Tag Archives: Congressional Budget Office

CBO projection of $8 billion from Risk Corridors is baffling

The Congressional Budget Office just issued a report that assumes the Affordable Care Act system of individual policies sold in Exchanges without medical underwriting can remain relatively stable. Tightly bound up with that assumption is its prediction about a controversial ACA program known as “Risk Corridors” that requires profitable insurers to pay the federal government up to 80% of profits they make on policies sold on the Exchanges but that also requires the federal government to pay insurers up to 80% of the losses they suffer from policies sold on the Exchanges.  The CBO now believes it has enough information to predict that Risk Corridors will actually make money — $ 8 billion over three years — for the government at the expense of insurers.

This CBO prediction of $8 billion in federal revenue, which has gained much publicity,  pulls the rug out from critics of the ACA such as Senator Marco Rubio who have introduced legislation that would repeal Risk Corridors as an insurance industry “bailout.” Such a blunting of Senator Rubio’s proposed repeal legislation is crucial in the ongoing battle over the ACA because repeal of Risk Corridors could  result in insurers (who just might not believe the CBO’s numbers) exiting the Exchanges for fear of having no government protection against losses resulting from unfavorable experiences in the new market the government has created. On the other hand, if the CBO is just getting its number wrong, Rubio’s case for repeal of Risk Corridors remains as strong (or problematic) as it ever was. The CBO projection is also important because Risk Corridors nets the government money if and only if the ACA works, insurers are able to make some profits, and a death spiral never takes hold. And this, as readers of this blog are aware, is a prediction about which many have serious doubts. 

Here’s the short version of the rest of this post.

I’ve done the math and I don’t see how the CBO is getting this $8 billion number unless it is assuming either very high enrollment in policies covered by Risk Corridors or very high rates of return made by insurers.  Or it made a mistake. I don’t think the CBO’s own numbers support very high enrollment in policies covered by Risk Corridors and I don’t believe either an emerging reality or the CBO’s own rhetoric justify assuming very high rates of return.  So I think the CBO ought to take a second look at its prediction. People should not yet make policy decisions based on the CBO estimate.

Reader, you now have a choice. I’m afraid that the next several paragraphs of this post become very technical. It’s kind of forensic mathematics in which one attempts to use statistics and numerical methods to deduce the circumstances under which something said could be true.  If that sounds dreadful, scary or tedious, I would not protest too loudly were you to skip ahead to the section titled “How could I be wrong?”  Before you leave, however, realize that what I am attempting to accomplish in the part you skip is a form of proof by contradiction. I prove that if what the CBO was saying were true, then insurers would have to be making 8% profit.  But nobody, including the CBO thinks they will make 8% profit, so the $8 billion number can’t be right.

On the other hand, dear reader, if you liked the Numb3rs television show (including my minor contributions thereto) or math or detective work or just care a lot about the Affordable Care Act, the rest of this post is for you.  What I am about to discuss is not only exciting math, but also the soul of the Affordable Care Act — whether the individual Exchanges without medical underwriting can remain relatively stable.

Forensic mathematics in action

Conceptually, here’s the calculation one needs to do.  What we want to figure out is the distribution of insurer profits (measured as a ratio of expenses divided by premium revenues)  upon which the CBO must be relying. I assume the CBO is using a  member from the “Normal” or “Lognormal” family of distributions because those are typical models of financial returns and there is little reason to think that the distributions of insurer profits (expenses minus revenues) will materially depart from those assumptions.  To continue reading this post, you don’t have to know exactly what those distributions are except that they look for our purposes like the “bell curves” you have seen for many years.  I’ve placed a graphic below showing some normal (blue) and lognormal (red) distributions. Although it should not matter all that much, I’m going to use a lognormal distribution from here on in because the ratio of insurer expenses to premiums should never be negative and the lognormal distribution, unlike its normal cousin, never takes on negative values.

