Impact of Green Finance on Chinese Urban Land Green Use Efficiency: An Empirical Study Based on a Quasinatural Experiment

To examine the impact of green finance (GF) on urban land green use efficiency (LGUE), we treat the Green Finance Reform and Innovation Pilot Zone (GFRIPZ) policy, implemented in 2017, as quasi-natural experiment. The results from a multi-period difference-in-difference model show that GF contributes to improving urban LGUE. This conclusion is validated further by a generalized random forest model. The mechanism analysis demonstrates that GF enhances LGUE through the effects of green technological innovation, industrial upgrading, and public green behavior. The moderation analysis further reveals that artificial intelligence can amplify the positive impact of GF on LGUE. The heterogeneity results show that the positive relationship between GF and LGUE is more pronounced in midwestern cities, non-resource-based cities, and cities with a high level of financial development. Therefore, it is essential to expand the GF pilot program in a structured manner and establish a coordinated mechanism to promote LGUE improvement through GF in different regions, thereby enhancing financial service efficiency for the real economy.

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Publication Details

Journal
Land
Published
2025-02-06
DOI
https://doi.org/10.3390/land14020332
Citations
9
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
28.18

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article

Impact of Green Finance on Chinese Urban Land Green Use Efficiency: An Empirical Study Based on a Quasinatural Experiment

Haikuo Zhang, Fen Wang, Jingjie Zhou
9 citations
Land
Energy, Environment, Economic Growth
28.18
article

Impact of Green Finance on Chinese Urban Land Green Use Efficiency: An Empirical Study Based on a Quasinatural Experiment

Haikuo Zhang, Fen Wang, Jingjie Zhou
article en
9 citations

Abstract

To examine the impact of green finance (GF) on urban land green use efficiency (LGUE), we treat the Green Finance Reform and Innovation Pilot Zone (GFRIPZ) policy, implemented in 2017, as quasi-natural experiment. The results from a multi-period difference-in-difference model show that GF contributes to improving urban LGUE. This conclusion is validated further by a generalized random forest model. The mechanism analysis demonstrates that GF enhances LGUE through the effects of green technological innovation, industrial upgrading, and public green behavior. The moderation analysis further reveals that artificial intelligence can amplify the positive impact of GF on LGUE. The heterogeneity results show that the positive relationship between GF and LGUE is more pronounced in midwestern cities, non-resource-based cities, and cities with a high level of financial development. Therefore, it is essential to expand the GF pilot program in a structured manner and establish a coordinated mechanism to promote LGUE improvement through GF in different regions, thereby enhancing financial service efficiency for the real economy.

LandVol. 14(2)
Ningbo University (CN), Wuhan University (CN)
Ministry of Education of the People's Republic of China
Openalex Percentile: Top 1%
Energy, Environment, Economic Growth
28.18
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