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

Michael Clements

ICMA Centre Discussion Papers in Finance from Henley Business School, University of Reading

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 US output growth is used to investigate small-sample properties.

Keywords: in-sample uncertainty; out-of-sample uncertainty; real-time-vintage estimation (search for similar items in EconPapers)
JEL-codes: C53 (search for similar items in EconPapers)
Date: 2015-01
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Journal Article: Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:rdg:icmadp:icma-dp2015-02

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