Can price collars increase insurance loss coverage?

Indradeb Chatterjee, MingJie Hao, Pradip Tapadar and R. Guy Thomas

Insurance: Mathematics and Economics, 2024, vol. 116, issue C, 74-94

Abstract: 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.

Keywords: Insurance loss coverage; Risk classification; Price collar; Demand elasticity; Marginal revenue-to-cost ratio; Arc elasticity; Partial community rating (search for similar items in EconPapers)
JEL-codes: D82 G22 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:116:y:2024:i:c:p:74-94

DOI: 10.1016/j.insmatheco.2024.02.003

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