IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v87y2022i3d10.1007_s11336-021-09839-1.html
   My bibliography  Save this article

A Censored Mixture Model for Modeling Risk Taking

Author

Listed:
  • Nienke F. S. Dijkstra

    (Erasmus University Rotterdam)

  • Henning Tiemeier

    (Erasmus University Rotterdam
    HARVARD T.H. CHAN SCHOOL OF PUBLIC HEALTH)

  • Bernd Figner

    (Radboud University, Behavioural Science Institute and Donders Institute for Brain, Cognition and Behaviour)

  • Patrick J. F. Groenen

    (Erasmus University Rotterdam)

Abstract

Risk behavior has substantial consequences for health, well-being, and general behavior. The association between real-world risk behavior and risk behavior on experimental tasks is well documented, but their modeling is challenging for several reasons. First, many experimental risk tasks may end prematurely leading to censored observations. Second, certain outcome values can be more attractive than others. Third, a priori unknown groups of participants can react differently to certain risk-levels. Here, we propose the censored mixture model which models risk taking while dealing with censoring, attractiveness to certain outcomes, and unobserved individual risk preferences, next to experimental conditions.

Suggested Citation

  • Nienke F. S. Dijkstra & Henning Tiemeier & Bernd Figner & Patrick J. F. Groenen, 2022. "A Censored Mixture Model for Modeling Risk Taking," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 1103-1129, September.
    • Handle: RePEc:spr:psycho:v:87:y:2022:i:3:d:10.1007_s11336-021-09839-1
    DOI: 10.1007/s11336-021-09839-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11336-021-09839-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11336-021-09839-1?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. Felix Holzmeister & Matthias Stefan, 2021. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 593-616, June.
    2. Andreas Pedroni & Renato Frey & Adrian Bruhin & Gilles Dutilh & Ralph Hertwig & Jörg Rieskamp, 2017. "The risk elicitation puzzle," Nature Human Behaviour, Nature, vol. 1(11), pages 803-809, November.
    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. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    2. Kopsacheilis, Orestis & Goerg, Sebastian J., 2023. "Order Effects in Eliciting Preferences," IZA Discussion Papers 16343, Institute of Labor Economics (IZA).
    3. Felix Holzmeister & Christoph Huber & Stefan Palan, 2022. "A critical perspective on the conceptualization of risk in behavioral and experimental finance," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 30, pages 408-413, Edward Elgar Publishing.
    4. Brice Corgnet & Roberto Hernán González, 2023. "On The Appeal Of Complexity," Working Papers 2312, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    5. repec:jdm:journl:v:17:y:2022:i:4:p:883-936 is not listed on IDEAS
    6. Balcombe, Kelvin & Fraser, Iain, 2024. "A Note on an Alternative Approach to Experimental Design of Lottery Prospects," MPRA Paper 119743, University Library of Munich, Germany.
    7. 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).
    8. Jacob K Goeree & Bernardo Garcia-Pola, 2023. "A Non-Parametric Test of Risk Aversion," Papers 2308.02083, arXiv.org.
    9. repec:cup:judgdm:v:17:y:2022:i:4:p:883-936 is not listed on IDEAS
    10. Dalton, Patricio S. & Nhung, Nguyen & Rüschenpöhler, Julius, 2020. "Worries of the poor: The impact of financial burden on the risk attitudes of micro-entrepreneurs," Journal of Economic Psychology, Elsevier, vol. 79(C).
    11. repec:cup:judgdm:v:14:y:2019:i:3:p:234-279 is not listed on IDEAS
    12. James Alm & Antoine Malézieux, 2021. "40 years of tax evasion games: a meta-analysis," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 699-750, September.
    13. Wang, Di, 2021. "Attention-driven probability weighting," Economics Letters, Elsevier, vol. 203(C).
    14. Shambhavi Tiwari & Morten Moshagen & Benjamin E. Hilbig & Ingo Zettler, 2021. "The Dark Factor of Personality and Risk-Taking," IJERPH, MDPI, vol. 18(16), pages 1-18, August.
    15. Marianne Lefebvre & Estelle Midler & Philippe Bontems, 2020. "Adoption of Environment-Friendly Agricultural Practices with Background Risk: Experimental Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(2), pages 405-428, July.
    16. Schneider, Sebastian O. & Sutter, Matthias, 2020. "Higher Order Risk Preferences: Experimental Measures, Determinants and Related Field Behavior," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224643, Verein für Socialpolitik / German Economic Association.
    17. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    18. Holzmeister, Felix & Stefan, Matthias, 2019. "The Risk Elicitation Puzzle Revisited: Across-Methods (In)consistency?," OSF Preprints pj9u2, Center for Open Science.
    19. 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.
    20. 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.
    21. Fabien Perez & Guillaume Hollard & Radu Vranceanu, 2021. "How serious is the measurement-error problem in risk-aversion tasks?," Journal of Risk and Uncertainty, Springer, vol. 63(3), pages 319-342, December.
    22. Friedman, Daniel & Habib, Sameh & James, Duncan & Crockett, Sean, 2018. "Varieties of risk elicitation," Discussion Papers, Research Professorship Market Design: Theory and Pragmatics SP II 2018-501, WZB Berlin Social Science Center.
    23. Mike Farjam & Olexandr Nikolaychuk & Giangiacomo Bravo, 2019. "Investing into climate change mitigation despite the risk of failure," Climatic Change, Springer, vol. 154(3), pages 453-460, June.

    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:spr:psycho:v:87:y:2022:i:3:d:10.1007_s11336-021-09839-1. 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.