The Lone Economist Does Obamacare

In a previous post I said that Obamacare’s long-term chances of survival are poor. And that assumes that enforcement of the individual mandate is eventually reinstated.

So why am I so pessimistic with regards to Obamacare? It’s popular and it’s responsible for a sizable decline in the number of people without health insurance.

Well, I’m not called the Country Contrarian for nothing. My contrariness is a product of my odd personality and mixture of backgrounds. As I stated in my first blog post, unlike most economists, I have had a hard time committing to a specialty. Before entering graduate school, I was a COBOL programmer and before that an accountant. Graduate economic students usually choose two fields, I chose four: monetary economics, industrial organization, public finance and econometrics. Monetary is a macroeconomics field and industrial organization is a microeconomics field. Public finance is a combination of the two and econometrics is all about statistical models.

I have taught my fair share of money and banking courses and even published a peer-reviewed article in the Journal of Money, Credit and Banking. But for the last twenty years I have devoted most of my research to health economics. Most health economists use a mixture of biostatistics and epidemiology to estimate incremental cost-effectiveness ratios. They know very little about monetary systems and macroeconomics in general.

“What does Obamacare have to do with monetary economics?” you might ask. Well, let me explain. The establishment of Obamacare is the latest episode in the long-running struggle to fix adverse selection in the health insurance market. This problem is often described in terms of fairness or rather the lack thereof, i.e. the inability of the chronically sick and elderly to obtain affordable health insurance. But in market terminology, it is the inability of health insurance markets to maintain stable equilibria.

Despite the obvious need to solve this instability problem, government intervention in the health insurance market is very controversial because it has a big impact on the distribution of wealth. Consequently, it divides our political parties with Democrats being “for” and Republicans being “against”. This health insurance dialectic has dragged on for decades and has yet to reach its synthesis.

Something quite similar to this has happened before in our nation’s history. Like insurance companies, banks are also financial intermediaries with an instability problem. Banks collect money from depositors and then lend some of those funds to borrowers. This creates the illusion that the depositors and borrowers possess more wealth than physically exists. As long as this illusion is maintained the amount of bank deposits continue to grow in a positive feedback loop.

Yet inevitably the illusion fails. A shock to the financial system, like a failed business venture, causes a few depositors to stop believing the bank has the funds to match their deposits. The sudden rush of withdrawals quickly becomes a self-fulfilling prophecy and the banking system mirage evaporates in a negative feedback loop.

Starting in the 17th century, central banks were established in Europe to solve this instability problem. By acting as both regulator (to prevent the rapid growth of the money supply and inflation, i.e. moral hazard) and lender of last resort (to prevent banking panics and deflation), central banks, such as the Bank of England, brought stability to an otherwise unstable system.

Alexander Hamilton, the first secretary of the treasury, established our first official central bank, the Bank of the United States, in 1791. But unlike the monarchies of Europe, the establishment of a central bank in a popular democracy like the U.S. proved to be very controversial. Like today’s health insurance debate, the establishment of a central bank had a huge impact on the distribution of wealth. The political parties of that time diverged on this issue with Hamilton’s Federalists being “for” and Thomas Jefferson’s Democratic-Republicans being “against”.

This political conflagration lasted for nearly half a century, only ending in 1836 when President Andrew Jackson closed the Second Bank of the United States. Without a functioning central bank, the U.S. experienced seven banking panics and their resulting economic depressions prior to the establishment of the Federal Reserve Bank in 1913. 

A central bank in theory only, the Fed’s very existence was controversial and the result of many political compromises. To limit its power, the Fed was composed of 12 separate regional banks with no clear central command structure. This lack of cohesiveness proved disastrous when the New York Stock Exchange crashed in 1929 resulting in the banking panics of the 1930’s and the Great Depression. By only appearing to be a lender of last resort that would come to the rescue to prevent banking panics, while failing to prevent the explosive growth of the money supply of the 1920’s, the Fed greatly magnified and prolonged the very economic disaster it was designed to prevent.

In the aftermath of this debacle it became clear that a decentralized central bank made no sense. How could we have been so stupid? Why didn’t we see this coming?

The Fed was repurposed and many laws were passed to prevent this from happening again. But guess what? It did happen again in 2008 with the collapse of the housing market and the Great Recession. Those safeguards enacted in the 1930’s had eroded to the point that the largest banks in the country were “too big to fail” and required massive bailouts to be kept afloat. This was a result of moral hazard on an enormous scale that the Fed had ignored for many years.

