Assessing Macro Uncertainty In Real- Time When Data Are Subject To Revision
Model-based estimates of future uncertainty are generally based on the in-sample ?t of the model, as when Box-Jenkins prediction intervals are calculated. However, this approach will generate biased uncertainty estimates in real time when there are data revisions. A simple remedy is suggested, and used to generate more accurate prediction intervals for 25 macroeconomic variables, in line with the theory. A simulation study based on an empirically-estimated model of data revisions for US output growth is used to investigate small-sample properties.
Keywords: in-sample uncertainty, out-of-sample uncertainty, real-time-vintage estimation
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Published on | 1st January 2015 |
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Authors | Professor Michael Clements |
Series Reference | ICM-2015-02 |