Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data
利用大型面板数据集，通过贝叶斯聚类和动态结构识别领先与同步序列组，用于历史转折点定年和未来转折点预测，并以奥地利数据验证模型有效性。
Abstract The information contained in a large panel dataset is used to date historical turning points and to forecast future ones. We estimate groups of series with similar time series dynamics and link the groups with a dynamic structure. The dynamic structure identifies a group of leading and a group of coincident series. Robust results across data vintages are obtained when series‐specific information is incorporated in the design of the prior group probability distribution. The forecast evaluation confirms that the Markov switching panel with dynamic structure performs well when compared to other specifications. Copyright © 2009 John Wiley & Sons, Ltd.