EconPapers    
Economics at your fingertips  
 

Using Confidence Data to Forecast the Canadian Business Cycle

Kevin Moran () and Simplice Aime Nono

Cahiers de recherche from Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques

Abstract: This paper assesses the contribution of confidence - or sentiment - data in predicting Canadian economic slowdowns. A probit framework is specified and applied to an indicator on the status of the Canadian business cycle produced by the OECD. Explanatory variables include all available Canadian data on sentiment (which arise from four different surveys) as well as various macroeconomic and financial data. The model is estimated via maximum likelihood and sentiment data are introduced either as individual variables, as simple averages (such as confidence indices) and as confidence factors extracted, via principal components' decompositions, from a larger dataset in which all available sentiment data have been collected. Our findings indicate that the full potential of sentiment data for forecasting future business cycles in Canada is attained when all data are used through the use of factor models.

New Economics Papers: this item is included in nep-mac
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.crrep.ca/sites/crrep.ca/files/fichier_publications/crrep-2016-06.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lvl:crrecr:1606

Access Statistics for this paper

More papers in Cahiers de recherche from Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques Contact information at EDIRC.
Bibliographic data for series maintained by Manuel Paradis ().

 
Page updated 2019-10-10
Handle: RePEc:lvl:crrecr:1606