correlated random effects for hurdle models applied to claim counts

New models for panel data that consist of a generalization of the hurdle model are presented and are applied to modeling a panel of claim counts. Correlated random effects are assumed for the two processes involved to allow for dependence among all the contracts held by the same insured. A method to obtain a posteriori distribution of the random effects as well as predictive distributions of the number of claims is presented. A numerical illustration of reported insurance claims shows that if independence between random effects is assumed, then the variance of a priori premiums may be underestimated. If dependence between random effects is considered, then the predicted number of claims given past observations and covariate information and its variance is also larger than the one obtained when independence is assumed