{"title":"Natural resources and green economic growth: The role of artificial intelligence","authors":"Chien-Chiang Lee , Chengnan Xuan , Fuhao Wang","doi":"10.1016/j.resourpol.2024.105322","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":20970,"journal":{"name":"Resources Policy","volume":"98 ","pages":"Article 105322"},"PeriodicalIF":10.2000,"publicationDate":"2024-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Resources Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0301420724006895","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Resources Policy is an international journal focused on the economics and policy aspects of mineral and fossil fuel extraction, production, and utilization. It targets individuals in academia, government, and industry. The journal seeks original research submissions analyzing public policy, economics, social science, geography, and finance in the fields of mining, non-fuel minerals, energy minerals, fossil fuels, and metals. Mineral economics topics covered include mineral market analysis, price analysis, project evaluation, mining and sustainable development, mineral resource rents, resource curse, mineral wealth and corruption, mineral taxation and regulation, strategic minerals and their supply, and the impact of mineral development on local communities and indigenous populations. The journal specifically excludes papers with agriculture, forestry, or fisheries as their primary focus.