Forecasting GDP over the Business Cycle in a Multi-Frequency and Data-Rich Environment

• Autores: Marie Bessec, Othman Bouabdallah
• Localización: Oxford bulletin of economics and statistics, ISSN 0305-9049, Vol. 77, Nº. 3, 2015, págs. 360-384
• Idioma: inglés
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• Resumen

  • 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 set consisting of mixed frequency variables and captures regime-switching behaviours. Monte Carlo simulations show that this specification tracks the dynamics of the process and predicts the regime switches successfully, both in-sample and out-of-sample. We apply this model to US data from 1959 to 2010 and properly detect recessions by exploiting the link between GDP growth and higher frequency financial variables.