Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

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.

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Publication Details

Journal
Land
Published
2025-03-20
DOI
https://doi.org/10.3390/land14030660
Citations
5
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
15.66
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article

Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

Yuanhe Zhang, Chaobo Zhou
5 citations
Land
Energy, Environment, Economic Growth
15.66
article

Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

Yuanhe Zhang, Chaobo Zhou
article en
5 citations

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.

LandVol. 14(3)
Ningbo University (CN), Wuhan University (CN), Wuhan Donghu University (CN)
Openalex Percentile: Top 2%
Energy, Environment, Economic Growth
15.66
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Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity — Yuanhe Zhang, Chaobo Zhou · Land (2025) | TGRS Research Map | TGRS