Combining Forecasts Based on Multiple Encompassing Tests in a Macroeconomic Core System

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-zeroweights to candidate models that add information no...

Ausführliche Beschreibung

Bibliographische Detailangaben
Link(s) zu Dokument(en):IHS Publikation
Hauptverfasser: Costantini, Mauro, Kunst, Robert M.
Format: IHS Series NonPeerReviewed
Sprache:Englisch
Veröffentlicht: Institut für Höhere Studien 2009
Beschreibung
Zusammenfassung: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-zeroweights 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.;