IDEAS home Printed from https://ideas.repec.org/p/hhs/cbsnow/2021_003.html
   My bibliography  Save this paper

Weighing Sample Evidence

Author

Listed:

Abstract

We model how sample evidence guides choice: An agent faces a number of alternative actions. For each action, she observes a sample of outcomes; she cannot see the distribution from where the sample was drawn. To make her choice, she evaluates the evidence for the hypothesis that an action is optimal. The strength of evidence in favor of the hypothesis is measured by the average decision utility of the outcomes in its sample; its weight gauges predictive validity and is approximated by the size of the sample. We identify necessary and sufficient conditions for her choice to be determined by the interaction of strength and weight, reflecting the determinants of confidence judgements documented in experiments (Griffin and Tversky, 1992). These conditions characterize a model consistent with non-trivial uncertainty attitudes and “frequentist" expected utility maximization.

Suggested Citation

  • Szwagrzak, Karol, 2021. "Weighing Sample Evidence," Working Papers 3-2021, Copenhagen Business School, Department of Economics.
    • Handle: RePEc:hhs:cbsnow:2021_003
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10398/6247b94a-4965-4271-ad2d-b63af960a700
    File Function: Full text
    Download Restriction: Full text not avaiable
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Blackorby,Charles & Bossert,Walter & Donaldson,David J., 2005. "Population Issues in Social Choice Theory, Welfare Economics, and Ethics," Cambridge Books, Cambridge University Press, number 9780521532587.
    2. Gravel, Nicolas & Marchant, Thierry & Sen, Arunava, 2018. "Conditional expected utility criteria for decision making under ignorance or objective ambiguity," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 79-95.
    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. Gilboa, Itzhak & Schmeidler, David, 1996. "Case-Based Optimization," Games and Economic Behavior, Elsevier, vol. 15(1), pages 1-26, July.
    5. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    6. Eddie Dekel & Barton L. Lipman & Aldo Rustichini, 2009. "Temptation-Driven Preferences," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 937-971.
    7. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, January.
    8. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    9. Eddie Dekel & Barton L. Lipman, 2012. "Costly Self‐Control and Random Self‐Indulgence," Econometrica, Econometric Society, vol. 80(3), pages 1271-1302, May.
    10. Gilboa, Itzhak & Schmeidler, David & Wakker, Peter P., 2002. "Utility in Case-Based Decision Theory," Journal of Economic Theory, Elsevier, vol. 105(2), pages 483-502, August.
    11. Dekel, Eddie & Lipman, Barton L & Rustichini, Aldo, 2001. "Representing Preferences with a Unique Subjective State Space," Econometrica, Econometric Society, vol. 69(4), pages 891-934, July.
    12. Amit Kothiyal & Vitalie Spinu & Peter P. Wakker, 2014. "Average Utility Maximization: A Preference Foundation," Operations Research, INFORMS, vol. 62(1), pages 207-218, February.
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    15. Faruk Gul & Wolfgang Pesendorfer, 2001. "Temptation and Self-Control," Econometrica, Econometric Society, vol. 69(6), pages 1403-1435, November.
    16. David S. Ahn, 2008. "Ambiguity Without a State Space," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(1), pages 3-28.
    17. Eddie Dekel & Barton L Lipman & Aldo Rustichini & Todd Sarver, 2007. "Representing Preferences with a Unique Subjective State Space: A Corrigendum -super-1," Econometrica, Econometric Society, vol. 75(2), pages 591-600, March.
    18. Kreps, David M, 1979. "A Representation Theorem for "Preference for Flexibility"," Econometrica, Econometric Society, vol. 47(3), pages 565-577, May.
    19. Gerard Debreu, 1959. "Topological Methods in Cardinal Utility Theory," Cowles Foundation Discussion Papers 76, Cowles Foundation for Research in Economics, Yale University.
    20. Wojciech Olszewski, 2007. "Preferences Over Sets of Lotteries -super-1," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(2), pages 567-595.
    21. Blackorby, Charles & Donaldson, David, 1984. "Social criteria for evaluating population change," Journal of Public Economics, Elsevier, vol. 25(1-2), pages 13-33, November.
