This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications by applying...

This paper merges two specifications developed recently in the forecasting literature: the MS-MIDAS model introduced by Gu´erin and Marcellino [2011] and the MIDAS-factor model considered in Marcellino and Schumacher [2010]. The MS-factor MIDAS model (MS-FaMIDAS) that we introduce incorporates...

This paper merges two specifications recently developed in the forecasting literature: the MS-MIDAS model (Guérin and Marcellino, 2013) and the factor-MIDAS model (Marcellino and Schumacher, 2010). The MS-factor MIDAS model that we introduce incorporates the information provided by a large data...

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications. In order to...

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications by applying...

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications. In order to...