New safeguards were erected and many a central banker vowed to never let this happen again. But there are already signs that the new safeguards are being eroded. And so it goes, until the next time.

“What does Obamacare have to do with monetary economics?” you might ask again, this time with a wisp of annoyance. Well I see several parallels between the multi-decade health insurance debate and the multi-century central bank debate. Both are controversial government interventions that split the political divide and are designed to stabilize a financial market. Both are products of political compromise and wishful thinking. And both have the potential to do more harm than good.

In the case of Obamacare, the compromise I allude to is the infamous individual mandate, i.e. the requirement that everybody, even young healthy people, purchase health insurance. This is a necessary evil that would eliminate the scourge of premium-financed health insurance, adverse selection.

The only trouble is, we don’t have an individual mandate. A mandate is a requirement, not an option. What we have (or rather had) is a slap-on-the wrist that millions of people ignored even when it was being enforced. Without a real mandate, there will not be a circuit breaker to stop the negative feedback loop of adverse selection.

This is how I see things playing out.  A recession starts and the unemployment rate rises. The newly unemployed with no health problems stop paying their health insurance premiums while the ones with expensive health problems find a way to keep paying theirs. The insurance companies see a big drop in revenues without a proportional drop in costs. They increase their premium rates to avoid insolvency. Even more people with low healthcare bills stop paying their premiums. The cycle continues until the exchange market propped up by Obamacare ceases to exist.

It is always possible that a massive bailout could save Obamacare, but that would just be throwing good money after bad. The fact is, the American political system does not have the stomach to enforce an effective mandate. Pretending that it does was always wishful thinking.

If the goal of Obamacare was to provide insurance to the uninsured, then it was only half successful at twice the cost. Its biggest beneficiaries by far are healthcare providers not consumers. That’s not a good deal for taxpayers and the uninsured and portraying it as such is just one more example of wishful thinking.

This will end badly.

Questions about The Lone Economist

I’ve gotten some questions about The Lone Economist that I need to address. A number of people want to know if there are any analogs for the other characters from “The Lone Ranger”, specifically Tonto. My answer is “no”. I am the Ponied Pontificator, the Country Contrarian, the one and only (quite literally by definition) Lone Economist! What part of “lone” escapes your comprehension?

Actually, I asked around for an assistant (a little data entry, maybe screen some emails), but it’s hard to find someone who will work for free. Besides, Tonto wasn’t much of a character to begin with. For those of you who know little about “The Lone Ranger”, it’s first incarnation was as a radio show. If the Lone Ranger had literally been alone there would have been no one for him to talk to, no dialogue for the audience to listen to that explained why he was doing whatever it was he was doing. Without Tonto, he would have had to talk to himself out loud. I guess then he could have been called the Loon Ranger.

My, the lengths I’ll go to set up one lame pun. If that was a horse, I’d have to shoot it.

Anyway, there is no Tonto analog and there likely never will be. The best I can do is provide analogs for the two horses on the show, Silver and Scout.

I’m actually afraid of horses (those things bite!), so we’ll have to settle for an orange and white house cat with a weight problem. Here’s a picture of him.

His name is “Silfur”. Get it? “Silfur” instead of “Silver”.

And here’s his sidekick, Scat.

Ain’t she cute?

And the other question I get a lot is “Does the Lone Economist make any money?” My answer to that is, the Lone Economist fights for truth, justice and the American way! Or was that Superman? I might be mixing my 1950’s TV show metaphors there, but you get the idea. The Lone Economist does not work for money.

His corporate sellout alter ego, however, works under cash retainer. No exceptions.

Let Me Be More Explicit

Apparently my first blog post, the mask icon and the name, “The Lone Economist” didn’t make it clear what this blog is about. So, let me be more explicit.

“The Lone Economist” is an allusion to the 1950’s TV show, “The Lone Ranger”. For those of you too young to remember, the Lone Ranger, was a masked vigilante who rode a magnificent white horse named “Silver” while dispensing justice to the rousing soundtrack of the William Tell Overture.

When I was a kid, I loved watching this show even though it never made any sense.  There may have been some origin episode that explained everything, but if there was, I never saw it. Here was a guy who had no visible means of support and apparently lived outdoors, but managed somehow to always wear a clean, pressed shirt. How he could afford to feed his horse, much less himself, was a mystery.

So why did I choose to associate my blog with the Lone Ranger? Well for starters, I’ve always wanted a job where I ride up on my big white horse and tell a bunch of people what their problem is. And I get to refer to myself in the third person!

