Assessing macro uncertainty in real-time when data are subject to revision
Clements, M. P.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1080/07350015.2015.1081596 Abstract/SummaryModel-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.
Download Statistics DownloadsDownloads per month over past year Altmetric Deposit Details University Staff: Request a correction | Centaur Editors: Update this record |