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Implications of real-time data for forecasting and modeling expectations

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  • Sharon Kozicki

Abstract

This note extends the analysis in Stark and Croushore (2001) with an emphasis on the importance of data vintage for survey forecasts and modeling expectations. For both of these types of empirical exercises, results suggest that the choice of latest available or real-time data is critical for variables subject to large level revisions, but almost irrelevant for variables subject to only small revisions. Other forecasting practices were examined, with some surprising results.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 01-12.

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Date of creation: 2001
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Handle: RePEc:fip:fedkrw:rwp01-12

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Keywords: Forecasting ; Real-time data;

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  1. Kozicki, Sharon & Tinsley, P A, 1998. "Moving Endpoints and the Internal Consistency of Agents' Ex Ante Forecasts," Computational Economics, Society for Computational Economics, vol. 11(1-2), pages 21-40, April.
  2. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
  3. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  4. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
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Cited by:
  1. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.

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