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The Record and Improvability of Economic Forecasting

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  • Victor Zarnowitz

Abstract

Have macroeconomic forecasts grown more or less accurate over time? This paper assembles, examines, and interprets evidence bearing on this question. Contrary to some critics, there are no indications that U.S. forecasts have grown systematically worse, that is, less accurate, more biased, or both. Neither do any definite trends in a positive direction emerge from comparisons of annual and quarterly multiperiod forecasts and time-series projections for the principal aggregative variables. The argument is developed and to some extent documented that major failures of forecasting are related to the incidence of slowdowns and contractions in general economic activity. Not only the forecasts of real GNP growth and unemployment but also those of nominal GNP growth and inflation often go seriously wrong when such setbacks occur. Forecasters tend to rely heavily on the persistence of trends in spending, output, and the price level. More attention to data and techniques that are sensitive to business cycle movements and turning points could help improve their record.

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  • Victor Zarnowitz, 1986. "The Record and Improvability of Economic Forecasting," NBER Working Papers 2099, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:2099
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    Cited by:

    1. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    2. Victor Zarnowitz, 1991. "Has Macro-Forecasting Failed?," NBER Working Papers 3867, National Bureau of Economic Research, Inc.
    3. Constantin Bürgi & Tara M. Sinclair, 2021. "What does forecaster disagreement tell us about the state of the economy?," Applied Economics Letters, Taylor & Francis Journals, vol. 28(1), pages 49-53, January.
    4. David Porter & Vernon Smith, 1994. "Stock market bubbles in the laboratory," Applied Mathematical Finance, Taylor & Francis Journals, vol. 1(2), pages 111-128.
    5. Karine Bouthevillain & Alexandre Mathis, 1995. "Prévisions : mesures, erreurs et principaux résultats," Économie et Statistique, Programme National Persée, vol. 285(1), pages 89-100.
    6. Jacques Kibambe & Renee van Eyden & charlotte du Toit, 2009. "Social Ingredients and Conditional Convergence in the Study of Sectoral Growth," Working Papers 200931, University of Pretoria, Department of Economics.
    7. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    8. 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.
    9. Zellner, Arnold & Israilevich, Guillermo, 2005. "Marshallian Macroeconomic Model: A Progress Report," Macroeconomic Dynamics, Cambridge University Press, vol. 9(2), pages 220-243, April.
    10. Crockett, Jean A., 1998. "Rational expectations, inflation and the nominal interest rate," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 349-363.
    11. Didier Borowski & Carine Bouthevillain & Catherine Doz & Pierre Malgrange & Pierre Morin, 1991. "Vingt ans de prévisions macro-économiques : une évaluation sur données françaises," Économie et Prévision, Programme National Persée, vol. 99(3), pages 43-65.
    12. William E. Cullison, 1988. "On recognizing inflation," Economic Review, Federal Reserve Bank of Richmond, vol. 74(Jul), pages 4-12.
    13. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    14. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.

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