Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/126238
Authors: 
Siliverstovs, Boriss
Year of Publication: 
2015
Series/Report no.: 
KOF Working Papers, KOF Swiss Economic Institute, ETH Zurich 397
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.
Subjects: 
Forecasting
Forecast Evaluation
Change Point Detection
Bayesian Estimation
JEL: 
C22
C53
Document Type: 
Working Paper

Files in This Item:
File
Size
138.13 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.