Assessing Forecast Uncertainties in a VECX Model for Switzerland: An Exercise in Forecast Combination Across Models and Observation Windows

58 Pages Posted: 16 Oct 2007

See all articles by Katrin Assenmacher

Katrin Assenmacher

Swiss National Bank

M. Hashem Pesaran

University of Southern California - Department of Economics

Date Written: October 2007

Abstract

We investigate the effect of forecast uncertainty in a cointegrating vector error correction model for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of averaging over forecasts from different models. Second, we look at different estimation windows. We find that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, we explore whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of the weighting scheme on forecast accuracy is small in our application.

Keywords: Bayesian model averaging, choice of observation window, long-run structural vector autoregression

JEL Classification: C53, C32

Suggested Citation

Assenmacher, Katrin and Pesaran, M. Hashem, Assessing Forecast Uncertainties in a VECX Model for Switzerland: An Exercise in Forecast Combination Across Models and Observation Windows (October 2007). CESifo Working Paper Series No. 2116, IZA Discussion Paper No. 3071, Available at SSRN: https://ssrn.com/abstract=1021953

Katrin Assenmacher

Swiss National Bank ( email )

Borsenstrasse 15
CH-8022 Zurich
Switzerland

M. Hashem Pesaran (Contact Author)

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

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