IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i14p5917-d1433120.html
   My bibliography  Save this article

Digital Economy and Urban Low-Carbon Transition: Theoretical Model and New Mechanisms

Author

Listed:
  • Kunpeng Ai

    (School of Political Science and Public Administration, Henan Normal University, Xinxiang 453007, China)

  • Wenjie Zhang

    (School of Management, Wuhan Polytechnic University, Wuhan 430048, China)

  • Xiang-Wu Yan

    (School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, China)

Abstract

Urban areas are at the forefront of economic activity and notably contribute to carbon emissions. Transforming cities to low-carbon models is imperative for addressing climate change. The digital economy (DE) has emerged as a pivotal force in driving global economic progress, offering unique benefits that support urban low-carbon transitions. Despite extensive research on the correlation between DE and urban low-carbon transformation (ULCT), there remains a gap in studies utilizing mathematical models to delve into the intrinsic mechanisms and deeper impacts. This research evaluates the influence of DE on ULCT by examining data from 283 prefecture-level and above cities in China, spanning from 2011 to 2019, through both theoretical frameworks and empirical testing. The analysis reveals that DE substantially fosters ULCT, a conclusion reinforced by rigorous robustness and endogeneity checks. Notably, DE’s impact on ULCT is more significant in southern cities than in northern ones. Interestingly, while DE in the Yangtze River Delta and Chengdu-Chongqing urban clusters showed limited promotion of ULCT, it had the highest impact in the middle reaches of the Yangtze River. DE enhances ULCT through several pathways, including scale economy effect, heightened public environmental awareness effects, and increased income effects, contributing 6.64%, 9.84%, and 16.2%, respectively. Furthermore, the effects of public environmental awareness and income are particularly pronounced in southern regions, unlike in northern areas. This study not only expands the theoretical research on the relationship between the digital economy and urban low-carbon transition but also provides specific guidance and support for related policy formulation and implementation. This helps promote cities toward more environmentally friendly and sustainable development. Furthermore, the conclusions of this study have important reference value for other major polluting countries (such as the US, India, and Germany). Different countries and regions should formulate targeted low-carbon transition strategies based on their own DE development, income levels, and public environmental awareness. This will effectively promote urban low-carbon transitions, achieving a win-win situation for economic development and environmental protection.

