Estimating Time-Variation in Measurement Error from Data Revisions; an Application to Forecasting in Dynamic Models

Bank of England Working Paper No. 238

35 Pages Posted: 21 Feb 2005

See all articles by George Kapetanios

George Kapetanios

King's College, London

Anthony Yates

Bank of England - Monetary Analysis

Date Written: November 2004

Abstract

Over time, economic statistics are refined. This means that newer data are typically less well measured than old data. Time or vintage-variation in measurement error like this influences how forecasts should be made. Measurement error is obviously not directly observable. This paper shows that modelling the behaviour of the statistics agency generates an estimate of this time-variation. This provides an alternative to assuming that the final releases of variables are true. The paper applies the method to UK aggregate expenditure data, and demonstrates the gains in forecasting from exploiting these model-based estimates of measurement error.

Keywords: Data uncertainty, measurement error, revisions, real-time data, forecasting

JEL Classification: C32, C53

Suggested Citation

Kapetanios, George and Yates, Anthony, Estimating Time-Variation in Measurement Error from Data Revisions; an Application to Forecasting in Dynamic Models (November 2004). Bank of England Working Paper No. 238, Available at SSRN: https://ssrn.com/abstract=670157 or http://dx.doi.org/10.2139/ssrn.670157

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

Anthony Yates (Contact Author)

Bank of England - Monetary Analysis ( email )

Threadneedle Street
London EC2R 8AH
United Kingdom

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