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Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System

  • Costantini, Mauro

    (Department of Economics and Finance, Brunel University London, United Kingdom)

  • Gunter, Ulrich

    (Austrian National Bank, Vienna, Austria)

  • Kunst, Robert M.

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria and Department of Economics, University of Vienna, Austria)

We study the benefits of forecast combinations based on forecast-encompassing tests relative to uniformly weighted forecast averages across rival models. For a realistic simulation design, we generate multivariate time-series samples of size 40 to 200 from a macroeconomic DSGE-VAR model. Constituent forecasts of the combinations are formed from four linear autoregressive specifications, one of them a more sophisticated factor-augmented vector autoregression (FAVAR). The forecaster is assumed not to know the true data-generating model. Results depend on the prediction horizon. While one-step prediction fails to support test-based combinations at all sample sizes, the test-based procedure clearly dominates at prediction horizons greater than two.

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Paper provided by Institute for Advanced Studies in its series Economics Series with number 292.

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Length: 39 pages
Date of creation: Oct 2012
Date of revision:
Handle: RePEc:ihs:ihsesp:292
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