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Forecasting with Bayesian multivariate vintage-based VARs

Andrea Carriero (), Michael Clements and Ana Galvão ()

International Journal of Forecasting, 2015, vol. 31, issue 3, 757-768

Abstract: We consider the forecasting of macroeconomic variables that are subject to revisions, using Bayesian vintage-based vector autoregressions. The prior incorporates the belief that, after the first few data releases, subsequent ones are likely to consist of revisions that are largely unpredictable. The Bayesian approach allows the joint modelling of the data revisions of more than one variable, while keeping the concomitant increase in parameter estimation uncertainty manageable. Our model provides markedly more accurate forecasts of post-revision values of inflation than do other models in the literature.

Keywords: Bayesian VARs; Multiple-vintage models; Forecasting; Output growth; Inflation (search for similar items in EconPapers)
Date: 2015
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