Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?

G\'abor Petneh\'azi; J\'ozsef G\'all

Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?

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arxiv 1909.05501 v2 pith:7UPHP6YK submitted 2019-09-12 q-fin.RM stat.APstat.ML

Gábor Petneházi , József Gáll This is my paper · ORCID

classification q-fin.RMstat.APstat.ML

keywords modelmortalityrateforecastinglee-carterneuralrecurrentages

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This article applies a long short-term memory recurrent neural network to mortality rate forecasting. The model can be trained jointly on the mortality rate history of different countries, ages, and sexes. The RNN-based method seems to outperform the popular Lee-Carter model.

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Zero-Shot Forecasting Mortality Rates: A Global Study
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Zero-shot CHRONOS forecasts are competitive for 5 and 10 year mortality horizons, TimesFM underperforms, and a mortality-trained random forest achieves the lowest SMAPE overall.

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