Examples of probability density functions for normal and lognormal distributions
Examples of probability density functions for normal and lognormal distributions

The problem is that there are an infinite number of lognormal distributions from which to choose.  How do we know which distribution the CBO is emulating in its computations?  How do we know just how positive the CBO assumes the individual Exchange market is going to be on average or how dispersed insurer profits are going to be? As it turns out, the complexity of the lognormal distribution can be characterized with just two “parameters” often labeled μ (mu, the mean of the distribution) and σ (sigma, the standard deviation of the distribution).  Once we have those two parameters (just two numbers), we can deduce everything we need about the entire distribution.

Now, to solve for two parameters, we often need two relationships. And, thoughtfully, the CBO has given us just enough information.  It has told us how much money in total it intends to raise from Risk Corridors ($8 billion) and the ratio (2:1) between money it collects from profitable insurers and the money it pays out to unprofitable insurers. These two facts help constrain the set of permissible combinations of Risk Corridor populations (the number of people purchasing policies in plans subject to the Risk Corridor program) and insurer profitability distributions. What I want to show is that it takes an extremely high Risk Corridor population in order to get rates of return that are not way larger than most people — including the CBO — think likely to occur.

I first want to calculate the amount of money insurers would pay to HHS under the Risk Corridors program if the total amount of premiums collected were $1. Some of the payments — those by highly profitable insurers  —  will be positive.  Those by highly unprofitable insurers will be negative. To do this I take the “expectation” of what I will call the “payment function” over a lognormal distribution characterized by having a mean of  μ and a standard deviation of  σ.  By payment function, I mean the relationship shown below and created by section 1342 of the ACA, 42 U.S.C. § 18062. This provision creates a formula for how much insurers pay the Secretary of HHS or the Secretary of HHS pays insurers depending on a proxy measure of the insurer’s profitability. The idea is to calculate a ratio of “allowable costs” (roughly expenses) to a “target amount” (roughly premiums).  If the ratio is significantly less than 1 (and outside a neutral “corridor”), the insurer makes money and pays the government a cut. If the result is significantly greater than 1 (and outside the neutral “corridor”), the insurer loses money and receives a “bailout”/”subsidy” from the government.  The program has been referred to with some justification as a kind of “derivative” of insurer profitability, the ultimate “Synthetic CDO.

The graphic below shows the relationship contained in the Risk Corridors provision of the ACA.  The blue line shows the net insurer payment (which could be negative) to the government as a function of this proxy measure of the insurer’s profitability. Ratios in the green zone represent profits for the insurer; ratios in the red zone represent losses. Results are stated as a fraction of  “the target amount,” which, as mentioned above, is, roughly speaking, premium revenue.

How much the insurer pays (positive) or receives (negative) under Risk Corridors as a function of  measurement of profitability
How much the insurer pays (positive) or receives (negative) under Risk Corridors as a function of a ratio-based measurement of profitability

When we do this computation, we get a ghastly (but closed form!) mathematical expression of which I set out just a part in small print below. (It won’t be on the exam). I’ll call this value the totalPaymentFactor. Just keep that variable in the back of your mind.

Excerpt of the formula for insurer total payout
Excerpt of the formula for insurer total payout

I next want to calculate the amount of payments profitable insurers will make to HHS. To do this, we truncate the lognormal distribution to include only situations where the ratio between premiums and expenses is greater than 1. Again, we get a pretty ghastly mathematical expression, a small excerpt of which is shown below. I will call it the expectedPositivePaymentFactor.

Formula for expected negative insurer payments under risk corridors over a truncated lognormal distribution
Formula for expected negative insurer payments under risk corridors over a truncated lognormal distribution

Finally, I want to calculate the amount of payments unprofitable insurers will receive from HHS. To do this, we truncate the lognormal distribution to include only situations where the ratio between premiums and expenses is less than 1. Again, we get a pretty ghastly mathematical expression, which, for those of you who can not get enough, I excerpt below. I will call it the expectedNegativePaymentFactor.

