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Subjective Probability Forecasts for Recessions

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  • Kajal Lahiri

    ()
    (Department of Economics, University of Albany, SUNY, Albany, NY, 12159, USA.)

  • J George Wang

    ()
    (College of Staten Island, CUNY, Staten Island, NY, 10314, USA.)

Abstract

Probabilistic forecasts are often more useful in business than point forecasts. In this paper, the joint subjective probabilities for negative GDP growth during the next two quarters obtained from the Survey of Professional Forecasters (SPF) are evaluated using various decompositions of the Quadratic Probability Score (QPS). Using the odds ratio and other forecasting accuracy scores appropriate for rare event forecasting, we find that the forecasts have statistically significant accuracy. However, compared to their discriminatory power, these forecasts have excess variability that is caused by relatively low assigned probabilities to forthcoming recessions. We suggest simple guidelines for the use of probability forecasts in practice.Business Economics (2006) 41, 26–37; doi:10.2145/20060204

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Bibliographic Info

Article provided by Palgrave Macmillan in its journal Business Economics.

Volume (Year): 41 (2006)
Issue (Month): 2 (April)
Pages: 26-37

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Handle: RePEc:pal:buseco:v:41:y:2006:i:2:p:26-37

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Cited by:
  1. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2009. "Measuring consensus in binary forecasts: NFL game predictions," International Journal of Forecasting, Elsevier, vol. 25(1), pages 182-191.
  2. Österholm, Pär, 2012. "The limited usefulness of macroeconomic Bayesian VARs when estimating the probability of a US recession," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 76-86.
  3. Giordani, Paolo & Soderlind, Paul, 2000. "Inflation Forecast Uncertainty," Working Paper Series in Economics and Finance 384, Stockholm School of Economics, revised 09 Oct 2000.
  4. Glenn D. Rudebusch & John C. Williams, 2007. "Forecasting recessions: the puzzle of the enduring power of the yield curve," Working Paper Series 2007-16, Federal Reserve Bank of San Francisco.
  5. Galbraith, John W. & van Norden, Simon, 2011. "Kernel-based calibration diagnostics for recession and inflation probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1041-1057, October.

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