And then there’s the masked vigilante thing. You see, unlike the Lone Ranger, the Lone Economist has a day job. In keeping with the western theme, I’m a hired gun. Moneyed interests pay me to do their bidding. Nowadays we’re called consultants and expert witnesses.

Although I’m paid to give my honest opinion, that’s seldom what my clients really want. They want my useful opinion and that’s what I have learned to give them. I have never lied, mind you, in any professional capacity as a consultant or as an expert witness, but I don’t volunteer that I’m not being asked the right questions either.

I‘ve found that complete honesty and candor can be a liability at times. For example, several years ago I was hired to testify for a hospital that was being sued by a doctor for wrongful termination. The doctor was a brain surgeon who alternated with another brain surgeon in the hospital’s surgical on-call rotation. That meant that every other week this doctor was the first surgeon that would be called if there was a patient who required emergency brain surgery. These are mostly head trauma cases and, not surprisingly, the mortality rate for these patients is pretty high. So when a patient dies, one does not think to immediately call a medical malpractice attorney.

Needless to say, a place in a hospital’s on-call rotation is very lucrative and not one most doctors will give up easily. When I asked why this doctor’s privileges had been revoked, the hospital’s lawyer just said he had a reputation for being “rough”. My job was to show that the hospital was well within its rights to terminate this individual.

Most states collect a lot of data from their hospitals and make them public. This hospital’s state was no exception. With those data in hand I set out to test the lawyer’s implicit hypothesis concerning Dr. Rough.

Please note that “Dr. Rough” is not his real name. Like “Dragnet” (another 1950’s TV show reference!), the names have been changed to protect the innocent, specifically me. I don’t want to get sued. If there is an actual Dr. Rough somewhere, that is not the person I am referring to.

The first step was to calculate the doctor’s surgical mortality rate, which is easy. It’s the number of surgical patients who die divided by the number of surgeries. Every surgeon knows exactly what his or her mortality rate is. But a high rate is not necessarily an indication of a bad surgeon.

Surgeons with high mortality rates invariably say that their patients are sicker than other surgeons’ patients. “All the really bad cases are sent to me because everybody knows that I am the best” is a typical surgeon’s lament. From my experience, this statement rings true in two different ways. It is true that many of the best surgeons in the medical profession have high mortality rates because they treat the sickest patients. And it is also true that surgeons are an extremely conceited lot.

Here’s a riddle for you: how many surgeons does it take to screw in a light bulb? Answer: None, surgeons are too good to screw in light bulbs.

So why do I bring this up, you might ask? Well, besides an opportunity to insult surgeons, it highlights a common problem in the use of performance statistics for healthcare providers.

In statistical terms, this problem is called omitted-variables bias or confounding. All the differences in the mortality rates are being attributed to the identities of the surgeons and none are being attributed to the differences between their patients. Some patients are young and vibrant. Others are old and fragile.

One obvious solution is to add more variables to the statistical model. If all the relevant variables are included, then none are omitted. But human health is too complex to completely capture in one or even a dozen variables. So, no matter how many variables we add to the model we can never be sure we have eliminated all the confounding.

The only surefire way to eliminate confounding is to randomize, i.e. randomly assign patients to doctors. That is the basis for all randomized clinical trials. It’s how we differentiate causation from mere correlation.

The more I thought about it though, the more I realized that we didn’t have an omitted-variables bias in this instance. It would have been impossible for the hospital to take in only severe head trauma cases in odd numbered weeks and only minor cases in the even numbered ones. By including Dr. Rough and the other brain surgeon in its on-call rotation, the hospital had unintentionally conducted a randomized clinical trial.

And what was Dr. Rough’s mortality rate? 24% versus the other brain surgeon’s rate of 8%. That amounted to an odds ratio of 3.0 and was well past the threshold for statistical significance. This covered several years and dozens of deaths. For every 30 of Dr. Rough’s patients who died, 20 would not have if the other surgeon had treated them. It would have been criminal if the hospital hadn’t revoked Dr. Rough’s privileges.

So, I presented my findings to the hospital’s lawyer expecting high fives and pats on the back, but instead I got “Are you crazy?!! I can’t have you testify under oath about this! I had no idea it was this bad! We’ll get sued into oblivion!” I’m paraphrasing and cleaning this up a bit.

Anyway, I was told to stop billing time to the case immediately and the hospital paid Dr. Rough a million dollars to go away quietly. I had found scientific evidence that Dr. Rough was in effect a serial killer. The only difference between his rampages and those of Jeffrey Dahmer and Ted Bundy was that his were unintentional, perfectly legal and performed in an operating room. I got the old heave-ho and he got a million bucks. The absurdity of the situation left me stupefied.

