Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published August 2, 2017 | Submitted
Report Open

Objective Lotteries as Ambiguous Objects: Allais, Ellsberg, and Hedging

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

Files

sswp1356_-_revised.pdf
Files (1.1 MB)
Name Size Download all
md5:c43e8bef13a10076de0fda8f82d0c2b3
599.9 kB Preview Download
md5:d388e31897a32ba584ee3bbe9e07c37d
529.1 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
January 13, 2024