Thursday, June 23, 2016

Liberals Embracing the "No Fly" List, Conservatives Half-heartedly Rejecting It

I’m sad to see a couple of things that are happening right now.

People who call themselves “liberal” are embracing the no-fly list, because it’s politically convenient. It allows them to grandstand on gun control, and apparently that’s enough for them to betray their core values.

People who call themselves “conservatives” acknowledge that depriving people of their gun rights without due process is wrong, but don’t go on to acknowledge that depriving people of their right to fly without due process is also wrong. They should be calling for a repeal (at least a drastic pairing-down) of the no-fly list, not dictating when due process does and does not apply. (“Dictating when due process does and doesn’t apply”…hmm. Isn’t there a word for that?)

If anyone thinks that citizens should be deprived of their rights without due process, they should say so explicitly and explain why. But they probably shouldn’t be calling themselves “liberal”, which connotes a principled belief in liberty (individual rights, due process, etc.). And they probably shouldn’t be calling themselves “conservative”, which connotes respect for the constitution. Isn’t a “no fly list” technically a bill of attainder, which is explicitly forbidden in the constitution?

Maybe you think the government should be constrained by certain principles (due process, enumerated powers, prohibitions  on laws against speech and religion, etc.). Say so plainly, but you have to stick with those principles when they’re inconvenient, not just when they help you. Maybe you think the government should be able to do whatever seems like a good idea at the time. Once again, say so plainly, but don’t ever appeal to “principle” when government does something you don’t like. Appealing to a principle you don’t really believe in is deeply insincere.  

Maybe I’m overthinking this. Maybe every policy opinion is chosen ad hoc, and almost nobody feels constrained by any principle whatsoever. And I guess that’s the part that makes me sad.

Monday, June 20, 2016

Press a Single Button, Produce All the World’s Food

This is an extreme example to illustrate how to think about personal income and how it relates to a worker’s productive output. Imagine that agriculture becomes so automated over the next century or so that the entire world’s output can be produced by pressing a single button. Yes, it’s silly to imagine that the button-pressing could not be automated as well, but bear with me. The entire world’s agricultural output can be done with a single person who has no particular skills.

Think for a moment about our single button-pressing laborer. How much does he earn? Should it be trillions of dollars, since he creates so much of the world’s total value? He creates all of a necessary ingredient to a functioning economy (and a living human species, for that matter). But that’s not the right answer, because he’s easily replaceable. He is not uniquely qualified. *Anyone* can push that button (for the sake of this example). So you only need to pay him enough to attract him to that job. He needs to be paid just as much as any other unskilled worker with a similarly difficult (which is to say similarly easy) job. He’ll earn roughly what an unskilled landscaping worker or dishwasher earns per unit of time worked, because the product of his labor, though massive, would be produced whether we had him or not.

Hopefully this simple example points out that you can’t just look at the value of the final product and claim that the worker produced it all. You have to talk about a person’s *marginal* productivity, which is the difference between what you’d get *with* vs *without* that person in the world. A person’s income depends strongly on this, the marginal product of labor. In no sense can you simply map a person’s labor onto a final product, determine the value of that product, and thus quantify the worker’s contribution. In most cases, some or most of that final product would be produced anyway by someone else. In other cases (say, a CEO of a company who creates a truly novel product, one that wouldn’t exist but for her/him), the final product would be substantially different without that person.

Now we’ll change the example a bit. Suppose again that there is a machine that produces all the agricultural output in the world, but it requires quite a lot of skill to use. And there’s no upper-limit to this skill; the very best “agriculture machine operator” in the world isn’t identical to the median or 80th or 99th or even 99.99th percentile. Suppose there is variation all the way to the top. There are so many idiosyncrasies and complexities to running the agriculture machine that you absolutely need the very best, very most productive person in the world to do it. The relative value of the very best and the second best might be only a 1% difference in productivity, but that translates into tens of billions of dollars. Humanity should be willing to pay something comparable to make sure they attract the very best person to this job. If the very best machine operator can produce $100 billion more in output each year than the second best, then getting this person for a $50 billion annual salary is an absolute steal.

In the simple button-pushing case, where an unskilled worker can do the job and it’s nearly impossible to screw it up, humanity will be just as well off if the current button-pusher ceased to be. In the other example, if you don’t put the best guy in the world in that job, humanity really will be a great deal worse off for it.

I’m not seeking to morally justify income inequality with this post, although I personally think that income differences that are driven by true productivity differences are perfectly fair in a moral sense. My goal with this post is far less ambitious. I’m trying to get the reader to consider *why* these big differentials in income exist. What is missing from many rants against inequality is any *theory* about the determinants of income. You can’t possibly know that something (like a person’s income, for example) is too high or too low unless you have some kind of theory telling you what it should be. If someone actually had such a theory, and it told them that everyone (at least every identifiable class or sufficiently large grouping of people) earned basically what the theory said they should earn, it would be a lot harder to claim that inequality is a big problem. If someone’s theory tells them that, say, farmers are underpaid but bankers are overpaid, then we can open up that theory to scrutiny and see if it’s failing to capture something important. This can be an enlightening exercise. It needs to take place.


World gdp = $75 trillion in nominal terms, $108 trillion in real terms (adjusting for purchasing power).

World Agriculture = 4.5 Trillion in nominal terms, 6.5 Trillion in real terms.

But it’s kind of silly to talk about the “total” value of agriculture. The first 90% is probably necessary for humanity to exist at its current population. It's silly to talk about its "total value," which you might argue is infinite. The next 10% is worth quite a bit less than 1/9th of the first 90%. This last 10% goes into making our food tastier (feeding cattle and making sugary snacks), not meeting our basic caloric needs. An additional 10% beyond what currently exists possibly has negative value if you account for health issues related to overeating or the costs associated with storing borderline-useless food and dumping spoiled food. I acknowledge I am playing fast and loose with the marginal value of food in my post; if the extra food produced by Mr. Super Producer in the 4th paragraph isn’t very valuable, then his compensation will obviously be less than I imply above. Hopefully you can look past that and acknowledge the point about the marginal product of labor. You can always change the example to something that doesn’t have a steeply declining marginal value.

Another aside. The examples above describe a ridiculous amount of productivity coming from a vanishingly small proportion of the population. These scenarios are not absurdly far off, if you think in relative terms. Two hundred years ago almost everyone in the United States was a farmer; today almost nobody is. To a crude-but-relevant first approximation, the percent of the US population who were farmers has gone from 100% to 0%. The developing world is seeing dramatic economic growth, so presumably (I should say hopefully) they will follow a similar trajectory, so that what’s true of the US will eventually be true everywhere. The point here is that absurdly few people are now doing the work of what used to be absurdly many people.

