Assessing the impact of artificial intelligence on the transition to renewable energy? Analysis of US states under policy uncertainty

被引:0
|
作者
Fang, Yuzhu [1 ]
Lee, Chi-Chuan [1 ,2 ]
Li, Xinghao [2 ,3 ]
机构
[1] Southwestern Univ Finance & Econ, Sch Publ Adm, Chengdu, Peoples R China
[2] Minist Educ, Big Data Lab Financial Secur & Behav, Lab Philosophy & Social Sci, SWUFE, Chengdu, Peoples R China
[3] Southwestern Univ Finance & Econ, Res Inst Digital Econ & Interdisciplinary Sci, 555 Liutai Ave, Chengdu, Peoples R China
关键词
Technological innovation; Sustainable development goals; Economic policy uncertainty; Carbon neutrality; Regional heterogeneity; AREA; AI;
D O I
10.1016/j.renene.2025.122969
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the context of the increasingly severe global climate change, technological innovation and energy transition have formed a critical path to achieving sustainable development. This research employs panel data from 51 states/district in the United States for 2018-2021 to explore the impact of artificial intelligence (AI) development on energy transition and discusses the moderating effect of economic policy uncertainty. The results indicate that AI has a significantly positive impact on energy transition. Economic policy uncertainty at the state level has a significantly positive moderating effect on AI's impact on energy transition, but national-level policy uncertainty does not affect their nexus. AI has a significantly positive correlation with energy transition in states with high electricity prices, low electricity consumption, and those states that are net electricity consumers, while its impact is also significant in regions with frequent extreme weather events. Heterogeneity analysis based on different geographical locations and economic characteristics shows that AI significantly promotes energy transition in the West and Midwest regions. Furthermore, AI significantly promotes the consumption of wind, solar, and hydropower, but inhibits biomass consumption. From the above results, this paper offers relevant policy recommendations.
引用
收藏
页数:10
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