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A Laplace stochastic frontier model

Author

Listed:
  • William C. Horrace
  • Christopher F. Parmeter

Abstract

We propose a Laplace stochastic frontier model as an alternative to the traditional model with normal errors. An interesting feature of the Laplace model is that the distribution of inefficiency conditional on the composed error is constant for positive values of the composed error, but varies for negative values. A simulation study suggests that the model performs well relative to the normal-exponential model when the two-sided error is misspecified. An application to U.S. Airlines is provided.

Suggested Citation

  • William C. Horrace & Christopher F. Parmeter, 2018. "A Laplace stochastic frontier model," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 260-280, March.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:3:p:260-280
    DOI: 10.1080/07474938.2015.1059715
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    Citations

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    Cited by:

    1. Oleg Badunenko & Daniel J. Henderson, 2024. "Production analysis with asymmetric noise," Journal of Productivity Analysis, Springer, vol. 61(1), pages 1-18, February.
    2. Horrace, William C. & Rothbart, Michah W. & Yang, Yi, 2022. "Technical efficiency of public middle schools in New York City," Economics of Education Review, Elsevier, vol. 86(C).
    3. Tsionas, Mike G. & Assaf, A. George & Andrikopoulos, Athanasios, 2020. "Quantile stochastic frontier models with endogeneity," Economics Letters, Elsevier, vol. 188(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. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    6. Zangin Zeebari & Kristofer Månsson & Pär Sjölander & Magnus Söderberg, 2023. "Regularized conditional estimators of unit inefficiency in stochastic frontier analysis, with application to electricity distribution market," Journal of Productivity Analysis, Springer, vol. 59(1), pages 79-97, February.
    7. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2021. "Density deconvolution with Laplace errors and unknown variance," Journal of Productivity Analysis, Springer, vol. 56(2), pages 103-113, December.
    8. William C. Horrace & Christopher F. Parmeter & Ian A. Wright, 2024. "On asymmetry and quantile estimation of the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 61(1), pages 19-36, February.
    9. Phill Wheat & Alexander D. Stead & William H. Greene, 2019. "Robust stochastic frontier analysis: a Student’s t-half normal model with application to highway maintenance costs in England," Journal of Productivity Analysis, Springer, vol. 51(1), pages 21-38, February.
    10. William C. Horrace & Yulong Wang, 2022. "Nonparametric tests of tail behavior in stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 537-562, April.
    11. 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.
    12. Papadopoulos, Alecos & Parmeter, Christopher F., 2023. "A specification test for the composed error term in the stochastic frontier model," Economics Letters, Elsevier, vol. 233(C).
    13. Papadopoulos, Alecos & Parmeter, Christopher F., 2021. "Type II failure and specification testing in the Stochastic Frontier Model," European Journal of Operational Research, Elsevier, vol. 293(3), pages 990-1001.
    14. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    15. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    16. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    17. Cheol-Keun Cho & Peter Schmidt, 2020. "The wrong skew problem in stochastic frontier models when inefficiency depends on environmental variables," Empirical Economics, Springer, vol. 58(5), pages 2031-2047, May.
    18. Graziella Bonanno & Filippo Domma, 2022. "Analytical Derivations of New Specifications for Stochastic Frontiers with Applications," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
    19. Alexander D. Stead, 2025. "Maximum likelihood estimation of normal-gamma and normal-Nakagami stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 63(2), pages 183-198, April.
    20. William C. Horrace & Hyunseok Jung & Yi Yang, 2023. "The conditional mode in parametric frontier models," Journal of Productivity Analysis, Springer, vol. 60(3), pages 333-343, December.
    21. Alecos Papadopoulos, 2024. "The noise error component in stochastic frontier analysis," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 333-367, Springer.
    22. 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).
    23. Kamil Makie{l}a & B{l}a.zej Mazur, 2020. "Stochastic Frontier Analysis with Generalized Errors: inference, model comparison and averaging," Papers 2003.07150, arXiv.org, revised Oct 2020.
    24. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2024. "Penalized sieve estimation of zero‐inefficiency stochastic frontiers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 41-65, January.
    25. Stead, Alexander D. & Wheat, Phill & Greene, William H., 2023. "Robust maximum likelihood estimation of stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 309(1), pages 188-201.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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