Recently, there has been a great deal of press coverage of the latest federal government report on longevity in the U.S. that showed a decline in life expectancy. Changes in life expectancy matter to employers that sponsor pension plans because uncertainty about longevity must be taken into account as part of the financial stewardship of those plans.
Mortality assumptions are a key driver of the value of a plan’s liability. As such, those assumptions have implications for the plan’s cash-flow requirements, investment portfolio, de-risking strategy and even design features, such as whether to offer a lump-sum window to terminated-vested participants. Given that it is impossible to forecast mortality changes with certainty, employers that are concerned changes could have a significant negative or even catastrophic impact on their plans’ finances, and thus their business forecasts, might consider modeling alternative future scenarios. Stochastic modeling, in particular, is valuable because it illustrates the probability of various outcomes.1
The modeling exercise can help avoid selecting mortality assumptions that are too conservative or too aggressive. It can also reveal potential vulnerabilities that could be addressed through de-risking techniques, such as plan design changes or liability buy-outs. For example, in light of the uncertainty about life expectancy, employers that have a de-risking strategy that includes transferring risk to an insurer may want to consider spreading the risk transfer over time so one liability purchase price does not apply to the entire transaction.
This issue of Ideas draws attention to the latest age-related longevity data and the implications for pension plans. It also addresses how mortality projections for pension plans are determined.
Would either scenario change:
These, and other, considerations are inevitably connected to the “fair” value of the liability and decisions plan sponsors make. One of the key drivers of that value is an accurate mortality assumption.
The latest report on longevity in the U.S. from the National Center for Health Statistics (NCHS) noted that 2016 was the second consecutive year of overall decline in life expectancy at birth.2 That finding was newsworthy because it represents a reversal of a multi-decade pattern of improved life expectancy.3
The headline-grabbing finding can be misleading for pension plan sponsors. Here’s why: Despite the decline in life expectancy at birth, life expectancy is still improving for those who have reached (or will reach) retirement age.
Between 2015 and 2016, death rates increased significantly for the under-45 age groups studied. In contrast, death rates decreased for the post-65 retirement-age groups. These findings are illustrated in the graph below.
Source: Kenneth D. Kochanek, M.A., Sherry L. Murphy, B.S., Jiaquan Xu, M.D. and Elizabeth Arias, Ph.D. “Mortality in the United States, 2016.” NCHS Data Brief No. 293 (December 2017)
A subsequent analysis by the Society of Actuaries (SOA) released on January 11, 2018 confirmed that, while the expected life expectancy for a newborn decreased based on the NCHS study, the overall age-adjusted mortality rate in the U.S. improved (by less than 1 percent).4
For professionals who study population statistics, like actuaries and demographers, there are subtle but significant differences between life expectancy, longevity, life span and mortality. Life expectancy is the result of a calculation that estimates the average number of years until death at a specific age. Longevity and life span are less specific. They refer to an estimate of how long an individual might live. The mortality rate is a ratio of the actual number of deaths to the size of the total population for a specific age or age group. Despite these differences, the media tends to use the terms interchangeably to refer to the estimated number of years until death.
Shorter life expectancy (higher mortality) translates into reduced costs for pension plans. Knowing that, it can be tempting to conclude that the latest NCHS data being widely reported is good news for pension plan costs and may suggest that a change in mortality improvement assumptions would be timely.
In fact, the recent mortality rates observed for the retired population continue to support expected improvements in life expectancy for this group. Therefore, pension actuaries should not reverse their expectations for mortality improvement in response to the latest data,but make ongoing adjustments. As additional experience emerges, there may be refinements necessary in the actuaries’ assumptions for pension plans, but they should be based on longer-term trends.
Funding for single-employer pension plans is based on mortality tables and projection scales mandated by law. Those tables were recently updated.*
For determining pension expense for accounting, the mortality tables should reflect the organization’s best estimate. The determination of mortality projection scales requires large amounts of data to produce credible results. Even large employers that use their own plan data to determine tables for a baseline level of mortality are not large enough to use their own experience to develop projection scales. That’s why projection scales from either the Social Security Administration or the SOA are typically used — either directly or with some modification. Those standard tables are updated annually. Some organizations update their projection scales annually. Others update them periodically.
* See Sibson Consulting’s October 10, 2017 hot topic, “Treasury’s Final Pension Mortality Regulations Are Effective for 2018 Lump-Sum Payments; Delay to 2019 Possible for Funding.”
The 2016 longevity data from the NCHS will probably have some impact on the next annual SOA update (MP-2018), which is due out in the fall.
We should be cautious of generalizing too much from one year of data given that there is a lot of year-to-year volatility. According to the SOA’s MP-2016 report:
Continuing to focus on the 50–95 age grouping, the average annual age-adjusted mortality improvement rate from 2000 through 2009 was 1.93% for males and 1.46% for females. The corresponding rates for the period 2010 through 2014 dropped to 0.60% and 0.42%, respectively.
There has indeed been a trend of lower improvement over the last several years even at the older ages, but we should be cautious about setting long-term assumptions based on shorter-term trends — even when those trends last a decade.
The data is unclear on whether longevity for the retired population will continue to improve at high rates. A recent paper published by the Center for Retirement Research at Boston College5 concluded:
The key debate for long-range projections hinges on whether the future will mirror the past, with mortality rates of improvement fluctuating around the long-term rate of about 1 percent per year, or whether the big gains are behind us, with mortality improving less rapidly in the future.
Uncertainty about long-term changes in life expectancy means plan sponsors are, in effect, making a bet about mortality projections. To understand the potential consequences of that bet, they may wish to construct stochastic models of future outcomes to not only assess sensitivity to changes, but the probability of those outcomes as well. Armed with this knowledge, plan sponsors can consider additional de-risking or hedging strategies with greater confidence.
For more information about retirement readiness and/or to discuss how Sibson Consulting can help you help your employees prepare to retire, contact your Sibson consultant, the nearest Sibson office or one of the following professionals:
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2 Kenneth D. Kochanek, M.A., Sherry L. Murphy, B.S., Jiaquan Xu, M.D. and Elizabeth Arias, Ph.D. “Mortality in the United States, 2016.” NCHS Data Brief No. 293 (December 2017) (Return to the publication)
3 Deaths related to opioid abuse were a factor in the reversal. There was a 9.7 percent increase in deaths from unintentional injuries, which includes drug overdoses and accidents. (Return to the publication)
4 That analysis, US Population Mortality Observations – Updated with 2016 Experience, took into account 2016 mortality data released in October 2017 by the Centers for Disease Control and Prevention, as well as prior mortality experience data from 1999 through 2015. (Return to the publication)
5 Anqi Chen, Alicia H. Munnell and Geoffrey T. Sanzenbacher, “What’s Happening to U.S. Mortality Rates?” Center for Retirement Research at Boston College, Number 17-17 (September 2017). (Return to the publication)
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