摘要
本文基于1997—2013年中国高技术产业数据,构建不同行业和不同地区高技术产业动态面板数据模型,采用系统GMM估计实证分析三大产业集聚的外部性(MAR外部性、Jacobs外部性、Porter外部性)对高技术产业创新的影响,实证结果显示:产业多样化对中国高技术产业创新具有显著的促进作用,而产业专业化和企业竞争对高技术产业创新影响并不显著;东中西部地区和五大高技术行业的产业集聚外部性对产业创新影响效果不同,循环累积效应在不同模型中对区域产业创新均具有显著的正向影响;地区规模、人力资本水平和外商直接投资三大控制变量及其平方项在不同模型中的作用效果和显著性水平具有明显差异.
Based on the data of China＇s high-tech industry form 1997 to 2013, it built the high-tech industry dynamic panel data models with different industries and different regions, and used system GMM estimation to analyze the impact of three major industrial agglomeration externalities （MAR externality, Jacobs externality, Porter externality） on high- teeh industry innovation. Empirical results show： industrial diversification plays a significant role in promoting China＇s high-tech industry innovation, but the impact of industrial specialization and enterprises＇ competitiveness on the high- tech industry innovation are not significant. The industrial agglomeration externalities have different effects on high-tech industry innovation in the eastern, central, western regions and five high-tech industries, and cumulative effects have a significant positive impact on regional industrial innovation in different models. The effects and significance levels of three control variables （regional scale, human capital and foreign direct investment） and their square term have signifi- cant differences in different models.
出处
《研究与发展管理》
CSSCI
北大核心
2016年第6期27-37,共11页
R&D Management
基金
全国统计科学研究计划项目"中国高技术产业发展非均衡测度及改进路径研究"(2014LY035)
山东省软科学研究项目"山东省生产性服务业发展非均衡
极化及改进路径研究"(2015RKB01043)
青岛市软科学项目"青岛市生产性服务业发展非均衡
空间极化及改进路径研究"(15-9-2-1-(23)-zhc)
关键词
中国高技术产业
产业专业化
产业多样化
企业竞争程度
系统GMM估计
China＇s high-tech industry
industrial specialization
industrial diversification
degree of enterprise compe- tition
system GMM estimation
