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A Comparison of Classification/Regression Trees and Logistic Regression in Failure Models.
- Source :
- Procedia Economics & Finance; 2015, Vol. 26, p23-28, 6p
- Publication Year :
- 2015
-
Abstract
- The use of non-parametric statistical methods, the development of models geared towards the homogeneous characteristics of corporate sub-populations, and the introduction of non-financial variables, are three main issues analysed in this paper. This study compares the predictive performance of a non-parametric methodology, namelyClassification/Regression Trees (CART), against traditional logistic regression (LR) by employing a vast set of matched-pair accounts of the smallest enterprises, known as micro-entities,from the United Kingdom for the period 1999 to 2008 that includes financial, non-financial, and macroeconomic variables. Our findings show that CART outperforms the standard approach in the literature, LR. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22125671
- Volume :
- 26
- Database :
- Supplemental Index
- Journal :
- Procedia Economics & Finance
- Publication Type :
- Academic Journal
- Accession number :
- 110408873
- Full Text :
- https://doi.org/10.1016/S2212-5671(15)00797-2