On the sensitivity of US electric utilities' efficiency estimates - a distance function approach
Christian Growitsch () and
Borge Hess ()
Applied Economics Letters, 2009, vol. 16, issue 8, 847-851
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.
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