Preliminary data and econometric forecasting: an application with the Bank of Italy Quarterly Model
This paper discusses the use of preliminary data in econometric forecasting. The standard practice is to ignore the distinction between preliminary and final data, the forecasts that do so here being termed naïve forecasts. It is shown that in dynamic models a multistep-ahead naïve forecast can achieve a lower mean square error than a single-step-ahead one, as it is less affected by the measurement noise embedded in the preliminary observations. The minimum mean square error forecasts are obtained by optimally combining the information provided by the model and the new information contained in the preliminary data, which can be done within the state space framework as suggested in numerous papers. Here two simple, in general suboptimal, methods of combining the two sources of information are considered: modifying the forecast initial conditions by means of standard regressions and using intercept corrections. The issues are explored using Italian national accounts data and the Bank of Italy Quarterly Econometric Model. Copyright © 2006 John Wiley & Sons, Ltd.
Volume (Year): 25 (2006)
Issue (Month): 1 ()
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- Patterson, K. D., 1995. "Forecasting the final vintage of real personal disposable income: A state space approach," International Journal of Forecasting, Elsevier, vol. 11(3), pages 395-405, September.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Koopman, Siem Jan & Harvey, Andrew, 2003. "Computing observation weights for signal extraction and filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 27(7), pages 1317-1333, May.
- A. C. Harvey & Siem Jan Koopman, 2000. "Computing Observation Weights for Signal Extraction and Filtering," Econometric Society World Congress 2000 Contributed Papers 0888, Econometric 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.
- Yates, Tony & Richard Harrison & George Kapetanios, 2003. "Forecasting with measurement errors in dynamic models," Royal Economic Society Annual Conference 2003 225, Royal Economic Society.
- Richard Harrison & George Kapetanios & Tony Yates, 2004. "Forecasting with measurement errors in dynamic models," Bank of England working papers 237, Bank of England.
- 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.
- Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
- Jon Faust & John H. Rogers & Jonathan H. Wright, 2000. "News and noise in G-7 GDP announcements," International Finance Discussion Papers 690, Board of Governors of the Federal Reserve System (U.S.).
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
- 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 445-453, October.
- N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
- Howrey, E Philip, 1978. "The Use of Preliminary Data in Econometric Forecasting," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 193-200, May.
- Rosanne Cole, 1969. "Introduction to "Errors in Provisional Estimates of Gross National Product"," NBER Chapters,in: Errors in Provisional Estimates of Gross National Product, pages 3-6 National Bureau of Economic Research, Inc.
- 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 275-286, April.
- Rosanne Cole, 1969. "Errors in Provisional Estimates of Gross National Product," NBER Books, National Bureau of Economic Research, Inc, number cole69-1, Enero-Jun.
- Howrey, E Philip, 1984. "Data Revision, Reconstruction, and Prediction: An Application to Inventory Investment," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 386-393, August.
- Patterson, K. D., 2000. "Which vintage of data to use when there are multiple vintages of data?: Cointegration, weak exogeneity and common factors," Economics Letters, Elsevier, vol. 69(2), pages 115-121, November. Full references (including those not matched with items on IDEAS)