IDEAS home Printed from https://ideas.repec.org/p/ven/wpaper/2012_23.html
   My bibliography  Save this paper

Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach

Author

Listed:
  • Noemi Pace

    (Department of Economics, University Of Venice C� Foscari)

  • Giuseppe Attanasi

    (University of Strasbourg)

  • Christian Gollier

    (Toulouse School of Economics)

  • Aldo Montesano

    (Bocconi University, Milan)

Abstract

We define coherent-ambiguity aversion within the Klibanoff, Marinacci and Mukerji (2005) smooth ambiguity model (henceforth KMM) as the combination of choice-ambiguity aversion and value-ambiguity aversion. We analyze theoretically five ambiguous decision tasks, where a subject faces two-stage lotteries with binomial, uniform or unknown second-order probabilities. We check our theoretical predictions through a 10-task laboratory experiment. In (unambiguous) tasks 1-5, we elicit risk aversion both through a portfolio choice method and through a BDM mechanism. In (ambiguous) tasks 6-10, we elicit choice-ambiguity aversion through the portfolio choice method and value-ambiguity aversion through the BDM mechanism. We find that more than 75% of classified subjects behave according to the KMM model in all tasks 6-10, independent of their degree of risk aversion. Further, the percentage of coherently-ambiguity-averse subjects is lower in the binomial than in the uniform and in the unknown treatment, with only the latter difference being significant. Finally, highly-risk-averse subjects are more prone to coherent-ambiguity.

Suggested Citation

  • Noemi Pace & Giuseppe Attanasi & Christian Gollier & Aldo Montesano, 2012. "Eliciting ambiguity aversion in unknown and in compound lotteries: A KMM experimental approach," Working Papers 2012_23, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2012_23
    as