Formula for expected positive insurer payments under risk corridors over a truncated lognormal distribution
Formula for expected positive insurer payments under risk corridors over a truncated lognormal distribution

The CBO has told us in its recent report that the government will collect twice as much from profitable insurers (expectedPositivePaymentFactor) as it pays out to unprofitable ones (expectednegativePaymentFactor).  We can use numeric methods to find the set of μ, σ combinations for which that relationship exists.  The thick black line in the graphic below shows those combinations.

 

Black line shows combination of mu and sigma that result in the correct ratio of positive and negative insurer payouts under Risk Corridors
Black line shows combination of mu and sigma that result in the correct ratio of positive and negative insurer payouts under Risk Corridors

To determine which point on the black line above, which combination of the parameters μ, σ , is the actual distribution, we need to use our information about the totalPaymentFactor.  The idea is to realize that the totalPaymentFactor must be equal to the quotient of the CBO’s estimated $8 billion and the total premium collected by Risk Corridor plans over the next three years.  But we know that the total premium collected should be equal to the mean premium charged by the Exchanges multiplied by the number of people in Risk Corridor plans. Some math, discussed in the technical notes, suggests that the mean premium under the ACA is about $3,962. And the CBO accounts for 8 million people being in Risk Corridor plans in 2014, 15 million being in Risk Corridor plans in 2015 and 25 million being in Risk Corridor plans in 2016. This means that the total premiums collected by insurers under Risk Corridor plans over the next 3 years should be about $190.2 billion. And this in turn means that the totalPaymentFactor must be 0.042.

Ready?

It turns out that of all the infinite number of lognormal distributions there is only one that satisfies the requirements that (a) the government will collect twice as much from profitable insurers (expectedPositivePaymentFactor) as it pays out to unprofitable ones (expectednegativePaymentFactor) and (b) for which the totalPaymentFactor takes on a value of 0.042. It is a distribution in which the mean value is 0.923 and the standard deviation is 0.113.  I plot the distribution below. A dotted line marks the break even point for insurers.  Points to the left of the break even line correspond with profitable insurers; points to the right correspond with unprofitable insurers.

Lognormal distribution of insurer profitability consistent with CBO data
Lognormal distribution of insurer profitability consistent with CBO data

Here are some factoids about the uncovered distribution.  The  average insurer will have expenses that are 92.3% of premiums and the median insurer will have expenses that are only 91.6% of profits. In other words, they will be making 7.7 cent and  8.4 cents respectively on every dollar of premium they take in.  For reasons discussed below, this is a difficult figure to accept. It is particularly difficult in light of the pessimistic news that is emerging about things such as the age distribution of enrollees , reports from Deutsche Bank that one of the largest insurers in the Exchanges, Humana, expects to receive (not pay!) a lot of money under the Risk Corridors program, the hardly exuberant forecasts of other publicly traded insurers about the ACA, and the recent general downgrading of the insurance sector by Moody’s partly because of the ACA.

Implicit in my finding about the most likely distribution of profitability is an assertion by the CBO that 76% of insurers will be profitable under the ACA while 24% will be unprofitable. About 17% will be sufficiently unprofitable that they will receive subsidies (a/k/a bailouts) from the federal government and 9% will be sufficiently unprofitable that their marginal losses will be covered at 80%. Only 15% of insurers will be “inside” the risk corridor and neither pay nor receive under the program.

How could I be wrong?

I feel  confident that I’ve done the ” gory math part” of this blog post correctly. Mathematica, which is the software I’ve used to do the integral calculus and the numeric components involved just does not make mistakes.  I also feel pretty confident that I understand how the Risk Corridors program works under section 1342 of the ACA.  That’s kind of my day job. And so, readers who skipped down to this part, I do believe that if the CBO were right about the $8 billion, that could only happen if insurers were, on average, earning an implausible 8% in the Exchanges.

