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No. 521: Forecasting with Measurement Errors in Dynamic Models

Richard Harrison , Bank of England
George Kapetanios , Queen Mary, University of London

October 1, 2004

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Abstract

In this paper we explore the consequences for forecasting of the following two facts: first, that over time statistical agencies revise and improve published data, so that observations on more recent events are those that are least well measured. Second, that economies are such that observations on the most recent events contain the the largest signal about the future. We discuss a variety of forecasting problems in this environment, and present an application using a univariate model of the quarterly growth of UK private consumption expenditure.

J.E.L classification codes: C32, C53

Keywords:Forecasting, Data revisions, Dynamic models

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