APPLICATION OF RECURSIVE PARTITIONING TO AGRICULTURAL CREDIT SCORING

Michael P. Novak and Eddy L. LaDue

Journal of Agricultural and Applied Economics, 1999, vol. 31, issue 01, 14

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.

Keywords: Agricultural; Finance (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:joaaec:15129

DOI: 10.22004/ag.econ.15129

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