If I’m wrong, then, it is because, except for the little issue I will mention at the end, I have made bad assumptions about the total premiums insurers expect to collect over the next three years in policies covered by Risk Corridors. That error could come from two sources. I could have the mean premium per policy wrong or I could have the relevant enrollment wrong. Let’s look at each of these.

Could I be wrong about the mean premium?

I computed the mean premium in the computation above by using data collected by the Kaiser Family Foundation on the ratio of premiums by age under most insurance plans and the typical Silver plan premium for a 21 year old (non-smoker). I then used the original forecast about the age distribution of insureds to compute an expected premium.  I got $3,962.  And this number seems very much in line with earlier HHS estimates, which were that mean premiums would be $3,936. So, I think I have the mean premium correct.

Could I be wrong about the number of people in Risk Corridor plans?

I computed the number of people enrolled in policies covered by Risk Corridors by looking at the CBO’s own figures.  I’m not vouching that the CBO is right in its projections, but this is not the day to argue that point.  The CBO now says (Table B-3, p. 109) that individual enrollment in the Exchanges will be 6 million, 13 million and 22 million respectively over the next three years.   And it says that employment-based coverage purchased through Exchanges (which I assume are SHOP Exchanges) will be 2 million, 2 million and 3 million respectively.  So , by addition, that’s where the figures I used of 8 million,  15 million and 25 million come from.  I’m not aware of anyone else who would purchase a policy subject to Risk Corridors. Again, bottom line, I don’t think I’m doing anything wrong here.

The little issue at the end: Could ACA definitions be responsible for the incongruity?

The only other conceivable explanation of the divergence between the CBO figures and my analysis is that I am failing to take a subtlety of Risk Corridors into account.  Remember, careful readers, that sentence earlier up that started out: “The idea is to calculate a ratio of “allowable costs” (roughly expenses) to a “target amount” (roughly premiums).” I stuck in the “roughlies” because the “allowable costs” are not exactly expenses and the “target amount” is not exactly premiums. When you look at the statute and the regulations, you can see that both of these terms are tweaked: basically you subtract administrative costs from both values.  And you subtract reinsurance payments from expenses — but that makes sense because the insurer reduced premiums in anticipation of those reinsurance payments.

So, in the end, I don’t see why these subtleties should affect my analysis in any significant way. But I am not infallible. And I do pledge that if someone points out an error to me, I will dutifully assess it and report it.

Sensitivity Analysis

Out of an abundance of caution, however, I have rerun the numbers on the assumption that premium revenue from policies subject to Risk Corridors is 50% greater than my original estimate either because of an underestimate of per policy costs or a failure to understand that there is some additional group within Risk Corridors protection.  When I do that, though, I find that the ratio of expenses to premiums is 0.943, meaning that insurers are still earning a pretty substantial 5.6%.  Although that is more believable than the earlier figure of 7.7%, it is still pretty high. 

Conclusion

To be honest, it makes me very nervous to say that the CBO did its math wrong or, worse, to accuse it of bad faith.  These are intelligent, educated professionals and they have access to a lot more data and a lot more personnel than I do.  Here at acadeathspiral  it’s just me and my little computer along with some very powerful software.  On the other hand, it’s not as if the CBO hasn’t been wrong before. It assumed earlier that the government would reduce its deficit $70 billion over 10 years as a result of Title VIII of the ACA (the so-called CLASS Act on long term care insurance) when many independent sources believed — rightly as it turned out — that the now-repealed CLASS Act was obviously structured in a way that could never fly.  The CBO assumed in July 2012 that 9 million people would enroll in the Exchanges in 2014, a number that is now down to 6 million. And, while there are explanations for each of these changes, the bottom line is that CBO is fallible too.

