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Data Envelopment Analysis DEA

In: Benchmarking with DEA, SFA, and R

Author

Listed:
  • Peter Bogetoft

    (Copenhagen Business School CBS)

  • Lars Otto

    (University of Copenhagen)

Abstract

In this and the next chapter, we cover the basics and some additional material on Data Envelopment Analysis (DEA). DEA combines the estimation of the technology with the measurement of performance as related to this technology. It thereby integrates the two basic problems of a) defining a performance standard, the technology, and b) evaluating achievements against the established standard. There are several DEA methods that differ in terms of the estimated technology and the efficiency concept used. We will cover the most important ones and emphasize what unites the class of methods that make up DEA.

Suggested Citation

  • Peter Bogetoft & Lars Otto, 2011. "Data Envelopment Analysis DEA," International Series in Operations Research & Management Science, in: Benchmarking with DEA, SFA, and R, chapter 0, pages 81-113, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-7961-2_4
    DOI: 10.1007/978-1-4419-7961-2_4
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    Cited by:

    1. Álvarez, Inmaculada & Barbero, Javier & Zofío, Jose Luis, 2016. "A Data Envelopment Analysis Toolbox for MATLAB," Working Papers in Economic Theory 2016/03, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    2. Ather Hassan Dar & Somesh Kumar Mathur & Sila Mishra, 2021. "The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 653-701, December.

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