IDEAS home Printed from https://ideas.repec.org/a/kap/jrisku/v66y2023i1d10.1007_s11166-022-09398-5.html
   My bibliography  Save this article

Towards a typology of risk preference: Four risk profiles describe two-thirds of individuals in a large sample of the U.S. population

Author

Listed:
  • Renato Frey

    (University of Zurich
    Princeton University)

  • Shannon M. Duncan

    (Columbia University
    University of Pennsylvania)

  • Elke U. Weber

    (Princeton University)

Abstract

It has been a longstanding goal of the behavioral sciences to measure and model people’s risk preferences. In this article, we adopt a novel theoretical perspective of doing so and test to what extent specific types of individuals share similar risk profiles (i.e., configurations of multidimensional risk preferences). To this end, we analyzed data of a U.S. sample (N = 3,123) in a comprehensive and rigorous way, resulting in a twofold contribution. First, based on data from the Domain-Specific Risk-Taking scale (DOSPERT) and using a cross-validation procedure, we established a multidimensional trait space including general and domain-specific dimensions of risk preference. Second, we employed model-based cluster analyses in this multidimensional trait space, finding that 66% of participants can be described well with four basic risk profiles. In sum, the typological perspective proposed in this article has important implications for current theories of risk preference and the measurement of individual differences therein.

Suggested Citation

  • Renato Frey & Shannon M. Duncan & Elke U. Weber, 2023. "Towards a typology of risk preference: Four risk profiles describe two-thirds of individuals in a large sample of the U.S. population," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 1-17, February.
    • Handle: RePEc:kap:jrisku:v:66:y:2023:i:1:d:10.1007_s11166-022-09398-5
    DOI: 10.1007/s11166-022-09398-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11166-022-09398-5
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11166-022-09398-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    2. Armin Falk & Anke Becker & Thomas Dohmen & David Huffman & Uwe Sunde, 2023. "The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences," Management Science, INFORMS, vol. 69(4), pages 1935-1950, April.
    3. 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..
    4. Arslan, Ruben C. & Brümmer, Martin & Dohmen, Thomas & Drewelies, Johanna & Hertwig, Ralph & Wagner, Gert G., 2020. "How people know their risk preference," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10.
    5. Robert Jennrich & Peter Bentler, 2011. "Exploratory Bi-Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 537-549, October.
    6. repec:cup:judgdm:v:1:y:2006:i::p:33-47 is not listed on IDEAS
    7. Elke U. Weber & Richard A. Milliman, 1997. "Perceived Risk Attitudes: Relating Risk Perception to Risky Choice," Management Science, INFORMS, vol. 43(2), pages 123-144, February.
    8. Martin Gerlach & Beatrice Farb & William Revelle & Luís A. Nunes Amaral, 2018. "A robust data-driven approach identifies four personality types across four large data sets," Nature Human Behaviour, Nature, vol. 2(10), pages 735-742, October.
    9. Ann-Renée Blais & Elke U. Weber, 2006. "A Domain-Specific Risk-Taking (DOSPERT)Scale for Adult Populations," CIRANO Working Papers 2006s-24, CIRANO.
    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. Baláž, Vladimír & Chen, Jason Li & Williams, Allan M. & Li, Gang, 2024. "Stability of risk and uncertainty preferences in tourism," Annals of Tourism Research, Elsevier, vol. 105(C).

