William M. Briggs

Read Part I. I’ll be away from the computer a large portion of today and will be slow in answering comments.

Your health care will degrade

Since the deficit will be almost impossibly high, taxes will not be able to be raised fast enough to pay for it. Thus, in the period of ten to twenty years out, politicians will be forced to cut government payouts.

This includes payouts from Social Security, Medicare, Medicaid, and Obamacare. Again, this is not something which is merely probable, but is certain. Demographics alone guarantee this.

Health care must eventually be “rationed,” in the same sense as it is in other countries with socialized medicine. In effect, those other countries will also suffer, because the States will no longer be available as a destination for superior care. Newfoundland and Labrador Premier Danny Williams will have to stay home next time he wants heart surgery.

Currently, few to none are denied care, regardless of their financial status. Poor people go to the emergency room for (expensive) routine care, for example. These costs are spread among those with money: already, in effect, people with insurance are already subsidizing those without.

That will continue to be so under Obamacare, where the subsidies are given a new name, but with the addition of two new layers of bureaucracy: one on the business and hospital side, and one on government. The cost savings of shifting people out of the emergency rooms and into offices will be ate up by paperwork. That must mean that service will degrade.

Be clear: poor people aren’t being granted new health, they are being granted a new name for what is already given.

Because this is true, I think predictions about doctor shortages are incorrect in one sense. Since everybody can already have care if they need it, there are, within some range, enough physicians to provide that care.

I mean, there will not be a flood of new patients, because these people are already there, somewhere in the system. What will instead happen is that these people will be redistributed in the system. We will see fewer ER visits for routine care, and more to general practitioners. There could be a doctor shortage in that sense, but that will quickly stabilize.

Doctors will receive less money for their services, and this will persuade some that would opt for that career to do something else. Any trend in availability will be gradual, however, because of the large inertia in the system.

Your liberty will be restricted

Health can mean, and will come to mean, anything which is related to human behavior. Absolutely everything you can think of, or say, or do can be plausibly related to health.

Since the government will be paying the bills, it will feel it has the right to proscribe or tax any behavior that would adversely affect your “health.”

Government especially will call for new sin taxes to pay for the deficit. This will lead to hypocrisy and lying of the highest order. I mean, politicians will know they are lying when they say, “We have to add this health tax on internet usage, because heavy internet use is associated with poor attention in school. We care about the mental health of our children!”

Enjoy the occasional soda pop? No, sir! That’s bad for you. “Waiter, where’s the salt shaker?” “I’m sorry sir. The law won’t allow us to add salt to our food.” Listen to talk radio? That’s bad for your stress level, I’m afraid. The “Fairness” Doctrine will help ease your suffering.

Too much CO₂ in the air leads to adverse global warming, which leads to effects too numerous and too horrible to list. Yet the EPA will give it their best effort: it will take decades to do so. My most novel prediction: the number of miles driven per citizen will be limited, with inspections and fees paid for overages.

Favored political groups—”mascots” as economist Thomas Sowell calls them—women desiring abortions, people who want sex changes, drug addicts, and on and on and on, will find a way to squeeze money out of the government.

I have already speculated how homeopaths and other quack medics will seek protection. Perhaps many thought I was exaggerating. But Friday, Dennis Kucinich (D-Ohio) in an interview to explain his vote switch with Fox News reporter Neil Cavuto, said that he looks forward to a “whole new way of” medicine. To include, he said, “complementary and alternative” treatments. Just as I predicted.

All these moves will dramatically increase the Gross National Cynicism and increase the antagonism between special interest groups and citizens, further degrading public life.

Your sense of paternalism will increase

I saved the best for last.

Liberty used to be the most important part of life in the States. For those who are not natives, our heated emotion over this topic might seem strange. But recall that our country began with a provocation infinitely smaller; a trivial tax, which would have been far cheaper to pay for than any rebellion.

We saw it as a question of who would be allowed to decide our fate. We did not want to be dictated to from on high. We wanted to be left alone.

But no more. Increasingly, people see “government” as something other than themselves. They see “government” as an entity that somehow exists independently and can be called upon to fix all ills, even personal ones. Resources appear like magic.

