Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System
Abstract: We study the benefits of forecast combinations based on forecast-encompassing tests relative to uniformly weighted forecast averages across rival models. For a realistic simulation design, we generate multivariate time-series samples of size 40 to 200 from a macroeconomic DSGE-VAR model. C...| Link(s) zu Dokument(en): | IHS Publikation |
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| Hauptverfasser: | , , |
| Format: | IHS Series NonPeerReviewed |
| Sprache: | Englisch |
| Veröffentlicht: |
Institut für Höhere Studien
2012
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| Zusammenfassung: | Abstract: We study the benefits of forecast combinations based on forecast-encompassing tests relative to uniformly weighted forecast averages across rival models. For a realistic simulation design, we generate multivariate time-series samples of size 40 to 200 from a macroeconomic DSGE-VAR model. Constituent forecasts of the combinations are formed from four linear autoregressive specifications, one of them a more sophisticated factor-augmented vector autoregression (FAVAR). The forecaster is assumed not to know the true data-generating model. Results depend on the prediction horizon. While one-step prediction fails to support test-based combinations at all sample sizes, the test-based procedure clearly dominates at prediction horizons greater than two.; |
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