Working Paper Series no. 384: Forecasting GDP over the business cycle in a multi-frequency and data-rich environment

Abstract

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 introduce  incorporates the information provided by a large data-set, takes into account mixed frequency variables and captures regime-switching behaviors. Monte Carlo simulations show that this new specification tracks the dynamics of the process quite well and predicts the regime switches successfully, both in sample and out-of-sample. We apply this new 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.

Marie Bessec and Othman Bouabdallah
June 2012

Classification JEL : C22, E32, E37

Keywords : Markov-Switching, factor models, mixed frequency data, GDP forecasting