I’m pleased to announce that Forbes has invited me to write for them as part of their prestigious The Apothecary blog. I’ve taken them up on their offer. It should mean a considerably greater readership. The first post will be up soon. Both it and the post to follow will be, immodestly, among the best I’ve ever written. So stay tuned!
My acceptance means, however, that this blog, acadeathspiral, is going to enter a new phase of life. It won’t be dead but it will be quieter. For a while, I’ll simply provide links to the latest Apothecary material. After a few months though, it will either be material that outside the topics on which Forbes wants me to blog, doesn’t fit certain formatting restrictions of The Apothecary or when I’ve “used up” the two blogs per month I am supposed to do for Forbes. So don’t stop periodically checking this site.
I want to thank everyone for their readership. I’ve learned a lot writing these entries and hope that you’ve enjoyed reading them.
We will have a fuller picture in a few weeks when the federal government is supposed to release the premiums and plans available on heathcare.gov, which serves about 34 states, but if Minnesota is representative, there are signs that the ACA is entering a dangerous phase. That state has posted its rates for 2016 already. It’s not pretty. Gross premiums for policies sold on its Exchange will go up between 14% and 49%. Net premiums will go up more than this or less than this depending on the income of the subscriber.
The table below shows the average rate increases for 2016 among the insurance carriers selling on MNSURE, Minnesota’s health insurance exchange. The data is simply copied from its website.
The spreadsheet shown below indicates gross and net premiums for a 40 year old individual residing in Minneapolis, earning $25,000 per year and selecting a silver plan. The rate increases contained there make the simplifying assumption that each insurer applied its average rate increase to the listed plans. We don’t have actual plan-by-plan data that would enable us to provide a better estimate. Here, the net premiums assume that the individual is deemed able under to contribute about $136 per month to the premium. As one can see the the net premiums go up between 2015 and 2016 by -7% for a few of the Medica plans to up to 36% for the more expensive Blue Cross plans.
If we reduce the income of the purchaser, the net premium increases can grow. Here, we take our same 40 year old but cut his income down to $18,000. The individual is (somehow) supposed to be able to contribute about $62 a month for a policy. Now the net premiums for the silver plans swing more dramatically, going from -15% for one of the Medica plans to 61% for one of the Blue Cross plans.
Is Minnesota representative? Not entirely. It is probably at the high end of premium increases in part because its premiums were unusually low in 2015. But if other states experience rate hikes anything like Minnesota, we will see healthier individuals search out alternatives or start to be more creative about hardship exemptions in the event they decide that insurance under the ACA is just too expensive. Either way, there is beginning to be a significant risk of the exchange markets unraveling.
The Obama administration announced earlier today that it would increase the rate of subsidy provided insurers under the transitional reinsurance program established by the Affordable Care Act. This program, in effect for the policies sold in 2014, 2015, and 2016 on one of the individual insurance exchanges fostered by the ACA, provides free specific stop loss reinsurance to insurers, something insurers would otherwise have to pay a lot of money to obtain. The Center for Medicare and Medicaid Services (CMS) announced today that instead of taxpayers giving insurers 80% of the losses on any individual for their claims between $45,000 and $250,000, it would now pay a full 100% of these losses.
The higher rate of reinsurance should not be interpreted as a sign that claims were lower than insurers expected — something that would run contrary to many of the recent insurer rate hike filings or the losses reported by many insurers. It is not a sign of the success of Obamacare; rather it is an artifact of its problems. If, for example, there were 14% fewer people enrolled in Obamacare than at the time the reinsurance rates were initially determined (7 million vs. 6 million), reinsurance payments could be, as here, yet more generous to insurers even if claims were 10% higher than originally projected.
There are several implications of today’s announcement. First, it means that, on a percentage basis, the ACA is subsidizing exchange insurers for 2014 even more than regulations enacted under it had heretofore prescribed. Since this same money paid to insurers could instead have been used to provide greater subsidies to poorer and middle class individuals trying to purchase health insurance, the candy distributed today to insurers is a bit troubling. Second, because CMS says it will actually have money left over from 2014 even after the increase in reinsurance rates, and because enrollment in Obamacare remains considerably lower than was estimated at the time of its enactment, there is an increased likelihood of reinsurance payments to insurers being higher than originally authorized in 2015.