You might wonder why I didn’t go to the authorities. Well, which authorities? I couldn’t go to the police. There was no criminality here. Dr. Rough was just a bad doctor. There are a lot of bad doctors out there. His was just another face in the crowd.

What about the state medical board? Couldn’t they take his license away? Not with the evidence I had. Although scientific, it was still only a point estimate. His incompetence might have actually killed only 18 or maybe 23. I just didn’t know for sure. And I couldn’t say exactly which 20 of the 30 patients he had killed either. To take someone’s license away, the accusation and the evidence need to be specific.

More to the point, I had a professional and contractual duty to my client, the hospital, not to put them in legal jeopardy. Malpractice attorneys sue for money and Dr. Rough didn’t have much. The hospital, on the other hand, had very deep pockets. It would have suffered the full brunt of all the legal claims.

Hospitals can’t win. They get sued and lose a lot of money when they do the wrong thing. And they get sued and lose a lot of money when they do the right thing.

But back to the main topic, you see my dilemma, right? I can’t talk about this stuff openly. I’ve seen things. I know things. Things that would test one’s faith in the basic goodness of lawyers.

Sorry, I couldn’t resist. No one in their right mind has faith in the basic goodness of lawyers. Wow, I’ve insulted two professions in one post. I’ve exceeded my quota!

And then there are my government agency clients. I don’t know how they would react to the news that I think Obamacare is doomed and the indiscriminate expansion of Medicare would be a disaster.

History is replete with heroes who bravely spoke truth to power in the full light of day. The Lone Economist will not be one of them. Remember John the Baptist? He spoke truth to power and the power spoke back. The Lone Economist does not want his head served on a platter.

So, like my childhood idol, I’ll conduct my lonely crusade anonymously from behind a mask.

Hiyo Silver!

The U.S. Healthcare System Might be Better than You Think (Part II)

Last time we outlined the challenges posed by the single-payer model of health insurance adopted by Canada, the UK and several other countries. The gist of that posting was that single-payer systems rely entirely on tax revenues to compensate providers for the costs they incur and therefore the aggregate cost of healthcare is under-reported in these countries.

The U.S. has not adopted the single-payer model. We instead use a complex combination of taxes, premiums, and unfunded mandates. By exploiting the market power of providers, we shift a large share of the costs of healthcare onto private insurance customers, thus reducing the burden on taxpayers, the sick and the elderly.

Many find the U.S. healthcare system wanting when compared to single-payer systems and have proposed our own single-payer system, i.e. Medicare For All. However, the U.S. system is so complex that facile comparisons with the relatively simple single-payer systems of other countries can be misleading. As we did with single-payer systems in the previous posting, we need to examine how well (or poorly) the U.S. system handles moral hazard, adverse selection, cost redistribution and quality. We kickoff that discussion with today’s topic.

The Market Power of U.S. Healthcare Providers

Market power is the ability a supplier possesses to choose the price it charges to buyers. Without it, the supplier can only charge the price collectively dictated by its buyers. Typically, the more market power a supplier has, the higher price it will charge its customers.

The market power of healthcare providers is plain to see. Most hospitals enjoy a local monopoly in the geographic area surrounding their location, especially for emergency services. Few people suffering a heart-attack will haggle over the price of emergency care. They generally go to the nearest emergency department regardless of price and quality. The fact that many states restrict the services offered by hospitals by requiring them to obtain “certificates of need” only magnifies the market power of the ones who manage to obtain them. And when you consider that physicians choose the hospitals where they treat their patients, rather than the patients and insurers who actually pay the hospital bills, it is easy to see how hospitals have so much market power. Pharmaceutical companies derive their market power from patent protections. Physicians tend to have less market power than hospitals and pharmaceutical companies, but they have organized into physician groups to counteract this disadvantage.

The more market power a supplier has over its customers, the more it can markup its price above the costs it incurs. So, do healthcare providers charge large markups to patients? The answer is a resounding “yes”, depending on who is paying of course. For example, Figure 2. shows the percentage markup charged by short-term hospitals by type of ownership in 2017. On average the percentage price markup for all hospitals was 360%. Not surprisingly, for-profit hospitals markup their prices the most (656% mean, 517% median), but even private not-for-profit and government-owned hospitals have very high markup percentages.

