[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/aea/aejmic/v9y2017i1p123-51.html
   My bibliography  Save this article

Making Case-Based Decision Theory Directly Observable

Author

Listed:
  • Han Bleichrodt
  • Martin Filko
  • Amit Kothiyal
  • Peter P. Wakker
Abstract
Case-based decision theory (CBDT) provided a new way of revealing preferences, with decisions under uncertainty determined by similarities with cases in memory. This paper introduces a method to measure CBDT that requires no commitment to parametric families and that relates directly to decisions. Thus, CBDT becomes directly observable and can be used in prescriptive applications. Two experiments on real estate investments demonstrate the feasibility of our method. Our implementation of real incentives not only avoids the income effect, but also avoids interactions between different memories. We confirm CBDT's predictions except for one violation of separability of cases in memory.

Suggested Citation

  • Han Bleichrodt & Martin Filko & Amit Kothiyal & Peter P. Wakker, 2017. "Making Case-Based Decision Theory Directly Observable," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 123-151, February.
  • Handle: RePEc:aea:aejmic:v:9:y:2017:i:1:p:123-51
    Note: DOI: 10.1257/mic.20150172
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/articles?id=10.1257/mic.20150172
    Download Restriction: no

    File URL: https://www.aeaweb.org/articles/attachments?retrieve=wjgHDlu4HdskFH03Fr8dkFhSJDXTxUnz
    Download Restriction: no

    File URL: https://www.aeaweb.org/articles/attachments?retrieve=6mUIRsJ7wQq9b7IPxvcuVtam_92pzSzM
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    References listed on IDEAS

    as
    1. Gilboa, Itzhak & Lieberman, Offer & Schmeidler, David, 2011. "A similarity-based approach to prediction," Journal of Econometrics, Elsevier, vol. 162(1), pages 124-131, May.
    2. Dan Lovallo & Carmina Clarke & Colin Camerer, 2012. "Robust analogizing and the outside view: two empirical tests of case‐based decision making," Strategic Management Journal, Wiley Blackwell, vol. 33(5), pages 496-512, May.
    3. Eichberger, Jürgen & Guerdjikova, Ani, 2013. "Ambiguity, data and preferences for information – A case-based approach," Journal of Economic Theory, Elsevier, vol. 148(4), pages 1433-1462.
    4. 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.
    5. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
    6. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    7. Gayer Gabrielle & Gilboa Itzhak & Lieberman Offer, 2007. "Rule-Based and Case-Based Reasoning in Housing Prices," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-37, April.
    8. 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.
    9. Bernard, Carole & Ghossoub, Mario, 2009. "Static Portfolio Choice under Cumulative Prospect Theory," MPRA Paper 15446, University Library of Munich, Germany.
    10. Nicholas Bardsley, 2000. "Control Without Deception: Individual Behaviour in Free-Riding Experiments Revisited," Experimental Economics, Springer;Economic Science Association, vol. 3(3), pages 215-240, December.
    11. Starmer, Chris & Sugden, Robert, 1991. "Does the Random-Lottery Incentive System Elicit True Preferences? An Experimental Investigation," American Economic Review, American Economic Association, vol. 81(4), pages 971-978, September.
    12. Pape, Andreas Duus & Kurtz, Kenneth J., 2013. "Evaluating case-based decision theory: Predicting empirical patterns of human classification learning," Games and Economic Behavior, Elsevier, vol. 82(C), pages 52-65.
    13. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, October.
    14. Vivek F. Farias & Srikanth Jagabathula & Devavrat Shah, 2013. "A Nonparametric Approach to Modeling Choice with Limited Data," Management Science, INFORMS, vol. 59(2), pages 305-322, December.
    15. Itzhak Gilboa & David Schmeidler, 1996. "Act similarity in case-based decision theory (*)," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 9(1), pages 47-62.
    16. 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.
    17. Wolfgang Ossadnik & Dirk Wilmsmann & Benedikt Niemann, 2013. "Experimental evidence on case-based decision theory," Theory and Decision, Springer, vol. 75(2), pages 211-232, August.
    18. Henry Stott, 2006. "Cumulative prospect theory's functional menagerie," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 101-130, March.
    19. Blonski, Matthias, 1999. "Social learning with case-based decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 38(1), pages 59-77, January.
    20. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    21. Brit Grosskopf & Rajiv Sarin & Elizabeth Watson, 2015. "An experiment on case-based decision making," Theory and Decision, Springer, vol. 79(4), pages 639-666, December.
    22. Nicholas Bardsley, 2000. "Control without Deception," Tinbergen Institute Discussion Papers 00-107/1, Tinbergen Institute.
    23. Camerer, Colin F, 1989. "An Experimental Test of Several Generalized Utility Theories," Journal of Risk and Uncertainty, Springer, vol. 2(1), pages 61-104, April.
    24. Pape, Andreas & Kurtz, Kenneth, 2013. "Evaluating Case-based Decision Theory: Predicting Empirical Patterns of Human Classification Learning (Extensions)," MPRA Paper 45206, University Library of Munich, Germany.
    25. Guerdjikova, Ani, 2008. "Case-based learning with different similarity functions," Games and Economic Behavior, Elsevier, vol. 63(1), pages 107-132, May.
    26. 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.
    27. Ignacio Esponda Jr. & Emanuel Vespa Jr., 2014. "Hypothetical Thinking and Information Extraction in the Laboratory," American Economic Journal: Microeconomics, American Economic Association, vol. 6(4), pages 180-202, November.
    28. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
    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. Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
    2. Roxane Bricet, 2018. "Precise versus imprecise datasets: revisiting ambiguity attitudes in the Ellsberg paradox," THEMA Working Papers 2018-08, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    3. Ilke Aydogan & Yu Gao, 2020. "Experience and rationality under risk: re-examining the impact of sampling experience," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1100-1128, December.
    4. Gilboa, Itzhak & Minardi, Stefania & Samuelson, Larry, 2020. "Theories and cases in decisions under uncertainty," Games and Economic Behavior, Elsevier, vol. 123(C), pages 22-40.
    5. Todd Guilfoos & Andreas Pape, 2016. "Predicting human cooperation in the Prisoner’s Dilemma using case-based decision theory," Theory and Decision, Springer, vol. 80(1), pages 1-32, January.
    6. Cheng, Xiu & Long, Ruyin & Chen, Hong, 2020. "A policy utility dislocation model based on prospect theory: A case study of promoting policies with low-carbon lifestyle," Energy Policy, Elsevier, vol. 137(C).
    7. Benjamin Radoc & Robert Sugden & Theodore L. Turocy, 2019. "Correlation neglect and case-based decisions," Journal of Risk and Uncertainty, Springer, vol. 59(1), pages 23-49, August.
    8. Benjamin Radoc, 2020. "Bandit with similarity information," Department of Economics, Ateneo de Manila University, Working Paper Series 202002, Department of Economics, Ateneo de Manila University.

