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作 者:任保显 王洪庆 REN Bao-xian;WANG Hong-qing(School of International Economics and Trade,Henan University of Economics and Law,Zhengzhou 450046,China)
机构地区:[1]河南财经政法大学国际经济与贸易学院
出 处:《经济经纬》2019年第6期95-102,共8页Economic Survey
基 金:河南省哲学社会科学规划项目(2018BJJ004);河南省教育厅人文社会科学研究项目(2020-ZDJH-017)
摘 要:利用中国2009-2016年高技术产业的省级面板数据,构建SFA模型测度高技术产业的创新效率,先从最优R&D资助规模视角研究了政府R&D资助对高技术产业创新效率的非线性影响以及企业规模对最优R&D资助强度的影响,然后对高技术产业的最优R&D资助强度特征及区间分布进行分析,最后测度了偏离最优R&D资助强度带来的效率损失。研究表明:政府R&D资助对高技术产业创新效率的影响表现为倒"U"形关系,最优R&D资助强度随企业规模变大而提高;现阶段政府R&D资助主要表现为"挤入效应";东部地区R&D资助强度与最优R&D资助强度差距最大,中部次之,西部最小;全国高技术产业的创新效率损失具有上升的趋势,且效率损失在东部地区最大,中、西部地区较小。Based on the provincial panel data of China’s high-tech industry from 2009 to 2016, this paper constructs a stochastic frontier approach model(SFA) to measure the innovation efficiency of high-tech industry. From the perspective of optimal R&D funding scale, this paper studies the non-linear impact of government R&D funding on innovation efficiency of high-tech industry and the impact of enterprise size on optimal R&D funding intensity. Then, the characteristics and interval distribution of the optimal R&D funding intensity in high-tech industry are analyzed. Finally, the efficiency losses caused by deviation from the optimal R&D funding intensity are measured. It is found that the impact of government R&D funding on innovation efficiency of high-tech industry can be illustrated as an inverted "U" curve, and the scale of enterprises will improve the optimal R&D funding intensity. At present, government R&D funding brings more "crowding-in effect". The gap between R&D funding intensity and optimal R&D funding intensity in the eastern region is the largest, followed by the central region and the western region. The loss of innovation efficiency of the national high-tech industry has an upward trend, and there is a largest efficiency loss in the eastern region and the middle and western regions are relatively small.
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