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Data Envelopment Analysis: An Overview


  • Subhash C. Ray

    (University of Connecticut)


Over the past decades Data Envelopment Analysis (DEA) has emerged as an important nonparametric method of evaluating performance of decision making units through benchmarking. Although developed primarily for measuring technical efficiency, DEA is now applied extensively for measuring scale efficiency, cost efficiency, and profit efficiency as well. This paper integrates the different DEA models commonly applied in empirical research with their underlying theoretical foundations in neoclassical production economics.

Suggested Citation

  • Subhash C. Ray, 2014. "Data Envelopment Analysis: An Overview," Working papers 2014-33, University of Connecticut, Department of Economics.
  • Handle: RePEc:uct:uconnp:2014-33

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    References listed on IDEAS

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    7. Banker, Rajiv D. & Chang, Hsihui & Cooper, William W., 1996. "Equivalence and implementation of alternative methods for determining returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 89(3), pages 473-481, March.
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    14. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
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    More about this item


    Linear Programming; Technical Efficiency; Returns to Scale; Distance Functions;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D2 - Microeconomics - - Production and Organizations

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