So, if I might, I would strongly urge the CBO to double check its numbers and provide more information on the data it relied upon and the methodology it employed in getting to its results.  I’d ask Congress, which has ongoing oversight of the ACA, to insist that the Congressional Budget Office, which is exempt from Freedom of Information Act requests from ordinary citizens, provide further detail.  American healthcare is indeed too important to have policy decisions made on the basis of what could be some sort of mathematical error.

Really Technical Notes

  1. I’m using a reparameterized version of the lognormal distribution that permits direct inspection of its mean and standard deviation rather than the conventional one, which in my opinion is less informative.   The explanation for doing so and the formula for reparameterization is here.
  2. To compute the average premium, I took the premium ratios used by the Kaiser Family Foundation, calibrated it so that a 21 year old was paying the national average payment for a silver plan purchased by a 21 year old. I then computed the expected premium over the distribution of purchase ages originally assumed by those modeling the ACA.
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The Two Million Scenario: What if the Affordable Care Act enrolls a lot fewer people in the Exchanges than predicted?

People can be blinded by dreams in many spheres
People can be blinded by dreams in many spheres

Many people who remain basically positive about the Affordable Care Act are viewing the enrollment statistics like the football fan whose team is 2-6 and who point out that the team could win 7 out of its 8 remaining games and still probably make the playoffs.  Yes, getting off to a really bad start doesn’t preclude a happy ending. Success may still be mathematically possible. But unless there’s good reason to think that the fundamental factors such as poor coaching,  poor game plans or unexpected injuries that have led to the bad start no longer apply, the more reasonable prediction is that things will continue more or less as they have.

It’s time to start thinking realistically about what happens if a core component of the Affordable Care Act, subsidized, non-underwritten health insurance available from private insurers, essentially fails to provide many with better access to medical care. This might not happen in every state — there might be a few whose Exchanges can be deemed “successful” — but it is looking more and more to me as if we are heading for enrollments in many states well, well short of that on which the arguments for the ACA were significantly premised. Indeed, some supporters of the ACA have started moving the goal posts, revising history to say that the real goal of the Act wasn’t to reduce the number of uninsureds but to have an actuarially sound pool. (So the purpose of the Act was to help insurance companies stay afloat?) And it hardly helps enrollment when President Obama urges his allies to hold back enrollment efforts so the insurance marketplace does not collapse this coming week under a crush of new users even after he earlier assured the nation  healthcare.gov  was supposed to be working much better by this time.

For purposes of this blog entry, I’m going to assume that enrollment in the Exchanges ends up being about 2 million for 2014 instead of the projected 7 million.  I can’t rigorously justify that number — but, of course, neither could the pundit who is now saying 4 million. And, if I had time and space I’d prefer to do this analysis under a variety of scenarios, but, for now, the 2 million figure feels about right. And if I were betting on which side of the 2 million we will fall, it would be the lower side. What are the consequences? I can’t address all of them in a single blog entry — and trying to predict matters past 2014 gets very treacherous — but here are some.

And, for those of you who don’t want to read further, here’s the headline:

Insurance sold through Exchanges without medical underwriting — a central promise of the Affordable Care Act — is likely to implode in a significant number of states by 2015 while limping along in several others but providing little net desired decrease in the number of people without quality health insurance.  The silver lining in this failure will be that the program will likely cost less than projected due to fewer number of people receiving subsidies, although this reduction will be partly offset by higher-than-projected subsidies to the insurance industry. Expect significant pressure to grow among supporters of the Affordable Care Act to use these net savings to increase the subsidies available to people buying coverage through the Exchanges and to lure insurers in the problem states back into the Exchanges.

1. The number of people without private health insurance may actually grow

This is so because, if 2 million obtain insurance through the Exchanges but more people (3.5 million is a prevailing estimate from sources ranging from Forbes to Jonathan Gruber) lose their current individual health insurance, that’s a net decrease in the number of insured.  And if we add in the loss of 100,000 or so people from the Pre-Existing Condition Insurance Plan that likewise is terminated or those who heretofore were in various state high risk pools, there is a serious risk that the Affordable Care Act will have decreased the number with private health insurance.

