On a retarded stochastic system with discrete diffusion modeling life tables

TL;DR

This paper introduces a stochastic model for mortality rates that captures both historical trends and randomness, providing improved forecasting accuracy over traditional methods, with applications to Spanish mortality data.

Contribution

It presents a novel stochastic modeling approach that combines discrete diffusion processes with life tables, enhancing mortality rate forecasting accuracy.

Findings

Model successfully captures mortality dynamics

Outperforms classical forecasting methods

Provides mathematical analysis of model properties

Abstract

This work proposes a method for modeling and forecasting mortality rates. It constitutes an improvement over previous studies by incorporating both the historical evolution of the mortality phenomenon and its random behavior. In the first part, we introduce the model and analyze mathematical properties such as the existence of solutions and their asymptotic behavior. In the second part, we apply this model to forecast mortality rates in Spain, showing that it yields better results than classical methods.