IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i24p16927-d1302108.html
   My bibliography  Save this article

How Does Green Finance Policy Affect the Capacity Utilization Rate of Polluting Enterprises?

Author

Listed:
  • Xing Cai

    (Hunan Key Laboratory of Macroeconomic Big Data Mining and Its Application, Hunan Normal University, Changsha 410081, China
    School of Business, Hunan Normal University, Changsha 410081, China)

  • Guoran Chen

    (School of Business, Hunan Normal University, Changsha 410081, China)

  • Fei Wang

    (School of Business, Hunan Normal University, Changsha 410081, China)

Abstract

Effectively addressing overcapacity is the main task of China’s deepening supply-side reform and represents an intrinsic requirement for achieving sustainable economic development. Green finance policy, as a kind of environmental regulation policy that influences the behavior of polluting enterprises, can not only effectively facilitate the green transformation of production methods but also have a significant effect on the capacity utilization rate of enterprises. We use the promulgation of the Guidance on Building a Green Financial System in 2016 as a quasinatural experiment and the differences-in-differences (DID) method to study the effect of green finance policies on the capacity utilization rates of polluting enterprises based on data from 2012 to 2020 on A-share listed companies on the Shanghai Stock Exchanges (SSE) and Shenzhen Stock Exchanges (SZSE). We obtained the following results: (1) The implementation of green finance policies markedly improved polluting enterprises’ capacity utilization rate, which was supported by a sequence of robustness tests; (2) The mechanism test revealed that green finance policies serve to rectify information asymmetry and constrain improper government interventions through credit resource allocation mechanisms, thereby inhibiting overinvestments in polluting enterprises and ultimately increasing the capacity utilization rate. Additionally, green finance policies can improve product quality and diversity by incentivizing polluting enterprises’ technological innovation, enabling products to better meet market demand, and ultimately improving the capacity utilization rate; (3) The results of the heterogeneity analysis indicate that, for state-owned and large-scale polluting enterprises, green finance policies play a stronger role in increasing the capacity utilization rate. We have enriched the research related to the policy effects of green finance and the impact of environmental regulation on the capacity utilization rate, thus providing a useful reference for China to utilize green finance policies to address overcapacity, promote the transition to a more environmentally sustainable economic society, and achieve sustainable development.

Suggested Citation

  • Xing Cai & Guoran Chen & Fei Wang, 2023. "How Does Green Finance Policy Affect the Capacity Utilization Rate of Polluting Enterprises?," Sustainability, MDPI, vol. 15(24), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16927-:d:1302108
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/24/16927/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/24/16927/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bruno De Borger & Kristiaan Kerstens, 2000. "The Malmquist Productivity Index and Plant Capacity Utilization," Scandinavian Journal of Economics, Wiley Blackwell, vol. 102(2), pages 303-310, June.
    2. Adam B. Jaffe & Karen Palmer, 1997. "Environmental Regulation And Innovation: A Panel Data Study," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 610-619, November.
    3. Christopher Wright, 2012. "Global Banks, the Environment, and Human Rights: The Impact of the Equator Principles on Lending Policies and Practices," Global Environmental Politics, MIT Press, vol. 12(1), pages 56-77, February.
    4. Berndt, Ernst R & Morrison, Catherine J, 1981. "Capacity Utilization Measures: Underlying Economic Theory and an Alternative Approach," American Economic Review, American Economic Association, vol. 71(2), pages 48-52, May.
    5. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    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. Yun Wang & Meiyi Xiong & Zhang-Hangjian Chen, 2025. "The Impact of Supply Chain Finance on Enterprises’ Capacity Utilization: An Empirical Study Based on A-Share Listed Manufacturing Companies," Sustainability, MDPI, vol. 17(16), pages 1-24, August.
    2. Liugang Ye & Zhenhua Fang, 2025. "The Impact of New-Quality Productivity on Environmental Pollution: Empirical Evidence from China," Sustainability, MDPI, vol. 17(7), pages 1-21, April.

    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. Bruno De Borger & Kristiaan Kerstens & Diego Prior & Ignace Van de Woestyne, 2013. "Static efficiency decompositions and capacity utilization: integrating economic and technical capacity notions," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3529-3529, August.
    2. Ma, Hongqi & Mei, Xinxiang & Tian, Yuan, 2020. "The impacts and potential mechanisms of credit support with regard to overcapacity: Based on theoretical and empirical analyses of steel enterprises," Resources Policy, Elsevier, vol. 68(C).
    3. Dale Squires & Kathleen Segerson, 2022. "Capacity and Capacity Utilization in Production Economics," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 24, pages 1001-1037, Springer.
    4. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    5. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    6. Jonas Hedlund & Carlos Oyarzun, 2018. "Imitation in heterogeneous populations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 937-973, June.
    7. Cao, Melanie & Shi, Shouyong, 2006. "Signaling in the Internet craze of initial public offerings," Journal of Corporate Finance, Elsevier, vol. 12(4), pages 818-833, September.
    8. Fang, Mingyue & Nie, Huihua & Shen, Xinyi, 2023. "Can enterprise digitization improve ESG performance?," Economic Modelling, Elsevier, vol. 118(C).
    9. Kraemer, Carlo & Noth, Markus & Weber, Martin, 2006. "Information aggregation with costly information and random ordering: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 59(3), pages 423-432, March.
    10. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    11. Cavatorta, Elisa & Guarino, Antonio & Huck, Steffen, 2024. "Social learning with partial and aggregate information: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 146(C), pages 292-307.
    12. Edgardo Arturo Ayala Gaytán, 2009. "Social network externalities and price dispersion in online markets," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.
    13. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    14. Boğaçhan Çelen & Kyle Hyndman, 2012. "An experiment of social learning with endogenous timing," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 251-268, September.
    15. Hiroshi Kitamura, 2007. "Capacity Expansion in Markets with Intertemporal Consumption Externalities," Discussion Papers in Economics and Business 07-11, Osaka University, Graduate School of Economics.
    16. Bohl, Martin T. & Branger, Nicole & Trede, Mark, 2017. "The case for herding is stronger than you think," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 30-40.
    17. Chen, Zhenling & Zhang, Xiaoling & Ni, Guohua, 2020. "Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions," Energy Policy, Elsevier, vol. 139(C).
    18. Hussinger, Katrin & Pellens, Maikel, 2019. "Guilt by association: How scientific misconduct harms prior collaborators," Research Policy, Elsevier, vol. 48(2), pages 516-530.
    19. Di Bella, Gabriel & Grigoli, Francesco, 2019. "Optimism, pessimism, and short-term fluctuations," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 79-96.
    20. Yang Shen & Xiuwu Zhang, 2022. "Study on the Impact of Environmental Tax on Industrial Green Transformation," IJERPH, MDPI, vol. 19(24), pages 1-18, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:24:p:16927-:d:1302108. 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.