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Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930

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  • Robert Goldfarb
  • H. O. Stekler
  • Joel David

Abstract

This paper examines some economic forecasts made in late 1930 that were intended to predict economic activity in the United States in order to shed light on several methodological issues. We document that these forecasts were extremely optimistic, predicting that the recession in the US would soon end, and that 1931 would show a recovery. These forecasts displayed egregious errors, because 1931 witnessed the largest negative growth rate for the US economy in any year in the twentieth century. A specific question is what led forecasters to make such serious and substantial empirical errors. A second more general issue involves the methodology of forecasting. The 1930 forecasts were sometimes based on explicit analogies with previous serious business cycles. Modern forecasting approaches are based on techniques that may not be recognized as analogies. Using the 1930 forecasts, we examine the implicit-analogy content of forecasts, and what might render such implicit analogies valid or invalid. This 1930 forecast example also resonates beyond the confines of economic methodology because forecasts about the Great Depression are of continuing interest to the profession at large, and we produce a forecast series not previously available.

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  • Robert Goldfarb & H. O. Stekler & Joel David, 2005. "Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(4), pages 517-542.
  • Handle: RePEc:taf:jecmet:v:12:y:2005:i:4:p:517-542
    DOI: 10.1080/13501780500343524
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    Cited by:

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    9. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    10. Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O., 2020. "A textual analysis of Bank of England growth forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1478-1487.
    11. Gabriel Mathy & Christian Roatta, 2018. "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers 2018-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. Green, Kesten C. & Armstrong, J. Scott, 2007. "Structured analogies for forecasting," International Journal of Forecasting, Elsevier, vol. 23(3), pages 365-376.
    13. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    14. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.
    15. Gabriel Mathy & Herman Stekler, 2018. "Was the deflation of the depression anticipated? An inference using real-time data," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(2), pages 117-125, April.
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    17. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
    18. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
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    20. Nakilcioğlu, Emin & Rizvanolli, Anisa & Rendel, Olaf, 2022. "Workload forecasting of a logistic node using Bayesian neural networks," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 237-264, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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