Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/153601
Authors: 
Gambetti, Luca
D’Agostino, Antonello
Giannone, Domenico
Year of Publication: 
2010
Series/Report no.: 
ECB Working Paper 1167
Abstract: 
The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coefficients VAR with Stochastic Volatility (TV-VAR) for the US. The model generates accurate predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the na¨ıve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.
Subjects: 
forecasting
inflation
stochastic volatility
Time Varying Vector Autoregression
JEL: 
C32
E37
E47
Document Type: 
Working Paper

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