基于Bayesian Gibbs Sampler的状态空间模型估计方法研究及其在中国潜在产出估计上的应用被引量：13

Estimation Method of State Space Model Using Bayesian Gibbs Sampler and Its Application on Estimating China's Potential Growth Rate

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摘要本文将贝叶斯吉伯斯样本生成(Bayesian Gibbs Sampling,BGS)方法应用到状态空间模型的估计。首先介绍了BGS方法的基本内容和计算步骤,然后给定参数生成满足状态空间模型的模拟数据,并对模拟数据应用BGS方法估计。结果表明参数和状态向量的估计值与参数和状态向量的真实值相当接近,明显优于基于Kalman滤波的最大似然估计结果。最后,本文将BGS算法应用于中国1980至2008年的潜在增长率与增长率缺口的估计。 In this paper we apply the Bayesian Gibbs Sampling （BGS） method to the estimate of state space model. First, we introduce the basic contents and computing algorithm, then giving the parameters we generated the data that satisfy a state space model and estimate the model using BGS method. The results show that the estimated parameters and state vector are very close to the real ones and are clearly prior to those of the maximum likelihood estimation based on Kalman filter. Finally, we estimate China＇s potential GDP growth rate and growth rate gap from 1980 to 2008.

作者赵昕东耿鹏

机构地区华侨大学数量经济研究院华侨大学商学院

出处《统计研究》 CSSCI 北大核心 2009年第9期55-63,共9页 Statistical Research

基金福建省自然科学基金(2009J01312)资助

关键词贝叶斯估计吉伯斯样本生成状态空间模型潜在增长率 Bayesian Estimation Gibbs Sampler State Space Model Potential Growth Rate

分类号 O212 [理学—概率论与数理统计]

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参考文献23

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