The new format is also filled with bugs.
Meanwhile, most of the more sane members of the comment section seem to have given up, leaving it to the rabid libertarians, who attack and gnaw at the few remaining less rabid libertarians like jackals at a corpse.
Also meanwhile, nearly two weeks after McArdle published "Myth Diagnosis," she has yet to directly answer her critics. McArdle's posts supporting her stupidity (Nine! Count 'em! Nine! Lovely supporting posts!) mostly restate her stupidity rather than backing it up with facts.
Stupidity the First: Make Up Shit
So while it's entirely possible--indeed certain--that some number of people are saved by having insurance, it's also very likely that some number of people are saved by not having it, or having less generous insurance, because they don't go in for a treatment that would have killed them.
The 2009 paper was looking at a small subset of conditions that are urgent, and which we're relatively adept at treating. But it may be washed out by the people who die having knee surgery.
Stupidity the Second: Nobody Knows Anything, Ever
I thought I'd made it clear, but apparently not: I think it is possible that the lack of insurance has no effect on aggregate mortality statistics. I do not think that this is likely, but I think it's possible. What I think is likely is that the effect is not that large, because if it were large, it would be very surprising to see so little effect on the mortality of an elderly population with a high mortality rate, or to have a study that samples 600,000 people and finds no effect.
Mostly what I think is that the statistics are really, really flawed. Not because the authors are bad social scientists, but because this stuff is so hard to tease out. Natural experiments are rare, and data sets often hard to come by.
Stupidity the Third: Science Stuff Is Too Hard To Figure Out
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.
McArdle promised to answer her critics within a few days, but that was about a week ago, so it must have slipped her wedding-occupied mind.
ADDED: More information from a post discussing the bugs in the new system:
This blog may never be exactly what you want. Let's be honest: I work for a commercial organization, and in order for them to continue to pay my paycheck, this site needs to be profitable. So we're going to have ads and other features that may well annoy you from time to time.
It's going to have to be a lot more profitable to make up a $3-5 million shortfall.