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Forecasting with Measurement Errors in Dynamic Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Richard Harrison (Bank of England)
George Kapetanios () (Queen Mary, University of London)
Tony Yates (Bank of England)
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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.
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Paper provided by Queen Mary, University of London, Department of Economics in its series Working Papers with number
521.
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Date of creation: Oct 2004Date of revision:
Handle: RePEc:qmw:qmwecw:wp521Contact details of provider: Postal: London E1 4NS Phone: +44 (0) 20 7882 5096 Fax: +44 (0) 20 8983 3580 Web page: http://www.econ.qmul.ac.uk More information through EDIRC
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Keywords: Forecasting Data revisions Dynamic models Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
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Dean Croushore, 2008.
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