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Macroeconomic Forecasting and Structural Change

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  • D'Agostino, Antonello

    (Central Bank and Financial Services Authority of Ireland)

  • Gambetti, Luca

    (Universitat Autonoma de Barcelona)

  • Giannone, Domenico

    (ECARES, Université Libre de Bruxelles)

  • 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 TVVAR outperforms, in terms of mean square forecast error, all the competing models: fixed coefficients VARs, Time-Varying ARs and the na¨ýve 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 Central Bank of Ireland in its series Research Technical Papers with number 8/RT/09.

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Length: 29 pages
Date of creation: Oct 2009
Date of revision:
Handle: RePEc:cbi:wpaper:8/rt/09

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  17. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
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