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Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet

Denise Desjardins (), Georges Dionne and Yang Lu ()
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Denise Desjardins: HEC Montreal, Canada Research Chair in Risk Management
Yang Lu: Concordia University, https://www.concordia.ca/artsci/math-stats/faculty.html?fpid=yang-lu

No 21-2, Working Papers from HEC Montreal, Canada Research Chair in Risk Management

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C23 C25 C55 G22 (search for similar items in EconPapers)
Pages: 61 pages
Date: 2021-02-18
New Economics Papers: this item is included in nep-ias, nep-ore and nep-tre
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