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

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  • 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
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    References listed on IDEAS

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    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, September.
    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.
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