Application of Recursive Partitioning to Agricultural Credit Scoring

Michael P. Novak and Eddy LaDue

Journal of Agricultural and Applied Economics, 1999, vol. 31, issue 1, 109-122

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.

Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:cup:jagaec:v:31:y:1999:i:01:p:109-122_02

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