Work

Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity

Year: 2025

Type: article

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.

Source: Land

DOI: 10.3390/land14030660

Authors: Yuanhe Zhang, Chaobo Zhou

Institutions: Wuhan University, Ningbo University of Finance & Economics

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $3,137