Dynamic information acquisition under ambiguity

More on Sarah Auster

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*Joint with Yeon-Koo Che and Konrad Mierendorff

Abstract:  "The paper studies sequential information acquisition under ambiguity about the relevant states in a setting where an agent decides for how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that due to changes in the worst-case scenario over time, the agent is faced with a problem of time inconsistency. The agent resolves the conflict with her future selves by using an information acquisition rule that is non-monotonic and features random stopping for intermediate sets of beliefs."