IDEAS home Printed from
   My bibliography  Save this paper

Perfect Competition vs. Riskaverse Agents: Technology Portfolio Choice in Electricity Markets


  • Malte Sundkötter
  • Daniel Ziegler

    (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen)


Investments in power generation assets are risky due to high construction costs and long asset lifetimes. Technology diversification in generation portfolios represents one option to reduce long-term investment risks for risk-averse decision makers. In this article, we analyze the impact of market imperfections induced by risk-aversion on the long-term investment portfolio structure in the market. We show that risk-averse electricity market agents who receive a managerial profit share may shift the technology structure in the market significantly away from the welfare optimum. A numerical example provides estimates on the potential scale of this effect and discusses sensitivities of key parameters.

Suggested Citation

  • Malte Sundkötter & Daniel Ziegler, 2013. "Perfect Competition vs. Riskaverse Agents: Technology Portfolio Choice in Electricity Markets," EWL Working Papers 1303, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Apr 2013.
  • Handle: RePEc:dui:wpaper:1303

    Download full text from publisher

    File URL:
    File Function: First Version, 2013
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.

    More about this item


    Nodal Pricing; Market Design; Electricity Markets;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:dui:wpaper:1303. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    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.

    We have no bibliographic references for this item. You can help adding them by using 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: Andreas Fritz (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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.