Non-linear research on artificial intelligence empowering green economic efficiency under integrated governance framework - Zhichun Song; Yao Deng (Frontiers in Environmental Economics)
Artificial intelligence (AI) plays a pivotal role in the development of the green economy. This paper examines the impact of artificial intelligence (AI) on green economic efficiency (GEE) using panel data from 30 provinces in China spanning 2011–2020. A multiple linear regression model, alongside various endogeneity and robustness tests, is applied to ensure reliable findings. The empirical results indicate that AI significantly enhances GEE. However, the marginal effect of AI on GEE is influenced by different governance approaches. In terms of policy governance, excessive market-based environmental regulation (MER) diminishes the marginal impact of AI, while stronger administrative-command environmental regulations (CER) and informal environmental regulations (IER) amplify it. Regarding technological governance, substantive green technological innovations (SUG) reduce AI's marginal effect, whereas symbolic green technological innovations (SYG) may increase it. Notably, the threshold effect of SUG surpasses that of SYG. In legal governance, both administrative and judicial intellectual property protections reduce the marginal effect of AI, though administrative protection (AIP) exhibits a more significant threshold effect than judicial protection (JIP). These findings offer practical insights for optimizing governance strategies to maximize AI's role in promoting GEE. These insights highlight the need for balanced governance to maximize AI's role in sustainable development. Policymakers should tailor regulations and encourage regional collaboration to harness AI's spatial spillover effects. Enterprises can leverage AI-driven innovations to align growth with ecological goals, fostering coordinated green development.