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Forecasting Limited Dependent Variables: Better Statistics For Better Steaks

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

Abstract

Little research has been conducted on evaluating out-of-sample forecasts of limited dependent variables. This study describes the large and small sample properties of two forecast evaluation techniques for limited 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 slightly better at detecting forecast accuracy in small samples, while receiver-operator curves are better at comparing forecasts across different data. 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

  • Lusk, Jayson L. & Norwood, F. Bailey & Brorsen, B. Wade, 2004. "Forecasting Limited Dependent Variables: Better Statistics For Better Steaks," 2004 Annual Meeting, February 14-18, 2004, Tulsa, Oklahoma 34612, Southern Agricultural Economics Association.
    • Handle: RePEc:ags:saeaft:34612
    DOI: 10.22004/ag.econ.34612
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    References listed on IDEAS

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