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.
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Paper provided by Sveriges Riksbank (Central Bank of Sweden) in its series Working Paper Series with number
138.
Length: 24 pages Date of creation: 01 Aug 2002 Date of revision: Publication status: Published in Journal of Forecasting, 2004, pages 479-496. Handle: RePEc:hhs:rbnkwp:0138
Find related papers by JEL classification: C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
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