People will not be as quick to think that they or their families can take care of themselves. They will more often go to the government and asked to be looked after.

And they will be.

Read Part I

Update For those who doubt the “every aspect of life” prediction: don’t forget this country once lost its mind with alcohol, even to the extent of modifying the Constitution. What happened before can happen again.

Here are some things I think will happen if Obamacare is passed. When I say “you” or “your”, I mean “people on average.” Obviously, some people will benefit. This is only a two-part post, as we’re all growing weary of discussing this topic.

Your insurance costs will increase

Democrats are ever lamenting that those with pre-existing conditions have difficulty finding insurance. Obamacare mandates that insurance companies “cover” these people.

Mandating “coverage” of those who have are known to have maladies translates to mandating that insurance companies decrease profits, perhaps to the point that they are guaranteed to lose money.

I have tried many times to show that insurance is a bet. You are betting you will get sick and the insurer is betting you won’t. If you do get sick, the insurer pays. If you don’t, you pay. This bet is remade monthly. If you bet you’ll get sick and you already are, you are, in effect, cheating. The insurer has to pay and there is no way that the money you give him will make up for his loss.

That means that mandating insurers “cover” those who are guaranteed to win their bets—those with pre-existing conditions—necessarily increases companies’ costs.

Those costs will be passed along in two ways: to you (possibly through your employer), and to the employees of the insurer. Insurance companies profits—now hovering at 3 to 4 percent—must drop. There is a real danger that small insurers will fail.

This will lead to the direct opposite of the what was intended: when these small insurers fail, people will lose coverage. They will be able to find new coverage, but from larger companies with higher rates.

This new crop of “insurance homeless” will provide leverage for “progressives” to suggest, and probably win, complete government control of health.

Your health costs will increase

Your insurance costs are guaranteed to rise. Note carefully: as just shown, this is certain to happen. It is not merely probable, but inevitable. This is true even if you believe Obamacare is a good idea and that people with pre-existing conditions should be “covered.”

That euphemism is misleading: they are not “covered.” What really happens is that their health costs are subsidized by everybody else.

You or your employer will face higher insurance premiums. Thus, the extent of your coverage will be shrunk. To keep costs down, you will see higher deductibles, lower limits on payouts and such forth.

The costs of insurance paid by your employer will be offset by either cutting pay, reducing future raises, or most likely by hiring fewer workers in the future. That later will be especially true of large employers.

Small- and medium-sized companies will hire fewer people, too. While the influence of any one company is small, the effect in aggregate will be large. Small- and medium-sized business will either have to pay for insurance or pay a penalty for not buying it. So will individuals (it’s now just under $500 per year).

Businesses but not individuals will be offered a tax incentive offset. This tax incentive will be whittled away slowly and surely.

Since most businesses will hire fewer, or they will cut payrolls, or not increase them, tax revenues to the government will decrease.

Your taxes will increase

The government will expand. Obamacare will create a massive new bureaucracy, which will suck funds from the public teat.

Taxes are already guaranteed to increase to pay for many of Obamacare’s provisions: this is in the bill. But they will increase more than estimated because the bureaucracy must be fed. All experience shows that bureaucracies grow fatter in time, consuming more tax dollars as they do so. There has never been an instance in history where this was not so. Health bureaucracies especially grow quickly.

Because payroll and income tax revenue will decrease, because businesses will hire fewer and pay existing employees less, and because small- and medium-sized business are initially allowed a tax incentive, the deficit will increase at a faster rate.

Since you will have less money, you will spend less, and this will have its normal effects.

Social security revenues, for the first time this year, fell below payouts. With our inescapable demographics, this trend is guaranteed to continue. Congress has also stolen a massive amount of money from the Social Security trust fund.

Couple to this the situation of Medicare, and the deficit due will soar to, as Mr Obama likes to say, “unprecedented” levels.

Incidentally, the majority of the so-called savings to the deficit to the Obamacare bill are made by the government takeover of student loans. This measure was tacked onto health care so that the House could cheat and use reconciliation to pass the Obamacare. And so are a host of—so far unknown—additions to the House reconciliation “fix” package (which the Senate might not pass).

