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Complementary Information and Learning Traps

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  • Annie Liang
  • Xiaosheng Mu

Abstract

We develop a model of social learning from complementary information: short-lived agents sequentially choose from a large set of flexibly correlated information sources for prediction of an unknown state, and information is passed down across periods. Will the community collectively acquire the best kinds of information? Long-run outcomes fall into one of two cases: (i) efficient information aggregation, where the community eventually learns as fast as possible; (ii) “learning traps,” where the community gets stuck observing suboptimal sources and information aggregation is inefficient. Our main results identify a simple property of the underlying informational complementarities that determines which occurs. In both regimes, we characterize which sources are observed in the long run and how often.

Suggested Citation

  • Annie Liang & Xiaosheng Mu, 2020. "Complementary Information and Learning Traps," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(1), pages 389-448.
  • Handle: RePEc:oup:qjecon:v:135:y:2020:i:1:p:389-448.
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    File URL: http://hdl.handle.net/10.1093/qje/qjz033
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    Cited by:

    1. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299, Cowles Foundation for Research in Economics, Yale University.
    2. Alessandro Lizzeri & Eran Shmaya & Leeat Yariv, 2024. "Disentangling Exploration from Exploitation," Papers 2404.19116, arXiv.org.
    3. Istipliler, Baris & Ahrens, Jan-Philipp & Bort, Suleika & Isaak, Andrew, 2023. "Is exposure to the family firm always good for the next CEO? How successor pre-succession firm experience affects post-succession performance in family firms," Journal of Business Research, Elsevier, vol. 167(C).
    4. Simone Cerreia-Vioglio & Roberto Corrao & Giacomo Lanzani, 2020. "Robust Opinion Aggregation and its Dynamics," Working Papers 662, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    5. Aleksei Smirnov & Egor Starkov, 2024. "Designing Social Learning," Papers 2405.05744, arXiv.org, revised May 2024.
    6. Bobkova, Nina & Mass, Helene, 2022. "Two-dimensional information acquisition in social learning," Journal of Economic Theory, Elsevier, vol. 202(C).
    7. Mats Köster & Paul Voss, 2023. "Conversations," CESifo Working Paper Series 10275, CESifo.
    8. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R2, Cowles Foundation for Research in Economics, Yale University, revised Jul 2022.

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