We can get some sense of the magnitude of the changes announced today. To do so, I use data embedded in the Actuarial Value Calculator, a document produced by CMS for the purposes of figuring out whether various insurance plans met the standards for bronze, silver, gold and platinum policies. For an average silver policy, for example, the reinsurance that would have been provided prior to today would have been expected to save insurers about 11% in expenses, and, quite likely, premiums. With the new reinsurance parameters, the transitional reinsurance program will save insurers selling the same silver policies about 14%.
We can do the same exercise for platinum, gold and bronze policies. The results are not much different. The table below shows the results.
1. This is actually the second time CMS has made the transitional reinsurance program for 2014 more generous. Originally, the reinsurance would “attach” at $60,000. If an individual’s claims were below that amount, no reinsurance would kick in. Leter, CMS changed the attachment point to $45,000.
2. How could I do this computation so swiftly? I’ve been preparing for testimony before the House Ways and Means Committee on, among other things, the effect of the transitional reinsurance program on insurer rate changes and I’ve been working on a talk on a similar topic for the R in Insurance Conference later this month. So, all I had to do was plug the new parameters into my model, and out came the results. Be prepared.
Much has been made of the enrollment data in the Exchanges — pronounced “a success” by the Obama administration — and of the demographics of enrollments in the Exchanges — distributed enough towards the older end to be troubling. We don’t yet have the key data, however: what are the actual claims being filed by those newly insured on the Exchanges relative to what was expected. If the medical claims are higher than expected, that is likely to raise the costs of the Affordable Care Act this year and in the future. This year, high claims will increase “Risk Corridor payments” made by the federal government to losing insurers. Next year. it will place pressure on gross premiums charged by insurers or possibly force some insurers to withdraw from the marketplace. The result will be increased amounts paid by insureds, increased premium tax credit payments made by the government, and increased payments made by the government to address cost sharing reductions. It will also shrink the number of insureds below what it would have been had claims costs and, derivatively, premiums remained as expected.
Some evidence on claims costs is beginning to trickle in, however. Express Scripts, a large Pharmacy Benefit Management company that, so far as I know, has no axe to grind either in favor or opposition to the ACA, has published a report indicating that, at least so far, costs per member on the Exchanges are 35% higher than they are for commercial policies off the Exchanges. The study is based on a national sample of more than 650,000 pharmacy claims (423,000 covered lives) for the first two months of 2014 for patients enrolled in an Exchange policy with with pharmacy benefit coverage administered by Express Scripts. The analysis compared these pharmacy claims to those from commercial health plans, with pharmacy coverage administered by Express Scripts, during the same time period.
The key Express Scripts result — a 35% increase in claims costs — is significant for two reasons. According to data from the government’s own Actuarial Value Calculator, pharmaceutical expenses comprise about 21% of total healthcare expenses. Having to pay 35% more for such expenses is thus significant in and of itself. But peer-reviewed scholarly research such as that summarized and extended here indicates that pharmaceutical claims correlate positively with overall healthcare expenses. The higher pharmaceutical claims may just be the tip of the iceberg. Although these medical claims are often slower to be processed, Express Scripts has provided a disturbing leading indicator.
Before anyone pushes the panic button, however, there are less distressing possibilities. Everyone expected that those without prior health insurance or with lousy prior health insurance would result in a surge of claims to insurers for previously untreated conditions. One hopes insurers anticipated this surge in their pricing. If the surge is only transient as patients get various conditions under control, unanticipated extra costs on insurers will be addressed through Risk Corridor payments for this year and will not result in insurers revising their actuarial models of the risks posed by insuring on the Exchanges in an environment where most conventional underwriting methods are prohibited.
And, if one looks at the conditions that are apparently contributing to the high use of pharmaceuticals, a different spin can be placed on matters. The Express Scripts reports a higher use of anti-HIV/AIDS drugs, including expensive ones such as Atripla, among the Exchange population than among commercial insurers. So, it may be that the existence of subsidized coverage in the Exchanges is proving a vehicle for bringing hope and treatment to individuals with HIV or AIDS who previously were falling through the cracks (or being treated by other programs). The counter-spin, however, is that the fact that HIV treatment is a worthy end may be served does not mean that a general insurance scheme is the right way to address untreated HIV or AIDS. A coarsely rated and somewhat voluntary insurance scheme is a problematic vehicle for providing access to care to groups that include high-expense individuals, such as many with HIV or AIDS. The high and disproportionate prevalence of high expense individuals in a common pool contributes to the risk that the system will enter an adverse selection death spiral.