In fairness, I have not taken Medicaid expansion into account. Some may see it as unfair to count just the number of people with private health insurance rather than the number with access to health care through private insurance or public schemes such as Medicaid. And, indeed, in those states in which Medicaid has been expanded — one can’t blame President Obama too much if other states choose not to participate — enrollment has outpaced enrollment in private plans at about a 4-to-1 ratio. This suggests, by the way, that people are willing to use a web site, even some clunky ones, to sign up for health care if they think the price is right.

The rejoinder to the argument that we should consider Medicaid, however, is that an awful lot of political energy and an awful lot of monetary investment has been predicated on healthcare reform benefiting more than just the poor but the middle class too. If it turns out the middle class has, net, been hurt by the 2014 features of Affordable Care Act or has paid a large investment for the 2014 features of a law that, net, does provide little marginal benefit, it’s fair to criticize the 2014 features of the Act for their architectural shortcomings. And, yes, I know all about staying on your parents’ policy until you are 26 and limitations on rescissions, but none of those pre-2014 “achievements” should count in assessing the 2014 record.

2. The number of people with quality health insurance may stay about the same

Yes, there will be people who formerly had no health insurance or who had rotten health insurance who, thanks to the 2014 aspects of the ACA, now have health insurance that covers more.  There are many news accounts from pro-ACA forces providing evidence of this. Here’s one (although all the “success stories” are likely to have high medical claims); here’s another (notice again that the successes are likely to have high medical claims).

But it may well be that for every such success story apparently to be catalogued by paid grants from the government, there is another who had health insurance tailored to their needs (such as policies for the 50 and over set that did not cover maternity expenses) who now find themselves priced out of the health insurance market with its Essential Health Benefits requirement (section 1302 of the ACA). Here’s a website inviting people to post their cancellation notices.  Here are some anecdotes relating such problems (although one always have to be very careful about exaggerations in this arena; see here for a discussion of a particular case by Consumer Reports).  Here’s another.

On balance, though, it’s quite believable that, many of the gains due to subsidization may be offset due to government offering only products that have more “features” than many people are willing to pay for.  To analogize, consider a law that prohibited people from owning either a clunker car (defined somehow) or a car without four-wheel drive. The theory behind the law was that clunkers were unsafe and that four-wheel drive is sometimes useful: even if you don’t need it right now, you might need it or have needed it at some point.  Fair enough. But such a law might not actually increase the number of people driving quality cars that fit their needs. Some people just can’t afford a new car.  And others, who could afford a respectable car without four wheel drive and didn’t think they needed it right then (urban Floridians, for example), might simply decide not to get a car rather than use scarce marginal dollars for cars with features they don’t need. While such a result need not occur — it depends on all sorts of factors — my sense is that this is where we are heading with the Affordable Care Act and its fairly demanding and undifferentiated requirements for coverage in policies sold on the Exchanges.

3.  Federal mandate tax payments may be a little bit bigger than expected for 2014

The Congressional Budget Office estimates this spring that the United States Treasury would receive about 2 billion dollars as a result of the individual mandate tax (26 U.S.C. § 5000A). That figure was premised, however, on a belief that 7 million people would enroll in the Exchanges.  If only 2 million people get insurance through the Exchange that’s roughly 5 million fewer than anticipated who will not. There thus could be as many as 5 million more people who will have to pay the individual mandate (26 U.S.C. §5000A) and could lead to something like another $500 million in revenue next year.

Before we spend the money of 5 million more Americans who might have to pay extra in tax, however,  we need to we need to subtract off two categories of people.  (1) We should subtract off those who acquire faux-grandfathered policies created by President Obama’s recent turnabout to let people who like their (potentially cruddy) coverage keep it under some circumstances and not have to pay the individual mandate.  (2) We should subtract off the small number of people who were projected to purchase policies on the Exchange but, because of poverty or otherwise, would not have had to pay the mandate tax had they failed to do so.

