Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/82445 
Year of Publication: 
2002
Series/Report no.: 
Sveriges Riksbank Working Paper Series No. 138
Publisher: 
Sveriges Riksbank, Stockholm
Abstract: 
We consider a Bayesian Model Averaging approach for the purpose of forecasting Swedish consumer price index inflation using a large set of potential indicators, comprising some 80 quarterly time series covering a wide spectrum of Swedish economic activity. The paper demonstrates how to efficiently and systematically evaluate (almost) all possible models that these indicators in combination can give rise to. The results, in terms of out-of-sample-performance, suggest that Bayesian Model Averaging is a useful alternative to other forecasting procedures, in particular recognizing the flexibility by which new information can be incorporated.
Subjects: 
Variable selection
Markov chain Monte Carlo
Forecast
JEL: 
C11
C51
C52
C53
Document Type: 
Working Paper

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