Data/hora: 02/06/2024 15:39:37

Provedor de dados: | 31
País: | United States
Título: | APPLICATION OF RECURSIVE PARTITIONING TO AGRICULTURAL CREDIT SCORING
Autores: | Novak,   Michael P.; LaDue,   Eddy L.
Data: | 2003-01-29
Ano: | 1999
Palavras-chave: | Finance; Credit scoring; Misclassification; Recursive partitioning algorithm; Agricultural Finance.
Resumo: | 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.
Tipo: | Journal Article
Idioma: | Inglês

Identificador:

6869

http://purl.umn.edu/15129

Editor: | AgEcon Search
Relação: | Journal of Agricultural and Applied Economics&gt;Volume 31, Number 01, April 1999

Formato:

14

application/pdf