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Evaluating Wall Street Journal survey forecasters: a multivariate approach

Author

Listed:
  • Robert A. Eisenbeis
  • Daniel F. Waggoner
  • Tao Zha

Abstract

This paper proposes a methodology for assessing the joint performance of multivariate forecasts of economic variables. The methodology is illustrated by comparing the rankings of forecasters by the Wall Street Journal with the authors’ alternative rankings. The results show that the methodology can provide useful insights as to the certainty of forecasts as well as the extent to which various forecasts are similar or different.

Suggested Citation

  • Robert A. Eisenbeis & Daniel F. Waggoner & Tao Zha, 2002. "Evaluating Wall Street Journal survey forecasters: a multivariate approach," FRB Atlanta Working Paper 2002-8, Federal Reserve Bank of Atlanta.
  • Handle: RePEc:fip:fedawp:2002-8
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    File URL: http://www.frbatlanta.org/filelegacydocs/wp0208a.pdf
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    References listed on IDEAS

    as
    1. Kahn, Charles M. & Roberds, William, 2001. "Real-time gross settlement and the costs of immediacy," Journal of Monetary Economics, Elsevier, vol. 47(2), pages 299-319, April.
    2. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, pages 4-18.
    3. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, pages 639-651.
    Full references (including those not matched with items on IDEAS)

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    Keywords

    Forecasting;

    Statistics

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