So, let me sound a notion of caution here. Just as the “enrollment” of 7 million people is not grounds for proclaiming the ACA a “success” or here to stay in any sort of stable way, an early datum about one component of claims is not grounds to proclaim the ACA a failure or to say with certainty that ACA insurance policies are likely to undergo massive premium increases. Still, since insurers will likely need to be making pricing decisions for 2015 in the coming months, and not after all the data is in early data can be important. The latest information from Express Scripts should be worrisome indeed.
Much has been made here and elsewhere about how young people are subsidizing older people under the Affordable Care Act. While there is a substantial element of truth to this contention, at least young people generally get to become older people. So, if the ACA were to last for decades, one could drive a small bit of comfort by viewing the arguable inequity as instead amounting to younger purchasers under the ACA just financing the health care they will receive at subsidized rates as they enter their 50s and beyond. The analogy doesn’t work terribly well because unlike something like a long term life insurance policy in which a similar “subsidy” exists, there is nothing that forces those insured later in life to have insured earlier on. But at least youth is a “burden” that most of us share.
A closer look at the evidence, however, shows that the major determinant of whether someone is subsidizing another or being subsidized under the ACA is gender. As shown here, gender is more important than age for purposes of ACA subsidization. And, for most of their adult lives males subsidize women under the ACA. Since gender is largely immutable, males never get the money back. While there are many factors that bear on whether this system is fair, the extent of subsidization is large enough to be worth considering.
The graphic above shows the extent of subsidization. For each adult age (21-64) and each gender, I show the subsidy (positive or negative) the person receives under the ACA. The pink line shows the subsidy for women; the blue line shows the subsidy for men. Subsidization is the difference between the expected costs the person incurs and the person’s premiums under the ACA (without consideration of any government premium subsidies) normalized by dividing the difference by the person’s premiums. Expected costs are calculated based on research by the Society of Actuaries and available in Excel data format from this web site. Premiums are calculated based on data provided by the Kaiser Family Foundation following its study of the ACA. To make sure that the units of of cost used by Kaiser and the Society of Actuaries match up, I apply a multiplicative correction factor to the premiums to ensure that the total level of subsidization is zero assuming that the estimated distribution of uninsured all enroll in ACA plans at an age-independent rate. Use of more complicated assumptions about enrollment patterns, such as incorporation of the apparent fact that most of those purchasing policies in the individual Exchanges already had insurance, would result in a different correction factor but should not alter the basic conclusions of this post about cross-gender subsidization.
When one adds children into the mix, the picture becomes a bit more complex. As shown in the graphic below, insurers under the ACA appear heavily to subsidize children of both genders, although male children are subsidized somewhat more. The calculations here are based on an assumption that child-only policies cost 65.2% of the price for policies sold to 21 year olds. (The 3:1 constraint on the ratio of premiums under the ACA applies only to adults (42 U.S.C. § 300gg(a)(1)(A)(iii)). This assumption was based on my sampling actual policies sold in the individual Exchanges under the ACA.
What is curious and perhaps somewhat comforting to those wanting to see the ACA succeed is the fact that, notwithstanding the significant differences in subsidization, women have not enrolled at rates way higher than men. Overall, government statistics show that 54% of the enrollees are women and only 46% are men. Nor are children forming a large part of the group enrolling in the individual Exchanges notwithstanding the high subsidization rates; they amount to just 6% of the total enrollees as of January 1, 2014. Now, part of this relative equality in enrollment rates by gender could be due to the masking effects of aggregation. It might be that the female/male ratio is considerably higher among those ages 25-35, where the subsidization differential is quite large and the female/male ratio is much lower among those over age 60. Thus, even if the overall ratio of enrollees was quite even, we could conceivably be seeing unequal enrollment patterns within age brackets. As noted in an earlier post, neither the federal government nor any of the states have released data with the degree of detail that would be needed to confirm or refute this possibility and thus the actual joint distribution of enrollment by age and gender remains a matter for estimation using algebra and numeric methods rather than actual data. Still, it certainly appears that the rate of subsidization can not be the only factor affecting enrollment patterns; matters such as income, savings, risk aversion, as well as political, cultural and social factors are likely to be playing a role as well. How else can one, after all, explain the enormous differences in rates of enrollment across various states?
