摘要
现有文献大多支持绿色金融对碳排放具有抑制作用的观点。论文基于2011—2022年长江经济带108个地级市及以上城市的面板数据,综合运用一系列计量模型对二者关系进行了再考察。首先,采用双固定效应模型,研究发现绿色金融对碳排放的影响呈现显著的正“U”型非线性关系,其抑制作用随绿色金融发展的提升,表现出先增强后减弱的趋势,存在边际递减特征。其次,选用门限模型识别出了不同银行竞争水平下,绿色金融的减排效应具有显著差异。在银行竞争水平较低的地区,其抑制作用更为显著;而在银行竞争激烈的地区,减排效应相对较弱。再次,运用中介效应模型,证实了人工智能是绿色金融影响碳排放的重要传导渠道。绿色金融通过促进人工智能发展间接降低了碳排放,证实了“绿色金融—人工智能—碳排放”这一中介路径的存在。最后,借助空间面板模型,发现绿色金融对碳排放的影响存在显著的空间溢出效应。不仅作用于本地区,也对邻近地区产生类似的先抑制后促进的“U”型空间影响,凸显了区域协同的重要性。基于以上结论,提出如下政策建议:优化绿色金融政策以协调区域银行竞争差异产生的碳排放异质性;加强人工智能在绿色金融中的应用;建立绿色金融的区域合作机制,促进区域协同减排。
Most existing literature supports the view that green finance has an inhibitory effect on carbon emissions.This paper reexamines the relationship between green finance and carbon emissions based on panel data from 108 prefecture-level and above cities in the Yangtze River Economic Belt from 2011 to 2022,by using a series of econometric models.Initially,a two-way fixed effects model is adopted,revealing that:The impact of green finance on carbon emissions follows an inverted U-shaped nonlinear relationship.The inhibitory effect strengthens initially and then weakens with the development of green finance,indicating diminishing marginal returns.Subsequently,a threshold effect model is employed to meticulously analyze the differentiated impact of green finance on carbon emissions under varying levels of bank competition.In regions with lower bank competition,the inhibitory effect is more pronounced,whereas in regions with intense bank competition,the emission reduction effect is relatively weaker.Further,a mediation effect model is used to confirm that artificial intelligence serves as an important channel through which green finance influences carbon emissions.Green finance indirectly reduces carbon emissions by promoting the development of artificial intelligence,validating the existence of the green finance-artificial intelligence-carbon emissions path.Finally,a spatial panel model demonstrates a significant spatial spillover effect of green finance on carbon emissions.This effect not only operates within the local region but also exerts a similar inverted U-shaped spatial influence on neighboring areas,first inhibiting and then promoting emissions,highlighting the importance of regional coordination.Based on these conclusions,the following policy recommendations are proposed:Optimizing green finance policies to coordinate the heterogeneity of carbon emissions arising from regional bank competition differences;Strengthening the application of artificial intelligence in green finance;Establishing regional cooperation mechanisms for green finance to promote coordinated emission reductions across regions.
作者
曾小晏
张华
ZENG Xiaoyan;ZHANG Hua(Institute for Chengdu-Chongqing Economic Zone Development,Chongqing Technology and Business University,Chongqing 400067,China;School of Accounting,Chongqing Technology and Business University,Chongqing 400067,China)
出处
《生态经济》
北大核心
2026年第1期47-57,共11页
Ecological Economy
基金
国家社会科学基金项目“‘双碳’目标下页岩气开采技术跨组织双向协同研发机制及实现路径研究”(22BGL186)。
关键词
绿色金融
碳排放
银行竞争
人工智能
green finance
carbon emission
bank competition
artificial intelligence