Libertarianism as a Cease-Fire

I could be wrong about this, but I strongly suspect that most people dislike having bad policies imposed on them more than they like imposing their favored polices on unwilling citizens. Most Hilary voters dislike Trump more than they like Hilary, and vice versa. Most secular liberals would like the option of escaping a religious indoctrination of their children *more* than they like being able to impose a secular education on their religious neighbors’ children. Likewise, most religious parents would prefer the ability to escape a secular indoctrination for their children over the ability to impose a religious education on their neighbors’ children. Many of us harbor authoritarian attitudes, but mostly we prefer the preservation of our own freedom over the ability to restrict other people’s freedom.  Unfortunately, voting is cheap. If people could charge for the privilege of imposing hated policies on them, and we had to pay for that privilege, most of us wouldn’t pony up. We’d for the most part leave our neighbors in peace. Since voting for a controversial policy is so inexpensive compared to  the actual cost (as judged by those who would rather not bear that cost), society as a whole ends up with more government than it collectively wants.  

Libertarianism is a truce. We could have a big fight over what policies will be imposed on everyone and bitterly contest every little issue that comes up in this fight. Or we can avoid the fight altogether, at least for those cases where there’s no need to have one single policy for everyone. We don’t all need to have the same health insurance plan with all the exact same terms (possibly provided by a single shared insurer, as many have proposed). We don’t all need to have the same schooling with the same curriculum. We don’t all have to be subject to the same “protections” from potential employers. You can always insist on your own employment terms that are stricter or less strict (corresponding to a lower or greater chance, respectively, of getting hired) than some default set of protections.

So why do we have to fight over all these issues? Why don’t we just call the cease-fire, given that we mostly prefer our own freedom if it's purchased at the tiny cost of granting other people their freedom? What’s going on here?

Perhaps there are some cases where we all have to share the same policy, and I’ll grant that for the moment. We as a nation all need to have the same shared “nuclear deterrence” policy, and I probably need to share the same environmental policies as my immediate neighbor (though certainly not with someone a few states over). Sure, there are “public goods” issues like these, where some kind of coordination (perhaps even forced coordination) is required. But this describes a tiny fraction of what the government actually does. And many of these public goods issues are very localized, at the state or city or even subdivision level. There is no role for a federal government, and indeed a single federal rule is inappropriate for diverse communities with diverging needs.

Perhaps people are extremely cynical when it comes to their voting behaviors. Suppose team red and team blue sense when they are likely to get their way. Why bother calling a cease-fire when you can just have your way? As in, “We *could* grant religious parents the freedom that we want for ourselves, but we’re so likely to get our policy of ‘secular education for all’ that it makes no sense to grant this concession.” But in this case, there’s still an opportunity for a general cease-fire, as opposed to a one-off cease-fire. The cynical secular liberal in this example says to the conservative religious parent, “We’ll grant you the freedom to educate your children as you please and you’ll grant us the freedom to ingest whatever chemicals we like without police interference.” Even if one team senses that they are likely to get their way on a majority of policies, a cease-fire still makes sense. The pendulum swings both ways, so a general, long-term cease-fire makes sense as a way to prevent future removals of liberty.  Seen this way, imposing unwanted policy on your neighbors from the opposite team sets you up for an everlasting cycle of recriminations and retributions. They’ll get you back when it’s their turn. Even if one team senses that they will mostly get their way for a very long time, a ceasefire might still make sense as an insurance policy against a few really bad reversals where the other team gets its way. Also, most people find themselves in the minority on *some* issues, where they prefer to keep their freedom while a majority (perhaps even a large majority, perhaps crossing over traditional left-right/conservative-progressive lines) prefers to deprive them of that freedom. I don’t know how most people value “taking away other people’s freedom” compared to “losing my own freedom,” but I suspect it would require a very large amount of the former to compensate for a small amount of the latter. A cease-fire still probably makes sense unless you are nearly certain of maintaining total hegemony for several decades. Libertarianism offers us a fair truce. Simply limit the power of government to a few very basic functions, and you won’t have most of these conflicts.

Maybe people simply don’t give any thought to these things. Perhaps every political question gets its own ad hoc answer, with no sense of internal consistency whatsoever. Perhaps there is no consideration for opposing policy preferences, as in “My policy is plainly ‘right’ and yours is plainly ‘wrong.’ Any ‘preference’ for something else deserves no consideration at all.” While a person exhibiting this behavior in normal life would be considered a narcissist and a sociopath, it’s fairly common in politics (the personal politics of voters and the “professional” politics of politicians). In this kind of environment, where people have the attention span and the manners of small children, it may be impossible to call upon voters to sign a general cease-fire. Even so, here is the grand compromise, if anyone wants it. It's essentially a variant of "live and let live" or "do unto others," applied to politics.

Am I being unfair in framing my policy prescriptions as “neutral” and the mainstream left vs. right policy prescriptions as warring factions? I don’t think I am. I’m merely choosing “government activism requires overwhelming justification” as my default position, along with agnosticism over which of two warring factions is really “right” in some theological sense. I don't think any other default position makes a lot of sense. If A wants to impose a hated educational regime on B’s children, and B wants to impose a hated educational regime on A’s children, then splitting the difference means getting the government out of education. It doesn’t mean taking some kind of “average” of A and B’s policy regimes and imposing the middle ground policy on everyone. Libertarianism gets unfairly tagged as some kind of extreme outlier, but in reality it’s the most neutral possible territory for many policy conflicts. Many of these conflicts can be entirely avoided with a libertarian truce. The conflict makes us all worse off, and often so do the resulting policies. 

Tuesday, June 14, 2016

When “Public Heath” Isn’t Public

I don’t quite know the meaning of the term “public health.” Googling the definition hasn’t helped me, because in context its definition is never consistent. The Google definition is “the health of the population as a whole, especially as monitored, regulated, and promoted by the state.” Maybe this vague definition is the right one, because whenever there is some kind of general health problem (like rising obesity or drug overdoses) the argument for government intervention always starts with “This is a public health issue!” Notice that this isn’t really an argument, in the sense that it’s totally circular.

I think “public health” ought to mean something like, “health issues by which one actor can affect the general health of the population.” Basically it should be a reference to the effect of a person’s behavior on *other* people’s health but not his own. This is actually a radically different definition than the one Google gives and the one that (I *think*) most people have in mind when they use the term. If I over-eat, or adopt a dangerous drug habit, or smoke, or skateboard, then it’s not really a public health issue. In those cases I’m only harming myself. Contrived counterexamples aside, none of those behaviors significantly affects “the public.” A single instance of, say, a risky prescription painkiller habit only affects the user. I don’t think it’s meaningful to count up all the individual instances of “private health” problems and say that the summation converts it to a “public health” issue. One person deciding to roll the dice with his own existence is a private health issue; a thousand (or a million for that matter) doing the same is *still* a private health issue, just one that many people have in common.

