贝叶斯隐马尔科夫异质面板模型及应用研究

针对不可观测异质性非时变假设导致的删失变量偏差及推断无效问题，构建贝叶斯隐马尔科夫异质面板模型，刻画截面个体间的动态时变不可观测异质性，诊断经济系统环境中可能存在的隐性变点，设计相应的马尔科夫链蒙特卡洛抽样算法估计模型参数，并对中国各地区的金融发展与城乡收入差距关系进行实证分析，捕捉到金融发展与城乡收入差距间长期稳定关系的隐性变化，发现了区域个体不可观测异质性存在的动态时变特征。研究结果表明各参数的迭代轨迹收敛且估计误差非常小，验证了贝叶斯隐马尔科夫异质面板模型的有效性。

Bayesian Heterogeneous Hidden Markov Panel Model and its Application

For time-invariant unobserved heterogeneity assumption lead to censored variable bias and invalid inference problem, this paper constructed Bayesian Heterogeneous Hidden Markov Panel Model to characterize the dynamics time-varying unobserved heterogeneity between sectional individuals and diagnose the hidden changes existing in economic system environment, designed the corresponding Markov Chain Monte Carlo sampling algorithm to estimate model parameters, and analyzed the relationships between financial development and urban-rural income gap. The empirical research captured hidden changes in the long term stable relationships between financial development and urban-rural income gap, found out that regional individual unobserved heterogeneity existed dynamic time-varying characteristics. Results showed that the parameters iterative trajectory converges and the estimated error was very small, it verified the effectiveness of the Bayesian Heterogeneous Hidden Markov Panel Model.Bayesian Heterogeneous Hidden Markov Panel Model and its Application