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Man vs. model? The role of judgment in forecasting

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  • Stephen K. McNees

Abstract

This article presents evidence on the role that judgmental adjustments play in macroeconomic forecast accuracy. It starts by contrasting the predictive records of four prominent forecasters who adjust their models with those of three models that are used mechanically. The adjusted forecasts tend to be more accurate overall, although important exceptions can be found. Next the article compares adjusted forecasts with those generated mechanically by the same models. Again, with some significant exceptions, judgmental adjustments improve accuracy more often than not. ; The article closes by considering whether macroeconomic forecasters should place more or less emphasis on their adjustments relative to their models. The author finds a clear tendency for modelers to overadjust their models, illustrating what prominent psychologists have termed \"the major error of intuitive prediction.\" In short, model builders should not hesitate to adjust their models to offset models limitations but should also guard against the tendency to overestimate the value of their personal insights.

Suggested Citation

  • Stephen K. McNees, 1990. "Man vs. model? The role of judgment in forecasting," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 41-52.
  • Handle: RePEc:fip:fedbne:y:1990:i:jul:p:41-52
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    File URL: http://www.bostonfed.org/economic/neer/neer1990/neer490c.pdf
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    References listed on IDEAS

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    1. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    2. Stephen K. McNees, 1988. "How accurate are macroeconomic forecasts?," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 15-36.
    3. Wallis, Kenneth F, 1989. "Macroeconomic Forecasting: A Survey," Economic Journal, Royal Economic Society, vol. 99(394), pages 28-61, March.
    4. Nelson, Charles R, 1972. "The Prediction Performance of the FRB-MIT-PENN Model of the U.S. Economy," American Economic Review, American Economic Association, vol. 62(5), pages 902-917, December.
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    6. Haitovsky, Yoel & Treyz, George I, 1972. "Forecasts with Qtrly Macroeconometric Models: Equation Adjustments, and Benchmark Predictions: The U.S. Experience," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 317-325, August.
    7. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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    Cited by:

    1. Victor Zarnowitz, 1991. "Has Macro-Forecasting Failed?," NBER Working Papers 3867, National Bureau of Economic Research, Inc.
    2. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    3. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Bank of Finland Research Discussion Papers 4/1991, Bank of Finland.
    4. Ricardo Mestre & Peter McAdam, 2011. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 303-324, April.
    5. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    6. Binder, Carola Conces & Wetzel, Samantha, 2018. "The FOMC versus the staff, revisited: When do policymakers add value?," Economics Letters, Elsevier, vol. 171(C), pages 72-75.

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