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Journal of Agricultural and Resource Economics >
Volume 29, Number 03, December 2004 >
Please use this identifier to cite or link to this item:
http://purl.umn.edu/30912
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| Title: | Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks |
| Authors: | Norwood, F. Bailey
Lusk, Jayson L.
Brorsen, B. Wade |
| Keywords: | discrete dependent variables
forecasting
likelihood functions
model selection
out-of-sample
quality grades
receiver-operator curves |
| Issue Date: | 2004-12 |
| 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. |
| URI: | http://purl.umn.edu/30912 |
| Institution/Association: | Journal of Agricultural and Resource Economics>Volume 29, Number 03, December 2004 |
| Total Pages: | 16 |
| Language: | English |
| From Page: | 404 |
| To Page: | 419 |
| Collections: | Volume 29, Number 03, December 2004
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| 29030404.pdf | 724Kb | PDF | View/Open |
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