IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i22p15874-d1278727.html
   My bibliography  Save this article

Research on the Impact of Green Finance and the Digital Economy on the Energy Consumption Structure in the Context of Carbon Neutrality

Author

Listed:
  • Tao Yang

    (Jincheng College of Nanjing University of Aeronautics and Astronautics, Nanjing 211156, China)

  • Rong Wang

    (Business School, Nanjing Xiaozhuang University, Nanjing 211171, China)

Abstract

Improving the structure of energy consumption (ECS) through green finance and the digital economy is one of the main paths to achieving the goal of carbon neutrality. This paper explores the impact of green finance and the digital economy on the ECS of 30 regions in China from 2007 to 2022 using the Generalized method of moments(GMM) model, further analyzes its heterogeneity, and then provides a reference for the scientific development of relevant decisions. The conclusions are as follows: (1) The change in the ECS is closely related to the degree of optimization of the ECS in the previous year, and this is a process of dynamic adjustment. The level of digital economy development can improve the ECS of the country as a whole and in the eastern and central regions, while the western regions have not yet played a significant role due to the underdevelopment of the digital economy. Green finance can inhibit fossil fuel energy consumption in all regions, and it promotes cleaner, more efficient, and low-carbon energy consumption, thereby improving the ECS. However, the impact effect is the largest in the east and smaller in the west. (2) The urbanization levels of the country as a whole and that of the central and western regions show a positive correlation with the results of energy consumption. However, in the eastern region, it shows an inhibitory effect on fossil fuel energy consumption, which can optimize the ECS. The industrial structures in all regions have positive impact coefficients; the development of industry is not conducive to the optimization of the ECS. Trade openness can improve the ECS only in the eastern region; technological progress in all regions can significantly improve the ECS. Based on the background of carbon neutrality, this paper reveals that green finance and the digital economy promote cleaner, more efficient, and lower carbon energy consumption and reduce the level of energy consumption. This paper also provides a reference for the scientific formulation of relevant decisions.

Suggested Citation

  • Tao Yang & Rong Wang, 2023. "Research on the Impact of Green Finance and the Digital Economy on the Energy Consumption Structure in the Context of Carbon Neutrality," Sustainability, MDPI, vol. 15(22), pages 1-19, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15874-:d:1278727
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/22/15874/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/22/15874/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Shahbaz, Muhammad & Lean, Hooi Hooi, 2012. "Does financial development increase energy consumption? The role of industrialization and urbanization in Tunisia," Energy Policy, Elsevier, vol. 40(C), pages 473-479.
    3. Tamazian, Artur & Bhaskara Rao, B., 2010. "Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies," Energy Economics, Elsevier, vol. 32(1), pages 137-145, January.
    4. Li, Menghan & Hamawandy, Nawzad Majeed & Wahid, Fazle & Rjoub, Husam & Bao, Zongke, 2021. "Renewable energy resources investment and green finance: Evidence from China," Resources Policy, Elsevier, vol. 74(C).
    5. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    6. Gregor Semieniuk & Mariana Mazzucato, 2018. "Financing Green Growth," Working Papers 210, Department of Economics, SOAS University of London, UK.
    7. Bourcet, Clémence, 2020. "Empirical determinants of renewable energy deployment: A systematic literature review," Energy Economics, Elsevier, vol. 85(C).
    8. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    9. Zhi-Fu Mi & Su-Yan Pan & Hao Yu & Yi-Ming Wei, 2014. "Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Beijing," CEEP-BIT Working Papers 51, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Moyer, Jonathan D. & Hughes, Barry B., 2012. "ICTs: Do they contribute to increased carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 919-931.
    11. Ivan A. Kapitonov & Tatiana G. Filosofova & Vitaly G. Korolev, 2019. "Development of Digital Economy in the Energy Industry-specific Modernization," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 273-282.
    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. Dong-Hyeon Kim & Yi-Chen Wu & Shu-Chin Lin, 2022. "Carbon dioxide emissions, financial development and political institutions," Economic Change and Restructuring, Springer, vol. 55(2), pages 837-874, May.
    2. Oğuz Saygın & Ömer İskenderoğlu, 2022. "Does the level of financial development affect renewable energy? Evidence from developed countries with system generalized method of moments (System‐GMM) and cross‐sectionally augmented autoregressive," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 1326-1342, October.
    3. Claire Giordano, 2023. "Revisiting the real exchange rate misalignment‐economic growth nexus via the across‐sector misallocation channel," Review of International Economics, Wiley Blackwell, vol. 31(4), pages 1329-1384, September.
    4. Acheampong, Alex O., 2019. "Modelling for insight: Does financial development improve environmental quality?," Energy Economics, Elsevier, vol. 83(C), pages 156-179.
    5. Chien, Fengsheng & Anwar, Ahsan & Hsu, Ching-Chi & Sharif, Arshian & Razzaq, Asif & Sinha, Avik, 2021. "The role of information and communication technology in encountering environmental degradation: Proposing an SDG framework for the BRICS countries," Technology in Society, Elsevier, vol. 65(C).
    6. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    7. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    8. Amuakwa-Mensah, Franklin & Klege, Rebecca A. & Adom, Philip K. & Amoah, Anthony & Hagan, Edmond, 2018. "Unveiling the energy saving role of banking performance in Sub-Sahara Africa," Energy Economics, Elsevier, vol. 74(C), pages 828-842.
    9. Deleidi, Matteo & Mazzucato, Mariana & Semieniuk, Gregor, 2020. "Neither crowding in nor out: Public direct investment mobilising private investment into renewable electricity projects," Energy Policy, Elsevier, vol. 140(C).
    10. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
    11. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    12. Catalán, Mario & Hoffmaister, Alexander W. & Harun, Cicilia Anggadewi, 2020. "Bank capital and lending: Evidence of nonlinearity from Indonesia," Journal of Asian Economics, Elsevier, vol. 68(C).
    13. Bertoldi, Paolo & Mosconi, Rocco, 2020. "Do energy efficiency policies save energy? A new approach based on energy policy indicators (in the EU Member States)," Energy Policy, Elsevier, vol. 139(C).
    14. Susie Lee & Ingmar Schumacher, 2011. "When does financial sector (in)stability induce financial reforms?," Working Papers hal-00637954, HAL.
    15. George E. Halkos & Michael L. Polemis, 2017. "Does Financial Development Affect Environmental Degradation? Evidence from the OECD Countries," Business Strategy and the Environment, Wiley Blackwell, vol. 26(8), pages 1162-1180, December.
    16. Shaiara Husain & Kazi Sohag & Yanrui Wu, 2024. "Proven Reserve Oil and Renewable Energy Nexus: Efficacy of Policy Stringency," Economics Discussion / Working Papers 24-02, The University of Western Australia, Department of Economics.
    17. Biørn, Erik, 2012. "The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation," Memorandum 02/2012, Oslo University, Department of Economics.
    18. Arnab Bhattacharjee & Sean Holly, 2011. "Structural interactions in spatial panels," Empirical Economics, Springer, vol. 40(1), pages 69-94, February.
    19. Francesco Venturini & Ana Rincon-Aznar & Dr Michela Vecchi, 2013. "ICT as a general purpose technology: spillovers, absorptive capacity and productivity performance," National Institute of Economic and Social Research (NIESR) Discussion Papers 416, National Institute of Economic and Social Research.
    20. Budnik, Katarzyna, 2020. "The effect of macroprudential policies on credit developments in Europe 1995-2017," Working Paper Series 2462, European Central Bank.

    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:15:y:2023:i:22:p:15874-:d:1278727. 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.