Can artificial intelligence technology reduce carbon emissions? A global perspective

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics Pub Date : 2025-02-03 DOI:10.1016/j.eneco.2025.108285

Qingfeng Cao , Chuenyu Chi , Junhui Shan

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引用次数: 0

Abstract

Whether Artificial Intelligence (AI) technology can contribute to carbon reduction remains an issue that requires further research. We measure the level of AI technology by the number of AI patents filed in each country, and use panel data from 30 countries spanning 2005 to 2020 to examine the impact of AI technology on carbon emissions. Our findings indicate that AI technology significantly reduces carbon emission levels. This conclusion remains robust after endogeneity and various robustness tests. Mechanism tests reveal that AI technology improves energy efficiency by reducing per capita carbon emissions and the energy intensity of primary energy. Additionally, AI technology reduces carbon emissions by inducing skill-biased and routine-biased technological change. When government regulation is more flexible, the carbon-reducing effect of AI technology is stronger. Further analysis indicates that AI technology has a significant impact on reducing carbon emissions in countries that are closer to the leading country in AI technology, have lower income level, and are highly dependent on traditional fossil fuels. Moreover, the carbon reduction effects of AI technology applied to energy management are more significant. Thus, promoting the innovation and diffusion of AI technology on a global scale plays a crucial role in advancing global carbon reduction targets.

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来源期刊

Energy Economics ECONOMICS-

CiteScore

18.60

自引率

12.50%

发文量

524

期刊介绍： Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.