    Download full text from publisher

    File URL: https://www.unive.it/web/fileadmin/user_upload/dipartimenti/DEC/doc/Pubblicazioni_scientifiche/working_papers/2012/WP_DSE_attanasi_gollier_montesano_pace_23_12.pdf
    File Function: First version, 2012
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Sujoy Chakravarty & Jaideep Roy, 2009. "Recursive expected utility and the separation of attitudes towards risk and ambiguity: an experimental study," Theory and Decision, Springer, vol. 66(3), pages 199-228, March.
    2. Larry G. Epstein, 2010. "A Paradox for the “Smooth Ambiguity” Model of Preference," Econometrica, Econometric Society, vol. 78(6), pages 2085-2099, November.
    3. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2012. "On the Smooth Ambiguity Model: A Reply," Econometrica, Econometric Society, vol. 80(3), pages 1303-1321, May.
    4. Michèle Cohen & Jean-Marc Tallon & Jean-Christophe Vergnaud, 2011. "An experimental investigation of imprecision attitude and its relation with risk attitude and impatience," Theory and Decision, Springer, vol. 71(1), pages 81-109, July.
    5. Arthur Snow, 2010. "Ambiguity and the value of information," Journal of Risk and Uncertainty, Springer, vol. 40(2), pages 133-145, April.
    6. John D. Hey & Noemi Pace, 2018. "The explanatory and predictive power of non two-stage-probability theories of decision making under ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 6, pages 139-167, World Scientific Publishing Co. Pte. Ltd..
    7. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    8. Anna Conte & John D. Hey, 2018. "Assessing multiple prior models of behaviour under ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 7, pages 169-188, World Scientific Publishing Co. Pte. Ltd..
    9. John D. Hey & Gianna Lotito & Anna Maffioletti, 2018. "The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 8, pages 189-219, World Scientific Publishing Co. Pte. Ltd..
    10. Camerer, Colin & Weber, Martin, 1992. "Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 325-370, October.
    11. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    12. Yoram Halevy, 2007. "Ellsberg Revisited: An Experimental Study," Econometrica, Econometric Society, vol. 75(2), pages 503-536, March.
    13. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2005. "A Smooth Model of Decision Making under Ambiguity," Econometrica, Econometric Society, vol. 73(6), pages 1849-1892, November.
    14. David Ahn & Syngjoo Choi & Douglas Gale & Shachar Kariv, 2014. "Estimating ambiguity aversion in a portfolio choice experiment," Quantitative Economics, Econometric Society, vol. 5, pages 195-223, July.
    15. Karni, Edi & Safra, Zvi, 1987. ""Preference Reversal' and the Observability of Preferences by Experimental Methods," Econometrica, Econometric Society, vol. 55(3), pages 675-685, May.
    16. John Quiggin, 2007. "Ambiguity and the Value of Information: An Almost-objective Events Analysis," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 30(3), pages 409-414, March.
    17. Machina, Mark J, 2001. "Almost-Objective Uncertainty," University of California at San Diego, Economics Working Paper Series qt3ps1k85f, Department of Economics, UC San Diego.
    18. Carmela Di Mauro & Anna Maffioletti, 2004. "Attitudes to risk and attitudes to uncertainty: experimental evidence," Applied Economics, Taylor & Francis Journals, vol. 36(4), pages 357-372.
    19. Cohen, Michele & Jaffray, Jean-Yves & Said, Tanios, 1987. "Experimental comparison of individual behavior under risk and under uncertainty for gains and for losses," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(1), pages 1-22, February.
    20. Mark Machina, 2004. "Almost-objective uncertainty," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 24(1), pages 1-54, July.
    21. Giuseppe Attanasi & Aldo Montesano, 2012. "The price for information about probabilities and its relation with risk and ambiguity," Theory and Decision, Springer, vol. 73(1), pages 125-160, July.
    22. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    23. Christian Gollier, 2001. "Should we beware of the Precautionary Principle?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 16(33), pages 302-327.
    24. K. J. Arrow, 1964. "The Role of Securities in the Optimal Allocation of Risk-bearing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 31(2), pages 91-96.
    25. Andersen, Steffen & Fountain, John & Harrison, Glenn W. & Rutström, Elisabet E., 2009. "Estmating Aversion to Uncertainty," Working Papers 07-2009, Copenhagen Business School, Department of Economics.
    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. Giuseppe Attanasi & Christian Gollier & Aldo Montesano & Noemi Pace, 2014. "Eliciting ambiguity aversion in unknown and in compound lotteries: a smooth ambiguity model experimental study," Theory and Decision, Springer, vol. 77(4), pages 485-530, December.
    2. Robin Cubitt & Gijs Kuilen & Sujoy Mukerji, 2018. "The strength of sensitivity to ambiguity," Theory and Decision, Springer, vol. 85(3), pages 275-302, October.
    3. Roxane Bricet, 2018. "The price for instrumentally valuable information," THEMA Working Papers 2018-10, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    4. Giuseppe Attanasi & Aldo Montesano, 2012. "The price for information about probabilities and its relation with risk and ambiguity," Theory and Decision, Springer, vol. 73(1), pages 125-160, July.
    5. Roxane Bricet, 2018. "Preferences for information precision under ambiguity," THEMA Working Papers 2018-09, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    6. Christoph Bühren & Fabian Meier & Marco Pleßner, 2023. "Ambiguity aversion: bibliometric analysis and literature review of the last 60 years," Management Review Quarterly, Springer, vol. 73(2), pages 495-525, June.
    7. Prokosheva, Sasha, 2016. "Comparing decisions under compound risk and ambiguity: The importance of cognitive skills," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 64(C), pages 94-105.
    8. John D. Hey & Noemi Pace, 2018. "The explanatory and predictive power of non two-stage-probability theories of decision making under ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 6, pages 139-167, World Scientific Publishing Co. Pte. Ltd..
    9. Jeffrey Butler & Luigi Guiso & Tullio Jappelli, 2014. "The role of intuition and reasoning in driving aversion to risk and ambiguity," Theory and Decision, Springer, vol. 77(4), pages 455-484, December.
    10. Calford, Evan M., 2020. "Uncertainty aversion in game theory: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 720-734.
    11. My, Kene Boun & Brunette, Marielle & Couture, Stéphane & Van Driessche, Sarah, 2024. "Are ambiguity preferences aligned with risk preferences?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 111(C).
    12. Johanna Etner & Meglena Jeleva & Jean‐Marc Tallon, 2012. "Decision Theory Under Ambiguity," Journal of Economic Surveys, Wiley Blackwell, vol. 26(2), pages 234-270, April.
    13. Enrica Carbone & Konstantinos Georgalos & Gerardo Infante, 2019. "Individual vs. group decision-making: an experiment on dynamic choice under risk and ambiguity," Theory and Decision, Springer, vol. 87(1), pages 87-122, July.
    14. Steffen Andersen & John Fountain & Glenn Harrison & Arne Hole & E. Rutström, 2012. "Inferring beliefs as subjectively imprecise probabilities," Theory and Decision, Springer, vol. 73(1), pages 161-184, July.
    15. Adam Dominiak & Wendelin Schnedler, 2011. "Attitudes toward uncertainty and randomization: an experimental study," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 48(2), pages 289-312, October.
    16. Robin Cubitt & Gijs van de Kuilen & Sujoy Mukerji, 2020. "Discriminating Between Models of Ambiguity Attitude: a Qualitative Test," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 708-749.
    17. Daniela Di Cagno & Daniela Grieco, 2019. "Measuring and Disentangling Ambiguity and Confidence in the Lab," Games, MDPI, vol. 10(1), pages 1-22, February.
    18. Sasha Prokosheva, 2014. "Comparing Decisions under Compound Risk and Ambiguity: The Importance of Cognitive Skills," CERGE-EI Working Papers wp525, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    19. Wu, Keyu & Fehr, Ernst & Hofland, Sean & Schonger, Martin, 2024. "On the Psychological Foundations of Ambiguity and Compound Risk Aversion," IZA Discussion Papers 17032, Institute of Labor Economics (IZA).
    20. Milos Borozan & Loreta Cannito & Barbara Luppi, 2022. "A tale of two ambiguities: A conceptual overview of findings from economics and psychology," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 6(S1), pages 11-21, July.

    More about this item

    Keywords

    coherent-ambiguity aversion; value-ambiguity aversion; choice-ambiguity aversion; smooth ambiguity model; binomial distribution; uniform distribution; unknown urn.;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ven:wpaper:2012_23. 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: Sassano Sonia (email available below). General contact details of provider: https://edirc.repec.org/data/dsvenit.html .

    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.