Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/210008 
Year of Publication: 
2012
Series/Report no.: 
Working Paper No. 2012/09
Publisher: 
Norges Bank, Oslo
Abstract: 
This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point and density forecasts of macroeconomic variables. In this analysis, we consider both Bayesian autoregressive and Bayesian vector autoregressive models that incorporate some form of time-varying volatility, precisely stochastic volatility (both with constant and time-varying autoregressive coefficients), stochastic volatility following a stationary AR process, stochastic volatility coupled with fat tails, GARCH and mixture of innovation models. The comparison is based on the accuracy of forecasts of key macroeconomic time series for real-time post War-II data both for the United States and United Kingdom. The results show that the AR and VAR specifications with widely-used stochastic volatility dominate models with alternative volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree.
Subjects: 
GARCH
stochastic volatility
forecasting
JEL: 
E17
C11
C53
Persistent Identifier of the first edition: 
ISBN: 
978-82-7553-672-1
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper
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