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 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...

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...

Progresses in fiscal consolidation programs are often expressed in cyclically-adjusted terms, meaning that business cycles have to be accurately estimated. In this paper, we put forward a parametric framework enabling to assess business cycles, especially at the end of recession periods by...

This paper proposes a two-regime Bounce-Back Function augmented Self-Exciting Threshold AutoRegression (SETAR) model which allows for various shapes of recoveries from the recession regime. It relies on the bounce-back effects which were first analyzed in a Markov-Switching setup by Kim, Morley,...

This paper proposes a two-regime Bounce-Back Function augmented Self-Exciting Threshold AutoRegression (SETAR) which allows for various shapes of recoveries from the recession regime. It relies on the bounce-back effects first analyzed in a Markov-Switching setup by Kim, Morley and Piger [2005]...

This paper explores the various shapes the recoveries may exhibit within a Markov- Switching model. It relies on the bounce-back effects first analyzed by Kim, Morley and Piger (2005) and extends the methodology by proposing i) a more flexible bounce-back model, ii) explicit tests to select the...