Steady-state priors and Bayesian variable selection in VAR forecasting
2016 ◽
Vol 20
(5)
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Keyword(s):
AbstractThis 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.
2019 ◽
Keyword(s):
2010 ◽
Vol 54
(12)
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pp. 3289-3299
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2011 ◽
pp. 237-260