Objective Lotteries as Ambiguous Objects: Allais, Ellsberg, and Hedging
- Creators
- Dean, Mark
- Ortoleva, Pietro
Abstract
We derive axiomatically a model in which the Decision Maker can exhibit simultaneously both the Allais and the Ellsberg paradoxes in the standard setup of Anscombe and Aumann (1963). Using the notion of 'subjective', or 'outcome' mixture of Ghirardato et al. (2003), we define a novel form of hedging for objective lotteries, and introduce a novel axiom which is a generalized form of preferences for hedging. We show that this axiom, together with other standard ones, is equivalent to a represen- tation in which the agent reacts to ambiguity using multiple priors like the MaxMin Expected Utility model of Gilboa and Schmeidler (1989), generating an Ellsberg-like behavior, while at the same time, she treats also objective lotteries as 'ambiguous objects,' and use a fixed (and unique) set of priors to evaluate them – generating an Allais-like behavior. We show that this representation is equivalent to one in which the agent evaluates lotteries using a set of concave rank-dependent utility functionals. A comparative notion of preference for hedging is also introduced.
Additional Information
First WP October 2011, revised June 2012. We would like to thank Simone Cerreia-Vioglio, David Dillengerger, Federico Echenique, Paolo Ghirardato, Anna Gumen, Edi Karni, Peter Klibanoff, Fabio Maccheroni, Massimo Marinacci, Stefania Minardi, Efe Ok, Leonardo Pejsachowicz, Philipp Sadowski, Todd Sarver, Andrei Savochkin, Kyoungwon Seo, Marciano Siniscalchi, and the participants of seminars at Bocconi University and Northwestern University for very useful comments and suggestions.Attached Files
Submitted - sswp1356_-_revised.pdf
Submitted - sswp1356.pdf
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Additional details
- Eprint ID
- 79488
- Resolver ID
- CaltechAUTHORS:20170727-103944043
- Created
-
2017-08-02Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 1356