So, let’s say on balance that 3 million fewer people than projected pay the tax under 26 U.S.C. 5000A. It’s hard to know exactly what sort of tax revenue would be involved, but it is likely in excess of $285 million per year because each such person would have been responsible for at least a $95 per person penalty. (I know, I know, there are lots of complications because the penalty is difficult to enforce and because you only have to pay half for children, but then there are complications the other way in that $95 is a floor and one may have to pay 1% of household income). Why don’t we use round numbers, though, and say that the government might get about $300 million more in tax revenue for 2014 (although they may not get the money until 2015) due to lower-than-projected enrollments in the Exchanges.

4. Before the federal government subsidizes them, insurers in the Exchange will lose billions

4. Before consideration of various subsidies (a/k/a bailouts) of the insurance industry created by the Affordable Care Act, insurers could lose $2 billion as a result of having gambled that the Exchanges would be successful.  Here’s how I get that figure. No one knows for sure but, if the experience under the PCIP plan is any guide, when about 1/3 of the projected number of people apply to a plan that is not medically underwritten, expenses per person can be more than double that originally expected.  Even if we assume that experience under the PCIP is not fully applicable, given an enrollment 1/3 of that projected, it would shock me if covered claims were not at least 125% of that expected. If so, on balance that means that losses per insured could total roughly $1,000. If we multiply $1,000 per insured by 2 million insureds, we get about $2 billion. If the Exchanges lose money at the same rate as the PCIP, insurer losses could be upwards of  $7 billion. Again, I make no pretense of precision here. I am simply trying to get a sense of the order of magnitude.

5. The federal government will subsidize insurers more than expected but insurers will still lose money

The Affordable Care Act creates several methods heralded as protecting insurers writing in the Exchanges from claims that were greater than they expected.  One such method, Risk Corridors under section 1342 of the ACA, could end up helping insurers in the Exchanges significantly. But, if, as discussed here, enrollment in the Exchanges for 2014 is 2 million persons, the cost of helping the insurance industry in this fashion will be another $500 million for 2014. Risk Corridors, which have recently been aptly analogized to synthetic collateralized debt obligations (CDOs), requires the government to reimburse insurers for up to 80% of any losses they suffer on the Exchanges.  It also imposes what amounts to a special tax (again of up to 80%) on profits that insurers may make on the Exchanges. The system was supposed to be budget neutral but, as I and others have observed, will in fact require the federal government to pay money in the event that insurer losses on the Exchange outweigh insurer gains. The basis for my $500 million computation is set forth extensively in a prior blog entry. It will only be more if, as discussed in another prior blog entry, the Obama administration modifies Risk Corridors to indemnify insurers for additional losses they suffer as a result of President Obama’s decision to let those with recently cancelled medically underwritten health insurance policies stay out of the Exchanges.

If claims are, as I have suggested 25% higher as a result of enrollment of 2 million, insurers will lose, after Risk Corridors are taken into account, about 9% on their policies. It would thus not surprise me to see insurers put in for at least a 9 or 10% increase on their policies for 2015 simply as a result of enrollment in the pools being smaller than expected.

The relatively modest 9% figure masks a far more significant problem, however.  It is just a national average. Consider states such as Texas in which only 2,991 out of the 774,662 projected have enrolled thus far.  If, say, Texas ends up enrolling “only” increasing its enrollment by a factor of 16 and gets to 50,000 enrollees, I would not be surprised to see claims be double of what was projected.  Even with Risk Corridors, insurers could still lose about 24% on their policies. A compensating 24% gross premium increase, even if experienced only by that portion of the insurance market paying gross premiums, could well be enough to set off an adverse selection death spiral.

