Monthly Archives: December 2018

Insuring Health Insurability

22 Saturday Dec 2018

Posted by in Health Insurance

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The latest blow to Obamacare went down just before the holidays when a federal judge in Texas ruled that the individual mandate was unconstitutional. The decision will be appealed, so it will have no immediate impact on the health-care law or insurance markets. But as Eugene Volokh noted, the mandate itself became meaningless from an enforcement perspective after the repeal of the penalty tax for non-coverage in 2017, despite the fact that some individuals might still opt for coverage out of “respect for the law”. What will really matter, when and if the decision is upheld, is the nullification of the complex web of regulations created by Obamacare, officially known as the Affordable Care Act or ACA. Perhaps most important among these is the requirement that buyers in good health and those in poor health must be charged the same price for coverage. That is “community rating” and it is the chief reason for the escalation of insurance premiums under Obamacare.

One Size Misfits All

Community rating means that everyone pays the same premium regardless of health. Those in good health must pay higher than actuarially fair premiums to subsidize the sick or high-risk with premiums that are less than actuarially fair. Two provisions of the ACA were intended to make this work: first, the individual mandate required everyone to remain in the game (and paying the subsidies) rather than going uninsured and paying the “tax” penalty. But the penalty was so light that many preferred it to actually buying insurance. Now, of course, the penalty has been repealed. Second, individuals with incomes below 250% of poverty line receive premium subsidies from the federal government to offset the high cost of coverage. That means low-income buyers do not have to confront the high premiums, which was hoped to keep them in the game.

Community rating caused premiums in the individual insurance market to increase dramatically. This was compounded by the law’s minimum coverage requirements, which are more comprehensive than many consumers would have preferred. Lots of younger, healthier consumers opted out while the sick opted in, or even worse, opted in only when they became sick. This deterioration in the “risk pool” is the so-called insurance “death spiral”. The pool of insureds becomes increasingly risky, premiums escalate, more healthy consumers opt out, and the process repeats. At the root of it is the distortion in the way that risk is priced by community rating.

Tailored Coverage

The coverage and pricing of risk is better left to markets. That means consumers and insurers will reach agreement on policy provisions that are mutually beneficial ex ante. Insurers will offer to cover risks up to the point at which the expected marginal cost of underwriting is equal to value, or the buyer’s willingness to pay. An insurer who offers unattractive policies or charges too much will find its business undercut by competitors. But when risk is priced by government fiat and community rating, this natural form of market information discovery is impossible.

Tax vs. Premium Subsidies

Many in the high-risk population will be unable to afford coverage in the absence of community rating. There are only two general options: they pay what they can for care but otherwise go without insurance coverage, accepting charity care if they are willing; or, taxpayers pay, as under Medicaid. Most lack coverage because they simply cannot afford it, even when they earn too much to qualify for Medicaid.

That situation can be resolved in the long-term (as I’ll describe below), but an overhang of individuals with pre-existing conditions in need of subsidies will persist for a period of years. Under Obamacare, subsidies were paid by charging higher premia to healthy individuals through community rating. Again, that distorted signals about risk and value, creating unhealthy incentives among insurance buyers. The death spiral is the outcome. Subsidies funded by general taxation do not create these price distortions, however, and should be relied upon for assisting the high-risk population, at least those who are determined to qualify.

Health Status Insurance

The overhang of individuals with pre-existing conditions requiring subsidies can never be eliminated entirely—every day there are children born with critical, unanticipated health needs. However, the overhang can shrink drastically over time under certain conditions. A development that is already receiving meaningful attention in the market is the sale of health insurance options, as described by John Cochrane. I have written about this method of protecting future insurability here.

Cochrane raises the subject within the context of new HHS rules allowing insurance companies to offer “temporary” insurance coverage up to a year, but with guaranteed renewability through a total of 36 months of coverage. Unfortunately, if you get sick before the end of the 36th month, you’ll have to give up your policy and pay more elsewhere.  But Cochrane speculates:

“Unless, perhaps, they really are letting insurance companies offer the right to buy health insurance as a separate product, and that can have as long a horizon as you want? If they haven’t done that, I suggest they do so! I don’t think the ACA forbids the selling of options on health insurance of arbitrary duration.”

