• Media type: E-Book
  • Title: Forecasting GDP Over the Business Cycle in a Multi-Frequency and Data-Rich Environment
  • Contributor: Bessec, Marie [Author]; Bouabdallah, Othman [Other]
  • Published: [S.l.]: SSRN, [2012]
  • Published in: Banque de France Working Paper ; No. 384
  • Extent: 1 Online-Ressource (33 p)
  • Language: English
  • DOI: 10.2139/ssrn.2090915
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 1, 2012 erstellt
  • Description: 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 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
  • Access State: Open Access