On the other hand, if I drive recklessly, or dump pollutants into the drinking water supply, or fail to immunize myself or my children, or if the government implements a policy that makes food or medicine very scarce, these could legitimately be called public health problems. They are instances of one party’s behavior affecting another party’s health. Some kinds of intravenous drug use could also be considered public health issues, considering that these drug users are extremely prone to blood-borne pathogens that find their way into their sexual partners or people who share their injection equipment. One could quibble about how in some of these cases the relevant “public” voluntarily puts itself at risk and in others it doesn’t, but at least in this case including the word “public” in “public health” is meaningful.

I recall sitting through a debate on drug legalization. The person who was pro-legalization finished his argument, and a person behind me said indignantly to her friends, “He’s ignoring the public health issues.” No, he was not. He was explicitly arguing that individuals have the right to harm themselves; they have the right to put whatever chemicals they like into their own bodies. (He also gave the other standard arguments for drug legalization, which I won’t list here as I’ve discussed them in detail elsewhere.) He was arguing, without exactly using my terminology, that there is a difference between public and private health, and that you don’t convert the former to the latter just by adding up the instances across a big population. The confused person behind me was trying to ignore this difference. She was trying to conflate two different things and paper over the difference by adding the word “public” to the word “health”. (Perhaps she had in mind that intravenous drug users infect their partners, in which case I’m being terribly unfair for the sake of making my point. But this was not the only time I’ve heard “public health” used in this manner, so I won’t refrain from using this as an example.)

I think there are four different types of health issues that vary in their degree of public-ness, and they should all be treated separately. We should drop the term “public health” altogether and explicitly state what kind of issue we are talking about. The first of the four kinds is the situation in which my behavior harms myself and no one else (or the harm to others is minimal at any rate). I dedicated a paragraph to this above, so I won’t belabor the point here.

The second kind is the situation where I can control my own exposure to the risk. If I have promiscuous sex or engage in IV drug use with shared needles, then it’s true that someone can harm me. But I can *decide* whether I’m exposed to this risk or not. It’s perfectly fair to treat this as a kind of public health issue, because you may want to know how these kinds of infections spread and how to stop them. However, we need to keep in mind that these populations consent to the risks they are taking. Another example is a polluting factory that is the only source of economic value for a community. Let’s suppose (not unreasonably) that everyone in the town has the opportunity to move away if they wish to. Everyone is there of their own volition. Living near a polluting factory is worth the cost of inhaling pollutants, because you get to work in a factory or sell goods and services to the factory workers. It may be meaningful to call the factory a public health hazard, but it needs to be kept in mind that everyone is better off *with* the factory than *without* it. Also consider driving. Not reckless driving, but normal driving. There is a non-zero chance that you will kill someone every time you drive somewhere, but everyone consents to this risk under the assumption that everyone else obeys various safe driving practices (obey traffic laws, avoid debilitating drugs, etc.). It would be great to reduce the risks of these behaviors, but keep in mind that taking these hazards as a given, people consent to them. People engage in recreational drug use or normal driving or live near factories because, in their view, the benefit is worth the risk.

A third kind of health issue is one where you can affect someone’s health involuntarily. Suppose the IV drug user above doesn’t inform his wife about his habit and infects her with HIV or hepatitis. Or suppose a factory agrees to abide by zoning laws and pollution regulations, but then clandestinely dumps a dangerous dose of pollutants into the water supply. Or suppose someone drives their car extremely recklessly, perhaps while under the influence of drugs. It’s fair to say these are all public health issues, because a party is causing harm to a non-consenting party. These are cases where the actor who does harm could restrict their contribution to the hazard, but chooses not to. The harmed party can’t reasonably restrict their exposure to the hazard. There is a “bad guy” in this story, and it’s fair to sanction these kinds of behaviors so as to limit the hazard. Moreover, unlike in the next case I will discuss, sanctioning the hazard-producer *works*.

A fourth kind of health issue, and one that I consider true “public health”, is the spread of communicable diseases. My case of the IV drug user above is slightly different, because those were cases where someone can limit their exposure to the risk *or* their contribution to the risk. There isn’t necessarily malice or recklessness in this fourth case, as in the case of the polluting factory or reckless driver. There isn’t necessarily a villain, just normal people going about their lives within a population exposed to some infection risk. These are situations where it’s nearly impossible to limit your own exposure to the risk or your contribution to the risk. The instructions for the former are “don’t breathe in” and the instructions for the latter are “don’t breathe out”. Or perhaps there is a less extreme possibility such as “become a complete shut-in,” but let’s suppose that’s so impractical that it’s not really an option for most people. These are the situations that truly justify a public policy. That’s not necessarily to say a government policy. It could take the form of suggested travel restrictions, rather than mandatory ones. Or a billionaire purchasing vaccines and giving them away, as Larry Page did for every child in San Francisco. Never mind that, I’m not going to stand on libertarian principles here. If ever there is a good case for government intervention, this is it. There is a true public good/collective action problem in limiting communicable diseases. The point is not that the travel restrictions protect the individual who obeys them, or that the vaccines protect the vaccinated. The point is to disrupt transmission in general. This forth kind of health issue is one where population effects are important and large. The one-off bilateral transmissions take a back-seat to these bigger population effects. There are tipping-points, by which reaching some threshold of infected people dramatically increases the risk of further infections. There are herd immunity effects, whereby achieving a certain level of immunization (either with vaccines or with people surviving prior infections) dramatically reduces the risk of a pandemic. This is very different in kind from bilateral harms like “I drive recklessly and hit you with my car” or self-harm like “I engage in risky drug use and accidentally kill myself.”

Above I have discussed four very different kinds of health issues. I think we should stop papering over the difference by referring to all of them as “public health.” These different issues have very different policy implications. I did once encounter someone who didn’t accept the difference. He insisted to me that smoking was a public health issue because having friends who smoke makes it more likely that you will smoke. Smoking, in this framing, is more like a communicable disease and less like a choice. I don’t buy his framing of this particular issue, but I won’t discuss it in detail because that’s not the argument I’m making with this post.  I simply want to acknowledge that these four categories might overlap somewhat and that it might be ambiguous which category is appropriate for a given issue. We should be explicitly talking about which category applies. And that’s exactly the discussion that people are dodging when they promiscuously recite the magic words “public health.” I think people just lazily use this term when they want the government to do something about the problem, because “public” sounds like it means it’s happening to all of us. That’s not right. The “public” in “public health” often just means “I counted up instances of private health problems over an entire population.” Simply adding one word to another word does not conjure policy implications out of thin air. That would require making some kind of argument. 

Thursday, June 9, 2016

No Single News Story "Proves" Your Worldview

Stop reacting to singular news events as if they were massive social trends. No single instance of a privileged white kid escaping justice, or of a young black man being abused or killed by cops, or of a cop escaping justice after clearly breaking the law, necessarily indicates a larger social problem. No matter how extreme the injustice, it’s still a single event. And it’s in the news *because* it’s so extreme.

