人工智能对全球能源脆弱性的影响

IF 7.9 2区 经济学 Q1 ECONOMICS
Qingyuan Zhu , Chenhao Sun , Chengzhen Xu , Qianqian Geng
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引用次数: 0

摘要

研究人工智能(AI)对能源脆弱性(EVI)的影响,对于了解技术进步如何改变能源系统的复原力和可持续性至关重要。然而,它们之间的定量关系仍然缺乏实证证据。本研究首先从能源安全、能源消耗、能源效率和能源可用性的角度构建了 2000 年至 2019 年全球 54 个经济体的能源脆弱性指数。然后,采用固定效应模型研究人工智能与经济脆弱性指数之间的关系。结果表明:(1) 人工智能可以显著降低全球经济脆弱性指数。经过多次稳健性检验,核心结论仍然可靠。(2)机制分析表明,人工智能可以通过促进金融发展和技术进步来降低经济脆弱性指数。(3)异质性分析表明,人工智能对经济脆弱性指数的阻碍作用在低收入和工业化水平较低的国家更为明显。此外,在工业 4.0 和金融危机之后,人工智能对经济脆弱性指数的阻碍作用更加明显。据此,进一步提出了一些政策影响,以减少全球经济脆弱性指数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of artificial intelligence on global energy vulnerability
Investigating the effect of artificial intelligence (AI) on energy vulnerability (EVI) is crucial to understanding how technological advances are changing the resilience and sustainability of energy systems. However, their quantitative relationship still lacks empirical evidence. This study first constructs the EVI of 54 global economies from the perspective of energy security, energy consumption, energy efficiency, and energy availability from 2000 to 2019. Then, a fixed-effect model is employed to investigate the relationship between AI and EVI. Results show that (1) AI can considerably reduce global EVI. The core findings remain reliable after several robustness checks. (2) Mechanism analysis implies that AI can reduce EVI by promoting financial development and technological progress. (3) Heterogeneity analysis implies that the impeding role of AI on EVI is more pronounced in countries with low incomes and industrialization levels. Furthermore, the hindering effect of AI on EVI is strengthened after Industry 4.0 and the financial crisis. Some policy implications are further proposed accordingly to reduce global EVI.
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来源期刊
CiteScore
9.80
自引率
9.20%
发文量
231
审稿时长
93 days
期刊介绍: Economic Analysis and Policy (established 1970) publishes articles from all branches of economics with a particular focus on research, theoretical and applied, which has strong policy relevance. The journal also publishes survey articles and empirical replications on key policy issues. Authors are expected to highlight the main insights in a non-technical introduction and in the conclusion.
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