Document Type : Original Article
Authors
1 PhD Student, Department of Economics, Fi.C., Islamic Azad University, Firoozkooh, Iran
2 Islamic Azad University of Firuzkuh: Islamic Azad University Foroozkooh Branch
3 Department of Economics, Fi.C., Islamic Azad University, Firoozkooh, Iran
Abstract
This study examines the impact of artificial intelligence on energy consumption and carbon dioxide emissions in the United States over the period 1976 to 2020. Given the potential for nonlinear relationships and varying effects of artificial intelligence under different economic conditions, a Smooth Transition Regression model with a logistic transition function (LSTR) was employed. In this model, the degree of economic openness is considered as a threshold variable to investigate whether the effect of artificial intelligence on environmental variables differs across various levels of economic openness. The estimation results indicate that the relationship between artificial intelligence and both energy consumption and carbon dioxide is threshold-dependent and contingent on economic openness. At the threshold level of openness (approximately 23%), a significant change in the intensity of the effect is observed. In particular, when the degree of economic openness exceeds this level, artificial intelligence has a decreasing effect on carbon dioxide emissions, while its effect on energy consumption initially increases and then tends to stabilize. These findings suggest that integration into the global economy and trade openness can act as mediators in the impact of new technologies. Additionally, control variables such as per capita income and urbanization have significant positive effects on increasing energy consumption and pollution. Based on these results, it is recommended that policymakers, in promoting artificial intelligence development, take economic openness into account and simultaneously focus on advancing clean technologies, technology transfer, and smart environmental policies.
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