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An Economist's Perspective on Probability Matching

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  • Vulkan, Nir
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    Abstract

    The experimental phenomenon known as "probability matching" is often offered as evidence in support of adaptive learning models and against the idea that people maximise their expected utility. Recent interest in dynamic-based equilibrium theories means the term reappears in Economics. However, there seems to be conflicting views on what is actually meant by the term and about the validity of the data. The purpose of this paper is therefore threefold: First, to introduce today's readers to what is meant by probability matching, and in particular to clarify which aspects of this phenomenon challenge the utility-maximisation hypothesis. Second, to familiarise the reader with the different theoretical approaches to behaviour in such circumstances, and to focus on the differences in predictions between these theories in light of recent advances. Third, to provide a comprehensive survey of repeated, binary choice experiments. Copyright 2000 by Blackwell Publishers Ltd

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    Bibliographic Info

    Article provided by Wiley Blackwell in its journal Journal of Economic Surveys.

    Volume (Year): 14 (2000)
    Issue (Month): 1 (February)
    Pages: 101-18

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    Handle: RePEc:bla:jecsur:v:14:y:2000:i:1:p:101-18

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    Cited by:
    1. Bar-Eli, Michael & Azar, Ofer H. & Ritov, Ilana & Keidar-Levin, Yael & Schein, Galit, 2005. "Action bias among elite soccer goalkeepers: The case of penalty kicks," MPRA Paper 4477, University Library of Munich, Germany.
    2. Ding, Jieyao & Nicklisch, Andreas, 2013. "On the impulse in impulse learning," Economics Letters, Elsevier, vol. 121(2), pages 294-297.
    3. Azar, Ofer H. & Bar-Eli, Michael, 2009. "Do soccer players play the mixed-strategy Nash equilibrium?," MPRA Paper 20964, University Library of Munich, Germany.
    4. Wolfgang Gaissmaier & Lael J. Schooler & Rui Mata, 2008. "An ecological perspective to cognitive limits: Modeling environment-mind interactions with ACT-R," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3, pages 278-291, March.
    5. Hanan Shteingart & Yonatan Loewenstein, 2014. "Reinforcement Learning and Human Behavior," Discussion Paper Series dp656, The Center for the Study of Rationality, Hebrew University, Jerusalem.
    6. Yaakov Kareev & Klaus Fiedler & Judith Avrahami, 2007. "Expected Prediction Accuracy and the Usefulness of Contingencies," Discussion Paper Series dp455, The Center for the Study of Rationality, Hebrew University, Jerusalem.
    7. Rubinstein, Ariel, 2002. "Irrational diversification in multiple decision problems," European Economic Review, Elsevier, vol. 46(8), pages 1369-1378, September.
    8. Gianluigi Mongillo & Hanan Shteingart & Yonatan Loewenstein, 2014. "The Misbehavior of Reinforcement Learning," Discussion Paper Series dp661, The Center for the Study of Rationality, Hebrew University, Jerusalem.
    9. Yaakov Kareev & Klaus Fiedler & Judith Avrahami, 2007. "Expected Prediction Accuracy and the Usefulness of Contingencies," Levine's Bibliography 843644000000000171, UCLA Department of Economics.

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