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Macroeconomic Forecasting and Structural Change

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  • D Agostino, Antonello
  • Gambetti, Luca
  • Giannone, Domenico

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 Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7542.

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Date of creation: Nov 2009
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Handle: RePEc:cpr:ceprdp:7542

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Keywords: Forecasting; Inflation; Stochastic Volatility; Time Varying Vector Autoregression;

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