State space models in actuarial science by Piet

The article discusses the usefulness of the state space model for analyzing insurance data. State space models can be viewed as as a framework to describe “smoothness” and purge data of “noise.” It is the smooth features in data which are critical for inference and extrapolation. We describe simple state models and apply them to two insurance data sets: one dealing with mortality, the other with insurance claims. The state space framework avoids the need to “reinvent the wheel” when dealing with the modelling, estimation, checking and projecting of smooth data features.