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Copycats and Common Swings: The Impact of the Use of Forecasts in Information Sets

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  • Giampiero M. Gallo

    (International Monetary Fund)

  • Clive W.J. Granger

    (International Monetary Fund)

  • Yongil Jeon

    (International Monetary Fund)

Abstract

This paper presents evidence, using data from Consensus Forecasts, that there is an "attraction" to conform to the mean forecasts; in other words, views expressed by other forecasters in the previous period influence individuals' current forecast. The paper then discusses--and provides further evidence on--two important implications of this finding. The first is that the forecasting performance of these groups may be severely affected by the detected imitation behavior and lead to convergence to a value that is not the "right" target. Second, since the forecasts are not independent, the common practice of using the standard deviation from the forecasts' distribution, as if they were standard errors of the estimated mean, is not warranted. Copyright 2002, International Monetary Fund

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Bibliographic Info

Article provided by Palgrave Macmillan in its journal IMF Staff Papers.

Volume (Year): 49 (2002)
Issue (Month): 1 ()
Pages: 2

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Handle: RePEc:pal:imfstp:v:49:y:2002:i:1:p:2

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  1. John R. Graham, 1999. "Herding among Investment Newsletters: Theory and Evidence," Journal of Finance, American Finance Association, vol. 54(1), pages 237-268, 02.
  2. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
  3. 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.
  4. David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 3-12.
  5. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
  6. Mills, Terence C. & Pepper, Gordon T., 1999. "Assessing the forecasters: an analysis of the forecasting records of the Treasury, the London Business School and the National Institute," International Journal of Forecasting, Elsevier, vol. 15(3), pages 247-257, July.
  7. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias In Macroeconomic Forecasts," The Quarterly Journal of Economics, MIT Press, vol. 114(1), pages 293-318, February.
  8. Victor Zarnowitz & Louis A. Lambros, 1987. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.
  9. Batchelor, Roy & Dua, Pami, 1998. "Improving macro-economic forecasts: The role of consumer confidence," International Journal of Forecasting, Elsevier, vol. 14(1), pages 71-81, March.
  10. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-73, Sept.-Oct.
  11. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
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