UCL School of Management is delighted to welcome Francis de Vericourt, INSEAD, to host a research seminar discussing ‘Warning Against Recurring Risks: An Information Design Approach’.
The World Health Organization seeks eﬀective ways to alert its member states about global pandemics. Motivated by this challenge, we study a public agency’s problem of designing warning policies to mitigate potential disasters that occur with advance notice. The agency privately receives early information about recurring harmful events and issues warnings to induce an uninformed party to take costly preemptive actions. The agency’s decision about whether to issue a warning critically depends on its credibility, which we deﬁne as the uninformed party’s belief regarding the accuracy of the agency’s information. This belief is updated over time by comparing the agency’s warnings with the actual incidence of harmful events. The sender, therefore, faces a trade-oﬀ between eliciting a proper response today and maintaining her credibility in order to elicit responses to future adverse events. We formulate this problem as a dynamic Bayesian persuasion game, which we solve in closed form. We ﬁnd that the agency must be suﬃciently credible to elicit a mitigating action from the uninformed party for a given period. More importantly, the agency sometimes strategically misrepresents its advance information about a current threat in order to cultivate its future credibility. When its credibility is low (i.e., below a threshold), the agency downplays the risk and actually downplays more as its credibility improves. By contrast, when its credibility is high (i.e., above a second higher threshold), the agency sometimes exaggerates the threat. In this case, a less credible agency exaggerates more. Only when the agency’s credibility is moderate does it consistently send warning messages that fully disclose its private information about a potential disaster. These ﬁndings provide prescriptive guidelines for designing warning policies and suggest a plausible rationale for some of the false alarms or omissions observed in practice.