绿色金融对低碳转型的影响:中国的空间溢出效应

IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE
Jing Zhao
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引用次数: 0

摘要

本研究基于主成分分析法(PCA)建立了绿色金融指标体系,利用中国 30 个省市 2014 年至 2021 年的面板数据研究绿色金融对碳排放的影响。主要研究结果表明,绿色投资和绿色债务能有效减少碳排放,而绿色股权的影响有限。实证结果表明,绿色金融能提高创新效率,进而促进减排。此外,空间杜宾模型显示出显著的空间溢出效应,一个省的进步会惠及周边地区。该研究的政策含义表明,加强绿色公平和根据地区条件调整融资战略可以大大推进中国的碳减排目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of green finance on low-carbon transformation: Spatial spillover effects in China

This study developed a green financial indicator system based on a Principal Component Analysis (PCA) approach to investigate the impacts of green finance on carbon emissions by using the panel data from 30 Chinese provinces and municipalities from 2014 to 2021. The key findings conclude that green investments and debts are effective at reducing emissions, while green equity has a limited impact. Empirical results demonstrate that green finance enhances innovation efficiency, which in turn facilitates reductions in emissions. Additionally, the Spatial Durbin Model indicates significant spatial spillover effects, with progress in one province benefiting neighboring areas. The policy implications of the study suggest that enhancing green equity and adapting finance strategies to regional conditions could significantly advance the carbon reduction objectives for China.

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来源期刊
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
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