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Updating beliefs with imperfect signals : experimental evidence

Author

Listed:
  • François Poinas

    (Toulouse School of Economics (University Toulouse 1 - GREMAQ) - Toulouse F-31000, France)

  • Julie Rosaz

    (Université de Lyon, Lyon, F-69003, France; CNRS, GATE Lyon St Etienne, UMR 5824, 93, chemin des Mouilles, Ecully, F-69130, France; ENS-LSH, Lyon, France)

  • Béatrice Roussillon

    (Université de Lyon, Lyon, F-69003, France ; Université Jean Monnet ; CNRS, GATE Lyon St Etienne,)

Abstract

This article analyses belief updating when agents receive a signal that restricts the number of possible states of the world. We create an experiment on individual choice under uncertainty. In this experiment, the subject observes an urn, containing yellow and blue balls, whose composition is partially revealed. The subject has to assess the composition of the urn and form an initial belief. Then, he receives a signal that restricts the set of the possible urns from which the initial observed sample is drawn. Once again, he has to estimate the composition of the urn. Our results show that, on the whole, this type of signal increases the frequency of correct assessment. However, differences appear between validating and invalidating signals (i.e. signals that either confirm or disprove the initial belief). The later significantly increase the probability to make a correct assessment whereas validating signals reduce the frequency of correct estimations. We find evidences of lack of persistence in choice under uncertainty. The literature shows that people may persist with their choice even when they are wrong. We show that they may also change even if they are right.

Suggested Citation

  • François Poinas & Julie Rosaz & Béatrice Roussillon, 2010. "Updating beliefs with imperfect signals : experimental evidence," Working Papers 1033, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
  • Handle: RePEc:gat:wpaper:1033
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    Cited by:

    1. is not listed on IDEAS
    2. Marek Jenöffy, 2023. "Can the Seesaw Model Depict the Certainty Effect?," Working Papers hal-04136569, HAL.
    3. Johanna Choumert-Nkolo & Anaïs Lamour & Pascale Phélinas, 2021. "The Economics of Volcanoes," Economics of Disasters and Climate Change, Springer, vol. 5(2), pages 277-299, July.
    4. Carlos Alós-Ferrer & Alexander Jaudas & Alexander Ritschel, 2021. "Effortful Bayesian updating: A pupil-dilation study," Journal of Risk and Uncertainty, Springer, vol. 63(1), pages 81-102, August.
    5. Aurélien Baillon & Han Bleichrodt & Umut Keskin & Olivier l’Haridon & Chen Li, 2018. "The Effect of Learning on Ambiguity Attitudes," Management Science, INFORMS, vol. 64(5), pages 2181-2198, May.
    6. Aurélien Baillon & Han Bleichrodt & Umut Keskin & Olivier L'Haridon & Author-Name: Chen Li, 2013. "Learning under ambiguity: An experiment using initial public offerings on a stock market," Economics Working Paper Archive (University of Rennes & University of Caen) 201331, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.

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    Keywords

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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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