Hierarchical random‐effects model for the insurance pricing of vehicles belonging to a fleet
提出一种带分层随机效应的计数数据模型，用于车队车辆的后验保险费率厘定，允许车队、车辆和时间三个层面的随机效应，并推导出简洁的费率公式。
Summary We propose a count‐data model with hierarchical random effects for the posterior insurance ratemaking of vehicles belonging to a fleet, by allowing random effects for the fleet, the vehicles, and time. We derive a simple closed‐form ratemaking formula based on a hierarchical random‐effects specification. We estimate the corresponding econometric model and compute insurance premiums according to the past experience of both the vehicle and the fleet. Our model can be used in other count‐data applications with random individual and common effects on events involving many agents having activities with a principal in a hierarchical principal–agent environment, such as in education, health care management, finance, and business firms.