From academic papers to mainstream media, reports on changes in life expectancy abound.1 While the U.S. population has experienced overall positive mortality improvements over time, disparities remain evident among different sub-groups.
The lifespans of defined benefit (DB) pensioners in particular may deviate from those of the general population, with distinct characteristics influencing their mortality. Digging even deeper, different pensioner groups may have their own specific mortality-influencing characteristics.
When considering baseline mortality assumptions of DB pensioners, insurers often distinguish between the general population and various socioeconomic groups or industry segments. This differentiation is less common for mortality improvement assumptions. However, evidence suggests that distinguishing between various groups should, at least to some extent, be applied to these assumptions as well. This tailored approach allows for more accurate modeling of the mortality improvements and liabilities of DB pension plans.
Often derived from overall U.S. population data, general mortality improvement assumptions may not capture the nuanced characteristics of DB pensioners.
RGA research indicates that adjusting population mortality improvements when projecting pension liabilities can help ensure a more accurate model and reduce the risk of understating pension liabilities.
This paper explores the Society of Actuaries (SOA) research on life expectancy across socioeconomic groups2and examines the potential implications for the pension industry.
Why Distinct Mortality Dynamics Matter
The pension and insurance industry has traditionally relied on U.S. general population-level mortality improvements. For example, a commonly used scale for projecting future mortality rates is the Society of Actuaries’ (SOA) Mortality Improvement Scale MP-2021, which is calibrated to the U.S. population.
However, U.S. population data may not fully represent DB pensioners. Consider this: Of the U.S. population age 60 and older, working less than 30 hours a week, less than half received an income source from a DB pension in 2013.3
DB pensioners, characterized by distinct employment histories and healthcare access, may have different mortality improvement dynamics than the average U.S. person, challenging the validity of a one-size-fits-all approach. For instance, DB pensioners were healthy enough to earn a DB pension through years of sustained, regular employment and likely enjoyed employer-provided healthcare.
The individual characteristics of different pension groups can also influence life expectancy. In private-sector retirement plans, for example, participants in white collar jobs tend to have lower rates of mortality than those in blue collar positions.4
It is therefore reasonable to assume that it is not always appropriate to use general population mortality improvements to project pension liabilities.