A Picture of Adverse Selection Derived From the Federal Register

Adverse selection in health insurance is the proclivity of insureds who accurately perceive themselves to be of higher than average risk to purchase insurance with greater frequency and, where possible, with higher benefits, than those who accurately perceive themselves to be of lower than average risk. Unchecked adverse selection can greatly restrict the amount of risk that can be transferred through an insurance market and cause a true loss to society. Insurers normally attempt to reduce adverse selection by “underwriting,” i.e. offering different contract terms based upon the insurer’s hopefully unbiased assessment of risk.  Settings in which such underwriting is impracticable or unlawful create a serious impediment to optimal risk transfer.

The Affordable Care Act (a/k/a Obamacare) creates a risk of severe adverse selection by prohibiting medical underwriting in the sale of health insurance.  One of the ways it attempts to palliate the contraction of the market that would otherwise occur is by subsidizing insurers in rough proportion to the riskiness of their insurance pool. Thus, although the high risk insured does not pay the insurer more for insurance than the low risk insured (except in limited ways for age, tobacco use and geographic location), the insurer ends up getting more for enrolling high risk insureds due to transfer payments made under the Risk Adjustment provisions codified in 18 U.S.C. § 18063. To establish this system, the government, among other things had to estimate the true “demographic risk” of individuals.  By demographic risk, one means risk of medical claims independent of “ICD-9 diagnosable” medical conditions that the individual may have. This demographic risk is revealed in part by the age and gender of the insured but also by their selection from amongst four (or five) levels of expected benefits known as “actuarial value.”  Persons purchasing policies with high actuarial value and thus having lower deductible and copay requirements, tend to be riskier than those purchasing policies with low actuarial value and thus having higher deductible and copay requirements.

The government data collected in this effort to implement Risk Adjustment under 18 U.S.C. § 18063 and placed in the Federal Register (78 F.R. 15409, 15422 (March 11, 2013)) gives us a rare opportunity to really see adverse selection in action not just as a matter of theory but as an empirical proposition.  The interactive element below shows this clearly.  It presents a graph showing for each gender and adult age level for which insurance through a private insurer is likely obtained, the relationship between the actuarial value of the plan selected and the risk factor posed. (Do not concern yourself with the units in which risk is measured).  What one can see is that there is a definite correlation for all ages and genders between the actuarial value of the plan selected and the risk factor of the individual. The line turns pink when females are selected for examination, blue when males are selected for examination. If you see a picture but no interactive elements, you need to download the free CDF player available here.
[WolframCDF source=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection.cdf” CDFwidth=”600″ CDFheight=”400″ altimage=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection1.png”]

We can also show the relationship in which risk factor appears on the x-axis and the actuarial value of the plan purchased appears on the y-axis.

[WolframCDF source=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection-2.cdf” CDFwidth=”600″ CDFheight=”500″ altimage=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection2.png”]

One of the many interesting features of this visualization is that the data is independent of the insured’s knowledge of disease.  Disease is  dealt with separately by the regulations implementing the Risk Adjustment provisions of the Affordable Care Act. It is also apparently independent of moral hazard — the proclivity of insureds with higher levels of coverage to more frequently incur events covered by the insurance policy. In this context, moral hazard would mean the proclivity of people with, say, platinum policies that have low cost sharing, to visit medical professionals more frequently and provide less resistance to proposed expensive medical procedures than people with, say, bronze policies. That tendency is addressed in the modeling embodied in the Risk Adjustment regulations, but is addressed as a separate “Induced Demand” factor. Thus, not only do we get a well researched estimate of the actual extent of adverse selection, but we get its effects disentangled from those of moral hazard — at least if the government has done it right and I am reading the document correctly.

The picture also gives rise to a question.  The Affordable Care Act permits insurers to price health insurance based on age. So, is provision of transfer payments that includes age in the mix “double counting”?  Why does government need to subsidize that for which insurers already are compensated? Is it an effort to address the fact that the statute constrains the extent to which age counts, limiting the pricing ratio to 3:1 from most expensive age level to least expensive age level?  I don’t know the answer to this question and welcome comments.

Exploring the effective marginal tax created by the Affordable Care Act

The Patient Protection and Affordable Care Act uses a refundable tax credit to subsidize purchase of health insurance through an Exchange by individuals with household incomes between 100 and 400% of the federal poverty level. 26 U.S.C. § 36B. It likewise requires insurers offering health insurance through an Exchange to offer purchasers with household incomes between 100 and 250% of FPL a contract providing heightened “actuarial value” for the price of a “silver policy.”  42 U.S.C. § 18071 (“reduced cost-sharing”).

The interactive graphic available via CDF here provides a framework for study of the effect of these provisions on the effective marginal tax rates of low- and middle income individuals. It shows that the Affordable Care Act typically adds 20-30% to these effective marginal tax rates. Because of discontinuities in the subsidization structure that occur as the taxpayer crosses various multiples of the federal poverty level, however, the effective marginal tax rate will sometimes go from 50% up to well over 100%, particular for those with incomes about 3.5 federal poverty level ($40,000 single individual; $82,000 family of 4). The estimates made here are even higher than those recently computed by the Congressional Budget Office since that organization de-emphasized issues created by discontinuities.  When combined with other federal income-based subsidies for those of low to moderate income such as SNAP (food stamps), the earned income tax credit, housing assistance, and, now the Pay As You Earn student loan program, the Affordable Care Act creates considerable disincentives to earn taxable income.

How did this come about? Harvard Law School has asked me to speak briefly on a topic related to health law at my upcoming 30th reunion. So, I thought I would update an article I did a few years back that attempted to project the tax implications of various subsidies provided by the Affordable Care Act designed to induce the purchase of health insurance.  A lot has happened since 2010 when the work on the article was done. We have a lot better idea about how the premium subsidies and the cost-sharing reductions are going to work.  We have somewhat better estimates of what premiums for the basic “metal tiers” are going to be.  And I’ve been joined by a few other academics and the Congressional Budget Office in thinking this topic is important.  These other sources, by the way, mostly confirm what I found back in 2010.

And why should you care?  You may like the Affordable Care Act or, more likely, some of the impulses behind the Affordable Care Act. But regardless of one’s political stance, one should not be blind to the significant problems that law creates. Particularly when you couple the effect of the Affordable Care Act with other federal programs intended to assist the poor, the effective marginal tax rates on the poor can become extremely high.  When you add in state and local programs, the rates get even higher. This is troubling because it creates a situation in which dependency is rational and in which government induces atrophy of the the sort of self-reliance that may become important when federal funds dry up.

Anyway, here’s the CDF.
[WolframCDF source=”http://mathlaw.org/wp-content/uploads/2013/04/The-Effect-of-Premium-Subsidies-and-Cost-Sharing-Reductions-on-Effective-Marginal-Tax-Rates-v2-.cdf” CDFwidth=”601″ CDFheight=”5000″ altimage=””]