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Optimal Dynamic Information Provision


  • Renault, Jérôme
  • Solan, Eilon
  • Vieille, Nicolas


We study a dynamic model of information provision. A state of nature evolves according to a Markov chain. An advisor with commitment power decides how much information to provide to an uninformed decision maker, so as to influence his short-term decisions. We deal with a stylized class of situations, in which the decision maker has a risky action and a safe action, and the payoff to the advisor only depends on the action chosen by the decision maker. The greedy disclosure policy is the policy which, at each round, minimizes the amount of information being disclosed in that round, under the constraint that it maximizes the current payoff of the advisor. We prove that the greedy policy is optimal in many cases – but not always.

Suggested Citation

  • Renault, Jérôme & Solan, Eilon & Vieille, Nicolas, 2017. "Optimal Dynamic Information Provision," TSE Working Papers 17-749, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:31316

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    Cited by:

    1. Xu, Hedong & Tian, Cunzhi & Ye, Wenxing & Fan, Suohai, 2018. "Effects of investors’ power correlations in the power-based game on networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 424-432.
    2. Wei Zhao & Claudio Mezzetti & Ludovic Renou & Tristan Tomala, 2020. "Contracting over persistent information," Papers 2007.05983,
    3. Xu, Hedong & Fan, Suohai & Tian, Cunzhi & Xiao, Xinrong, 2019. "Evolutionary investor sharing game on networks," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 138-145.
    4. Deepanshu Vasal, 2020. "Dynamic information design," Papers 2005.07267,
    5. Ashkenazi-Golan, Galit & Rainer, Catherine & Solan, Eilon, 2020. "Solving two-state Markov games with incomplete information on one side," Games and Economic Behavior, Elsevier, vol. 122(C), pages 83-104.
    6. Xu, Hedong & Tian, Cunzhi & Xiao, Xinrong & Fan, Suohai, 2018. "Evolutionary investors’ power-based game on networks," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 125-133.
    7. Aditya Aradhye & J'anos Flesch & Mathias Staudigl & Dries Vermeulen, 2020. "Incentive compatibility in sender-receiver stopping games," Papers 2004.01910,

    More about this item


    Dynamic information provision; optimal strategy; greedy algorithm; commitment;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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