Skip to main content
Article thumbnail
Location of Repository

Forecasting Substantial Data Revisions in the presence of model uncertainty

By Anthony Garratt, G. Koop and S.P. Vahey


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

Topics: ems
Publisher: Wiley-Blackwell
Year: 2008
OAI identifier:

Suggested articles


  1. (2001). A real-time data set for macroeconomists’, doi
  2. (1992). A simple nonparametric test of predictive performance’, doi
  3. (2003). A time series approach to revisions’,
  4. (2005). An evaluation of inflation forecasts from surveys using real-time data’, mimeo, doi
  5. (2001). Are parent findings of nonlinearity due to structural instability in economic time series?’, doi
  6. Are preliminary announcements of the money stock rational forecasts’, doi
  7. (2006). Are statistical reporting agencies getting it right? Data rationality and business cycle asymmetry’, doi
  8. (1998). Bayes factors and nonlinearity: evidence from economic time series’, doi
  9. (2003). Bayesian analysis of endogenous delay threshold models’, doi
  10. (2003). Bayesian Econometrics, doi
  11. (2001). Benchmark priors for Bayesian model averaging’, doi
  12. (2002). Building a real-time database for GDP(E)’,
  13. (2003). Computation and analysis of multiple structural change models’, doi
  14. (1991). Data revisions and the expenditure components of GDP’, doi
  15. (2005). Data revisions are not well behaved’, mimeo, doi
  16. (1999). Dynamic asymmetries in U.S. unemployment’, doi
  17. (2000). Economic and statistical measures of forecast accuracy’, doi
  18. (1978). Estimating the dimension of a model’, doi
  19. (1991). Forecasting output with the composite leading index: a real-time analysis’, doi
  20. (2006). Forecasting substantial data revisions in the presence of model uncertainty’, RBNZ Discussion Paper doi
  21. (2002). Has the business cycle changed and why?’, doi
  22. (2003). Have output growth rates stabilised? Evidence from the G-7 economies’, doi
  23. (1993). Improving macro-economic statistics’,
  24. (2002). Keep it real!’ A real-time UK macro data set’, doi
  25. (2005). News and noise in G7 doi
  26. (2005). Official Statistics: Perceptions and doi
  27. (2000). Output fluctuations in the United States: What has changed since the early 1980s?’, doi
  28. (2005). Publications of revision triangles on the National Statistics website’,
  29. (2001). Revisions analysis of initial estimates of annual constant price GDP and its components’,
  30. (2004). Revisions to Economic Statistics,
  31. (2003). Revisions to quarterly GDP growth and expenditure components’,
  32. (2005). Revisions to quarterly GDP growth and its production (output), expenditure and income components’,
  33. (2005). Revisions to quarterly GDP growth and its production and expenditure components,
  34. (2003). Revisions to quarterly GDP growth’,
  35. (1998). Statistics A Matter of Trust: A Consultation Document, The Stationery Office,
  36. (2003). The application of annual chain-linking to the Gross National Income System’,
  37. (2002). The prediction of business cycle phases: financial variables and international linkages’, doi
  38. (1992). The View From No. 11: Memoirs of a Tory Radical,

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.