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Learning and risk aversion

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  • Oyarzun, Carlos
  • Sarin, Rajiv

Abstract

We study how learning shapes behavior towards risk when individuals are not assumed to know, or to have beliefs about, probability distributions. In any period, the behavior change induced by learning is assumed to depend on the action chosen and the payoff obtained. We characterize learning processes that, in expected value, increase the probability of choosing the safest actions and provide sufficient conditions for them to converge to the choices of risk averse expected utility maximizers. We provide a learning theoretic motivation for long run risk choices, such as those in expected utility theory with known payoff distributions.

Suggested Citation

  • Oyarzun, Carlos & Sarin, Rajiv, 2013. "Learning and risk aversion," Journal of Economic Theory, Elsevier, vol. 148(1), pages 196-225.
  • Handle: RePEc:eee:jetheo:v:148:y:2013:i:1:p:196-225
    DOI: 10.1016/j.jet.2012.09.011
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    References listed on IDEAS

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    Cited by:

    1. Oyarzun, Carlos & Ruf, Johannes, 2014. "Convergence in models with bounded expected relative hazard rates," Journal of Economic Theory, Elsevier, vol. 154(C), pages 229-244.
    2. Oyarzun, Carlos, 2014. "A note on absolutely expedient learning rules," Journal of Economic Theory, Elsevier, vol. 153(C), pages 213-223.
    3. repec:eee:eecrev:v:98:y:2017:i:c:p:1-31 is not listed on IDEAS

    More about this item

    Keywords

    Reinforcement learning; Risk aversion; Expected utility;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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