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Learning and Risk Aversion

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  • Carlos Oyarzun
  • Rajiv Sarin

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.
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Suggested Citation

  • Carlos Oyarzun & Rajiv Sarin, 2005. "Learning and Risk Aversion," Levine's Bibliography 784828000000000482, UCLA Department of Economics.
    • Handle: RePEc:cla:levrem:784828000000000482
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    File URL: http://econweb.tamu.edu/rsarin/learningandriskaversion905.pdf
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    References listed on IDEAS

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    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Albert Burgos, 2002. "Learning to deal with risk: what does reinforcement learning tell us about risk attitudes?," Economics Bulletin, AccessEcon, vol. 4(10), pages 1-13.
    3. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    4. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    5. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    6. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    7. David Easley & Aldo Rustichini, 1999. "Choice without Beliefs," Econometrica, Econometric Society, vol. 67(5), pages 1157-1184, September.
    8. Tilman Börgers & Antonio J. Morales & Rajiv Sarin, 2004. "Expedient and Monotone Learning Rules," Econometrica, Econometric Society, vol. 72(2), pages 383-405, March.
    9. Dekel, Eddie & Scotchmer, Suzanne, 1999. "On the Evolution of Attitudes towards Risk in Winner-Take-All Games," Journal of Economic Theory, Elsevier, vol. 87(1), pages 125-143, July.
    10. Robson, Arthur J., 1996. "The Evolution of Attitudes to Risk: Lottery Tickets and Relative Wealth," Games and Economic Behavior, Elsevier, vol. 14(2), pages 190-207, June.
    11. Drew Fudenberg & Jean Tirole, 1991. "Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061414, December.
    12. Jean-François Laslier & Bernard Walliser, 2005. "A reinforcement learning process in extensive form games," International Journal of Game Theory, Springer;Game Theory Society, vol. 33(2), pages 219-227, June.
    13. Rustichini, Aldo, 1999. "Optimal Properties of Stimulus--Response Learning Models," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 244-273, October.
    14. Beggs, A.W., 2005. "On the convergence of reinforcement learning," Journal of Economic Theory, Elsevier, vol. 122(1), pages 1-36, May.
    15. Hopkins, Ed, 2007. "Adaptive learning models of consumer behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 64(3-4), pages 348-368.
    16. Jehiel, Philippe & Samet, Dov, 2005. "Learning to play games in extensive form by valuation," Journal of Economic Theory, Elsevier, vol. 124(2), pages 129-148, October.
    17. repec:ebl:ecbull:v:4:y:2002:i:10:p:1-13 is not listed on IDEAS
    18. Laslier, Jean-Francois & Topol, Richard & Walliser, Bernard, 2001. "A Behavioral Learning Process in Games," Games and Economic Behavior, Elsevier, vol. 37(2), pages 340-366, November.
    19. Hopkins, Ed & Posch, Martin, 2005. "Attainability of boundary points under reinforcement learning," Games and Economic Behavior, Elsevier, vol. 53(1), pages 110-125, October.
    20. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    21. Carlos Oyarzun & Johannes Ruf, 2009. "Monotone imitation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 41(3), pages 411-441, December.
    22. Borgers, Tilman & Sarin, Rajiv, 2000. "Naive Reinforcement Learning with Endogenous Aspirations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 921-950, November.
    23. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
    24. Robson, Arthur J., 1996. "A Biological Basis for Expected and Non-expected Utility," Journal of Economic Theory, Elsevier, vol. 68(2), pages 397-424, February.
    25. Herbert Simon, 1956. "A comparison of game theory and learning theory," Psychometrika, Springer;The Psychometric Society, vol. 21(3), pages 267-272, September.
    26. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
    27. Rothschild, Michael & Stiglitz, Joseph E., 1970. "Increasing risk: I. A definition," Journal of Economic Theory, Elsevier, vol. 2(3), pages 225-243, September.
    28. John G. Cross, 1973. "A Stochastic Learning Model of Economic Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(2), pages 239-266.
    29. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Gotts, Nicholas M. & Polhill, J. Gary, 2007. "Transient and asymptotic dynamics of reinforcement learning in games," Games and Economic Behavior, Elsevier, vol. 61(2), pages 259-276, November.
    30. DellaVigna, Stefano & LiCalzi, Marco, 2001. "Learning to make risk neutral choices in a symmetric world," Mathematical Social Sciences, Elsevier, vol. 41(1), pages 19-37, January.
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    Cited by:

    1. Johannes G. Jaspersen & Richard Peter, 2017. "Experiential Learning, Competitive Selection, and Downside Risk: A New Perspective on Managerial Risk Taking," Organization Science, INFORMS, vol. 28(5), pages 915-930, October.
    2. Carlos Oyarzun & Johannes Ruf, 2009. "Monotone imitation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 41(3), pages 411-441, December.
    3. 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.
    4. Oyarzun, Carlos, 2014. "A note on absolutely expedient learning rules," Journal of Economic Theory, Elsevier, vol. 153(C), pages 213-223.
    5. Oyarzun, Carlos & Sanjurjo, Adam & Nguyen, Hien, 2017. "Response functions," European Economic Review, Elsevier, vol. 98(C), pages 1-31.

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    More about this item

    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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