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Title:Estimating time-variation in measurement error from data revisions: An application to forecasting in dynamic models PDF Logo
Authors:Kapetanios, George
Yates, Anthony
Issue Date:2004
Series/Report no.:Working Paper, Department of Economics, Queen Mary, University of London 520
Abstract:Over time, economic statistics are refined. This means that newer data is typically less well measured than old data. Time variation in measurement error like this influences how forecasts should be made. We show how modelling the behaviour of the statistics agency generates both an estimate of this time variation and an estimate of the absolute amount of uncertainty in the data. We apply the method to UK aggregate expenditure data, and illustrate the gains in forecasting from exploiting our model estimates of measurement error.
Subjects:Forecasting, Data revisions
JEL:C32
C53
Document Type:Working Paper
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

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