摘要翻译：
在本研究中，对于结构向量自回归模型发展贝叶斯推理，其中结构参数是通过马尔可夫切换异方差来辨识的。在这样一个模型中，在同态异构情况下只是识别的限制变成了过度识别，可以进行测试。构造了一组参数约束，在此约束下，结构矩阵可以全局或部分识别，并用Savage-Dickey密度比来评价识别条件的有效性。后者通过解析推导得到方便，使计算速度快，数值标准误差小。作为一个实证例子，使用异方差作为一种额外的识别手段来比较货币模型。实证结果支持带有货币的利率反应函数模型。
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英文标题：
《Bayesian Inference for Structural Vector Autoregressions Identified by
  Markov-Switching Heteroskedasticity》
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作者：
Helmut L\"utkepohl and Tomasz Wo\'zniak
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最新提交年份：
2018
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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：
  In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the homoskedastic case, become over-identifying and can be tested. A set of parametric restrictions is derived under which the structural matrix is globally or partially identified and a Savage-Dickey density ratio is used to assess the validity of the identification conditions. The latter is facilitated by analytical derivations that make the computations fast and numerical standard errors small. As an empirical example, monetary models are compared using heteroskedasticity as an additional device for identification. The empirical results support models with money in the interest rate reaction function.
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PDF链接：
https://arxiv.org/pdf/1811.08167