None of this is to say that those larger social problems don’t exist. I’m sure that rich/white/privileged people get better treatment than poor minorities from the justice system, and I’m sure that black people get treated unfairly by the police, and that cops who misbehave get let off the hook too easily. But you probably need some statistics to prove it. Your blinding outrage at a single news story doesn’t quite cut it. Don’t confuse the intensity of your outrage with the probability of your correctness. If anything, the relationship between those two items is an inverse one.

I’ll make the caveat that some “single events” involve the cooperation of so many people that they really do indicate an institutional problem, and these events startle the line between “data” and “anecdote.” For instance, if a police officer *clearly* breaks the law and the entire department covers for him, I recognize that this is strong evidence of a much larger problem. It’s a single news event with dozens of sub-events, so one might treat the many sub-events as data. Then again these can always be rare flukes, so you’re much better off comparing the number of these that you actually see to the number you might expect to see by sheer chance. Also remember that what you see as a clear-cut injustice looks to many people like a borderline case (and to many others a clear-cut case of justice being served). Step outside yourself for a moment when you feel moral outrage coming on. It’s worth shutting off your “moral outrage” mode and turning on your “analytical” mode once in a while.

File this post under, “Stop posting this shit, it makes you look gullible.”

Tuesday, June 7, 2016

The Beautiful Tree, by James Tooley

If you go to the poorest parts of the world, in the dirtiest slums, far away from any government infrastructure, you will find schools. You will see class rooms with very active participation by students and dedicated teachers. You will find dues-paying parents. That’s right. The very poorest people in the world, whose material standard of living is a small fraction of the American poverty line, pay out-of-pocket for their children’s schooling.

James Tooley writes all about this phenomenon in his wonderful book “The Beautiful Tree”. He recently did an Econtalk podcast.  You can get a general outline of the book from the podcast, but the book really fleshes out the details. It really tells an incredible story. (It’s a mere $2 on Amazon for the Kindle, and there are used copies selling for a penny, so expense should be no issue here. And it's available on audiobook if that's what you prefer.)

Tooley has done quite a lot of on-the-ground work in the 3rd world. He went to China, India, Ghana, and many other countries, and he found the same thing everywhere. Government officials told him repeatedly that he would not find any “private schools” for the poor. Some insisted that the very concept was a contradiction in terms; private schools, he was told, are only for the rich. Officials in every country said the same thing. But he found the same thing everywhere: private schools attended by the children of dues-paying parents. The very poor denizens of these very poor countries were *not* being served by their governments. There were government schools, for sure, but the teachers did not teach. Government teachers, Tooley found, were paid the same whether they taught or not. They often slept on the job, or taught a quick perfunctory lesson and then read the newspaper or drank tea for the rest of the day. Often they were totally absent. Or they forced the children to do menial chores for their (the teachers’) personal benefit. The teachers were a powerful political constituency, so it was impossible to impose any kind of discipline or accountability on them. Many children attended the government schools, but they didn’t learn much.

The private schools, on the other hand, were accountable to the parents. If a private school failed to teach, the parents would pull their children out. Teachers were accountable to the head master, who was often forced to fire teachers who were lazy or who had problems with attendance. The students of these schools were better educated than the students of government schools. Wherever Tooley was able to collect data on the performance of the students, the private schools typically produced the higher-performing students. And remember these aren’t swanky, high-end private schools like you would see in America. These are tiny schools in dirty slums, with classes held in re-purposed chicken-sheds. The “selection effect” that you’d see in America (where the kids attending private school are probably smarter in the first place) just isn’t present in the poorest parts of the world.

I want to be a little bit cautious about drawing the obvious conclusions from this book. A model of education that is prevalent in the third world probably has limited value for a rich society like ours. But it should certainly force us to re-think our assumptions. Rather than trying to hold this up as some kind of “proof” of libertarian principles, I want to hold it up as a criticism of progressive ideas about education.

The typical progressive position is that poor families can’t afford to pay out-of-pocket for their children’s schooling. If government didn’t provide schools for these children, they would not go to school at all. Even disregarding the expense issue, private schools for the poor wouldn’t work for other reasons. Private schools have an incentive to slash costs as much as possible and effectively cheat their students. Parents have a difficult time monitoring the effectiveness of private schools. The parents don’t themselves have any expertise in education, so they have no idea whether their children are being effectively educated or not. An attempt to privatize education for the poor would leave us with an under-educated underclass, who have been robbed blind by “for-profit” schools. Tooley’s research in the third world shows us that every aspect of the progressive-left position is false.

The parents in poor countries, who are in fact paying for their children’s education, are far poorer than the poorest American. While schooling was sometimes a significant household expense for these parents, it was manageable, especially considering that the education was well worth the cost. The profit motive actually keeps institutions honest, quite contrary to the standard progressive position. Private schools know that parents will pull their children out of school if they underperform. If they try to cheat their customers, those customers will go elsewhere. This level of accountability is actually absent in government schools, which unfortunately aren’t threatened with the “exit option.” The progressive position is actually quite backwards: accountability *only* exists in the private schools and is absent in public schools. And parents know quite well whether their children are actually learning, even if they don’t know anything about the topics their children are studying. In Tooley’s conversations with parents of private school children, he found that they knew pretty clearly whether their children were *actually* learning English or not (for example). These parents, who are on average less educated and have less access to information than even the poorest Americans, were very savvy about rating their children’s schools. And, once again, the private schools outperformed the government schools. The profit motive creates strong accountability, and this turns out to matter a great deal. You can see it in the final product.

Our institutions aren’t *quite* as bad as those in very poor countries. Average public schools, even bad public schools, are reasonably conducive to learning. I doubt if the wholesale flouting of one’s teaching duties is seen here, at least not nearly to the degree that Tooley and others have observed in the third world. So it might be harder for private schools to improve upon government schools here in America. But we can at least slay some myths about private schools being unobtainable for the poor (clearly they’re not), or how the profit motive is inherently corrupting (clearly it’s not). I don’t want to overplay my hand and say Tooley’s research definitively proves the libertarian position. But I think it’s perfectly fair to say that his research severely discredits the progressive position. If you thought that something was totally impractical or even impossible, and someone shows you that it actually exists, and is widespread, and outperforms your preferred institutional arrangements by a wide margin, then it’s time to reexamine your assumptions. Once in a while you have to step back and say, “This piece of evidence is a complete surprise to me. I would never have imagined it. Something is wrong with my worldview.”

