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Wrong skewness and finite sample correction in the normal-half normal stochastic frontier model

Author

Listed:
  • Jun Cai

    (Huazhong University of Science and Technology)

  • Qu Feng

    (Nanyang Technological University)

  • William C. Horrace

    (Syracuse University)

  • Guiying Laura Wu

    (Nanyang Technological University)

Abstract

In parametric stochastic frontier models, the composed error is specified as the sum of a two-sided noise component and a one-sided inefficiency component, which is usually assumed to be half-normal, implying that the error distribution is skewed in one direction. In practice, however, estimation residuals may display skewness in the wrong direction. Model respecification or pulling a new sample is often prescribed. Since wrong skewness may manifest as a finite sample problem, this paper proposes a finite sample adjustment to existing estimators to obtain the desired direction of residual skewness. This provides an alternative empirical approach to deal with the wrong skewness problem that does not require respecification of the model.

Suggested Citation

  • Jun Cai & Qu Feng & William C. Horrace & Guiying Laura Wu, 2021. "Wrong skewness and finite sample correction in the normal-half normal stochastic frontier model," Empirical Economics, Springer, vol. 60(6), pages 2837-2866, June.
    • Handle: RePEc:spr:empeco:v:60:y:2021:i:6:d:10.1007_s00181-020-01988-z
    DOI: 10.1007/s00181-020-01988-z
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    References listed on IDEAS

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    Cited by:

    1. Dan Ben-Moshe & David Genesove, 2022. "Regulation and Frontier Housing Supply," Papers 2208.01969, arXiv.org, revised Sep 2022.
    2. Subal C. Kumbhakarⓡ & Emir Malikovⓡ & Christopher F. Parmeterⓡ, 2021. "Applications of efficiency and productivity analysis: editors’ introduction," Empirical Economics, Springer, vol. 60(6), pages 2657-2663, June.
    3. Zhao, Shirong & Parmeter, Christopher F., 2022. "The “wrong skewness” problem: Moment constrained maximum likelihood estimation of the stochastic frontier model," Economics Letters, Elsevier, vol. 221(C).
    4. Christopher F. Parmeter & Shirong Zhao, 2023. "An alternative corrected ordinary least squares estimator for the stochastic frontier model," Empirical Economics, Springer, vol. 64(6), pages 2831-2857, June.
    5. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.

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    More about this item

    Keywords

    Stochastic frontier model; Skewness; MLE; Constrained estimators; BIC;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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