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Using Regulatory Benchmarking Techniques to Set Company Performance Targets: The Case of Us Electricity

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  • P. Nillesen
  • M. Pollitt
Abstract
Consolidation in many sectors has lead to the formation of "groups of companies". Extracting all the potential cost savings from these independent or separate operating units is a challenge given asymmetric information. We develop a step-by-step approach that applies regulatory benchmarking techniques to set efficiency targets for operating units. Holding company management - like a regulator - will want to set targets to encourage efficient operation but in the absence of full information on effort, costs and environmental conditions. Our approach using the parallel with regulation incorporates issues such as measurement error and potential environmental factors that could influence the underlying efficiency score. We demonstrate the approach using data from the US electricity distribution sector and show that substantial savings can be extracted using this approach that was originally developed for regulatory purposes.

Suggested Citation

  • P. Nillesen & M. Pollitt, 2010. "Using Regulatory Benchmarking Techniques to Set Company Performance Targets: The Case of Us Electricity," Competition and Regulation in Network Industries, Intersentia, vol. 11(1), pages 50-85, March.
    • Handle: RePEc:sen:journl:v:11:i:1:y:2010:p:50-85
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    Cited by:

    1. Jamasb, T. & Orea, L. & Pollitt, M.G., 2010. "Weather Factors and Performance of Network Utilities: A Methodology and Application to Electricity Distribution," Cambridge Working Papers in Economics 1042, Faculty of Economics, University of Cambridge.
    2. William Yu & Tooraj Jamasb & Michael Pollitt, 2008. "Does Weather Explain the Cost and Quality? An Analysis of UK Electricity Distribution Companies," Working Papers EPRG 0827, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    3. Agrell, Per J. & Teusch, Jonas, 2020. "Predictability and strategic behavior under frontier regulation," Energy Policy, Elsevier, vol. 137(C).
    4. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    5. Paul Nillesen & Michael Pollitt, 2011. "Ownership Unbundling in Electricity Distribution: Empirical Evidence from New Zealand," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 38(1), pages 61-93, January.
    6. Pollitt, Michael G. & Steer, Steven J., 2012. "Economies of scale and scope in network industries: Lessons for the UK water and sewerage sectors," Utilities Policy, Elsevier, vol. 21(C), pages 17-31.
    7. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    8. 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.
    9. Anaya, Karim L. & Pollitt, Michael G., 2017. "Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1078-1094.
    10. Karim L. Anaya & Michael G. Pollitt, 2014. "Does Weather Have an Impact on Electricity Distribution Efficiency? Evidence from South America," Working Papers EPRG 1404, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    11. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    12. Hampf, Benjamin, 2018. "Cost and environmental efficiency of U.S. electricity generation: Accounting for heterogeneous inputs and transportation costs," Energy, Elsevier, vol. 163(C), pages 932-941.
    13. Vishal Chandr Jaunky and Lin Zhang, 2016. "Convergence of Operational Efficiency in Chinas Provincial Power Sectors," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    14. Sebastian Nick & Heike Wetzel, 2016. "The hidden cost of investment: the impact of adjustment costs on firm performance measurement and regulation," Journal of Regulatory Economics, Springer, vol. 49(1), pages 33-55, February.
    15. Haney, Aoife Brophy & Pollitt, Michael G., 2013. "International benchmarking of electricity transmission by regulators: A contrast between theory and practice?," Energy Policy, Elsevier, vol. 62(C), pages 267-281.
    16. Jaunky, Vishal Chandr, 2013. "Divergence in technical efficiency of electric utilities: Evidence from the SAPP," Energy Policy, Elsevier, vol. 62(C), pages 419-430.
    17. Rita, Rui & Marques, Vitor & Bárbara, Diogo & Chaves, Inês & Macedo, Pedro & Moutinho, Victor & Pereira, Mariana, 2023. "Crossing non-parametric and parametric techniques for measuring the efficiency: Evidence from 65 European electricity Distribution System Operators," Energy, Elsevier, vol. 283(C).

    More about this item

    JEL classification:

    • L98 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Government Policy
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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