Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

Yuanhe Zhang and Chaobo Zhou ()
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Yuanhe Zhang: Dong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan 430072, China
Chaobo Zhou: College of International Economics and Trade, Ningbo University of Finance and Economics, Ningbo 315175, China

Land, 2025, vol. 14, issue 3, 1-20

Abstract: The manner of achieving high-quality economic development in China through artificial intelligence (AI) has become a focus of academic attention. On the basis of panel data of prefecture-level cities in China from 2010 to 2021, this research utilizes the exogenous impact of the implementation of the National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AIPZ) to explore the causal effect between AI and green total factor productivity (GTFP). The results are as follows: (1) AI has a significant enhancement effect on urban GTFP. After using a series of robustness tests, such as parallel trend sensitivity test, heterogeneity treatment effect test, and machine learning, this conclusion remains robust. (2) Subsequent mechanism analysis shows that the impact of AI on urban GTFP is mainly achieved by enhancing urban green innovation, promoting industrial structure upgrading, and reducing land resource misallocation. (3) Lastly, the effect of AI on urban GTFP is heterogeneous. AI has also markedly significant enhancement effects on high human capital, non-resource-based economies, and high levels of green consumption behavior. This study provides useful insights for China to develop AI and achieve green development.

Keywords: artificial intelligence; green total factor productivity; green innovation; industrial structure upgrading; land resource misallocation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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