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Misspecified Beliefs about Time Lags

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  • Yingkai Li
  • Harry Pei

Abstract

We examine the long-term behavior of a Bayesian agent who has a misspecified belief about the time lag between actions and feedback, and learns about the payoff consequences of his actions over time. Misspecified beliefs about time lags result in attribution errors, which have no long-term effect when the agent's action converges, but can lead to arbitrarily large long-term inefficiencies when his action cycles. Our proof uses concentration inequalities to bound the frequency of action switches, which are useful to study learning problems with history dependence. We apply our methods to study a policy choice game between a policy-maker who has a correctly specified belief about the time lag and the public who has a misspecified belief.

Suggested Citation

  • Yingkai Li & Harry Pei, 2020. "Misspecified Beliefs about Time Lags," Papers 2012.07238, arXiv.org.
    • Handle: RePEc:arx:papers:2012.07238
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    References listed on IDEAS

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    Cited by:

    1. Yingkai Li & Argyris Oikonomou, 2024. "Dynamics and Contracts for an Agent with Misspecified Beliefs," Papers 2405.20423, arXiv.org.
    2. Yingkai Li & Aleksandrs Slivkins, 2022. "Exploration and Incentivizing Participation in Clinical Trials," Papers 2202.06191, arXiv.org, revised Jan 2025.
    3. Bowen, T. Renee & Galperti, Simone & Dmitriev, Danil, 2021. "Learning from Shared News: When Abundant Information Leads to Belief Polarization," CEPR Discussion Papers 15789, C.E.P.R. Discussion Papers.

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