There is a sad note in Tooley’s book. The progressive position on education is so deeply entrenched. It’s effectively a religion. Most international anti-poverty activists (think employees of the World Health Organization or the world bank) admitted that there were problems with the government schools, but rather than allow for alternatives they insisted that all efforts be focused on getting those schools to perform better. Tooley found a working model for education, a way to bring education to the poor. He found it in the wild, too. Anti-poverty activists were almost completely uninterested in his research and hostile to his conclusions. A reasonable person might have said, “Here is something that works. Let’s make it easier to open a school.” And a reasonable policy response might have been, say, removing some regulations on private schools. Some such regulations were quite onerous, and the government schools didn’t comply with them anyway, and non-compliant schools could simply pay a bribe to avoid closure, and (most importantly) the students were better off with a regulation-flouting private school than with no school at all.  But no. The overwhelming response was, “We just need to keep pouring money and effort into getting the governments schools to work better.” When government institutions are really bad, citizens attempt to solve things with markets. Sometimes that works well, and Tooley’s research gives us rich examples. Rather than embracing a working solution, education “activists” effectively told poor third-world citizens, “Go solve an impossible public choice problem. Once you do that, you can have the decent education your children deserve. No fair doing a simple, easily implemented end-run around this impossible problem. I must insist you endure shitty institutions until you fix them.” This attitude is especially sinister when a simple private solution is available.  

Friday, June 3, 2016

Age Is a Major Risk Factor in Drug Overdoses

I noticed something interesting in the CDC’s mortality data. I’ve recently started looking into the age distribution of drug poisoning deaths, as in what’s the average age of someone who dies of a drug poisoning, how sharply peaked is the distribution, has this distribution changed much over time, etc. I also compared this with the age distribution for drug use. (See here.  The age distribution figures start around page 150 or so. This is a big 10 MB pdf, so it may take a few moments to load.) Drug users skew young, but overdose deaths skew old.

Here is what got me thinking about the age distribution of drug overdose deaths. I knew that age is an overwhelmingly powerful driver of mortality rates. Duh!, you say. Obvious as it is, I was surprised to see the magnitudes (see this post on my blog on mortality by age).  My thinking was that if the population of drug users has been aging, there are many more chances for people to die from other causes, and many more chances for a death to be labeled an overdose (even if it isn’t). An aging population of drug users combined with a tendency to misclassify deaths as “drug related” will introduce a spurious increasing trend in drug overdose deaths. (That question requires looking at how the distribution of drug users changes over time, and I haven’t looked into that yet. Perhaps in a future post…) I also wanted to see if the average drug OD decedent has been aging over time. I was expecting to see an aging of the average decedent, considering that the “opioid epidemic” is supposedly exploding into the general population. Drug use is mostly a youth phenomenon, so I was expecting to see that 15 years ago, before the drug death rates started rising, the average decedent was young, and this age should have crept up over time. So these were my “priors,” and what I actually saw did surprise me a bit.

The average overdose death didn’t age by much. The average decedent in a drug poisoning death was 40.9 in 2000 and 42.8 in 2014. A two-year aging doesn’t describe the massive demographic shift I was expecting, of opioids saturating the whole of society rather than just being a youth phenomenon. Poisoning deaths *did* get a little less sharply peaked.

This graph shows you how the drug poisoning deaths in each year are distributed across ages, compared to the distribution of illicit drug use for opioids and then for cocaine based on the SAMHSA drug use survey. (So if you sum up the % for each age, you get 100% for each of these curves.)

Notice the illicit opioid use rates and cocaine use rates (dotted lines) and contrast them with the death rates. This confirms the general notion that illicit drug *use* is a youth phenomenon that most people grow out of in their 20s.  The surprise here was how poorly the death curves and the use curves overlapped. Notice also how the peak of the drug OD line has been moving; while the *average* decedent has only aged about 2 years, the modal (peak of the distribution) decedent has aged about 10 years.

(Note: Use rates look like a step function for part of the graph because the use rates by age are in categories that span 5 years, as in “40-44”, “45-49”, etc. Use rates are given for each individual age up to 25, but after that they are in age groupings. I assumed that the number of total users from the SAMHSA data was evenly distributed over the years within these groupings.)

The above graph is plotting the distribution of *all* drug related deaths, which potentially muddies the waters. Different drugs have different age of use distributions, so let’s fixate on cocaine. It’s a good choice for analysis. It kills a large number of people each year, about 5,000 in 2014. While that makes it a tragic social problem, it’s also makes it a statistically well-behaved social problem because the data volume is sufficiently large for analysis. If you were looking at, say, hallucinogens, there are so few deaths that you couldn’t even analyze the issue, other than doing very crude sums and saying, “It killed six guys last year.” Big social problems are tragic, but at least we can study and understand them. 

There are also a fairly large number of users, so cocaine use shows up in a statistically significant way in drug use surveys. These surveys are done on a random sampling of about 30 or 40 thousand people. Cocaine use is common enough that these surveys can sample its use effectively. Cocaine use is in the 0.5% of total population range for past month use, and in the 1.5% range for past year use, so the magnitudes found in these surveys are significant. Heroin, which kills more people than cocaine (as of very recently anyway), has so few users that these surveys don’t register it very well (past month use of heroin is in the 0.1-0.2% range). Cocaine should be statistically “well-behaved” for the sake of mortality and usage analysis. Also, I’m not muddying the analysis by comparing drug deaths (most heavily driven by legal prescription painkillers) to usage rates (most heavily driven by marijuana use, which doesn’t actually kill anyone). I’m comparing cocaine use rates to cocaine deaths rates.

Here is what I get for the usage distribution and the mortality distribution. Notice again that usage is a youth phenomenon, but it’s mostly older people who are actually dying of cocaine-related drug poisonings. In 2014, the average *user* is only 33, but the average decedent is 43, ten years older. People 30 and under make up about 50% of users but only 18% of overdose deaths. For people 40 and under, these figures are 70% and 41%. For people under 20 these figures are 12% and 2%. If you like, you can look at this in the other direction. People 50 and over make up 17% of users but 36% of overdoses. People 40 and over make up 31% of users and 61% of deaths. Older people die of cocaine use *way* out of proportion to their usage rates.

I also want to show you a mortality picture (as in “deaths per 100k”), but there are important caveats to this. It’s hard to know what the appropriate denominator is for calculating cocaine-related mortality. Do I assume *all* past year users are at risk? In that case, I’d divide the number of cocaine deaths in 2014 by the number of past-year users in 2014. But wait, the number of past month users is something like 1/3 the number of past-year users (giving the lie, btw, to the notion that this drug is hopelessly addictive). Maybe it’s just this population of continuing users who are at risk. Surely the hard-core addicts are in this group, not the “past year use” group. Naturally, this will give me a higher mortality, because I’m dividing the same 2014 cocaine death count by a smaller denominator. Anyway, I’ll just plot them both so you can see what this looks like.

