Garratt, Anthony, Koop, Gary and Vahey, Shaun P. (2008) Forecasting substantial data revisions in the presence of model uncertainty. The Economic Journal, Volume 118 (Number 530). pp. 1128-1144. doi:10.1111/j.1468-0297.2008.02163.x ISSN 0013-0133.

Research output not available from this repository.

Request-a-Copy directly from author or use local Library Get it For Me service.

Request Changes to record.

Abstract

A recent revision to the preliminary measurement of GDP(E) growth for 2003Q2 caused considerable press attention, provoked a public enquiry and prompted a number of reforms to UK statistical reporting procedures. In this article, we compute the probability of ‘substantial revisions’ that are greater (in absolute value) than the controversial 2003 revision. The predictive densities are derived from Bayesian model averaging over a wide set of forecasting models including linear, structural break and regime-switching models with and without heteroscedasticity. Ignoring the nonlinearities and model uncertainty yields misleading predictives and obscures recent improvements in the quality of preliminary UK macroeconomic measurements.

Item Type:	Journal Article
Divisions:	Faculty of Social Sciences > Warwick Business School > Global Energy Faculty of Social Sciences > Warwick Business School
Journal or Publication Title:	The Economic Journal
Publisher:	Wiley-Blackwell Publishing Ltd.
ISSN:	0013-0133
Official Date:	July 2008
Dates:	Date Event July 2008 Published 28 June 2008 Available 8 December 2008 Accepted 7 February 2006 Submitted
Volume:	Volume 118
Number:	Number 530
Number of Pages:	16
Page Range:	pp. 1128-1144
DOI:	10.1111/j.1468-0297.2008.02163.x
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item