G2TT
来源类型Discussion paper
规范类型论文
来源IDDP15017
DP15017 Preparing for the Worst But Hoping for the Best: Robust (Bayesian) Persuasion
Piotr Dworczak; Alessandro Pavan
发表日期2020-07-08
出版年2020
语种英语
摘要We propose a robust solution concept for Bayesian persuasion that accounts for the Sender’s ambiguity over (i) the exogenous sources of information the Receivers may learn from, and (ii) the way the Receivers play (when multiple strategy profiles are consistent with the assumed solution concept and the available information). The Sender proceeds in two steps. First, she identifies all information structures that yield the largest payoff in the “worst-case scenario,” i.e., when Nature provides information and coordinates the Receivers’ play to minimize the Sender’s payoff. Second, she picks an information structure that, in case Nature and the Receivers play favorably to her, maximizes her expected payoff over all information structures that are “worst-case optimal.” We characterize properties of robust solutions, identify conditions under which robustness requires separation of certain states, and qualify in what sense robustness calls for more information disclosure than standard Bayesian persuasion. Finally, we discuss how some of the results in the Bayesian persuasion literature change once robustness is accounted for.
主题Industrial Organization
关键词Persuasion Information design Robustness Worst-case optimality
URLhttps://cepr.org/publications/dp15017
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/543966
推荐引用方式
GB/T 7714
Piotr Dworczak,Alessandro Pavan. DP15017 Preparing for the Worst But Hoping for the Best: Robust (Bayesian) Persuasion. 2020.
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