Lastly, for the first five years people and businesses pay the new tax but receive almost none of the new entitlements. Those start after year five, when costs begin to escalate. This appalling accounting trick means that after about fifteen years, health care will run a magnificent deficit on its own.

Taxes must increase at a dramatic rate.

A side effect will the creation of more “poor” people: I mean, “poor” people will become a larger percentage of the population because of the cuts in pay and in employment. Since these poor are the ones receiving “free” or reduced-cost health care, government payouts (and deficits) will be vastly larger than estimated. I’d say, after fifteen years, about twice what was estimated.

History is on the side of this prediction: it has happened with every entitlement.

Coming tomorrow: Part II and the best predictions.

Today’s post is at Pajamas Media: Sudden Acceleration or Creeping Fear?

Charlie Martin, now science and tech editor at Pajamas, asked me to look into the fatal accidents occurring in Toyotas said to be caused by sudden acceleration.

Tagline: Do Toyota automobiles really have a “sudden acceleration” problem? Maybe not.

Note carefully: this is a qualitative analysis of the fatal accidents only.

I promised this article a long time ago: I hope these well known calculations are enough to give the gist.

Randomized controlled trials are supposed to be the gold standard of experimental research. This is true. But it would be just as true if we said “controlled trials” without the “randomized.”

“Randomness” is not needed. “Random” trials are even the opposite of what we desire. Which is information and evidence. Since “randomness” means “unknown”, adding randomness decreases information.

There is just one reason, which I’ll reveal later, why “randomness” is important.

Suppose you’re designing a marketing, finance, or drug trial: anything where you have “treatments” to compare. Since everybody understands drugs trials, we’ll use that.

A controlled study splits a group of people in two; it gives one half drug A, the other half B. The results are measured, and if more people improve using A, then A is said to be better. How much better depends on what kind of probability model is used to measure the distance.

How to make the groups? If you need 100 folks, take the first 50 and give them A, the second 50 gets B. That sound suspicious to you?

Ordinarily, the groups would be split using “randomness”, usually computerized coin flips. “Randomness” is supposed to roughly equally distribute characteristics that might affect the drug. This being so, any difference in A and B is due to the drugs themselves and not to these unmeasured characteristics.

This view is false.

One measurable characteristic is sex. If men and women appear equally and uniformly (yet unpredictably) then the chance one group is filled with all men is 2^-n, where n is the number of people in your study. If n = 50, the chance is about 10^-16: that’s a decimal point followed by a lot of zeros. If n = 100, the chance is about 10^-30. Pretty low.

All men in one group is an extreme imbalance. But if men were, say, 70% of one group, this would still be cause for concern. The chance of at least this sized discrepancy for n = 50 is 0.001; and for n = 100 is 0.000016. Quite a difference! While a discrepancy is still unlikely, it no longer seems impossible.

Of course, men and women don’t always show up equally and uniformly. Any departure from these ideals only makes the chance for a discrepancy between the groups higher. How much higher depends on what is meant by “unequally” and “non-uniformly.” However, the effect will always be substantial.

Very well. If we just measure sex, then the chance of a discrepancy is low. But now consider fat and skinny (say, divided by some preset BMI). We now have two groups to balance with our coin flips. The chance that we have at least one discrepancy (in sex or weight) doubles.

For n = 50 it is now 0.0026; and for n = 100 it is 0.000032.

OK, we measure sex and weight; add race (white or non-white). The chance of at least one discrepancy is higher still; about three to four times higher than with just one characteristic.

How many measurable characteristics are there? Can we think of more? Height, blood pressure, various blood levels, ejection fraction, and on and on and on. At least three to four dozen—call it 50-100—characteristics might be important and are routinely measured in medical trials.

You can see where we’re going. Every person is, by definition, different from every other person. There are enormous differences between people at every level, from physiological to cellular to genetic.

