TY  - RPRT
        AU  - Assenmacher-Wesche, Katrin
AU  - Pesaran, M. Hashem
        TI  - Assessing Forecast Uncertainties in a VECX Model for Switzerland: An Exercise in Forecast Combination across Models and Observation Windows
        PY  - 2007/Sep/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 3071
        UR  - https://www.iza.org/publications/dp3071
        AB  - 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.
        KW  - choice of observation window
KW  - long-run structural vector autoregression
KW  - Bayesian model averaging
        ER  -