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Application of Panel Data Models in Benchmarking Analysis of the Electrivity Distribution Sector

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Author Info

  • 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)

  • William Greene

    (Department of Economics, Stern School of Business, New York University, 44 West 4th St., New York, NY 10012, USA)

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. When these factors are considered as a separate stochastic term, the efficiency estimates are substantially higher indicating that conventional models could confound efficiency differences with other unobserved variations among companies. The results suggest that alternative panel models such as the “true” random effects model proposed by Greene (2005) could be used to evaluate the possible impacts of unobserved factors such as network effects on efficiency estimates.

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File URL: http://www.cepe.ethz.ch/publications/workingPapers/CEPE_WP39.pdf
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Bibliographic Info

Paper provided by CEPE Center for Energy Policy and Economics, ETH Zurich in its series CEPE Working paper series with number 05-39.

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Length: 21 pages
Date of creation: Jul 2005
Date of revision:
Handle: RePEc:cee:wpcepe:05-39

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References

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  1. Tim Coelli & Antonio Estache & Sergio Perelman & Lourdes Trujillo, 2003. "A Primer on Efficiency Measurement for Utilities and Transport Regulators," World Bank Publications, The World Bank, number 15149, July.
  2. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
  3. Bauer, Paul W. & Berger, Allen N. & Ferrier, Gary D. & Humphrey, David B., 1998. "Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods," Journal of Economics and Business, Elsevier, vol. 50(2), pages 85-114, March.
  4. Mehdi Farsi & Massimo Filippini, 2004. "Regulation and Measuring Cost-Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," Review of Industrial Organization, Springer, vol. 25(1), pages 1-19, 08.
  5. Estache, Antonio & Rossi, Martin A. & Ruzzier, Christian A., 2002. "The case for international coordination of electricity regulation : evidence from the measurement of efficiency in South America," Policy Research Working Paper Series 2907, The World Bank.
  6. Irastorza, Veronica, 2003. "Benchmarking for Distribution Utilities: A Problematic Approach to Defining Efficiency," The Electricity Journal, Elsevier, vol. 16(10), pages 30-38, December.
  7. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980.
  8. Antonioli, B. & Filippini, M., 2001. "The use of a variable cost function in the regulation of the Italian water industry," Utilities Policy, Elsevier, vol. 10(3-4), pages 181-187.
  9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  10. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  11. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2004. "Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models," CEPE Working paper series 04-33, CEPE Center for Energy Policy and Economics, ETH Zurich.
  12. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
  13. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
  14. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, 07.
  15. Jamasb, T. & Pollitt, M., 2000. "Benchmarking and regulation: international electricity experience," Utilities Policy, Elsevier, vol. 9(3), pages 107-130, September.
  16. Simar, L. & Wilson, P.W., 1999. "Statistical Inference in Nonparametric Frontier Models: the State of the Art," Papers 9904, Catholique de Louvain - Institut de statistique.
  17. Polachek, Solomon W & Yoon, Bong Joon, 1996. "Panel Estimates of a Two-Tiered Earnings Frontier," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 169-78, March-Apr.
  18. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
  19. Jamasb, Tooraj & Pollitt, Michael, 2003. "International benchmarking and regulation: an application to European electricity distribution utilities," Energy Policy, Elsevier, vol. 31(15), pages 1609-1622, December.
  20. Simar, L., 1991. "Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with boot strapping," CORE Discussion Papers 1991026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  21. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  22. Bill Greene with Antonio Alvarez (Univ. of Oviedo) & Carlos Arias (Univ. of Leon), 2004. "Accounting For Unobservables In Production Models: Management And Inefficiency," Econometric Society 2004 Australasian Meetings 341, Econometric Society.
  23. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
  24. Andrew Street, 2003. "How much confidence should we place in efficiency estimates?," Health Economics, John Wiley & Sons, Ltd., vol. 12(11), pages 895-907.
  25. Uwe Jensen, 2000. "Is it efficient to analyse efficiency rankings?," Empirical Economics, Springer, vol. 25(2), pages 189-208.
  26. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
  27. Luis R. Murillo-Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, 02.
  28. Mehdi Farsi & Massimo Filippini, 2005. "A Benchmarking Analysis of Electricity Distribution Utilities in Switzerland," CEPE Working paper series 05-43, CEPE Center for Energy Policy and Economics, ETH Zurich.
  29. Nillesen , P.H.L. & Pollitt, M.G., 2004. "The Consequences for Consumer Welfare of the 2001-2003 Electricity Distribution Price Review in The Netherlands," Cambridge Working Papers in Economics 0446, Faculty of Economics, University of Cambridge.
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Citations

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Cited by:
  1. Astrid Cullmann, 2012. "Benchmarking and firm heterogeneity: a latent class analysis for German electricity distribution companies," Empirical Economics, Springer, vol. 42(1), pages 147-169, February.
  2. Anne-Kathrin Last & Heike Wetzel, 2010. "The efficiency of German public theaters: a stochastic frontier analysis approach," Journal of Cultural Economics, Springer, vol. 34(2), pages 89-110, May.
  3. Tooraj Jamasb & Magnus Söderberg, 2010. "The Effects of Average Norm Model Regulation: The Case of Electricity Distribution in Sweden," Review of Industrial Organization, Springer, vol. 36(3), pages 249-269, May.
  4. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.

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