Optimal Dynamic Information Acquisition

Abstract

I study a dynamic model in which a decision‐maker (DM) acquires information about the payoffs of different alternatives prior to making a decision. The model's key feature is the flexibility of information: the DM can choose any dynamic signal process as an information source, subject to a flow cost that depends on the informativeness of the signal. Under the optimal policy, the DM acquires a signal that arrives according to a Poisson process. The optimal Poisson signal confirms the DM's prior belief and is sufficiently precise to warrant immediate action. Over time, given the absence of the arrival of a Poisson signal, the DM continues seeking an increasingly precise but less frequent Poisson signal.