Bruce McCullough points me to this note by Bernard Harcourt on the negative correlation between the rates of institutionalization and homicide. Basically, when more people have been in mental hospitals, there have been fewer homicides, and vice-versa.
It makes sense since, presumably, men who are institutionalized are more likely to commit crimes, so I’m surprised that Harcourt descrbes his results as “remarkable–actually astounding. These regressions cover an extremely lengthy time period . . . a large number of observations . . . and the results remain robust and statistically significant . . .” With a large data set, you’re more likely to find statistically significance. Especially when the main result is so plausible in the first place.
Harcourt concludes with some interesting comments about the applicability of his results. (I’d also like to recommend the paper by Donohue and Wolfers on death penalty deterrence as a model example of this sort of analysis.)
P.S. See here for an update by Harcourt, where he explains why he finds his results surprising. I’m not convinced–I believe the results are important, just not that they’re suprising.
Funny stuff
Harcourt’s blog entry had some amusing comments:
I don’t understand why you’re including standard errors and p-values in your results.
What is your stochastic model, exactly? If I understand correctly, the underlying data (e.g. the crime rates) are population statistics, not sample estimates, correct?
So where is the randomness coming from?
(Good question. The randomness in the model comes from state-to-state and year-to-year variation.)
Graphs with two y-axes on different scales make Baby Jesus cry, especially when the axes aren’t labeled.
(Actually, I understand from Howard Wainer that scatterplots are a fairly recent invention, probably not around in Jesus’s time.)
Can you explain your findings in English for people like me who do not speak graph?
(Google clearly needs to implement that Graph -> English translator.)
Remember when this blog was all sweetness and light and Eugene’s insightful comments on a variety of topics and puzzleblogger Kevan Choset’s interesting observations and Adler’s/Juan’s snarky comments?
This blog used to be fun. Now, whoa, Ilya thinks he probably didn’t (but maybe did!) change US policy on drug eradication in Afghanistan, and we’ve got graphs with two Y-axes on different scales, and it’s all wonk all the time. Why have we abandoned the idea that posts should be entertaining and interesting to someone other than the author?
Include me out!
That’s pretty funny, but even better is the note below the comment area:
Comment Policy: We’d like the posts to be civil, of course (no profanity, personal insults, and the like), but we’re also hoping that people try to be as calm, reasoned, and substantive as possible. So please, also avoid rants, invective, substantial and repeated exaggeration, and radical departures from the topic of the thread.
Hey, I’d love to have some good rants here . . .
The note continues:
Here’s a tip: Reread your post, and think of what people would think if you said this over dinner. If you think people would view you as a crank, a blowhard, or as someone who vastly overdoes it on the hyperbole, rewrite your post before hitting enter.
And if you think this is the other people’s fault — you’re one of the few who sees the world clearly, but fools wrongly view you as a crank, a blowhard, or as someone who overdoes it on the hyperbole — then you should still rewrite your post before hitting enter. After all, if you’re one of the few who sees the world clearly, then surely it’s especially important that you frame your arguments in a way that is persuasive and as unalienating as possible, even to fools.
In all seriousness, I doubt that this advice will work. I’m afraid a delusional person will not be able to process this sort of rational, well-intentioned advice. But I guess it doesn’t hurt to try.
I'm surprised that you're surprised that Harcourt finds the results surprising. I do too! Perhaps in this case I am just too ignorant to have expected these results: I would have thought that the vast majority of murders are not committed by people who would be institutionalized under any institutionalization regime that we've ever had. Sure, any individual wacko is more likely to commit murder than a randomly selected non-wacko, but lots of non-wackos commit murder, most wackos never do, and most wackos are never institutionalized anyway. So I would have expected any effect of institutionalization to be lost in the noise.
And in fact, taking a look at the write-up, I don't think the relationship in the data is causal at all. I'd still be "surprised" if it is.
Speaking as the author of that second comment re Baby Jesus, I want to defend myself and say that I hope it's amusing in a somewhat different sense from one or two of the other comments.
And of course Jesus knew about scatterplots — He knows about everything, remember.
Phil, do you have any data on the ratio of wacko to non-wacko murderers? If it is very high wacko to very low non-wacko, then institutionalizing even a small fraction of the wackos might move the curve. I think the result was 'surprising' due to the belief (probably true) that more men than women commit murder but traditionally more women than men were institutionalized for 'mental' causes.
If both of the above are true, then it would seem to imply that there is a very high probability (compared to the probability for non-wackos) that any given male wacko will eventually commit a murder unless imprisoned in some way. That is just a little scary, I think. If it is the case, what, given our view of individual rights, is the correct policy?
"Here's a tip: Reread your post, and think of what people would think if you said this over dinner. If you think people would view you as a crank, a blowhard, or as someone who vastly overdoes it on the hyperbole, rewrite your post before hitting enter."
What if I usually eat dinner with cranks and blowhards?
No, Jorg, I don't have any data…which is why I say that the fact that I find the relationship surprising (if it is assumed to be causal, anyway) may be due to my ignorance.
I think (based on not much) that most homicides are related to drunken (or drug-related) arguments, domestic violence, gang activity, drug turf wars, and robberies gone bad, and that although the people involved in some of this stuff might not be the most stable people in the world, most of these people are not put into mental institutions under any regulatory regime.
I also think, based on not much, that the "insanity defense" is rarely used and even more rarely successful, suggesting that people who "should have been" confined for mental reasons are not the ones doing most of the killing.
I still think there's something else going on with these data. Maybe more people are put into institutions when economic times are good (because the government can afford to treat them or at least confine them), and crime rates also drop when economic times are good. Or perhaps my skepticism is unfounded.
I agree with the surprised reaction and was extremely suprprised myself when I saw the "mirror image" graph in Harcourt's paper. The main reasons are that (1) using the aggregated institutionalized rate is not in line with the previous research in macro-level homicide and (2) the relationship looks to be relatively robust, perhaps moreso than any other predictors previously used in theory testing. As Harcourt said, "practically all our criminology has failed to connect the prison to the asylum." So the shocking part is not so much the model but the ramifications that this finding could have….if anyone listens, that is.
He also expects some stiff resistance, which I think is a pretty good prediction. He will have some resistance from the prevailing theorists in criminology and will also have some of the mental health academics (who have not really published all that much with criminologists) gunning at this.