Deliberately Stochastic

38 Pages Posted: 30 May 2017

See all articles by Simone Cerreia-Vioglio

Simone Cerreia-Vioglio

Bocconi University - Department of Decision Sciences

David Dillenberger

University of Pennsylvania - Department of Economics

Pietro Ortoleva

Princeton University - Department of Economics

Gil Riella

Getulio Vargas Foundation (FGV)

Date Written: May 25, 2017

Abstract

We study stochastic choice as the outcome of deliberate randomization. After first deriving a general representation of a stochastic choice function with such property, we proceed to characterize a model in which the agent has preferences over lotteries that belong to the Cautious Expected Utility class (Cerreia Vioglio et al., 2015), and the stochastic choice is the optimal mix among available options. This model links stochasticity of choice and the phenomenon of Certainty Bias, with both behaviors stemming from the same source: multiple utilities and caution. We show that this model is behaviorally distinct from models of Random Utility, as it typically violates the property of Regularity, shared by all of them.

Keywords: Stochastic Choice, Random Utility, Hedging, Cautious Expected Utility, Convex Preferences, Regularity

JEL Classification: D80, D81

Suggested Citation

Cerreia-Vioglio, Simone and Dillenberger, David and Ortoleva, Pietro and Riella, Gil, Deliberately Stochastic (May 25, 2017). PIER Working Paper No. 17-013; Columbia Business School Research Paper No. 17-58. Available at SSRN: https://ssrn.com/abstract=2977320 or http://dx.doi.org/10.2139/ssrn.2977320

Simone Cerreia-Vioglio

Bocconi University - Department of Decision Sciences ( email )

Via Roentgen 1
Milan, 20136
Italy

David Dillenberger (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
133 South 36th Street
Philadelphia, PA 19104-6297
United States
215-898-1503 (Phone)

Pietro Ortoleva

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

Gil Riella

Getulio Vargas Foundation (FGV) ( email )

R. Dr. Neto de Araujo 320 cj 1307
Rio de Janeiro, Rio de Janeiro 22250-900
Brazil

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