IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v55y2020i1d10.1007_s10614-018-9871-0.html
   My bibliography  Save this article

Comments on “Opinion Dynamics Driven by Various Ways of Averaging”

Author

Listed:
  • Youzong Xu

    (Xi’an Jiaotong-Liverpool University)

  • Yunfei Cao

    (Beijing Institute of Technology
    Beijing Institute of Technology)

Abstract

The two main findings in Hegselmann and Krause (Comput Econ 25:381–405, 2005), the theorem on opinion stabilization and the corollary on consensus formation, are built on partial abstract means (PAMs) with bounded confidence sets that are assumed to be continuous. However, we show that any PAM with bounded confidence sets cannot be continuous. The discontinuity of such PAMs threatens the validity of the main findings in Hegselmann and Krause (Comput Econ 25:381–405, 2005). Moreover, the condition that the corollary on consensus formation considers necessary and sufficient, under which agents will approach a consensus, is, in fact, not a sufficient condition. To resolve these issues, we provide a sufficient condition for PAMs with bounded confidence sets under which the theorem on opinion stabilization becomes valid. We also show that under this condition the condition in the corollary on consensus formation is necessary condition for agents to approach a consensus.

Suggested Citation

  • Youzong Xu & Yunfei Cao, 2020. "Comments on “Opinion Dynamics Driven by Various Ways of Averaging”," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 303-326, January.
    • Handle: RePEc:kap:compec:v:55:y:2020:i:1:d:10.1007_s10614-018-9871-0
    DOI: 10.1007/s10614-018-9871-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-018-9871-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-018-9871-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Loretta Mastroeni & Maurizio Naldi & Pierluigi Vellucci, 2023. "Personal Finance Decisions with Untruthful Advisors: An Agent-Based Model," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1477-1522, April.

    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:kap:compec:v:55:y:2020:i:1:d:10.1007_s10614-018-9871-0. 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.