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A comparison of nonparametric efficiency estimators: DEA, FDH, DEAC, FDHC, order-m and quantile

Author

Listed:
  • Tarcio Da Silva

    (Secretariat of Economic Policy, Ministry of Finance)

  • Carlos Martins-filho

    (Department of Economics, University of Colorado at Boulder)

  • Eduardo Ribeiro

    (Institute of Economics - Federal University of Rio de Janeiro)

Abstract

In this paper we compare six nonparametric estimators for technical efficiency and use them to evaluate the efficiency of the banking sector in Brazil. The estimators considered are data envelopment analysis (DEA), free disposal hull (FDH), bias corrected FDH (FDHC), bias corrected DEA (DEAC), order-m and alpha-conditional quantile. Their theoretical properties are discussed and their implementation is illustrated using a sample of 184 Brazilian banks that extends from 1995 to 2004. The results indicate that these estimators can lead to significant discrepancy in estimated efficiency scores. Order-m and alpha-conditional quantile estimators have proven to be useful tools in identifying extreme values and are shown to be rather robust relative to DEA and FDH. Bias correction for both DEA and FDH was problematic, producing significant changes in firms rankings and estimated efficiencies.

Suggested Citation

  • Tarcio Da Silva & Carlos Martins-filho & Eduardo Ribeiro, 2016. "A comparison of nonparametric efficiency estimators: DEA, FDH, DEAC, FDHC, order-m and quantile," Economics Bulletin, AccessEcon, vol. 36(1), pages 118-131.
    • Handle: RePEc:ebl:ecbull:eb-15-00306
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    More about this item

    Keywords

    technical efficiency; nonparametric efficiency estimation; Brazilian banks.;
    All these keywords.

    JEL classification:

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

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