(Translated by https://www.hiragana.jp/)
An Improved Statistical Model for Multiparty Electoral Data
IDEAS home Printed from https://ideas.repec.org/p/clt/sswopa/1111.html
   My bibliography  Save this paper

An Improved Statistical Model for Multiparty Electoral Data

Author

Listed:
  • Honaker, James
  • Katz, Jonathan K.
  • King, Gary

Abstract

Katz and King (1999) develop a model for predicting or explaining aggregate electoral results in multiparty democracies. Their model is, in principle, analogous to what least squares regression provides American politics researchers in that two-party system. Katz and King applied their model to three-party elections in England and revealed a variety of new features of incumbency advantage and where each party pulls support from. Although the mathematics of their statistical model covers any number of political parties, it is computationally very demanding, and hence slow and numerically imprecise, with more than three. The original goal of our work was to produce an approximate method that works quicker in practice with many parties without making too many theoretical compromises. As it turns out, the method we offer here improves on Katz and King's (in bias, variance, numerical stability, and computational speed) even when the latter is computationally feasible. We also offer easy-to-use software that implements our suggestions.

Suggested Citation

  • Honaker, James & Katz, Jonathan K. & King, Gary, 2001. "An Improved Statistical Model for Multiparty Electoral Data," Working Papers 1111, California Institute of Technology, Division of the Humanities and Social Sciences.
    • Handle: RePEc:clt:sswopa:1111
    as

    Download full text from publisher

    File URL: http://www.hss.caltech.edu/SSPapers/wp1111.pdf
    Download Restriction: no
    ---><---

    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:clt:sswopa:1111. 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: Victoria Mason (email available below). General contact details of provider: http://www.hss.caltech.edu/ss .

    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.