Data Envelopment Analysis Development in Banking Sector

Data Envelopment Analysis Development in Banking Sector

Sepideh Kaffash (University of Massachusetts – Boston, USA) and Mehran Torshizi (Higher Banking Institute, Iran)
DOI: 10.4018/978-1-5225-2990-3.ch020
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Abstract

Data Envelopment Analysis is a non-linear programming model introduced by Charnes, Cooper and Rhodes in 1978. It is used widely in literature to measure the relative performance of units in several various fields including the banking. The fascinating real life cases and problems needed to be solved, the nature of data and the types of indicators in the banking field makes it one the most popular fields for DEA researchers theoretically and empirically. DEA and its applications have been the subject of several reviews. However, in this paper the authors specifically review the classic and new DEA models and the applications of them in the banking field.
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Background

Efficiency measurement originates from the definition of efficiency of DMU by Koopmans (1951) and Debreu (1951).They stated that DMU is efficient when producing one more unit of any output results in using more of some inputs or producing less of some outputs. For measuring the radial distance of DMU from the frontier, Debreu (1951) introduced output-expanding direction distance function while Shepherd (1956) introduced input-conserving direction distance function. Farrell (1957) presented efficiency measure as the product of allocated efficiency and technical efficiency. Using his idea, frontier approaches have been developed in two groups; parametric and non-parametric approaches. Based on these two approaches numerous models with different applications to a variety of industries were developed. Depending on the availability of data and the reason for efficiency measurement, scholars choose different models for their research. Table 1 illustrates the methods developed according to these two approaches.

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