Modeling Data Revisions
A dynamic linear model for data revisions and delays is proposed. This model extends Jacobs & Van Norden's  in two ways. First, the "true" data series is observable up to a fixed period of time M. And second, preliminary figures might be biased estimates of the true series. Otherwise, the model follows Jacobs & Van Norden's  so their gains are extended through the new assumptions. These assumptions represent the data release process more realistically under particular circumstances, and improve the overall identification of the model. An application to the year to year growth of the Colombian quarterly GDP reveals that preliminary growth reports under-estimate the true growth, and that measurement errors are predictable from the information available at the data release. The models implemented in this note help this purpose.
|Date of creation:||08 Feb 2011|
|Date of revision:|
|Contact details of provider:|| |
References listed on IDEAS
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.:
- Anthony Garratt & Shaun P Vahey, 2005.
"UK Real-Time Macro Data Characteristics,"
Birkbeck Working Papers in Economics and Finance
0502, Birkbeck, Department of Economics, Mathematics & Statistics.
- Aruoba, Boragan, 2005.
"Data Revisions Are Not Well-Behaved,"
CEPR Discussion Papers
5271, C.E.P.R. Discussion Papers.
- Bordignon, Silvano & Trivellato, Ugo, 1989. "The Optimal Use of Provisional Data in Forecasting with Dynamic Model s," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(2), pages 275-86, April.
- Fabio Busetti, 2006.
"Preliminary data and econometric forecasting: an application with the Bank of Italy Quarterly Model,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 25(1), pages 1-23.
- Busetti, Fabio, 2004. "Preliminary Data and Econometric Forecasting: An Application with the Bank of Italy Quarterly Model," CEPR Discussion Papers 4382, C.E.P.R. Discussion Papers.
- Pierre Siklos, 2006. "What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation: Some US Evidence," Working Papers eg0049, Wilfrid Laurier University, Department of Economics, revised 2006.
- Trivellato, Ugo & Rettore, Enrico, 1986. "Preliminary Data Errors and Their Impact on the Forecast Error of Simultaneous-Equations Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 445-53, October.
- Yates, Tony & Richard Harrison & George Kapetanios, 2003.
"Forecasting with measurement errors in dynamic models,"
Royal Economic Society Annual Conference 2003
225, Royal Economic Society.
- Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
- Richard Harrison & George Kapetanios & Tony Yates, 2004. "Forecasting with Measurement Errors in Dynamic Models," Working Papers 521, Queen Mary University of London, School of Economics and Finance.
- Richard Harrison & George Kapetanios & Tony Yates, 2004. "Forecasting with measurement errors in dynamic models," Bank of England working papers 237, Bank of England.
- Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
When requesting a correction, please mention this item's handle: RePEc:col:000094:007929. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Clorith Angélica Bahos Olivera)
If references are entirely missing, you can add them using this form.