Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/12652
Title: | Forecast combinations in a DSGE-VAR lab |
Authors: | Costantini, M Gunter, U Kunst, R |
Keywords: | Forecasting;Combining forecasts;Encompassing tests;Model selection;Time series |
Issue Date: | 2016 |
Publisher: | Wiley |
Citation: | Journal of Forecasting, (2016) |
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 algorithm that fuses test-based and Bates–Granger weighting. For a realistic simulation design, we generate multivariate time series samples from a macroeconomic DSGE-VAR (dynamic stochastic general equilibrium–vector autoregressive) 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. |
URI: | http://onlinelibrary.wiley.com/doi/10.1002/for.2427/abstract http://bura.brunel.ac.uk/handle/2438/12652 |
DOI: | http://dx.doi.org/10.1002/for.2427 |
ISSN: | 1099-131X |
Appears in Collections: | Dept of Economics and Finance Research Papers |
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