IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2109.09871.html
   My bibliography  Save this paper

Overinference from Weak Signals and Underinference from Strong Signals

Author

Listed:
  • Ned Augenblick
  • Eben Lazarus
  • Michael Thaler

Abstract

When people receive new information, sometimes they revise their beliefs too much, and sometimes too little. In this paper, we show that a key driver of whether people overinfer or underinfer is the strength of the information. Based on a model in which people know which direction to update in, but not exactly how much to update, we hypothesize that people will overinfer from weak signals and underinfer from strong signals. We then test this hypothesis across four different environments: abstract experiments, a naturalistic experiment, sports betting markets, and financial markets. In each environment, our consistent and robust finding is overinference from weak signals and underinference from strong signals. Our framework and findings can help harmonize apparently contradictory results from the experimental and empirical literatures.

Suggested Citation

  • Ned Augenblick & Eben Lazarus & Michael Thaler, 2021. "Overinference from Weak Signals and Underinference from Strong Signals," Papers 2109.09871, arXiv.org, revised Jun 2024.
    • Handle: RePEc:arx:papers:2109.09871
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2109.09871
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 17(1), pages 31-57, January.
    2. Neeraja Gupta & Luca Rigotti & Alistair Wilson, 2021. "The Experimenters' Dilemma: Inferential Preferences over Populations," Papers 2107.05064, arXiv.org, revised Jul 2021.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    5. Duarte Gonçalves & Jonathan Libgober & Jack Willis, 2021. "Learning versus Unlearning: An Experiment on Retractions," NBER Working Papers 29512, National Bureau of Economic Research, Inc.
    6. Manoj Thomas & Vicki Morwitz, 2005. "Penny Wise and Pound Foolish: The Left-Digit Effect in Price Cognition," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 54-64, June.
    7. Nicholas C. Barberis, 2013. "Thirty Years of Prospect Theory in Economics: A Review and Assessment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 173-196, Winter.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kenneth Chan & Gary Charness & Chetan Dave & J. Lucas Reddinger, 2024. "On Prior Confidence and Belief Updating," Papers 2412.10662, arXiv.org.
    2. Luca Braghieri, 2023. "Biased Decoding and the Foundations of Communication," CESifo Working Paper Series 10432, CESifo.
    3. Mel Win Khaw & Ziang Li & Michael Woodford, 2022. "Cognitive Imprecision and Stake-Dependent Risk Attitudes," CESifo Working Paper Series 9923, CESifo.
    4. Charlotte Cordes & Jana Friedrichsen & Simeon Schudy, 2023. "Motivated Procrastination," Rationality and Competition Discussion Paper Series 471, CRC TRR 190 Rationality and Competition.
    5. Larry G Epstein & Kaushil Patel, 2024. "Identifying Heterogeneous Decision Rules From Choices When Menus Are Unobserved," Papers 2405.09500, arXiv.org.
    6. Philipp Denter & Boris Ginzburg, 2024. "Troll Farms," Papers 2411.03241, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kai Barron, 2021. "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 31-58, March.
    2. Ambuehl, Sandro & Li, Shengwu, 2018. "Belief updating and the demand for information," Games and Economic Behavior, Elsevier, vol. 109(C), pages 21-39.
    3. Dertwinkel-Kalt, Markus & Köster, Mats, 2017. "Local thinking and skewness preferences," DICE Discussion Papers 248, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    4. Carolin Bock & Maximilian Schmidt, 2015. "Should I stay, or should I go? – How fund dynamics influence venture capital exit decisions," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 68-82, November.
    5. Jascha-Alexander Koch & Michael Siering, 2019. "The recipe of successful crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 661-679, December.
    6. Klein, Martin & Deissenroth, Marc, 2017. "When do households invest in solar photovoltaics? An application of prospect theory," Energy Policy, Elsevier, vol. 109(C), pages 270-278.
    7. Alex Imas & Sally Sadoff & Anya Samek, 2017. "Do People Anticipate Loss Aversion?," Management Science, INFORMS, vol. 63(5), pages 1271-1284, May.
    8. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    9. Carpentier, A. & Reboud, X., 2018. "Why farmers consider pesticides the ultimate in crop protection: economic and behavioral insights," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277528, International Association of Agricultural Economists.
    10. Bryce McLaughlin & Jann Spiess, 2022. "Algorithmic Assistance with Recommendation-Dependent Preferences," Papers 2208.07626, arXiv.org, revised Jan 2024.
    11. Mariya Burdina & Scott Hiller, 2021. "When Falling Just Short is a Good Thing: The Effect of Past Performance on Improvement," Journal of Sports Economics, , vol. 22(7), pages 777-798, October.
    12. Häckel, Björn & Pfosser, Stefan & Tränkler, Timm, 2017. "Explaining the energy efficiency gap - Expected Utility Theory versus Cumulative Prospect Theory," Energy Policy, Elsevier, vol. 111(C), pages 414-426.
    13. Mohit Anand & Ruiqing Miao & Madhu Khanna, 2019. "Adopting bioenergy crops: Does farmers’ attitude toward loss matter?," Agricultural Economics, International Association of Agricultural Economists, vol. 50(4), pages 435-450, July.
    14. repec:dgr:rugsom:14022-eef is not listed on IDEAS
    15. Gergely Hajdu & Balázs Krusper, 2023. "Choice-induced Sticky Learning," Department of Economics Working Papers wuwp349, Vienna University of Economics and Business, Department of Economics.
    16. Edsel L. Beja, 2017. "The Asymmetric Effects of Macroeconomic Performance on Happiness: Evidence for the EU," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 52(3), pages 184-190, May.
    17. Asanov, Igor, 2021. "Bandit cascade: A test of observational learning in the bandit problem," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 150-171.
    18. de Koning, Koen & Filatova, Tatiana & Bin, Okmyung, 2017. "Bridging the Gap Between Revealed and Stated Preferences in Flood-prone Housing Markets," Ecological Economics, Elsevier, vol. 136(C), pages 1-13.
    19. Dian Yu & Jianjun Gao & Weiping Wu & Zizhuo Wang, 2022. "Price Interpretability of Prediction Markets: A Convergence Analysis," Papers 2205.08913, arXiv.org, revised Nov 2023.
    20. Gary Charness & Edi Karni & Dan Levin, 2007. "Individual and group decision making under risk: An experimental study of Bayesian updating and violations of first-order stochastic dominance," Journal of Risk and Uncertainty, Springer, vol. 35(2), pages 129-148, October.
    21. Amedeo Piolatto & Matthew D. Rablen, 2017. "Prospect theory and tax evasion: a reconsideration of the Yitzhaki puzzle," Theory and Decision, Springer, vol. 82(4), pages 543-565, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2109.09871. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.