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Panel Stochastic Frontier Analysis with Positive Skewness

Author

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  • Rachida El Mehdi

    (Mohammed First University)

  • Christian M. Hafner

    (Université Catholique de Louvain)

Abstract

This paper focuses on solving the problem of technical efficiency estimation for panel data when residuals are right-skewed. Indeed, there is an ambiguity in stochastic frontier analysis when the residuals of the ordinary least squares estimates are right-skewed, which might indicate that either there is no inefficiency, or that the model is misspecified. To overcome and avoid this problem, we propose a panel model in which the inefficiency term has an extended-half-normal distribution. Hence, our work is an extension of existing work for the cross-section case to panel data with time varying inefficiencies. We first propose estimators of the inefficiency under the extended-half-normal distribution assuming independence between the noise and the inefficiency term. A simulation study illustrates the good performance of our procedure. An application to drinking water for forty-two Moroccan municipalities in the period 2017 to 2019 favors our extended model. Results reveal that the performance of this public sector is generally medium and therefore the waste was significant.

Suggested Citation

  • Rachida El Mehdi & Christian M. Hafner, 2025. "Panel Stochastic Frontier Analysis with Positive Skewness," Computational Economics, Springer;Society for Computational Economics, vol. 65(5), pages 2743-2760, May.
    • Handle: RePEc:kap:compec:v:65:y:2025:i:5:d:10.1007_s10614-024-10646-w
    DOI: 10.1007/s10614-024-10646-w
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    References listed on IDEAS

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    1. Rachida El Mehdi & Christian M. Hafner, 2014. "Local Government Efficiency: The Case of Moroccan Municipalities," African Development Review, African Development Bank, vol. 26(1), pages 88-101, March.
    2. Gholamreza Hajargasht, 2015. "Stochastic frontiers with a Rayleigh distribution," Journal of Productivity Analysis, Springer, vol. 44(2), pages 199-208, October.
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    4. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    5. DEPRINS, Dominique & SIMAR, Léopold, 1989. "Estimating technical inefficiencies with correction for environmental conditions with an application to railway companies," LIDAM Reprints CORE 834, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Leopold Simar & Paul Wilson, 2010. "Inferences from Cross-Sectional, Stochastic Frontier Models," Econometric Reviews, Taylor & Francis Journals, vol. 29(1), pages 62-98.
    7. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    8. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128, October.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
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    11. Rachida El Mehdi & Christian M. Hafner, 2021. "Panel Stochastic Frontier Analysis with Dependent Error Terms," International Econometric Review (IER), Economic Research Association, vol. 13(2), pages 24-40, June.
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