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Testing bias in professional forecasts

Author

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  • Philip Hans Franses

Abstract

Professional forecasters can rely on econometric models, on their personal expertise or on both. To accommodate for adjustments to model forecasts, this paper proposes to use two stage least squares (TSLS) (and not ordinary least squares [OLS]) for the familiar Mincer–Zarnowitz regression when examining bias in professional forecasts, where the instrumental variable is the consensus forecast. An illustration for 15 professional forecasters with their quotes for real gross domestic product (GDP) growth, inflation and unemployment for the United States documents the usefulness of this new estimation method. It also shows that TSLS suggests less bias than OLS does.

Suggested Citation

  • Philip Hans Franses, 2021. "Testing bias in professional forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1086-1094, September.
    • Handle: RePEc:wly:jforec:v:40:y:2021:i:6:p:1086-1094
    DOI: 10.1002/for.2765
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    References listed on IDEAS

    as
    1. Lovell, Michael C, 1986. "Tests of the Rational Expectations Hypothesis," American Economic Review, American Economic Association, vol. 76(1), pages 110-124, March.
    2. Franses,Philip Hans, 2014. "Expert Adjustments of Model Forecasts," Cambridge Books, Cambridge University Press, number 9781107081598, Enero-Abr.
    3. Jeong, Jinook & Maddala, G S, 1991. "Measurement Errors and Tests for Rationality," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 431-439, October.
    4. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
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    Cited by:

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