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Quantile DEA: Estimating qDEA-alpha Efficiency Estimates with Conventional Linear Programming

In: Productivity and Inequality

Author

Listed:
  • Joseph A. Atwood

    (Montana State University)

  • Saleem Shaik

    (North Dakota State University)

Abstract

Conventional non-parametric linear programming (LP) based data envelopment analysis (DEA) models have the advantage of being able to estimate multiple input-output efficiency metrics but suffer from sensitivity to outliers and statistical observational noise. Previous observation-deleting approaches to the outlier/noise problem have been somewhat ad hoc usually requiring iterative LP and non-LP problem solving methods. We present the theory and methodology of quantile-DEA (qDEA), similar in concept to quantile-regression, which enables the analyst to directly use LP to obtain efficiency metrics while specifying that no more than ψ-percent of data points can lie external to the efficiency hull. Estimated qDEA-α frontiers encompassing proportion α = 1 − ψ of the data observations are contrasted to order-α frontier estimates. Quantile DEA is shown to be useful in addressing outliers in a study examining changes in relative state level agricultural efficiency measures over time.

Suggested Citation

  • Joseph A. Atwood & Saleem Shaik, 2018. "Quantile DEA: Estimating qDEA-alpha Efficiency Estimates with Conventional Linear Programming," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Paul Makdissi & Robin C. Sickles & Michael Veall & Marcel-Cristia (ed.), Productivity and Inequality, pages 305-326, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-68678-3_14
    DOI: 10.1007/978-3-319-68678-3_14
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    Citations

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    Cited by:

    1. Atwood, Joseph & Shaik, Saleem, 2020. "Theory and statistical properties of Quantile Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 649-661.
    2. Sakouvogui Kekoura & Shaik Saleem & Addey Kwame Asiam, 2020. "Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector," Open Economics, De Gruyter, vol. 3(1), pages 50-69, January.

    More about this item

    Keywords

    Data envelopment analysis; Partial moments; Outliers; Statistical noise; Quantile DEA;
    All these keywords.

    JEL classification:

    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land

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