中国省际高技术产业创新效率评价研究——基于超效率DEA模型和Malmquist指数法

基于中国29个省区市2014-2018年高技术产业的面板数据,首先采用超效率DEA模型对各省市生产效率进行测算,进而构建DEA-Malmquist模型对各省市综合生产率指数进行计算和分解.结果表明:中国高技术产业创新效率的总体水平较高,但是超过一半的省市区要素投入结构不合理,而且主要分布在中部和西部地区,创新效率存在较大的区域差异;中国高技术产业的全要素生产率指数平均值大于1,很多省份存在规模效率不高的问题,导致创新效率呈现N型的回调震动形态,技术进步和技术效率是全要素生产率提高的主要动力.因此,为了进一步提高我国高技术产业创新效率,需要注意保持高技术产业的技术水平和技术效率,尤其要注重高技术产业科技资源的优化配置,提升高技术产业创新资源的管理水平.

Research on innovation efficiency evaluation of China's interprovincial high-tech Industries -- Based on super-efficiency DEA model and malmquist index method

Based on the panel data of high-tech industries of 29 provinces, autonomous regions and municipalities in China from 2014 to 2018, the super-efficiency DEA model was first used to calculate the production efficiency of each province, and then the DEA-Malmquist model was constructed to calculate and decompose the comprehensive productivity index of each province. The results show that: The overall level of innovation efficiency of China''s high-tech industries is relatively high, but more than half of the provinces and municipalities have unreasonable factor input structure, which is mainly distributed in the central and western regions, and the innovation efficiency has great regional differences. The average total factor productivity index of China''s high-tech industries is greater than 1. Many provinces suffer from low scale efficiency, resulting in n-type callback vibration of innovation efficiency. Technological progress and technical efficiency are the main driving forces for total factor productivity improvement. Therefore, in order to further improve the innovation efficiency of China''s high-tech industry, attention should be paid to maintain the technical level and efficiency of high-tech industry, especially to optimize the allocation of high-tech industry''s scientific and technological resources, and to improve the management level of high-tech industry''s innovative resources.