 Natural resources and green economic growth: The role of artificial intelligenceChien-Chiang Lee (), Chengnan Xuan and Fuhao Wang Resources Policy, 2024, vol. 98, issue C 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. Keywords: Natural resource dependence; Resource curse; Green economic growth; Artificial intelligence; China (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:98:y:2024:i:c:s0301420724006895 DOI: 10.1016/j.resourpol.2024.105322 Access Statistics for this article Resources Policy is currently edited by R. G. Eggert More articles in Resources Policy from Elsevier |
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