中国省际创新要素流动对高技术产业创新效率的影响

The Influence of Interprovincial Innovation Factor Flow on Innovation Efficiency of High-Tech Industry in China

摘要: 为更好地推动经济发展由要素驱动转向创新驱动，高技术产业创新效率的提升成为必由之路。揭示各省份高技术产业创新效率区域差异，分析讨论创新要素流动对高技术产业创新效率的影响，对各省份因地制宜制定有针对性的高技术产业区域协调发展策略具有重要的理论意义和参考价值。本文利用2000~2022年30个省市地区(除西藏)的面板数据，选用数据包络分析法和引力模型对中国各省高技术产业创新效率及创新要素流动量进行测算，采用面板计量模型和空间计量模型探究各省创新要素流动对中国高技术产业创新效率的影响。回归结果显示：创新要素流动对各省高技术产业创新效率的提升具有显著促进作用，且创新人才流动对高技术产业创新效率提升的贡献要高于创新资本流动的贡献。创新人才流动对高技术产业创新效应具有较强的正向空间溢出效应，而创新资本流动的空间溢出效应不显著。

Abstract: In order to better promote economic development from factor driven to innovation-driven, the improvement of innovation efficiency in high-tech industries has become the only way. It is of great theoretical significance and reference value to reveal regional differences in innovation efficiency of high-tech industries in different provinces, analyze and discuss the influence of innovation factor flow on innovation efficiency of high-tech industries, and formulate targeted regional coordinated development strategies for high-tech industries in different provinces. Based on the panel data of 30 provinces and cities (except Tibet) from 2000 to 2022, this paper uses data enveloping analysis and gravity model to measure the innovation efficiency and innovation factor flow of China’s high-tech industries by provinces, and uses panel econometric model and spatial econometric model to explore the impact of innovation factor flow of provinces on the innovation efficiency of China’s high-tech industries. The regression results show that the flow of innovation factors has a significant effect on the improvement of innovation efficiency of high-tech industries in each province, and the contribution of innovation talent flow to the improvement of innovation efficiency of high-tech industries is higher than that of innovation capital flow. The flow of innovative talents has a strong positive spatial spillover effect on the innovation effect of high-tech industry, but the spatial spillover effect of innovative capital flow is not significant.