A Multi-population Locally-Coherent Mortality Model

A Neural Network (NN) approach for the modelling of mortality rates in a multi-population framework is compared to three classical mortality models. The NN setup contains two instances of Recurrent NNs, including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) networks. The stochastic approaches comprise the Li and Lee model, the Common Age Effect model of Kleinow, and the model of Plat. All models are applied and compared in a large case study on decades of data of the Italian population as divided in counties. In this case study, a new index of multiple deprivation is introduced and used to classify all Italian counties based on socio-economic indicators, sourced from the local office of national statistics (ISTAT). The aforementioned models are then used to model and predict mortality rates of groups of different socio-economic characteristics, sex, and age.

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A Multi-population Locally-Coherent Mortality Model

Cited by 2 publications

References 12 publications

Locally-coherent multi-population mortality modelling via neural networks

Locally-coherent multi-population mortality modelling via neural networks

A neural network approach for the mortality analysis of multiple populations: a case study on data of the Italian population

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