A factor-augmented probit model for business cycle analysis
Christophe Bellégo and
Laurent Ferrara ()
No 2010-14, EconomiX Working Papers from University of Paris Nanterre, EconomiX
Dimension reduction of large data sets has been recently the topic of interest of many research papers dealing with macroeconomic modelling. Especially dynamic factor models have been proved to be useful for GDP nowcasting or short-term forecasting. In this paper, we put forward an innovative factor-augmented probit model in order to analyze the business cycle. Factor estimation is carried either by standard statistical methods or by allowing a richer dynamic behaviour. An application is provided on euro area data in order to point out the ability of the model to detect recessions over the period 1974-2008.
Pages: 13 pages
New Economics Papers: this item is included in nep-bec, nep-cba, nep-ecm, nep-eec, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:drm:wpaper:2010-14
Access Statistics for this paper
More papers in EconomiX Working Papers from University of Paris Nanterre, EconomiX Contact information at EDIRC.
Bibliographic data for series maintained by Valerie Mignon ().