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The Impact of Green Finance on Urban Carbon Emission Efficiency: Threshold Effects Based on the Stages of the Digital Economy in China

Author

Listed:
  • Zhaoxia Wu

    (School of Business, Xiangtan University, Xiangtan 411105, China)

  • Xi Xu

    (School of Business, Xiangtan University, Xiangtan 411105, China)

  • Mai He

    (School of Business, Xiangtan University, Xiangtan 411105, China)

Abstract

As one of the effective ways to achieve “carbon neutrality”, examining the impact of green finance (GF) on carbon emission efficiency (CE) is of great significance for promoting low-carbon development in China. Moreover, the digital economy is a key catalyst in achieving China’s “dual-carbon” targets, as its “greening” characteristic is considered instrumental in promoting urban low-carbon development. However, the effects of the digital economy (Dig) stage on GF on urban CE have not been sufficiently studied. Using panel data from 276 Chinese cities from 2011 to 2021 and constructing a theoretical model based on the Cobb–Douglas production function, this paper analyzes the impact of GF on urban CE. The empirical results indicate that (1) GF can improve CE, and the two have a positive U-shaped relationship, which is still valid after robustness tests. (2) The heterogeneity results indicate that the impact of GF on CE is more significant in non-resource-based cities, low-carbon pilot cities, and cities with higher financial development levels. (3) GF significantly improves urban CE by driving green technology innovation (Gti) and energy efficiency improvement (Eei). (4) The effects of GF on CE have a dual-threshold effect based on the Dig. When the Dig level is excessively high, the positive effect of GF on urban CE will be weakened.

Suggested Citation

  • Zhaoxia Wu & Xi Xu & Mai He, 2025. "The Impact of Green Finance on Urban Carbon Emission Efficiency: Threshold Effects Based on the Stages of the Digital Economy in China," Sustainability, MDPI, vol. 17(3), pages 1-30, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:3:p:854-:d:1573215
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    References listed on IDEAS

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    1. Yongtong Hu & Jiaqi Xu & Tao Liu, 2025. "The Impact of Digitalization on Carbon Emission Efficiency: An Intrinsic Gaussian Process Regression Approach," Sustainability, MDPI, vol. 17(14), pages 1-25, July.

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