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<p>As the pursuit of a sustainable economy intensifies, understanding how green finance development (GFD) promotes energy efficiency has become increasingly important, especially in large, regionally diverse countries like China. However, the spatial characteristics of energy efficiency and GFD remain underexplored. This study addresses this gap by employing a panel dataset consisting of 30 Chinese mainland provinces over 2008–2019. A panel stochastic frontier model is adopted to assess provincial energy efficiency, and a spatial Durbin model (SDM) is applied to assess GFD’s spatial impact. The results reveal that energy efficiency exhibits significant global spatial correlation and local clustering, with Moran’s <i>I</i> increasing from 0.148 to 0.155 over the sample period. A 1% increase in GFD leads to a 0.129% increase in energy efficiency, demonstrating its role in promoting local energy efficiency. Moreover, GFD generates positive spatial spillovers, raising the efficiency of neighboring provinces’ efficiency as well, as evidenced by a spatial interaction coefficient of 0.288. However, the effect is significantly positive in the eastern region, which is significant and negative in the western region but is insignificant in the central region. The mechanism analysis suggests that technological innovation and industrial structure transformation mediate these effects. These findings suggest the inclusion of regional heterogeneity when formulating green finance policies. Policymakers are advised to strengthen innovation capacity and industrial upgrading, especially in less developed regions, to fully realize the benefits of GFD for nationwide energy efficiency improvement.</p>

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Spatial insights into green finance development and energy efficiency in China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月19日

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  • Kunming Li,
  • Zhen Wu,
  • Linxing Huang,
  • Zifeng Zhong,
  • Wenming Shi

摘要

As the pursuit of a sustainable economy intensifies, understanding how green finance development (GFD) promotes energy efficiency has become increasingly important, especially in large, regionally diverse countries like China. However, the spatial characteristics of energy efficiency and GFD remain underexplored. This study addresses this gap by employing a panel dataset consisting of 30 Chinese mainland provinces over 2008–2019. A panel stochastic frontier model is adopted to assess provincial energy efficiency, and a spatial Durbin model (SDM) is applied to assess GFD’s spatial impact. The results reveal that energy efficiency exhibits significant global spatial correlation and local clustering, with Moran’s I increasing from 0.148 to 0.155 over the sample period. A 1% increase in GFD leads to a 0.129% increase in energy efficiency, demonstrating its role in promoting local energy efficiency. Moreover, GFD generates positive spatial spillovers, raising the efficiency of neighboring provinces’ efficiency as well, as evidenced by a spatial interaction coefficient of 0.288. However, the effect is significantly positive in the eastern region, which is significant and negative in the western region but is insignificant in the central region. The mechanism analysis suggests that technological innovation and industrial structure transformation mediate these effects. These findings suggest the inclusion of regional heterogeneity when formulating green finance policies. Policymakers are advised to strengthen innovation capacity and industrial upgrading, especially in less developed regions, to fully realize the benefits of GFD for nationwide energy efficiency improvement.