Cochrane links to this earlier article in which John C. Goodman discusses the ruling allowing the sale of temporary plans:

“The ruling pertains to ‘short-term, limited duration’ health plans. These plans are exempt from Obamacare regulations, including mandated benefits and a prohibition on pricing based on expected health expenses. Although they typically last up to 12 months, the Obama administration restricted them to 3 months and outlawed renewal guarantees that protect people who develop a costly health condition from facing a big premium hike on their next purchase.

The Trump administration has now reversed those decisions, allowing short-term plans to last up to 12 months and allowing guaranteed renewals up to three years. The ruling also allows the sale of a separate plan, call ‘health status insurance,’ that protects people from premium increases due to a change in health condition should they want to buy short-term insurance for another 3 years.”

That is far from permanent insurability, but the concept has nevertheless taken hold. An active market in health status insurance would reduce the pre-existing conditions problem to a bare minimum. The financial risks of deteriorating health would be underwritten in advance. Once stricken with illness, those unlucky individuals would then have coverage at standard rates by virtue of the earlier pooling of the risk of future changes in health status. At standard rates, relatively few high-risk individuals would require subsidies in order to afford coverage .

Will healthy, temporarily insured or uninsured individuals buy these options? Some, but not all, so subsidies will never disappear entirely. Still, the population of uninsured individuals with pre-existing conditions will shrink drastically. In the meantime, a healthy market for health insurance coverage should flourish, reestablishing the authority of the consumer over the kind of health care coverage they wish to purchase and the kinds of financial risks they are willing to bear.

 

 

You’re Welcome: Charitable Gifts Prompt Statist Ire

14 Friday Dec 2018

Posted by in Central Planning, Charity, Uncategorized

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Charitable acts are sometimes motivated by a desire to cultivate a favorable reputation, or even to project intelligence. Perhaps certain charitable acts are motivated by guilt of one kind or another. Tax deduction are nice, too. But sometimes a charitable gift is prompted by no more than a desire to help others less fortunate. It’s likely a combination of motives in many cases, but to gainsay the purity of anyone’s charitable motives is rather unseemly. Yet Gaby Del Valle does just that in Vox, casting a skeptical eye at Jeff Bezos’ efforts to help the homeless through his Day 1 Fund.

“Last week, Amazon founder and CEO Jeff Bezos announced that he and his wife, MacKenzie Bezos, were donating $97.5 million to 24 organizations that provide homeless services across the country. The donation is part of Bezos’s $2 billion ‘Day 1 Fund, a philanthropic endeavor … that, according to Bezos, focuses on establishing ‘a network of new, non-profit, tier-one preschools in low-income communities’ and funding existing nonprofits that provide homeless services.”

Del Valle says Bezos deserves little credit for his big gift for several reasons. First, Amazon very publicly opposed a recent initiative for a $275 per employee tax on large employers in Seattle. The proceeds would have been used to fund public programs for the homeless. This allegation suggests that Bezos feels guilty, or that the gift is a cynical attempt to buy-off critics. That might have an element of truth, but the tax was well worthy of opposition on economic grounds — almost as if it was designed to stunt employment and economic growth in the city.

Second, because Amazon has been an engine of growth for Seattle, Del Valle intimates that the company and other large employers are responsible for the city’s high cost of housing and therefore homelessness. Of course, growth in a region’s economy is likely to lead to higher housing prices if the supply of housing does not keep pace, but forsaking economic growth is not a solution. Furthermore, every large city in the country suffers from some degree of homelessness. And not all of those homeless individuals have been “displaced”, as Del Valle would have it. Some have relocated voluntarily without any guarantee or even desire for employment. As for the housing stock, government environmental regulations, zoning policies and rent control (in some markets) restrains expansion, leading to higher costs.

Finally, Del Valle implies that private efforts to help the homeless are somehow inferior to “leadership by elected officials”. Further, she seems to regard these charitable acts as threatening to “public” objectives and government control. At least she doesn’t disguise her authoritarian impulses. Del Valle also quotes a vague allegation that one of the charities beholden to Amazon is less than a paragon of charitable virtue. Well, I have heard similar allegations that government isn’t celebrated for rectitude in fulfilling its duties. Like all statists, Del Valle imagines that government technocrats possess the best vision of how to design aid programs. That attitude is an extension of the scientism and delusions of efficacy typical of central planners. Anyone with the slightest awareness of the government’s poor track record in low-income housing would approach such a question with trepidation. In contrast, private efforts often serve as laboratories in which to test innovative programs that can later be adopted on a broader scale.

