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Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities

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  • Shinji Yane
  • Sanford Berg

Abstract

This article examines the robustness of efficiency score rankings across four distributional assumptions for trans-log stochastic production-frontier models, using data from 1221 Japanese water utilities (for 2004 and 2005). One-sided error terms considered include the half-normal, truncated normal, exponential and gamma distributions. Results are compared for homoscedastic and doubly heteroscedastic models, where we also introduce a doubly heteroscedastic variable mean model, and examine the sensitivity of the nested models to a stronger heteroscedasticity correction for the one-sided error component. The results support three conclusions regarding the sensitivity of efficiency rankings to distributional assumptions. When four standard distributional assumptions are applied to a homoscedastic stochastic frontier model, the efficiency rankings are quite consistent. When those assumptions are applied to a doubly heteroscedastic stochastic frontier model, the efficiency rankings are consistent when proper and sufficient arguments for the variance functions are included in the model. When a more general model, like a variable mean model is estimated, efficiency rankings are quite sensitive to heteroscedasticity correction schemes.

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File URL: http://hdl.handle.net/10.1080/00036846.2012.663475
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Bibliographic Info

Article provided by Taylor and Francis Journals in its journal Applied Economics.

Volume (Year): 45 (2013)
Issue (Month): 17 (June)
Pages: 2337-2348

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Handle: RePEc:taf:applec:45:y:2013:i:17:p:2337-2348

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  1. Wei Siang Wang & Peter Schmidt, 2007. "On The Distribution of Estimated Technical Efficiency in Stochastic Frontier Models," CEPA Working Papers Series WP022007, School of Economics, University of Queensland, Australia.
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  3. Kaddour Hadri & Cherif Guermat & Julie Whittaker, 2003. "Estimating Farm Efficiency in the Presence of Double Heteroscedasticity Using Panel Data," Journal of Applied Economics, Universidad del CEMA, vol. 0, pages 255-268, November.
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  7. De Witte, Kristof & Marques, Rui C., 2008. "Capturing the environment, a metafrontier approach to the drinking water sector," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/158171, Katholieke Universiteit Leuven.
  8. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, 06.
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  10. Antonio Estache & Tim Coelli & Sergio Perelman & Lourdes Trujillo, 2003. "A Primer on Efficiency Measurement for Utilities and Transport Regulators," ULB Institutional Repository 2013/44106, ULB -- Universite Libre de Bruxelles.
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  12. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-63, July.
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