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Does data vintage matter for forecasting?

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Author Info
Dean Croushore
Tom Stark

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Abstract

This paper illustrates the use of a real-time data set for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, and shows how forecasts can be affected by data revisions.

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Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 99-15.

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Date of creation: 1999
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Handle: RePEc:fip:fedpwp:99-15

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Related research
Keywords: Forecasting;

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This paper has been announced in the following NEP Reports: 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. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis. [Downloadable!]
    Other versions:
  2. 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.).
  3. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, 07. [Downloadable!] (restricted)
    Other versions:
  4. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, 04. [Downloadable!] (restricted)
    Other versions:
  5. Rudebusch, Glenn D, 1998. "Do Measures of Monetary Policy in a VAR Make Sense?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 907-31, November.
    Other versions:
  6. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, issue Q 4, pages 4-20. [Downloadable!]
  7. Tom Stark, 1998. "A Bayesian vector error corrections model of the U.S. economy," Working Papers 98-12, Federal Reserve Bank of Philadelphia. [Downloadable!]
  8. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-35, September. [Downloadable!] (restricted)
  9. Evan F. Koenig & Sheila Dolmas, 1997. "Real-time GDP Growth Forecasts," Working Papers 97-10, Federal Reserve Bank of Dallas. [Downloadable!]
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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. Hui Feng, 2005. "Real-Time or Current Vintage: Does the Type of Data Matter for Forecasting and Model Selection?," Econometrics Working Papers 0515, Department of Economics, University of Victoria. [Downloadable!]
  2. 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!]
  3. C. Alan Garner, 2002. "Consumer confidence after September 11," Economic Review, Federal Reserve Bank of Kansas City, issue Q II. [Downloadable!]
  4. Dean Croushore & Tom Stark, 1999. "A real-time data set for marcoeconomists: does the data vintage matter?," Working Papers 99-21, Federal Reserve Bank of Philadelphia. [Downloadable!]
    Other versions:
  5. repec:bep:maccon:v:3:y:2003:i:1:p:1073-1073 is not listed on IDEAS
  6. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia. [Downloadable!]
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