While selfishness might motivate private acts of charity in some cases, only voluntary, private charity can ever qualify as real charity. Government benefits for the homeless are funded by taxes, which are compulsory. Such public programs might be justifiable as an extension of social insurance, but it is not charity in any pure sense; neither are it advocates engaged in promoting real charity, despite their conveniently moralistic positioning. And unlike private charity, government redistribution programs can be restrained only through a political process in which substantial payers are a distinct minority of the voting population.

Public aid and private charity have worked alongside each other for many years in the U.S. According to Russ Roberts, private giving to the poor began to be “crowded-out” during the Great Depression by a dramatic increase in public assistance programs. (Also see Doug Bandow’s “War On Charity“.) It’s certainly more difficult to make a case for gifts to the poor when donors are taxed by the government in order to redistribute income.

The statist war on private charity can take other forms. The regulatory apparatus can crowd-out private efforts to extend a helping hand. Chloe Anagnos of the American Institute for Economic Research (AIER) writes of a charity in Kansas City that wanted to provide home-cooked soup to the homeless, but health officials intervened, pouring bleach into the soup. I am aware of similar but less drastic actions in St. Louis, where organizations attempting to hand-out sandwiches to the poor were recently prohibited by health authorities.

Private charity has drawn criticism because its source has driven economic growth, its source has opposed policies that stunt comic growth, and because it might interfere with the remote possibility that government would do it better. But private charity plays a critical role in meeting the needs of the disadvantaged, whether as a substitute for public aid where it falls short, or as a supplement. It can also play a productive role in identifying the most effective designs for aid programs. Of course, there are corrupt organizations and individuals purporting to do charitable work, which argues for a degree of public supervision over private charities. But unfortunately, common sense is too often lost to overzealous enforcement. In general, the public sector should not stand in the way of private charities and charitable acts, but real generosity has little value to those who press for domination by the state.

Relieving the U.S. Public Toilet Shortage: User Fees

12 Wednesday Dec 2018

Posted by in Price Mechanism, Social Costs

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The musical comedy Urinetown opened in 2001 and ran for 965 performances, not a bad run by Broadway standards. The show, which is still performed in theaters around the country, is a melodramatic farce: a town tries to deal with a water shortage by mandating that all townspeople use pay toilets controlled by a malevolent private utility. Despite the play’s premise, pay toilets are a solution to the very real problem of finding decent facilities, or any facility, in which to relieve oneself in public places. Anyone who has ever strolled the streets of a city has encountered this problem from time-to-time. But in the U.S., where local budgets are typically strapped, the choice is often between scarce and decrepit free toilets or no toilets at all. Otherwise, those seeking relief must rely on the kindness business owners or pass laws allowing non-patrons to commandeer businesses’ bathrooms at will. Toilets with user fees, however, are an alternative that should get more emphasis.

In part, the theme of Urinetown reflects a longstanding notion among anti-capitalists that pay toilets are a disgustingly unfair solution to these urgent needs. One can imagine the logic: everyone has a need and a right to make waste, so we should all have access to sparkling public toilets for free! There is also the presumed misogyny of charging at stalls but not urinals (which are cheaper to maintain, after all), but overcoming that problem should not present a great technical hurdle. And surely pay toilets could be made to accept EBT cards, or locally-issued pee-for-free cards for the homeless.

Yes, we all make waste. However, most of us are so modest and fastidious that we quite literally “internalize the externality” we’d otherwise impose on others were we to seek relief in the street or behind trees in the park. We hold it and sometimes incur high costs in search of a restroom. Those are costs many of us would willingly pay to avoid.

As Alex Tabarrok says in “Legalize Pay Toilets“, outrage over pay toilets, very much like the kind expressed in Urinetown, is what led to outright bans on pay toilets in America during the 1970s (also see Sophie House’s discussion of the need for pay toilets at Citylab). According to Tabarrok, “In 1970 there were some 50,000 pay toilets in America and by 1980 there were almost none.” Many travelers know, however, that pay toilets are fairly commonplace in Europe.

