文章基本信息

标题：Markov-switching three-pass regression filter
本地全文：下载
作者：Pierre Guérin ; Danilo Leiva-Leon ; Massimiliano Marcellino 等
期刊名称：Documentos de Trabajo / Banco de España
印刷版ISSN：0213-2710
电子版ISSN：1579-8666
出版年度：2017
卷号：1
出版社：Banco de España
摘要：We introduce a new approach for the estimation of high-dimensional factor models withregime-switching factor loadings by extending the linear three-pass regression fi lter tosettings where parameters can vary according to Markov processes. The new method,denoted as Markov-switching three-pass regression fi lter (MS-3PRF), is suitable for data setswith large cross-sectional dimensions, since estimation and inference are straightforward,as opposed to existing regime-switching factor models where computational complexitylimits applicability to few variables. In a Monte Carlo experiment, we study the fi nite sampleproperties of the MS-3PRF and fi nd that it performs favourably compared with alternativemodelling approaches whenever there is structural instability in factor loadings. For empiricalapplications, we consider forecasting economic activity and bilateral exchange rates, fi ndingthat the MS-3PRF approach is competitive in both cases.
关键词：factor model; Markov-switching; forecasting.