Extended data envelopment analysis–discriminant analysis

A new non-parametric method is recently proposed for discriminant analysis. The new approach is referred to as ‘DEA–Discriminant Analysis (DEA–DA)’ that is designed to identify the existence of an overlap between two groups, then determining the group membership of a newly sampled observation. A unique feature of the new technique is that it does not assume any discriminant function for group classification. As an extension of this study, this research proposes a new type of DEA–DA, or ‘Extended DEA–DA’, that can overcome some methodological drawbacks of its original formulation, but simultaneously maintaining its discriminant capabilities. Using a real data set regarding Japanese banks and a large simulation study, this research confirms that the Extended DEA–DA outperforms conventional linear and nonlinear discriminant analysis techniques.