IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i10p4288-d1397685.html
   My bibliography  Save this article

Can Digital Finance Enable China’s Industrial Carbon Unlocking under Environmental Regulatory Constraints? Joint Tests of Regression Analysis and Qualitative Comparative Analysis

Author

Listed:
  • Weicheng Xu

    (School of Economics, Ocean University of China, Qingdao 266100, China
    Institute of Marine Development, Ocean University of China, Qingdao 266100, China)

  • Hanxia Li

    (School of Economics, Ocean University of China, Qingdao 266100, China)

Abstract

Sustainable development goals challenge the carbon lock-in dilemma of the industrial economy, and identifying the motivation and mechanism behind carbon unlocking has become an urgent priority. With its inclusive and precise advantages, digital finance (DF) provides a new impetus for the economy’s low-carbon transformation, while reasonable environmental regulation (ER) acts as an important guiding constraint. We focus on the carbon unlocking performance of DF under ER constraints. After constructing and calculating the industrial carbon unlocking efficiency (ICUE), we observe the trends of ICUE fluctuating positively, clustering towards the eastern region, and polarization. Subsequently, based on theoretical analyses, we explore the marginal and configuration effects of DF and ER in improving ICUE using panel data from 30 Chinese provinces between 2011 and 2021 and adopt a mixed research method with regression analysis (Tobit hierarchical regression and quantile regression for panel data (QRPD)) and dynamic fuzzy-set qualitative comparative analysis (fsQCA). The regression analysis results show that DF can notably enhance China’s provincial ICUE, with ER generally serving as a positive moderator; however, the unlocking potential of informal environmental regulations needs further exploration. As ICUE improves in a specific location or time, the positive contribution of DF to ICUE also increases, whereas the moderating effect of ER exhibits an optimal range and follows an inverted U-shape. The dynamic fsQCA results support the findings of the regression analysis and further emphasize that effective cooperation between DF and ER is crucial for high ICUE, while inadequate DF support and the absence of formal environmental regulations remain bottlenecks in industrial carbon lock-in. Moreover, configuration paths demonstrate clear path dependency in both time and space, indicating a prolonged unlocking endeavor.

