Modeling data revisions: Measurement error and dynamics of "true" values

Jan P. A. M. Jacobs, Simon van Norden*

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

41 Citaten (Scopus)


Policy makers must base their decisions on preliminary and partially revised data of varying reliability. Realistic modeling of data revisions is required to guide decision makers in their assessment of current and future conditions. This paper provides a new framework with which to model data revisions.

Recent empirical work suggests that measurement errors typically have much more complex dynamics than existing models of data revisions allow. This paper describes a state-space model that allows for richer dynamics in these measurement errors, including the noise, news and spillover effects documented in this literature. We also show how to relax the common assumption that "true" values are observed after a few revisions.

The result is a unified and flexible framework that allows for more realistic data revision properties, and allows the use of standard methods for optimal real-time estimation of trends and cycles. We illustrate the application of this framework with real-time data on US real output growth. (C) 2011 Elsevier B.V. All rights reserved.

Originele taal-2English
Pagina's (van-tot)101-109
Aantal pagina's9
TijdschriftJournal of Econometrics
Nummer van het tijdschrift2
StatusPublished - apr.-2011

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