Lee-Carter model: Assessing the potential to capture gender-related mortality dynamics

We investigate the ability of the Lee-Carter model to effectively estimate the Gender Gap Ratio (GGR), the ratio between the male death rates over the female ones, by using a Cox-Ingersoll-Ross process to provide a stochastic representation of the fitting errors. The novelty consists in the fact that we use the parameters characterizing the CIR process itself (long-term mean and volatility), in their intrinsic meanings, as quantitative measures of the long-term fitting attitude of the Lee-Carter model and syntethic indicators of the overall risk of this model. The analysis encompasses 25 European countries, to provide evidence-based indications about the goodness-of-fit of the Lee Carter model in describing the GGR evolution. We highlight some stylized facts, namely systematic evidence about the fitting bias and the risk of the model across ages and countries. Furthermore, we perform a Functional Cluster Analysis, allowing to capture similarities in the fitting performance of the Lee- Carter model among countries.