摘要
本文运用扩展的分布动态学模型,研究了中国1989—2012年间30个省级地区创新水平的趋同时空特征。核密度函数分析发现,中国创新水平极化程度经历了先增大后减小的趋势,整体趋同态势明显;考虑不同时长的马尔科夫链模型发现,高水平和低水平创新俱乐部存在明显趋同特征,且在1997年之后"俱乐部趋同"特征更加明显;区域背景对地区创新水平的转移存在影响,这为中国创新水平的"俱乐部趋同"特征给出了空间上的解释。研究还发现,显著的空间作用至少需要两年时间积累才能体现出来。
Based on Extended Distribution Dynamics model, this paper analyses the convergence and divergence of .the distribution of the innovative capacity of 30 provinces in China during 1989--2012. Based on kernel density function, we find that the convergence trend is evident; Markov chain model considered different time length reveals that there exists obvious "club convergence" characteris- tics for provinces in high-level and low-level clubs, and the features are more obvious after 1997; regional background can affect the transformation of innovation, which can explain'the "club convergence" characteristics of innovation level in China. The study also finds that the significant spatial spillover effect needs at least two years to appear.
出处
《中国科技论坛》
CSSCI
北大核心
2015年第6期11-15,共5页
Forum on Science and Technology in China
基金
中南财经政法大学博士研究生创新教育项目"基于高频数据的中国股市收益分布及预测研究"(2014B1901)
关键词
创新水平
区域趋同
核密度估计
马尔科夫链
Innovation level
Regional convergence
Kernel density estimation
Markov chain