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Can price collars increase insurance loss coverage?

Chatterjee, Indradeb, Hao, MingJie, Tapadar, Pradip, Thomas, R. Guy (2024) Can price collars increase insurance loss coverage? Insurance: Mathematics and Economics, 116 (2024). pp. 74-94. ISSN 0167-6687. (doi:10.1016/j.insmatheco.2024.02.003) (KAR id:100161)


Loss coverage, defined as expected population losses compensated by insurance, is a public policy criterion for comparing different risk classification regimes. Using a model with two risk-groups (high and low) and iso-elastic demand, we compare loss coverage under three alternative regulatory regimes: (i) full risk-classification (ii) pooling (iii) a price collar, whereby each insurer is permitted to set any premiums, subject to a maximum ratio of its highest and lowest prices for different risks. Outcomes depend on the comparative demand elasticities of low and high risks. If low-risk elasticity is sufficiently low compared with high-risk elasticity, pooling is optimal; and if it is sufficiently high, full risk classification is optimal. For an intermediate region where the elasticities are not too far apart, a price collar is optimal, but only if both elasticities are greater than one. We give extensions of these results for more than two risk-groups. We also outline how they can be applied to other demand functions using the construct of arc elasticity.

Item Type: Article
DOI/Identification number: 10.1016/j.insmatheco.2024.02.003
Uncontrolled keywords: Insurance loss coverage, risk classification, price collar, demand elasticity, marginal revenue-to-cost ratio, arc elasticity, partial community rating.
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Pradip Tapadar
Date Deposited: 21 Feb 2023 16:40 UTC
Last Modified: 23 Feb 2024 09:24 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Chatterjee, Indradeb.

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Hao, MingJie.

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Tapadar, Pradip.

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Thomas, R. Guy.

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