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The Use and Abuse of Real-Time Data in Economic Forecasting

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Listed:
  • Evan F. Koenig

    (Federal Reserve Bank of Dallas)

  • Sheila Dolmas
  • Jeremy Piger

    (Federal Reserve Bank of St. Louis)

Abstract

We distinguish between three different strategies for estimating forecasting equations with real-time data and argue that the most popular approach should generally be avoided. The point is illustrated with a model that uses current-quarter monthly industrial production, employment, and retail sales data to predict real GDP growth. When the model is estimated using either of our two alternative methods, its out-of-sample forecasting performance is superior to that obtained using conventional estimation and compares favorably with that of the Blue Chip consensus. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • 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, August.
    • Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:618-628
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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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