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Data vintages and measuring forecast model performance

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Author Info
John C. Robertson
Ellis W. Tallman

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Abstract

The data on economic variables are usually estimates, and these estimates may be revised many times after their initial publication. Most historical forecast evaluation exercises use the "latest available" or most recently revised vintage of historical data when constructing the forecasts-that is, they use estimates that may well have been unavailable to a forecaster in real time. Evaluations using such data could thus give a misleading picture of the forecast performance that can be expected in real-time situations. This fact is particularly relevant if a forecasting model's performance is to be compared with that of published real-time forecasts. One practical question is whether actually using the data set available to a forecaster in real time would lead to inferences that are substantially different from those made using the latest available vintage of data. A related question is whether it matters which vintage of data the forecasts are evaluated against. ; The authors argue that the choice of data vintage can have both a quantitative and a qualitative influence on forecast and model comparisons, at least over short horizons. This influence is illustrated by examining the performance of the composite index of leading indicators as a forecaster of alternative measures of real output. However, more research is required in order to determine whether the results generalize to forecasts of other series that are subject to revision, such as the various money aggregate measures.

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Publisher Info
Article provided by Federal Reserve Bank of Atlanta in its journal Economic Review.

Volume (Year): (1998)
Issue (Month): Q 4 ()
Pages: 4-20
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:fip:fedaer:y:1998:i:q4:p:4-20:n:v.83no.4

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Keywords: Econometric models ; Economic indicators ; Forecasting;

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.:

  1. Norman Swanson, 1996. "Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 1(1). [Downloadable!]
  2. Stephen K. McNees, 1988. "How accurate are macroeconomic forecasts?," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 15-36.
  3. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
  4. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November. [Downloadable!] (restricted)
    Other versions:
  5. Swanson, N.R., 1996. "Forecasting Using First Available Versus Fully Revised Economic Time Series data," Papers 4-96-7, Pennsylvania State - Department of Economics.
  6. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January. [Downloadable!] (restricted)
    Other versions:
  7. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  8. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June. [Downloadable!] (restricted)
  9. Makridakis, Spyros & Chatfield, Chris & Hibon, Michele & Lawrence, Michael & Mills, Terence & Ord, Keith & Simmons, LeRoy F., 1993. "The M2-competition: A real-time judgmentally based forecasting study," International Journal of Forecasting, Elsevier, vol. 9(1), pages 5-22, April. [Downloadable!] (restricted)
  10. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, 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.)

  1. Jean-Philippe Cayen & Simon van Norden, 2002. "La fiabilité des estimations de l'écart de production au Canada," Working Papers 02-10, Bank of Canada. [Downloadable!]
  2. Carlos Barrera-Chaupis, 2005. "Proyecciones desagregadas de la variación del índice de precios al consumidor (IPC), del índice de precios al por Mayor (IPM) y del Crecimiento del Producto Real (PBI)," Working Papers 2005-006, Banco Central de Reserva del Perú. [Downloadable!]
  3. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia. [Downloadable!]
  4. John C. Robertson & Ellis W. Tallman, 1999. "Improving forecasts of the federal funds rate in a policy model," Working Paper 99-3, Federal Reserve Bank of Atlanta. [Downloadable!]
  5. Scott Schuh, 2001. "An evaluation of recent macroeconomic forecast errors," New England Economic Review, Federal Reserve Bank of Boston, pages 35-56. [Downloadable!]
  6. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City. [Downloadable!]
    Other versions:
  7. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," International Finance Discussion Papers 684, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  8. Dean Croushore & Tom Stark, 1999. "Does data vintage matter for forecasting?," Working Papers 99-15, Federal Reserve Bank of Philadelphia. [Downloadable!]
  9. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia. [Downloadable!]
    Other versions:
  10. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia. [Downloadable!]
    Other versions:
  11. 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.). [Downloadable!]
    Other versions:
  12. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18. [Downloadable!]
  13. Clements, Michael P & Galvão, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation," The Warwick Economics Research Paper Series (TWERPS) 773, University of Warwick, Department of Economics. [Downloadable!]
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