Modelling residuals dependence in dynamic life tables: A geostatistical approach

The problem of modelling dynamic mortality tables is considered. In this context, the influence of age on data graduation needs to be properly assessed through a dynamic model, as mortality progresses over the years. After detrending the raw data, the residuals dependence structure is analysed, by considering them as a realisation of a homogeneous Gaussian random field defined on R × R. This setting allows for the implementation of geostatistical techniques for the estimation of the dependence and further interpolation in the domain of interest. In particular, a complex form of interaction between age and time is considered, by taking into account a zonally anisotropic component embedded into a nonseparable covariance structure. The estimated structure is then used for prediction of mortality rates, and goodness-of-fit testing is performed through some cross-validation techniques. Comments on validity and interpretation of the results are given.