摘要翻译：
在这篇论文中，我们的目标是通过考虑关于基础结构表示的不确定性来改进现有的经验汇率模型。在一个灵活的贝叶斯非线性时间序列框架内，我们的建模方法假设不同的制度由常用的结构性汇率模型来表征，它们的演化由马尔可夫过程驱动。我们假设一个时变的转移概率矩阵，转移概率依赖于国内外中央银行货币政策立场的度量。我们将这个模型应用于一组八种兑美国元的汇率。在一个预测练习中，我们发现模型证据随时间而变化，一个认真对待这一经验证据的模型方法在考虑的大多数货币对的密度预测精度上产生了改进。
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英文标题：
《Model instability in predictive exchange rate regressions》
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作者：
Niko Hauzenberger and Florian Huber
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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 paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian non-linear time series framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with their evolution being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at the home and foreign country. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time and a model approach that takes this empirical evidence seriously yields improvements in accuracy of density forecasts for most currency pairs considered.
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PDF链接：
https://arxiv.org/pdf/1811.08818