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Performance of the Bootstrap for DEA Estimators and Iterating the Principle

  • Léopold Simar
  • Paul W. WilsonEmail author
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 164)

Abstract

This chapter further examines the bootstrap method proposed by Simar and Wilson (Manag Sci 44(11):49–61, 1998) for DEA efficiency estimators. Some simplifications as well as Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method are offered. In addition, we present similar evidence for confidence intervals estimated with the so-called naive bootstrap to illustrate the fact that the naive bootstrap is inconsistent in the DEA setting. Finally, we propose an iterated version of the bootstrap which may be used to improve bootstrap estimates of confidence intervals.

Keywords

Data envelopment analysis Bootstrap Distance function Efficiency Frontier models 

Notes

Acknowledgments

Léopold Simar gratefully acknowledges the Research support from “Projet d’Actions de Recherche Concertées” (No. 98/03-217) and from the “Inter-university Attraction Pole,” Phase V (No. P5/24) from the Belgian Government.

Paul W. Wilson also gratefully acknowledges Research support from the Texas Advanced Computing Center at the University of Texas, Austin.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Institut de Statistique and COREUniversité Catholique de LouvainLouvain-la-NeuveBelgium
  2. 2.Department of EconomicsClemson UniversityClemsonUSA

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