Eventually, of course, it becomes all but certain that there will be a discrepancy between the two groups. Whether you measure that characteristic is irrelevant. It—actually many—will be there. And recall: not all these characteristics will present equally and uniformly; they’ll be all over the place. Discrepancies, imbalances between groups, are always there.

“Randomly” splitting groups, therefore, does not, and cannot, “balance” groups.

But control can.

Control means taking those characteristics we think are important, and splitting the groups such that each receives an equal proportion. There will always be, even when we control, discrepancies between the groups we did not control, and one or some of them might be responsible for the results. But if we choose our groups carefully, then the chance of this is small.

While “randomness” cannot live up to its promise, there is one good reason to use it in medical trials. The human animal cannot be trusted. He will cheat, steal, trick, and lie, even to himself—especially to himself.

You can’t trust a man to pick who receives what treatment for fear he will game the system, maybe even unawares. You have to remove the decision to a disinterested authority. Like a non-human computer.

Or a statistician.

The National Center for Complementary and Alternative Medicine was tacked forcibly onto the National Institute of Health after Tom Harkin (D-Iowa) and Orrin Hatch (R-Utah) thought more attention ought to be paid to beeswax.

As a curative agent, I mean. Those two, and others in charge of us, thought it would a fine idea if we paid to put alternative therapies to the test.

And they’re right: it is a good idea. Some potential palliatives can be dismissed immediately—for example, massive doses of arsenic to treat toenail fungus. But most cannot be brushed off without some evidence, because even the most ludicrous sounding treatment might be helpful.

Have a claim? Put it to a controlled test. Pass that test and all benefit. Flunk it, then admit defeat; or at least keep quiet and move on (which never happens, naturally).

The three treatments that have received the most exhaustive testing are acupuncture, chiropractic, and homeopathy. They have been subject to endless experiments, found wanting, but never found lacking proponents.

I worked for several years at Cornell Medical School’s Center for Complementary and Integrative Medicine, where I read over a hundred papers that made extraordinary claims. The best evidence for the efficacy of any of these treatments is statistical. But the more experiments any treatment undergoes, the more its signal fades into the noise. You have to wear cheap statistical magnifying glasses to see positive effects.

However, I do not say, and it is not true, that these treatments have no benefit. They surely do. But so do sugar pills. But with chiropractic, there is a real, documented chance of physical harm. Acupuncture and homeopathy are harmless. The later is guaranteed to be.

In case you are one of the few people left who don’t know, a homeopathic “drug” is made in the following manner.

Water—somehow this is “pure” water, but how it’s made, we’re never told—is dosed, tea-bag style, with some substance, usually some plant extract. The doped water is successively diluted until the probability that even one molecule of the substance remaining is about equal to you having the ability to jump to the moon.

This is boasted of. The water—by a mysterious process unknown to anybody—is able to memorize that it once knew the substance. When you eat that water in the form of a pill composed of miscellaneous ingredients that were soaked in the diluted water, it is supposed to help your body fix itself by releasing vibrations.

It’s always vibrations!

Nobody knows how homeopathy works. Because it doesn’t. We know a lot of science with varying degrees of accuracy, and there are few things we know so well that homeopathy and most other complementary procedures are groundless. Yet some insurance companies still pay for these treatments.

The actuaries who investigate these therapies are good enough statisticians to know that the therapies don’t perform as stated (biologically, physically), but they also know that they work in the following way: some people who would otherwise see an expensive physician will chose a cheap complementary procedure instead.

Usually, these people needn’t have gone to a physician anyway. They have colds, minor aches and pains, or other maladies that will self correct.

If complementary procedures were just as expensive as standard ones, insurance companies would surely not cover them. But since they are cheaper, actuaries can estimate how many people will use a placebo therapy that would have instead gone to a physician. Perhaps oddly, if the number that would opt for, say, homeopathy (if it were covered) is large, then the insurance company will cover homeopathic treatments. This saves them money.

When the government takes over medical care, they will have to legalize these kinds of actuarial calculations. It must decide what will be paid for and what won’t. For example, if I set up shop as a quack—I cure with taps of my healing hammer–the government will have to legislate whether it will pay me. Just as insurance companies do now.