Now, is this “fair”? That’s a difficult question. Most serious questions about insurance underwriting justice are difficult. (I’m going to include a short bibliography at the end of this post). A large chunk of the difference between male and female healthcare expenses are based on the attribution of costs arising out of joint sexual activity to the female only. It is, after all, the female’s body that is primarily affected by pregnancy. That attribution is based mostly on convenience, however, and, in many cases, the difficulty that would be created in trying to collect from a biological father. Moreover, it may be that subsidization in this area is compensatory, addressing countervailing subsidies of men in other government programs.
Even if it is fair, however, to the extent potential enrollees are responding to the extent of subsidization, we need to be concerned that unisex rating is reducing the efficacy of the ACA in shrinking the number of uninsureds. Remember all the ills created by lack of insurance that substantially motivated the ACA? Charging men “too much” leaves many of those ills untreated. If men are not signing up because they are being asked to pay too high a price, the goals of the ACA in reducing the number of uninsureds and improving individual health are compromised. Let us not forget as various politicians attempt to diminish expectations about the achievements of the ACA that it was heavily advertised as a program to reduce the number of uninsureds. Don’t believe me? Look here (32 million), here (34 million by 2019) and here for examples.
There are two additional pictures that may be helpful to those graphically minded in considering this issue. The first, shown below, shows the expected costs of males (blue) by age, the expected costs of females (pink) by age, and the unisex ACA premium (green)(normalized so that the overall subsidization rate would be zero if enrollment rates were age-independent).
The second graphic lets one compare the degree of age subsidization under the ACA. The purple line (kind of a blend of blue and pink) shows the expected costs of enrollees assuming that 50% are male and 50% are female. The green line shows the unisex ACA premium, again normalized so that the overall subsidization rate would be zero if enrollment rates were age-independent among the previously uninsured population. (A different normalization metric should not dramatically change the picture). As one can see although there is a zone between ages 20 and 32 in which premiums are exceeding cost and a zone between ages 60 and 64 where costs are exceeding premiums, and, although as mentioned above, children are heavily subsidized, for most of adulthood, premiums track expected costs pretty closely. This may help explain why neither under my analysis nor under that of the Kaiser Family Foundation do departures of the age distribution from those originally foreseen have a gigantic affect on the profitability of the system. What might have a larger effect, if it were to occur, would be departures of the gender distribution of enrollees from those originally foreseen; but, as mentioned above, thus far this does not seem to be occurring.
I do need to add one critical note. All of this assumes that the expected costs for each age come in as predicted. This is hardly known for sure. There are many reasons, including adverse selection, moral hazard, and others why those costs might depart seriously from that which was projected.
A “starter set” bibliography on insurance underwriting justice
Kenneth S. Abraham, Distributing Risk (1986) (the starting point for thinking about this issue)
Tom Baker, Containing the Promise of Insurance: Adverse Selection and Risk Classification, 9 Conn. Ins. L.J. 371 (2002-2003), available online here.
Seth J. Chandler, Insurance Underwriting with Two Dimensional Justice, available here.
Seth J. Chandler, Insurance Regulation, in the Encyclopedia of Law and Economics, available here.
City of Los Angeles Department of Water & Power v. Manhart, 435 U.S. 702 (1978) (available here)
Concerns about whether insurance sold on the individual Exchanges under the Affordable Care Act will succumb to an adverse selection death spiral have focused mainly on the shortage of younger enrollees into the system. This shortage is potentially a problem because, due to section 1201 of the ACA, premiums for younger enrollees must be at least one third of that for older enrollees even though actuarial science tells us that younger enrollee expenses are perhaps just one fifth of those for older enrollees. Younger enrollees are needed in large numbers to subsidize the premiums of the older enrollees. But at least premiums under the ACA respond at least somewhat to age.
