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Efficiency Measurement with the Weibull Stochastic Frontier

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  • Efthymios G. Tsionas

Abstract

In this paper we consider the Weibull distribution as a model for technical efficiency. The distribution has a shape and scale parameter like the gamma distribution and can be a reasonable competitor in practice. The techniques are illustrated using artificial data as well as a panel of Spanish dairy farms.

Suggested Citation

  • Efthymios G. Tsionas, 2007. "Efficiency Measurement with the Weibull Stochastic Frontier," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(5), pages 693-706, October.
    • Handle: RePEc:bla:obuest:v:69:y:2007:i:5:p:693-706
    DOI: 10.1111/j.1468-0084.2007.00475.x
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    1. Álvarez, Antonio & Arias, Carlos & Kumbhakar, Subal, 2003. "Empirical Consequences of Direction Choice in Technical Efficiency Analysis," Efficiency Series Papers 2003/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
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    Cited by:

    1. Graziella Bonanno & Domenico De Giovanni & Filippo Domma, 2017. "The ‘wrong skewness’ problem: a re-specification of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 47(1), pages 49-64, February.
    2. Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
    3. 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.
    4. Sheriff, Glenn, 2009. "Implementing second-best environmental policy under adverse selection," Journal of Environmental Economics and Management, Elsevier, vol. 57(3), pages 253-268, May.
    5. Graziella Bonanno & Filippo Domma, 2022. "Analytical Derivations of New Specifications for Stochastic Frontiers with Applications," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
    6. William C. Horrace & Christopher F. Parmeter, 2018. "A Laplace stochastic frontier model," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 260-280, March.
    7. Meena Badade & T. V. Ramanathan, 2020. "Probabilistic frontier regression model for multinomial ordinal type output data," Journal of Productivity Analysis, Springer, vol. 53(3), pages 339-354, June.
    8. Gholamreza Hajargasht & William E. Griffiths, 2018. "Estimation and testing of stochastic frontier models using variational Bayes," Journal of Productivity Analysis, Springer, vol. 50(1), pages 1-24, October.
    9. Yali Mu & Stephan von Cramon‐Taubadel, 2022. "Estimating dynamic market efficiency frontiers," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 633-653, September.
    10. 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.
    11. 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.
    12. Kamil Makieła & Błażej Mazur, 2020. "Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis," Econometrics, MDPI, vol. 8(2), pages 1-22, April.
    13. 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.
    14. Gholamreza Hajargasht, 2015. "Stochastic frontiers with a Rayleigh distribution," Journal of Productivity Analysis, Springer, vol. 44(2), pages 199-208, October.
    15. Shih-Tang Hwu & Tsu-Tan Fu & Wen-Jen Tsay, 2021. "Estimation and efficiency evaluation of stochastic frontier models with interval dependent variables," Journal of Productivity Analysis, Springer, vol. 56(1), pages 33-44, August.
    16. 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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