This research examines the impact of artificial intelligence (AI); environmental, social and governance (ESG) factors; renewable energy consumption (REC) and economic growth (gross domestic product (GDP)) on environmental quality, as measured by the load capacity factor (LCF), in the United States of America (USA). This measure compares ecological biocapacity with the ecological footprint of a country.
This study employed novel Wavelet Quantile on Quantile Regression (WQQR) to assess the effect of AI, ESG, REC and GDP on LCF and Wavelet Quantile on Quantile Granger Causality (WQQGC) determine the casual effect. The WQQR technique allows to explore the influence of these variables with respect to multiple quantiles on LCF for time period spanning from January 2011 to December 2022.
The WQQR outcomes show the heterogenous effect of AI, ESG, REC and GDP on the environment quality throughout quantiles. Such that AI degrades the environment in short term; however, in the medium to long term, it improves the environment quality. ESG factors have an initial negative impact due to transition costs, a mixed effect in the medium term and a positive effect in the long term. Whereas AI, GDP and REC negatively impact environmental quality in short- and medium-term quantiles due to transitional challenges and industrial expansion, their positive effect becomes more pronounced in the long term.
The findings suggest practical implications for governments, businesses and stakeholders. The findings inform policymakers how to promote the use of AI and ESG practices that raise environmental quality. Integration of AI and more ESG commitments can assist businesses achieve themselves, improved efficiency and decreased environmental impact. In particular, this study argues that primary importance should be given to increasing the REC so that environmental quality could be enhanced and that more investment in renewable energy infrastructure is required to supply the green technology to promote long-term growth.
To date, existing studies have not employed advanced econometric methods, such as WQQR and WQQGC, to estimate environmental quality for the USA. Furthermore, this study examines the impact of AI and ESG shocks on environmental quality, utilizing LCF as a proxy, which is an innovative approach to the literature on environmental quality.
