摘要
基于中国绿色信贷政策的实践,采用双重机器学习模型实证检验了其对重污染企业“脱虚向实”的影响。研究发现,绿色信贷政策对重污染企业金融资产投资具有显著抑制作用,尤其是对东部地区企业、营商环境好的地区企业、金融发展水平较高的地区企业、非国有企业、小规模企业以及成熟企业。机制分析表明:绿色信贷政策加剧了企业的融资约束,但减弱了企业政策不确定性感知,提高了实体金融投资的相对报酬。此外,企业减少金融资产配置后,资本配置趋于向实,绿色信贷政策促进了企业实体投资、环保投资和技术创新投资增加。
Based on the practice of China’s green credit policy,this paper employs a dual machine learning model to examine the impact of green credit policy on the“shift from fictitious to real”.The results reveal that green credit policies have a significant inhibitory effect on the financial asset investment of heavily polluted enterprises,particularly in eastern regions enterprises,enterprises in areas with high business environments,enterprises in regions with high levels of financial development,non-state-owned enterprises,smal-scale enterprises,and mature enterprises.The mechanism analysis shows that green credit policies have intensified financing constraints for enterprises;however,they also reduce the perception of uncertainty in corporate policies and increase the relative return on real financial investments.Furthermore,the reduction in corporate allocations to financial assets has led to a shift of capital toward the real economy.Green credit policies have effectively facilitated increased corporate investment in physical assets,environmental protection initiatives,and technological innovation.
作者
赵娜
袁梁
龙汉
朱维维
ZHAO Na;YUAN Liang;LONG Han;ZHU Weiwei(School of Economics and Finance,Xi’an International Studies University,Xi’an 710128,China;“Global South”Economic and Trade Cooperation Research Center,Xi’an 710128,China;School of Economics and Management,Weinan Normal University,Weinan 714099,China;School of Economics and Management,Xi’an University of Technology,Xi’an 710054,China)
出处
《湖南大学学报(社会科学版)》
北大核心
2025年第3期52-62,共11页
Journal of Hunan University(Social Sciences)
基金
陕西省软科学研究计划一般项目:绿色金融对陕西省碳排放的影响及优化路径研究(2023-CX-RKX-126)
西安外国语大学2022年度科研基金资助项目:中国地方税收竞争对绿色发展的影响机制及优化路径研究(22XWB02)
陕西省软科学研究计划一般项目:陕西省绿色金融政策改善生态环境质量的区域差异与长效机制研究(2023-CX-RKX-163)。
关键词
绿色信贷政策
重污染企业
脱虚向实
双重机器学习
green credit policy
heavily polluted enterprises
shift from fictitious to real
dual machine learning
