the coordinated governance of atmospheric pollutants and greenhouse gases (GHGs), and to meet the emission goals of carbon peak and carbon neutrality, China should optimize the spatial pattern of its coal consumption. The present study employs the global Malmquist–Luenberger index to calculate the total factor productivity (TFP) of high coal-consuming industries in different provinces in China. Taking TFP as the independent variable, provincial coal consumption (PCC) as the dependent variable, and urbanization rate (UR) and regional gross domestic product (GDP) as the control variables, we establish a dynamic spatial Durbin model of TFP and PCC. We also use spatial effects decomposition to analyze the spatial influence relation between TFP and PCC. The results show a fluctuating upward trend of TFP in China overall, but the TFP in the eastern region is higher than that in the central and western provinces. The direct effects show a significant U-shaped relation between TFP and PCC, where PCC trends down with an increase in TFP. The indirect effects show an inverted U-shaped relation between local TFP and PCC in neighboring provinces. Finally, according to the estimated results, we propose some policy recommendations for China's government to control coal consumption.

Suggested Citation

  • Zhao, Mingxuan & Lv, Lianhong & Wu, Jing & Wang, Shen & Zhang, Nan & Bai, Zihan & Luo, Hong, 2022. "Total factor productivity of high coal-consuming industries and provincial coal consumption: Based on the dynamic spatial Durbin model," Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:energy:v:251:y:2022:i:c:s0360544222008209
    DOI: 10.1016/j.energy.2022.123917
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222008209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123917?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. Bhattacharya, Mita & Rafiq, Shuddhasattwa & Bhattacharya, Sankar, 2015. "The role of technology on the dynamics of coal consumption–economic growth: New evidence from China," Applied Energy, Elsevier, vol. 154(C), pages 686-695.
    2. Olivier Parent & James P. LeSage, 2008. "Using the variance structure of the conditional autoregressive spatial specification to model knowledge spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 235-256.
    3. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    4. Huang, Yi & Yi, Qun & Kang, Jing-Xian & Zhang, Ya-Gang & Li, Wen-Ying & Feng, Jie & Xie, Ke-Chang, 2019. "Investigation and optimization analysis on deployment of China coal chemical industry under carbon emission constraints," Applied Energy, Elsevier, vol. 254(C).
    5. Wu, Ya & Zhang, Wanying, 2016. "The driving factors behind coal demand in China from 1997 to 2012: An empirical study of input-output structural decomposition analysis," Energy Policy, Elsevier, vol. 95(C), pages 126-134.
    6. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    7. Kurniawan, Robi & Managi, Shunsuke, 2018. "Coal consumption, urbanization, and trade openness linkage in Indonesia," Energy Policy, Elsevier, vol. 121(C), pages 576-583.
    8. 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).
    9. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    10. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    11. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    12. Wang, Qiang & Wu, Shi-dai & Zeng, Yue-e & Wu, Bo-wei, 2016. "Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1563-1579.
    13. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    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. Kuang, Yucen & Jiang, Tao & Wu, Longqi & Liu, Xiaoqian & Yang, Xuke & Sher, Farooq & Wei, Zhifang & Zhang, Shengfu, 2023. "High-temperature rheological behavior and non-isothermal pyrolysis mechanism of macerals separated from different coals," Energy, Elsevier, vol. 277(C).
    2. Yang, Tianle & Li, Fangmin & Du, Min & Huang, Miao & Li, Yinuo, 2023. "Impacts of alternative energy production innovation on reducing CO2 emissions: Evidence from China," Energy, Elsevier, vol. 268(C).
