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Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

Author

Listed:
  • Yuanhe Zhang

    (Dong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan 430072, China
    Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Chaobo Zhou

    (College of International Economics and Trade, Ningbo University of Finance and Economics, Ningbo 315175, China
    Climate Change and Energy Economics Study Center of Wuhan University, Wuhan 430072, China)

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.

Suggested Citation

  • Yuanhe Zhang & Chaobo Zhou, 2025. "Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity," Land, MDPI, vol. 14(3), pages 1-20, March.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:660-:d:1616534
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