News, Transaction Advisory

Look Beyond the Headlines on U.S. Life Expectancy Data

The most recent data released by the National Center for Health Statistics (NCHS) found that life expectancy at birth in the United States declined by nearly a full year from 2020 to 2021, from 77.0 years to 76.1 years, dropping U.S. life expectancy at birth to its lowest level since 1996. Moreover, when coupled with the 1.8 year decline in the prior year, the NCHS reported the biggest two-year drop in U.S. life expectancy since 1921-1923.

This headline data predictably sent many pundits to draw broad conclusions about longevity projections in America.

“The numbers are shocking,” said Dr. Michelle Williams, Dean of the Harvard T.H. Chan School of Public Health, on WP Live, a podcast from the Washington Post. She noted that “younger people in America are dying at higher rates than their counterparts in other high-income countries” and that the U.S. “also has among the highest maternal and infant mortality rates among upper-income countries.”

In fact, the latest NCHS data has reignited a debate about the structure, accessibility and effectiveness of the U.S. health care system.

“We have a wonderful sick care system that takes care of very sick people, but a very inadequate health care system,” said Dr. Asaf Bitton, Executive Director of Ariadne Labs, another guest on the WP Live podcast. “Investing in people’s health shouldn’t be contingent until the moment that they drop in front of us.”

Look Beyond the Headlines

But behind the shocking headlines and important social questions raised by the startling two-year drop in life expectancy, there are important nuances that begin to surface after more careful analysis.

For example, as the NCHS reported in August 2022, “the declines in life expectancy since 2019 are largely driven by the pandemic.” COVID-19 deaths contributed to nearly three-fourths (74%) of the decline from 2019 to 2020 and 50% of the decline from 2020 to 2021.

Another tragic driver of the decline in life expectancy can be traced to drug overdoses — most notably synthetic opioids such as fentanyl — amid the disturbing spike in opioid-related overdose deaths that took off in 2020.

And a deeper dive into the NCHS data reveals that for an average 65 year-old American, life expectancy has changed very little in the last few years, according to NewRetirement.com:

  • For both sexes, life expectancy is currently 18.4 years (83.4 years old), a decline of just 0.1 year from the previous year;
  • For men, average life expectancy is 17 years (82 years old), unchanged from the previous year; and
  • For women, average life expectancy is 19.7 years (84.7 years old), a decline of just 0.1 year from the previous year.

Meanwhile, a careful scrutiny of the NCHS data finds there are important differences in life expectancy based on factors such as geography and income.

For example, it is clear that people with more money live longer in America. “The wealthiest American men live 15 years longer than the poorest men, while the richest American women live 10 years longer than the poorest women,” reported NewRetirement.

And where you live is also a strong predictor of life expectancy in America. The state with the longest life expectancy at birth is Hawaii (80.7 years old), followed by Minnesota, Vermont, Washington and New Hampshire. The state with the lowest life expectancy is Mississippi (71.9 years old), followed by West Virginia, Alabama, Louisiana and Kentucky. These significant differences are correlated by education levels, smoking and obesity levels, and access to affordable healthcare, according to an analysis by World Population Review.

The point is that it is crucial to dig beneath the headlines related to U.S. life expectancy in order to have a more accurate understanding of the data, separating the signal from the noise. This is especially true for participants in the life settlement industry.

Importance of LE Forecasts

Monitoring Life Expectancy (LE) trends and creating LE forecasts is one of the most important disciplines in the life settlement industry as it shapes how market participants can determine the potential value of a life insurance policy on the secondary market.

A central component of determining an appropriate price for any policy is forecasting life expectancy, which involves a process of evaluating the medical history of an insured and projecting the remaining number of months that person can be expected to survive. For life settlement investors, this projection is crucial because it establishes the estimated time frame during which any premiums must continue to be paid by the policy owner and how long it will take to collect the death benefit. The shorter amount of time until the death benefit is projected to be paid out, the more cash the investor can offer to pay for the policy.

Life expectancy underwriting must be accurate and consistent if life settlement investors are going to be able to effectively manage longevity risk. If life expectancies are too high, the policy will be priced unfairly for the seller and consumers will not receive fair economic value for their policies. If life expectancies are too low, investors will end up overpaying for the policies and underperforming on their projected investment returns. Neither of these scenarios are in the long-term interests of investors in the life settlement asset class.

And here is where it is so important to look beyond the headlines on U.S. life expectancy data: We find that the cohort of the population that is most often associated with selling their life insurance policies on the secondary market tend to actually have longer life expectancies than the general population.

Conclusion

The life expectancy estimate is one of the most important factors in determining the price of a life settlement transaction, so it is crucial that investors and industry participants are able to have a high degree of confidence in the integrity of LE projections. An experienced portfolio manager who understands the nuances beneath the headlines related to the latest NCHS data will be able to separate the signal from the noise when determining a reliable life expectancy projection.