Therefore, if there is any rationality left in government, they will probably come to the same conclusions that insurance companies have, and they will fund homeopathic and other integrative therapies.

It’s worse. Governments cave more readily to special interests than do insurance companies. “You cover homeopathy? You should also cover wymen-centered Wiccan magick!” The actuarial tables will be tossed and votes will take their place.

Incidentally, Wiccan “cures” are cheaper than, say, new chemotherapies. And who are we to say which is better?

Just wait and see.

Note I’m traveling today and will be away from the computer.

Here’s an experiment you can try at home. Gather a set of children’s building blocks and form them into a square, flat on the floor.

The square can be of any dimension. In the middle of the square, and not touching any side, place another block on top. If your original square was more than three blocks on a side, then you can fit more than one block in the square’s center. These additional blocks form a second level.

Now take a step back and jump up and down once or twice. If the floor is hard and sturdy, nothing will happen. The blocks won’t topple unless your bouncing is of sufficient force to crack the foundation.

You can add a third level to your blocks, but only if that third level follows the same rules as the second: none of the blocks can touch the edges of the level below. After it’s built, recommence jumping: the structure should hold. It will still take devastating force to topple it.

If you want to add a fourth level, you’ll have to increase the size of the base. If you didn’t, the levels above would touch the edges, violating our rule.

You can continue quite a while along these lines: those blocks high up will be admirably supported by those below, but they will also add a substantial weight to the blocks under them. The base can be crushed by too many blocks on top.

Your experiment will show the most stable set up of blocks will have a wide base with only a few on top. You’ll need some on top, else the blocks below will move too easily; they will break apart slowly with persistent small vibrations. There will be a balance where you have a stable system that holds together naturally.

That pyramid of blocks is like a society as it stands at some point early on in its history; but not too far along, either.

Because eventually comes a new generation, and from them, a new government. Fresh politicians and unelected leaders look about and see that much of what needed to be done has already been done.
If the base has grown, there is a place for them. If not, they are not needed.

Ideally, they would do nothing. But people, especially people inclined to politics, are not inclined to sit still. They must do something. So they convince themselves that not all is well. They must add to and rearrange the structure! To not do so would be to admit their uselessness.

Being naturally fussy, the bureaucrats will meddle with the structure, adding to it there, subtracting to it there. Eventually, these folk will retire or die, only to be replaced by another batch.

They’ll be dissatisfied by the work that came before them; they’ll meddle, too. They’ll add more blocks on top, right near to their own. The occasional dishonest politician will add more than his fair share.

Occasionally, there will appear a few who want to shift the blocks into a stabler position. These “originalists” will be resisted most strongly by the people in the most unstable blocks, where the system is most unstable and complex because they benefit—in the here and now—by those complexities.

Eventually, inevitably, the structure will become sensitive to the slightest application of external force. Any small shock will send shivers everywhere. Some shocks can be anticipated: the smallest hint of troubles to come will require massive efforts to patch the structure so that it remains in balance. Yet the weight of the blocks and their odd configuration will require a delicate balance, a surgeon’s touch.

You know what is bound to happen: what has happened to every government that has ever existed. In time, it falls.

All experience shows that because people are people and must do something—politicians especially feel a burning desire to interlope—all governments grow until such a point that they can no longer sustain themselves. They end.

They either fall over on themselves, or they break apart into pieces; either mechanism brings destruction.

The only thing that has restrained—slowed, but not eliminated—the unlimited growth is a firm, fixed set of rules that all must adhere to. Allow the members of the government leeway to ignore the rules or rewrite them as they go along, and the growth and instability only increases its pace.

Well, all metaphors are limited. The thesis behind this one, even if expressed badly, is sound: that all governments where the population exceeds more than a handful grow inexorably, become overly sensitive to external forces, and then collapse. Just because people are ever dissatisfied.

This dissatisfaction leads to progress (and occasional collapses) in other areas, but nobody needs to progress a government beyond a solid foundation.

