基于潜类别随机前沿的区域创新效率及其影响因素分析

摘要

Use the latent class stochastic frontier model that can endogenous grouping according to the potential property of the research object ,and using the data of Chinese provinces from 1999 to 2012 , provincial innovation efficiency and influence factors were studied .The study found that levels of human capital and infrastructure conditions as the condition variable ,provinces are divided into two categories , respectively have their own technological frontier and functional form ; A category , the Shanghai innovation efficiency is highest ;The innovation efficiency of Hebei province was the highest in the category B ;On average ,each kind of categories innovation efficiency is on the rise ,openness ,industrial structure and financial development on innovation efficiency have significantly positive effect ;At the same time innovation efficiency exist club convergence in the each kinds of categories .%运用可根据研究对象的潜在属性内生分组的潜类别随机前沿模型，采用1999-2012年中国各省区数据，研究各省区的创新效率及影响因素。结果表明：以人力资本水平和基础设施状况为条件变量，将全国各省区分成两个技术类别，分别有各自的技术前沿和函数形式，A类别中上海市的创新效率最高，B类别中河北省的创新效率最高；平均来看，各类的创新效率均呈上升趋势，贸易开放、产业结构和金融发展对创新效率均有显著的正向作用，同时创新效率在各类内部均存在俱乐部收敛。