Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities
AbstractThis paper examines the robustness of efficiency score rankings across four distributional assumptions for trans-log stochastic production-frontier models, using data from 1,221 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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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 32892.
Date of creation: 2011
Date of revision:
stochastic production frontier models; Japanese water utilities; heteroscedasticity;
Other versions of this item:
- Shinji Yane & Sanford Berg, 2013. "Sensitivity analysis of efficiency rankings to distributional assumptions: applications to Japanese water utilities," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2337-2348, June.
- L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-29 (All new papers)
- NEP-ECM-2011-08-29 (Econometrics)
- NEP-EFF-2011-08-29 (Efficiency & Productivity)
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