Forecast combinations in a DSGE-VAR lab

Mauro Costantini, Ulrich Gunter and Robert Kunst (robert.kunst@univie.ac.at)
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Ulrich Gunter: Department of Tourism and Service Management, MODUL University Vienna

No 309, Economics Series from Institute for Advanced Studies

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.

Keywords: Combining forecasts; encompassing tests; model selection; time series; DSGE-VAR model (search for similar items in EconPapers)
Pages: 57 pages
Date: 2014-12
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-for
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https://irihs.ihs.ac.at/id/eprint/2911 First version, 2014 (application/pdf)

Related works:
Journal Article: Forecast Combinations in a DSGE‐VAR Lab (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:ihs:ihsesp:309

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