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Bayesian Model Averaging under Regime Switching with Application to Cyclical Macro Variable Forecasting

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  • Jianmin Shi

Abstract

Model uncertainty and recurrent or cyclical structural changes in macroeconomic time series dynamics are substantial challenges to macroeconomic forecasting. This paper discusses a macro variable forecasting methodology that combines model uncertainty and regime switching simultaneously. The proposed predictive regression specification permits both regime switching of the regression parameters and uncertainty about the inclusion of forecasting variables by employing Bayesian model averaging. In an empirical exercise involving quarterly US inflation, we observed that our Bayesian model averaging with regime switching leads to substantial improvements in forecast performance, particularly in the medium horizon (two to four quarters). Copyright © 2015 John Wiley & Sons, Ltd.

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  • Jianmin Shi, 2016. "Bayesian Model Averaging under Regime Switching with Application to Cyclical Macro Variable Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(3), pages 250-262, April.
    • Handle: RePEc:wly:jforec:v:35:y:2016:i:3:p:250-262
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    Cited by:

    1. Sajad Rahimian, 2021. "The Determinants of Democracy Revisited: An Instrumental Variable Bayesian Model Averaging Approach," Papers 2103.04255, arXiv.org.
    2. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.

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