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The Determinants of Decision Time

Author

Listed:
  • Anna Conte

    (Strategic Interaction Group, Max Planck Institute of Economics, Jena, and Department of Economics and Quantitative methods, WBS, University of Westminster)

  • John D. Hey

    (Department of Economics and Related Studies, University of York)

  • Ivan Soraperra

    (Dipartimento di Scienze Economiche, University of Verona,)

Abstract

This paper estimates the determinants of decision time for different types of decision maker in the context of an experimental investigation of multiple prior models of behaviour under ambiguity. Four models are considered: Expected Utility, Smooth, Rank Dependent Expected Utility and Alpha model. The results of a mixture model which assigns subjects to types enable us to distinguish the factors influencing the decision time of each of these four types. We find that the different types are influenced by different factors. In general, the Rank Dependent type takes more time, followed by the Smooth, the Expected Utility and finally the Alpha type, whose decision time is always the lowest. Our results reflect the relative complexity of the preference functionals used by the different types. Consequently, the importance of looking at the process of pairwise choices rather than simply at the choice made is raised to the attention of theorists and analysts.

Suggested Citation

  • Anna Conte & John D. Hey & Ivan Soraperra, 2014. "The Determinants of Decision Time," Jena Economics Research Papers 2014-004, Friedrich-Schiller-University Jena.
    • Handle: RePEc:jrp:jrpwrp:2014-004
    as

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    File URL: https://oweb.b67.uni-jena.de/Papers/jerp2014/wp_2014_004.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Peter Moffatt, 2005. "Stochastic Choice and the Allocation of Cognitive Effort," Experimental Economics, Springer;Economic Science Association, vol. 8(4), pages 369-388, December.
    3. 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..
    4. 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..
    5. 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.
    6. Johanna Etner & Meglena Jeleva & Jean-Marc Tallon, 2009. "Decision theory under uncertainty," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00429573, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Conte, Anna & Scarsini, Marco & Sürücü, Oktay, 2016. "The impact of time limitation: Insights from a queueing experiment," Judgment and Decision Making, Cambridge University Press, vol. 11(3), pages 260-274, May.
    2. Clithero, John A., 2018. "Response times in economics: Looking through the lens of sequential sampling models," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 61-86.
    3. repec:cup:judgdm:v:11:y:2016:i:3:p:260-274 is not listed on IDEAS

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    More about this item

    Keywords

    decision time; choice under uncertainty; censored regression;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • 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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