Steady-state priors and Bayesian variable selection in VAR forecasting

Dimitrios Louzis

Studies in Nonlinear Dynamics & Econometrics, 2016, vol. 20, issue 5, 495-527

Abstract: This study proposes methods for estimating Bayesian vector autoregressions (VARs) with a (semi-) automatic variable selection and an informative prior on the unconditional mean or steady-state of the system. We show that extant Gibbs sampling methods for Bayesian variable selection can be efficiently extended to incorporate prior beliefs on the steady-state of the economy. Empirical analysis, based on three major US macroeconomic time series, indicates that the out-of-sample forecasting accuracy of a VAR model is considerably improved when it combines both variable selection and steady-state prior information.

Keywords: Bayesian VAR; macroeconomic forecasting; steadystates; variable selection (search for similar items in EconPapers)
Date: 2016
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Working Paper: Steady-state priors and Bayesian variable selection in VAR forecasting (2015)
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DOI: 10.1515/snde-2015-0048

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