The lesser studied potential source of adverse selection problems, however, is the fact that medical expenses of women for many ages are essentially double those of men and yet the ACA forbids rating based on gender. In a rational world, one would therefore expect women of most of the ages eligible for coverage in the individual Exchanges to enroll in plans on the Exchange at a higher rate than men. But, since the women have higher than average expenses than men, premiums based on the average expenses of men and women will prove too low, creating pressure on insurers to raise prices. And, of course, there could also be some disproportionate enrollment by older men who have higher medical expenses than women of equal age. While I welcome contrary arguments in what I regard as a fairly new area of study involving the ACA, gender-based adverse selection would certainly appear to be a real problem created by the structure of that law. To me, it looks to be potentially as large a problem as age-based adverse selection. It is certainly one that needs continuing and careful evaluation.
I see only three limited factors that reduce what would otherwise appear to be a significant additional source for significant adverse selection. As set forth below, however, I do not believe that any of these factors are likely to materially reduce the problem.
The first is ignorance. Adverse selection emerges only if individuals can accurately foretell their future medical expenses with some accuracy. To the extent, therefore, that men and women are ignorant of the effect of gender on their projected medical expenses, adverse selection is potentially diminished. I say “potentially,” however, because of a subtlety: people don’t have to know why their expenses are what they are in order for adverse selection to emerge; they only have to be somewhat accurate in their guess. Thus, even if men and women don’t make the cognitive leap from seeing lower (or higher) medical expenses to issues of gender, but they still on balance get it right, adverse selection can exist. Thus, I end up doubting that ignorance of the correlation between gender and medical expense is going to retard adverse selection problems very much.
2. Correlation between gender and expense is lower for those 50-65.
The second factor that might reduce adverse selection based on gender is, curiously enough, adverse selection based on age. The difference between male and female medical expenses diminishes as one exits the middle 40s and heads into the 60s. Indeed, somewhere in the late 50s, the rates cross and men have slightly higher average medical expenses than women. Therefore, to the extent that it is the 50-65 set that is disproportionately purchasing coverage in the individual Exchanges, the potential for gender-based adverse selection is diminished — but only somewhat . I say “but only somewhat” because if males over the age of about 55 or 58 enroll at higher rates than women of similar ages there will actually be adverse selection pressures due to the higher medical expenses of men that age. On the other hand, to the extents efforts are made to reduce age-based adverse selection by promoting coverage to the younger (potentially child-bearing) set, the potential for most forms of gender-based adverse selection increases.
3. Gender-correlated risk aversion
The third factor that could in theory reduce adverse selection problems is if men are more risk averse than women with respect to medical expenses and therefore purchase health insurance at equivalent rates even though their risk is objectively lower. Men could conceivably be somewhat more risk averse due to prevailing gender roles in the economy: on average it is possible that health problems among men may affect the family’s income more than health problems among women. Although as an academic I feel I would be remiss in failing to at least mention this possibility, in the end I doubt it amounts to very much. The roles of men and women in the family economy are complex and variegated. And the sources of risk aversion with respect to health are likewise multifold, having a lot to due with individual psychology, family history and family structure. And, of course, it could be that middle aged men are less risk averse than women, in which case the effects of adverse selection are worse.
How do we know about the effects of gender? The graphics below show two studies on the topic. The first is from the Society of Actuaries and was relied on by the Kaiser Family Foundation in its recent study of the effect of age rating. Look at the solid blue (male) and pink (female) lines. (Cute, Kaiser). One can see that until age 18, the costs for men and women in the commercial market has been about the same. By the time we get to, say, age 32, the cost for women is about 2.5 times that for men. The gap then shrinks so that by the time we get to age 58 or so, men’s costs actually start to somewhat exceed women’s.
A study by the respected Milliman actuarial firm, although differing in detail, shows roughly the same pattern. At age 30 or so, female expenses (blue) and about double those of males (green). The gap shrinks until about age 55, at which point male expenses exceed female expenses. (I’m not sure why Milliman shows female expenses being so much higher than male expenses for the age bracket marked “to 25” unless by “to 25” they mean ages 18-25.)
Is Gender-Based Adverse Selection Actually Happening?
