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Dynamic Information Acquisition from Multiple Sources

Author

Listed:
  • Annie Liang

    (Department of Economics, University of Pennsylvania)

  • Xiaosheng Mu

    (Department of Economics, Harvard University)

  • Vasilis Syrgkanis

    (Microsoft Research, New England)

Abstract

Consider a decision-maker who dynamically acquires Gaussian signals that are related by a completely flexible correlation structure. Such a setting describes information acquisition from news sources with correlated biases, as well as aggregation of complementary information from specialized sources. We study the optimal sequence of information acquisitions. Generically, myopic signal acquisitions turn out to be optimal at sufficiently late periods, and in classes of informational environments that we describe, they are optimal from period 1. These results hold independently of the decision problem and its (endogenous or exogenous) timing. We apply these results to characterize dynamic information acquisition in games.

Suggested Citation

  • Annie Liang & Xiaosheng Mu & Vasilis Syrgkanis, 2017. "Dynamic Information Acquisition from Multiple Sources," PIER Working Paper Archive 17-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2017.
    • Handle: RePEc:pen:papers:17-023
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    File URL: https://economics.sas.upenn.edu/sites/default/files/filevault/SSRN_17-023.pdf
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    References listed on IDEAS

    as
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    2. Antonio Cabrales & Olivier Gossner & Roberto Serrano, 2013. "Entropy and the Value of Information for Investors," American Economic Review, American Economic Association, vol. 103(1), pages 360-377, February.
    3. Christian Hellwig & Laura Veldkamp, 2009. "Knowing What Others Know: Coordination Motives in Information Acquisition," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 223-251.
    4. Sébastien Bubeck & Rémi Munos & Gilles Stoltz, 2010. "Pure Exploration for Multi-Armed Bandit Problems," Working Papers hal-00257454, HAL.
    5. 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.
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    Cited by:

    1. Carlos Segura-Rodriguez, "undated". "Higher Order Information Complementarities and Polarization," PIER Working Paper Archive 19-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Annie Liang & Xiaosheng Mu, 2018. "Overabundant Information and Learning Traps," PIER Working Paper Archive 18-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 27 Mar 2018.

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