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AgEcon Search >
Journal of Agricultural and Applied Economics >
Volume 31, Number 01, April 1999 >
Please use this identifier to cite or link to this item:
http://purl.umn.edu/15129
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| Title: | APPLICATION OF RECURSIVE PARTITIONING TO AGRICULTURAL CREDIT SCORING |
| Authors: | Novak, Michael P.
LaDue, Eddy L. |
| Keywords: | finance
credit scoring
misclassification
recursive partitioning algorithm |
| Issue Date: | 1999-04 |
| Abstract: | Recursive Partitioning Algorithm (RPA) is introduced as a technique for credit scoring analysis, which allows direct incorporation of misclassification costs. This study corroborates nonagricultural credit studies, which indicate that RPA outperforms logistic regression based on within-sample observations. However, validation based on more appropriate out-of-sample observations indicates that logistic regression is superior under some conditions. Incorporation of misclassification costs can influence the creditworthiness decision. |
| URI: | http://purl.umn.edu/15129 |
| Institution/Association: | Journal of Agricultural and Applied Economics>Volume 31, Number 01, April 1999 |
| Total Pages: | 14 |
| Language: | English |
| From Page: | 109 |
| To Page: | 122 |
| Collections: | Volume 31, Number 01, April 1999
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| 31010109.pdf | 1170Kb | PDF | View/Open |
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