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Learning versus Unlearning: An Experiment on Retractions

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  • Duarte Gonc{c}alves
  • Jonathan Libgober
  • Jack Willis

Abstract

Widely discredited ideas nevertheless persist. Why do people fail to ``unlearn''? We study one explanation: beliefs are resistant to retractions (the revoking of earlier information). Our experimental design identifies unlearning -- i.e., updating from retractions -- and enables its comparison with learning from equivalent new information. Across different kinds of retractions -- for instance, those consistent or contradictory with the prior, or those occurring when prior beliefs are either extreme or moderate -- subjects do not fully unlearn from retractions and update less from them than from equivalent new information. This phenomenon is not explained by most of the well-studied violations of Bayesian updating, which yield differing predictions in our design. However, it is consistent with difficulties in conditional reasoning, which have been documented in other domains and circumstances.

Suggested Citation

  • Duarte Gonc{c}alves & Jonathan Libgober & Jack Willis, 2021. "Learning versus Unlearning: An Experiment on Retractions," Papers 2106.11433, arXiv.org, revised Nov 2022.
  • Handle: RePEc:arx:papers:2106.11433
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    Cited by:

    1. Ned Augenblick & Eben Lazarus & Michael Thaler, 2021. "Overinference from Weak Signals and Underinference from Strong Signals," Papers 2109.09871, arXiv.org, revised Mar 2023.

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    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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