In the wake of pay-toilet bans in America, and without the flow of revenue, those one-time pay toilets were not well-maintained nor replaced. In that sense, hostility to the concept of pay toilets is responsible for the paucity and abysmal condition of most public restrooms today. Public restrooms are often plagued by a tragedy of the commons. And when you do see a “free” public restroom in relatively good condition (in an airport, on a turnpike, or elsewhere), it is usually because its costs are cross-subsidized by payments for other goods and services offered in those facilities. It’s not as if you don’t pay for the bathrooms.

There is no question of a willingness to pay, but legal obstacles to pay toilets remain. Pay toilets are still very uncommon. New York City actually decriminalized public urination a few years ago, an odd way to deal with the shortage of restrooms. Some cities, such as Philadelphia, have initiated efforts to bring back pay toilets, but they have made little headway. Just last year, the toilet paper producer Charmin ran a successful publicity campaign in New York City by testing a mobile toilet-sharing service (à la Uber ride-sharing) called Charmin Van-GO. The company described the test as a big success in terms of publicity, but apparently the service has not been offered on a continuing basis.

The economic problem posed by full bladders and bowels on the public square can be solved with relative efficiency using the price mechanism: pay toilets. The flow of revenue can defray the costs of restrooms and their maintenance, easing the strain on public budgets and covering the cost of keeping them clean. Pay toilets can be provided publicly or built and operated by private providers. Pricing the use of toilets, whether offered publicly or privately, helps focus resources at the point of need. Free public toilets, in contrast, are scarce and typically unsanitary. Funding public restrooms through taxation, rather than user fees, involves a loss of efficiency because taxpayers are often distinct from actual users. Forcing purveyors of food and drink (or anything of value) to offer bathroom access to “free riders” creates another obvious source of inefficiency. Allowing the use of EBT cards at pay toilets, while overcoming certain objections, would also involve inefficiencies, but at least they’d be limited to subsidies for a small proportion of the bathroom-going public. Given the alternatives under the status quo, our cities would be far more pleasant if they were flush with pay toilets.

Certainty Laundering and Fake Science News

05 Wednesday Dec 2018

Posted by in Global Warming, Risk, Science

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Intriguing theories regarding all kinds of natural and social phenomena abound, but few if any of those theories can be proven with certainty or even validated at a high level of statistical significance. Yet we constantly see reports in the media about scientific studies purporting to prove one thing or another. Naturally, journalists pounce on interesting stories, and they can hardly be blamed when scientists themselves peddle “findings” that are essentially worthless. Unfortunately, the scientific community is doing little to police this kind of malpractice. And incredible as it seems, even principled scientists can be so taken with their devices that they promote uncertain results with few caveats.

Warren Meyer coined the term “certainty laundering” to describe a common form of scientific malpractice. Observational data is often uncontrolled and/or too thin to test theories with any degree of confidence. What’s a researcher to do in the presence of such great uncertainties? Start with a theoretical model in which X is true by assumption and choose parameter values that seem plausible. In all likelihood, the sparse data that exist cannot be used to reject the model on statistical grounds. The data are therefore “consistent with a model in which X is true”. Dramatic headlines are then within reach. Bingo!

The parallel drawn by Meyer between “certainty laundering” and the concept of money laundering is quite suggestive. The latter is a process by which economic gains from illegal activities are funneled through legal entities in order to conceal their subterranean origins. Certainty laundering is a process that may encompass the design of the research exercise, its documentation, and its promotion in the media. It conceals from attention the noise inherent in the data upon which the theory of X presumably bears.

Another tempting exercise that facilitates certainty laundering is to ask how much a certain outcome would have changed under some counterfactual circumstance, call it Z. For example, while atmospheric CO2 concentration increased by roughly one part per 10,000 (0.01%) over the past 60 years, Z might posit that the change did not take place. Then, given a model that embodies a “plausible” degree of global temperature sensitivity to CO2, one can calculate how different global temperatures would be today under that counterfactual. This creates a juicy but often misleading form of attribution. Meyer refers to this process as a way of “writing history”:

“Most of us are familiar with using computer models to predict the future, but this use of complex models to write history is relatively new. Researchers have begun to use computer models for this sort of retrospective analysis because they struggle to isolate the effect of a single variable … in their observational data.”

