摘要
基于2011—2018年83个国家高新区的面板数据,依次采用超越对数生产函数的随机前沿模型、K‑R方差分解、面板数据固定效应模型实证考察了国家高新区的创新效率增长的空间差异及其影响因素。研究发现:①国家高新区总体创新效率呈现先降后升的态势,且存在明显的空间差异,东部国家高新区创新效率增长最快,中部国家高新区次之,西部国家高新区最慢;②规模效率变化差异是国家高新区创新效率增长差异的主要来源;③经济发展水平对国家高新区创新效率增长具有显著的负向影响,人力资本、产业结构、国际化等则具有显著的正向影响。基于研究结论,提出了促进国家高新区创新效率协同提升和均衡发展的对策建议。
Based on the panel data of 83 national high-tech zones from 2011 to 2018,the spatial differences and its influencing factors of innovation efficiency growth in national high-tech zones are investigated by utilizing the stochastic frontier model,K-R variance decomposition and panel data fixed effect model.The results show as follows.The innovation efficiency of national high-tech zones shows a trend of first decreasing and then increasing,and the spatial differences are obvious,the innovation efficiency of eastern national high-tech zones growing fastest,followed by central national high-tech zones,and western national high-tech zones growing slowest.The difference of scale efficiency is the main source of the difference of innovation efficiency growth in national high-tech zones.The level of economic development has a significant negative impact on the innovation efficiency growth of national high-tech zones,while human capital,industrial structure and internationalization have significant positive impacts on innovation efficiency growth.Based on the research conclusion,some suggestions are put forward to promote the collaborative improvement and balanced development of innovation efficiency of national high-tech zones.
作者
张路娜
孙红军
胡贝贝
Zhang Luna;Sun Hongjun;Hu Beibei(School of Public Policy and Management,University of Chinese Academy of Sciences,Beijing 100049,China;Institutes of Science and Development,Chinese Academy of Sciences,Beijing 100190,China)
出处
《技术经济》
CSSCI
北大核心
2021年第6期1-8,共8页
Journal of Technology Economics
基金
国家自然科学基金青年基金“数字化创业生态系统的演化机理与治理模式研究”(72002212)。
关键词
国家高新区
创新效率增长
随机前沿生产函数
空间差异
影响因素
national high-tech zones
innovation efficiency growth
stochastic frontier production function model
spatial differences
influencing factors