    22. Wakker, Peter, 1993. "Additive representations on rank-ordered sets : II. The topological approach," Journal of Mathematical Economics, Elsevier, vol. 22(1), pages 1-26.
    23. Russell Golman & David Hagmann & George Loewenstein, 2017. "Information Avoidance," Journal of Economic Literature, American Economic Association, vol. 55(1), pages 96-135, March.
    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. Flores-Szwagrzak, Karol, 2022. "Learning by Convex Combination," Working Papers 16-2022, Copenhagen Business School, Department of Economics.
    2. Eddie Dekel & Barton L. Lipman, 2010. "How (Not) to Do Decision Theory," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 257-282, September.
    3. Nobuo Koida, 2018. "Anticipated stochastic choice," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(3), pages 545-574, May.
    4. André Lapied & Thomas Rongiconi, 2013. "Ambiguity as a Source of Temptation: Modeling Unstable Beliefs," Working Papers halshs-00797631, HAL.
    5. Daniele Pennesi, 2020. "Identity and information acquisition," Carlo Alberto Notebooks 610, Collegio Carlo Alberto, revised 2021.
    6. Daniele Pennesi, 2021. "Between Commitment and Flexibility: Revealing Anticipated Regret and Elation," Working papers 071, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    7. Gorno, Leandro, 2016. "Additive representation for preferences over menus in finite choice settings," Journal of Mathematical Economics, Elsevier, vol. 65(C), pages 41-47.
    8. Robin Cubitt & Gijs van de Kuilen & Sujoy Mukerji, 2020. "Discriminating Between Models of Ambiguity Attitude: a Qualitative Test," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 708-749.
    9. Barbos, Andrei, 2013. "A reference-dependent representation with subjective tastes," Journal of Mathematical Economics, Elsevier, vol. 49(2), pages 111-123.
    10. Ortoleva, Pietro, 2013. "The price of flexibility: Towards a theory of Thinking Aversion," Journal of Economic Theory, Elsevier, vol. 148(3), pages 903-934.
    11. Koida, Nobuo, 2022. "Indecisiveness, preference for flexibility, and a unique subjective state space," Journal of Mathematical Economics, Elsevier, vol. 103(C).
    12. Kaiser Karen & Schwabe Rainer, 2012. "Preference for Variety," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 12(1), pages 1-32, January.
    13. Chatterjee Kalyan & Krishna R. Vijay, 2012. "Uniquely Representing "A Preference for Uniformity"," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 12(1), pages 1-36, January.
    14. Riella, Gil, 2013. "Preference for Flexibility and Dynamic Consistency," Journal of Economic Theory, Elsevier, vol. 148(6), pages 2467-2482.
    15. Gayer, Gabrielle, 2010. "Perception of probabilities in situations of risk: A case based approach," Games and Economic Behavior, Elsevier, vol. 68(1), pages 130-143, January.
    16. Nicolas Gravel & Thierry Marchant, 2022. "Rank Dependent Weighted Average Utility Models for Decision Making under Ignorance or Objective Ambiguity," Working Papers hal-03817362, HAL.
    17. Leandro Gorno, 2010. "Additive representation for preferences over menus in finite choice settings," Working Papers 1292, Princeton University, Department of Economics, Econometric Research Program..
    18. Youichiro Higashi & Kazuya Hyogo & Gil Riella, 2020. "Dynamically Consistent Menu Preferences," KIER Working Papers 1047, Kyoto University, Institute of Economic Research.
    19. Veronika Köbberling & Peter P. Wakker, 2003. "Preference Foundations for Nonexpected Utility: A Generalized and Simplified Technique," Mathematics of Operations Research, INFORMS, vol. 28(3), pages 395-423, August.
    20. Higashi, Youichiro & Hyogo, Kazuya & Takeoka, Norio, 2009. "Subjective random discounting and intertemporal choice," Journal of Economic Theory, Elsevier, vol. 144(3), pages 1015-1053, May.

    More about this item

    Keywords

    Sample; Sample size; Uncertainty attitudes;
    All these keywords.

    JEL classification:

    • 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

    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:hhs:cbsnow:2021_003. 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: CBS Library Research Registration Team (email available below). General contact details of provider: https://edirc.repec.org/data/incbsdk.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.