Artificial intelligence and climate risk: A double machine learning approach

IF 7.5 1区 经济学 Q1 BUSINESS, FINANCE
Hua Yin , Xieyu Yin , Fenghua Wen
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引用次数: 0

Abstract

We study the use and environmental impact of AI technologies. We propose a measure of the country-level AI development index. Utilizing the double machine learning method, we discover a net mitigating impact of AI on climate risk. Mechanism analysis indicates that this influence primarily stems from advancements in resource utilization efficiency, the promotion of green innovation, the reinforcement of environmental policy effectiveness, and the augmentation of green finance. Heterogeneity analysis reveals that the mitigating effect of AI on climate risks is predominantly observed in developed countries and those with better institutional environments. Our results imply that while AI overall reduces climate risks, it can also contribute to the exacerbation of climate-related inequalities.
人工智能和气候风险:双重机器学习方法
我们研究人工智能技术的使用和对环境的影响。我们提出了一个国家级人工智能发展指数的衡量标准。利用双机器学习方法,我们发现人工智能对气候风险的净缓解影响。机制分析表明,这种影响主要来源于资源利用效率的提高、绿色创新的推进、环境政策有效性的增强和绿色金融的增强。异质性分析表明,人工智能对气候风险的缓解作用主要出现在发达国家和制度环境较好的国家。我们的研究结果表明,虽然人工智能总体上降低了气候风险,但它也可能加剧与气候相关的不平等。
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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