Forecast combinations in a DSGE-VAR lab
- Author(s)
- Mauro Costantini, Ulrich Gunter, Robert Kunst
- 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.- Organisation(s)
- Department of Economics
- External organisation(s)
- Brunel University London, MODUL University Vienna
- No. of pages
- 57
- Publication date
- 12-2014
- Austrian Fields of Science 2012
- 502025 Econometrics
- Keywords
- ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/forecast-combinations-in-a-dsgevar-lab(060c0ef0-39f3-4bc0-928f-f6293dcc6c48).html