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Method for Estimating Confidence Intervals for DEA Efficiency Models Using Regression Models

  • Filipe Giovani Bonin BisoffiEmail author
  • Graziella Cardoso Bonadia
  • Victor Henrique Duarte de Oliveira
  • Sérgio Ricardo Barbosa
Chapter
  • 408 Downloads
Part of the Telecommunications and Information Technology book series (TIT)

Abstract

Benchmarking methods, such as DEA (Data Envelopment Analysis), are used to compare a set of entities regarding their efficiency in a given process. The structure of the DEA method does not take random disturbances into consideration when estimating the efficiency of each entity. In most scenarios, this characteristic does not reflect the reality of the problem, since practically the entire process is subject to external disturbances. Using regression methods, it is possible to generate confidence intervals for DEA-estimated efficiency, considering the model’s inputs and outputs as independent variables. With this, the conclusions and subsequent actions based on the returned results are more robust, and begin to contemplate, in a certain manner, random disturbances suffered by the companies.

Keywords

DEA Confidence interval Nonparametric regression analysis 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Filipe Giovani Bonin Bisoffi
    • 1
    Email author
  • Graziella Cardoso Bonadia
    • 1
  • Victor Henrique Duarte de Oliveira
    • 2
  • Sérgio Ricardo Barbosa
    • 2
  1. 1.Decision Management Support & Applications DepartmentCPqD - Telecommunications Research and Development CenterCampinasBrazil
  2. 2.CEMIG Distribuição S.A.Belo HorizonteBrazil

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