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A Note on Qualitative Forecast Evaluation

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  • Gopal Naik
  • Raymond M. Leuthold

Abstract

Traditionally, the 2 × 2 contingency table method has been used for qualitative evaluation of forecasts. However, the conclusions drawn based on this method could be misleading because it does not account for the direction of the turning or no turning points. A 4 × 4 contingency table which overcomes this weakness and which gives more information on the qualitative performance of the forecast is suggested.

Suggested Citation

  • Gopal Naik & Raymond M. Leuthold, 1986. "A Note on Qualitative Forecast Evaluation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(3), pages 721-726.
    • Handle: RePEc:oup:ajagec:v:68:y:1986:i:3:p:721-726.
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    Cited by:

    1. J. M. Gil & L. M. Albisu, 1993. "Composite Forecasting Methods: An Application To Spanish Maize Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 44(2), pages 264-271, May.
    2. Kosei Fukuda, 2009. "Forecasting growth cycle turning points using US and Japanese professional forecasters," Empirical Economics, Springer, vol. 36(2), pages 243-267, May.
    3. Frédéric Docquier & Lucas Guichard & Stefano Iandolo & Hillel Rapoport & Riccardo Turati & Gonzague Vannoorenberghe, 2022. "Populism and the Skill-Content of Globalization: Evidence from the Last 60 Years," CESifo Working Paper Series 10068, CESifo.
    4. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German car sales using Google data and multivariate models," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 97-135.
    5. Hutson, Mark & Joutz, Fred & Stekler, Herman, 2014. "Interpreting and evaluating CESIfo's World Economic Survey directional forecasts," Economic Modelling, Elsevier, vol. 38(C), pages 6-11.
    6. Christopher S. McIntosh & Jeffrey H. Dorfman, 1992. "Qualitative Forecast Evaluation: A Comparison of Two Performance Measures," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(1), pages 209-214.
    7. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    8. Dean Fantazzini, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US Using Online Search Data," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-27, November.
    9. Kaylen, Michael S. & Devino, Gary T. & Procter, Michael H., 1988. "Optimal Use Of Qualitative Models: An Application To Country Grain Elevator Bankruptcies," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 20(2), pages 1-7, December.
    10. Tara Sinclair & H. O. Stekler & L. Kitzinger, 2010. "Directional forecasts of GDP and inflation: a joint evaluation with an application to Federal Reserve predictions," Applied Economics, Taylor & Francis Journals, vol. 42(18), pages 2289-2297.
    11. Zapata, Hector O. & Garcia, Philip, 1990. "Price Forecasting With Time-Series Methods And Nonstationary Data: An Application To Monthly U.S. Cattle Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 15(1), pages 1-10, July.
    12. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    13. Naik, Gopal & Dixon, Bruce L., 1986. "A Monte Carlo Comparison Of Alternative Estimators Of Autocorrelated Simultaneous Systems Using A U.S. Pork Sector Model As The True Structure," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-12, December.
    14. Waychal, Nachiketas & Laha, Arnab Kumar & Sinha, Ankur, 2022. "Customized forecasting with Adaptive Ensemble Generator," IIMA Working Papers WP 2022-06-04, Indian Institute of Management Ahmedabad, Research and Publication Department.

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