The scene was tense Wednesday, 3 March, when Mason Jammer, a student at Jefferson Elementary in Ionia, Michigan held his kindergarten class hostage by fashioning his finger into the shape of a gun. Ionia is far distant suburb east of the thriving metropolis of Grand Rapids.

During the siege, panicked teachers gathered outside the classroom expressed concerns that the finger might go off. “This just wasn’t funny,” said the Jefferson principal. “[This] made other students uncomfortable.”

Jammer strutted around the room with his right forefinger held straight out. His right thumb was held erect, though it occasionally sagged when Jammer’s attention was diverted by Sally Kipper, 6, trying to climb into the fish tank.

The situation was diffused by the classroom teacher, who talked Jammer down from his frenzy. “I offered him chocolate milk,” said the 54 year-old homeroom teacher. “He dropped the gun, and immediately the door burst open. I think it was at that point that I fainted.”

Coming through the door was the principal and the janitor, who had armed himself with the broken handle of a shovel. He held it pointy side forward, but did not have to use it because little Mason offered no resistance as he was taken into custody.

This wasn’t the first time Jammer has seen trouble with the law. At one January recess, he was seen making the gun sign and was heard to make the “Pshew!” sound at some birds passing overhead. Witnesses report Jammer’s thumb cocking back and forth.

Luckily, no birds were harmed, but Jammer was still given a warming.

A file on Jammer was also opened with the Michigan Department of National Resources. Jammer did not have a valid hunting license on him when he attempted to shoot the birds.

The officials at Jefferson decided not to take any more chances. They are quoted as having said that they “had been too lenient” with Jammer in the past. Jammer was suspended for two days for the latest incident. He may also undergo counseling so that he understands just what are and what are not valid targets.

The Grand Rapids Press has more details of this harrowing tale.

The frequency of these attacks has risen dramatically over the past two years. Some educators are speculating that a wave of violence is about to overtake Elementary schools if something isn’t done immediately.

For example, last November, Zachery DeRidder, 6, in Ville Platte, Louisiana was heard to make the “Dut dut dut dut dut” sound commonly associated with automatic assault weapons. No witness could identify DeRidder simultaneously making the shape of a machine gun with his two arms, so the matter never found its way into the courts. A union representing teachers did use this incident to demand higher wages, however.

In that same month, Jessica Hanford, 5, in Bakersfield, California allegedly repeatedly threw a kickball against the wall of Lincoln Elementary. As the ball hit, Hanford made the “Brak-sssh!” sound while throwing her arms into the air.

Dr Wilmer Frankford, a Harvard-trained psychologist said this clearly indicated violent intent. Hanford has been under observation since the incident, and will remain so until her trials begins, most likely sometime in June.

Educators have been vigilant in the policing of their classrooms, but there are costs for this increased surveillance. In February of this year, Jason Marshfield, 6, of Eau Claire, Wisconsin was tackled by the school’s gym teacher after what officials called “Unusual explosive sounds” were heard emanating from the boys lavatory.

It was later discovered that Marshfield was teaching his “best friend” Kyle Mellen, 6, “how to make fart sounds with his underarm.”

The FBI also maintains a growing file of papers confiscated from schools all over the country. On these papers—all produced by the hands of children—are a variety of war-like images.

Everything from Sopwith Camels to F-15s to UFOs are drawn shooting down other planes, attacking tanks, or dropping bombs on the heads of the unsuspecting innocents. Many of the images have sound effects written in.

Agent Fred Bellaire, of New York, said, “I mean, whoever heard of an F-15 dropping bombs? It’s a fighter and can’t carry bombs. Something suspicious is going on with these kids. But I want to assure you that the FBI is right on it.”

The principal of Jefferson Elementary best summed up the situation when he said, “If we don’t teach these kids early that guns are wrong, then they might grow up believing otherwise.”

There’s Nancy Pelosi, Six Gun of State strapped to her side, the sun burning overhead. And there’s you, armed only with Freedom, thirty paces off. It’s a standoff! If you blink, it’s all over.

You have one advantage: all those non-deductible surgeries she’s had have made it impossible for her to squint against the noonday sun. You can still get the draw on her!