    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. Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
    2. Ilke Aydogan & Yu Gao, 2020. "Experience and rationality under risk: re-examining the impact of sampling experience," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1100-1128, December.
    3. Nathalie Etchart-Vincent & Olivier l’Haridon, 2011. "Monetary incentives in the loss domain and behavior toward risk: An experimental comparison of three reward schemes including real losses," Journal of Risk and Uncertainty, Springer, vol. 42(1), pages 61-83, February.
    4. Aurélien Baillon & Han Bleichrodt & Vitalie Spinu, 2020. "Searching for the Reference Point," Management Science, INFORMS, vol. 66(1), pages 93-112, January.
    5. Cathleen Johnson & Aurélien Baillon & Han Bleichrodt & Zhihua Li & Dennie Dolder & Peter P. Wakker, 2021. "Prince: An improved method for measuring incentivized preferences," Journal of Risk and Uncertainty, Springer, vol. 62(1), pages 1-28, February.
    6. Glenn W. Harrison & J. Todd Swarthout, 2016. "Cumulative Prospect Theory in the Laboratory: A Reconsideration," Experimental Economics Center Working Paper Series 2016-04, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    7. 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.
    8. M. Huang & A. D. Pape, 2020. "The Impact of Online Consumer Reviews on Online Sales: The Case-Based Decision Theory Approach," Journal of Consumer Policy, Springer, vol. 43(3), pages 463-490, September.
    9. Brit Grosskopf & Rajiv Sarin & Elizabeth Watson, 2015. "An experiment on case-based decision making," Theory and Decision, Springer, vol. 79(4), pages 639-666, December.
    10. Ryan O. Murphy & Robert H. W. ten Brincke, 2018. "Hierarchical Maximum Likelihood Parameter Estimation for Cumulative Prospect Theory: Improving the Reliability of Individual Risk Parameter Estimates," Management Science, INFORMS, vol. 64(1), pages 308-328, January.
    11. Radoc, Benjamin, 2018. "Case-based investing: Stock selection under uncertainty," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 53-59.
    12. Todd Guilfoos & Andreas Pape, 2016. "Predicting human cooperation in the Prisoner’s Dilemma using case-based decision theory," Theory and Decision, Springer, vol. 80(1), pages 1-32, January.
    13. Jinrui Pan & Craig S. Webb & Horst Zank, 2019. "Delayed probabilistic risk attitude: a parametric approach," Theory and Decision, Springer, vol. 87(2), pages 201-232, September.
    14. Mohammed Abdellaoui & Han Bleichrodt & Hilda Kammoun, 2013. "Do financial professionals behave according to prospect theory? An experimental study," Theory and Decision, Springer, vol. 74(3), pages 411-429, March.
    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. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    17. Daniel R. Cavagnaro & Richard Gonzalez & Jay I. Myung & Mark A. Pitt, 2013. "Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach," Management Science, INFORMS, vol. 59(2), pages 358-375, February.
    18. Benjamin Radoc, 2020. "Bandit with similarity information," Department of Economics, Ateneo de Manila University, Working Paper Series 202002, Department of Economics, Ateneo de Manila University.
    19. Schunk, Daniel & Winter, Joachim, 2009. "The relationship between risk attitudes and heuristics in search tasks: A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 347-360, August.
    20. Daniel Navarro-Martinez & Graham Loomes & Andrea Isoni & David Butler & Larbi Alaoui, 2018. "Boundedly rational expected utility theory," Journal of Risk and Uncertainty, Springer, vol. 57(3), pages 199-223, December.

    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

    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:aea:aejmic:v:9:y:2017:i:1:p:123-51. 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.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.