IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v38y2017i2p175-200.html
   My bibliography  Save this article

Is Productivity Growth in Electricity Distribution Negative? An Empirical Analysis Using Ontario Data

Author

Listed:
  • Dimitrios Dimitropoulos
  • Adonis Yatchew

Abstract

Electricity industries are experiencing upward cost pressures in many parts of the world. This paper focuses on productivity trends in electricity distribution. We apply two methodologies for estimating productivity growth—an index based approach, and an econometric cost based approach—to data on 73 Ontario distributors for the period 2002 to 2012. The resulting productivity growth estimates are approximately -1% per year, suggesting a reversal of the positive estimates that have generally been reported in previous periods. We implement flexible semi-parametric specifications to assess the robustness of these conclusions and discuss the use of such statistical analyses for calibrating productivity and relative efficiency within a price-cap framework.

Suggested Citation

  • Dimitrios Dimitropoulos & Adonis Yatchew, 2017. "Is Productivity Growth in Electricity Distribution Negative? An Empirical Analysis Using Ontario Data," The Energy Journal, , vol. 38(2), pages 175-200, March.
    • Handle: RePEc:sae:enejou:v:38:y:2017:i:2:p:175-200
    DOI: 10.5547/01956574.38.2.ddim
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.38.2.ddim
    Download Restriction: no
    File URL: https://libkey.io/10.5547/01956574.38.2.ddim?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. Toru Hattori & Tooraj Jamasb & Michael Pollitt, 2005. "Electricity Distribution in the UK and Japan: A Comparative Efficiency Analysis 1985-1998," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-48.
    2. Irastorza, Veronica, 2003. "Benchmarking for Distribution Utilities: A Problematic Approach to Defining Efficiency," The Electricity Journal, Elsevier, vol. 16(10), pages 30-38, December.
    3. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521812832.
    4. Yatchew, Adonis & Sun, Yiguo & Deri, Catherine, 2003. "Efficient Estimation of Semiparametric Equivalence Scales with Evidence from South Africa," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 247-257, April.
    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. Dimitri Dimitropoulos and Adonis Yatchew, 2017. "Is Productivity Growth in Electricity Distribution Negative? An Empirical Analysis Using Ontario Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    2. Timothy K.M. Beatty & Erling Røed Larsen, 2005. "Using Engel curves to estimate bias in the Canadian CPI as a cost of living index," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(2), pages 482-499, May.
    3. Alex Sienaert, 2008. "Some Child Cost Estimates for South Africa," Economics Series Working Papers WPS/2008-15, University of Oxford, Department of Economics.
    4. Syed Abul Hasan, 2016. "Engel curves and equivalence scales for Bangladesh," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(2), pages 301-315, April.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    6. Almeida, Alexandre N. & Bravo-Ureta, Boris E., 2019. "Agricultural productivity, shadow wages and off-farm labor decisions in Nicaragua," Economic Systems, Elsevier, vol. 43(1), pages 99-110.
    7. Luis Orea, Inmaculada C. Álvarez, and Tooraj Jamasb, 2018. "A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in Norway," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    8. 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.
    9. SCHAFGANS, Marcia M.A. & ZINDE-WALSH, Victoria, 2007. "Robust Average Derivative Estimation," Cahiers de recherche 12-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    10. Zhang, Xiaobei & Wang, Xiaojun, 2021. "Measures of human capital and the mechanics of economic growth," China Economic Review, Elsevier, vol. 68(C).
    11. repec:ebl:ecbull:v:3:y:2005:i:11:p:1-10 is not listed on IDEAS
    12. Ye, Yuxiang & Koch, Steven F., 2021. "Measuring energy poverty in South Africa based on household required energy consumption," Energy Economics, Elsevier, vol. 103(C).
    13. Vincenzo Verardi, 2013. "Semiparametric regression in Stata," United Kingdom Stata Users' Group Meetings 2013 14, Stata Users Group.
    14. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    15. Lee, Jungyoon & Robinson, Peter M., 2016. "Series estimation under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 190(1), pages 1-17.
    16. Muhammad Shafiullah & Zhilun Jiao & Muhammad Shahbaz & Kangyin Dong, 2023. "Examining energy poverty in Chinese households: An Engel curve approach," Australian Economic Papers, Wiley Blackwell, vol. 62(1), pages 149-184, March.
    17. Akdeniz Duran, Esra & Härdle, Wolfgang Karl & Osipenko, Maria, 2012. "Difference based ridge and Liu type estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 164-175.
    18. Thanasis Stengos & Yiguo Sun & Dianqin Wang, 2006. "Estimates of semiparametric equivalence scales," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 629-639, July.
    19. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    20. Michael Lokshin, 2006. "Difference-based semiparametric estimation of partial linear regression models," Stata Journal, StataCorp LP, vol. 6(3), pages 377-383, September.
    21. Bravo, Francesco & Chu, Ba M. & Jacho-Chávez, David T., 2017. "Generalized empirical likelihood M testing for semiparametric models with time series data," Econometrics and Statistics, Elsevier, vol. 4(C), pages 18-30.

    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:38:y:2017:i:2:p:175-200. 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.