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The rapid economic growth in the United States has necessitated the exploration of innovative, sustainable approaches to mitigate climate change, particularly in terms of balancing economic development with environmental preservation. This study aims to investigate the asymmetric and long-term effects of artificial intelligence (AI) investment, green electricity adoption, and economic growth on environmental quality in the U.S. Using a novel econometric methodology, the study analyses quarterly time series data from 2012/Q1 to 2021/Q4. The originality of this research lies in its comprehensive assessment of AI investment, green electricity, and economic growth as influential factors on environmental quality, applying advanced techniques such as the ADF unit root test with breakpoints, BDS test, nonlinear ARDL bounds testing, and various diagnostic approaches. The findings reveal several key insights: (i) AI investment exhibits nonlinear and asymmetric effects on environmental quality in the long run, (ii) an increase in AI investment correlates with a higher ecological footprint and diminished environmental quality, (iii) the use of green electricity contributes to a reduction in environmental degradation and fosters sustainable environmental practices, and (iv) economic growth, if not accompanied by eco-friendly practices, can exacerbate ecological deterioration. These results align with both economic and environmental theories, suggesting that green energy solutions play a vital role in promoting sustainability while supporting economic growth. The study emphasizes the need for U.S. policymakers to invest in sustainable initiatives, prioritize research and development of clean technologies, and implement robust eco-friendly policies to effectively combat climate change and achieve long-term climate objectives.
Kırıkkaleli et al. (Sun,) studied this question.