In the double background of population aging and China’s economy increasingly driven by technological innovation, the investigation into the effect of population aging on technological innovation is of great importance. This paper evaluates three influence mechanisms of population aging on technological innovation, namely " human capital mechanism”, " labor productivity mechanism” and " the elderly burden mechanism”. Using dynamic factor analysis model, we choose multiple indicators in five aspects-innovation input, innovation output, innovation efficiency, synergy innovation and innovation environment. Then we get a new comprehensive index of technological innovation concerning 29 provinces from 1990 to 2014 and use it as a new indicator of innovation capacity. Using dynamic GMM model, we prove that population aging has two opposite effects on technological innovation: on one hand, population aging has positive effect on technological innovation by improving researchers’ labor efficiency, having the positive " labor productivity effect”; on the other hand, population aging has negative effect on technological innovation by reducing the level of human capital, aggravating the pension burden and squeezing out innovation input, having negative " human capital” and " elderly burden” effects. Our work contributes to the present research by creating a new innovation indicator and analyzing the effect of population aging on technological innovation, and has policy implications for dealing with the challenge of population aging.
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The Influence of Population Aging on Technological Innovation: Based on Innovation Evaluation Using Dynamic Factor Analysis and Dynamic GMM Model
Journal of Shanghai University of Finance and Economics Vol. 19, Issue 06, pp. 4 - 17 (2017) DOI:10.16538/j.cnki.jsufe.2017.06.001
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Cite this article
Wang Wei, Jiang Zhenmao. The Influence of Population Aging on Technological Innovation: Based on Innovation Evaluation Using Dynamic Factor Analysis and Dynamic GMM Model[J]. Journal of Shanghai University of Finance and Economics, 2017, 19(6): 4–17.
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