Footnote: For reasons I have addressed in an earlier blog entry, one of those methods, transitional reinsurance under section 1341 of the ACA is best thought of as a premium subsidy that induces insurers to write in the Exchanges. Because the government’s payment obligations are capped, however, the provision is unlikely to help them significantly if the cost per insured ends up being particularly high throughout the nation.

6. The federal government might save $19 billion in premium subsidies

The Congressional Budget Office assumed that premium subsidies would be $26 billion in 2014, representing a payment of about $3,700 per projected enrollee.  If the distribution of policies purchased and the income levels of purchasers are as projected, but only 2 million people apply, that would reduce subsidy payments down to $7.5 billion.  And if the policies sold in 2014 cost a little less than projected, that might further reduce subsidy payments.  I think it would be fair, then, to estimate that low enrollment could save the federal government something like $19 billion in premium subsidies in 2014. This savings coupled with heightened tax revenue under 26 U.S.C. §5000A — could we round it to $20 billion — would be more than enough to cover insurer losses resulting from the pool being smaller and less healthy than projected.

The Bottom Line

I suspect my conclusion will make absolutist ideologues on the left and right equally uncomfortable.  What I am wondering is if the Affordable Care Act might not die in 2015 with a giant imploding bang but rather limp on with a whimper. On balance, what we may well see if only 2 million enroll in Exchanges pursuant to the Affordable Care Act is a system that fails to function in some states and remains fragile and expensive elsewhere. On the one hand, it will be an expensive system because of the enormous overhead incurred in creating a highly regulated industry that provides assistance to a relatively small number of people. On the other hand, precisely because it will be helping far fewer people than projected, it might well cost significantly less  than anticipated. I would expect this departure from what was projected to lead to two sorts of pressures:

(1) There will be a claim from ACA supporters that we can use the savings to increase subsidies or the domain of the subsidies beyond the 400% of Federal Poverty Line cutoff  and thereby reduce the adverse selection problem that will already be manifesting itself.

(2) There will be a claim from ACA detractors that all of this confirms that, apart from ideological considerations, the bill is an expensive turkey and that, if  the only way to save it is to impose more and more regulation and spend more and more money, it ought simply to be repealed.

Complicating factors

Rules

There are many factors that could result in the estimates provided in this entry being quite wrong.  I do not want to fall into the same trap as others who have ventured into this field and claim that there are not very large error bars around all of these numbers.  And I do not believe the system is necessarily linear. It may be that small changes have cascading effects. Here are several reasons my estimates might be wrong.

1. The rules change in 2015. There are at least three significant rule changes in 2015.

a. The tax under 26 U.S.C. 5000A for not having government-approved health insurance increases significantly, going from the greater of $95 per person or 1% of household income to the greater $295 per person or 2% of household income. Insurers may therefore assume that enrollment will be greater in 2015 than in 2014.  Some people will be pushed over the edge by the higher tax rate into purchasing health insurance. If so, insurers may feel less pressure to increase prices because they believe their experience in 2014 will not be repeated in 2015.

b. The employer mandate will presumably not be delayed again by executive order which may have two offsetting events: employers reducing the number of full time employees thereby adding more to the Exchanges or employers maintaining health insurance thereby reducing the potential pool for the Exchanges.

c. As discussed in an earlier blog entry, there will be a decline in transitional reinsurance now provided free to insurers in the Exchange which, in and of itself, will put significant pressure on premiums

Realities

Finally, this is a field where events just frequently overtake predictions.  All of these predictions go out the window, for example:

a. if there is a major security breach in the government computer systems and people’s personal information is disclosed;

b. healthcare.gov continues to seriously malfunction during the critical pre-December 23 sign up period

c. if the yet-to-be-built payment system for insurers does not function and people become dissatisfied as a result;

d. if people find, as some are projecting (here and here), that the set of medical providers available in the Exchange policies is drastically reduced over what they expected; and

e. there is a major sea change in legislative power in Washington.

f. other

 

 

 

 

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