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Behavioral Patterns and Reduction of Sub-Optimality: An Experimental Choice Analysis

Author

Listed:
  • Daniela Di Cagno

    (LUISS, Rome)

  • Arianna Galliera

    (LUISS, Rome and Politecnico di Milano)

  • Werner Güth

    (LUISS, Rome and Max Planck Institute, Bonn)

  • Noemi Pace

    (Department of Economics, University Of Venice CÃ Foscari)

Abstract

This paper attempts to identify behavioral patterns and compare their average success considering several criteria of bounded rationality. Experimentally observed choice behavior in various decision tasks is used to assess heterogeneity in how individual participants respond to 15 randomly ordered portfolio choices, each of which is experienced twice. Treatments differ in (not) granting probability information and in (not) eliciting aspirations. Since in our setting neither other regarding concerns nor risk attitude matter and probability of the binary chance move is (optimal) choice-irrelevant, categorizing decision types relies on parameter dependence and choice adaptations. We find that most participants reduce systematically sub-optimality when following the identified criteria.

Suggested Citation

  • Daniela Di Cagno & Arianna Galliera & Werner Güth & Noemi Pace, 2017. "Behavioral Patterns and Reduction of Sub-Optimality: An Experimental Choice Analysis," Working Papers 2017:23, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2017:23
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    References listed on IDEAS

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    1. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    2. Reinhard Selten & Abdolkarim Sadrieh & Klaus Abbink, 1999. "Money Does Not Induce Risk Neutral Behavior, but Binary Lotteries Do even Worse," Theory and Decision, Springer, vol. 46(3), pages 213-252, June.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. John Conlisk, 1996. "Why Bounded Rationality?," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 669-700, June.
    5. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    6. John D. Hey & Yudistira Permana & Nuttaporn Rochanahastin, 2018. "When and how to satisfice: an experimental investigation," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 5, pages 121-137, World Scientific Publishing Co. Pte. Ltd..
    7. Daniela Di Cagno & Arianna Galliera & Werner Güth & Francesca Marzo & Noemi Pace, 2017. "(Sub) Optimality and (non) optimal satisficing in risky decision experiments," Theory and Decision, Springer, vol. 83(2), pages 195-243, August.
    8. Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
    9. Anna Conte & Daniela T. Di Cagno & Emanuela Sciubba, 2015. "Behavioral Patterns In Social Networks," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 1331-1349, April.
    10. Charles F. Manski, 2017. "Optimize, satisfice, or choose without deliberation? A simple minimax-regret assessment," Theory and Decision, Springer, vol. 83(2), pages 155-173, August.
    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.
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    Cited by:

    1. Daniela Di Cagno & Werner Güth & Noemi Pace, 2021. "Experimental evidence of behavioral improvement by learning and intermediate advice," Theory and Decision, Springer, vol. 91(2), pages 173-187, September.

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    More about this item

    Keywords

    (Un)Bounded Rationality; Satisficing; Experiments; Heterogeneity;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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