基于贝叶斯面板平滑转换模型的区域资本流动性研究  

Study of Regional Capital Liquidity Based on Bayesian Panel Smooth Transition Regression Models

作　　者：朱慧明[1] 彭成[1] 游万海[1] 曾昭法[2] 任英华[2] 

机构地区：[1]湖南大学工商管理学院,湖南长沙410082 [2]湖南大学金融与统计学院,湖南长沙410079

出　　处：《湖南大学学报（自然科学版）》2014年第4期113-117,共5页Journal of Hunan University:Natural Sciences

基　　金：国家自然科学基金资助项目(71221001;71031004;7171075);教育部博士点基金资助项目(20110161110025);湖南省自然科学基金资助项目(11JJ3090)

摘　　要：针对面板平滑转换模型参数不确定性风险问题,构建了区域资本流动性的贝叶斯面板平滑转换模型.通过模型的统计结构分析,选择参数先验分布,设计相应的MHGibbs混合抽样算法,据此估计模型参数,解决非线性OLS参数估计过程中遇到的算法难以收敛问题;并利用中国各地区投资与储蓄面板数据进行实证分析.研究结果表明:参数的迭代轨迹收敛,MH-Gibbs混合抽样算法能够准确地估计模型参数,证明了贝叶斯面板平滑转换模型的有效性.In order to study the regional capital liquidity, Bayesian panel smooth transition regression models were established to address uncertain risk of parameters estimation in PSTR models. Based on the analysis of model statistic structure and the selection of parameters prior, the Metropolis-Hasting within Gibbs sampling method was utilized to estimate model parameters, avoiding the convergent problem when using the nonlinear least square method in PSTR model. The empirical research applies Bayesian PSTR to analyse the panel data of investment and saving in Chinese provinces. The research outcome indicates that the iteration trace of parameters is convergent, and the Metropolis-Hasting within Gibbs sampling method estimates model parameters accurately, showing the effectiveness of Bayesian PSTR model approach.

关 键 词：面板数据模型 仿真 贝叶斯分析 资本流动性 MH-Gibbs混合抽样算法 

分 类 号：O212.8[理学—概率论与数理统计]