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Working memory and spatial judgments: Cognitive load increases the central tendency bias

Author

Listed:
  • Sarah R., Allred
  • L. Elizabeth, Crawford
  • Sean, Duffy
  • John, Smith

Abstract

Previous work demonstrates that memory for simple stimuli can be biased by information about the category of which the stimulus is a member. Specifically, stimuli with values greater than the category’s average tend to be underestimated and stimuli with values less than the average are overestimated. This is referred to as the central tendency bias. This bias has been explained as an optimal use of both noisy sensory information and category information. In a largely separate literature, cognitive load experiments attempt to manipulate the available working memory of participants in order to observe its effect on choice or judgments. In three experiments, we demonstrate that participants under a high cognitive load exhibit a stronger central tendency bias than when under a low cognitive load. Although not anticipated at the outset, we also find that judgments exhibit an anchoring bias.

Suggested Citation

  • Sarah R., Allred & L. Elizabeth, Crawford & Sean, Duffy & John, Smith, 2015. "Working memory and spatial judgments: Cognitive load increases the central tendency bias," MPRA Paper 63520, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:63520
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    References listed on IDEAS

    as
    1. Allred, Sarah & Duffy, Sean & Smith, John, 2016. "Cognitive load and strategic sophistication," Journal of Economic Behavior & Organization, Elsevier, vol. 125(C), pages 162-178.
    2. Duffy, Sean & Smith, John, 2011. "Cognitive load in the multi-player prisoner's dilemma game," MPRA Paper 30856, University Library of Munich, Germany.
    3. Paymon Ashourian & Yonatan Loewenstein, 2011. "Bayesian Inference Underlies the Contraction Bias in Delayed Comparison Tasks," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-8, May.
    4. Oechssler, Jörg & Roider, Andreas & Schmitz, Patrick W., 2009. "Cognitive abilities and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 147-152, October.
    5. Furnham, Adrian & Boo, Hua Chu, 2011. "A literature review of the anchoring effect," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 35-42, February.
    6. Shiv, Baba & Fedorikhin, Alexander, 1999. "Heart and Mind in Conflict: The Interplay of Affect and Cognition in Consumer Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 26(3), pages 278-292, December.
    7. Bergman, Oscar & Ellingsen, Tore & Johannesson, Magnus & Svensson, Cicek, 2010. "Anchoring and cognitive ability," Economics Letters, Elsevier, vol. 107(1), pages 66-68, April.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Duffy, Sean & Naddeo, JJ & Owens, David & Smith, John, 2016. "Cognitive load and mixed strategies: On brains and minimax," MPRA Paper 89720, University Library of Munich, Germany.
    2. Sean Duffy & John Smith, 2020. "On the category adjustment model: another look at Huttenlocher, Hedges, and Vevea (2000)," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 19(1), pages 163-193, June.
    3. Allred, Sarah & Duffy, Sean & Smith, John, 2016. "Cognitive load and strategic sophistication," Journal of Economic Behavior & Organization, Elsevier, vol. 125(C), pages 162-178.
    4. Duffy, Sean & Smith, John, 2017. "Category effects on stimulus estimation: Shifting and skewed frequency distributions - A reexamination," MPRA Paper 76042, University Library of Munich, Germany.
    5. Deck, Cary & Jahedi, Salar, 2015. "The effect of cognitive load on economic decision making: A survey and new experiments," European Economic Review, Elsevier, vol. 78(C), pages 97-119.

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    More about this item

    Keywords

    judgment; memory; anchoring; working memory; cognitive constraints; cognitive busyness;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • Z0 - Other Special Topics - - General

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