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Selective Sampling with Information-Storage Constraints

Author

Listed:
  • Philippe Jehiel

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UCL - University College of London [London])

  • Jakub Steiner

    (UZH - Universität Zürich [Zürich] = University of Zurich, CERGE-EI - UK - Univerzita Karlova [Praha, Česká republika] = Charles University [Prague, Czech Republic])

Abstract

A memoryless agent can acquire arbitrarily many signals. After each signal observation, she either terminates and chooses an action, or she discards her observation and draws a new signal. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the benefits of selective memory applied to the extracted signals. Implications—obtained in simple examples—include (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.

Suggested Citation

  • Philippe Jehiel & Jakub Steiner, 2020. "Selective Sampling with Information-Storage Constraints," Post-Print halshs-03229986, HAL.
    • Handle: RePEc:hal:journl:halshs-03229986
    DOI: 10.1093/ej/uez068
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    Cited by:

    1. Leung, B. T. K., 2020. "Learning in a Small/Big World," Cambridge Working Papers in Economics 2085, Faculty of Economics, University of Cambridge.
    2. Benson Tsz Kin Leung, 2020. "Learning in a Small/Big World," Papers 2009.11917, arXiv.org, revised Mar 2023.
    3. Chatterjee, Kalyan & Hu, Tai-Wei, 2023. "Learning with limited memory: Bayesianism vs heuristics," Journal of Economic Theory, Elsevier, vol. 209(C).
    4. Leung, Benson Tsz Kin, 2020. "Limited cognitive ability and selective information processing," Games and Economic Behavior, Elsevier, vol. 120(C), pages 345-369.

    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

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