As to whether the theoretical possibility of gender-based adverse selection is actually materializing, there is yet strikingly little evidence. I have scoured the Internet and found almost nothing on the gender of enrollees. In some sense this is not surprising since, unlike age, on which we have a trickle of data from CMS, which somehow is just unable to compile and release more complete information, gender is completely irrelevant to premium rates. On the other hand, as shown below, the federal application asks about gender, as do a few other state applications such as California, Kentucky and Washington State. So, in theory we should be able to get the information at some point. In the meantime, if anyone has information on this issue, I would love to see it. What we really need is a breakdown of enrollees based on both age and gender because the ratio’s role varies depending on whether enrollees below age 55 or so are involved or whether enrollees above age 55 are involved.
Two other notes
1. Someone might, I suppose, think that since the role of gender reverses at about age 55, the effects of gender on adverse selection cancel each other out. This would be totally wrong. If women have higher medical expenses than men up to about age 55 and if women therefore enroll at higher rates, that can cause adverse selection and premium pressures for enrollees of those ages. And if men have have higher medical expenses than women after about age 55 and if men therefore enroll at higher rates, that can cause adverse selection and premium pressures for enrollees of those ages. The effects are cumulative and not offsetting.
2. Does this mean I am opposed to unisex rating? No, not necessarily. First, women face higher medical expenses than men from about 20 to 50 significantly because of childbearing expenses. A family law expert on my faculty confirms what I suspected, which is that there is certainly no routine cause of action by the pregnant female against the prospective father for prenatal maternity expenses. We currently ascribe these expenses to the woman even though a male generally has contributed to those expenses through consensual sex. One could argue that unisex rating offsets this proxy for responsibility.
Second, if there are adverse selection problems caused by unisex rating, they can, in theory, be addressed by programs that that subsidize insurers for female enrollees. Impolitic as it might be to say so, one could treat being a fertile woman as a “risk factor” in the same way that section 1343 of the ACA currently treats medical conditions such as heart disease. The cost of the subsidies resulting therefrom could be seen as compensating somewhat for the transaction costs of figuring out which childbearing expenses the male partner has contributed to as well as tracking down the male partner and trying to hold him financially responsible.
What I am concerned about, however, is ignoring the issues created by unisex rating. Since it is not currently corrected for by section 1343 of the ACA and corrected for only in a very indirect and partial way by sections 1341 and 1342 of the ACA, there is the potential for the absence of gender rating to destabilize and ultimately shrink the insurance markets in ways that do few people any good. Wishing that a problem would go away or hoping that people don’t see the opportunities to optimize their behavior is seldom a recipe for successful government programs.
President Obama is holding a press conference this afternoon before he leaves on vacation. Here are three questions I would put to him.
1. A number of small businesses will receive cancellation notices sometime this year because their plans no longer conform with the Affordable Care Act. There’s some controversy about how many such notices will go out, but clearly millions of people will be affected. Will the protections you have now afforded to individuals who had their plans cancelled this year such as exemption from the individual mandate and the ability to uncancel their policy likewise apply to small employers and those insured by them?
2. Your Solicitor General argued to the Supreme Court that the individual mandate, what you called the minimum coverage provision, was crucial to the Affordable Care Act, that it, unlike other provisions of the ACA were inseverable. Here are quotes from pages 46 and 47 of the brief filed by your Solicitor General:
It is evident that Congress would not have intended the guaranteed-issue and community-rating reforms to stand if the minimum coverage provision that it twice described as essential to their success were held unconstitutional.
It is well known that community-rating and guaranteed issue coupled with voluntary insurance tends to lead to a death spiral of individual insurance.
Given the arguments made on your behalf, which may well have been correct, why are you not concerned that exempting more individuals from the individual mandate will not, as the insurance industry is complaining, destabilize the insurance markets and threaten the success of your legislation?
3. Are you concerned that while things are going better in some states such as New York, in many states such Oregon, Maryland, Texas there are a very low number of people enrolling in plans on the individual Exchanges so that even the most massive surge will not correct the situation before coverage begins January 1 or perhaps even before the end of March. Everyone agrees that low enrollment increases the risk that the markets in these states will become unstable? If that risk materializes, what is Plan B? What plans do you have to address the situation in those states?
