IDEAS home Printed from https://ideas.repec.org/p/brd/wpaper/110r4.html

Trust in Signals and the Origins of Disagreement

Author

Listed:
  • Ing-Haw Cheng

    (Tuck School of Business, Dartmouth College)

  • Alice Hsiaw

    (Brandeis University International Business School)

Abstract

Why do individuals interpret the same information differently? We propose that individuals follow Bayes’ Rule when forming posteriors with one exception: when assessing the credibility of signal sources, they “double-dip” the data and use alreadyupdated beliefs instead of their priors. Individuals who make this mistake either overor underreact to new information depending on the order in which they received previous signals. Traders engage in excessive speculation associated with price bubbles and crashes. Our model provides a theory of the origins of disagreement: individuals disagree about both unknown states and credibility despite sharing common priors and information.

Suggested Citation

  • Ing-Haw Cheng & Alice Hsiaw, 2016. "Trust in Signals and the Origins of Disagreement," Working Papers 110R4, Brandeis University, Department of Economics and International Business School, revised Dec 2018.
    • Handle: RePEc:brd:wpaper:110r4
    as

    Download full text from publisher

    File URL: http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP110R4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joshua Schwartzstein, 2014. "Selective Attention And Learning," Journal of the European Economic Association, European Economic Association, vol. 12(6), pages 1423-1452, December.
    2. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    3. Peter Koudijs & Hans-Joachim Voth, 2016. "Leverage and Beliefs: Personal Experience and Risk-Taking in Margin Lending," American Economic Review, American Economic Association, vol. 106(11), pages 3367-3400, November.
    4. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    5. Benjamin Enke & Florian Zimmermann, 2019. "Correlation Neglect in Belief Formation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 313-332.
    6. Hong, Harrison & Scheinkman, José & Xiong, Wei, 2008. "Advisors and asset prices: A model of the origins of bubbles," Journal of Financial Economics, Elsevier, vol. 89(2), pages 268-287, August.
    7. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    8. Stefano DellaVigna & Devin Pope, 2018. "Predicting Experimental Results: Who Knows What?," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2410-2456.
    9. , & , & ,, 2016. "Fragility of asymptotic agreement under Bayesian learning," Theoretical Economics, Econometric Society, vol. 11(1), January.
    10. Sendhil Mullainathan & Andrei Shleifer, 2005. "The Market for News," American Economic Review, American Economic Association, vol. 95(4), pages 1031-1053, September.
    11. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    12. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 37-82.
    13. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    14. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    15. Paola Sapienza & Luigi Zingales, 2013. "Economic Experts versus Average Americans," American Economic Review, American Economic Association, vol. 103(3), pages 636-642, May.
    16. Ulrike Malmendier & Stefan Nagel, 2011. "Depression Babies: Do Macroeconomic Experiences Affect Risk Taking?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(1), pages 373-416.
    Full references (including those not matched with items on IDEAS)

    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. Cheng, Ing-Haw & Hsiaw, Alice, 2022. "Distrust in experts and the origins of disagreement," Journal of Economic Theory, Elsevier, vol. 200(C).
    2. Hestermann, Nina & Le Yaouanq, Yves, 2018. "It\'s not my Fault! Self-Confidence and Experimentation," Rationality and Competition Discussion Paper Series 124, CRC TRR 190 Rationality and Competition.
    3. Jacob LaRiviere & Mikolaj Czajkowski & Nick Hanley & Katherine Simpson, 2016. "What is the Causal Impact of Knowledge on Preferences in Stated Preference Studies?," Working Papers 2016-12, Faculty of Economic Sciences, University of Warsaw.
    4. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.
    5. Jiao, Peiran & Veiga, André & Walther, Ansgar, 2020. "Social media, news media and the stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 63-90.
    6. Au, Pak Hung, 2016. "Price reaction and disagreement over public signal," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 81-106.
    7. Needham, Katherine & Czajkowski, Mikołaj & Hanley, Nick & LaRiviere, Jacob, 2018. "What is the causal impact of information and knowledge in stated preference studies?," Resource and Energy Economics, Elsevier, vol. 54(C), pages 69-89.
    8. Xavier Gabaix, 2017. "Behavioral Inattention," NBER Working Papers 24096, National Bureau of Economic Research, Inc.
    9. Jacob LaRiviere & Mikolaj Czajkowski & Nick Hanley & Katherine Simpson, 2015. "What is the Causal Effect of Knowledge on Preferences?," Discussion Papers in Environment and Development Economics 2015-09, University of St. Andrews, School of Geography and Sustainable Development.
    10. Philippe Jehiel, 2022. "Analogy-Based Expectation Equilibrium and Related Concepts:Theory, Applications, and Beyond," Working Papers halshs-03735680, HAL.
    11. Wei Xiong, 2013. "Bubbles, Crises, and Heterogeneous Beliefs," NBER Working Papers 18905, National Bureau of Economic Research, Inc.
    12. Ignacio Esponda & Emanuel Vespa & Sevgi Yuksel, 2024. "Mental Models and Learning: The Case of Base-Rate Neglect," American Economic Review, American Economic Association, vol. 114(3), pages 752-782, March.
    13. Theresa Kuchler & Basit Zafar, 2019. "Personal Experiences and Expectations about Aggregate Outcomes," Journal of Finance, American Finance Association, vol. 74(5), pages 2491-2542, October.
    14. 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.
    15. Nimark, Kristoffer P. & Sundaresan, Savitar, 2019. "Inattention and belief polarization," Journal of Economic Theory, Elsevier, vol. 180(C), pages 203-228.
    16. Camelia M. Kuhnen, 2015. "Asymmetric Learning from Financial Information," Journal of Finance, American Finance Association, vol. 70(5), pages 2029-2062, October.
    17. Chunxin Jia & Yaping Wang & Wei Xiong, 2015. "Social Trust and Differential Reactions of Local and Foreign Investors to Public News," NBER Working Papers 21075, National Bureau of Economic Research, Inc.
    18. Aislinn Bohren & Daniel Hauser, 2018. "Social Learning with Model Misspeciification: A Framework and a Robustness Result," PIER Working Paper Archive 18-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jul 2018.
    19. Yong-Ho Cheon & Kuan-Hui Lee, 2018. "Maxing Out Globally: Individualism, Investor Attention, and the Cross Section of Expected Stock Returns," Management Science, INFORMS, vol. 64(12), pages 5807-5831, December.
    20. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1533-1570, Elsevier.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:brd:wpaper:110r4. 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: Andrea Luna (email available below). General contact details of provider: https://edirc.repec.org/data/gsbraus.html .

    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.