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Learning and Decision Costs in One-Person Games

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  • Romeo, Charles
  • Sopher, Barry

Abstract

This paper reports the results of a two-part data analysis of learning in a repeated costly decision experiment. In the first part we test payoff dominance under the hypothesis of expected payoff maximization. We utilize a dynamic probability distribution over decisions for each player, characterizing what each player has learned about the payoff function by the moments from these distributions. In the second part, we test the hypothesis of expected payoff maximization for players in each treatment group. Expected payoff maximization is supported but payoff dominance is not.

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  • Romeo, Charles & Sopher, Barry, 1999. "Learning and Decision Costs in One-Person Games," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 335-357, July-Aug..
    • Handle: RePEc:jae:japmet:v:14:y:1999:i:4:p:335-57
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    Cited by:

    1. Hopkins, Ed, 1999. "Learning, Matching, and Aggregation," Games and Economic Behavior, Elsevier, vol. 26(1), pages 79-110, January.
    2. Scott J. Savage & Donald M. Waldman, 2008. "Learning and fatigue during choice experiments: a comparison of online and mail survey modes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 351-371.
    3. Gary E. Bolton & Sabrina Bonzelet & Tobias Stangl & Ulrich W. Thonemann, 2023. "Decision making under service‐level contracts: The role of cost saliency," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1243-1261, April.

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