The use and abuse of 'real-time' data in economic forecasting
AbstractWe distinguish between three different ways of using real-time data to estimate forecasting equations and argue that the most popular approach should generally be avoided. The point is illustrated with a model that uses monthly industrial production, employment, and retail sales data to predict real GDP growth. When the model is estimated using our preferred method, its out-of-sample forecasting performance is superior to that obtained using conventional estimation and compares favorably with that of the Blue-Chip consensus.
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Bibliographic InfoPaper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2001-015.
Date of creation: 2002
Date of revision:
Publication status: Published in Review of Economics and Statistics, August 2003, 85(3), pp. 618-28
Other versions of this item:
- 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.
- Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," Working Papers 0004, Federal Reserve Bank of Dallas.
- 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.).
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