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 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.
|Published on||12 January 2015|
|Authors||Professor Michael P. ClementsMichael P. Clements ICMA Centre Henley Business School|