IDEAS home Printed from https://ideas.repec.org/a/eee/streco/v74y2025icp1008-1019.html
   My bibliography  Save this article

Harnessing government digital attention: Reducing carbon emissions through the pathways of digitalization

Author

Listed:
  • Zhang, Pan
  • Wang, Shihong
  • Li, Boying

Abstract

Identifying the digital pathway is important for promoting regional green development and attracting diverse market entities. Existing studies predominantly conceptualized digitalization as a static state rather than a dynamic process, and failed to explore how government digital initiatives influence green development through facilitating digital economy growth. The paper employs instrumental variable analysis, threshold regression, and causal mediation analysis to investigate impacts of government digital attention on green development, with a focus on the mediating role of digital economy. It finds digital attention can lower carbon emissions by stimulating digital economy growth, and robustness tests support these findings. The results reveal that the digitalization process, from digital attention to a digital economy, enhances green development. Therefore, governments should take a more proactive approach to engaging market players in the digital sector.

Suggested Citation

  • Zhang, Pan & Wang, Shihong & Li, Boying, 2025. "Harnessing government digital attention: Reducing carbon emissions through the pathways of digitalization," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 1008-1019.
  • Handle: RePEc:eee:streco:v:74:y:2025:i:c:p:1008-1019
    DOI: 10.1016/j.strueco.2025.07.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0954349X25001171
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.strueco.2025.07.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    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:eee:streco:v:74:y:2025:i:c:p:1008-1019. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/525148 .

    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.