IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v98y2024ics0301420724006895.html
   My bibliography  Save this article

Natural resources and green economic growth: The role of artificial intelligence

Author

Listed:
  • Lee, Chien-Chiang
  • Xuan, Chengnan
  • Wang, Fuhao

Abstract

Based on the panel data of 90 resource-based cities in China from 2011 to 2019, the study examines the impact of resource dependence on green economic growth, the transmission mechanism, and then analyzes the regulatory role played by artificial intelligence (AI). The benchmark results robustly show that resource dependence leads to the resource curse for green economic growth. Mechanism analysis shows that resource dependence inhibits the growth of the green economy by crowding out the private economy and human capital. At the same time, artificial intelligence will exacerbate the resource curse, especially in mature, environmentally regulated, fast-transitioning, resource-based cities in the East. Further research has shown that when the level of artificial intelligence exceeds a certain threshold, it alleviates the local resource curse. Our research not only explores a new perspective on the development of AI applications, but also provides precious recommendations for government departments to break the resource curse and achieve sustainable development.

Suggested Citation

  • Lee, Chien-Chiang & Xuan, Chengnan & Wang, Fuhao, 2024. "Natural resources and green economic growth: The role of artificial intelligence," Resources Policy, Elsevier, vol. 98(C).
    • Handle: RePEc:eee:jrpoli:v:98:y:2024:i:c:s0301420724006895
    DOI: 10.1016/j.resourpol.2024.105322
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420724006895
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2024.105322?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 search for a different version of it.

    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:jrpoli:v:98:y:2024:i:c:s0301420724006895. 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/30467 .

    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.