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The use and abuse of "real-time" data in economic forecasting

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  • Evan F. Koenig
  • Sheila Dolmas
  • Jeremy Piger

Abstract

We distinguish between three different ways of using real-time data to estimate forecasting equations and argue that the most frequently used approach should generally be avoided. The point is illustrated with a model that uses monthly observations of industrial production, employment, and retail sales to predict real GDP growth. When the model is estimated using our preferred method, its out-of-sample forecasting performance is clearly superior to that obtained using conventional estimation, and compares favorably with that of the Blue-Chip consensus.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Dallas in its series Working Papers with number 0004.

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Date of creation: 2000
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Handle: RePEc:fip:feddwp:00-04

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Keywords: Gross domestic product;

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  1. Swanson Norman, 1996. "Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-20, April.
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  17. Preston J. Miller & Daniel M. Chin, 1996. "Using monthly data to improve quarterly model forecasts," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Spr, pages 16-33.
  18. Terry J. Fitzgerald & Preston J. Miller, 1989. "A simple way to estimate current-quarter GNP," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 27-31.
  19. Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, pages 3-11.
  20. Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 671-90, August.
  21. Evan F. Koenig, 1996. "Capacity utilization as a real-time predictor of manufacturing output," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q III, pages 16-23.
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