Combining forecasts based on multiple encompassing tests in a macroeconomic core system

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Reihe Ökonomie / Economics Series ; No. 243

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Forecasting Models; Simulation Methods
• Thema: combining forecasts ; encompassing tests ; model selection ; time series ; Prognoseverfahren ; Statistischer Test ; Modellierung ; Zeitreihenanalyse ; Monte-Carlo-Methode ; Schätzung ; Frankreich ; USA

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Costantini, Mauro ; Kunst, Robert M.
• Ereignis: Veröffentlichung
• (wer): Institute for Advanced Studies (IHS)
• (wo): Vienna
• (wann): 2009

Weitere Informationen

• Handle: http://hdl.handle.net/10419/72706
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