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Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks

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  • Norwood, F. Bailey
  • Lusk, Jayson L.
  • Brorsen, B. Wade

Abstract

Little research has been conducted on evaluating out-of sample forecasts of discrete dependent variables. This study describes the large and small sample properties of two forecast evaluation techniques for discrete dependent variables: receiver-operator curves and out-of-sample log-likelihood functions. The methods are shown to provide identical model rankings in large samples and similar rankings in small samples. The likelihood function method is better at detecting forecast accuracy in small samples. By improving forecasts of fed cattle quality grades, the forecast evaluation methods are shown to increase cattle marketing revenues by $2.59/head.

Suggested Citation

  • Norwood, F. Bailey & Lusk, Jayson L. & Brorsen, B. Wade, 2004. "Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-16, December.
    • Handle: RePEc:ags:jlaare:30912
    DOI: 10.22004/ag.econ.30912
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    References listed on IDEAS

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    1. Jayson L. Lusk & Randall Little & Allen Williams & John Anderson & Blair McKinley, 2003. "Utilizing Ultrasound Technology to Improve Livestock Marketing Decisions," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(1), pages 203-217.
    2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
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    8. Bailey Norwood & Matthew C. Roberts & Jayson L. Lusk, 2004. "Ranking Crop Yield Models Using Out-of-Sample Likelihood Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1032-1043.
    9. M. K. Haener & P. C. Boxall & W. L. Adamowicz, 2001. "Modeling Recreation Site Choice: Do Hypothetical Choices Reflect Actual Behavior?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 629-642.
    10. Koontz, Stephen R. & Hoag, Dana L. & Walker, Jodine L. & Brethour, John R., 2000. "Returns To Market Timing And Sorting Of Fed Cattle," 2000 Conference, April 17-18 2000, Chicago, Illinois 18930, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    11. Norwood, F. Bailey & Ferrier, Peyton Michael & Lusk, Jayson L., 2001. "Model Selection Criteria Using Likelihood Functions And Out-Of-Sample Performance," 2001 Conference, April 23-24, 2001, St. Louis, Missouri 18947, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    12. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-1291, November.
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    Cited by:

    1. Gallardo, R. Karina & Wang, Qianqian, 2013. "Willingness to Pay for Pesticides' Environmental Features and Social Desirability Bias: The Case of Apple and Pear Growers," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), pages 1-16, April.
    2. Andreas C. Drichoutis & Jayson L. Lusk, 2016. "What can multiple price lists really tell us about risk preferences?," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 89-106, December.
    3. Norwood, F. Bailey, 2005. "Can Calibration Reconcile Stated and Observed Preferences?," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 37(1), pages 1-10, April.
    4. KIANI, Khurshid M., 2007. "Business Cycle Asymmetries In Stock Returns: Robust Evidence," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(2), pages 99-120.
    5. Andreas C Drichoutis & Jayson L Lusk, 2014. "Judging Statistical Models of Individual Decision Making under Risk Using In- and Out-of-Sample Criteria," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-13, July.
    6. Dharmasena, Senarath & Bessler, David & Capps, Oral. Jr, 2016. "On the Evaluation of Probability Forecasts: An Application to Qualitative Choice Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235424, Agricultural and Applied Economics Association.
    7. Brorsen, B. Wade, 2009. "Research: Are We Valuing the Right Stuff?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-10, April.
    8. Lusk, Jayson L. & Crespi, John M. & McFadden, Brandon R. & Cherry, J. Bradley C. & Martin, Laura & Bruce, Amanda, 2016. "Neural antecedents of a random utility model," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PA), pages 93-103.
    9. Chang, Jae Bong & Lusk, Jayson L., 2008. "Concerns for Fairness and Preferences for Organic Food," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6414, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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