1. Steve Goss, Chief Actuary U.S. Social Security Administration
The Importance of Consistent Data on Deaths and Exposure over Time, by Age, Sex, and Cause of Death
Steve Goss, Chief Actuary
U.S. Social Security Administration
Longevity 12 Conference, Plenary Session III
September 30, 2016

2. Issues for Social Security, Medicare and for all Insurance/Benefit Plans
The aging issue, not just mortality
Age distribution = fertility, mortality, immigration
National population vs sub-population
Plan participants: active vs. in benefit
Data: need to be appropriate and consistent
Death data vs. exposure data
By gender, income, race, cause of death—as needed
Understanding the limitations
Projections only as good as the data used

3. Paying for “Retirement” at a Macro Level Aging (change in age distribution) mainly due to drop in birth rates 3

4. Mortality Data Needed: for Whom?
For population “at risk”
National data for universal social insurance
NCHS state-reported deaths; total, by cause
Census estimated population
Medicare/SSA data for ages 65 and over
Sub-populations
Retirees by career-average earnings level
“Disabled” beneficiaries by age and duration:

5. Appropriate Data: by Age Critical Age-gradient in reduction is clear

6. Consistent Deaths and Exposure: Inconsistency can distort measured rates
U.S. NCHS/Census national data
All we have under age 65
Completeness and age-reporting concerns
Used for Social Security as well as HMDB
NCHS deaths by cause very useful
Over age 65 Medicare/SSA data are better
Consistent deaths and exposure
More accurate age based on past reporting
Current reporting can vary over time

7. Death Rates 65+ : NCHS/Census have been declining faster than Medicare/SSA rates

8. Mortality Decline Varies Over Time Antibiotics/economy 1936-54; health spending 1968-82

9. Reductions Even for “Best Nations” Have Also Varied over Time9

10. Mortality Rate of Decline by Sex, Age, & cause of Death: from 1979 to 2013

11. Mortality Varies by Career Earnings Level Trustees Report projections have reflected this for decades 11

12. Limitations Better data = better projections = better planning
Most critical factors
Understanding the conditions of the past
Anticipating what is likely to be different for the future
Closing the table; is there an omega?
Projections for the future from past data
Interpretation and judgment

13. For More Information… http://www.ssa.gov/oact/
Documentation of Trustees Report data & assumptions
Historical and projected mortality rates
Annual Trustees Reports 13