Milliman was approached by a Native American community. The community has certain programs which they run for the benefit of their citizens such as monetary assistance, burial benefits, healthcare clinics, cultural retention programs, and education aid. All of these require funding. They were looking for information on how the funding demands for these programs would change over time. The community leaders had taken a look at recent enrollments and made a simplistic estimate as to what their growth rate would be from year to year, but they were hoping for validation of their estimate and a more precise model of how they might grow over the next 20 years.
To gain tribal membership, one must be a direct descendant of a tribal member, and while an applicant has until age 21 to sign up, the majority tend to apply early because of the benefits available. As a result, future changes to the community’s enrollment were assumed to come from births to current citizens and from deaths. As a result, Milliman gathered data on their citizens including gender, dates of birth, the dates of birth for their citizen parents, and dates of death.
Because the current community citizens are a relatively young group with over 50% of the citizens under the age of 25 and only 5% over age 65, it became clear that birth rates would likely have a much more significant impact on the future size of the community than would death rates. In fact, over the projection period, the number of births outweighed the number of deaths by a ratio of more than six to one. Normally, when looking at fertility, the focus is on the mothers. However, for this particular community, eligibility as a citizen does not require any particular blood quantum or percentage of Native American blood. As long as a person is a descendant of a registered ancestor, that person was eligible for membership. Therefore, the offspring of fathers (who may or may not have married a female citizen) are also eligible to become citizens. As a result, we looked at the fertility rates separately for male and female citizens and studied the likelihood for each gender that the other parent was also a tribal citizen. The raw rates were adjusted by gender for the percentage who married another citizen so that births would not be double counted.
Milliman’s analysis showed that female citizen fertility rates in the community were significantly higher than for the general U.S. population. We assumed that these would decline over time toward societal norms. And while there are not readily available fertility rates for males in the general U.S. population, we assumed that male fertility would also decline over time in the same proportion as was assumed for females. The age specific fertility rates developed from the data were then smoothed for use in projecting the population.
Due to the general age of the citizenry and the overall size of the group, there was insufficient data to determine death rates for this specific population. However, we had enough data to benchmark their death rates against a standard table to which we used an age adjustment to predict future deaths.
Milliman prepared a report for the community leaders that showed that the size of the citizenry was likely to increase 50% over the next 20 years. While this is a significant increase, the previous estimate led them to believe that they would reach this size in a period of only 10 years instead of 20. We were able to provide a more realistic prediction of how their group would change over time. The citizens’ average age was expected to increase from about 26.8 years to roughly 29.6 years over the same 20-year period. Finally, we were able to provide them with count estimates in five-year age groups at five, 10, 15, and 20 years in the future, as well as the expected number of deaths. They were very happy with the refined estimate because it will enable them to match the various programs with the appropriate age groups and, using the future counts, develop budgets and make more definite plans for the future.