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On the sensitivity of US electric utilities' efficiency estimates - a distance function approach

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  • Christian Growitsch
  • Borge Hess

Abstract

Previous applications of different benchmarking techniques, both in academia and regulation practice, have shown substantial differences among the models' results. To analyse the sensitivity of efficiency estimates of a sample of US electricity distribution utilities, we compare the results of the generalized least squares frontier model proposed by Schmidt and Sickles (1984) and the maximum likelihood estimation frontier model of Pitt and Lee (1981) with the true random effects frontier model introduced by Greene (2004, 2005). We find substantially higher efficiency scores for the Greene model, indicating that the other formulations underestimate firms' efficiency due to an insufficient consideration of firm specific heterogeneity. In contrast to other studies, the efficiency estimates in this article do not differ considerably.

Suggested Citation

  • Christian Growitsch & Borge Hess, 2009. "On the sensitivity of US electric utilities' efficiency estimates - a distance function approach," Applied Economics Letters, Taylor & Francis Journals, vol. 16(8), pages 847-851.
    • Handle: RePEc:taf:apeclt:v:16:y:2009:i:8:p:847-851
    DOI: 10.1080/13504850701222053
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    References listed on IDEAS

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    1. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Supawat Rungsuriyawiboon & Tim Coelli, 2004. "Regulatory Reform and Economic Performance in US Electricity Generation," CEPA Working Papers Series WP062004, School of Economics, University of Queensland, Australia.
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