Forecasting the Swiss Economy Using VECX* Models: An Exercise in Forecast Combination Across Modelsand Observation Windows

Katrin Assenmacher-Wesche () and M Hashem Pesaran ()

No 2008-3, Working Papers from Swiss National Bank

Abstract: This paper uses vector error correction models of Switzerland for forecasting output, inflation and the short-term interest rate. It considers three different ways of dealing with forecast uncertainties. First, it investigates the effect on forecasting performance of averaging over forecasts from different models. Second, it considers averaging forecasts from different estimation windows. It is found that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, it examines whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of alternative weighting schemes on forecast accuracy is small in the present application.

Keywords: Bayesian model averaging; choice of observation window; longrun structural vector autoregression (search for similar items in EconPapers)
JEL-codes: C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm and nep-for
Date: Written 2008-04-29
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