Abstract
We use the National Longitudinal Survey of Youth 1997 to obtain estimates of the number of crimes avoided through incapacitation of individual offenders. Incarcerated individuals are matched to comparable non-incarcerated counterparts using propensity score matching. Propensity scores for incarceration are calculated using a wide variety of time-stable and time-varying confounding variables. We separately analyze juvenile (age 16 or 17) and adult (age 18 or 19) incapacitation effects. Our best estimate is that between 6.2 and 14.1 offenses are prevented per year of juvenile incarceration, and 4.9 to 8.4 offenses are prevented per year of adult incarceration.
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Notes
It bears mentioning that these studies still generally purport to estimate the deterrent effect of imprisonment. However, Nagin (1978) rightly points out that these studies actually confound deterrence and incapacitation (not to mention rehabilitation), and Spelman (2000) acknowledges that by treating the crime prevention mechanism as a “black box,” top-down studies are unable to discriminate between competing explanations for prison effectiveness.
When we restrict our attention to the incarcerated subsample, the length of the reference window is reduced by the length of confinement during the wave of first incarceration.
We thank an anonymous reviewer for bringing these issues to our attention.
This was also the default kernel in Stata module psmatch2 (Leuven and Sianesi, 2003), which was used for all propensity score estimates in this study.
Note that Fig. 1 provides “effective” offense rates, or the number of crimes committed since the previous interview, without subtracting off the length of confinement for those individuals who are incarcerated. Fig. 1 also shows that the shape of the age distribution of crime remains unchanged despite the fact that we estimated separate age-crime curves for the subsamples. Specifically, for very different groups of individuals, we observe the usual, unimodal peak in self-report crime at about 17.5 years of age (see Hirschi and Gottfredson 1983).
We can also compare the age-crime curve in Fig. 1 for the 453 individuals who have ever been incarcerated with Fig. 2 for the 262 individuals incarcerated for the first time between the ages of 16 and 19. The peak offending rate in Fig. 1 is 12.6, whereas in Fig. 2 it is 19.0, but we caution that these estimates are not exactly comparable. The difference is only partially due to the fact that Fig. 1 provides offense frequency per year since the last interview, while Fig. 2 provides offense frequency per year while on the street. It is also due to the fact that Fig. 1 includes individuals incarcerated for the first time after age 19, who we may presume have a later age of onset and thus lower criminal propensity than individuals incarcerated for the first time before age 19 (although this is mildly offset by the handful of individuals incarcerated for the first time before age 16). To the extent that age of onset is negatively correlated with criminal propensity, individuals incarcerated for the first time at a younger age should be more heavily involved in criminal behavior at any given age than individuals incarcerated for the first time at a later age, all else equal (see Gottfredson and Hirschi 1990).
The information in Fig. 3 includes the wave in which respondents are incarcerated for the first time. However, in light of an absence of event history information at each time period as well as evidence of a “crime spurt” immediately prior to incarceration, as we show below, we calculate the mean offense rate while free to be 14.2 (median = 2.5) if we use only time periods prior to the wave of first incarceration for our 262 individuals.
The mean age (at interview) of incarceration across all spells is 18.9 years. The mean age of the first spell of incarceration is 18.8 years, of the second spell is 19.5 years, and of the third or later spell is 20.4 years.
While this evidence suggests that individuals may be more actively involved in crime just prior to incarceration, there are two important caveats which must be noted. First, because our criterion is self-report offending, there is no reason that individuals cannot report crimes even when incarcerated during the entire reporting window at time t. Youths can certainly steal and get into fights while incarcerated and there is no reason they should not report this activity because it happened while they were confined. In fact, for the 15 individuals who were locked up for the entire reporting window, the reported offending rate was 10.4 crimes per year. However, the fact that the pattern is identical for self-report arrest rates prior to incarceration helps mitigate this limitation. In addition, if we replicate Fig. 5 showing criminal activity for individuals leading up to their first arrest, only a fraction of whom (about 21%) will subsequently be incarcerated, the same pattern emerges. Second, within a reporting window, while we are able to determine the dates of confinement, we are unable to determine the dates of reported offending. The absence of crime event history information thus means that we are unable to identify whether self-report crimes occurred before, during, or after periods of confinement. The significance of the crime spurt hinges on which of these periods reported offending falls into.
To ensure that our finding of a crime spurt in time t in these data was not due to our computing the offending rate per year free (which shortens the reference window for the incarcerated sample by subtracting off the time during which they are confined), we computed the mean offending rate during the time since the last interview (using the entire reference window rather than street time only), or what is known as the “effective” offending rate in the criminal career literature. The pattern in Fig. 5 was replicated, with lambda at time t equal to 23.7.
We find that crime prevalence (an indicator for having committed any crime) and crime variety (the number of different crime types committed) increase in a fashion similar to crime frequency. Thus, incarceration appears to arise as a result of more frequent and widespread criminal involvement. We also find, interestingly enough, that although all crime types increase jointly, frequency of drug selling increases at a somewhat faster rate than frequency of other crime types in our data (e.g., vandalism, theft, assault). Thus incarceration may also be due in part to a modest change in crime mix favoring drug-related offenses.
