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Optimization of the Dynamic Measure of Spillover Effect Based on Knowledge Graph

Rui Hua1,2, Yongwen Bao3, Shengan Chen2, Ziyin Zhuang1,*

1 Economics and Management School, Wuhan University, Wuhan, China
2 Mathematics and Statistics School of Hubei Science and Technology University, Xianning, China
3 Public Health and Management of Hubei Medicine University, Shiyan, China

* Corresponding Author: Ziyin Zhuang, Economics and Management School, Wuhan University, Wuhan, China. Email:

Computer Systems Science and Engineering 2019, 34(4), 215-223.


This paper improves the dynamic Feder model based on the characteristics of knowledge production and separates the direct effect and spillover effect of R&D in order to determine the relationship between spillover effect of R&D and economic growth, and accurately measure it by examining Chinese provincial panel data from 2008–2016. The theoretical analysis shows that the spillover effect of R&D promotes economic growth. Empirical analysis using a combination of OLS, sysGMM, 2SLS and GLS shows that basic research and application research have significant spillover effects; the marginal revenue of the basic research is lower than that of the production sector, while the marginal revenue of the application research is higher than that of the production sector; and knowledge stock does not significantly promote innovation in China. However, any study on the influence of knowledge stock on innovation entails more than basic research.


Cite This Article

R. Hua, Y. Bao, S. Chen and Z. Zhuang, "Optimization of the dynamic measure of spillover effect based on knowledge graph," Computer Systems Science and Engineering, vol. 34, no.4, pp. 215–223, 2019.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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