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Entropy-Regularized Optimal Transport in Information Design

Author

Listed:
  • Jorge Justiniano

    (University of Bonn)

  • Andreas Kleiner

    (University of Bonn)

  • Benny Moldovanu

    (University of Bonn)

  • Martin Rumpf

    (University of Bonn)

  • Philipp Strack

    (Yale University)

Abstract

In this paper, we explore a scenario where a sender provides an information policy and a receiver, upon observing a realization of this policy, decides whether to take a particular action, such as making a purchase. The senderÕs objective is to maximize her utility derived from the receiverÕs action, and she achieves this by careful selection of the information policy. Building on the work of Kleiner et al., our focus lies specifically on information policies that are associated with power diagram partitions of the underlying domain. To address this problem, we employ entropy-regularized optimal transport, which enables us to develop an efficient algorithm for finding the optimal solution. We present experimental numerical results that highlight the qualitative properties of the optimal configurations, providing valuable insights into their structure. Furthermore, we extend our numerical investigation to derive optimal information policies for monopolists dealing with multiple products, where the sender discloses information about product qualities.

Suggested Citation

  • Jorge Justiniano & Andreas Kleiner & Benny Moldovanu & Martin Rumpf & Philipp Strack, 2024. "Entropy-Regularized Optimal Transport in Information Design," Cowles Foundation Discussion Papers 2419, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2419
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    File URL: https://cowles.yale.edu/sites/default/files/2025-01/d2419.pdf
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    References listed on IDEAS

    as
    1. Arieli, Itai & Babichenko, Yakov & Smorodinsky, Rann & Yamashita, Takuro, 2023. "Optimal persuasion via bi-pooling," Theoretical Economics, Econometric Society, vol. 18(1), January.
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