IDEAS home Printed from https://ideas.repec.org/h/spr/stcchp/978-3-030-48598-6_2.html
   My bibliography  Save this book chapter

Analyzing the Probability of Election Outcomes with Abstentions

In: Evaluating Voting Systems with Probability Models

Author

Listed:
  • William V. Gehrlein

    (University of Delaware)

  • Dominique Lepelley

    (University of La Réunion)

Abstract

Earlier analysis considered the coincidence probability for the Condorcet Winners from preference rankings of possible voters and of participating voters when abstention is allowed. The probability of non-coincidence becomes quite high for low voter participation rates with independent voters’ preferences. Pessimistic results were also found under the same conditions for both the Condorcet Efficiency and the probability of observing a Borda Paradox with some common single-stage voting rules. Two options are considered to reverse these negative results. The first adds dependence among voters’ preferences with a commonly used model. The second uses the single-stage voting rules as the basis for two-stage elimination election procedures. Both options are found to make things worse for all voting rules with low voter participation rates. The same negative outcome is also observed for Approval Voting when some voter indifference between candidates is allowed. These preliminary results are valid, but what they are actually found to be showing is that very bad results can be expected for all voting rules when statistical dependence exists among abstaining voters, particularly for low voter participation rates. If a model requires that voters choose to abstain independently, then the addition of dependence among the possible voters’ preferences significantly improves the very negative outcomes that were initially observed.

Suggested Citation

  • William V. Gehrlein & Dominique Lepelley, 2021. "Analyzing the Probability of Election Outcomes with Abstentions," Studies in Choice and Welfare, in: Mostapha Diss & Vincent Merlin (ed.), Evaluating Voting Systems with Probability Models, pages 15-53, Springer.
  • Handle: RePEc:spr:stcchp:978-3-030-48598-6_2
    DOI: 10.1007/978-3-030-48598-6_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    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:spr:stcchp:978-3-030-48598-6_2. 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.

    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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.