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政府补助对企业创新绩效的影响 被引量:15

The Influence of Government Subsidy on Enterprise Innovation Performance
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摘要 本文选取2010~2019年中国制造业A股上市公司的面板数据,基于创新数量和创新质量双维视角,构建面板向量自回归模型,通过方差分解、脉冲响应等方法实证检验政府补助对创新数量和创新质量的影响。研究结果表明:(1)政府补助与创新能力存在滞后1~2期的相互持续促进作用,政府补助政策绩效总体效果显著;(2)创新数量以及创新能力均能释放积极信号,以利于企业获得更多的政府补助,但创新质量显著抑制政府补助的增加;(3)政府补助对创新数量促进作用效果显著,但对创新质量的抑制作用效果显著;(4)创新能力对创新数量作用效果甚微,却显著抑制创新质量的提升。上述实证研究结论为政府补助政策以及创新政策的调整和完善提供借鉴和参考。 The article selects the panel data of Chinese manufacturing A-share listed companies from 2010 to 2019,and builds a panel vector autoregressive model based on the two-dimensional perspective of innovation quantity and innovation quality,and tests the impact of government subsidies on the quantity and quality of innovation through methods such as variance decomposi⁃tion and impulse response.The research results show that:(1)government subsidies and innovation capabilities have a lagging 1~2 period of mutual continuous promotion,and the overall effect of government subsidy policy performance is significant;(2)both the number of innovations and the ability to innovate can release positive signals to help enterprises obtain more government subsi⁃dies,but the quality of innovation significantly inhibits the increase of government subsidies;(3)government subsidies have a sig⁃nificant effect on promoting the quantity of innovation,but they have a significant effect on inhibiting the quality of innovation;(4)innovation ability has a significant effect on the quantity of innovation,however,it significantly inhibits the improvement of innova⁃tion quality.The above empirical research conclusions provide reference for the adjustment and improvement of government subsidy policies and innovation policies.
作者 张永安 关永娟 Zhang Yongan;Guan Yongjuan(School of Economics and Management,Beijing University of Technology,Beijing 100124,China)
出处 《工业技术经济》 北大核心 2021年第2期18-25,共8页 Journal of Industrial Technological Economics
基金 北京市社会科学基金项目“产业链协同视域的京津冀地区制造业产业优化研究”(项目编号:15JDJGA014)。
关键词 政府补助 创新能力 创新质量 创新数量 PVAR 模型 方差分解法 government subsidies innovation ability innovation quality number of innovations PVAR model variance decomposition mcthod
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