In insurance and related industries including healthcare, it is common to have several outcome measures that the analyst wishes to understand using explanatory variables. For example, in automobile insurance, an accident may result in payments for damage to one's own vehicle, damage to another...

This paper studies count processes in Insurance, in which we allow the underlying risk factor to be partially unobservable and potentially time-varying. We propose a Poisson model with a stochastic intensity, or dynamic frailty process. It is based on an autoregressive gamma process, which...

We introduce new semi-parametric models for the analysis of rates and proportions, such as proportions of default, (expected) loss-given-default and credit conversion factor encountered in credit risk analysis. These models are especially convenient for stress test exercises. We show that...

We propose a semi-parametric bivariate panel regression model that is suitable for mixed count/continuous variables. We develop a polynomial expansion approach for the distribution of the correlated bivariate random effect. Besides the distributional flexibility it offers, the model allows for...

In some survival analysis, characterizing tail properties is of vital importance because of the huge economic cost associated with the large duration samples. In this paper, I study asymptotic properties in bivariate survival models with bivariate heterogeneity (frailty).I derive the appropriate...