Abstract This study examines the application of three parametric mortality models—Gompertz, Makeham, and Weibull—to analyze mortality patterns and calculate annuity due values for male and female populations in Nigeria, Ghana, and Benin. Using World Health Organization Global Health Observatory data from 2000 to 2019, mortality parameters were estimated through optimization methods, with fitted parameters applied to comprehensive annuity due calculations using Nigerian data as a representative case study. Results revealed that the Gompertz model consistently provides the most robust fits across all three countries, establishing it as the preferred framework for West African mortality modeling. The Makeham model systematically overestimated mortality at younger ages, while the Weibull model demonstrated adequate performance with meaningful parameter evolution. Remarkable mortality convergence occurred across the three countries between 2000-2019, with substantial cross-country differences narrowing considerably. Gender differentials remain pronounced, with females consistently exhibiting lower baseline mortality across all populations. The Nigerian annuity analysis revealed substantial sensitivity to both model selection and interest rate assumptions, with gender differentials ranging from 8-18% depending on model choice and product duration. The model hierarchy—Weibull producing highest values, followed by Gompertz, then Makeham—provides practitioners with bounded estimates for sensitivity analysis. Interest rate sensitivity analysis demonstrates 40-60% variation in annuity values across typical West African economic conditions. This work contributes significantly to actuarial science by providing the first comprehensive mortality modeling framework for West African populations and establishing evidence-based foundations for insurance and pension product development in sub-Saharan Africa.
Oyelade et al. (Fri,) studied this question.