A Report on the Actuarial, Marketing, and Legal Analyses of the CLASS Program. Section IV: Estimating Participation in the CLASS Program

10/14/2011

One of the most challenging aspects of constructing a model that estimates voluntary participation in a new long-term care insurance product is the relationship between premiums and participation. We believe the level of participation in a voluntary, federally run long-term care insurance program will largely be based on the premium. To estimate premiums in an actuarially balanced insurance program, we must estimate both expected costs as well as expected income. Both costs and premium income are directly estimated via the participation in the program, putting us back where we started. As a result, premiums depend on participation, but participation depends on premiums.

From an economic standpoint, we would expect rational individuals to enroll in the program if the expected value of the benefit were greater than the expected cost of premiums over the course of enrollment. Once we determined this relationship, we could use observed rates of elasticity for long-term care insurance to vary enrollment for each age group based on the actual premium calculated by the Model. However, for the CLASS program we must also factor in the interaction with private long-term care insurance as well as general uncertainty about the need for any long-term care insurance.

Most of the observed elasticity rates are based on varying levels of benefits from different private long-term insurance programs, with different sub-populations of enrollment. To use these elasticity rates properly, we would need to anchor each age group to an external participation and premium level, which is difficult given the differences in benefits offered by traditional long-term care insurance. In addition, enrollees in private long-term care insurance may react differently than the general public to the need for long-term insurance, given the expected differences in demographic profiles. Both of these factors are likely to make enrollment in the CLASS program lower than it would be otherwise.

There is little evidence to determine the willingness to enroll in a program such as CLASS, although most experts tend to believe enrollment will be between one and six percent of eligible individuals. As such, we use a baseline assumption that two percent of the working population will enroll in the CLASS program in the first year, not including individuals eligible for the low-income subsidy. We assume subsequent years’ enrollment will be a fraction of this amount, with declining enrollment rates for the next 5 years, reaching a steady annual enrollment rate of approximately 0.1 percent of the eligible population. For the baseline model, these assumptions lead to non-low income enrollment of 2.2 million individuals in the first year, declining to 145 thousand new enrollees in 2017, and total enrollment by 2020 of 3.5 million individuals.

After estimating an overall participation rate, we applied age-adjusted participation rates. Since it is highly likely that participation will increase with age as individuals approach and begin to plan for retirement, we allow our participation estimate to also increase with age. We used two separate methods to estimate participation by age:

  • Smooth enrollment expectation: One approach to enrollment that we modeled applied a constant rate of increase or decrease based on an inflection point. We chose the age of 50 as our inflection point, assuming that the average participation would equal participation at age 50. We then increased participation at a rate of 2 percent for each age above 50, and decreased participation at a rate of 1 percent for each age below 50. This adjustment was applied as a growth rate. For example, with the baseline model assumption of 2 percent overall participation,we used this rate for enrollment at age 50. Using the smooth curve process, estimated participation at age 49 is 1.98 percent (2 percent x 0.99) and participation at age 51 is 2.04 percent (2 percent x 1.02). After experimenting with different factors, we chose these growth rates because they maintain an overall participation rate equal to our estimated rate.
  • Federal Long-Term Care Insurance Participation: In addition to the smooth estimation process, we modeled a separate enrollment expectation rate based on the observed enrollment rates in the federal long-term care insurance program (FLTCIP). Using the actual enrollment rates by age for in-force policies, we constructed a curve that starts with the total estimate of enrollment and distributes the enrollment by age mimicking the actual experience of the FLTCIP.

Exhibit 1 displays the enrollment distribution under these two options. Under the FLTCIP option, enrollment is much more heavily weighted towards individuals aged 50-60, while the smooth enrollment estimation has a higher proportion of enrollees aged 25-40.

EXHIBIT 1: Enrollment Estimation Methods

Line Chart.

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