Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62842 
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dc.contributor.authorKapetanios, Georgeen
dc.contributor.authorYates, Anthonyen
dc.date.accessioned2012-09-20T12:59:43Z-
dc.date.available2012-09-20T12:59:43Z-
dc.date.issued2004-
dc.identifier.urihttp://hdl.handle.net/10419/62842-
dc.description.abstractOver 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.en
dc.language.isoengen
dc.publisher|aQueen Mary University of London, Department of Economics |cLondonen
dc.relation.ispartofseries|aWorking Paper |x520en
dc.subject.jelC32en
dc.subject.jelC53en
dc.subject.ddc330en
dc.subject.keywordForecasting, Data revisionsen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwZeitreihenanalyseen
dc.subject.stwStatistische Erhebungen
dc.subject.stwStatistischer Fehleren
dc.titleEstimating time-variation in measurement error from data revisions: An application to forecasting in dynamic models-
dc.typeWorking Paperen
dc.identifier.ppn471225800en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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