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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Objekttyp
- Arbeitspapier
Beteiligte
- Kapetanios, George
- Yates, Anthony
- Queen Mary University of London, Department of Economics
Entstanden
- 2004