Forecasting GDP growth with a Markov-Switching Factor MIDAS model

This paper merges two specifications developed recently in the forecasting literature: the MS-MIDAS model introduced by Guérin and Marcellino [2011] and the MIDAS-factor model considered in Marcellino and Schumacher [2010]. The MS-factor MIDAS model (MS-FaMIDAS) that we consider allows 1) incorporating the information provided by a large data-set, 2) taking into account mixed frequency variables, 3) capturing regime-switching behaviors. Monte Carlo simulations show that this new specification tracks the dynamics of the process quite well and captures the regime switches successfully, both in sample and out-of-sample. We apply this model to US data from 1959 to 2010 and detect properly the US recessions by exploiting the link between GDP growth and higher frequency financial variables