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Public Disagreement

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  • Rajiv Sethi

    (Department of Economics, Barnard College, Columbia University and Institute for Advanced Study)

  • Muhamet Yildiz

    (Department of Economics, MIT and Institute for Advanced Study)

Abstract

Members of different social groups often hold widely divergent public beliefs regarding the nature of the world in which they live. We develop a model that can accommodate such public disagreement, and use it to explore questions concerning the aggregation of distributed information and the consequences of social integration. The model involves heterogeneous priors, private information, and repeated communication until beliefs become public information. We show that when priors are correlated, all private information is eventually aggregated and public beliefs are identical to those arising under observable priors. When priors are independently distributed, however, some private information is never revealed and the expected value of public disagreement is greater when priors are unobservable than when they are observable. If the number of individuals is large, communication breaks down entirely in the sense that disagreement in public beliefs is approximately equal to disagreement in prior beliefs. Interpreting integration in terms of the observability of priors, we show how increases in social integration can give rise to less divergent public beliefs on average. Communication in segregated societies can cause initial biases to be amplified and new biases to emerge where none previously existed. Even though all announcements are public and all signals equally precise, minority group members face a disadvantage in the interpretation of public information that results in medium run beliefs that are less closely aligned with the true state.

Suggested Citation

  • Rajiv Sethi & Muhamet Yildiz, 2009. "Public Disagreement," Economics Working Papers 0089, Institute for Advanced Study, School of Social Science.
  • Handle: RePEc:ads:wpaper:0089
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    References listed on IDEAS

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    Cited by:

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    2. Rodrik, Dani & Ash, Elliott & Mukand, Sharun, 2021. "Economic Interests, Worldviews, and Identities: Theory and Evidence on Ideational Politics," CEPR Discussion Papers 16699, C.E.P.R. Discussion Papers.
    3. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    4. Alonso, Ricardo & Câmara, Odilon, 2016. "Bayesian persuasion with heterogeneous priors," Journal of Economic Theory, Elsevier, vol. 165(C), pages 672-706.
    5. Wolfgang Kuhle, 2013. "A Global Game with Heterogenous Priors," Papers 1312.7860, arXiv.org.
    6. Azomahou, T. & Opolot, D., 2014. "Beliefs dynamics in communication networks," MERIT Working Papers 2014-034, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    7. George J. Mailath & Larry Samuelson, 2020. "Learning under Diverse World Views: Model-Based Inference," American Economic Review, American Economic Association, vol. 110(5), pages 1464-1501, May.
    8. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    9. Rajiv Sethi & Jennifer Wortman Vaughan, 2016. "Belief Aggregation with Automated Market Makers," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 155-178, June.
    10. Stone, Daniel, 2018. "Just a big misunderstanding? Bias and Bayesian affective polarization," SocArXiv 58sru, Center for Open Science.
    11. Gieczewski, Germán, 2022. "Verifiable communication on networks," Journal of Economic Theory, Elsevier, vol. 204(C).
    12. Daniel F. Stone, 2016. "A few bad apples: Communication in the presence of strategic ideologues," Southern Economic Journal, John Wiley & Sons, vol. 83(2), pages 487-500, October.
    13. Edward D. Van Wesep, 2016. "The Quality of Expertise," Management Science, INFORMS, vol. 62(10), pages 2937-2951, October.
    14. Gabriel Martinez & Nicholas H. Tenev, 2020. "Optimal Echo Chambers," Papers 2010.01249, arXiv.org, revised Feb 2024.

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    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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