Forecasting the Swiss economy using VECX models: An exercise in forecast combination across models and observation windows

Katrin Assenmacher and Mohammad Pesaran

National Institute Economic Review, 2008, vol. 203, issue 1, 91-108

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; long-run structural vector autoregression (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (27)

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Related works:
Journal Article: Forecasting the Swiss economy using VECX models: An exercise in forecast combination across models and observation windows (2008)
Working Paper: Forecasting the Swiss Economy Using VECX* Models: An Exercise in Forecast Combination Across Models and Observation Windows (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:sae:niesru:v:203:y:2008:i:1:p:91-108

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