Longevity risk—the risk of running out of money before we run out of time—is fundamental to retirement. We can be very precise about the distribution of longevity for the overall population, but there’s no way to know when our longevity will run out (and I’m not even sure I’d actually want to know).
The length of your retirement could be much shorter or longer than your statistical life expectancy. Half of the population will outlive their median life expectancy— and some will live far beyond it.
A long life is wonderful, but it is expensive.
As a first step to measuring longevity risk, it is important to understand what the data says about mortality and survivorship rates. Different data sources provide different longevity estimates for several key reasons:
(1) From what age is life expectancy being measured?
Life expectancy at birth is the number we are all most familiar with, though it is of little relevance for someone reaching retirement. If you have reached age sixty-five, then you did not die prior to age sixty-five. As obvious as it might be, this is important information because it changes exactly what we are trying to measure.
Your life expectancy upon reaching age sixty-five is not the same as your life expectancy at birth. As you age, your remaining life expectancy age actually increases.
The remaining number of years you can expect to live decreases as you get older, but not on a one-to-one basis with age. This commonly leads individuals to underestimate how long they may live in retirement, and we must keep in mind from which age life expectancy is being measured.
(2) Is life expectancy calculated from current year mortality rates or projected future mortality rates?
Probably the most commonly used source of mortality data is the Social Security Administration’s (SSA) Period Life Tables. A period life table makes calculations about remaining lifetimes using the mortality data from one year. For instance, calculations for the life expectancy of a sixty-five-year old would use the year’s mortality rates for different ages in that one year. How many seventy-year olds died that year? eighty-year olds? and so on.
This method has the advantage of using actual data without requiring any sort of projections, but it is bound to underestimate life expectancies on account of the persistent trends of increasing life expectancies over time. The alternative is to use a cohort life table, which tracks mortality for the same individual over time.
When a sixty-five-year-old in 2016 turns eighty-five in 2036, they will most likely be more likely to be alive than an eighty-five-year old in 2016. A cohort life table uses projections for future mortality improvements when calculating life expectancies. Cohort life tables will project longer lives and are surely a better choice for considering longevity when building a retirement income plan.
And we can see this in action.
In 1994, William Bengen chose thirty years as a conservative planning horizon for a sixty-five-year old couple. However, based on the CDC’s Life Expectancy Estimates for 2022 , that’s not a particularly conservative assumption any more.
There is a nearly one in five chance that at least one member of an opposite gender couple will still be alive when they are 95 if they are both 65 currently.
And mortality will continue to improve over time. Meaning that this planning horizon is becoming even less conservative.
(3) What is the underlying population for which mortality and survivorship is being calculated?
It may seem natural to base calculations on the aggregate U.S. population—as is done with the Social Security Administration life tables—but clear socioeconomic differences have been identified in mortality rates. Higher income levels and more education both correlate with longer lifespans.
Determining causation is difficult, as there are many factors that play into why different groups have different mortality rates, but the fact that you are reading this somewhat technical tome on retirement income suggests you probably have a longer-term focus and can expect to live longer than the average person. In this case, mortality data based on population-wide averages may underestimate your longevity.
This is not because I think our readers are all from Lake Wobegon (where everyone is above average), rather it is because of the important links between income, education, long-term planning, and health. Not everyone will live longer, as unfortunate accidents and illnesses will inevitably befall some along the way. But in a statistical sense, my average reader will live longer than the average person.
Like a lot of the most important numbers in retirement planning, life expectancy is inherently unknowable. We can estimate the life expectancy across the population – and they’ve gotten reasonably good at that – but we care about our own personal longevity from a planning perspective.
You can use the questions here, along with what you know about your family’s history, to start to estimate what your personal life expectancy might be.
We all want a long life, but to make the most of it we need to plan for it.
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