Will artificial intelligence accelerate or delay the race between nuclear energy technology budgeting and net-zero emissions?
Danish, Adnan Khan

TL;DR
This paper investigates how artificial intelligence influences the relationship between nuclear energy budgeting and CO2 emissions in OECD countries, revealing AI's significant moderating role in promoting low-carbon energy transitions.
Contribution
It introduces a novel analysis of AI's moderating effect on nuclear energy's impact on emissions using advanced quantile regression techniques, addressing endogeneity and heteroscedasticity.
Findings
AI significantly impacts CO2 emissions.
AI moderates the nuclear energy-emissions relationship.
Nuclear energy alone does not significantly reduce emissions.
Abstract
This study explores the impact of nuclear energy technology budgeting and artificial intelligence on carbon dioxide (CO2) emissions in 20 OECD economies. Unlike previous research that relied on conventional panel techniques, we utilize the Method of Moment Quantile Regression panel data estimation techniques. This approach provides quantile-specific insights while addressing issues of endogeneity and heteroscedasticity, resulting in a more nuanced and robust understanding of complex relationships. A novel aspect of this research work is introducing the moderating effect of artificial intelligence on the relationship between nuclear energy and CO2 emissions. The results found that the direct impact of artificial intelligence on CO2 emissions is significant, while the effect of nuclear energy technology budgeting is not. Additionally, artificial intelligence moderates the relationship…
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Taxonomy
TopicsEconomic and Technological Developments in Russia · Global Energy and Sustainability Research
