Actuaries rely on population mortality rates to determine compensation in cases of damages,
trends in mortality rates inform the modelling of mortality risk and valuation of insurance
companies and pension schemes and, not least, actuarial calculations of population mortality
contribute to wider societal debates. Estimating the level and trend in population mortality rates
at advanced ages in South Africa is complicated by potential problems. Population and death
data, particularly in developing countries, often suffer from age misreporting – age exaggeration
and digit preference. In addition, censuses may under- or overestimate the population and
registration of deaths is usually incomplete in developing countries
In this research, we use the Death Distribution Methods (Moultrie et al., 2013) to correct
the death data for incomplete registration of deaths, and the Near Extinct Generation (NEG)
methods (Thatcher et al., 2002) to estimate the population by projecting future deaths of nearly
extinct cohorts. In applying NEG methods to the South African data, we exploit the theoretical
connection to actuarial methods for the calculation of claims incurred but not yet reported,
and propose an adapted NEG method based on the chain-ladder model of Renshaw and Verrall
(1998) to smooth the digit preference in the death data. We use this model to re-estimate the
population at each age from 70 and above and to calculate mortality rates since 1996. We find
that both the population and death data suffer from the same pattern of digit preference and that
the population data are affected by age exaggeration, leading to underestimated mortality rates
if the census counts are used as exposures. The level and trend in mortality rates are discussed
and compared to the mortality rates in the Human Mortality Database, other studies of South
African mortality and insured life tables