首页|数字金融对企业绿色创新效率的影响研究——基于微观数据和机器学习模型的检验

数字金融对企业绿色创新效率的影响研究——基于微观数据和机器学习模型的检验

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基于2011-2019年中国上市企业面板数据,运用超效率SBM模型测算中国企业绿色创新效率,并实证检验数字金融对企业绿色创新效率的正向影响,进一步运用机器学习—随机森林模型研究数字金融对企业绿色创新效率的非线性效应.研究结果表明:数字金融能够赋能企业绿色创新效率提升,且对国有、大规模以及高污染企业绿色创新效率的赋能效应更强;数字金融可以通过缓解融资约束和降低金融风险间接促进企业绿色创新效率提升;数字金融对企业绿色创新效率的作用存在网络效应.
The Impact of Digital Finance on the Efficiency of Green Innovation in Enterprises Verification Based on Micro-data and Machine Learning Models
Based on panel data of Chinese listed companies from 2011 to 2019,the super efficiency SBM model is used to meas-ure the green innovation efficiency of Chinese enterprises,and the impact and mechanism of digital finance on the green innova-tion efficiency of enterprises are empirically tested.Furthermore,the machine learning random forest model is used to study the nonlinear effect of digital finance on the green innovation efficiency of enterprises.The research results indicate that digital finance can empower enterprises to improve their green innovation efficiency,and has a stronger empowering effect on the green innovation efficiency of state-owned,large-scale,and high polluting enterprises;Digital finance can indirectly promote the efficiency of green innovation in enterprises by alleviating financing constraints and reducing financial risks;There is a net-work effect of digital finance on the efficiency of green innovation in enterprises.

digital financegreen innovation efficiencyfinancing constraintsfinancial risk

周荣军、郑芳媛

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巢湖学院 经济与法学学院,安徽 巢湖 238000

信阳师范大学 商学院,河南 信阳 464000

数字金融 绿色创新效率 融资约束 金融风险

河南省哲学社会科学基金项目信阳师范大学科研创新基金项目

2020CJJ0922022KYJJ001

2024

信阳师范学院学报(哲学社会科学版)
信阳师范学院

信阳师范学院学报(哲学社会科学版)

CHSSCD
影响因子:0.322
ISSN:1003-0964
年,卷(期):2024.44(2)
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