Again, you can see clearly that cocaine-related mortality is heavily age-driven. I’m plotting the overall (all-cause) mortality at each age for comparison. So what’s going on here? Are older people just more susceptible to drug overdoses? Or are older people just more likely to die *for any reason*, so if cocaine is present in the toxicology screening it will be blamed for the death? In this latter explanation, there are just more older corpses that happen to have cocaine in them, even though it had nothing to do with the cause of death and even though living bodies with cocaine in them tend to skew younger.

If you like looking at the underlying numbers, the following data table is the basis for the previous two charts. Deaths are from CDC data files, use numbers are from the SAMHSA survey linked to above:

This next paragraph is a bit of an aside, but it relates to my quandary about calculating mortality rates. “What is the risk of death from cocaine use?” becomes an almost philosophical question, because it’s impossible to know what the relevant denominator is. This is a general problem for quantifying the risk of drug use. One could simply divide the number of death by the number of users in order to get a very rough-and-ready estimate of risk, but that’s probably not right. There are people who dabble in drug use for very short periods and then never touch them again (as you can see if you compare “past month”, “past year”, and “lifetime” usage). Surely it’s the continuing users who are really at risk, but then maybe it’s only a subset of *these*. Perhaps even addiction and dependence per se are not dangerous, it’s just that some individuals are *very* poorly informed and engage in unnecessarily risky behavior. The risk profile of cocaine users may be very heterogeneous; they don't all face an identical risk of death. It’s nice to have a solid easy-to-calculate figure in mind when you’re thinking about these issues, but you always have to remind yourself that this figure doesn’t mean what it appears to mean.

I worked up the above charts for prescription opioids too, and they look very similar. Once again, there is a 10-year difference between the average illicit user (about 33) and the average decedent (about 43). But I’m cautious about drawing any conclusions from these charts and mortality figures for opioids. I suspect that it’s wrong to divide the opioid related deaths by the number of illicit users, because the at-risk population is the full population of people who use opioids, not just those who use them illicitly. Remember that many people have legal prescriptions and legitimate medical need for painkillers; the usage rates from the SAMHSA survey only measure illicit use. My preferred explanation for the recent increase in opioid deaths is that normal users are accidentally mixing them with other drugs, not that we’ve created a growing population of high-risk drug addicts. We don’t see any increase in illicit use of opioids over time in the drug use surveys, so I think my preferred explanation makes more sense. So anyway, I *could* calculate an “opioid mortality per illicit user”, but it would be irrelevant because I’d be using the wrong denominator.

I looked at the average age of a drug overdose for the dozen most lethal drug categories, and I saw roughly similar patterns for all. The average age of decedent was in the 40-42 range for all categories, and there was a slight upward trend in age for 2000 to 2014. Heroin was the closest thing to an outlier, with a moderately young average age of death of 38. And “psychostimulants with potential for abuse” (meth and ADHD medicine) was the closes thing to an outlier in terms of the trend, with the average decedent aging from 36 to 43 over the 2000-2014 period. I didn’t do a thorough distributional analysis for each one of these, mostly because I don’t have the relevant corresponding drug use data (for all I know it doesn’t exist) at that level of detail. But considering the average age of decedent is similar for all these drug categories, I'd be very surprised if the result were any different. I suspect this general patter of younger average users and older average decedents holds up pretty well.

"So what?" you may be saying. Is this just a pointless exercise in data manipulation? No, I believe there are relevant lessons for drug policy here. For one, I think this supports my view that a lot of “drug overdoses” just aren’t. That is, many of these people are dying for other reasons related to age and health and they are wrongly being labeled as drug poisoning deaths. (See my previous post here on illnesses listed on the death records of drug poisonings.) It’s not smoking gun, but it pours a little cold water on the notion that there is a runaway opioid epidemic. The “spurious trend” story looks more credible in this light. But put aside the spurious trend story for a moment. Even supposing that *all* these drug poisoning deaths are correctly labeled and there’s no spurious trend or upward bias in the totals, there are still some policy implications. This is another case where a targeted deterrence policy makes a lot more sense than a general deterrence policy. If people in their 30s, 40s, and 50s are at a massively higher risk than people in their teens and 20s, we should warn them. “Just because your heart could take it at 20, doesn’t mean your heart can take it at 40,” might be a good slogan for a targeted anti-cocaine public service announcement. Or for that matter, and anti-meth or anti-opioid or anti-heroine public service announcement. It's trivially true that anyone can die of a drug overdose, but the magnitude of the risk is *very* different for different ages.

It would be interesting to see what the use vs mortality figures look like for legal opioid use, or for benzodiazepine use (another leading killer drug). If I manage to pull that together somehow, I’ll turn it into another post.

Thursday, June 2, 2016

Who is Driving the Recent Increase In Painkiller Overdoses: Addicts or Normal Users?

I’ve been looking over the CDC’s mortality data in great detail to see what insights I can gleam from it. One of the open questions is whether most of the drug overdose deaths (which have supposedly increased dramatically over the past 15 years) are from hard-core drug users or from normal users who don’t have a serious drug problem but just get careless one day and poison themselves. This distinction between hard-core and normal users might make less sense for heroin or cocaine, where an overdose probably indicates a serious drug problem. But the difference is very salient for things like prescription opioids and benzodiazepines, for which most users are normal people with legal prescriptions. This is a big deal, because different answers to this question can have different policy implications. Most of the media reports of the rise in prescription painkiller overdose deaths assume that loose prescribing habits have created a lot of addicts, who then turn into problematic drug abusers. An alternative narrative is that loose prescriptions per se don’t turn people into addicts, but suddenly cutting people off from their doctors when they “look like drug addicts” might induce these people toward risky behaviors, like seeking drugs on the black market. (Doctors can get into serious trouble for prescribing opioids to people who look like they’re abusing them, so doctors are extremely cautious and often do cut people off from their supply of painkillers if they see any suspicious behavior.) Another explanation is that the increase in deaths isn’t driven by an increase in addiction or risky recreational drug use, but is rather driven by people carelessly mixing drugs that they have a legal prescription for, as well as having a legitimate medical use for.

I had an idea that I thought would allow me to determine how many of these deaths were normal/legal users and how many were addicts with a serious drug problem. In the CDC death records data, there is room for up to 20 causes of death to be listed, and drug abuse disorders are often listed as contributing causes of death. These are cause of death codes F10-F19.9, for anyone who’s curious. They all start with “Mental and behavioral disorders due to use of…” and then list one or more drug types and “withdrawal”, “harmful use”, etc. At first blush, this settles it. There’s a code for whether the decedent had a serious drug habit, so just calculate the percent of drug poisonings that have such a code listed on the record. It’s a simple counting problem that Excel’s sumifs() or countifs() formula could handle. This should be able to tell me if the recent rise in opioid deaths is mostly attributable to people with a serious drug problem or not.

