IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/26258.html
   My bibliography  Save this paper

Modeling Imprecision in Perception, Valuation and Choice

Author

Listed:
  • Michael Woodford

Abstract

Traditional decision theory assumes that people respond to the exact features of the options available to them, but observed behavior seems much less precise. This review considers ways of introducing imprecision into models of economic decision making, and stresses the usefulness of analogies with the way that imprecise perceptual judgments are modeled in psychophysics — the branch of experimental psychology concerned with the quantitative relationship between objective features of an observer's environment and elicited reports about their subjective appearance. It reviews key ideas from psychophysics, provides examples of the kinds of data that motivate them, and proposes lessons for economic modeling. Applications include stochastic choice, choice under risk, decoy effects in marketing, global game models of strategic interaction, and delayed adjustment of prices in response to monetary disturbances.

Suggested Citation

  • Michael Woodford, 2019. "Modeling Imprecision in Perception, Valuation and Choice," NBER Working Papers 26258, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26258
    Note: ME
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w26258.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Timothy B. Heath & Subimal Chatterjee, 1995. "Asymmetric Decoy Effects on Lower-Quality Versus Higher-Quality Brands: Meta-Analytic and Experimental Evidence," Post-Print hal-00670480, HAL.
    2. George-Marios Angeletos & Zhen Huo, 2021. "Myopia and Anchoring," American Economic Review, American Economic Association, vol. 111(4), pages 1166-1200, April.
    3. Frederick Mosteller & Philip Nogee, 1951. "An Experimental Measurement of Utility," Journal of Political Economy, University of Chicago Press, vol. 59(5), pages 371-371.
    4. Jakub Steiner & Colin Stewart, 2016. "Perceiving Prospects Properly," American Economic Review, American Economic Association, vol. 106(7), pages 1601-1631, July.
    5. Heath, Timothy B & Chatterjee, Subimal, 1995. "Asymmetric Decoy Effects on Lower-Quality versus Higher-Quality Brands: Meta-analytic and Experimental Evidence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(3), pages 268-284, December.
    6. Paulo Natenzon, 2019. "Random Choice and Learning," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 419-457.
    7. Huber, Joel & Payne, John W & Puto, Christopher, 1982. "Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 90-98, June.
    8. Gerhardt, Holger & Biele, Guido P. & Heekeren, Hauke R. & Uhlig, Harald, 2016. "Cognitive load increases risk aversion," SFB 649 Discussion Papers 2016-011, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    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. Jerome R. Busemeyer & Jörg Rieskamp, 2014. "Psychological research and theories on preferential choice," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 3, pages 49-72, Edward Elgar Publishing.
    2. Howard Kunreuther & Erwann Michel-Kerjan, 2015. "Demand for fixed-price multi-year contracts: Experimental evidence from insurance decisions," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 171-194, October.
    3. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.
    4. Salvatore Nunnari & Jan Zapal, 2017. "A Model of Focusing in Political Choice," Working Papers 599, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    5. Castillo, Geoffrey, 2020. "The attraction effect and its explanations," Games and Economic Behavior, Elsevier, vol. 119(C), pages 123-147.
    6. Michael Canty & Felix Josua Lang & Susanne Jana Adler & Marcel Lichters & Marko Sarstedt, 2024. "Caffeine’s complex influence on the attraction effect: a mixed bag of outcomes," Marketing Letters, Springer, vol. 35(3), pages 451-476, September.
    7. Li, Feng & Du, Timon C. & Wei, Ying, 2020. "Enhancing supply chain decisions with consumers’ behavioral factors: An illustration of decoy effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    8. Mohr, Peter N. C. & Heekeren, Hauke R. & Rieskamp, Jörg, 2017. "Attraction Effect in Risky Choice Can Be Explained by Subjective Distance Between Choice Alternatives," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7, pages 1-10.
    9. Batley, Richard & Hess, Stephane, 2016. "Testing for regularity and stochastic transitivity using the structural parameter of nested logit," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 355-376.
    10. Sürücü, Oktay & Djawadi, Behnud Mir & Recker, Sonja, 2019. "The asymmetric dominance effect: Reexamination and extension in risky choice – An experimental study," Journal of Economic Psychology, Elsevier, vol. 73(C), pages 102-122.
    11. Jörg Rieskamp & Jerome R. Busemeyer & Barbara A. Mellers, 2006. "Extending the Bounds of Rationality: Evidence and Theories of Preferential Choice," Journal of Economic Literature, American Economic Association, vol. 44(3), pages 631-661, September.
    12. Mehran Spitmaan & Oihane Horno & Emily Chu & Alireza Soltani, 2019. "Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-31, October.
    13. Yuin Jeong & Sangheon Oh & Younah Kang & Sung-Hee Kim, 2021. "Impacts of Visualizations on Decoy Effects," IJERPH, MDPI, vol. 18(23), pages 1-19, December.
    14. Marco Marini & Alessandro Ansani & Fabio Paglieri, 2020. "Attraction comes from many sources: Attentional and comparative processes in decoy effects," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(5), pages 704-726, September.
    15. repec:cup:judgdm:v:15:y:2020:i:5:p:704-726 is not listed on IDEAS
    16. Zhang, Tao & Zhang, David, 2007. "Agent-based simulation of consumer purchase decision-making and the decoy effect," Journal of Business Research, Elsevier, vol. 60(8), pages 912-922, August.
    17. Davies, Antony & Cline, Thomas W., 2005. "A consumer behavior approach to modeling monopolistic competition," Journal of Economic Psychology, Elsevier, vol. 26(6), pages 797-826, December.
    18. Ronayne, David & Brown, Gordon D.A., 2016. "Multi-attribute decision by sampling: An account of the attraction, comprimise and similarity effects," The Warwick Economics Research Paper Series (TWERPS) 1124, University of Warwick, Department of Economics.
    19. Slaughter, Jerel E. & Bagger, Jessica & Li, Andrew, 2006. "Context effects on group-based employee selection decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 100(1), pages 47-59, May.
    20. Müller, Holger & Benjamin Kroll, Eike & Vogt, Bodo, 2010. "“Fact or artifact? Empirical evidence on the robustness of compromise effects in binding and non-binding choice contextsâ€," Journal of Retailing and Consumer Services, Elsevier, vol. 17(5), pages 441-448.
    21. Linhai Wu & Pingping Liu & Xiujuan Chen & Wuyang Hu & Xuesen Fan, 2021. "Contents of product attributes and the decoy effect: A study on traceable pork from the perspective of consumer utility," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 974-984, June.

    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:nbr:nberwo:26258. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.