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Forecast combinations in a DSGE-VAR lab

Author

Listed:
  • Costantini, Mauro

    (Department of Economics and Finance, Brunel University)

  • Gunter, Ulrich

    (Department of Tourism and Service Management, MODUL University Vienna)

  • Kunst, Robert M.

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

Abstract

We explore the benefits of forecast combinations based on forecast-encompassing tests compared to simple averages and to Bates-Granger combinations. We also consider a new combination method that fuses test-based and Bates-Granger weighting. For a realistic simulation design, we generate multivariate time-series samples from a macroeconomic DSGE-VAR model. Results generally support Bates-Granger over uniform weighting, whereas benefits of test-based weights depend on the sample size and on the prediction horizon. In a corresponding application to real-world data, simple averaging performs best. Uniform averages may be the weighting scheme that is most robust to empirically observed irregularities.

Suggested Citation

  • Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2014. "Forecast combinations in a DSGE-VAR lab," Economics Series 309, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:309
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    Keywords

    Combining forecasts; encompassing tests; model selection; time series; DSGE-VAR model;

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