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.