    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. Schaewitz, Johannes & Wang, Mei & Rieger, Marc Oliver, 2022. "Culture and Institutions: Long-lasting effects of communism on risk and time preferences of individuals in Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 785-829.
    2. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    3. Goytom Abraha Kahsay & Daniel Osberghaus, 2018. "Storm Damage and Risk Preferences: Panel Evidence from Germany," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 301-318, September.
    4. Heß, Moritz & Scheve, Christian von & Schupp, Jürgen & Wagner, Aiko & Wagner, Gert G., 2018. "Are Political Representatives More Risk-Loving Than the Electorate? Evidence from German Federal and State Parliaments," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 4, pages 1-7.
    5. Arslan, Ruben C. & Brümmer, Martin & Dohmen, Thomas & Drewelies, Johanna & Hertwig, Ralph & Wagner, Gert G., 2020. "How people know their risk preference," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10.
    6. Deck, Cary & Lee, Jungmin & Reyes, Javier A. & Rosen, Christopher C., 2013. "A failed attempt to explain within subject variation in risk taking behavior using domain specific risk attitudes," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 1-24.
    7. Paolo Crosetto & Antonio Filippin, 2013. "The “bomb” risk elicitation task," Journal of Risk and Uncertainty, Springer, vol. 47(1), pages 31-65, August.
    8. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    9. Rafaï, Ismaël & Blayac, Thierry & Dubois, Dimitri & Duchêne, Sébastien & Nguyen-Van, Phu & Ventelou, Bruno & Willinger, Marc, 2023. "Stated preferences outperform elicited preferences for predicting reported compliance with COVID-19 prophylactic measures," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    10. Thomas Dohmen & Simone Quercia & Jana Willrodt, 2023. "On the psychology of the relation between optimism and risk taking," Journal of Risk and Uncertainty, Springer, vol. 67(2), pages 193-214, October.
    11. Joshua Tasoff & Wenjie Zhang, 2022. "The Performance of Time-Preference and Risk-Preference Measures in Surveys," Management Science, INFORMS, vol. 68(2), pages 1149-1173, February.
    12. Willebrands, Daan & Lammers, Judith & Hartog, Joop, 2012. "A successful businessman is not a gambler. Risk attitude and business performance among small enterprises in Nigeria," Journal of Economic Psychology, Elsevier, vol. 33(2), pages 342-354.
    13. Gary Charness & Thomas Garcia & Theo Offerman & Marie Claire Villeval, 2020. "Do measures of risk attitude in the laboratory predict behavior under risk in and outside of the laboratory?," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 99-123, April.
    14. Andreas Hackethal & Michael Kirchler & Christine Laudenbach & Michael Razen & Annika Weber, 2023. "On the role of monetary incentives in risk preference elicitation experiments," Journal of Risk and Uncertainty, Springer, vol. 66(2), pages 189-213, April.
    15. Christian Ehm & Christine Kaufmann & Martin Weber, 2014. "Volatility Inadaptability: Investors Care About Risk, but Cannot Cope with Volatility," Review of Finance, European Finance Association, vol. 18(4), pages 1387-1423.
    16. Samek, Anya & Gray, Andre & Datar, Ashlesha & Nicosia, Nancy, 2021. "Adolescent time and risk preferences: Measurement, determinants and field consequences," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 460-488.
    17. Matthias Brachert & Walter Hyll & Abdolkarim Sadrieh, 2020. "Entry into self-employment and individuals’ risk-taking propensities," Small Business Economics, Springer, vol. 55(4), pages 1057-1074, December.
    18. Victor Stango & Jonathan Zinman, 2019. "We Are All Behavioral, More or Less: Measuring and Using Consumer-Level Behavioral Sufficient Statistics," Working Papers 19-14, Federal Reserve Bank of Philadelphia.
    19. Andreas Hack & Frauke Bieberstein & Nils D. Kraiczy, 2016. "Reference point formation and new venture creation," Small Business Economics, Springer, vol. 46(3), pages 447-465, March.
    20. Stefanescu, Razvan & Dumitriu, Ramona, 2015. "Alegerea soluţiilor pentru expunerile faţă de risc [Choosing solutions to risk exposures]," MPRA Paper 65074, University Library of Munich, Germany.

    More about this item

    Keywords

    Risk preference; Psychometric modeling; DOSPERT; Bayesian latent profile analyses;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:kap:jrisku:v:66:y:2023:i:1:d:10.1007_s11166-022-09398-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.