IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v61y2020i1p189-217.html
   My bibliography  Save this article

Just A Big Misunderstanding? Bias And Bayesian Affective Polarization

Author

Listed:
  • Daniel F. Stone

Abstract

I present a model of affective polarization—growth in hostility over time between two parties—via quasi‐Bayesian inference. In the model, two agents repeatedly choose actions. Each choice is based on a balance of concerns for private interests and the social good. More weight is put on private interests when an agent's character is intrinsically more self‐serving and when the other agent is believed to be more self‐serving. Each agent Bayesian updates about the other's character, and dislikes the other more when she is perceived as more self‐serving. I characterize the effects on growth in dislike of three biases: a prior bias against the other agent's character, the false consensus bias, and limited strategic thinking. Prior bias against the other's character remains constant or declines over time, and actions do not diverge. The other two biases cause actions to become more extreme over time and repeatedly be “worse” than expected, causing mutual growth in dislike, that is, affective polarization. The magnitude of dislike can become arbitrarily large—even when both players are arbitrarily “good” (unselfish). The results imply that seemingly irrelevant cognitive biases can be an important cause of the devolution of relationships, in politics and beyond, and that subtlety and unawareness of bias can be key factors driving the degree of polarization.

Suggested Citation

  • Daniel F. Stone, 2020. "Just A Big Misunderstanding? Bias And Bayesian Affective Polarization," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(1), pages 189-217, February.
  • Handle: RePEc:wly:iecrev:v:61:y:2020:i:1:p:189-217
    DOI: 10.1111/iere.12421
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12421
    Download Restriction: no

    File URL: https://libkey.io/10.1111/iere.12421?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
    ---><---

    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:wly:iecrev:v:61:y:2020:i:1:p:189-217. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    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.