Forecasting Substantial Data Revisions in the Presence of Model Uncertainty

Anthony Garratt (), Gary Koop and Shaun Vahey

No DP2006/02, Reserve Bank of New Zealand Discussion Paper Series from Reserve Bank of New Zealand

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 paper, we compute the probability of "substantial revisions" that are greater (in absolute value) than the controversial 2003 revision. The pre-dictive 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 the improvement in the quality of preliminary UK macroeconomic measurements relative to the early 1990s.

JEL-codes: C11 C32 C53 E01 (search for similar items in EconPapers)
Pages: 31 p.
Date: 2006-02
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Related works:
Journal Article: Forecasting Substantial Data Revisions in the Presence of Model Uncertainty (2008)
Journal Article: Forecasting Substantial Data Revisions in the Presence of Model Uncertainty (2008)
Working Paper: Forecasting Substantial Data Revisions in the Presence of Model Uncertainty (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:nzb:nzbdps:2006/02

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