IDEAS home Printed from https://ideas.repec.org/a/wly/emetrp/v89y2021i6p2601-2635.html
   My bibliography  Save this article

Learning Dynamics in Social Networks

Author

Listed:
  • Simon Board
  • Moritz Meyer‐ter‐Vehn

Abstract

This paper proposes a tractable model of Bayesian learning on large random networks where agents choose whether to adopt an innovation. We study the impact of the network structure on learning dynamics and product diffusion. In directed networks, all direct and indirect links contribute to agents' learning. In comparison, learning and welfare are lower in undirected networks and networks with cliques. In a rich class of networks, behavior is described by a small number of differential equations, making the model useful for empirical work.

Suggested Citation

  • Simon Board & Moritz Meyer‐ter‐Vehn, 2021. "Learning Dynamics in Social Networks," Econometrica, Econometric Society, vol. 89(6), pages 2601-2635, November.
    • Handle: RePEc:wly:emetrp:v:89:y:2021:i:6:p:2601-2635
    DOI: 10.3982/ECTA18659
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/ECTA18659
    Download Restriction: no
    File URL: https://libkey.io/10.3982/ECTA18659?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
    ---><---

    References listed on IDEAS

    as
    1. Bramoulle, Yann & Galeotti, Andrea & Rogers, Brian (ed.), 2016. "The Oxford Handbook of the Economics of Networks," OUP Catalogue, Oxford University Press, number 9780199948277.
    2. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    3. Kenneth Hendricks & Alan Sorensen & Thomas Wiseman, 2012. "Observational Learning and Demand for Search Goods," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 1-31, February.
    4. Jing Cai & Adam Szeidl, 2018. "Interfirm Relationships and Business Performance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1229-1282.
    5. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    6. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    7. Abhijit V. Banerjee, 1993. "The Economics of Rumours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 309-327.
    8. 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.
    9. Ali, S. Nageeb, 2018. "Herding with costly information," Journal of Economic Theory, Elsevier, vol. 175(C), pages 713-729.
    10. Yann Bramoullé & Andrea Galeotti & Brian Rogers, 2016. "The Oxford Handbook of the Economics of Networks," Post-Print hal-03572533, HAL.
    11. Arthur Campbell, 2013. "Word-of-Mouth Communication and Percolation in Social Networks," American Economic Review, American Economic Association, vol. 103(6), pages 2466-2498, October.
    12. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    13. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    14. Bohren, Aislinn & Hauser, Daniel, 2017. "Learning with Heterogeneous Misspecified Models: Characterization and Robustness," CEPR Discussion Papers 12036, C.E.P.R. Discussion Papers.
    15. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    16. Erik Eyster & Matthew Rabin, 2014. "Extensive Imitation is Irrational and Harmful," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(4), pages 1861-1898.
    17. Monzón, Ignacio & Rapp, Michael, 2014. "Observational learning with position uncertainty," Journal of Economic Theory, Elsevier, vol. 154(C), pages 375-402.
    18. Chamley, Christophe & Gale, Douglas, 1994. "Information Revelation and Strategic Delay in a Model of Investment," Econometrica, Econometric Society, vol. 62(5), pages 1065-1085, September.
    19. J. Aislinn Bohren & Daniel N. Hauser, 2021. "Learning With Heterogeneous Misspecified Models: Characterization and Robustness," Econometrica, Econometric Society, vol. 89(6), pages 3025-3077, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    2. John Higgins & Tarun Sabarwal, 2023. "Control and spread of contagion in networks with global effects," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(6), pages 1149-1187, December.
    3. John Higgins & Tarun Sabarwal, 2021. "Control and Spread of Contagion in Networks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202201, University of Kansas, Department of Economics, revised Jan 2022.
    4. Julian Hidalgo & Michelle Sovinsky, 2023. "Internet (Power) to the People: How to Bridge the Digital Divide," CRC TR 224 Discussion Paper Series crctr224_2023_461, University of Bonn and University of Mannheim, Germany.
    5. Aloosh, Arash & Choi, Hyung-Eun & Ouzan, Samuel, 2023. "The tail wagging the dog: How do meme stocks affect market efficiency?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 68-78.

    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. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    2. Mira Frick & Ryota Iijima & Yuhta Ishii, 2018. "Dispersed Behavior and Perceptions in Assortative Societies," Cowles Foundation Discussion Papers 2128, Cowles Foundation for Research in Economics, Yale University.
    3. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    4. Sushil Bikhchandani & David Hirshleifer & Omer Tamuz & Ivo Welch, 2024. "Information Cascades and Social Learning," Journal of Economic Literature, American Economic Association, vol. 62(3), pages 1040-1093, September.
    5. Islam, Asadul & Ushchev, Philip & Zenou, Yves & Zhang, Xin, 2019. "The Value of Information in Technology Adoption," IZA Discussion Papers 12672, Institute of Labor Economics (IZA).
    6. Michel Grabisch & Agnieszka Rusinowska & Xavier Venel, 2019. "Diffusion in countably infinite networks," Documents de travail du Centre d'Economie de la Sorbonne 19017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2016. "Networks: An Economic Perspective," Papers 1608.07901, arXiv.org.
    8. Camilo García-Jimeno & Angel Iglesias & Pinar Yildirim, 2022. "Information Networks and Collective Action: Evidence from the Women's Temperance Crusade," American Economic Review, American Economic Association, vol. 112(1), pages 41-80, January.
    9. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    10. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    11. Tristan Gagnon-Bartsch & Antonio Rosato, 2024. "Quality Is in the Eye of the Beholder: Taste Projection in Markets with Observational Learning," American Economic Review, American Economic Association, vol. 114(11), pages 3746-3787, November.
    12. Arthur Campbell & C. Matthew Leister & Yves Zenou, 2020. "Word‐of‐mouth communication and search," RAND Journal of Economics, RAND Corporation, vol. 51(3), pages 676-712, September.
    13. Michel Grabisch & Agnieszka Rusinowska, 2020. "A Survey on Nonstrategic Models of Opinion Dynamics," Games, MDPI, vol. 11(4), pages 1-29, December.
    14. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Misinterpreting Others and the Fragility of Social Learning," Econometrica, Econometric Society, vol. 88(6), pages 2281-2328, November.
    15. Mira Frick & Yuhta Ishii, 2015. "Innovation Adoption by Forward-Looking Social Learners," Cowles Foundation Discussion Papers 1877, Cowles Foundation for Research in Economics, Yale University.
    16. Bing Han & David Hirshleifer & Johan Walden, 2023. "Visibility Bias in the Transmission of Consumption Beliefs and Undersaving," Journal of Finance, American Finance Association, vol. 78(3), pages 1647-1704, June.
    17. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Belief Convergence under Misspecified Learning: A Martingale Approach," Cowles Foundation Discussion Papers 2235R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2021.
    18. Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
    19. Mueller-Frank, Manuel, 2024. "As strong as the weakest node: The impact of misinformation in social networks," Journal of Economic Theory, Elsevier, vol. 215(C).
    20. Nikolas Tsakas, 2014. "Optimal influence under observational learning," Gecomplexity Discussion Paper Series 4, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.

    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:emetrp:v:89:y:2021:i:6:p:2601-2635. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.