Improving discrimination in data envelopment analysis: some practical suggestions

Improving discrimination in data envelopment analysis: some practical suggestions

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Article ID: iaor20083472
Country: Netherlands
Volume: 28
Issue: 1/2
Start Page Number: 117
End Page Number: 126
Publication Date: Oct 2007
Journal: Journal of Productivity Analysis
Authors: ,
Abstract:

In some contexts data envelopment analysis (DEA) gives poor discrimination on the performance of units. While this may reflect genuine uniformity of performance between units, it may also reflect lack of sufficient observations or other factors limiting discrimination on performance between units. In this paper, we present an overview of the main approaches that can be used to improve the discrimination of DEA. This includes simple methods such as the aggregation of inputs or outputs, the use of longitudinal data, more advanced methods such as the use of weight restrictions, production trade-offs and unobserved units, and a relatively new method based on the use of selective proportionality between the inputs and outputs.

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