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Regulation and Measuring Cost Efficiency with Panel Data Models: Application to Electricity Distribution Utilities

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  • Mehdi Farsi

    (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

  • Massimo Filippini

    (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

Abstract

This paper examines the application of different parametric methods to measure cost efficiency of electricity distribution utilities. The cost frontier model is estimated using four methods: Displaced Ordinary Least Squares, Fixed Effects, Random Effects and Maximum Likelihood Estimation. These methods are applied to a sample of 59 distribution utilities in Switzerland. The data consist of an unbalanced panel over a nine-year period from 1988 to 1996. Different specifications are compared with regards to the estimation of cost frontier characteristics and inefficiency scores. The results point to some advantages for the FE model in the estimation of cost function’s characteristics. The mutual consistency of different methods with regard to efficiency measures is analyzed. The results are mixed. The summary statistics of inefficiency estimates are not sensitive to the specification. However, the ranking changes significantly from one model to another. In particular, the least and most efficient companies are not identical across different methods. These results suggest that a valid benchmarking analysis should be applied with special care. It is recommended that the regulator use several specifications and perform a (mutual) consistency analysis. Finally, the out-of-sample prediction errors of different models are analyzed. The results suggest that benchmarking methods can be used as a control instrument in order to narrow the information gap between the regulator and regulated companies.

Suggested Citation

  • Mehdi Farsi & Massimo Filippini, 2003. "Regulation and Measuring Cost Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," CEPE Working paper series 03-19, CEPE Center for Energy Policy and Economics, ETH Zurich.
    • Handle: RePEc:cee:wpcepe:03-19
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