绿色信贷对中国工业绿色技术创新效率的影响研究  

Research on the Impact of Green Credit on Green Technology Innovation Efficiency of Industry in China

作　　者：王韶华[1] 林小莹 张伟[1] 李庆怡 WANG Shao-hua;LIN Xiao-ying;ZHANG Wei;LI Qing-yi(School of Economics and Management,Yanshan University,Qinhuangdao 066004,China)

机构地区：[1]燕山大学经济管理学院,河北秦皇岛066004

出　　处：《统计与信息论坛》2023年第4期88-102,共15页Journal of Statistics and Information

基　　金：河北省高等学校人文社会科学研究重点项目“稳增长和强‘双控’下京津冀能耗结构低碳协同优化研究”(SD2022072);河北省社会科学发展研究课题“河北省工业行业内绿色转型:驱动因素、作用机理与支持政策”(20220202464);河北省高等学校人文社会科学重点研究基地经费资助项目“数字经济赋能我国工业绿色发展的机制、效应及路径研究”(JJ2220)。

摘　　要：绿色技术创新是实现绿色发展的重要抓手,绿色信贷可以通过激励和约束双重机制影响中国工业行业的绿色技术创新效率。基于2011—2019年中国30个省份的面板数据,运用SBM-DEA模型测度工业绿色技术创新效率,再运用双向固定效应模型考察绿色信贷对工业绿色技术创新效率的影响,进一步基于金融发展水平进行区域异质性分析,最后运用逐步回归法探究信贷规模与信贷成本的间接影响路径。研究结果表明:中国各地区的工业绿色技术创新效率总体上呈现“倒N”型趋势,绿色信贷对工业绿色技术创新效率有显著促进作用。内生性检验发现:在系统GMM模型与2SLS模型的双重检验下,绿色信贷对地区工业绿色技术创新效率的促进作用仍然显著。区域异质性分析得出:绿色信贷对于金融发展水平处于第二梯队地区的工业绿色技术创新效率的促进作用最为突出。影响机制分析表明:除直接影响外,绿色信贷通过信贷规模与信贷成本两个部分中介间接影响工业绿色技术创新效率。Green technology progress is an important link to achieve green development.Through a dual mechanism of incentive and restraint,green credit can influence the Chinese industry’s level of green technology innovation efficiency.Based on panel data from China’s 30 provinces(autonomous regions and municipalities that fall under the direct control of a Central Government)between 2011 and 2019.Firstly,the industrial pollution index is calculated using the enhanced panel entropy approach.Secondly,the basic formula for CO 2emissions in the IPCC recommendations for national greenhouse gas inventories is cited,and the sum of industrial carbon emissions is determined by using the pertinent carbon emission factors in the recommendations and the consumption of pertinent energy sources in the statistical yearbook.Finally,the SBM-DEA model is employed to gauge the adoption of green technology in business.The two-way fixed effect model is used to examine the influence of green credit on the effectiveness of green technology innovation in industry,based on the findings of the Hausman test.Utilize the level of financial development to further investigate regional heterogeneity while taking into account the impact of regional financial development level on green credit.Finally,use the stepwise regression approach to investigate the indirect influence path of credit scale and credit cost in order to investigate the mechanism of the impact of green credit on the effectiveness of industrial green technology innovation.The findings indicate that all regions of China exhibit an“inverted N”trend in terms of the level of industrial green technology innovation efficiency.Of these,Hainan Province has been at the highest level during the study period,while Hebei Province has been at the lowest level nationwide.Baseline regression findings demonstrate that green credit is crucial in fostering the effectiveness of regional industrial green technology innovation.According to the double test of the system GMM model and the 2SLS model,the

关 键 词：绿色信贷 绿色技术创新效率 SBM-DEA模型 信贷规模 信贷成本 

分 类 号：F427[经济管理—产业经济]