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|
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- Richard Harrison & George Kapetanios & Tony Yates, 2004.
"Forecasting with measurement errors in dynamic models,"
Bank of England working papers
237, Bank of England.
- 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.
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- 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.
- S. Boragan Aruoba, 2008.
"Data Revisions Are Not Well Behaved,"
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Blackwell Publishing, vol. 40(2-3), pages 319-340, 03.
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Computing in Economics and Finance 2005
253, Society for Computational Economics.
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- Busetti, Fabio, 2004.
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CEPR Discussion Papers
4382, C.E.P.R. Discussion Papers.
- 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.
- 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.
- 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.
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