I’m in the middle of a major posting and my day job so I have not had the ability to post anything particularly insightful in the past 24 hours or so. But others have been writing good stuff. So here’s a compendium of Affordable Care Act / Adverse Selection stuff worth reading. I’m hoping to have the big post out tomorrow or maybe late tonight.
Excellent visuals on enrollment in the Exchanges by states. From this article in the Washington Post.
An Exchange website worse than healthcare.gov? It’s possible. And it’s a sitting Duck for criticism. Read about it here.
A dissection of New York Times columnist Paul Krugman’s statistical nonsense about the California enrollment numbers. Krugman echoes the meme that where the websites are working, the young are signing up in the Exchanges. James Taranto of the Wall Street Journal joins my posts here and here in showing that the evidence does not support this point and exposes with some precision exactly Mr. Krugman’s path of sophistry. Note to Mr. Krugman: there are other states with working websites. Have you looked at the enrollment picture there?
An article from KUOW providing anecdotal evidence that the substitution of subsidized Exchange policies for canceled private insurance may in many instances be welcomed by insureds — particularly those who have had high medical expenses. If you ignore for a moment the tax costs of providing the subsidies — which is close to but not quite the equivalent of the macabre “Other than that, Mrs. Lincoln, how did you like the play?” joke — the ACA has made some people better off. The harder question is whether one gets much bang for the buck with the ACA.
According to a news report from Reuters, which is being picked up widely, early figures from four states are suggesting that the pool of insureds enrolling in the Exchanges is older than anticipated. If this situation persists and is not an artifact of either the particular states involved or simply the urgency with which older people applied, it further threatens the ability of the Affordable Care Act to sustain its plan of equalizing opportunity to acquire health insurance. This is so because, although older people do pay more in the Exchanges established by the Affordable Care Act, they pay less than would be actuarially appropriate. Young people, by contrast, pay more.
Here’s the key passage from the Reuter’s report.
The Obama administration is aiming to enroll about 2.7 million 18- to 35-year-olds in the exchanges by the end of March, out of 7 million total, or about 38 percent.
Early data from Connecticut, Kentucky, Washington and Maryland show that so far more than 20 percent of the 23,500 combined enrollees in private insurance plans are 18 to 34 years old, ranging from about 19 percent in Kentucky and Connecticut to about 27 percent in Maryland. About 36 percent of enrollees across the four states are 55 to 64. Additional demographic data is expected from California on Thursday.
A back of the envelope computation shows that this situation could result in additional losses of about 10% by insurers before risk adjustment payments are taken into account. And this is true even if each age group in the pool is as healthy as anticipated. The insurer losses resulting from disproportionate enrollment of older insureds has several important consequences: (1) insurers may decide to exit the pool in the future; (2) insurers may decide to raise premiums to adjust to the real pool as opposed to the projected pool; and (3) the government is going to pay more in Risk Corridor payments than anticipated.
The graphic above attempts to explain the issue. The x-axis shows the “true ratio” of expected medical claims to be paid between the oldest people in the pool and the expected medical claims to be paid of the youngest people in the pool. No one knows this figure for sure, but it could well be about 5 to 1. (This is why the Affordable Care Act is forced to hold premiums to a 3 to 1 ratio; otherwise premiums for the older group would be extremely high.) The y-axis shows the percentage of people entering the Exchange pools who are between 18 and 35. As the Reuters story indicates, it was hoped this group would comprise 38% of the pool. The green dot shows the result that might be hoped for if the young (18-35) indeed constitute 38% of the pool and the true ratio of claims paid between oldest and youngest is 5 to 1. At this level, insurers neither make unusual profits nor suffer unusual losses. The blue dot shows the result that might be seen if the young end up constituting — as the Reuters says the early evidence shows — about 20% of the pool. As one can see the red dot produces losses that are close to 10% of the risk assumed by insurers.
I’m placing a Mathematica notebook on Dropbox showing the computation. The idea, is that one finds a linear relationship between age and premium relationship that just covers claims payments for any value of the true ratio but subject to the constraint that the premium the oldest person pays can not be more than three times bigger than the premium the youngest person pays and under the assumption that those under age 35 constitute 38% of the pool. One then determines profits for any combination of true ratio and percentage of the pool under age 35. The process takes a little algebra (mostly rescaling operations), some calculus (finding “expectations” of distributions) and some visualization.
