Multi-population and factor-based mortality analytics
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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.