Predicting Credit Default in an Agricultural Bank: Methods and Issues

Oluwarotimi O. Odeh, Allen Featherstone and Das Sanjoy

No 35359, 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida from Southern Agricultural Economics Association

Abstract: This study examines the performance of logistic regression, artificial neural networks and adaptive neuro-fuzzy inference system in predicting credit default using data from Farm Credit System. Empirical findings show that credit default predictions vary with empirical model used.

Keywords: Agricultural; Finance (search for similar items in EconPapers)
Pages: 21
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:ags:saeaso:35359

DOI: 10.22004/ag.econ.35359

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