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Optimal insurance with belief heterogeneity and incentive compatibility

Yichun Chi () and Sheng Chao Zhuang

Insurance: Mathematics and Economics, 2020, vol. 92, issue C, 104-114

Abstract: People may evaluate risk differently in the insurance market. Motivated by this, we examine an optimal insurance problem allowing the insured and the insurer to have heterogeneous beliefs about loss distribution. To reduce ex post moral hazard, we follow Huberman et al. (1983) to assume that alternative insurance contracts satisfy the principle of indemnity and the incentive-compatible constraint. Under the assumption that the insurance premium is calculated by the expected value principle, we establish a necessary and sufficient condition for an optimal insurance solution and provide a practical scheme to improve any suboptimal insurance strategy under an arbitrary form of belief heterogeneity. By virtue of this condition, we explore qualitative properties of optimal solutions, and derive optimal insurance contracts explicitly for some interesting forms of belief heterogeneity. As a byproduct of this investigation, we find that Theorem 3.6 of Young (1999) is not completely true.

Keywords: Belief heterogeneity; Incentive compatibility; Monotone likelihood ratio order; Optimal insurance design; Partial insurance over a layer (search for similar items in EconPapers)
JEL-codes: C02 G22 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:92:y:2020:i:c:p:104-114

DOI: 10.1016/j.insmatheco.2020.03.006

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Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

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