IDEAS home Printed from https://ideas.repec.org/a/bpj/bejtec/v11y2011i1n1.html
   My bibliography  Save this article

Network Architecture and the Left-Right Spectrum

Author

Listed:
  • Taubinsky Dmitry

    (Harvard University and Harvard Business School, taubinsk@fas.harvard.edu)

Abstract

We study a model of opinion formation and analyze the link between network architecture and the “left-right spectrum” that frequently characterizes opinions and beliefs. We correct a key result of DeMarzo, Vayanos and Zwiebel (QJE, 2003) who claim that after some time, an agent’s position on a set of different issues will always be either “left” on all of those issues or “right” on all of those issues. We provide counterexamples to this claim and show that in the long-run an agent’s position can flip-flop between “left” on all issues and “right” on all issues indefinitely. However, we provide necessary and sufficient conditions for a stable left-right characterization of opinions to be possible in the long run. Roughly, a flip-flop will occur when agents give relatively little weight to the opinions of agents with similar political positions (including themselves). Following this intuition, we show that a simple sufficient condition is that agents become “stubborn” over time and give little weight to the opinions of others. Finally, we characterize classes of networks in which it is possible for agents to flip-flop between “left” and “right” indefinitely. We argue that qualitatively, these results are robust to alternative models of opinion formation.

Suggested Citation

  • Taubinsky Dmitry, 2011. "Network Architecture and the Left-Right Spectrum," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 11(1), pages 1-25, February.
    • Handle: RePEc:bpj:bejtec:v:11:y:2011:i:1:n:1
    DOI: 10.2202/1935-1704.1742
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1935-1704.1742
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1935-1704.1742?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.

    References listed on IDEAS

    as
    1. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    2. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 37-82.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gabriel Martinez & Nicholas H. Tenev, 2020. "Optimal Echo Chambers," Papers 2010.01249, arXiv.org, revised Jun 2025.
    2. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    3. Cheng, Ing-Haw & Hsiaw, Alice, 2022. "Distrust in experts and the origins of disagreement," Journal of Economic Theory, Elsevier, vol. 200(C).
    4. Delavande, Adeline & Zafar, Basit, 2018. "Information and anti-American attitudes," Journal of Economic Behavior & Organization, Elsevier, vol. 149(C), pages 1-31.
    5. Jiao, Peiran & Veiga, André & Walther, Ansgar, 2020. "Social media, news media and the stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 63-90.
    6. Bohren, J. Aislinn, 2016. "Informational herding with model misspecification," Journal of Economic Theory, Elsevier, vol. 163(C), pages 222-247.
    7. Bogaçhan Çelen & Sen Geng & Huihui Li, 2018. "Belief Error and Non-Bayesian Social Learning: An Experimental Evidence," GRU Working Paper Series GRU_2018_022, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    8. Fernandes, Marcos R., 2023. "Confirmation bias in social networks," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 59-76.
    9. Minardi, Stefania & Savochkin, Andrei, 2019. "Subjective contingencies and limited Bayesian updating," Journal of Economic Theory, Elsevier, vol. 183(C), pages 1-45.
    10. Gallo, E. & Langtry, A., 2020. "Social Networks, Confirmation Bias and Shock Elections," Cambridge Working Papers in Economics 2099, Faculty of Economics, University of Cambridge.
    11. López-Pérez, Raúl & Pintér, Ágnes & Sánchez-Mangas, Rocío, 2022. "Some conditions (not) affecting selection neglect: Evidence from the lab," Journal of Economic Behavior & Organization, Elsevier, vol. 195(C), pages 140-157.
    12. Edoardo Gallo & Alastair Langtry, 2020. "Social networks, confirmation bias and shock elections," Papers 2011.00520, arXiv.org.
    13. Bobba, Matteo & Frisancho, Veronica, 2022. "Self-perceptions about academic achievement: Evidence from Mexico City," Journal of Econometrics, Elsevier, vol. 231(1), pages 58-73.
    14. Joshua Schwartzstein & Adi Sunderam, 2021. "Using Models to Persuade," American Economic Review, American Economic Association, vol. 111(1), pages 276-323, January.
    15. 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.
    16. Philippe Jehiel & Jakub Steiner, 2020. "Selective Sampling with Information-Storage Constraints [On interim rationality, belief formation and learning in decision problems with bounded memory]," The Economic Journal, Royal Economic Society, vol. 130(630), pages 1753-1781.
    17. Guglielmo Zappalà, 2023. "Drought Exposure and Accuracy: Motivated Reasoning in Climate Change Beliefs," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 85(3), pages 649-672, August.
    18. Benjamin Enke & Florian Zimmermann, 2019. "Correlation Neglect in Belief Formation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 313-332.
    19. Schnellenbach, Jan & Schubert, Christian, 2015. "Behavioral political economy: A survey," European Journal of Political Economy, Elsevier, vol. 40(PB), pages 395-417.
    20. Urs Fischbacher & Simeon Schudy, 2014. "Reciprocity and resistance to comprehensive reform," Public Choice, Springer, vol. 160(3), pages 411-428, September.

    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:bpj:bejtec:v:11:y:2011:i:1:n:1. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.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.