Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models

George Kapetanios and Anthony Yates ()

Bank of England working papers from Bank of England

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.

Date: 2004-11
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (8)

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Working Paper: Estimating Time-Variation in Measurement Error from Data Revisions: An Application to Forecasting in Dynamic Models (2004)
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