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Robust Inference in Risk Elicitation Tasks

Author

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  • Ola Andersson

    (Uppsala University and IFN)

  • H�kan J. Holm

    (Lund University, Department of Economics)

  • Jean-Robert Tyran

    (University of Vienna, Department of Economics and University of Copenhagen, Department of Economics)

  • Erik Wengström

    (University of Vienna, Department of Economics and University of Copenhagen, Department of Economics)

Abstract

Recent experimental evidence suggests that noisy behavior correlates strongly with cognitive ability. This puts previous studies that found a negative relation between cognitive ability and risk aversion into perspective and in particular raises the question of how to achieve robust inference in this domain. This paper shows that using structural estimation that models heterogeneity of noise in combination with a balanced design allows us to mitigate the bias problem. Our estimations show that cognitive ability is related to noisy behavior rather than risk preferences. We also find age and education to be strongly related to noise, but the personality characteristics obtained using the Big Five inventory, are less related to noise and more robustly correlated to risk preferences.

Suggested Citation

  • Ola Andersson & H�kan J. Holm & Jean-Robert Tyran & Erik Wengström, 2018. "Robust Inference in Risk Elicitation Tasks," Discussion Papers 18-09, University of Copenhagen. Department of Economics.
  • Handle: RePEc:kud:kuiedp:1809
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    Cited by:

    1. James J. Heckman & Tomáš Jagelka & Timothy D. Kautz, 2019. "Some Contributions of Economics to the Study of Personality," NBER Working Papers 26459, National Bureau of Economic Research, Inc.
    2. 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).
    3. Marco Santorsola & Rocco Caferra & Andrea Morone, 2023. "The salience of informed risk: an experimental analysis," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(9), pages 21-35, June.
    4. Jose Apesteguia & Miguel Ángel Ballester, 2020. "Random utility models with ordered types and domains," Economics Working Papers 1719, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Belzil, Christian & Pernaudet, Julie & Poinas, François, 2021. "Estimating Coherency between Survey Data and Incentivized Experimental Data," IZA Discussion Papers 14594, Institute of Labor Economics (IZA).
    6. Celse, Jeremy & Karakostas, Alexandros & Zizzo, Daniel John, 2023. "Relative risk taking and social curiosity," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 243-264.
    7. Thomas Meissner & David Albrecht, 2022. "Debt Aversion: Theory and Measurement," Papers 2207.07538, arXiv.org, revised Jul 2022.
    8. Boutin, Delphine & Petifour, Laurene & Megzari, Haris, 2023. "Permanent Instability of Preferences after COVID-19 Crisis: A Natural Experiment from Urban Burkina Faso," IZA Discussion Papers 16075, Institute of Labor Economics (IZA).
    9. Estepa-Mohedano, Lorenzo & Espinosa, María Paz, 2023. "Comparing risk elicitation in lotteries with visual or contextual aids," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    10. Holzmeister, Felix & Stefan, Matthias, 2019. "The Risk Elicitation Puzzle Revisited: Across-Methods (In)consistency?," OSF Preprints pj9u2, Center for Open Science.
    11. 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.
    12. Estepa-Mohedano, Lorenzo & Espinosa, Maria Paz, 2021. "Comparing risk elicitation in lotteries with visual or contextual framing aids," MPRA Paper 108440, University Library of Munich, Germany.
    13. Nicolas Eber & Patrick Roger & Tristan Roger, 2024. "Finance and intelligence: An overview of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 503-554, April.
    14. Apesteguia, Jose & Ballester, Miguel A., 2023. "Random utility models with ordered types and domains," Journal of Economic Theory, Elsevier, vol. 211(C).
    15. Delphine Boutin & Laurène Petifour & Haris Megzari, 2022. "Instability of preferences due to Covid-19 Crisis and emotions: a natural experiment from urban Burkina Faso," Working Papers hal-03623601, HAL.
    16. Felix Holzmeister & Matthias Stefan, 2019. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Working Papers 2019-19, Faculty of Economics and Statistics, Universität Innsbruck.
    17. 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.
    18. repec:jdm:journl:v:17:y:2022:i:4:p:883-936 is not listed on IDEAS
    19. Holden , Stein T. & Tilahun , Mesfin, 2019. "The Devil is in the Details: Risk Preferences, Choice List Design, and Measurement Error," CLTS Working Papers 3/19, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 16 Oct 2019.
    20. Tomáš Jagelka, 2020. "Are Economists’ Preferences Psychologists’ Personality Traits? A Structural Approach," ECONtribute Discussion Papers Series 014, University of Bonn and University of Cologne, Germany.
    21. Delphine BOUTIN & Laurène PETIFOUR & Haris MEGZARI, 2022. "Instability of preferences due to Covid-19 Crisis and emotions: a natural experiment from urban Burkina Faso," Bordeaux Economics Working Papers 2022-05, Bordeaux School of Economics (BSE).
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    More about this item

    Keywords

    Risk preference; cognitive ability; experiment; noise;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • 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

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