高校创新效率动态演进分析及影响因素识别——基于非参数核密度估计和SFA模型  

Analysis on the Dynamic Evolution and Discernment of Innovation Efficiency Influencing Factors in China's Universities:Based on Nonparametric Kernel Density Estimation and SFA Model

作　　者：王晓珍[1] 蒋子浩 郑颖 WANG Xiao-zhen;JIANG Zi-hao;ZHENG Ying(School of Management,China University of Mining and Technology,Xuzhou 221116,China)

机构地区：[1]中国矿业大学管理学院,江苏徐州221116

出　　处：《统计与信息论坛》2018年第9期81-87,共7页Journal of Statistics and Information

基　　金：国家自然科学基金项目<时滞周期;市场创新绩效动态测度与三级科技经费配置结构优化研究>(71303234);江苏省教育科学"十二五"规划重点资助项目<江苏省高等教育经费的投入产出效率测度及优化配置研究>(Ba/2015/01/022)

摘　　要：基于核密度估计和SFA模型,剖析2011—2015年中国高校创新效率及分解指标动态演进趋势和高校创新效率影响因素。通过对样本期内中国不同省级行政单位的面板数据分析发现:高校创新技术效率"双峰"态势显著、规模效率"单峰"态势显著,而纯技术效率分布曲线形态较多变,表明技术效率双极聚集、规模效率省域差异显著、纯技术效率波动较大;同时,经济优势、区域创新氛围、政策扶持力度、区位优势是影响高校创新效率的主要因素。据此提出改善并优化高校创新效率的对策建议。Based on kernel density estimation method and SFA model,this paper analyzes the trends of innovation efficiency and decomposition indicators of universities in China and the factors influencing the innovation efficiency of universities during the 2011-2015 period,and finds that the innovation efficiency and the decomposition index shows that the"two peak"trend is remarkable,the scale efficiency"single peak"is remarkable,and the distribution curve of pure technical efficiency is more variable,which shows that the technical efficiency is bipolar aggregation,the scale efficiency is distinct,and the pure technical efficiency wave changes much.At the same time,economic advantage,regional innovation atmosphere,policy support and location advantages are the main causes affecting the innovation efficiency of universities.And then the paper puts forward some suggestions.

关 键 词：高校创新效率 核密度估计 区域创新环境 

分 类 号：F213.5[经济管理—国民经济]