Data source: Medicare Cost Reports, 2017. The number of short-term hospitals for each hospital type are shown in parentheses.

To put these figures in context, grocery stores typically charge markups of 15% or less and clothing stores charge markups of 55% to 62%. So, markups of several hundred percent are astronomical. The fact that the mean markup percentages are greater than the median percentages indicates that the distribution is skewed to the right. In other words, large hospitals tend to charge higher markups than small hospitals. Which is further evidence that market power is the cause of these markup percentages.

One cautionary note, these are accounting figures and so the “costs” reported do not account for all economic costs incurred. Unlike not-for-profit and government-owned hospitals, for-profit hospitals must pay for all the capital they use to care for patients out of net revenues. Despite the ubiquitous use of the word “capital” in business and finance, its exact meaning in the context of economics is often poorly understood. In general, the under-measured cost of capital is the minimum amount of net revenues (as a percentage of capital invested) necessary to keep investors from transferring their capital to some other enterprise. Its value varies over time and depends on the reliability of expected future net revenues but will normally be in the 5%-15% range. Consequently, the under-measured cost of capital alone does not explain the difference in price markups between for-profit and not-for-profit hospitals.

The U.S. Healthcare System Might be Better than You Think

In our quest to design an optimal healthcare insurance system, we need to assess the relative strengths and weaknesses of our current system to that of other countries. You might have noticed that the U.S. healthcare system doesn’t get a lot of respect in many quarters nowadays. In the universe of developed countries, the percentage of people in the U.S. without health insurance is an outlier.  Many politicians point to Canada and the UK and wonder “why not us”?  

The fact is though that few politicians have the patience to really understand the U.S. healthcare system. It’s much more complex than those in Canada and Europe. It certainly has its relative weaknesses, but it also has its relative strengths and those are poorly understood and rarely mentioned in the current policy debates. Many of these strengths require the standard tools and theories of economists to fully appreciate. So, here is the Lone Economist to the rescue!

The Problems with Health Insurance

Every national healthcare system must attract resources (e.g. doctors, nurses, hospital buildings, etc.) to the production of healthcare (i.e. supply) and limit the quantity and quality of healthcare consumed by its residents (i.e. demand) in some way. Otherwise there would not be enough doctors, hospitals, etc. to treat all the people who want to consume healthcare in a given time period. In a pure market system, this is achieved via the price mechanism. The costs incurred by healthcare providers are equal to the prices charged to healthcare consumers, i.e. patients. If a patient doesn’t have enough money to pay the price of healthcare, he doesn’t receive any. Whether or not you believe it to be fair, the market system automatically equalizes the quantities of healthcare supplied and demanded.

Since an individual’s need for healthcare can be very expensive and highly unpredictable, health insurance is used to spread the costs onto a broad swath of the population; even the lucky ones who have no need for healthcare in a given year. Insurance, however, presents a new set of problems. For one, it divorces the cost of care from the price borne by the patient, thus removing the automatic supply and demand equilibrium feature of the price mechanism. This problem is called moral hazard. For another, the premiums charged by insurers and the informational advantage the insured have over the insurers creates incentives that result in some people with expensive health problems not being able to obtain health insurance, i.e. the uninsured. This second problem is called adverse selection.

The Single-Payer Model

To prevent the moral hazard and adverse selection posed by health insurance, many developed countries, like the UK and Canada, have adopted the single-payer model. Simply put, the single-payer model cures moral hazard by placing strict limits on the quantity and quality of healthcare provided. These include long wait times and lack of coverage for certain procedures and medications. Adverse selection, on the other hand, is eliminated by replacing insurance premiums with tax revenues. This redistributes the cost of healthcare away from patients — a population that is disproportionately old and sick – and onto taxpayers. For many people, this redistribution of costs solves the fairness problem of the market system.

You might have noticed by now that with every government solution to an economic problem, another problem tends to arise. The single-payer model is no exception to this rule. The limits on the quantity and quality of healthcare meant to solve moral hazard can be arbitrary and even harmful. Any collection of preset rules and prohibitions cannot anticipate all the possible variations of needs and costs encountered in the healthcare market. An expensive treatment might be a waste of precious resources for some patients, but not for others.

Taxation too has its problems. It is a well-known fact that a dollar of insurance premium revenue does not equal a dollar of tax revenue in its cost to the economy. Every tax creates something called deadweight loss. This is the decreased employment caused by the payroll tax, the lost investment caused by the corporate income tax, and the foregone transactions caused by the sales tax. It is an unavoidable, but necessary extra cost of paying for government services through taxation.

