Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/68523
Authors: 
Costantini, Mauro
Gunter, Ulrich
Kunst, Robert M.
Year of Publication: 
2012
Series/Report no.: 
Economics Series, Institute for Advanced Studies 292
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.
Subjects: 
combining forecasts
encompassing tests
model selection
time series
DGSE-VAR model
JEL: 
C15
C32
C53
Document Type: 
Working Paper

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