But the clouds are gathering. You’ll have to act fast. You have one more chance to be allowed to take care of yourself. Call or email your representative today, tomorrow at the latest. Put the fear of non-re-electability into ‘em.

Obamacare, by rooting through your wallet, would provide many with insurance (and those gifted with your largess would be asked nothing in return for it). But having insurance is not equivalent to having health. Although some might mistakenly believe that they want insurance, what they really want is health. And the best way to deliver that is not via a government-controlled health-care bureaucracy. Here’s why.

Mr Obama has placed himself in front of many teleprompters and has been prompted to cast the most outrageous aspersions against insurance companies. The party line is that they are evil, incorrigible. This is so, the reasoning goes, because insurance firms refuse to provide some people health care, and because they receive a profit for their services.

Yet socialized medicine, we are assured, will, by dousing it with regulatory holy water, exorcise the evil from insurance companies. Begone vile profits!

But somehow, in that wisdom they are always touting, Democrats have forgotten that insurance companies do not provide health care. They provide money when they are on the losing end of a bet. You wager you’ll get sick, they say you won’t. If you do get sick, they pay out. If you don’t, they keep your money. A fair transaction entered into freely by both parties.

What would a rational bookie do if you were to say to him, “I’m already sick. I want to bet you that if I get sick, you’ll pay me a lot of money.”? He’d ask that you re-take your elementary math class, that’s what. Yet Mr Obama would require your bookie, the insurance company, to take your bet. He wants to guarantee that the insurance company pays out on what is a losing bet.

What necessarily follows from this? The insurance company must raise its rates. It must charge more to its other clients to make up for its guaranteed, government-mandated loss. The cost of insurance—to be perfectly clear—will rise.

Not only that, but insurance companies will be required to set up internal offices, well stocked with lawyers and accountants, to communicate to the government that they are following the complex regulations set over them. That costs money, so insurance companies will have to raise their prices yet again.

Government, too, will have to set up its own offices that talk back to the insurance companies and to the people it’s giving free money to. The feeding and care of these government employees cost lots of cash.

The money the government requires will come from you. You will not be allowed to refuse to pay it. The extra money the insurance companies must charge will also come from you. Ordinarily, you would be allowed to refuse to pay that. But the law will be such that you can’t turn the private insurance companies down, either.

What’s the worst part? Absolutely none of these vast amount of monies will go towards improving health care. Since all that money is necessarily funneled to a bureaucracy, less will be available to spend on health care improvements.

We have returned to the inevitable Progressive Law of Unintended Consequences. Government meddling, motivated by the best of intentions, when it tries to improve health care and make it cheaper, will cause it to become limited and more expensive.

Further—and perhaps its true purpose after all—it will create a dependency on itself. It will, by law, mandate reliance on itself. The health bureaucracy will become self-perpetuating. And since every bureaucracy ever known has become larger and less efficient through time…well, you can connect those dots.

My solution? Tax the health care money provided from companies to their employees as income. Make that money income. Let people know exactly how much of their own money they are spending on insurance and care. The major reason health care has become so expensive is that nobody knows what anything costs. This opacity has given birth to a private bureaucracy, and as we’ve seen any such creature drives costs up.

I don’t have space to convince you that this solution is ideal. But I hope I’ve shown you that Congressperson Pelosi’s solution is suboptimal. And we haven’t even discussed how, since the government will be paying the bills, they’ll use that leverage to forbid you certain activities (smoking, eating salt, drinking soda pop, etc.), or to require you to perform certain others.

Just remember what P.J. O’Rourke said: “If you think health care is expensive now, just wait until it’s free.”

Update An anonymous reader tells us of a Rally in Washington D.C. on the 16th. Details here.

Update 2 Here, from The Hill is a list of the Democrats leaning on voting No. All Republicans are expected to vote no.

Read Part I

The Analysis (cont.)

Two problems arise when comparing a model’s integration (the forecast) with an analysis of new observations, which are not found when comparing the forecast to the observations themselves. Verifying the model with an analysis, we compare two equally sized “grids”; verifying the model with observations, we compare a tiny number of model grid points with reality.

