(iv) Roodman’s review of incarceration notes that multiple studies find strong evidence that incapacitation works to prevent crime.
But that’s tautological or close to tautological given Roodman’s definition of incapacitation (p. 10, Sec. 2.2.2):
Because prison crime is so rarely studied, and because crime outside of prison has particular political salience, “incapacitation” in this review will refer to crime outside of prison.
(I say “close to tautological” because some crimes committed by someone in prison, e.g. mail fraud, might nonetheless be considered crimes outside of prison.)
If we consider total crime, not just reported crime or just crime outside of prison, then the quoted incapacitation figures will be overstated. Indeed, it’s quite plausible that the full incapacitation effect is negative on some margins. So for instance consider someone in jail for a relatively short period of a week or a month. I would guess their risk of being a victim of crime (theft, assault, rape) is typically higher than the risk of them committing or being a victim of a crime outside of jail over the same period.
Given the line you quote it’s totally reasonable for you to think this, but I think Roodman’s summary is actually very misleading. If you look at the tables where the actual calculations take place, you can see negative coefficients for incapacitation for both Rape and Aggravated Assault: he assumes imprisonment increases these crimes during the period of ‘incapacitation’! If we ignored crimes among felons, these figures would be positive, and increased incarceration would actually look more desirable on the current margin than his report concludes:
Leaving Roodman’s report to one side for the moment, there is an important empirical (non-tautological) insight in the incapacitation benefits of prison: crimes are very concentrated among a small segment of the population, so you can imprison 1% of people and catch much more than 1% of all crimes.
Thanks for the reply. I agree that’s a natural tentative interpretation of Table 26, taken in isolation. But note that table doesn’t give any indication of confidence intervals for the relevant column.
Have a look at Table 11 (below). We see the same numbers (up to rounding) in the final row, with 90% confidence intervals. Note the negative point estimates for rape and assault are very close to the center of their confidence intervals and thus not distinguishable from zero. Basically, there was a natural experiment in which California reduced the prisoner population and for those two categories, on a relative basis to (most of) the rest of the country, crime happened to decrease very slightly, but only to an extent well within the statistical noise. (In fact of the seven categories, only motor vehicle theft is significant—and barely so—at the p=0.1 level and none is significant at the conventional p=0.05 level.)
Note the crime numbers being used here are inferred from official crimes reported, rescaled using national estimates of the reporting rate (which helps to put e.g. murder and larceny on the same footing, despite their very different reporting rates). Since only a tiny fraction of crimes in prison are reported (at least that’s my sense), that means that crimes in prisons and jails are essentially being ignored (as Roodman states in his definition of incapacitation I initially cited).
The bottom line as I see it: If someone wants to do a CEA analysis of an intervention in this space, they should think carefully about the incapacitation term as sources (Roodman and I suspect the underlying literature) will tend to exclude crimes in prisons and jails. In fairness, it’s likely hard to get good estimates, but things don’t fail to be real because they are hard to estimate.
I don’t think that’s correct. There’s a recent study showing a reduction in mortality for prisoners that are incarcerated relative to a control group of people who were not incarcerated. It appears that most of the reduction in mortality is from reduction in overdose death risk but also a reduction in homicide. The implication is that people in prisons are safer than they would be outside. Probably most of the data showing otherwise comes from poorly done studies that don’t use appropriate control groups, EG they may use the general population as control group relative to prisoners.
You write:
But that’s tautological or close to tautological given Roodman’s definition of incapacitation (p. 10, Sec. 2.2.2):
(I say “close to tautological” because some crimes committed by someone in prison, e.g. mail fraud, might nonetheless be considered crimes outside of prison.)
If we consider total crime, not just reported crime or just crime outside of prison, then the quoted incapacitation figures will be overstated. Indeed, it’s quite plausible that the full incapacitation effect is negative on some margins. So for instance consider someone in jail for a relatively short period of a week or a month. I would guess their risk of being a victim of crime (theft, assault, rape) is typically higher than the risk of them committing or being a victim of a crime outside of jail over the same period.
Given the line you quote it’s totally reasonable for you to think this, but I think Roodman’s summary is actually very misleading. If you look at the tables where the actual calculations take place, you can see negative coefficients for incapacitation for both Rape and Aggravated Assault: he assumes imprisonment increases these crimes during the period of ‘incapacitation’! If we ignored crimes among felons, these figures would be positive, and increased incarceration would actually look more desirable on the current margin than his report concludes:
Leaving Roodman’s report to one side for the moment, there is an important empirical (non-tautological) insight in the incapacitation benefits of prison: crimes are very concentrated among a small segment of the population, so you can imprison 1% of people and catch much more than 1% of all crimes.
Thanks for the reply. I agree that’s a natural tentative interpretation of Table 26, taken in isolation. But note that table doesn’t give any indication of confidence intervals for the relevant column.
Have a look at Table 11 (below). We see the same numbers (up to rounding) in the final row, with 90% confidence intervals. Note the negative point estimates for rape and assault are very close to the center of their confidence intervals and thus not distinguishable from zero. Basically, there was a natural experiment in which California reduced the prisoner population and for those two categories, on a relative basis to (most of) the rest of the country, crime happened to decrease very slightly, but only to an extent well within the statistical noise. (In fact of the seven categories, only motor vehicle theft is significant—and barely so—at the p=0.1 level and none is significant at the conventional p=0.05 level.)
Note the crime numbers being used here are inferred from official crimes reported, rescaled using national estimates of the reporting rate (which helps to put e.g. murder and larceny on the same footing, despite their very different reporting rates). Since only a tiny fraction of crimes in prison are reported (at least that’s my sense), that means that crimes in prisons and jails are essentially being ignored (as Roodman states in his definition of incapacitation I initially cited).
The bottom line as I see it: If someone wants to do a CEA analysis of an intervention in this space, they should think carefully about the incapacitation term as sources (Roodman and I suspect the underlying literature) will tend to exclude crimes in prisons and jails. In fairness, it’s likely hard to get good estimates, but things don’t fail to be real because they are hard to estimate.
I don’t think that’s correct. There’s a recent study showing a reduction in mortality for prisoners that are incarcerated relative to a control group of people who were not incarcerated. It appears that most of the reduction in mortality is from reduction in overdose death risk but also a reduction in homicide. The implication is that people in prisons are safer than they would be outside. Probably most of the data showing otherwise comes from poorly done studies that don’t use appropriate control groups, EG they may use the general population as control group relative to prisoners.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3644719