An Explanation for the Paradox Phenomenon in Taiwan’s Bank Performances

Ming-Chung Chang

doi:10.5430/ijfr.v5n1p21

Abstract

A traditional DEA (data envelopment analysis) model is useful for estimating the best performances for a successful and a more efficiency DMU (decision-making unit). This study uses a traditional DEA model to estimate the efficiency score of bank z in Taiwan and get a good efficiency score based on the 2006 data, however the bank z was taken over by the government in early 2007. In illustrating this paradox phenomenon, the study reconsiders the tradition DEA model by contributing a worst-practice frontier under a traditional DEA model. Findings: the bank z is located on the intersection of the worst-practice frontier and the traditional DEA model frontier. This study provides a critical determinant of a bank’s failure that a bank has a location such as the bank z.

Highlights

Measuring the efficiency of a decision making unit (DMU) is one of the major objectives of data envelopment analysis (DEA). Farrell (1957) builds a DEA methodology to estimate the ratio efficiency of a DMU through some specific mathematical programming models
DEA can estimate the relative efficiency of bank without assuming a prior production function (Chebat et al, 1994), and provides a single efficiency score for each estimated bank based on multiple input and/or multiple output variables (Bauer et al, 1998)
The result of the efficiency score in the BCC model shows that bank z has a good performance, but the bank z was taken over by government in early 2007

Summary

Introduction

Measuring the efficiency of a decision making unit (DMU) is one of the major objectives of data envelopment analysis (DEA). Farrell (1957) builds a DEA methodology to estimate the ratio efficiency of a DMU through some specific mathematical programming models. Measuring the efficiency of a decision making unit (DMU) is one of the major objectives of data envelopment analysis (DEA). Farrell (1957) builds a DEA methodology to estimate the ratio efficiency of a DMU through some specific mathematical programming models. Following Charnes et al (1978) and Banker et al (1984), the operations research and management science (OR/MS) researchers, economists, and experts apply the DEA methodology into their respective disciplines (Førsund and Sarafoglou, 2002, 2005). DEA can estimate the relative efficiency of bank without assuming a prior production function (Chebat et al, 1994), and provides a single efficiency score for each estimated bank based on multiple input and/or multiple output variables (Bauer et al, 1998). Charnes et al (1985) create an additive DEA model in which the slacks are used to calculate the efficiency value of DMU. Some studies turn the ratio efficiency and the slacks into a scalar measure (Tone, 1993)

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Conclusion