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Author
Date
2015-11Type
- Working Paper
ETH Bibliography
yes
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Abstract
In this paper we suggest an approach to comparison of models? forecasting performance in unstable environments. Our approach is based on combination of the Cumulated Sum of Squared Forecast Error Differential (CSSFED) suggested earlier in Welch and Goyal (2008) and the Bayesian change point analysis based on Barry and Hartigan (1993). The latter methodology provides the formal statistical analysis of the CSSFED time series which turned out to be a powerful graphical tool for tracking how the relative forecasting performance of competing models evolves over time. We illustrate the suggested approach by using forecasts of the GDP growth rate in Switzerland. Show more
Permanent link
https://doi.org/10.3929/ethz-a-010692101Publication status
publishedJournal / series
KOF Working PapersVolume
Publisher
KOF Swiss Economic Institute, ETH ZurichSubject
ECONOMETRICS AND ECONOMETRIC MODELS (OPERATIONS RESEARCH); FORECASTING BASED ON STATISTICS (MATHEMATICAL STATISTICS); ÖKONOMETRIE UND ÖKONOMETRISCHE MODELLE (OPERATIONS RESEARCH); PROGNOSEN AUF STATISTISCHER BASIS (MATHEMATISCHE STATISTIK); Change Point Detection; Forecasting; Bayesian Estimation; Forecast EvaluationOrganisational unit
02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute
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ETH Bibliography
yes
Altmetrics