For some reason, everyone I've seen who has so far responded to my piece on mortality and the lack of insurance has pulled exactly the same debater's trick: they restate my argument in maximalist form, and then proceed to really kick the hell out of the strawman they've created. I mean, there's hay and shreds of fabric on the ceiling of offices three floors above them. Button eyes flying off so fast that several have achieved escape velocity. Crows shrieking in terror as far away as Fresno and Marseilles. It's a stunning display of . . . something.
But I have not asserted that insuring the uninsured wouldn't save anyone's lives, so I don't know why they're making this argument while linking to me. What I said is, the studies so far done often cannot exclude the possibility that there is no effect--this is true of one of the two studies that IOM/Urban relied upon, and also of the largest observational study done to date, which found no effect. That is not the same as saying there is no effect. Health data, like economic data, is very noisy. Sometimes effects that we're pretty sure exist just can't be easily teased out of the data . . . like, oh, I dunno, the effectiveness of fiscal stimulus, say.
What I am saying is that we don't know how big the effect is. Refuting me involves, not saying that well, here's another study showing some effect, but rather, taking a stand and saying we do know how big the effect is, or at minimum, that we can prove it's probably at least 20,000 people a year, the figure I was discussing.
Because of course, size matters. If you want to argue in favor of a national health care system on the basis of improvements in mortality, then the number really has to be quite large. By 2019, the CBO expects the government to be spending just about $163 billion more the exchanges, and the Medicaid/S-Chip expansions. (About $100 billion of that is to be offset by Medicare and other cuts--but I'm just trying to isolate how much we're going to spend to expand coverage, since we could do the coverage expansion without the Medicare cuts, or the Medicare cuts without the coverage expansion--and doing the latter would give us money for other things, so there is an opportunity cost to using them for this).
If 1,000 people die a year, that means that we will be spending $163 million per life saved. If the number is 5,000 we would be spending $33 million. In fact, you need the number of people dying from lack of insurance each year to be quite large--more than 20,000--to get the dollars-per-lives-saved within the ranges that say, the EPA or the NHTSA use for doing cost-benefit analyses on regulations.
Now, obviously, as I've also said repeatedly, there are reasons beyond mortality that we might support this system. Mortality is only one element, albeit an important one. And of course, the CBO numbers are them selves very, very rough guesses.
But I think that journalistic hunger for "a number" has resulted in some very rough numbers with a lot of weaknesses being adopted as a fact in the debates. They're not facts, they're very rough guesses, and they shouldn't have been used as a selling point for this plan without at least some investigation of how reliable they were. Moreover, I know that the people arguing with the study understand the problems, because they suddenly rediscovered them in regards to the data on deaths before and after age 65. A lot of people are arguing that we should ignore the aggregate data on Medicare mortality statistics in favor of Card's paper on the discontinuity between health outcomes for ER admits who are just under 65, and those just over, or some other more targeted work.
I see the argument for using easier-to-measure subgroups in an attempt to isolate causality. But here's the thing: you cannot say, well, aggregate data isn't very good for capturing causality, and also cite the figures from the Urban Institute, or Himmelstein et. al. as if they had some meaning. Those data are far worse than the Medicare data, because at least the Medicare data gives you a natural experiment, and it doesn't try to isolate "the uninsured" on the basis of their insurance status on a single day. Either it's reasonable to infer causality from large and noisy data sets, or it isn't.
If you want to see the argument only in maximalist terms, I'd like to see some of the people who have pushed my argument to its maximalist conclusion endorse some maximalist propositions of their own. If you've used the 20,000 or 45,000 figures regularly, approvingly cited the Himmelstein et. al. bankruptcy data, and stated as a fact that the health care bill will reduce deficits because the CBO said so, you should have no trouble signing on to the following propositions:
- Since I think that the Urban and/or Himmelstein figures are reliable, and at least 60% of the uninsured will be covered by the new plans, I expect that mortality rates among those under 65 will begin a discontinuous fall by late in this decade. I expect them to drop by at least 10,000 (1.5%) and very possibly by 22,500 (3.5%), or even more, by 2025.
- I expect that within 5 years of implementing this plan, we will see a kink in the bankruptcy curve representing an at least 20% decline in the overall level of bankruptcies from trend.
- Since I believe that the CBO's accuracy at predicting the future with their reports are very high, and conservatives who question them are disingenuous, I do not believe that total government expenditures on health care will rise by more than $90 billion a year + [the health care CPI x current expenditures] + the annual cost of the doctor fix.
- Since I have frequently cited international mortality and infant mortality figures as an example of the failure of the American health care system, I expect that within 10 years of implementing this plan, we will have begun to substantially close the gap between the US and other developed nations with better mortality statistics. I believe that this plan will ultimately reduce the mortality gap by at least a third within 25 years, and virtually eliminate it within 50 years.
I doubt that many people want to take the maximalist position, because, well, the universe is messy. I don't either, which is why I didn't make it. I don't think we know how many people die every year from lack of health insurance. I think the number is probably smaller than Urban, because I expect the pressure from the unobserved variable bias to be upward. But I could be wrong. Further than that, I am unwilling to say.
Update: Oops! Links to Matthew Yglesias, Ezra Klein, and Austin Frakt, all of whom have interesting points, but all of whom focus on the question of whether there is an effect, rather than how large it is, and how well we can estimate it. Also Tyler Cowen, who has very similar thoughts to mine.