IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v142y2025ics0140988324008788.html

Corrigendum to “Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement” [Energy Economics Volume 131, March 2024, 107388]

Author

Listed:
  • Chishti, Muhammad Zubair
  • Xia, Xiqiang
  • Dogan, Eyup

Abstract

This study contributes to the existing literature by investigating and confirming a range of diverse outcomes related to the interplay of factors shaping the global energy transition (ET). Employing advanced methodologies, including the extension of the QVAR technique to short-term (SR), medium-term (MR), and long-term (LR) connectedness analysis, as well as the application of the CQ method to explore relationships within varying market conditions and timeframes, the study examines the interconnectedness of critical variables: artificial intelligence (AI), the Belt and Road Initiative (BRI), the Paris Agreement (PA), green technologies (GT), geopolitical risk (GPR), and ET. The findings highlight several crucial insights. Firstly, all selected variables demonstrate substantial interconnectedness across different time horizons, except for MR, which exhibits comparatively weaker connectedness than SR and LR. Secondly, independent series reveal diverse impacts on ET across various market conditions and periods. For example, in SR, most series produce mixed effects on ET, with BRI having primarily adverse consequences and GPR predominantly yielding positive impacts. In MR, the influence of AI, PA, and GT on ET varies, while BRI enhances ET, and GPR essentially hampers it. Notably, in LR, AI, BRI, PA, and GT significantly promote ET, while GPR disrupts its progress. Additionally, the study underscores the dynamic and time-varying nature of the relationships between AI, BRI, PA, GT, GPR, and ET across different market conditions, thus holding essential implications for shaping global policies to foster sustainable energy transitions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Chishti, Muhammad Zubair & Xia, Xiqiang & Dogan, Eyup, 2025. "Corrigendum to “Understanding the effects of artificial intelligence on energy transition: The moderating role of Paris Agreement” [Energy Economics Volume 131, March 2024, 107388]," Energy Economics, Elsevier, vol. 142(C).
  • Handle: RePEc:eee:eneeco:v:142:y:2025:i:c:s0140988324008788
    DOI: 10.1016/j.eneco.2024.108169
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324008788
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.108169?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    More about this item

    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:eneeco:v:142:y:2025:i:c:s0140988324008788. 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/eneco .

    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.