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Measuring individual risk preferences

Author

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  • Catherine C. Eckel

    (Texas A&M University, USA)

Abstract

Risk aversion is an important factor in many settings, including individual decisions about investment or occupational choice, and government choices about policies affecting environmental, industrial, or health risks. Risk preferences are measured using surveys or incentivized games with real consequences. Reviewing the different approaches to measuring individual risk aversion shows that the best approach will depend on the question being asked and the study's target population. In particular, economists’ gold standard of incentivized games may not be superior to surveys in all settings.

Suggested Citation

  • Catherine C. Eckel, 2019. "Measuring individual risk preferences," IZA World of Labor, Institute of Labor Economics (IZA), pages 454-454, June.
    • Handle: RePEc:iza:izawol:journl:2019:n:454
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    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.
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    6. Catherine C. Eckel & Philip J. Grossman, 2008. "Forecasting Risk Attitudes: An Experimental Study Using Actual and Forecast Gamble Choices," Monash Economics Working Papers archive-01, Monash University, Department of Economics.
    7. Ola Andersson & Håkan J. Holm & Jean-Robert Tyran & Erik Wengström, 2016. "Risk Aversion Relates To Cognitive Ability: Preferences Or Noise?," Journal of the European Economic Association, European Economic Association, vol. 14(5), pages 1129-1154, October.
    8. Charness, Gary & Gneezy, Uri & Imas, Alex, 2013. "Experimental methods: Eliciting risk preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 87(C), pages 43-51.
    9. Chetan Dave & Catherine Eckel & Cathleen Johnson & Christian Rojas, 2010. "Eliciting risk preferences: When is simple better?," Journal of Risk and Uncertainty, Springer, vol. 41(3), pages 219-243, December.
    10. Paolo Crosetto & Antonio Filippin, 2016. "A theoretical and experimental appraisal of four risk elicitation methods," Experimental Economics, Springer;Economic Science Association, vol. 19(3), pages 613-641, September.
    11. Paolo Crosetto & Antonio Filippin, 2013. "A Theoretical and Experimental Appraisal of Five Risk Elicitation Methods," SOEPpapers on Multidisciplinary Panel Data Research 547, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Galizzi, Matteo M. & Machado, Sara R. & Miniaci, Raffaele, 2016. "Temporal stability, cross-validity, and external validity of risk preferences measures: experimental evidence from a UK representative sample," LSE Research Online Documents on Economics 67554, London School of Economics and Political Science, LSE Library.
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    Cited by:

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    2. David Johnson & John Barry Ryan, 2020. "Amazon Mechanical Turk workers can provide consistent and economically meaningful data," Southern Economic Journal, John Wiley & Sons, vol. 87(1), pages 369-385, July.
    3. Sigl, Lukas & Hirschauer, Norbert, 2024. "The hedging efficiency of wheat futures in various types of farms in Germany," SocArXiv pvq9t, Center for Open Science.
    4. Pace, Noemi & Daidone, Silvio, 2024. "Impact of development interventions on individual risk preferences: Evidence from a field-lab experiment and survey data," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 111(C).
    5. Jacob K Goeree & Bernardo Garcia-Pola, 2023. "A Non-Parametric Test of Risk Aversion," Papers 2308.02083, arXiv.org.
    6. 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.

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    More about this item

    Keywords

    risk aversion; risk preferences; incentivized measures; survey measures;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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