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Finding good predictors for inflation: a Bayesian model averaging approach

Author

Listed:
  • Sune Karlsson

    (Stockholm School of Economics, Sweden)

  • Tor Jacobson

    (Sveriges Riksbank, Stockholm, Sweden)

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. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Sune Karlsson & Tor Jacobson, 2004. "Finding good predictors for inflation: a Bayesian model averaging approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 479-496.
    • Handle: RePEc:jof:jforec:v:23:y:2004:i:7:p:479-496
    DOI: 10.1002/for.924
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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