文章基本信息

标题：Consideration of Uneven Misclassification Cost and Group Size for Bankruptcy Prediction
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作者：Yi-Chun Kuo
期刊名称：American Journal of Industrial and Business Management
印刷版ISSN：2164-5167
电子版ISSN：2164-5175
出版年度：2013
卷号：3
期号：8
页码：708-714
DOI：10.4236/ajibm.2013.38080
出版社：Scientific Research Publishing
摘要：Despite a larger number of approaches developed for predicting bankruptcy over the past three decades, rare research has considered the effects of misclassification cost and group size. Uneven cost of misclassification results from Type I (misclassify a healthy company as a failure) and Type II errors (misclassify a failed company as healthy), which are seldom considered. Without accounting for unevenness in misclassification cost, the classifier is developed based on minimizing total misclassification errors to improve the hit-ratio for classification performance. This not only results in poor decision capability, but also causes bias towards the larger group. This paper explores the issues of uneven misclassification costs and imbalanced group size by applying an asymmetric-stratified data envelopment analysis to bankruptcy prediction. The results show a tradeoff between hit-ratio and misclassification cost when Type II error cost is ten times over that of Type I, that is, the higher the hit-ratio is, the greater the resulting misclassification costs are. By incorporating different proportions of Type II error costs to Type I into the classification procedures, the proposed approach provides greater flexibility to decision makers for credit evaluation or bankruptcy prediction based on different risk attitudes and situations.
关键词：Bankruptcy Prediction; Misclassification Cost; Data Envelopment Analysis (DEA)