IDEAS home Printed from https://ideas.repec.org/p/eve/wpaper/01-16.html
   My bibliography  Save this paper

Attitude towards Information and Non-Expected Utility Preferences : a Characterization by Choice Functions

Author

Listed:
  • Marc-Arthur Diaye

    (EPEE, Université d’Evry and CREST (LSM))

  • Jean-Max Koskievic

    (EUREQua, Université Paris I)

Abstract

In the Allais paradox, if an agent’s preferences violate independence axiom, the (non- Expected Utility) decision maker appears to be prone to dynamic inconsistency, that is in some sequential decision problem he may be expected to embark upon (action) plans which he is not going to follow through. Moreover, Wakker (1988) proves that non-EU decision maker can be made worse o¤, in dynamic choice setting, by getting a prior knowledge of what nature’s moves will be. Thus, dynamic inconsistency and Information aversion are closely linked. Following Wakker’s argument, a number of papers have set out the relationship between dynamic consistency and information attitude, but authors restrict the class of non-EU preferences by imposing di¤erent consistent properties, non- EU preferences must satisfy. Our approach in this paper is di¤erent, instead of starting from agent’s preferences to infer agent’s attitude towards information, conversely we start from the attitude towards information to infer the agent’s preferences “logically” possible. We display in the simplest dynamic version of the Allais’ paradox, the di¤erent possible attitudes towards information and characterize them in the Choice Functions Theory’s framework. We show for instance that an agent who has non-EU preferences can be Information Averse as pointed out by Wakker (1988) but also Information Lover. Therefore, the simple observation of non-EU preferences cannot give us any piece of information about the agent’s attitude towards information.

Suggested Citation

  • Marc-Arthur Diaye & Jean-Max Koskievic, 2001. "Attitude towards Information and Non-Expected Utility Preferences : a Characterization by Choice Functions," Documents de recherche 01-16, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
  • Handle: RePEc:eve:wpaper:01-16
    as

    Download full text from publisher

    File URL: https://www.univ-evry.fr/fileadmin/mediatheque/ueve-institutionnel/03_Recherche/laboratoires/Epee/wp/01-16.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Manjira Datta & Leonard J. Mirman & Edward E. Schlee, 2002. "Optimal Experimentation in Signal Dependent Decision Problems," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(2), pages 577-608, May.
    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. Braz Camargo & Elena Pastorino, 2016. "Learning-by-Employing: The Value of Commitment under Uncertainty," Journal of Labor Economics, University of Chicago Press, vol. 34(3), pages 581-620.
    2. Edward E. Schlee, 2001. "The Value of Information in Efficient Risk-Sharing Arrangements," American Economic Review, American Economic Association, vol. 91(3), pages 509-524, June.
    3. Godfrey Keller, 2005. "The (in)appropriate benchmark when beliefs are not the only state variable," Economics Series Working Papers 223, University of Oxford, Department of Economics.
    4. Marc-Andreas Muendler, 2005. "Rational Information Choice in Financial Market Equilibrium," CESifo Working Paper Series 1436, CESifo.
    5. Lars J. Olson & Santanu Roy, 2006. "Theory of Stochastic Optimal Economic Growth," Springer Books, in: Rose-Anne Dana & Cuong Le Van & Tapan Mitra & Kazuo Nishimura (ed.), Handbook on Optimal Growth 1, chapter 11, pages 297-335, Springer.
    6. Bertocchi, Graziella & Spagat, Michael, 1998. "Growth under uncertainty with experimentation," Journal of Economic Dynamics and Control, Elsevier, vol. 23(2), pages 209-231, September.
    7. Leonard Mirman & Marc Santugini, 2014. "Learning and Technological Progress in Dynamic Games," Dynamic Games and Applications, Springer, vol. 4(1), pages 58-72, March.
    8. Koulovatianos, Christos & Mirman, Leonard J. & Santugini, Marc, 2009. "Optimal growth and uncertainty: Learning," Journal of Economic Theory, Elsevier, vol. 144(1), pages 280-295, January.
    9. Christos Koulovatianos & Leonard J. Mirman & Marc Santugini, 2006. "Investment in a Monopoly with Bayesian Learning," Vienna Economics Papers 0603, University of Vienna, Department of Economics.
    10. Leonard J. Mirman & Kevin Reffett & Marc Santugini, 2016. "On learning and growth," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 61(4), pages 641-684, April.
    11. Johnson, Timothy C., 2007. "Optimal learning and new technology bubbles," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2486-2511, November.
    12. Cunha-e-Sa, Maria A. & Santos, Vasco, 2008. "Experimentation with accumulation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 470-496, February.
    13. Hilde Patron, 2005. "Temporary Acceleration of Inflation: What Can a Central Bank Learn from It?," Southern Economic Journal, John Wiley & Sons, vol. 71(4), pages 737-751, April.
    14. Leonard J. Mirman & Marc Santugini, 2012. "Learning and Technology Progress in Dynamic Games," Cahiers de recherche 1217, CIRPEE.

    More about this item

    Keywords

    Information; Decision Theory;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

    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:eve:wpaper:01-16. 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: Samuel Nosel (email available below). General contact details of provider: https://edirc.repec.org/data/epevrfr.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.