Sensitivity Analysis

Joe Zhu ()
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Joe Zhu: Worcester Polytechnic Institute

Chapter 11 in Quantitative Models for Performance Evaluation and Benchmarking, 2014, pp 207-244 from Springer

Abstract: Abstract One important issue in DEA which has been studied by many DEA researchers is the efficiency sensitivity to perturbations in the data. Some DEA sensitivity studies focus on the sensitivity of DEA results to the variable and model selection. Most of the DEA sensitivity analysis studies focus on the misspecification of efficiency classification of a test DMU. However, note that DEA is an extremal method in the sense that all extreme points are characterized as efficient. If data entry errors occur for various DMUs, the resulting isoquant may vary substantially. We say that the calculated frontiers of DEA models are stable if the frontier DMUs that determine the DEA frontier remain on the frontier after particular data perturbations are made.

Keywords: Stability Region; Linear Programming Problem; Data Perturbation; Efficiency Classification; Efficiency Stability (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-3-319-06647-9_11

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