IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i16p10104-d888608.html
   My bibliography  Save this article

Spatiotemporal Coupling Effect of Regional Economic Development and De-Carbonisation of Energy Use in China: Empirical Analysis Based on Panel and Spatial Durbin Models

Author

Listed:
  • Xintong Zhang

    (School of Management, China University of Mining and Technology, Beijing 100083, China)

  • Cuijie Lu

    (School of Management, China University of Mining and Technology, Beijing 100083, China)

  • Yuncai Ning

    (School of Management, China University of Mining and Technology, Beijing 100083, China)

  • Jingtao Wang

    (School of Management, China University of Mining and Technology, Beijing 100083, China)

Abstract

The synergistic development of economic construction and low-carbon transformation of energy systems must be promoted for building a green, low-carbon, and cyclic economic system and achieving the “double carbon” goal in China. Based on the panel data of 30 provincial-level administrative regions in China from 2015 to 2019, the global entropy method, coupling coordination degree model, and spatial statistical analysis methods are applied to analyse the factors affecting the coupling effect. The coordination degree increased in the study period, with Beijing, Shanghai, Tianjin, Jiangsu, and Zhejiang being the regions with the highest values. The spatial distribution of the coupling coordination degree is strongly positively correlated with the eastern provincial-level administrative regions located in the high–high concentration area of the Moran scatterplot and western provincial-level administrative regions concentrated in the low–low concentration area. The spatial association pattern is stable in the study period, with only two provinces exhibiting a transition: Shandong province made the transition to high–high agglomeration areas, and Liaoning province made the transition to low–low agglomeration areas. The level of regional economy, urbanization process, energy consumption structure, and level of investment in science and innovation enhance the coupling coordination degree, whereas the industrial structure deteriorates this degree.

