财政科技支出、绿色技术创新与碳生产率——基于PVAR模型的实证检验
Fiscal science and technology expenditures,green technology innovation and carbon productivity-an empirical test based on the PVAR model for prefecture-level cities
孟晓虹 1郭丕斌 2吴青龙1
作者信息
- 1. 中北大学经济与管理学院,山西太原 030051
- 2. 中北大学经济与管理学院,山西太原 030051;山西经济管理干部学院经济管理系,山西太原 030024
- 折叠
摘要
在"双碳"背景下,厘清财政科技支出、绿色技术创新与碳生产率之间的动态交互关系对政府决策具有非常重要的现实意义.以2006-2020年中国30个省份的面板数据为研究样本,通过面板向量自回归(PVAR)模型,对上述问题进行了测度.结果表明,财政科技支出在促进绿色创新水平提升方面发挥了有效作用,但存在即时性,而政府受到绿色创新水平提升的鼓舞,会进一步增加科技支出,二者之间存在良好的交互促进关系;财政科技支出和绿色创新水平提升都显著促进了地区碳生产率的提高,且绿色技术创新的影响具有持续性,对促进碳生产率提升的贡献率更高.最后基于以上研究结果,提出了政府应鼓励绿色技术创新、加大财政对科技创新的支持力度、加快构建低碳经济发展,形成三者之间良性循环结构的政策建议.
Abstract
Under the background of dual carbon,it is very important to clarify the dynamic relationship between financial and technical expenditure,green technology innovation and carbon productivity of government decision-making.From 2006 to 2020,the panel data of 30 provinces in China were used to measure the above problems when using the Panel Vector Regression Model(PVAR).The results show that the fiscal expenditure on science and technology has played an effective role in promoting the improvement of green innovation level,but it is also timely.The government has further increased the expenditure on science and technology while encouraging the improvement of green innovation level,and there is a good mutual promotion relationship between them.The improvement of expenditure and green innovation level in finance technology will greatly promote the improvement of regional carbon productivity,and the impact of green technology innovation will be lasting and the contribution rate will be higher.Finally,on the basis of the above achievements,the government should encourage green technological innovation,increase financial support for scientific and technological innovation,accelerate the construction of low-carbon economy,and form a virtuous cycle model of the three.
关键词
财政科技支出/绿色创新/碳生产率/面板向量自回归模型Key words
fiscal science and technology expenditures/green innovation/carbon productivity/panel vector autoregressive model引用本文复制引用
基金项目
国家自然科学基金(71874119)
教育部人文社会科学研究一般项目(21YJA790062)
出版年
2024
NETL
NSTL
万方数据