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A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis

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Listed:
  • Christopher F. Parmeter

    (University of Miami)

  • Valentin Zelenyuk

    (University of Queensland)

Abstract

A recent spate of research has attempted to develop estimators for the stochastic frontier model which embrace semi- and nonparametric insights to enjoy the advantages inherent in the more traditional operations research method of data envelopment analysis. These newer methods explicitly allow statistical noise in the model, which is a common criticism of the data envelopment estimator. Further, several of these newer methods have focused on ensuring that axioms of production hold. These models and their subsequent estimators, despite having many appealing features, have yet to appear regularly in applied research. Given the pace at which estimators of this style are being proposed coupled with the dearth of formal applications, we seek to review the literature and discuss practical implementation issues of these methods. We provide a general overview of the major recent developments in this exciting field, draw connections with the data envelopment analysis field and discuss how useful synergies can be undertaken.

Suggested Citation

  • Christopher F. Parmeter & Valentin Zelenyuk, 2016. "A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis," Working Papers 2016-10, University of Miami, Department of Economics.
  • Handle: RePEc:mia:wpaper:2016-10
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    File URL: http://bus.miami.edu/_assets/files/repec/WP2016-10.pdf
    File Function: First version, 2016
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    References listed on IDEAS

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    Cited by:

    1. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2017. "Stochastic Frontier Analysis: Foundations and Advances," Working Papers 2017-10, University of Miami, Department of Economics.

    More about this item

    Keywords

    Partly Linear; Heteroskedasticity; Nonparametric; Bandwidth Publication Status: Under Review;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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