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Dynamic Linkages among Carbon Emissions, Artificial Intelligence, Economic Policy Uncertainty, and Renewable Energy Consumption: Evidence from East Asia and Pacific Countries

Author

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  • Salman Ali Shah

    (Academy of China-ASEAN International and Regional Studies, Guangxi Minzu University, Nanning 530006, China)

  • Xingyi Ye

    (Academy of China-ASEAN International and Regional Studies, Guangxi Minzu University, Nanning 530006, China)

  • Bo Wang

    (School of Politics and Public Administration, Guangxi Minzu University, Nanning 530006, China)

  • Xiangjun Wu

    (Academy of China-ASEAN International and Regional Studies, Guangxi Minzu University, Nanning 530006, China)

Abstract

A growing number of countries are concerned about the reliability of environmental indicators; as a result, there is a pressing need to find ways to improve ecological welfare on a global scale. This study investigates the dynamic linkages among CO 2 emissions, AI, economic policy uncertainty (EPU), and renewable energy consumption. To analyze these relationships empirically, this study used panel data for East Asian and Pacific countries from 2000 to 2023. This study used fully modified ordinary least squares (FMOLSs), dynamic ordinary least squares (DOLSs), Hausman fixed effects (FEs) and random effects (REs), the generalized method of moments (GMM), and variance decomposition tests. This study’s results show that AI has a positive relationship with CO 2 emissions in terms of the benchmark regression, while it shows minimal impact on CO 2 emissions according to the variance decomposition test. Similarly, economic policy uncertainty shows a strong positive relationship with CO 2 emissions through benchmark regression FEs and REs, GMM, and the variance decomposition test. An increase in EPU will positively affect CO 2 emissions. Renewable energy consumption has a strong negative impact on CO 2 emissions in East Asian and Pacific countries. These findings reveal that a unit increase in renewable energy consumption will decrease CO 2 emissions. Based on the results of this study, it is suggested that policy certainty and an upsurge in renewable energy consumption are essential for environmental upgrading. In contrast, adopting AI has no robust effect on ecological degradation (CO 2 emissions). East Asian and Pacific countries need to focus on the adoption of renewables, as well as the control of economic policy uncertainty. While AI in East Asian and Pacific countries is still in the initial stage of adoption, policy formation is essential to overcome the possible carbon footprint of AI in the short term.

Suggested Citation

  • Salman Ali Shah & Xingyi Ye & Bo Wang & Xiangjun Wu, 2024. "Dynamic Linkages among Carbon Emissions, Artificial Intelligence, Economic Policy Uncertainty, and Renewable Energy Consumption: Evidence from East Asia and Pacific Countries," Energies, MDPI, vol. 17(16), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:4011-:d:1455436
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    References listed on IDEAS

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