IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v17y1996i3p1-21.html

System Average Rates and Management Efficiency: A Statistical Benchmark Study of U.S. Investor-Owned Electric Utilities

Author

Listed:
  • Ernst R. Berndt
  • Roy Epstein
  • Michael J. Deane

Abstract

Proposals to restructure electric utilities have heightened interest in understanding what factors contribute to the variation in system average rates (SARs) across utilities. Direct comparisons of utilities' average rates have been used to assess management performance and the possibility of using mandatory restructuring to reduce rates. However, direct rate comparisons can lead to highly unreliable conclusions because they ignore the wide variety of regional, economic, and regulatory factors that affect rates across utilities. This paper presents a statistical benchmark study of SARs using 1984-93 data on 99 U.S. investor-owned utilities. The model is applied to evaluate the electric rates of three California investor-owned utilities. We find electric rates are affected to a large extent by factors outside the direct and immediate control of management. Controlling for these effects, there is no evidence that these California utilities, which have relatively high system average rates, suffer from poor management performance.

Suggested Citation

  • Ernst R. Berndt & Roy Epstein & Michael J. Deane, 1996. "System Average Rates and Management Efficiency: A Statistical Benchmark Study of U.S. Investor-Owned Electric Utilities," The Energy Journal, , vol. 17(3), pages 1-21, July.
  • Handle: RePEc:sae:enejou:v:17:y:1996:i:3:p:1-21
    DOI: 10.5547/ISSN0195-6574-EJ-Vol17-No3-1
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/ISSN0195-6574-EJ-Vol17-No3-1
    Download Restriction: no

    File URL: https://libkey.io/10.5547/ISSN0195-6574-EJ-Vol17-No3-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Baltagi, Badi H. & Li, Qi, 1992. "A monotonic property for iterative GLS in the two-way random effects model," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 45-51.
    2. Galbraith, John W. & Zinde-Walsh, Victoria, 1995. "Transforming the error-components model for estimation with general ARMA disturbances," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 349-355.
    3. repec:aen:journl:1992v13-04-a03 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qiu, Jin & Ma, Qing & Wu, Lang, 2019. "A moving blocks empirical likelihood method for panel linear fixed effects models with serial correlations and cross-sectional dependences," Economic Modelling, Elsevier, vol. 83(C), pages 394-405.
    2. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    3. Biorn, Erik & Hagen, Terje P. & Iversen, Tor & Magnussen, Jon, 2002. "The Effect of Activity-Based Financing on Hospital Efficiency: A Panel Data Analysis of DEA Efficiency Scores 1992-2000," MPRA Paper 8099, University Library of Munich, Germany.
    4. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    5. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2025. "Two-way random effects model with serial correlation," Empirical Economics, Springer, vol. 68(5), pages 2041-2072, May.
    6. Liangjun Su & Zhenlin Yang, 2008. "Asymptotics and Bootstrap for Transformed Panel Data Regressions," Development Economics Working Papers 22477, East Asian Bureau of Economic Research.
    7. Yuichi Goto & Koichi Arakaki & Yan Liu & Masanobu Taniguchi, 2023. "Homogeneity tests for one-way models with dependent errors under correlated groups," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 163-183, March.
    8. Badi H. Baltagi & Long Liu, 2020. "Forecasting with unbalanced panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 709-724, August.
    9. Biorn, Erik, 2004. "Regression systems for unbalanced panel data: a stepwise maximum likelihood procedure," Journal of Econometrics, Elsevier, vol. 122(2), pages 281-291, October.
    10. Paolo, Foschi, 2005. "Estimating regressions and seemingly unrelated regressions with error component disturbances," MPRA Paper 1424, University Library of Munich, Germany, revised 07 Sep 2006.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:sae:enejou:v:17:y:1996:i:3:p:1-21. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.