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Overreacting to a black box

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  • Yanagita, Shohei

Abstract

We often receive recommendations whose generation process is so complex that we cannot understand it. In such cases, we cannot perform accurate Bayesian updating. Moreover, it is well-documented that when such recommendations are unexpected for us, we often overreact to them. Based on the framework established by Ke, Wu, and Zhao (2024), we characterize an updating rule expressing such a reaction. In the resulting updating rule, if the distance between the recommendation and the decision maker’s prior belief is significant enough, she perceives it as unexpected and overreacts. This rule can be seen as a generalization of the contraction rule, proposed by Ke, Wu, and Zhao (2024).

Suggested Citation

  • Yanagita, Shohei, 2025. "Overreacting to a black box," Journal of Mathematical Economics, Elsevier, vol. 118(C).
    • Handle: RePEc:eee:mateco:v:118:y:2025:i:c:s0304406825000485
    DOI: 10.1016/j.jmateco.2025.103131
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    Keywords

    Black box; Overreaction; Non-bayesian updating;
    All these keywords.

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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