Optimization of the dynamic measure in spillover effect based on knowledge graph

10Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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

CITATION STYLE

APA

Hua, R., Bao, Y., Chen, S., & Zhuang, Z. (2019). Optimization of the dynamic measure in spillover effect based on knowledge graph. Computer Systems Science and Engineering, 34(4), 215–223. https://doi.org/10.32604/CSSE.2019.34.215

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free