Unfortunately, it looks like these F-codes have not been used consistently over time. In 2000, only 29% of heroin overdoses deaths and 32% of cocaine overdose deaths had such a code; in 2014 it was 58% and 59%. I don’t know what the appropriate level is for these numbers, but my guess would be that someone who overdoses from one of these drugs is probably someone with a serious drug problem. I’m thinking both the 29% and the 58% numbers for heroin are low. The proportion of these overdoses that are due to serious drug users has supposedly increased by a factor of roughly two (1.99 for heroin and 1.83 for cocaine). I see a similar, if slightly larger, magnitude for other opioids, benzodiazepines, methadone, and “psychostimulants with potential for abuse” (meth and ADHD medication). If this increase was very different for heroin/cocaine than it is for benzodiazepines and prescription opioids, I might have believed these figures. But it looks like there is a general upward trend in the use of these “f-code” causes of death that probably has nothing to do with an actual increase in addiction rates. My conclusion is not that the proportion of drug poisonings due to serious drug addicts has increased; rather I conclude from this that the death record data isn’t very good and contains many spurious trends. I’m chalking this one up as another of those “data quality issues” I mentioned in this earlier post. It’s too bad, really, because the coding system actually has the potential to answer the questions I’m asking of the data, if only it were used properly. But to get accurate answers, the coding system would have to be used in a consistent way over time and across the country (even across different countries). This necessary consistency is sorely missing.

Why does this matter? If a life is tragically cut short by a drug poisoning, who cares whether it was a helpless addict or a careless normal user with a legal prescription? A corpse is a corpse, right? It actually matters quite a bit for drug policy. Popular media reports tell us that the increase in opioid prescriptions is creating an addiction epidemic, and these helpless addicts, their will having been overtaken by drugs, poison themselves. If this story is right, then some kind of massive drug abuse treatment initiative might be in order. (I don’t think this story is correct, because we don’t see any increase in illicit use of prescription painkillers in drug use surveys, and we don’t see a substantial increase in the number of people with substance abuse disorders.) Another explanation is that drug use, even drug dependence, is mostly safe, but addicts turn to risky behaviors when they are suddenly cut off from their legal supply. In this story, we should make opioids *more* accessible, not less, because it is the *lack* of access that is driving people to risky behaviors. My preferred explanation is that most of the drug overdoses are coming from normal users with legal prescriptions, who accidentally take too many pills (single-drug overdoses are rare) or mix them with benzodiazepines, alcohol, or some other drug that causes a fatal interaction (multi-drug poisonings are much more common). In this story, these additional overdoses actually represent a very small hazard. Considering that there are roughly as many legal prescriptions each year as there are adults in the US, 10 to 20 thousand deaths represents a risk of only about 1 death for every 15,000 prescriptions. (20,000 deaths /260,000,000 prescriptions gets you 1/13,000; in the previous sentence I’m being imprecise on purpose because I think the underlying figures are imprecise.)  This is probably an acceptable risk for someone who is suffering severe chronic pain, especially if it is a risk that the user can actively mitigate (say, by avoiding dangerous drug combinations and taking only the recommended dosage). In this view, the policy implication is a stern warning from the doctor (perhaps reinforced by the pharmacist, and then again by the drug’s packaging), but blanket restrictions on opioid prescriptions are unnecessary. If these deaths were accurately coded, we would have been able to see whether the increase in deaths is driven by hard-core addicts or normal non-addicted users, and we’d have a better idea of the policy implications.

Drug Overdoses vs Chronic Illness: What is Driving Increasing Opioid Death Rates?

I’ve written several posts on the recent dramatic increase in drug poisoning deaths. I think it’s still an open question whether there are *really* more drug overdoses or if there are just more people who happen to die with high opiate levels in their blood because there are so many more people using prescription painkillers. It’s possible that someone with a high-dosage prescription for painkillers will drop dead for some unrelated reason, and a lazy/incurious/ignorant medical examiner will mark it as a drug overdose because that’s the most handy explanation available. With any death, a human being using their fallible judgment has to ultimately decide on the cause of death, which ultimately gets marked down as *the* underlying cause of death in the Center for Disease Control’s mortality database. It’s always possible that one of many contributing causes gets singled out as the one underlying cause. Or perhaps a person is stricken down by an invisible cause (say a heart arrhythmia, which won’t leave any physical sign), but something visible, like a toxicology screening showing elevated levels of opioids, conveniently explains away the death.

The CDC maintains an excellent database, which lists every single death in the US for every year going back to 1968. (See the Mortality Multiple Cause Files here.) Each row in these files is a single death record, listing the age, gender, and other demographic variables, along with the causes of death. A single “underlying” cause of death is singled out, and then there are 20 spaces to list contributing causes of death. For example, the underlying cause might be “drug poisoning” and in the 20 spaces listing the contributing causes of death, it might say, “heroin”, “alcohol”, and “benzodiazepines” (plus a bunch of blanks). (The CDC files actually list codes, not the named descriptions. You need a file that lists the codes and what they mean to actually decode the CDC’s file.) Knowing that this database even exists, we’re off to a good start. Superficially it looks like we have all the information we need to determine how many drug overdoses are happening each year, and from which classes of drugs they are coming from. If one naively counts the drug poisoning deaths, there does indeed seem to be a recent rapid increase in drug-related deaths, particularly those related to opioids.

However, many of these “drug overdoses” also list various kinds of organ failures, illnesses, and vague infirmities among the up to 20 causes of death listed on the death record. That raises a serious question about what killed many of these individuals. Take an individual with “cardiomegaly.” Perhaps this really was a drug overdose and an irrelevant medical condition was simply listed on the death certificate. But it could be the other way around. Maybe this person had a heart condition that killed them, but an irrelevant drug habit was listed on the death record. Or possibly an underlying medical condition *did* contribute to the person’s death, as in the drugs would not have been lethal to a healthy individual. (Cue philosophy lecture on the nature of causation in a world that is dense with causal factors.) Or perhaps someone’s drug habit damaged his health and organs, ultimately contributing to his death. Some of these cases are true overdoses, some are not overdoses per se even though they are related to societies drug problem, and some have nothing whatsoever to do with drugs. I think we need to be very cautious about how we interpret this data, especially since there is a general bias toward exaggerating the harmfulness of drugs and blaming them for things that they didn’t do.

Now, some of these have an obvious connection to heroin use or an opioid overdose, and I’ve marked them in red. “Respiratory arrest” and “anoxic brain damage” sound like the effects of an opioid overdose. Usually these people die because respiration is suppressed so much that they asphyxiate. “Chronic viral hepatitis C” sounds like infection from intravenous drug use. I’m willing to chalk such a death down as indicative of society’s drug problem, but I think it’s fair to say this casts a lot of doubt on what killed these people. Were the hepatitis C deaths *really* drug overdoses, or were they cases of gradual organ failure?

