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Higher Order Risk Preferences: New Experimental Measures, Determinants and Field Behavior

Author

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  • Sebastian Schneider

    (Max Planck Institute for Research on Collective Goods, Bonn)

  • Matthias Sutter

    (Max Planck Institute for Research on Collective Goods, Bonn)

Abstract

We use a novel method to elicit and measure higher order risk preferences (prudence and temperance) in an experiment with 658 adolescents. In line with theoretical predictions, we find that higher order risk preferences – particularly prudence – are strongly related to adolescents' field behavior, including their financial decision making, eco-friendly behavior, and health status, including addictive behavior. Most importantly, we show that dropping prudence and temperance from the analysis of students' field behavior would yield largely misleading conclusions about the relation of risk aversion to these domains of field behavior. Thus our paper puts previous work that ignored higher order risk preferences into an encompassing perspective and clarifies which orders of risk preferences can help understand field behavior of adolescents.

Suggested Citation

  • Sebastian Schneider & Matthias Sutter, 2020. "Higher Order Risk Preferences: New Experimental Measures, Determinants and Field Behavior," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2020_22, Max Planck Institute for Research on Collective Goods.
  • Handle: RePEc:mpg:wpaper:2020_22
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    File URL: http://www.coll.mpg.de/pdf_dat/2020_22online.pdf
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    References listed on IDEAS

    as
    1. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    2. Joseph P. Romano & Michael Wolf, 2005. "Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 94-108, March.
    3. Emad Abd Elmessih Shehata, 2011. "RIDGEREG: Stata module to compute Ridge Regression Models," Statistical Software Components S457347, Boston College Department of Economics, revised 29 Dec 2012.
    4. Romano, Joseph P. & Wolf, Michael, 2016. "Efficient computation of adjusted p-values for resampling-based stepdown multiple testing," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 38-40.
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    Cited by:

    1. List, Greta & List, John A. & Ramirez, Lina M. & Samek, Anya, 2022. "Time and risk preferences of children predict health behaviors but not BMI," Economics Letters, Elsevier, vol. 218(C).
    2. Angerer, Silvia & Dutcher, E. Glenn & Glätzle-Rützler, Daniela & Lergetporer, Philipp & Sutter, Matthias, 2021. "The Formation of Risk Preferences through Small-Scale Events," IZA Discussion Papers 14679, Institute of Labor Economics (IZA).
    3. Werthschulte, Madeline & Löschel, Andreas, 2021. "On the role of present bias and biased price beliefs in household energy consumption," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    4. Irene Mussio & Maximiliano Sosa Andrés & Abdul H Kidwai, 2023. "Higher order risk attitudes in the time of COVID-19: an experimental study," Oxford Economic Papers, Oxford University Press, vol. 75(1), pages 163-182.
    5. Thomas Meissner & Xavier Gassmann & Corinne Faure & Joachim Schleich, 2023. "Individual characteristics associated with risk and time preferences: A multi country representative survey," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 77-107, February.

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    More about this item

    Keywords

    Higher order risk preferences; prudence; temperance; risk aversion; field behavior; adolescents; health; addictive behavior; smartphone addiction; experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • 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
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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