Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/97333
Authors: 
Alessandri, Piergiorgio
Mumtaz, Haroon
Year of Publication: 
2014
Series/Report no.: 
Working Paper, School of Economics and Finance, Queen Mary, University of London 715
Abstract: 
When do financial markets help in predicting economic activity? With incomplete markets, the link between financial and real economy is state-dependent and financial indicators may turn out to be useful particularly in forecasting tail macroeconomic events. We examine this conjecture by studying Bayesian predictive distributions for output growth and inflation in the US between 1983 and 2012, comparing linear and nonlinear VAR models. We find that financial indicators significantly improve the accuracy of the distributions. Regime-switching models perform better than linear models thanks to their ability to capture changes in the transmission mechanism of financial shocks between good and bad times. Such models could have sent a credible advance warning ahead of the Great Recession. Furthermore, the discrepancies between models are themselves predictable, which allows the forecaster to formulate reasonable real-time guesses on which model is likely to be more accurate in the next future.
Subjects: 
Financial frictions
Predictive densities
Great Recession
Threshold VAR
JEL: 
C53
E32
E44
G01
Document Type: 
Working Paper

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