It’s very hard to quantify this uncertainty, but here’s how I tried. When I counted the number of “drug poisoning” records that have one of the causes listed in this table, excluding the ones marked in red, I get that about 20-25% of records have at least one of these causes. (Don’t sum up the numbers in this table to get a total. That will overcount because a death might have, say, three of these causes listed on the death record and thus will be counted three times in such a total.) A more precise estimate for this figure would require someone to go through the list of contributing causes of death and saying, “This is a common drug-related illness, this is not, this one is, this one isn’t…” The full list of contributing infirmities is much longer than the table above; there are about 1,000 different causes of death to sift through that are related to organ failures and other infirmities. Someone with far more expertise on drug pathology would need to do this sifting.

I looked at another item that’s relevant to this discussion: How many deaths had a drug listed as one of the contributing causes of death, but weren’t counted as drug overdoses? (In other words, these didn’t have X40-X44, X60-X65, X85, or Y10-Y14 listed as the underlying cause of death code. For example, some of these had “other opioids” listed as one of the 20 causes of death, but the underlying cause was cancer or a heart attack or an automobile accident.) It was very rare to have any drug poisoning mentioned as any one of the contributing cause of loss codes, but *not* have the underlying cause of death be a drug poisoning. For example, only 1.7% of deaths that mentioned heroin (cause of death code T40.1 ) were *not* counted as drug overdoses. This number was 4% for methadone, 2.6% for “other synthetic narcotics”, 3.9% for “other opioids”, 4.3% for “other antidepressants.” When I averaged this figure for all the most lethal drugs (which captures an overwhelming majority of drug-related deaths), I get about 5% for this figure. So in other words, 95% of the time when there’s a drug on the death record, they count it as an overdose. But a significant proportion of drug poisonings list another type of illness as a contributing cause of death (25% by my reckoning, and the real number is probably quite a lot higher). I take these together to mean that there is a significant bias in favor of labeling deaths “drug overdoses” if there’s any kind of evidence of drug use.

If there really is a tendency to misattribute the cause of death to a drug poisoning, it could go even deeper than it appears. I’ve described above how many deaths are labeled in a way that leaves the underlying cause of death ambiguous. But many of the deaths that aren’t ambiguously coded could still be in error. If a sudden heart attack or pulmonary embolism kills someone, and there is outward evidence of opioid use, a lazy or incurious medical examiner might simply say, “Code it as X42, drug overdose. Done! I’m going to lunch.” From a previous post, autopsies are missing in about 20% or more of these drug poisoning cases, and some causes of death aren’t obvious even *with* an autopsy. Pathology of Drug Abuse, a popular textbook on the topic by Steven B. Karch, goes into great detail on this point: it’s easy to misclassify a death as a drug overdose. If a large proportion of these deaths are misattributed to drugs when they are really some other cause of death entirely, then the recent moral panic over opioids is overblown. It could be an exaggerated problem, or not a problem at all (at least not an *increasingly severe* problem, as we’ve been led to believe.) In short, if we are mistaken about the magnitude and causes of a problem, we will implement the wrong set of policies to address that problem. Based on what I’ve seen, this misattribution problem is a big deal.

I want to make another slightly different point about the policy implications of all this. It’s possible that drug use is relatively safe for most people, but risky for people with certain medical conditions. It is worth considering the implications of this for drug policy. If the risk of a fatal poisoning is different for different people, then there is a lot of low-hanging fruit to pluck. Instead of deterring drug use per se, a policy of deterring drug use for high-risk individuals could be more effective and ultimately save more lives. Public service announcements that warn against the dangers of drugs in general are bound to backfire, because people who encounter drugs and come out unscathed will learn that the government is just lying to them. But a public service announcement warning that people who experience sleep apnea are especially prone to drug overdoses might be taken more seriously. “Sleep Apnoea” and “obesity” appear frequently on the death records for drug poisonings, and it’s not hard to see why this might be the case. Opioid overdoses suppress respiration, and the decedent asphyxiates. Someone with sleep apnea or obesity, who has trouble breathing during sleep anyway, will be especially susceptible to suppressed respiration.

There’s a limit to what I can do with the CDC’s death record data. If these data are miscoded, as I’m arguing in this post, then the information I need to answer the relevant questions doesn’t exist. Someone would have to do a thorough investigation of a large sample of drug poisonings to see if a potential cause of death was missed. I’d like to know just how many of these deaths are *actually* drug poisonings, and I’d also like to know what medical conditions are risk factors for drug poisonings. Both would help in crafting good drug policy.

Wednesday, June 1, 2016

Who Holds “Market Power”? Who Sets Wages?

Suppose you work for an employer who pays you roughly the market wage for your labor, and there are several other employers who would have you for a roughly comparable compensation. Can your employer harm you in this scenario? Not really. If your employer tries to pull some shenanigans whereby they capture more of the value that you create for them, say by cutting your pay or benefits, you can simply go work for another employer. Even if they flat-out fire you, you’ll be back on your feet soon enough. When you’re earning close to the market wage for your labor, it’s very hard to exploit you, and it’s implausible that *as a class* people like you are being systematically exploited.

Now suppose your current employer is far and away your best option. Suppose they pay you 50% to 100% more than the next best option available to you. If your employer suddenly disappeared, you would find work again, but the transition would hurt. Can such an employer exploit you? Once again, I’d say “Not really.” Sure, it’s within their power to make your life less comfortable than it is right now, but that’s only because they are currently paying you so much more than your next best option. Whatever they are extracting from you via “exploitation,” they are paying pretty dearly for it. Exploitation is a poor description of this arrangement; it would be a more accurate and fairer description to say that the employer has paid you a compensating differential for whatever unpleasantness you have to put up with.

A third possibility is that you are being compensated at significantly *less* than your best option, but if that’s true it’s hardly the fault of your employer. If you’re accepting lower pay to work for them, it must be because that job offers you non-wage perks that are, in you valuation, worth at least as much as the forgone pay. Such an employer only has the power to *offer* you a salary lower than your best option; it can’t compel you to accept it.

I don’t know which of these scenarios people have in mind when they talk about exploited workers, but none of these possibilities is consistent with an exploitation narrative. I describe the cases where your pay is more than, equal to, and less than the market wage, so this short list is actually exhaustive of all logical possibilities. One can tell a “monopsony” (single buyer) story in which the sole employer of labor can call all the shots, but that is not really descriptive of most labor markets. Even most small towns have several restaurants and chain stores, so there are multiple buyers of low-wage labor. And there’s plenty of demand for mid-level office workers. If we think of exploitation as meaning there is only one feasible employer, who thus can call the shots without the threat of the employee leaving, the most exploited workers are probably superstar athletes and CEOs. But these examples hardly fit anyone’s notion of exploitation. This entire concept is philosophically bankrupt and needs to be rethought, or dropped altogether.