Suggested Citation

  • Weicheng Xu & Hanxia Li, 2024. "Can Digital Finance Enable China’s Industrial Carbon Unlocking under Environmental Regulatory Constraints? Joint Tests of Regression Analysis and Qualitative Comparative Analysis," Sustainability, MDPI, vol. 16(10), pages 1-37, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4288-:d:1397685
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/10/4288/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/10/4288/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kathuria, Vinish, 2007. "Informal regulation of pollution in a developing country: Evidence from India," Ecological Economics, Elsevier, vol. 63(2-3), pages 403-417, August.
    2. Pargal, Sheoli & Wheeler, David, 1996. "Informal Regulation of Industrial Pollution in Developing Countries: Evidence from Indonesia," Journal of Political Economy, University of Chicago Press, vol. 104(6), pages 1314-1327, December.
    3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    4. Mattauch, Linus & Creutzig, Felix & Edenhofer, Ottmar, 2015. "Avoiding carbon lock-in: Policy options for advancing structural change," Economic Modelling, Elsevier, vol. 50(C), pages 49-63.
    5. Fang, Guochang & Gao, Zhengye & Tian, Lixin & Fu, Min, 2022. "What drives urban carbon emission efficiency? – Spatial analysis based on nighttime light data," Applied Energy, Elsevier, vol. 312(C).
    6. Ouyang, Xiaoling & Fang, Xingming & Cao, Yan & Sun, Chuanwang, 2020. "Factors behind CO2 emission reduction in Chinese heavy industries: Do environmental regulations matter?," Energy Policy, Elsevier, vol. 145(C).
    7. Li, Jie & Wu, Yu & Xiao, Jing Jian, 2020. "The impact of digital finance on household consumption: Evidence from China," Economic Modelling, Elsevier, vol. 86(C), pages 317-326.
    8. Solji Nam & Jungwoo Shin & Jaena Ryu & Hanee Ryu, 2021. "Climate impacts on geographical changes in the energy industry," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 478-488, January.
    9. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    10. Dan Luo & Man Luo & Jiamin Lv, 2022. "Can Digital Finance Contribute to the Promotion of Financial Sustainability? A Financial Efficiency Perspective," Sustainability, MDPI, vol. 14(7), pages 1-29, March.
    11. Wang, Yuyan & Wu, Qinghua & Razi, Ummara, 2023. "Drivers and mitigants of resources consumption in China: Discovering the role of digital finance and environmental regulations," Resources Policy, Elsevier, vol. 80(C).
    12. You-Dong Li & Chen-Li Yan & Yun-Hui Zhao & Jia-Qi Bai, 2023. "Analysing Multiple Paths of Urban Low-Carbon Governance: A Fuzzy-Set Qualitative Comparative Analysis Method Based on 35 Key Cities in China," Sustainability, MDPI, vol. 15(9), pages 1-20, May.
    13. Zhao, Congyu & Dong, Kangyin & Jiang, Hong-Dian & Wang, Kun & Dong, Xiucheng, 2023. "How does energy poverty eradication realize the path to carbon unlocking? The case of China," Energy Economics, Elsevier, vol. 121(C).
    14. Lee, Chien-Chiang & Wang, Fuhao, 2022. "How does digital inclusive finance affect carbon intensity?," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 174-190.
    15. Yingzhi Xu & Biying Dong & Yan Chen & Hanwen Qin, 2022. "Effect of industrial transfer on carbon lock-in: a spatial econometric analysis of Chinese cities," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 65(6), pages 1024-1055, May.
    16. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    17. Li, Guoxiang & Wu, Haoyue & Jiang, Jieshu & Zong, Qingqing, 2023. "Digital finance and the low-carbon energy transition (LCET) from the perspective of capital-biased technical progress," Energy Economics, Elsevier, vol. 120(C).
    18. Langpap, Christian & Shimshack, Jay P., 2010. "Private citizen suits and public enforcement: Substitutes or complements?," Journal of Environmental Economics and Management, Elsevier, vol. 59(3), pages 235-249, May.
    19. Feng, Suling & Zhang, Rong & Li, Guoxiang, 2022. "Environmental decentralization, digital finance and green technology innovation," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 70-83.
    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. Zhao, Congyu & Dong, Kangyin & Lee, Chien-Chiang, 2024. "Carbon lock-in endgame: Can energy trilemma eradication contribute to decarbonization?," Energy, Elsevier, vol. 293(C).
    2. Zhao, Congyu & Dong, Kangyin & Wang, Kun & Dong, Xiucheng, 2022. "How does energy trilemma eradication reduce carbon emissions? The role of dual environmental regulation for China," Energy Economics, Elsevier, vol. 116(C).
    3. Xiangyang Yang & Zheng Zhang & Siqi Rao & Bei Liu & Yueyue Li, 2022. "How Does Environmental Information Disclosure Affect Pollution Emissions: Firm-Level Evidence from China," IJERPH, MDPI, vol. 19(19), pages 1-20, October.
    4. Xie, Rong-hui & Yuan, Yi-jun & Huang, Jing-jing, 2017. "Different Types of Environmental Regulations and Heterogeneous Influence on “Green” Productivity: Evidence from China," Ecological Economics, Elsevier, vol. 132(C), pages 104-112.
    5. Bin Fan & Mingyang Li, 2022. "The Effect of Heterogeneous Environmental Regulations on Carbon Emission Efficiency of the Grain Production Industry: Evidence from China’s Inter-Provincial Panel Data," Sustainability, MDPI, vol. 14(21), pages 1-27, November.
    6. Lv, Chengchao & Song, Jie & Lee, Chien-Chiang, 2022. "Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 502-521.
    7. Yiqun Hu & Xiong Dai & Li Zhao, 2022. "Digital Finance, Environmental Regulation, and Green Technology Innovation: An Empirical Study of 278 Cities in China," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
    8. Yaru Tang & Mengdi Liu & Fan Xia & Bing Zhang, 2024. "Informal regulation by nongovernmental organizations enhances corporate compliance: Evidence from a nationwide randomized controlled trial in China," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 43(1), pages 234-257, January.
    9. Timo Goeschl & Ole Jürgens, 2012. "Environmental quality and welfare effects of improving the reporting capability of citizen monitoring schemes," Journal of Regulatory Economics, Springer, vol. 42(3), pages 264-286, December.
    10. Zheng, Qiaoqiao & Wan, Liang & Wang, Shanyong & Chen, Zexian & Li, Jun & Wu, Jie & Song, Malin, 2023. "Will informal environmental regulation induce residents to form a green lifestyle? Evidence from China," Energy Economics, Elsevier, vol. 125(C).
    11. Tan, Yan & Uprasen, Utai, 2022. "The effect of foreign direct investment on renewable energy consumption subject to the moderating effect of environmental regulation: Evidence from the BRICS countries," Renewable Energy, Elsevier, vol. 201(P2), pages 135-149.
    12. Mingyong Hong & Mengjie Tian & Ji Wang, 2022. "Digital Inclusive Finance, Agricultural Industrial Structure Optimization and Agricultural Green Total Factor Productivity," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    13. Shen, Hongshan & Qin, Mengyao & Li, Tianyi & Zhang, Xuan & Zhao, Yang, 2024. "Digital finance and industrial structure upgrading: Evidence from Chinese counties," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    14. Davtalab-Olyaie, Mostafa & Begen, Mehmet A. & Yang, Zijiang & Asgharian, Masoud, 2024. "Incentivization in centrally managed systems: Inconsistencies resolution," Omega, Elsevier, vol. 129(C).
    15. Tang, Yunfeng & Zhang, Xuan & Lu, Shibao & Taghizadeh-Hesary, Farhad, 2023. "Digital finance and air pollution in China: Evolution characteristics, impact mechanism and regional differences," Resources Policy, Elsevier, vol. 86(PA).
    16. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    17. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    18. Aimin Zhang & Moses Nanyun Nankpan & Bo Zhou & Joseph Ato Forson & Edmund Nana Kwame Nkrumah & Samuel Evergreen Adjavon, 2024. "A COP28 Perspective: Does Chinese Investment and Fintech Help to Achieve the SDGs of African Economies?," Sustainability, MDPI, vol. 16(7), pages 1-14, April.
    19. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.
    20. Haixiang Xu & Rui Zhang, 2024. "Dynamic Analysis of Urban Land Use Efficiency in the Western Taiwan Strait Economic Zone," Land, MDPI, vol. 13(8), pages 1-26, 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:16:y:2024:i:10:p:4288-:d:1397685. 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.