• français
    • English
  • English 
    • français
    • English
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.
BIRD Home

Browse

This CollectionBy Issue DateAuthorsTitlesSubjectsJournals BIRDResearch centres & CollectionsBy Issue DateAuthorsTitlesSubjectsJournals

My Account

Login

Statistics

View Usage Statistics

Forecasting GDP over the business cycle in a multi-frequency and data-rich environment

Thumbnail
Date
2015
Dewey
Théorie économique
Sujet
Markov-Switching; factor models, mixed frequency data; GDP forecasting
JEL code
C.C1.C15
Journal issue
Oxford Bulletin of Economics and Statistics
Volume
77
Number
3
Publication date
2015
Article pages
360-384
Publisher
Basil Blackwell
DOI
http://dx.doi.org/10.1111/obes.12069
URI
https://basepub.dauphine.fr/handle/123456789/15384
Collections
  • LEDa : Publications
Metadata
Show full item record
Author
Bessec, Marie
status unknown
Bouabdallah, Othman
Type
Article accepté pour publication ou publié
Abstract (EN)
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.

  • Accueil Bibliothèque
  • Site de l'Université Paris-Dauphine
  • Contact
SCD Paris Dauphine - Place du Maréchal de Lattre de Tassigny 75775 Paris Cedex 16

 Content on this site is licensed under a Creative Commons 2.0 France (CC BY-NC-ND 2.0) license.