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Anchoring in social context

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  • Meub, Lukas
  • Proeger, Till E.

Abstract

The anchoring-and-adjustment heuristic has been studied in numerous experimental settings and is increasingly drawn upon to explain systematically biased decisions in economic areas as diverse as auctions, real estate pricing, sports betting and forecasting. In these cases, anchors result from publicly observable and aggregated decisions of other market participants. However, experimental studies have neglected this social dimension by focusing on neutral, experimenter-provided anchors in purely individualistic settings. We present a novel experimental design with a socially derived anchor, monetary incentives for unbiased decisions and feedback on performance to more accurately implement market conditions. Despite these factors, we find robust effects for the socially derived anchor, an increased bias for higher cognitive load, and only weak learning effects. A comparison to a neutral anchor shows that the social context increases biased behavior. Further, we find that this increase is not driven by differences in perceived relevance of anchor values. Our results support the assumption that anchoring remains a valid explanation for systematically biased decisions within market contexts.

Suggested Citation

  • Meub, Lukas & Proeger, Till E., 2015. "Anchoring in social context," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 55(C), pages 29-39.
    • Handle: RePEc:eee:soceco:v:55:y:2015:i:c:p:29-39
    DOI: 10.1016/j.socec.2015.01.004
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    References listed on IDEAS

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    Cited by:

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    3. Ivanova-Stenzel, Radosveta & Seres, Gyula, 2021. "Are strategies anchored?," European Economic Review, Elsevier, vol. 135(C).
    4. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    5. Sara Suarez-Fernandez & Maria Jose Perez-Villadoniga & Juan Prieto-Rodriguez, 2018. "Are We (Un)Consciously Driven by First Impressions? Price Declarations vs. Observed Cinema Demand when VAT Increases," ACEI Working Paper Series AWP-02-2018, Association for Cultural Economics International, revised Jul 2018.
    6. Jetter, Michael & Walker, Jay K., 2020. "At what age does the anchoring heuristic emerge? Evidence from Jeopardy!," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 757-766.
    7. Meub, Lukas & Proeger, Till, 2016. "Can anchoring explain biased forecasts? Experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 12(C), pages 1-13.
    8. Yigit Oezcelik & Michel Tolksdorf, 2023. "Non-numerical and social anchoring in consumer-generated ratings," Working Papers 202319, University of Liverpool, Department of Economics.
    9. Jetter, Michael & Walker, Jay K., 2017. "Anchoring in financial decision-making: Evidence from Jeopardy!," Journal of Economic Behavior & Organization, Elsevier, vol. 141(C), pages 164-176.
    10. Fox, Bryanna & Moule, Richard K. & Parry, Megan M., 2018. "Categorically complex: A latent class analysis of public perceptions of police militarization," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 33-46.
    11. Di Cagno, Daniela & Güth, Werner & Lohse, Tim & Marazzi, Francesca & Spadoni, Lorenzo, 2024. "Who cares when Value (Mis)reporting may be found out? An Acquiring-a-Company experiment with value messages and information leaks," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 108(C).
    12. Jetter, Michael & Walker, Jay K., 2016. "Anchoring in Financial Decision-Making: Evidence from the Field," IZA Discussion Papers 10151, Institute of Labor Economics (IZA).
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    14. Lukas Meub & Till Proeger, 2018. "Are groups ‘less behavioral’? The case of anchoring," Theory and Decision, Springer, vol. 85(2), pages 117-150, August.

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    More about this item

    Keywords

    Anchoring; Heuristics and biases; Incentives; Laboratory experiment;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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