摘要
针对传统的随机前沿模型测度创新效率中存在的问题,结合投影寻踪模型降维的特点,构建更加有效的随机前沿评测效率的改进模型。在此基础上,选用2003—2011年中国30个省市地区的面板数据对中国各省域研发创新效率及影响因素进行实证分析,结果表明:中国省域研发创新效率均值不足0.5,处于较低水平,存在较大的无效率现象,尚有较大的提升空间;且各省域研发创新效率差异性较大,发展不均衡。在分析研发创新效率的影响因素中发现,经济水平、对外开放程度、政府资助、教育重视程度、产权保护意识以及信息化水平均是促进研发创新效率提升的有利因素。
As there are problems in measuring innovation efficiency with the traditional stochastic frontier analysis model(SFA), combined with the characters of projection pursuit model which can reduce the dimensionality of multidimensional data, the paper improves to SFA in order to effectively measure innovation efficiency. On this basis, regional R&D innovation efficiency in Chinese provinces was analyzed empirically by adopting the data from30 provinces of China in 2003-2011, and the result shows: the average of regional R&D innovation efficiency is below 0.5 percent, which is generally in a lower level and has the existence of the phenomenon of inefficiency,so there has large spaces to be doing better. The paper analyzes impact factors of innovation efficiency found that the level of economy, foreign opening degree, government funding, emphasis put on educating, property rights awareness, informationization level are favorable factors for R&D innovation efficiency.
出处
《科学学与科学技术管理》
CSSCI
北大核心
2015年第4期124-132,共9页
Science of Science and Management of S.& T.
基金
国家自然科学基金项目(71473055)
教育部新世纪优秀人才支持计划(NCET-11-0825)
教育部人文社会科学研究项目(14YJA630002)
中央高校基本科研业务经费支持计划(HEUCF140901)
黑龙江省普通高等学校青年学术骨干支持计划(1252G015)
关键词
研发创新
效率
投影寻踪模型
随机前沿分析模型
R&D innovation
efficiency
projection pursuit model(PP)
stochastic frontier analysis model(SFA)