Optimal Insurance under Maxmin Expected Utility

46 Pages Posted: 28 Nov 2020 Last revised: 22 Jun 2022

See all articles by Corina Birghila

Corina Birghila

University of Waterloo

Tim J. Boonen

University of Amsterdam

Mario Ghossoub

University of Waterloo

Date Written: September 10, 2021


We examine a problem of demand for insurance indemnification, when the insured is sensitive to ambiguity and behaves according to the Maxmin-Expected Utility model of Gilboa and Schmeidler (1989), whereas the insurer is a (risk-averse or risk-neutral) Expected-Utility maximizer. We characterize optimal indemnity functions both with and without the customary ex ante no-sabotage requirement on feasible indemnities, and for both concave and linear utility functions for the two agents. This allows us to provide a unifying framework in which we examine the effects of the no-sabotage condition, marginal utility of wealth, belief heterogeneity, as well as ambiguity (multiplicity of priors) on the structure of optimal indemnity functions. In particular, we show how the singularity in beliefs leads to an optimal indemnity function that involves full insurance on an event to which the insurer assigns zero probability, while the decision maker assigns a positive probability. We examine several illustrative examples, and we provide numerical studies for the case of a Wasserstein and a Renyi ambiguity set.

Keywords: Optimal Insurance, Ambiguity, Multiple Priors, Maxmin-Expected Utility, Heterogeneous Beliefs

JEL Classification: C02, C61, D86, G22

Suggested Citation

Birghila, Corina and Boonen, Tim J. and Ghossoub, Mario, Optimal Insurance under Maxmin Expected Utility (September 10, 2021). Available at SSRN: https://ssrn.com/abstract=3711743 or http://dx.doi.org/10.2139/ssrn.3711743

Corina Birghila

University of Waterloo ( email )

Tim J. Boonen

University of Amsterdam ( email )

Roetersstraat 11
Amsterdam, 1018 WB

HOME PAGE: http://www.uva.nl/profiel/b/o/t.j.boonen/t.j.boonen.html

Mario Ghossoub (Contact Author)

University of Waterloo ( email )

Dept. of Statistics & Actuarial Science
200 University Ave. W.
Waterloo, Ontario N2L 3G1

HOME PAGE: http://uwaterloo.ca/scholar/mghossou

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