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Updating Beliefs with Ambiguous Evidence: Implications for Polarization

Author

Listed:
  • Roland G. Fryer, Jr.
  • Philipp Harms
  • Matthew O. Jackson

Abstract

We introduce and analyze a model in which agents observe sequences of signals about the state of the world, some of which are ambiguous and open to interpretation. Instead of using Bayes' rule on the whole sequence, our decision makers use Bayes' rule in an iterative way: first to interpret each signal and then to form a posterior on the whole sequence of interpreted signals. This technique is computationally efficient, but loses some information since only the interpretation of the signals is retained and not the full signal. We show that such rules are optimal if agents sufficiently discount the future; while if they are very patient then a time-varying random interpretation rule becomes optimal. One of our main contributions is showing that the model provides a formal foundation for why agents who observe exactly the same stream of information can end up becoming increasingly polarized in their posteriors.

Suggested Citation

  • Roland G. Fryer, Jr. & Philipp Harms & Matthew O. Jackson, 2013. "Updating Beliefs with Ambiguous Evidence: Implications for Polarization," NBER Working Papers 19114, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19114
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    File URL: http://www.nber.org/papers/w19114.pdf
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    References listed on IDEAS

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    1. Fryer Roland & Jackson Matthew O., 2008. "A Categorical Model of Cognition and Biased Decision Making," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 8(1), pages 1-44, February.
    2. Joan Esteban & Debraj Ray, 2011. "Linking Conflict to Inequality and Polarization," American Economic Review, American Economic Association, vol. 101(4), pages 1345-1374, June.
    3. Edward L. Glaeser & Cass R. Sunstein, 2013. "Why Does Balanced News Produce Unbalanced Views?," NBER Working Papers 18975, National Bureau of Economic Research, Inc.
    4. Coate, Stephen & Loury, Glenn C, 1993. "Will Affirmative-Action Policies Eliminate Negative Stereotypes?," American Economic Review, American Economic Association, vol. 83(5), pages 1220-1240, December.
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    Citations

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    Cited by:

    1. Benoît, Jean-Pierre & Dubra, Juan, 2018. "When do populations polarize? An explanation," MPRA Paper 86173, University Library of Munich, Germany.
    2. McMurray, Joseph, 2017. "Voting as communicating: Mandates, multiple candidates, and the signaling voter's curse," Games and Economic Behavior, Elsevier, vol. 102(C), pages 199-223.
    3. Millner, Antony & Ollivier, Hélène & Simon, Leo, 2014. "Policy experimentation, political competition, and heterogeneous beliefs," Journal of Public Economics, Elsevier, vol. 120(C), pages 84-96.
    4. Stone, Daniel, 2018. ""Unmotivated Bias" and Partisan Hostility: Empirical Evidence," SocArXiv hr5ba, Center for Open Science.
    5. Benoît, Jean-Pierre & Dubra, Juan, 2014. "A Theory of Rational Attitude Polarization," MPRA Paper 60129, University Library of Munich, Germany.
    6. Nimark, Kristoffer P. & Sundaresan, Savitar, 2019. "Inattention and belief polarization," Journal of Economic Theory, Elsevier, vol. 180(C), pages 203-228.
    7. Stone, Daniel F., 2019. "“Unmotivated bias” and partisan hostility: Empirical evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 12-26.

    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

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