Modelling Regime Switching and Structural Breaks with an Infinite Dimension Markov Switching Model
Modelling Regime Switching and Structural Breaks with an Infinite Dimension Markov Switching Model
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使用无限维马尔可夫切换模型对机制切换和结构断裂进行建模
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Yong Song
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文献类型：
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作者：
Yong Song
本文提出了一个无限维马尔可夫转换模型，以适应机制转换和结构突变动态或两者的组合在贝叶斯框架。两个平行的层次结构，一个管理的转移概率和另一个管理的参数的条件数据密度，保持模型的简约和提高预测。这种非参数的方法允许政权的持久性和估计的状态自动的数量。提出了一种结构变化与状态转换的全局辨识算法。美国的真实的利率和通货膨胀的应用比较新的模型，现有的参数替代品。除了识别政权转换和结构突变的情节，层次分布的参数的条件数据密度提供了显着的收益预测精度。
This paper proposes an infinite dimension Markov switching model to accommodate regime switching and structural break dynamics or a combination of both in a Bayesian framework. Two parallel hierarchical structures, one governing the transition probabilities and another governing the parameters of the conditional data density, keep the model parsimonious and improve forecasts. This nonparametric approach allows for regime persistence and estimates the number of states automatically. A global identification algorithm for structural changes versus regime switching is presented. Applications to U.S. real interest rates and inflation compare the new model to existing parametric alternatives. Besides identifying episodes of regime switching and structural breaks, the hierarchical distribution governing the parameters of the conditional data density provides significant gains to forecasting precision.