当代财经 ›› 2017, Vol. 0 ›› Issue (10): 220-.

• • 上一篇    

人力资本与中国资本和技术密集型产业技术创新——基于分位数回归模型的经验研究

马颖,何清   

  1. (武汉大学 经济发展研究中心/经济与管理学院,湖北 武汉 430072)
  • 收稿日期:2017-07-04 发布日期:2021-01-21
  • 作者简介:马 颖,武汉大学教授,博士,主要从事发展经济学研究,通讯作者联系方式yingma9494@126.com;何 清,武汉大学博士研究生,主要从事发展经济学研究。

Human Capital and Technological Innovation in China’s Capital-Intensive and Technology-Intensive Industries: An Empirical Study Based on Quantile Regression Model

MA Ying, HE Qing   

  1. (Wuhan University, Wuhan 430072, China)
  • Received:2017-07-04 Published:2021-01-21

摘要: 基于中国资本密集型和技术密集型产业的面板数据,实证分析了人力资本投入对我国资本和技术密集型产业的技术创新产出的影响。静态分析结果表明,从资本和技术密集型产业的平均技术创新水平来看,人力资本投入显著地促进了资本和技术密集型产业的技术创新产出。分位数回归结果表明,人力资本投入对资本和技术密集型产业中相关行业的技术创新水平的影响呈现显著差异:对资本和技术密集型产业中处于中低端技术创新水平的行业来说,人力资本投入对提升技术创新水平的贡献更加明显;而对资本和技术密集型产业中处于高端技术创新水平的行业来说,人力资本投入的促进作用较弱一些。

关键词: 人力资本,资本密集型产业,技术密集型产业,技术创新,分位数回归

Abstract: Based on the panel data of China’s capital-intensive industries and technology-intensive industries, this paper makes an empirical analysis of the impacts of human capital inputs on the technological innovation outputs of China’s capital-intensive and technology-intensive industries. The results of the static analysis show that, in terms of the average level of technological innovation of both the industries, the inputs of human capital have significantly increased the outputs of technological innovation in the capital-intensive industry and the technology-intensive industries. But, the results of the quantile regression analysis indicate that the impacts of the human capital inputs on the technological innovation of the related fields of the two industries are prominently different: the human capital inputs can make greater contribution to the promotion of technological innovation for the industries with middle or lower level of technological innovation; while for the industries at the higher-end of technological innovation, the contribution made by the inputs of human capital is less.

Key words: human capital; capital-intensive industries; technology-intensive industries; technological innovation; quantile regression model