A Comparison of Stochastic Claims Reserving Methods

In order to preserve their solvency, it is very important for insurance companies to accurately estimate their future required reserves. The aim of this article is to determine reserves by using different stochastic models: 1) distribution-free model (Mack's model), 2) probability distribution based models (Normal, Poisson, Gamma and Inverse Gaussian distributions), and 3) these latter probability based models combined with bootstrapping. To implement these models we used data on life-insurance and non-life insurance. Our findings indicate among distribution based methods, Mack's model (dataset 1 and 2) and Gamma probability distribution based model (dataset 3) are the best model in estimating reserves. The model based on Normal distribution produces the worst results, whatever the dataset. Regarding results of bootstrapping based on probability distribution models, they show that method based on Normal probability distribution (dataset 1 and 3) and ODP distribution (dataset 2) fit better. Our results also indicate that bootstrap method based on Chain-Ladder performs quit similarly than the best fitting probability distribution based bootstrap models. Among all retained models, methods based on bootstrapping present higher good-of-fit.

Implications of we-talk for relationships and health among patients with type 1 diabetes and their spouses

We-talk (first-person plural pronoun usage) is frequently used to represent the degree to which a person views an illness as shared within a couple. There is evidence that we-talk is related to good relationship and health. However, research has failed to examine the implications of we-talk for spouses and the interpersonal mechanisms that underlie relational and health benefits. To address these limitations, we investigated the association of we-talk to relationship and health among 199 couples in which one person had type 1 diabetes. We-talk was assessed in the context of a brief coping interview with patients and spouses separately. Patients reported their perceptions of their spouse’s behavior over the past month. Actor–partner interdependence, regression, and bootstrap models showed that patient we-talk was unrelated to patient and spouse well-being, but greater spouse we-talk was associated with higher patient relationship satisfaction, higher patient self-efficacy, and better patient self-care behavior. For spouses, greater spouse we-talk also was associated with higher relationship satisfaction, lower stress, and fewer depressive symptoms. Mediational analyses showed that patients’ perceptions of spouses’ greater emotional support and fewer critical behaviors partially accounted for these associations. Spouse we-talk may be more important than patient we-talk because it signifies that spouses are involved in helping with diabetes management, namely by providing emotional support and refraining from criticizing the patient.