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Title: Macroeconomic Forecasting and Structural Change

Author(s): Antonello D'Agostino, Luca Gambetti and Domenico Giannone

Publication Date: November 2009

Keyword(s): Forecasting, Inflation, Stochastic Volatility and Time Varying Vector Autoregression

Programme Area(s): International Macroeconomics

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 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.

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Bibliographic Reference

D'Agostino, A, Gambetti, L and Giannone, D. 2009. 'Macroeconomic Forecasting and Structural Change'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=7542