The authors are grateful to the Swiss Federal Office for Education and Science for their financial support. They also wish to thank the editor and two anonymous referees for their helpful suggestions, and Aurelio Fetz for his assistance.
APPLICATION OF PANEL DATA MODELS IN BENCHMARKING ANALYSIS OF THE ELECTRICITY DISTRIBUTION SECTOR†
Article first published online: 31 AUG 2006
Annals of Public and Cooperative Economics
Volume 77, Issue 3, pages 271–290, September 2006
How to Cite
Farsi, M., Filippini, M. and Greene, W. (2006), APPLICATION OF PANEL DATA MODELS IN BENCHMARKING ANALYSIS OF THE ELECTRICITY DISTRIBUTION SECTOR. Annals of Public and Cooperative Economics, 77: 271–290. doi: 10.1111/j.1467-8292.2006.00306.x
Résumé en fin d'article; Zusammenfassung am Ende des Artikels; resumen al fin del artículo.
- Issue published online: 31 AUG 2006
- Article first published online: 31 AUG 2006
- Received July 2005; final revision accepted March 2006
ABSTRACT‡: This paper explores the application of several panel data models in measuring productive efficiency of the electricity distribution sector. Stochastic Frontier Analysis has been used to estimate the cost-efficiency of 59 distribution utilities operating over a nine-year period in Switzerland. The estimated coefficients and inefficiency scores are compared across three different panel data models. The results indicate that individual efficiency estimates are sensitive to the econometric specification of unobserved firm-specific heterogeneity. This paper shows that alternative panel models such as the ‘true’ random effects model proposed by Greene (2005) could be used to explore the possible impacts of unobserved firm-specific factors on efficiency estimates. When these factors are specified as a separate stochastic term, the efficiency estimates are substantially higher suggesting that conventional models could confound efficiency differences with other unobserved variations among companies. On the other hand, refined specification of unobserved heterogeneity might lead to an underestimation of inefficiencies by mistaking potential persistent inefficiencies as external factors. Given that specification of inefficiency and heterogeneity relies on non-testable assumptions, there is no conclusive evidence in favour of one or the other specification. However, this paper argues that alternative panel data models along with conventional estimators can be used to obtain approximate lower and upper bounds for companies' efficiency scores.