Decarbonizing the U.S. Economy through Artificial Intelligence and Information Technology: An Empirical ARDL Analysis
Abstract
Climate change has become one of the most paramount threats to the sustainable world and therefore, this requires the development of sophisticated technological and financial strategies to become carbon neutral. This paper discusses how innovations in Artificial Intelligence (AI), stock market development, adoption of Information and Communication Technology (ICT), economic growth, and population dynamics have the effect of affecting carbon emissions in the United States, both between 1990 and 2021. Using Autoregressive Distributed Lag (ARDL) model and Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Canonical Cointegrating Regression (CCR) estimators, the analysis establishes short-run and long run associations between the variables chosen. The results indicate that economic growth, capitalization of stocks in the market, and population increase contribute greatly to carbon emissions but the innovation of AI and diffusion of ICT decrease the emissions considerably in the long term. The diagnostics of robustness test or prove the reliability of the models and there are not problems with serial correlation or heteroscedasticity. These results underscore the twofold nature of the digitalization and financial development in building the environmental sustainability. The paper emphasizes that policies that foster AI-based energy optimization, sustainable financial operations, and environmentally focused technological invention were needed to facilitate the American journey of achieving carbon neutrality.
Keywords:
Artificial intelligence, Information and communication technology, Stock market development, Carbon neutrality, Using autoregressive distributed lag, United StatesReferences
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