Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision

Michael Clements

Journal of Business & Economic Statistics, 2017, vol. 35, issue 3, 420-433

Abstract: Model-based estimates of future uncertainty are generally based on the in-sample fit 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 U.S. output growth is used to investigate small-sample properties.

Date: 2017
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Working Paper: Assessing Macro Uncertainty In Real-Time When Data Are Subject To Revision (2015)
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DOI: 10.1080/07350015.2015.1081596

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