DP7542 Macroeconomic Forecasting and Structural Change
Author(s): | Antonello D'Agostino, Luca Gambetti, Domenico Giannone |
Publication Date: | November 2009 |
Keyword(s): | Forecasting, Inflation, Stochastic Volatility, Time Varying Vector Autoregression |
JEL(s): | C32, E37, E47 |
Programme Areas: | International Macroeconomics |
Link to this Page: | cepr.org/active/publications/discussion_papers/dp.php?dpno=7542 |
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 naïve random walk model. These results are also shown to hold over the most recent period in which it has been hard to forecast inflation.