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Rationalizing dynamic choices

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  • Henrique de Oliveira
  • Rohit Lamba

Abstract

An analyst observes an agent take a sequence of actions. The analyst does not have access to the agent's information and ponders whether the observed actions could be justified through a rational Bayesian model with a known utility function. We show that the observed actions cannot be justified if and only if there is a single deviation argument that leaves the agent better off, regardless of the information. The result is then extended to allow for distributions over possible action sequences. Four applications are presented: monotonicity of rationalization with risk aversion, a potential rejection of the Bayesian model with observable data, feasible outcomes in dynamic information design, and partial identification of preferences without assumptions on information.

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  • Henrique de Oliveira & Rohit Lamba, 2025. "Rationalizing dynamic choices," Papers 2504.05251, arXiv.org.
    • Handle: RePEc:arx:papers:2504.05251
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    File URL: http://arxiv.org/pdf/2504.05251
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