These “what-if-instead” exercises generally apply ceteris paribus assumptions inappropriately, presuming the dominant influence of a single variable while ignoring other empirical correlations which might have countervailing effects. The exercise usually culminates in a point estimate of the change “implied” by X, without any mention of possible errors in the estimated sensitivity nor any mention of the possible range of outcomes implied by model uncertainty. In many such cases, the actual model and its parameters have not been validated under strict statistical criteria.

Meyer goes on to describe a climate study from 2011 that was quite blatant about its certainty laundering approach. He provides the following quote from the study:

“These question cannot be answered using observations alone, as the available time series are too short and the data not accurate enough. We therefore used climate model output generated in the ESSENCE project, a collaboration of KNMI and Utrecht University that generated 17 simulations of the climate with the ECHAM5/MPI-OM model to sample the natural variability of the climate system. When compared to the available observations, the model describes the ocean temperature rise and variability well.”

At the time, Meyer wrote the following critique:

“[Note the first and last sentences of this paragraph] First, that there is not sufficiently extensive and accurate observational data to test a hypothesis. BUT, then we will create a model, and this model is validated against this same observational data. Then the model is used to draw all kinds of conclusions about the problem being studied.

This is the clearest, simplest example of certainty laundering I have ever seen. If there is not sufficient data to draw conclusions about how a system operates, then how can there be enough data to validate a computer model which, in code, just embodies a series of hypotheses about how a system operates?”

In “Imprecision and Unsettled Science“, I wrote about the process of calculating global surface temperatures. That process is plagued by poor quality and uncertainties, yet many climate scientists and the media seem completely unaware of these problems. They view global and regional temperature data as infallible, but in reality these aggregated readings should be recognized as point estimates with wide error bands. Those bands imply that the conclusions of any research utilizing aggregate temperature data are subject to tremendous uncertainty. Unfortunately, that fact doesn’t get much play.

As Ashe Schow explains, junk science is nothing new. Successful replication rates of study results in most fields are low, and the increasing domination of funding sources by government tends to promote research efforts supporting the preferred narratives of government bureaucrats.

But perhaps we’re not being fair to the scientists, or most scientists at any rate. One hopes that the vast majority theorize with the legitimate intention of explaining phenomena. The unfortunate truth is that adequate data for testing theories is hard to come by in many fields. Fair enough, but Meyer puts his finger on a bigger problem: One simply cannot count on the media to apply appropriate statistical standards in vetting such reports. Here’s his diagnosis of the problem in the context of the Fourth National Climate Assessment and its estimate of the impact of climate change on wildfires:

“The problem comes further down the food chain:

  1. When the media, and in this case the US government, uses this analysis completely uncritically and without any error bars to pretend at certainty — in this case that half of the recent wildfire damage is due to climate change — that simply does not exist
  2. And when anything that supports the general theory that man-made climate change is catastrophic immediately becomes — without challenge or further analysis — part of the ‘consensus’ and therefore immune from criticism.”

That is a big problem for science and society. A striking point estimate is often presented without adequate emphasis on the degree of noise that surrounds it. Indeed, even given a range of estimates, the top number is almost certain to be stressed more heavily. Unfortunately, the incentives facing researchers and journalists are skewed toward this sort of misplaced emphasis. Scientists and other researchers are not immune to the lure of publicity and the promise of policy influence. Sensational point estimates have additional value if they support an agenda that is of interest to those making decisions about research funding. And journalists, who generally are not qualified to make judgements about the quality of scientific research, are always eager for a good story. Today, the spread of bad science, and bad science journalism, is all the more virulent as it is propagated by social media.

The degree of uncertainty underlying a research result just doesn’t sell, but it is every bit as crucial to policy debate as a point estimate of the effect. Policy decisions have expected costs and benefits, but the costs are often front-loaded and more certain than the hoped-for benefits. Any valid cost-benefit analysis must account for uncertainties, but once a narrative gains steam, this sort of rationality is too often cast to the wind. Cascades in public opinion and political momentum are all too vulnerable to the guiles of certainty laundering. Trends of this kind are difficult to reverse and are especially costly if the laundered conclusions are wrong.