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Optimal Risk Sharing Without Preference Convexity: An Aggregate Convexity Approach

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  • Vasily Melnikov

Abstract

We consider the optimal risk sharing problem with a continuum of agents, modeled via a non-atomic measure space. Individual preferences are not assumed to be convex. We show the multiplicity of agents induces the value function to be convex, allowing for the application of convex duality techniques to risk sharing without preference convexity. A computationally tractable formula for the conjugate of the value function is derived, yielding an explicit dual representation of the value function. Applications of our results include a version of the two fundamental theorems of welfare economics for a large class of non-convex preferences, and non-existence results for Pareto optima when preferences are distortion risk measures whose corresponding distortion function fails to majorize the identity.

Suggested Citation

  • Vasily Melnikov, 2025. "Optimal Risk Sharing Without Preference Convexity: An Aggregate Convexity Approach," Papers 2509.08832, arXiv.org, revised Aug 2026.
    • Handle: RePEc:arx:papers:2509.08832
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    References listed on IDEAS

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    1. Marcelo Brutti Righi & Marlon Ruoso Moresco, 2024. "Inf-convolution and optimal risk sharing with countable sets of risk measures," Annals of Operations Research, Springer, vol. 336(1), pages 829-860, May.
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