Speaking in very broad terms, there are only two sources of income from which we extract tax revenues: labor and capital.  For example, for low and middle-income households the personal income tax is a tax on labor, but for wealthy households it is mostly a tax on capital. The payroll tax is a tax on labor and the corporate income tax is a tax on capital. 

It is perhaps an unfortunate, but inescapable fact that taxes on capital create much greater deadweight losses than taxes on labor. That is why the U.S. tax system tends to shy away from taxes on capital and relies so heavily on taxes on labor. I say ‘unfortunate’ because for many people a good tax is a fair tax and they consider taxes on capital (e.g. the capital gains tax, the corporate income tax, Elizabeth Warren’s wealth tax proposal) to be particularly fair. Why this is inescapable is a subject for a future posting.

So, the Achilles’ heels of single-payer systems are the deadweight losses caused by the taxes raised to pay for all the healthcare costs incurred by providers. The need to minimize these deadweight losses explains some of the more draconian limits placed on the provision of healthcare to control moral hazard and why the U.S. spends so much more per capita on healthcare than single-payer countries. For example, when dialysis was first made available, the U.K.’s National Health Service did not cover the cost of dialysis for anyone over the age of 50. This was a virtual death sentence for anyone over that age with End Stage Renal Disease (ESRD) except for wealthy individuals who could pay for private healthcare out-of-pocket. In contrast, the U.S. made everyone with ESRD eligible for Medicare regardless of age.

How could the U.S. afford to do that while the U.K.’s single-payer system could not? That is the subject of my next posting.

How Many People Are Truly Uninsured?

In a previous posting I established the need to define a theoretical optimal health insurance system with which to compare to the several legislative proposals now circulating. This posting identifies a source of data, the types of healthcare services covered, how much is spent on them and how many people are truly uninsured.

To estimate the costs of an optimal system, we need data and the latest publicly available data on health expenditures and insurance comes from the 2016 Medical Expenditures Panel Survey (MEPS) produced by the Agency for Healthcare Research and Quality (AHRQ). Using this survey, we can estimate the cost of providing health insurance to those who were uninsured in 2016 and then to those who would have been uninsured in 2016 had the subsidized health insurance exchange market and its individual mandate (aka Obamacare) not existed.

What Kinds of Healthcare Should Be Covered by Insurance?
There are several different kinds of healthcare. There are traditional services such as surgery and office visits and non-traditional services such as acupuncture and hypnosis. Some have proven to be highly effective (or debunked) by randomized clinical trials. Most have never even been tested and continue to be administered simply out of tradition. Should all of them be covered by health insurance?

Establishing an objective standard for health insurance coverage is beyond the scope and capacity of this study. So, I’ll simply include the six categories that are normally covered by health insurance and tracked by MEPS: inpatient stays (including physician fees), office visits, prescription drugs, outpatient visits, home health, and emergency department visits. This excludes other healthcare services like chiropractic and optometry because those kinds of services are not generally covered by health insurance, but they are tracked by MEPS. In any event, the six covered categories comprise 89.9% of the $1.6 trillion spent on healthcare in 2016.

The big three are inpatient stays, office visits and prescription drugs with each accounting for nearly a fourth of total spending. In spite of what you might have read, we spend about the same on inpatient stays as we do on office visits. This happens because although the average hospital stay is very expensive, only a small fraction of the population experiences a hospital stay in a given year. So, controlling the cost of hospitalization is not significantly more important than controlling other types of healthcare.

How Many People Are Truly Uninsured?
Identifying the uninsured population via a public survey might sound like a straightforward task — simply ask the respondents if they have health insurance? –, but the truth depends on what it means to be uninsured, that is, on your own with no other source of payment. According to the 2016 MEPS, an estimated 24.6 million U.S. residents (7.6%) claimed to have no health insurance. These are the nominally uninsured. However, only 13.3 million of these people (a little more than half) had any healthcare expenditures that year and most of their healthcare expenditures were paid by somebody else, like the Veterans Health Administration (VHA) or Worker’s Compensation (WC). To be precise, 82% of the $35 billion in insurable healthcare expenses incurred by the nominally uninsured were paid by entities other than the patients themselves.

So, were all of these 24.6 million nominally uninsured people really uninsured in the true sense of the word? While organizations like the VHA and WC may not provide insurance to individuals and families, they are de facto insurance providers and should not be ignored when estimating the cost of providing health insurance to the nominally uninsured.

