Forecast combinations in a DSGE-VAR lab

Mauro Costantini, Ulrich Gunter, Robert Kunst

Publications: Working paper

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 macroe-
conomic 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. Uni-
form averages may be the weighting scheme that is most robust to
empirically observed irregularities.
Original languageEnglish
Number of pages57
Publication statusPublished - Dec 2014

Publication series

SeriesIHS economics series : working paper
Volume309

Austrian Fields of Science 2012

  • 502025 Econometrics

Keywords

  • combining forecasts, encompassing tests, model selection, time series, DSGE-VAR model

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