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Forecasting with Bayesian multivariate vintage-based VARs
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DOI：10.1016/j.ijforecast.2014.05.007.png)
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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. (C) 2014 The Authors. Published by Elsevier B.V. on behalf of International Institute of Forecasters.
Keyword:
Bayesian VARs
Multiple-vintage models
Forecasting
Output growth
Inflation
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分享收藏AN INTEGRATED MODEL OF THE DATA MEASUREMENT AND DATA GENERATION PROCESSES WITH AN APPLICATION TO CONSUMERS EXPENDITURE.png)
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