Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/72706 
Erscheinungsjahr: 
2009
Schriftenreihe/Nr.: 
Reihe Ökonomie / Economics Series No. 243
Verlag: 
Institute for Advanced Studies (IHS), Vienna
Zusammenfassung: 
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.
Schlagwörter: 
combining forecasts
encompassing tests
model selection
time series
JEL: 
C22
C53
Dokumentart: 
Working Paper

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