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Convergence in models of misspecified learning

Author

Listed:
  • Heidhues, Paul

    (Düsseldorf Institute for Competition Economics, Heinrich-Heine Universität Düsseldorf)

  • Koszegi, Botond

    (Department of Economics and Business, Central European University)

  • Strack, Philipp

    (Department of Economics, Yale University)

Abstract

We establish convergence of beliefs and actions in a class of one-dimensional learning settings in which the agent's model is misspecified, she chooses actions endogenously, and the actions affect how she misinterprets information. Our stochastic-approximation-based methods rely on two crucial features: that the state and action spaces are continuous, and that the agent's posterior admits a one-dimensional summary statistic. Through a basic model with a normal-normal updating structure and a generalization in which the agent's misinterpretation of information can depend on her current beliefs in a flexible way, we show that these features are compatible with a number of specifications of how exactly the agent updates. Applications of our framework include learning by a person who has an incorrect model of a technology she uses or is overconfident about herself, learning by a representative agent who may misunderstand macroeconomic outcomes, as well as learning by a firm that has an incorrect parametric model of demand.

Suggested Citation

  • Heidhues, Paul & Koszegi, Botond & Strack, Philipp, 2021. "Convergence in models of misspecified learning," Theoretical Economics, Econometric Society, vol. 16(1), January.
    • Handle: RePEc:the:publsh:3558
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    Citations

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    Cited by:

    1. Esponda, Ignacio & Pouzo, Demian & Yamamoto, Yuichi, 2021. "Asymptotic behavior of Bayesian learners with misspecified models," Journal of Economic Theory, Elsevier, vol. 195(C).
    2. Ba, Cuimin & Gindin, Alice, 2023. "A multi-agent model of misspecified learning with overconfidence," Games and Economic Behavior, Elsevier, vol. 142(C), pages 315-338.
    3. Matthes, Julian & Momsen, Katharina, 2024. "Preferences and Demand for Mental Models," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302412, Verein für Socialpolitik / German Economic Association.
    4. Gamp, Tobias & Krähmer, Daniel, 2022. "Biased Beliefs in Search Markets," Rationality and Competition Discussion Paper Series 365, CRC TRR 190 Rationality and Competition.

    More about this item

    Keywords

    Misspecified model; Bayesian learning; convergence; Berk-Nash equilibrium;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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