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Forecasting Substantial Data Revisions in the Presence of Model Uncertainty

  • Anthony Garratt

    (Department of Economics, Mathematics & Statistics, Birkbeck)

  • Gary Koop
  • Shaun 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 paper, 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 heteroskedasticity. Ignoring the nonlinearities and model uncertainty yields misleading predictives and obscures recent improvements in the quality of preliminary UK macroeconomic measurements.

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File URL: http://www.bbk.ac.uk/ems/research/wp/PDF/BWPEF0617.pdf
File Function: First version, 2006
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Paper provided by Birkbeck, Department of Economics, Mathematics & Statistics in its series Birkbeck Working Papers in Economics and Finance with number 0617.

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Date of creation: Dec 2006
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Handle: RePEc:bbk:bbkefp:0617
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