 Comparative analysis of failure prediction methods: the Finnish caseTeija Laitinen and Maria Kankaanpaa European Accounting Review, 1999, vol. 8, issue 1, 67-92 Abstract: This paper first briefly discusses six alternative methods that have been applied to financial failure prediction: linear discriminant analysis, logit analysis, recursive partitioning, survival analysis, neural networks and the human information processing approach. The main objective was to study empirically whether the results stemming from the use of alternative methods differ from each other. This was conducted using the Finnish data one, two and three years prior to failure in empirical analysis. The results indicated that there was a statistically significant difference in prediction accuracy only between logistic analysis and survival analysis one year prior to failure. Two and three years prior to failure statistically significant differences were not found. The results indicate, with the three variables employed in this study, that no superior method has been found. Even one of the latest applications, neural networks, is in its present form only as effective as discriminant analysis was as early as thirty years ago. Date: 1999 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:euract:v:8:y:1999:i:1:p:67-92 Ordering information: This journal article can be ordered from Access Statistics for this article European Accounting Review is currently edited by Laurence van Lent More articles in European Accounting Review from Taylor & Francis Journals |
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