Now, some kinds of screwiness in the model are also endemic in the analysis: the model and analysis are, after all, built from the same materials. Some screwiness, therefore, will remain hidden, undetectable in the model-analysis verification.

However, the model-analysis verification can reveal certain systematic errors, the knowledge of which can be used to improve the model. But the result is that the model, in its improvement cycle, is pushed towards the analysis. And always remember: the analysis is not reality, but a model of it.

Therefore, if models over time are tuned to analyses, they will reach an accuracy limit which is a function of how accurate the analyses are. In other words, a model might come to predict future analyses wonderfully, but it could still predict real-life observations badly.

Which brings us to the second major problem of model-against-analysis verification. We do not know actually how well the model is performing because it is not being checked against reality. Modelers who rely solely on the analysis model-checking method will be—they are guaranteed to be—overconfident.

The direct output of most climate and weather models is difficult to check against actual observations because models makes predictions at orders and orders of magnitude more locations than there are observations. Yet modelers are anxious to check their models at all places, even where there are no observations. They believe that analysis-verification is the only way they can do this.

This is important, so allow me a redundancy: models make predictions at wide swaths of the Earth’s surface where no observations are taken. At a point near Gilligan’s Island, the model says “17^oC”, yet we can never know whether the model was right or wrong. We’ll never be able to check the model’s accuracy at that point.

We can guess accuracy at that point by using an analysis to make a guess of what the actual temperature is. But since model points—in the atmosphere, in the ocean, on the surface—outnumber actual observation locations by so much, our guess of accuracy is bound to be poor.

MOS

Actual observations can be brought into the picture by matching model forecasts to future observations and then building a statistical model between the two. This is called model output statistics, or MOS. The whole model, at all its grid points, is fed into a statistical model: luckily, many of the points in the model will be found to be non-predictive and thus are dropped. Think of it like a regression. The models’ output are like the Xs, and the observations are like the Ys, and we statistically model Y as a function of the Xs.

So, when a new model integration comes along, it is fed into a MOS model, and that model is used to make forecasts. Forecasters will also make reference to the physical model integrations, but the MOS will often be the starting point.

Better, MOS predictions are checked against actual observations, and it is by these checks which we know meteorological models are improving. And those checks are also fed back into the model building process, creating another avenue for model improvement. MOS techniques are common for meteorological models, but not yet for climatological models.

Measurement Error

MOS is a good approach to correct gross model biases and inaccuracies. It is also used to give a better indication of how accurate the model—the model+MOS, actually—really is, because it tells us how the model works at actual observation locations.

But MOS verification will still given an overestimate of the accuracy of the model. This is because of measurement error in the observations.

In many cases, nowadays, measurement error of observations is small and unbiased. By “unbiased” I mean, sometimes the errors are too high, sometimes too low, and the high and low errors balance themselves out given enough time. However, measurement error is still significant enough that an analysis must be used to read data into a model; the raw data measured with error will lead to unphysical model solutions (we don’t have space to discuss why).

Measurement error is not harmless. This is especially true for the historical data that feeds climate models, especially proxy-derived data. Proxy-derived data is itself the result of a model from some proxy (like a tree ring) and a desired observation (like temperature). The modeled—not actual—temperature is fed to an analysis, which in turn models the modeled observations, which in turn is physically modeled. Get it?

Measurement error is a problem is two ways. Historical measurement error can lead to built-in model biases: after all, if you’re using mistaken data to build—or if you like “inform”—a model, that model, while there is a chance it will be flawless, is not likely to be.

Plus, even if we use a MOS-type system for climate models, if we check the MOS against observations measured with error, and we do not account for that measurement error in the final statistics (and nobody does), then we will be too certain of the model’s accuracy in the end.

In short, the opportunity for over-certainty is everywhere.

Read Part I

Today’s post is at Pajamas Media: President Obama To Make Poverty Permanent.

The Obama administration will create a new definition of poverty, one that changes as a function of how much money everybody has. The more everybody has, the higher the poverty level.

This, of course, guarantees that “poverty” will always be with us.