Prospectively, that is, at the start of the covered time period, we can only guess how much healthcare expenses will be incurred by a group of people. But since this is a retrospective analysis, we need only consider nominally uninsured people who had healthcare expenditures in 2016 and received no outside help in paying their healthcare bills, in other words, the truly uninsured. This reduces the number of uninsured from 24.6 million down to only 4.0 million people. This core of truly uninsured people incurred healthcare expenses of $5.5 billion of which they were able to pay only $1.4 billion (25%).

The rest of these incurred expenses were not collected by the hospitals, doctors and other providers of healthcare. This effectively amounts to a 75% price discount payed by the uninsured (as a whole, but with a great deal of variation by patient). That percentage discount might sound large, but it should be noted that Medicare and private insurers also pay large discounts on average and the amount of expenses incurred (i.e. billed charges) are much greater than the actual costs incurred by hospitals, etc. for providing care.

So, only 13.3 million of the 24.6 million nominally uninsured actually incurred healthcare expenses in 2016. The remaining 11.3 million had no healthcare expenditures during this time period. How many of them were truly uninsured? In other words, how many would have had to pay the full cost of their healthcare if they had had any? It is impossible to know for sure, but it is safe to say that it is likely that many of them could have counted on the VHA and other payers if they had incurred healthcare costs. The most we can say is that the truly uninsured ranged from 15.3 million to 4.0 million (4.7% to 1.2%) with the exact percentage likely being somewhere near the middle of that range. This is a far cry from the 7.6% who stated they were uninsured in the survey and the $5.5 billion in incurred expenses are a far cry from the $35 billion incurred by everyone who self-identifies as being uninsured.

An Optimal Health Insurance System

It is now nine years after the passage of the Affordable Care Act (ACA) and there are still 28 million Americans without any form of health insurance. Despite its current strong financial health, the long-term continuation of the ACA exchange market is in doubt. The individual mandate is no longer being enforced by the Trump administration and there continue to be challenges to the ACA in federal courts.

There are several legislative proposals to either create a public health insurance option or do away with private insurance altogether (aka Medicare-For-All (MFA)). In a series of posts, I will analyze these various proposals by estimating their costs to society as well as their effects on healthcare access and quality. My aim is to be as thorough and balanced as I can.

Before diving into specific proposals, I want to first explore something I call “optimal” public health insurance. Any public provision of health insurance will necessarily call for costs borne by taxpayers and consumers. If the main objective is to provide health insurance to those who do not already have it, then an interesting starting place for that discussion would be to see how that can be done at a minimum cost to society. Only once we have established how an optimal system is designed and how much it costs can we intelligently assess the relative costs and benefits of specific legislative proposals.

Using the concept of constrained optimization, we should first identify the objective to be optimized (i.e. minimum costs) and then the constraint (i.e. everyone has access to a minimally-acceptable level of healthcare). Without this constraint the solution might seem simple – leave the provision of health insurance entirely to private insurers. The direct costs to taxpayers would be zero in that case, similar to what the U.S. had prior to the start of Medicare and Medicaid in the 1960’s. But notice that I did not restrict costs only to those borne by taxpayers. The costs of public health insurance can be borne by many different entities and are not restricted to the amount of money paid in taxes or premiums.

There are three main types of costs associated with the public provision of health insurance:  taxation, adverse selection, and moral hazard. Taxation is usually the focus of the current policy debate: the Public Option vs. MFA. Yet the other two types of costs are even more germane to that debate. These two costs are inextricably linked and explain why health insurance has been such an intractable public policy problem for so long.

What would an optimal public health insurance system look like? The details are for future posts, but here are a few broad strokes. First, it would completely achieve the main objective of providing insurance to all those who don’t already have it. It is worth noting that although the number of uninsured has declined significantly, the ACA has failed to completely achieve this objective. So, an optimal system would look a lot different than our current taxpayer-subsidized exchange markets.

To minimize the cost to taxpayers, it would rely on our current public insurance infrastructure so that the cost of creating a new one is avoided. This is something that an optimal health insurance system would have in common with MFA. Medicare has well-established payment structures based on data it collects annually from providers.

To avoid adverse selection — the incentive for healthy people not to pay an actuarially fair premium — the optimal system would not charge a premium for coverage. This provision is key because adverse selection is a main reason why so many people lack health insurance. Many of the uninsured are relatively young and healthy individuals who believe the actuarially fair premium for health insurance is too high. In this regard, the optimal system is much closer to MFA than to the ACA.

