Baseline regression estimation results.

Green finance promotes the optimization of industrial structure and continuous improvement of ecological environment by supporting the development of green industries. Based on the panel data of 30 provinces in China from 2012 to 2020, this paper uses the entropy weight TOPSIS method to measure the development level of green finance and the level of industrial structure optimization in China, and constructs a panel data model to empirically test the impact of green finance on the upgrading of China’s industrial structure. The study finds that there is still an imbalance and insufficiency in the development of green finance and industrial structure optimization in China. From 2012 to 2020, the development level of green finance and the level of industrial structure optimization in China have been continuously rising, but there is obvious heterogeneity, showing an eastern>central>western spatial pattern. Empirical analysis results show that at the significance level of 1‰, the development of green finance has a significant promoting effect on the rationalization and upgrading of the industrial structure. However, there is significant heterogeneity in the impact of green finance on industrial structure optimization. In terms of regional heterogeneity, at the significance level of 1‰, the role of green finance in promoting the optimization of industrial structure in central and western China is higher than that in eastern China, and the impact of green finance on China’s industrial structure shows a spatial pattern of western>central>eastern China. In terms of industry heterogeneity, at the significance level of 1‰, green finance has a significant promoting effect on the development of green industries, and a significant inhibiting effect on the development of high-energy-consuming industries. Specifically, in the green industry, green finance has the greatest promoting effect on the communication and other electronic equipment manufacturing industry; in the high-energy-consuming industry, green finance has the greatest inhibiting effect on the black metal smelting and rolling processing industry, and the smallest impact on the petroleum, coal and other fuel processing industry. Finally, based on this, policy suggestions for green finance to support the optimization of industrial structure are proposed from two dimensions: government and financial institutions.

绿色金融（Green Finance）通过扶持绿色产业发展，推动产业结构优化与生态环境持续改善。本文基于2012-2020年中国30个省份的面板数据（panel data），采用熵权TOPSIS法（entropy weight TOPSIS method）测算中国绿色金融发展水平与产业结构优化水平，并构建面板数据模型实证检验绿色金融对中国产业结构升级的影响。研究发现，当前中国绿色金融发展与产业结构优化仍存在不平衡与不充分问题。2012-2020年，中国绿色金融发展水平与产业结构优化水平持续提升，但存在显著异质性，呈现出东部＞中部＞西部的空间分布格局。实证分析结果显示，在1‰的显著性水平下，绿色金融发展对产业结构合理化与高级化均具有显著的正向促进作用。但绿色金融对产业结构优化的影响存在显著异质性。从区域异质性来看，在1‰的显著性水平下，绿色金融对中西部地区产业结构优化的促进作用高于东部地区，绿色金融对中国产业结构的影响呈现出西部＞中部＞东部的空间格局。从行业异质性来看，在1‰的显著性水平下，绿色金融对绿色产业发展具有显著促进作用，而对高耗能产业发展则具有显著抑制作用。具体而言，在绿色产业中，绿色金融对通信及其他电子设备制造业的促进作用最为显著；在高耗能产业中，绿色金融对黑色金属冶炼和压延加工业的抑制作用最强，对石油、煤炭及其他燃料加工业的影响最弱。最后，据此从政府与金融机构两个维度，提出绿色金融支持产业结构优化的政策建议。