Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/72706
Authors: 
Costantini, Mauro
Kunst, Robert M.
Year of Publication: 
2009
Series/Report no.: 
Reihe Ökonomie / Economics Series, Institut für Höhere Studien (IHS) 243
Abstract: 
We investigate whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non-zero weights to candidate models that add information not covered by other models. The potential benefits of this procedure are explored in extensive Monte Carlo simulations using realistic designs that are adapted to U.K. and to French macroeconomic data. The real economic growth rates of these two countries serve as the target series to be predicted. Generally, we find that the test-based averaging of forecasts yields a performance that is comparable to a simple uniform weighting of individual models. In one of our role-model economies, test-based averaging achieves some advantages in small samples. In larger samples, pure prediction models outperform forecast averages.
Subjects: 
combining forecasts
encompassing tests
model selection
time series
JEL: 
C22
C53
Document Type: 
Working Paper

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