    3. Wei Wei & Qiao Fan & Aijun Guo, 2022. "China’s Industrial TFPs at the Prefectural Level and the Law of Their Spatial–Temporal Evolution," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    4. Yang Sun & Mengna Du & Leying Wu & Changzhe Li & Yulong Chen, 2022. "Evaluating the Effects of Renewable Energy Consumption on Carbon Emissions of China’s Provinces: Based on Spatial Durbin Model," Land, MDPI, vol. 11(8), pages 1-17, August.
    5. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(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. 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).
    2. Hao, Yu & Liu, Yiming & Weng, Jia-Hsi & Gao, Yixuan, 2016. "Does the Environmental Kuznets Curve for coal consumption in China exist? New evidence from spatial econometric analysis," Energy, Elsevier, vol. 114(C), pages 1214-1223.
    3. Wei Chen & Rui He & Qun Wu, 2017. "A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method," Complexity, Hindawi, vol. 2017, pages 1-11, December.
    4. Wang, Xianzhu & Huang, He & Hong, Jingke & Ni, Danfei & He, Rongxiao, 2020. "A spatiotemporal investigation of energy-driven factors in China: A region-based structural decomposition analysis," Energy, Elsevier, vol. 207(C).
    5. Atella, Vincenzo & Belotti, Federico & Depalo, Domenico & Piano Mortari, Andrea, 2014. "Measuring spatial effects in the presence of institutional constraints: The case of Italian Local Health Authority expenditure," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 232-241.
    6. Wang, Weilong & Wang, Jianlong & Wu, Haitao, 2024. "The impact of energy-consuming rights trading on green total factor productivity in the context of digital economy: Evidence from listed firms in China," Energy Economics, Elsevier, vol. 131(C).
    7. Haller, Peter & Heuermann, Daniel F., 2016. "Job search and hiring in local labor markets: Spillovers in regional matching functions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 125-138.
    8. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2019. "The sustainability of China’s metal industries: features, challenges and future focuses," Resources Policy, Elsevier, vol. 60(C), pages 215-224.
    9. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    10. Juan Aparicio & Jose Manuel Cordero & Carlos Díaz-Caro, 2020. "Efficiency and productivity change of regional tax offices in Spain: an empirical study using Malmquist–Luenberger and Luenberger indices," Empirical Economics, Springer, vol. 59(3), pages 1403-1434, September.
    11. Chen, Lifeng & Wang, Kaifeng, 2022. "The spatial spillover effect of low-carbon city pilot scheme on green efficiency in China's cities: Evidence from a quasi-natural experiment," Energy Economics, Elsevier, vol. 110(C).
    12. Feng Ye & Zhongna Yang & Mark Yu & Susan Watson & Ashley Lovell, 2023. "Can Market-Oriented Reform of Agricultural Subsidies Promote the Growth of Agricultural Green Total Factor Productivity? Empirical Evidence from Maize in China," Agriculture, MDPI, vol. 13(2), pages 1-20, January.
    13. Sheng, Jichuan & Qiu, Wenge, 2022. "Water-use technical efficiency and income: Evidence from China's South-North Water Transfer Project," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    14. hu, zongyi & tang, liwei & su, jin, 2013. "区域环境绩效测度及收敛性分析 [Regional eco-performance measure and its convergence]," MPRA Paper 60367, University Library of Munich, Germany.
    15. Wang, Qiang & Lin, Jian & Zhou, Kan & Fan, Jie & Kwan, Mei-Po, 2020. "Does urbanization lead to less residential energy consumption? A comparative study of 136 countries," Energy, Elsevier, vol. 202(C).
    16. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    17. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    18. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    19. Xi Qin & Xiaoling Wang & Yusen Xu & Yawen Wei, 2019. "Exploring Driving Forces of Green Growth: Empirical Analysis on China’s Iron and Steel Industry," Sustainability, MDPI, vol. 11(4), pages 1-11, February.
    20. Yao-yao Song & Xian-tong Ren & Guo-liang Yang, 2023. "Capacity utilization change over time," Journal of Productivity Analysis, Springer, vol. 59(1), pages 61-78, February.

    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:251:y:2022:i:c:s0360544222008209. 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.