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Deliberately Stochastic

Author

Listed:
  • Simone Cerreia-Vioglio
  • David Dillenberger
  • Pietro Ortoleva
  • Gil Riella

Abstract

We study stochastic choice as the outcome of deliberate randomization. We derive a general representation of a stochastic choice function where stochasticity allows the agent to achieve from any set the maximal element according to her underlying preferences over lotteries. We show that in this model stochasticity in choice captures complementarity between elements in the set, and thus necessarily implies violations of Regularity/Monotonicity, one of the most common properties of stochastic choice. This feature separates our approach from other models, e.g., Random Utility.

Suggested Citation

  • Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2019. "Deliberately Stochastic," American Economic Review, American Economic Association, vol. 109(7), pages 2425-2445, July.
  • Handle: RePEc:aea:aecrev:v:109:y:2019:i:7:p:2425-45
    Note: DOI: 10.1257/aer.20180688
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    Other versions of this item:

    • Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2012. "Deliberately Stochastic," PIER Working Paper Archive 17-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 May 2017.

    References listed on IDEAS

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    2. Duffy, Sean & Smith, John, 2020. "An economist and a psychologist form a line: What can imperfect perception of length tell us about stochastic choice?," MPRA Paper 99417, University Library of Munich, Germany.
    3. Nur Ayvaz‐Çavdaroğlu & Mürüvvet Büyükboyacı, 2022. "Analyzing multiple pricing decisions for substitutes under stochastic demand: An experiment," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1351-1361, July.
    4. Baillon, Aurélien & Bleichrodt, Han & Li, Chen & Wakker, Peter P., 2021. "Belief hedges: Measuring ambiguity for all events and all models," Journal of Economic Theory, Elsevier, vol. 198(C).
    5. Dean, Mark & Ortoleva, Pietro, 2017. "Allais, Ellsberg, and preferences for hedging," Theoretical Economics, Econometric Society, vol. 12(1), January.
    6. Wolitzky, Alexander, 2016. "Mechanism design with maxmin agents: theory and an application to bilateral trade," Theoretical Economics, Econometric Society, vol. 11(3), September.
    7. Narayanaswamy Balakrishnan & Efe A. Ok & Pietro Ortoleva, 2021. "Inferential Choice Theory," Working Papers 2021-60, Princeton University. Economics Department..
    8. Guo, Liang, 2021. "Contextual deliberation and the choice-valuation preference reversal," Journal of Economic Theory, Elsevier, vol. 195(C).
    9. Duffy, Sean & Gussman, Steven & Smith, John, 2021. "Visual judgments of length in the economics laboratory: Are there brains in stochastic choice?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    10. Despoina Alempaki & Andrew M. Colman & Felix Kölle & Graham Loomes & Briony D. Pulford, 2022. "Investigating the failure to best respond in experimental games," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 656-679, April.
    11. Wakker, Peter P. & Yang, Jingni, 2021. "Concave/convex weighting and utility functions for risk: A new light on classical theorems," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 429-435.
    12. John K. -H. Quah & Gerelt Tserenjigmid, 2022. "Price Heterogeneity as a source of Heterogenous Demand," Papers 2201.03784, arXiv.org, revised Jan 2022.
    13. Cettolin, Elena & Riedl, Arno, 2019. "Revealed preferences under uncertainty: Incomplete preferences and preferences for randomization," Journal of Economic Theory, Elsevier, vol. 181(C), pages 547-585.
    14. Yosuke Hashidate, 2018. "Preferences for Randomization and Anticipated Utility," CIRJE F-Series CIRJE-F-1083, CIRJE, Faculty of Economics, University of Tokyo.
    15. Arts, Sara & Ong, Qiyan & Qiu, Jianying, 2020. "Measuring subjective decision confidence," MPRA Paper 106811, University Library of Munich, Germany.
    16. Allen, Roy & Dziewulski, Paweł & Rehbeck, John, 2022. "Making sense of monkey business: Re-examining tests of animal rationality," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 220-228.
    17. Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure," Management Science, INFORMS, vol. 66(11), pages 5075-5093, November.
    18. Heydari, Pedram, 2021. "Luce arbitrates: Stochastic resolution of inner conflicts," Games and Economic Behavior, Elsevier, vol. 126(C), pages 33-74.

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    More about this item

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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