Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/302246 
Year of Publication: 
2024
Series/Report no.: 
ISER Discussion Paper No. 1247
Publisher: 
Osaka University, Institute of Social and Economic Research (ISER), Osaka
Abstract: 
We consider a dynamic model in which a principal decides what information to release about a product of unknown quality (e.g., a vaccine) to incentivize agents to experiment with the product. Assuming that the agents are long-lived and forward-looking, their incentive to wait and see other agents' experiences poses a significant obstacle to social learning. We show that the optimal feedback mechanism to mitigate information free-riding takes a strikingly simple form: the principal recommends adoption as long as she observes no bad news, but only with some probability; once she does not recommend at some point, she stays silent forever after that. Our analysis suggests the optimality of premature termination, which in turn implies that: (i) false positives (termination in the good state) are more acceptable than false negatives (continuation in the bad state); (ii) overly cautious mechanisms that are biased toward termination can be welfare-enhancing.
Subjects: 
strategic experimentation
information design
free-rider problem
social learning
COVID-19 pandemic
JEL: 
D82
D83
Document Type: 
Working Paper

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