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The Potential for Segmentation of the Retail Market for Electricity in Ireland

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  • Hyland, Marie
  • Leahy, Eimear
  • Tol, Richard S. J.

Abstract

We estimate the gross margin that is earned from the supply of electricity to households in Ireland. Using half hourly electricity demand data, the system marginal price (also called the wholesale price) and the retail price of electricity, we analyse how the gross margin varies across customers with different characteristics. The wholesale price varies throughout the day, thus, the time at which electricity is used affects the gross margin. The main factor in determining gross margin, however, is demand. The highest gross margins are earned from supplying customers that have the following characteristics: being aged between 46 and 55, having a household income of at least ?75,000 per annum, being self?employed, having a third level education, having a professional or managerial occupation, living in a household with 7 or more people, living in a detached house, having at least 5 bedrooms or being a mortgage holder. An OLS regression shows that gross margin is partly explained by the energy conservation measures which are present in a household, the number of household members, the number of bedrooms, income, age, occupation and accommodation type.

Suggested Citation

  • Hyland, Marie & Leahy, Eimear & Tol, Richard S. J., 2012. "The Potential for Segmentation of the Retail Market for Electricity in Ireland," Papers WP433, Economic and Social Research Institute (ESRI).
    • Handle: RePEc:esr:wpaper:wp433
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    Cited by:

    1. Dutta, Goutam & Mitra, Krishnendranath, 2015. "Dynamic Pricing of Electricity: A Survey of Related Research," IIMA Working Papers WP2015-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Adam Konto Kyari & Labaran Mohammed Lawal, 2021. "An Empirical Enquiry into Stakeholders Perception of Electricity Pricing Methodology," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 75-82.
    3. Mulder, M. & Willems, Bert, 2016. "Competition in Retail Electricity Markets : An Assessment of Ten Years Dutch Experience," Discussion Paper 2016-011, Tilburg University, Tilburg Law and Economic Center.
    4. Robert Thomas, Daniel & Agrawal, Shalu & Harish, S.P. & Mahajan, Aseem & Urpelainen, Johannes, 2020. "Understanding segmentation in rural electricity markets: Evidence from India," Energy Economics, Elsevier, vol. 87(C).
    5. Simeone, Christina E. & Lange, Ian & Gilbert, Ben, 2023. "Pass-through in residential retail electricity competition: Evidence from Pennsylvania," Utilities Policy, Elsevier, vol. 80(C).
    6. Goutam Dutta & Krishnendranath Mitra, 2017. "A literature review on dynamic pricing of electricity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1131-1145, October.
    7. Fu, Xin & Zeng, Xiao-Jun & Feng, Pengpeng & Cai, Xiuwen, 2018. "Clustering-based short-term load forecasting for residential electricity under the increasing-block pricing tariffs in China," Energy, Elsevier, vol. 165(PB), pages 76-89.
    8. Oggioni, Giorgia & Schwartz, Alexandra & Wiertz, Ann-Kathrin & Zöttl, Gregor, 2024. "Dynamic pricing and strategic retailers in the energy sector: A multi-leader-follower approach," European Journal of Operational Research, Elsevier, vol. 312(1), pages 255-272.
    9. Gosnell, Greer & McCoy, Daire, 2023. "Market failures and willingness to accept smart meters: Experimental evidence from the UK," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).

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    data/education/electricity/Ireland/regression;

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