Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/72708
Authors: 
Costantini, Mauro
Pappalardo, Carmine
Year of Publication: 
2008
Series/Report no.: 
Reihe Ökonomie / Economics Series, Institut für Höhere Studien (IHS) 228
Abstract: 
This paper proposes a strategy to increase the efficiency of forecast combining methods. Given the availability of a wide range of forecasting models for the same variable of interest, our goal is to apply combining methods to a restricted set of models. To this aim, an algorithm procedure based on a widely used encompassing test (Harvey, Leybourne, Newbold, 1998) is developed. First, forecasting models are ranked according to a measure of predictive accuracy (RMSFE) and, in a consecutive step, each prediction is chosen for combining only if it is not encompassed by the competing models. To assess the robustness of this procedure, an empirical application to Italian monthly industrial production using ISAE short-term forecasting models is provided.
Subjects: 
combining forecasts
econometric models
evaluating forecasts
models selection
time series
JEL: 
C32
C53
Document Type: 
Working Paper

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