摘要翻译：
马尔可夫切换模型是一个流行的模型家族，它以状态或制度特定值的形式引入参数的时变。重要的是，这种时变是由一个具有有限记忆的离散值潜在随机过程控制的。更具体地说，状态指示符的当前值仅由来自前一周期的状态指示符的值确定，从而由马尔可夫性质和转移矩阵确定。后者通过给定当前周期中的状态，确定下一个周期中每个状态可以被访问的概率来表征马尔可夫过程的性质。这种设置决定了Markov切换模型的两个主要优点。即，利用滤波和平滑方法估计每个样本周期中状态发生的概率，以及估计特定于状态的参数。这两个特征为改进与特定制度有关的参数和相应制度概率的解释以及改进基于持久制度和表征这些制度的参数的预报性能提供了可能性。
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英文标题：
《Markov Switching》
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作者：
Yong Song, Tomasz Wo\'zniak
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最新提交年份：
2020
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  Markov switching models are a popular family of models that introduces time-variation in the parameters in the form of their state- or regime-specific values. Importantly, this time-variation is governed by a discrete-valued latent stochastic process with limited memory. More specifically, the current value of the state indicator is determined only by the value of the state indicator from the previous period, thus the Markov property, and the transition matrix. The latter characterizes the properties of the Markov process by determining with what probability each of the states can be visited next period, given the state in the current period. This setup decides on the two main advantages of the Markov switching models. Namely, the estimation of the probability of state occurrences in each of the sample periods by using filtering and smoothing methods and the estimation of the state-specific parameters. These two features open the possibility for improved interpretations of the parameters associated with specific regimes combined with the corresponding regime probabilities, as well as for improved forecasting performance based on persistent regimes and parameters characterizing them.
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PDF链接：
https://arxiv.org/pdf/2002.03598