Suggested Citation

  • Xintong Zhang & Cuijie Lu & Yuncai Ning & Jingtao Wang, 2022. "Spatiotemporal Coupling Effect of Regional Economic Development and De-Carbonisation of Energy Use in China: Empirical Analysis Based on Panel and Spatial Durbin Models," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10104-:d:888608
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/16/10104/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/16/10104/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    2. Meicun Li & Chunmei Mao, 2019. "Spatial-Temporal Variance of Coupling Relationship between Population Modernization and Eco-Environment in Beijing-Tianjin-Hebei," Sustainability, MDPI, vol. 11(4), pages 1-13, February.
    3. Liam Brunt & Cecilia García-Peñalosa, 2022. "Urbanisation and the Onset of Modern Economic Growth," The Economic Journal, Royal Economic Society, vol. 132(642), pages 512-545.
    4. Yu Liu & Hongwei Xiao & Precious Zikhali & Yingkang Lv, 2014. "Carbon Emissions in China: A Spatial Econometric Analysis at the Regional Level," Sustainability, MDPI, vol. 6(9), pages 1-19, September.
    5. Mingcui Su & Zeng Lian & Jianjun Li, 2016. "An analysis of the relationship between energy consumption and economic growth: Evidence from the BRICS," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2016(1), pages 73-89.
    6. Sharma, Susan Sunila, 2011. "Determinants of carbon dioxide emissions: Empirical evidence from 69 countries," Applied Energy, Elsevier, vol. 88(1), pages 376-382, January.
    7. Yanjing Zhang & Zhengguo Su & Guan Li & Yuefei Zhuo & Zhongguo Xu, 2018. "Spatial-Temporal Evolution of Sustainable Urbanization Development: A Perspective of the Coupling Coordination Development Based on Population, Industry, and Built-Up Land Spatial Agglomeration," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    8. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    9. Poumanyvong, Phetkeo & Kaneko, Shinji, 2010. "Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis," Ecological Economics, Elsevier, vol. 70(2), pages 434-444, December.
    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. Hanen Ragoubi & Zouheir Mighri, 2021. "Spillover effects of trade openness on CO2 emissions in middle‐income countries: A spatial panel data approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 835-877, June.
    2. Azevedo, I. & Leal, V., 2021. "A new model for ex-post quantification of the effects of local actions for climate change mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    3. Gritli, Mohamed Ilyes & Charfi, Fatma Marrakchi, 2023. "The determinants of oil consumption in Tunisia: Fresh evidence from NARDL approach and asymmetric causality test," Energy, Elsevier, vol. 284(C).
    4. Wang, Yuan & Zhang, Xiang & Kubota, Jumpei & Zhu, Xiaodong & Lu, Genfa, 2015. "A semi-parametric panel data analysis on the urbanization-carbon emissions nexus for OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 704-709.
    5. Cerdeira Bento, João Paulo, 2014. "The determinants of CO2 emissions: empirical evidence from Italy," MPRA Paper 59166, University Library of Munich, Germany.
    6. Asane-Otoo, Emmanuel, 2015. "Carbon footprint and emission determinants in Africa," Energy, Elsevier, vol. 82(C), pages 426-435.
    7. Shahbaz, Muhammad & Haouas, Ilham & Hoang, Thi Hong Van, 2019. "Economic growth and environmental degradation in Vietnam: Is the environmental Kuznets curve a complete picture?," Emerging Markets Review, Elsevier, vol. 38(C), pages 197-218.
    8. Yan-Qing Kang & Tao Zhao & Peng Wu, 2016. "Impacts of energy-related CO 2 emissions in China: a spatial panel data technique," 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. 81(1), pages 405-421, March.
    9. Ji Han & Xing Meng & Yanqi Zhang & Jiabin Liu, 2017. "The Impact of Infrastructure Stock Density on CO 2 Emissions: Evidence from China Provinces," Sustainability, MDPI, vol. 9(12), pages 1-13, December.
    10. Hussain Ali Bekhet & Nor Salwati Othman & Tahira Yasmin, 2020. "Interaction Between Environmental Kuznet Curve and Urban Environment Transition Hypotheses in Malaysia," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 384-402.
    11. Alex O. Acheampong, 2022. "The impact of de facto globalization on carbon emissions: Evidence from Ghana," International Economics, CEPII research center, issue 170, pages 156-173.
    12. Sheng, Pengfei & Guo, Xiaohui, 2016. "The Long-run and Short-run Impacts of Urbanization on Carbon Dioxide Emissions," Economic Modelling, Elsevier, vol. 53(C), pages 208-215.
    13. Ekpeno L. Effiong, 2018. "On the urbanization-pollution nexus in Africa: a semiparametric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 445-456, January.
    14. Charfeddine, Lanouar & Ben Khediri, Karim, 2016. "Financial development and environmental quality in UAE: Cointegration with structural breaks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1322-1335.
    15. Niu, Honglei & Lekse, William, 2017. "Carbon emission effect of urbanization at regional level: Empirical evidence from China," Economics Discussion Papers 2017-62, Kiel Institute for the World Economy (IfW Kiel).
    16. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    17. Wang, Shaojian & Fang, Chuanglin & Guan, Xingliang & Pang, Bo & Ma, Haitao, 2014. "Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces," Applied Energy, Elsevier, vol. 136(C), pages 738-749.
    18. Dominik Hartmann & Diogo Ferraz & Mayra Bezerra & Andreas Pyka & Flavio L. Pinheiro, 2021. "Comparing cars with apples? Identifying the appropriate benchmark countries for relative ecological pollution rankings and international learning," Papers 2107.14365, arXiv.org.
    19. Wang, Zhaohua & Rasool, Yasir & Zhang, Bin & Ahmed, Zahoor & Wang, Bo, 2020. "Dynamic linkage among industrialisation, urbanisation, and CO2 emissions in APEC realms: Evidence based on DSUR estimation," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 382-389.
    20. Mohammed Musah & Yusheng Kong & Isaac Adjei Mensah & Stephen Kwadwo Antwi & Mary Donkor, 2021. "The connection between urbanization and carbon emissions: a panel evidence from West Africa," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11525-11552, August.

    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:14:y:2022:i:16:p:10104-:d:888608. 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.