The asymmetric impacts of artificial intelligence and oil shocks on clean energy industries by considering COVID-19

Hongwei Zhang, Beixin Fang, Pengwei He and Wang Gao

Energy, 2024, vol. 291, issue C

Abstract: Can grand environmental goals still be achieved when the 1.5 °C climate target and Industry 4.0 encounter the COVID-19 pandemic? Exploring the impacts of artificial intelligence (AI) and crude oil shocks as critical drivers on clean energy stocks may provide fresh insights to tackle this question. This paper explores the asymmetric impacts of positive and negative changes in the AI index and different oil shocks on clean energy stock sub-sectors by adopting the non-linear autoregressive distributed lag (NARDL) model. Our investigation of a sample reveals a significant positive long-run relationship between the AI index and clean energy stocks. Additionally, the impacts of AI and oil shocks on clean energy stocks vary broadly across different sub-sectors. The COVID-19 pandemic has strengthened the cointegration relationship and reduced the long- or short-term asymmetry among the AI index and clean energy stocks. This study incorporates the AI index into the research framework of oil and clean energy, which has not been explored in previous research, and is of significant importance for clean energy investment and provides guidance for market participants.

Keywords: Artificial intelligence; Oil shocks; Clean energy stock; NARDL model; COVID-19 pandemic (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:291:y:2024:i:c:s0360544223035910

DOI: 10.1016/j.energy.2023.130197

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