A Report on the Actuarial, Marketing, and Legal Analyses of the CLASS Program. Section VI: Adverse Selection

10/14/2011

In a mandatory long-term care insurance program, the rate of disability for participants will match the overall population average. Premiums will reflect the mix of people with disabilities and people without disabilities in the overall population. However, in a voluntary program, there is the possibility that certain individuals will have better knowledge of their own likelihood for disability. Those with knowledge that they will definitely require some sort of long-term care will be more likely to enroll in a program that pays these costs. This leads to higher than average costs for the program, which in turn leads to higher premiums, which can lead to lower participation among those with lower probability of disability. Called adverse selection and sometimes referred to as a death spiral, this effect at its worst results in an insurance program that is financially unsustainable.

The inverse of this situation is termed advantageous selection. Individuals may lack knowledge of their future expected need for long-term care, but may instead be risk averse and wish to sign up for the protection offered by long-term care insurance. Many times this risk aversion can also lead to a less risky lifestyle, which can lower the probability of certain types of disability.

The amount of adverse and advantageous selection in the current long-term care insurance market is a subject of debate. While some individuals likely do have better knowledge of potential future needs as a result of personal medical information or family history, the studies done to date have failed to show higher probability of disability among insured individuals. There are three factors that can account for much of this: risk underwriting by private long-term care insurance companies, the offsetting factors of adverse and advantageous selection, and the role of Medicaid as a safety-net program for low-income individuals which makes them less likely to purchase private long-term care insurance. Each of these factors has been cited in research as a possible reason for a lack of evidence of adverse selection.

For the CLASS program, the impact of adverse selection becomes more acute because there is no risk underwriting in this federal program. We treat the availability of this new federal program in much the same manner as the general Medicare program. Individuals are eligible to receive benefits as long as they have contributed for the required length of time, and the level of contribution is not determined by personal health factors. While participants must be attached to the workforce and contribute to the program for five years before becoming eligible for benefits, neither of these requirements can completely eliminate the effect of adverse selection.

While we can expect some amount of advantageous selection would partially offset this risk, we also now have to consider the impact of the private long-term care insurance market. That market could potentially “cherry-pick” the low risk individuals, thus exacerbating the impact of adverse selection in the program. Finally, we believe there are likely a number of individuals who desire this form of insurance but are unable to purchase it due to lack of affordability in the private market. We believe this pent-up demand could also increase the potential impact of adverse selection in the program relative to the current private LTC insurance market.

In order to estimate the role of adverse selection in the program, we first developed an estimate of the number of people by age that will develop a severe disability over the next five years. Next, for a given rate of assumed overall participation in the program, we compared the number of people that we assumed would enroll in the program against the total estimated incidence of disability for the entire eligible population over the next five years. Under a pure adverse selection scenario, people who would develop a severe disability over the next five years would all enroll in the program, which we termed “perfect knowledge”. To calculate the impact of this “perfect knowledge” scenario, we created alternate incidence rates using the individuals who develop a severe disability over the next five years in the numerator and the estimated enrollment in the program (which we calculated separately) in the denominator. As the total estimated enrollment increases, the alternate incidence rate declines until it reaches the overall population incidence rate for a program enrollment of 100 percent.

To address the unlikely nature of “perfect knowledge”, we dampened these alternate incidence rates downward to account for a portion of the population that would not have “perfect knowledge”, but would instead represent the overall average incidence rate. We also changed this dampening factor over time, to account for the likely pent-up demand in the early years of this new social program. For the first enrollment group, we assume the impact of adverse selection will be the greatest, with an initial weight of 75 percent towards the “perfect knowledge” incidence and 25 percent towards average incidence. This weighting declines for the first enrollment group over time as the effect of the initial pent-up demand wanes. For subsequent enrollment groups, we assume the impact of adverse selection will be muted but still present given the nature of the CLASS program.

Finally, we vary the starting impact of adverse selection based on a number of variables associated with earnings and work requirements for the program. Based on an analysis of the ACS, we determined that there is a higher prevalence of modest disability with lower-wage workers. If the earnings requirement is raised, it is possible that the initial impact of adverse selection on the overall CLASS program would be reduced. Therefore, we lower the starting weight for the “perfect knowledge” situation for higher levels of earnings requirement. Similar to the overall adverse selection calculations, this impact is also dampened for estimates of future enrollment groups.

Our baseline estimates do not make any adjustment to continuance rates based on program enrollment. In other words, we assume the average disabled person in the CLASS program will remain disabled for the same length of time as the average disabled person who is not enrolled in the CLASS program. If one of the results of adverse selection is not only a higher incident rate but also a higher continuance rate, the program could cost even more than our model currently estimates.

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