Suggested Citation

  • Kunpeng Ai & Wenjie Zhang & Xiang-Wu Yan, 2024. "Digital Economy and Urban Low-Carbon Transition: Theoretical Model and New Mechanisms," Sustainability, MDPI, vol. 16(14), pages 1-22, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5917-:d:1433120
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/14/5917/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/14/5917/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Ning Xu & He Zhang & Tixin Li & Xiao Ling & Qian Shen, 2022. "How Big Data Affect Urban Low-Carbon Transformation—A Quasi-Natural Experiment from China," IJERPH, MDPI, vol. 19(23), pages 1-16, December.
    3. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-765, September.
    4. Baiardi, Donatella & Morana, Claudio, 2021. "Climate change awareness: Empirical evidence for the European Union," Energy Economics, Elsevier, vol. 96(C).
    5. William Brock & M. Taylor, 2010. "The Green Solow model," Journal of Economic Growth, Springer, vol. 15(2), pages 127-153, June.
    6. Lans Bovenberg, A. & Smulders, Sjak, 1995. "Environmental quality and pollution-augmenting technological change in a two-sector endogenous growth model," Journal of Public Economics, Elsevier, vol. 57(3), pages 369-391, July.
    7. Nordhaus, William D., 1993. "Rolling the 'DICE': an optimal transition path for controlling greenhouse gases," Resource and Energy Economics, Elsevier, vol. 15(1), pages 27-50, March.
    8. 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.
    9. Zhuoxi Yu & Shan Liu & Zhichuan Zhu, 2022. "Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    10. Hanhua Shao & Jixin Cheng & Yuansheng Wang & Xiaoming Li, 2022. "Can Digital Finance Promote Comprehensive Carbon Emission Performance? Evidence from Chinese Cities," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    11. Ping Chen & Jiawei Gao & Zheng Ji & Han Liang & Yu Peng, 2022. "Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities," Energies, MDPI, vol. 15(15), pages 1-16, August.
    12. Yi, Ming & Liu, Yafen & Sheng, Mingyue Selena & Wen, Le, 2022. "Effects of digital economy on carbon emission reduction: New evidence from China," Energy Policy, Elsevier, vol. 171(C).
    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. Simon Dietz & Nicholas Stern, 2014. "Endogenous growth, convexity of damages and climate risk: how Nordhaus� framework supports deep cuts in carbon emissions," GRI Working Papers 159, Grantham Research Institute on Climate Change and the Environment.
    2. Ofori, Isaac K & Gbolonyo, Emmanuel Y. & Ojong, Nathanael, 2022. "Foreign Direct Investment and Inclusive Green Growth in Africa: Energy Efficiency Contingencies and Thresholds," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1-58.
    3. Ofori, Isaac K. & Gbolonyo, Emmanuel Y. & Ojong, Nathanael, 2022. "Foreign Direct Investment and Inclusive Green Growth in Africa: Energy Efficiency Contingencies and Thresholds," MPRA Paper 115379, University Library of Munich, Germany, revised 09 Nov 2022.
    4. Alassane DRABO, 2010. "Interrelationships between Health, Environment Quality and Economic Activity: What Consequences for Economic Convergence," Working Papers 201005, CERDI.
    5. Maxime Menuet & Alexandru Minea & Patrick Villieu & Anastasios Xepapadeas, 2020. "Economic Growth and the Environment: A Theoretical Reappraisal," DEOS Working Papers 2031, Athens University of Economics and Business.
    6. Ofori, Isaac K. & Gbolonyo, Emmanuel Y. & Ojong, Nathanael, 2023. "Foreign direct investment and inclusive green growth in Africa: Energy efficiency contingencies and thresholds," Energy Economics, Elsevier, vol. 117(C).
    7. Yukun Ma & Shaojian Wang & Chunshan Zhou, 2023. "Can the Development of the Digital Economy Reduce Urban Carbon Emissions? Case Study of Guangdong Province," Land, MDPI, vol. 12(4), pages 1-13, March.
    8. Ralph Hippe, 2015. "Why did the knowledge transition occur in the West and not in the East? ICT and the role of governments in Europe, East Asia and the Muslim world," GRI Working Papers 180, Grantham Research Institute on Climate Change and the Environment.
    9. Brock, William A. & Taylor, M. Scott, 2005. "Economic Growth and the Environment: A Review of Theory and Empirics," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 28, pages 1749-1821, Elsevier.
    10. Isaac K. Ofori & Emmanuel Y. Gbolonyo & Nathanael Ojong, 2022. "Foreign Direct Investment and Inclusive Green Growth in Africa: Energy Efficiency Contingencies and Thresholds," Working Papers 22/089, European Xtramile Centre of African Studies (EXCAS).
    11. Lal, Amant, 2009. "An Empirical Time Series Model of Economic Growth and Environment," MPRA Paper 66475, University Library of Munich, Germany.
    12. Isaac K. Ofori & Emmanuel Y. Gbolonyo & Nathanael Ojong, 2022. "Foreign Direct Investment and Inclusive Green Growth in Africa: Energy Efficiency Contingencies and Thresholds," Working Papers of the African Governance and Development Institute. 22/089, African Governance and Development Institute..
    13. Fangzhi Wang & Hua Liao & Richard S. J. Tol, 2023. "Baumol's Climate Disease," Papers 2312.00160, arXiv.org.
    14. Ning Xu & He Zhang & Tixin Li & Xiao Ling & Qian Shen, 2022. "How Big Data Affect Urban Low-Carbon Transformation—A Quasi-Natural Experiment from China," IJERPH, MDPI, vol. 19(23), pages 1-16, December.
    15. Sabrina Auci & Giovanni Trovato, 2018. "The environmental Kuznets curve within European countries and sectors: greenhouse emission, production function and technology," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(3), pages 895-915, December.
    16. Henri de Groot, 2001. "On the optimal timing of reductions of CO2 emissions; an economists' perspective on the debate on "when flexibility"," CPB Discussion Paper 1.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    17. Johan Eyckmans & Michael Finus, 2006. "New roads to international environmental agreements: the case of global warming," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 7(4), pages 391-414, December.
    18. Smulders, Sjak & Gradus, Raymond, 1996. "Pollution abatement and long-term growth," European Journal of Political Economy, Elsevier, vol. 12(3), pages 505-532, November.
    19. Rosendahl, Knut Einar, 2004. "Cost-effective environmental policy: implications of induced technological change," Journal of Environmental Economics and Management, Elsevier, vol. 48(3), pages 1099-1121, November.
    20. Matilda Baret & Maxime Menuet, 2024. "Fiscal and Environmental Sustainability: Is Public Debt Environmentally Friendly?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(6), pages 1497-1520, June.

    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:16:y:2024:i:14:p:5917-:d:1433120. 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.