马尔可夫切换向量误差中的随机模型规范 修正模型

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摘要翻译：
针对马尔可夫切换向量误差修正模型，提出了一种分层建模方法来实现随机模型规范。我们假设一个共同的分布引起制度特定的回归系数。这种分布的均值和方差被视为完全随机的，并使用适当的收缩先验值。这些收缩先验值能够以灵活的方式评估不同制度的系数。在系数相似的情况下，我们的模型将参数空间的各个区域推向公共分布。这允许选择一个节省的模型，同时仍然保持足够的灵活性来控制参数的突然变化，如果需要的话。我们将我们的建模方法应用于欧元区的实时数据，并假设扩张和衰退制度之间的转换概率由协整误差驱动。结果表明，制度分配受短期调整系数子集和制度特定方差-协方差矩阵的控制。这些发现得到了样本外预测的补充，说明了该模型在实时预测欧元区通胀方面的优势。
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英文标题：
《Stochastic model specification in Markov switching vector error
  correction models》
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作者：
Niko Hauzenberger, Florian Huber, Michael Pfarrhofer, Thomas O.
  Z\"orner
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最新提交年份：
2019
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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：
  This paper proposes a hierarchical modeling approach to perform stochastic model specification in Markov switching vector error correction models. We assume that a common distribution gives rise to the regime-specific regression coefficients. The mean as well as the variances of this distribution are treated as fully stochastic and suitable shrinkage priors are used. These shrinkage priors enable to assess which coefficients differ across regimes in a flexible manner. In the case of similar coefficients, our model pushes the respective regions of the parameter space towards the common distribution. This allows for selecting a parsimonious model while still maintaining sufficient flexibility to control for sudden shifts in the parameters, if necessary. We apply our modeling approach to real-time Euro area data and assume transition probabilities between expansionary and recessionary regimes to be driven by the cointegration errors. The results suggest that the regime allocation is governed by a subset of short-run adjustment coefficients and regime-specific variance-covariance matrices. These findings are complemented by an out-of-sample forecast exercise, illustrating the advantages of the model for predicting Euro area inflation in real time.
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PDF链接：
https://arxiv.org/pdf/1807.00529

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关键词：马尔可夫 随机模型 coefficients econometrics distribution 误差 stochastic regime 变化 转换