论文标题
贝叶斯分析季节性协整VAR模型
Bayesian analysis of seasonally cointegrated VAR model
论文作者
论文摘要
该论文旨在开发贝叶斯季节性协调模型，以获取季度数据。我们提出了先验的结构，得出完整条件后分布的集合，并提出采样方案。协同空间的识别是\ emph {via}的正常限制，对跨它们的向量施加了。在年度频率的情况下，协调向量很复杂，在识别它们时应考虑到它们。还讨论了协整空间的点估计。通过模拟实验说明了所提出的方法，并用于对波兰经济的货币和价格进行分析。
The paper aims at developing the Bayesian seasonally cointegrated model for quarterly data. We propose the prior structure, derive the set of full conditional posterior distributions, and propose the sampling scheme. The identification of cointegrating spaces is obtained \emph{via} orthonormality restrictions imposed on vectors spanning them. In the case of annual frequency, the cointegrating vectors are complex, which should be taken into account when identifying them. The point estimation of the cointegrating spaces is also discussed. The presented methods are illustrated by a simulation experiment and are employed in the analysis of money and prices in the Polish economy.
