Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession
Laurent Ferrara and
Clément Marsilli
Post-Print from HAL
Abstract:
The global economic recession, referred to as the Great Recession, endured by the main industrialized countries during the period 2008-09, in the wake of the financial and banking crises, has pointed out the current importance of the financial sector in macroeconomics. In this article, we evaluate the predictive power of some major financial variables to anticipate GDP growth in euro area countries during this specific period of time. In this respect, we implement a Mixed Data Sampling (MIDAS)-based modelling approach, put forward by Ghysels et al. (2007), that enables to forecast quarterly Gross Domestic Product (GDP) growth rates using exogenous variables sampled at higher frequencies. Empirical results show that, overall, stock prices help to improve the accuracy of GDP forecasts by comparison with a standard opinion survey variable, whereas oil prices and term spread appear to be less informative.
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (13)
Published in Applied Economics Letters, 2013, 20 (3), pp.233 - 237. ⟨10.1080/13504851.2012.689099⟩
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Journal Article: Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession (2013) 
Working Paper: Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession (2012) 
Working Paper: Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession (2012) 
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:hal:journl:hal-01385844
DOI: 10.1080/13504851.2012.689099
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().