So far, our optimal plan sounds a lot like MFA: health insurance that is provided at a zero premium to everyone that doesn’t already have it and that relies on the current Medicare system. But here is where the similarities to MFA stop. MFA would replace our current patchwork system of private and public health insurance with a single-payer approach. Although private health insurance would not be banned outright, MFA would leave little room for its continued existence. Taxpayers would bear the full cost of our healthcare system.

Moral hazard, the tendency for people to over-utilize the healthcare system when they bear no costs for using it, would be a significant problem that MFA would likely exacerbate. By subsidizing private health plans that impose out-of-pocket costs to the insured, the ACA does a relatively good job in this regard.

And lastly, a plan that minimized taxation, would be very different from both the ACA and MFA. The ACA mandates that everyone purchase insurance. This form of taxation is necessary with a system that relies on revenues from premiums, but since this mandate is no longer being enforced, the exchange markets will likely fail during our next economic recession. Even when the mandate was being enforced many people chose to pay the penalty rather than purchase health insurance. The penalty is a percentage of taxable income and is therefore not collectible for the unemployed. During the next recession, healthy people who are out of work will tend to stop paying their premiums while people with pre-existing health problems will maintain their coverage. This is a textbook example of adverse selection. Even if it was still being enforced, it is doubtful the mandate was ever large enough or reliable enough to create a stable health insurance exchange market.

The ACA’s taxation, however, pales in comparison to that of the MFA. Without a price mechanism for limiting the demands on healthcare resources, the moral hazard inherent in an MFA plan would result in an enormous increase in taxes or require restrictions on certain procedures, limited allocations of medications and long wait times.

In summary, the optimal system would bear some similarities with MFA (i.e. everyone is insured, uses the Medicare system, and charges no premiums therefore no adverse selection and no individual mandate) and some with the ACA (i.e. allows private insurance and imposes out-of-pocket costs therefore controlling moral hazard). That’s a tall order, but one that I believe is doable. The next posts will describe the optimal public health insurance system in more detail.

My Inability to Specialize Makes Me Special

A long time ago …

A long time ago near the start of my career as an economist, my mentor at that time sat me down to tell me one word. “Specialize” he advised. I outwardly acknowledged his wisdom while secretly knowing that if specialization was necessary for success in our profession, then I was doomed.

Since that conversation I’ve published peer-reviewed articles on a bizarrely diverse set of subjects. I started with an article on how to accurately measure consumer welfare in the face of non-linear prices. I then segued to the effects that unexpected changes in wheat harvests have on net exports in Australia. Next I published evidence that professional baseball players with long-term contracts don’t work as hard as other players. I followed that up with an oft-cited article that proved gamblers do not randomly select lottery numbers even though they would be better off if they did. My seemingly random list of articles also includes subjects such as the effect of physician fee capitation on consumer satisfaction, a test of the arbitrator exchangeability hypothesis using final-offer arbitration data from Major League Baseball, and how to estimate personal consumption using a statistical modelling technique called “instrumental variables”.

The closest I have come to a “specialty” is a series of articles dealing with cancer care, including cervical cancer in the Vietnamese-American population, the incidence of colorectal cancer by bowel section and the effect of distance to provider on the incidence of breast cancer. I’ve also published articles about the effectiveness of an employer-sponsored weight-management program and the rate of moral hazard caused by health insurance.

I should mention that I published these articles and much more while working at four different universities, a state agency, a county government and four different consulting companies. I’ve testified as an expert witness in both state and federal courts of law on things as unrelated as the government’s efforts to eradicate an infectious plant disease, anti-trust behavior in the stretch limousine market and hospital payment rates by Workers Compensation. Twenty-five years after earning my PhD in economics, I went back to school to earn a Masters’ degree in health services and completed my post-doctoral training at a well-known cancer research center.

Someone unfamiliar with the economics profession might be impressed with these accomplishments, but I can assure you that other economists are not. When they see my long array of seemingly random academic pursuits, they invariably wrinkle their noses in bewilderment. That mentor who advised me in my youth to specialize stopped talking to me nearly twenty years ago when he realized I was a lost cause.

I would like to claim that all this was part of some well-reasoned plan, but the truth is that I struggle with a restlessness that I am incapable of controlling. I have learned to embrace my weirdness. Ironically, my inability to specialize makes me special.

Hence the name of my blog: The Lone Economist. I plan to pursue a data-driven analysis of topics about which I am well-versed, such as Medicare-For-All vs. the Public Option, and a new type of baseball statistic.

Of course, given my history, who knows what I might talk about.