Skip to main content
Kent Academic Repository

Can price collars increase insurance loss coverage?

Tapadar, Pradip (2023) Can price collars increase insurance loss coverage? In: 26th International Congress on Insurance: Mathematics and Economics, 4-7 July 2023, Heriot-Watt University. (Unpublished) (KAR id:102030)

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.

Item Type: Conference or workshop item (Lecture)
Uncontrolled keywords: Insurance loss coverage; risk classification; price collar; partial community rating; pooling.
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Funders: University of Kent (https://ror.org/00xkeyj56)
Depositing User: Pradip Tapadar
Date Deposited: 10 Jul 2023 19:59 UTC
Last Modified: 05 Nov 2024 13:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/102030 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.