中国经济随机前沿模型效率的贝叶斯统计推断
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引用本文:张理想 1,李亚琼 1 ,马饶晴 2.中国经济随机前沿模型效率的贝叶斯统计推断[J].经济数学,2019,(2):10-17
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作者单位
张理想 1,李亚琼 1 ,马饶晴 2 (1.湖南大学 数学与计量经济学院,湖南 长沙 4100822.伦敦大学国王学院英国 伦敦 SE5 9RJ) 
中文摘要:基于扩展的随机生产前沿模型,研究了区域生产效率的差异和其影响因素的作用效果,应用贝叶斯统计方法对中国各省份2010-2017的年度数据(不包含港澳台地区,下同)进行了实证研究.研究发现:生产效率总体呈逐渐下降的趋势,地区间生产效率有一定的差异,高等教育规模对生产效率具有显著的直接影响.人力资本能有效促进东部和中部地区的经济增长,西部地区主要依靠资本促进经济增长.环境污染对中部地区的经济增长具有一定的负向作用.
中文关键词:数理统计  随机前沿模型  贝叶斯统计推断  生产效率分析  Gibbs算法
 
Bayesian Statistical Inference on the Efficiency of Stochastic Frontier Model for Chinese Economy
Abstract:Based on the extended stochastic production frontier model, the difference of regional production efficiency and the effect of its influencing factors were studied, and then the annual data of various provinces in China from 2010 to 2017 were used to conduct an empirical research by using Bayesian statistical method. Through the research, it is found that the production efficiency shows a trend of gradual decline generally, and there are certain differences in the production efficiency between regions. The scale of higher education has a significant direct impact on the production efficiency. Human capital can effectively promote economic growth in the eastern and central regions, while the western region mainly relies on capital to promote economic growth. Environmental pollution has a significant negative impact on the economic growth of the central region.
keywords:mathematical statistics  stochastic frontier model  Bayesian statistical inference  production efficiency analysis  Gibbs algorithm
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