Multi-population and factor-based mortality analytics
Abstract
In this thesis, I develop a model that uses socio-economic characteristics to explain
differences in the mortality of different populations. This thesis has two main objectives. Firstly we look at mortality data of population from three countries/regions
and test a wide range of stochastic multi-population mortality models with different
sub-population datasets grouped using criteria relevant to socio-economic factors. The
most appropriate model is selected and we can learn the mortality difference over the
sub-populations that is explained by socio-economic differences. Secondly, we take
advantage of a England demographic dataset of large volume and high granularity –
a large number of small geographical areas (i.e. small neighbourhoods) along with
mortality experiences and most relevant socio-economic factors in each of them. With
this granular dataset we implement non-parametric and machine learning models. We
eventually produce a mortality index for the small neighbourhoods in England using
the estimated mortality rates.