An inquiry into the nexus between artificial intelligence and energy poverty in the light of global evidence

Tao Ding, Hao Li, Li Liu and Kui Feng

Energy Economics, 2024, vol. 136, issue C

Abstract: Energy poverty is a global challenge that constrains economic development, jeopardizes people's health, and impedes the improvement of people's lives. Artificial intelligence (AI) could be an important tool to reverse this dilemma. We utilize a panel data covering 64 countries during 2000–2019 to examine AI's impact on energy poverty. The findings reveal that the application of AI effectively alleviates energy poverty. After a series of robustness checks, this conclusion remains valid. Moreover, heterogeneity tests show that AI significantly alleviates energy poverty in high-income countries and lower-middle-income countries, but this positive influence is not found in upper-middle-income countries. Mechanism tests indicate that the application of AI can generate economic effects, driving technological progress and enhancing human capital, thereby easing energy poverty. Further discussion reveals AI's impact on energy poverty is long-lasting. In addition, its effects are more prominent in countries that do not participate in cooperative organizations. Our findings offer a fresh perspective and approach to improving the global state of energy poverty. Based on these conclusions, we provide relevant policy implications.

Keywords: Energy poverty; Artificial intelligence; Global evidence; Mechanism test; Long-term impact (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:136:y:2024:i:c:s0140988324004560

DOI: 10.1016/j.eneco.2024.107748

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