Forecasting cohort mortality trajectories under the overlapping cohorts perspective

What are the leading causes of death afflicting our societies, and how do they contribute to mortality inequality? Life tables and their related measures are possibly the most widely applied demographic tools and are frequently used to answer this and other fundamental questions. Furthermore, alternative methods based on the mixture of individual cohorts’ mortality regimes of a population in a particular period (i.e., overlapping cohort perspective) could provide different narratives when evaluating mortality (Pifarré i Arolas et al., 2023). There are several applications for using this alternative approach. For instance, valuations on lifespan inequalities, life expectancy, years of life lost, among others, could provide different stories when life tables with complete cohorts’ mortality trajectories are accounted for, compared with traditional life tables. This is particularly important in countries with mortality shocks since these shocks could affect every cohort in the population differently. Therefore, it is important to consider the differences across cohorts rather than assuming that all of them experience the same mortality pattern (i.e., synthetic cohort life table). While this novel approach could offer a more realistic analysis in assessing mortality dynamics, its limitation lies in the requirement for rich data availability. For example, when analyzing lifespan variation in 2020 using the overlapping cohorts perspective, complete mortality cohort information from individuals born between 1920 and 2020 is necessary. Therefore, it is essential to consider observed mortality trajectories far in the past as well as estimates of future mortality patterns. Currently, such comprehensive data is available for countries like Sweden, France, Norway, Italy, and a few others. However, what about countries lacking sufficient mortality data? Furthermore, current estimates of mortality trajectories are based on period mortality rates. Nevertheless, recent literature suggests cohort mortality forecasting in high-income countries could provide better estimates at cohort-level. In this context, I aim to evaluate different forecasting approaches under the overlapping cohorts perspective, particularly in Latin American countries that lack sufficient data and have experienced mortality shocks. My contribution in this research aims to identify the best method for cohort mortality forecasting, thereby creating the necessary framework to analyze the impact of mortality shocks in terms of years of life lived, lost, and lifespan inequalities using the overlapping cohorts approach. I use forecasting methods based on mortality rates (Basellini et al., 2020), improvements of mortality rates (Bohk-Ewald & Rau, 2017), as well as traditional forecasting methods (Lee & Carter, 1992) for comparison purposes. Assessing these forecasting methods under the overlapping cohorts perspective will offer more realistic insights into the evaluation of years of life lived, lost, and lifespan inequalities in Latin American countries that have experienced mortality shocks, such as waves of violence.