Arbeitspapier

Estimating time-variation in measurement error from data revisions: An application to forecasting in dynamic models

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.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 520

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
Thema
Forecasting, Data revisions
Prognoseverfahren
Zeitreihenanalyse
Statistische Erhebung
Statistischer Fehler

Ereignis
Geistige Schöpfung
(wer)
Kapetanios, George
Yates, Anthony
Ereignis
Veröffentlichung
(wer)
Queen Mary University of London, Department of Economics
(wo)
London
(wann)
2004

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Kapetanios, George
  • Yates, Anthony
  • Queen Mary University of London, Department of Economics

Entstanden

  • 2004

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