Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet
61 Pages Posted: 23 Feb 2021
Date Written: February 18, 2021
We propose a hierarchical random effect model for the posterior insurance ratemaking of vehicles belonging to a ﬂeet by allowing random effects for ﬂeet, vehicle, and time. The model is an alternative to the gamma-Dirichlet model of Angers et al (2018), which does not allow for a closed form posterior ratemaking formula. Our theoretical extension derives a simple and tractable closed form ratemaking formula based on a hierarchical random effects speciﬁcation. We estimate the corresponding econometric model and compute insurance premiums in relation to the past experience of both the vehicle and the fleet. Our econometric model can also be applied to any other dynamic count modeling application with random individual, time, and common effects, such as labor contracting, chirurgical accidents, or any other random event implying principals and many agents.
Keywords: Hierarchical model, vehicle insurance pricing, posterior ratemaking, random effect, hierarchical random effects, panel data.
JEL Classification: C23, C25, C55, G22.
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