IDEAS home Printed from https://ideas.repec.org/p/ris/ewikln/2010_003.html
   My bibliography  Save this paper

Efficiency effects of quality of service and environmental factors: experience from Norwegian electricity distribution

Author

Listed:
  • Growitsch, Christian

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Jamasb, Tooraj

    () (Faculty of Economics University of Cambridge)

  • Wetzel, Heike

    () (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

Abstract

Since the 1990s, efficiency and benchmarking analysis has increasingly been used in network utilities research and regulation. A recurrent concern is the effect of environmental factors that are beyond the influence of firms (observable heterogeneity) and factors that are not identifiable (unobserved heterogeneity) on measured cost and quality performance of firms. This paper analyses the effect of geographic and weather factors and unobserved heterogeneity on a set of 128 Norwegian electricity distribution utilities for the 2001-2004 period. We utilize data on almost 100 geographic and weather variables to identify real economic inefficiency while controlling for observable and unobserved heterogeneity. We use the factor analysis technique to reduce the number of environmental factors into few composite variables and to avoid the problem of multicollinearity. We then estimate the established stochastic frontier models of Battese and Coelli (1992; 1995) and the recent true fixed effects models of Greene (2004; 2005) without and with environmental variables. In the former models some composite environmental variables have a significant effect on the performance of utilities. These effects vanish in the true fixed effects models. However, the latter models capture the entire unobserved heterogeneity and therefore show significantly higher average efficiency scores.

Suggested Citation

  • Growitsch, Christian & Jamasb, Tooraj & Wetzel, Heike, 2010. "Efficiency effects of quality of service and environmental factors: experience from Norwegian electricity distribution," EWI Working Papers 2010-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2010_003
    as

    Download full text from publisher

    File URL: http://www.ewi.uni-koeln.de/fileadmin/user_upload/Publikationen/Working_Paper/EWI_WP_10-03_Norwegian-Electricity-Distribution.pdf
    File Function: Full text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, pages 28-45.
    3. Yu, William & Jamasb, Tooraj & Pollitt, Michael, 2009. "Does weather explain cost and quality performance? An analysis of UK electricity distribution companies," Energy Policy, Elsevier, vol. 37(11), pages 4177-4188, November.
    4. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, pages 7-32.
    5. Mehdi Farsi & Massimo Filippini, 2006. "An Analysis of Efficiency and Productivity in Swiss Hospitals," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 142(I), pages 1-37, March.
    6. Peter Lambert & Thor Thoresen, 2009. "Base independence in the analysis of tax policy effects: with an application to Norway 1992–2004," International Tax and Public Finance, Springer;International Institute of Public Finance, pages 219-252.
    7. William Greene, 2002. "Fixed and Random Effects in Stochastic Frontier Models," Working Papers 02-16, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, pages 233-238.
    9. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, pages 1095-1105.
    10. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, pages 69-90.
    11. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2006. "Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 95-118, January.
    12. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, pages 69-90.
    13. Jamasb, T. & Pollitt, M., 2000. "Benchmarking and regulation: international electricity experience," Utilities Policy, Elsevier, pages 107-130.
    14. Førsund, Finn R. & Kittelsen, Sverre A. C., 1998. "Productivity development of Norwegian electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 20(3), pages 207-224, September.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, pages 21-37.
    16. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, pages 269-303.
    17. Leland Gerson Neuberg, 1977. "Two Issues in the Municipal Ownership of Electric Power Distribution," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 303-323, Spring.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Efficiency; Quality of service; Input distance function; Stochastic frontier analysis;

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:ewikln:2010_003. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sabine Williams). General contact details of provider: http://edirc.repec.org/data/ewikode.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.