1. Although I modeled it that way, I am fully aware that the relationship between age and claims is non-linear. It’s probably more cubic. I’m also fully aware the relationship between age and premiums tends not to be linear under the Affordable Care Act. You can use the wonderful Kaiser Calculator or go to the fabulous Health Sherpa website to see that. And I’m also aware that using a uniform distribution to model the distribution of ages within the 18-35 group and the 35-64 group is imperfect. Still, for purposes of getting just some rapid order of magnitude estimates to guard against those who would dismiss the problem or wildly exaggerate it, I believe the linear assumption is supportable. It keeps things simple in a situation in which one has to be very careful about false assertions of precision and in which predictions are often hideously wrong.
2. As mentioned earlier, if the disproportionate enrollment of the elderly does not persist, as supporters of the ACA hope, the problem identified in this entry is reduced. Other problems, such as disproportionate enrollment of the unhealthy — which is a far more significant issue — may persist. But we don’t have data at present on the health of those enrolling. It is troublesome, however, that most of the time proponents of the ACA trot out someone who has actually enrolled in the Exchanges (or is a Jessica Sanford who thought they would), it is someone who has higher-than-average medical expenses. I wish they would more frequently show off someone who is healthy now but just wants protection against the possibility of an adverse health event.
Note: this entry will likely be updated today as new information comes in.
President Obama is stating right now that the Executive branch of the federal government will fix the problems created by insurer cancellation of many individual health policies by forcing insurers to renew cancelled policies. It may be that state insurance commissioners will be able to veto this imposition within their own states.
A number of legal and economic issues are created by this proposal. I sketch them here.
1. Where does President Obama get the authority to issue such a regulation? The President can not rule by decree and it will be challenging to figure out what statute authorizes him to undo parts of the Affordable Care Act that would have prohibited insurers from selling such policies. Perhaps the President will argue that all he is doing is directing the Secretary of HHS and other executive officials not to prosecute or otherwise punish insurers for selling policies without Essential Health Benefits but only with respect to policies they had just recently cancelled? Or possibly he might expand the definition of what it means to be “grandfathered.” In any event, there is a separation of powers issue here worth thinking about.
But, if I am hearing the President correctly and reading news accounts properly, I am wondering who will have “standing” to challenge the ruling since no one appears to be forced to do anything. If I’m reading things incorrectly and insurers are indeed going to be forced to uncancel, then, unlike earlier expansionist views of executive authority such as delay of the employer mandate, there will definitely be institutions with “standing” — some insurer that does not want to renew — to challenge the ruling.
As one might expect, law professors are opining on the legality of the President acting here without congressional authority. Professor Eugene Kontorovich from Northwestern University Law School has published a quick piece on The Volokh Conspiracy, a leading conservative-libertarian blog, arguing that the President’s fix violates separation of powers. He also cites to the letter actually sent by CMS to State Insurance Commissioners explaining the President’s ruling.
2. From what I am now hearing, it appears that insurers will not be forced to reissue these policies. Nor will state insurance commissioners be forced to authorize sale of these policies. That should eliminate federalism issues or possibly due process issues. Otherwise there would have been a question as to whether forced insurance by the federal government — whether done by a legislature or through executive action — violates any independent protections of the Constitution? Assuming this is regulation of interstate commerce, nonetheless neither the executive nor the legislature can take property without just compensation and, on occasion, this provision has been interpreted to encompass regulations that effectively take property.
3. Assuming insurers accept the President’s invitation, doesn’t this create more problems for the Exchange? The hundreds of thousands or millions of people who are potentially being helped here are people who have recently been medically underwritten and are most likely healthy. If these people have the chance of being forced into a pool in which there is no medical underwriting and one in which there is, many will opt — even if there is no subsidy — into the underwritten pool, particularly if the Exchange policies offers a feature/price mix that they do not want. But the withdrawal of these people from the Exchange pools makes it ever more likely that an adverse selection death spiral could develop in the Exchange. The horse journalists and others should be beating now is not about breaches of promise — that’s been thoroughly discussed — but about how insurers who have agreed to write policies in the Exchange on one set of assumptions about the pool are going to react when those assumptions change.
Exploring the likely implosion of the Affordable Care Act