These variables (measured at the wave prior to age 16 unless noted) include: Male, black, delinquency variety, ever arrested, ever in a gang, an antisocial peer index, cigarettes smoked per day, marijuana use (0/1), suspended from school, got in fight at school (wave 1), five academic aptitude indicators (wave 1), years of sexual activity, living independently, interviewer assessment of outside of dwelling (two dummy variables), type of dwelling (two dummy variables), and residence in northeast region.
This is not to say that the same configuration of background variables will always result in assignment to the treated group in all applications of this method, only that in our particular application, 100% of the youths with these configurations happen to be in the treated group. In the language of instrumental variables models for treatment effect estimation, these are analogous to the “always-takers,” for whom there is no estimable counterfactual (see Angrist et al. 1996).
With all propensity score matching estimates of incapacitation, NLSY97 sampling weights are used only in generating propensity scores. Confidence intervals are obtained from the 5th and 95th percentiles of 500 bootstrap estimates of the matching model.
Males and females are included in our models, but our estimates are not gender-specific. We reproduced our propensity score matching results with a male-only sample and found substantively similar results. Three of the four matching estimates were slightly higher, and one was lower. None were statistically significantly different from reported estimates.
Heckman and Smith (1999) point out that the degree to which the estimates are overestimated depends on whether the dip is permanent or transitory. If the dip is transitory and is correlated with entry into the training program, then using earnings data from the dip will severely bias estimates of program impacts.
To be sure, Maltz and Pollock (1980) do not deny that individuals undergo genuine crime spurts prior to arrest and imprisonment, only that the observed crime spurt bears a strong resemblance to data simulated in such a way that an apparent crime spurt arises as a result of plausible sample selection processes.
Maltz and Pollock (1980) also point out that a similar artifactual crime spurt would be observed even if individuals were endowed with two underlying, state-specific arrest rates for “active” and “quiescent” periods. Conditional on an instant arrest as the selection rule, they show that the arrest rate will decay exponentially into the past to a steady state. We are grateful to an anonymous reviewer for bringing this important article to our attention.
If the crime spurt is genuine, it begs the question of what might be going on in the lives of offenders during this period of increasing volatility in their criminal history, and whether it is possible to intervene before things get out of hand and they are incarcerated.
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Appendix: Standardized and Adjusted Bias for Each Type of Matching
Appendix: Standardized and Adjusted Bias for Each Type of Matching
Variable | Unmatched | Arrested | Convicted | Nearest neighbor | Kernel | |||||
|---|---|---|---|---|---|---|---|---|---|---|
16–17 | 18–19 | 16–17 | 18–19 | 16–17 | 18–19 | 16–17 | 18–19 | 16–17 | 18–19 | |
Malea | 60.2 | 83.4 | 26.1 | 42.2 | 27.9 | 37.7 | 4.2 | −6.5 | 11.7 | 5.1 |
Hispanicb | 5.7 | −1.4 | 11.7 | −1.3 | 8.2 | −2.8 | 16.0 | 12.1 | 2.5 | 7.3 |
Blacka | 14.0 | 33.8 | 5.1 | 37.1 | 17.6 | 55.9 | −14.7 | −10.4 | 1.6 | 2.5 |
Nonwhiteb | 3.3 | −12.9 | 7.4 | −10.2 | 7.9 | −8.9 | 13.1 | −8.3 | 1.7 | 3.6 |
Rural, age 12 | −4.4 | −13.5 | 7.0 | −6.7 | 32.5 | −2.7 | −5.2 | −17.8 | −3.2 | −10.5 |
Urban, age 12 | −7.9 | 0.4 | −15.9 | −4.8 | −26.3 | −1.1 | −9.6 | 12.7 | −4.3 | 2.7 |
Dwelling: housea | −23.3 | −8.6 | −21.5 | 1.8 | −16.8 | 10.6 | 16.3 | 17.0 | −2.0 | 11.6 |
Dwelling: apartmenta | 18.9 | 4.9 | 12.9 | −1.0 | 14.1 | −2.8 | −6.8 | −20.9 | 1.8 | −11.4 |
Dwelling: other | 9.9 | 6.8 | 15.9 | −1.4 | 6.6 | −13.1 | −16.3 | 2.5 | 0.6 | −2.3 |
Prop offenses, age 12 | 13.7 | 17.6 | −2.5 | 9.1 | 4.8 | 12.6 | −18.4 | −2.7 | −6.1 | 6.0 |
Theft, age 12 | 34.0 | 25.6 | 9.3 | 7.8 | −4.5 | −7.6 | −12.9 | 14.0 | 6.6 | 16.9 |
Other property offenses, age 12 | 16.6 | 25.1 | −10.1 | 14.4 | −12.4 | 2.5 | −19.9 | 23.0 | −11.8 | 16.9 |
Attack others, age 12 | 27.7 | 12.2 | 27.1 | 8.2 | 12.1 | 5.7 | 16.7 | −12.2 | 9.7 | −4.3 |
Drug sales, age 12 | 29.1 | 13.7 | 5.6 | −7.3 | −23.7 | −21.6 | 4.1 | −14.1 | 2.3 | −11.5 |
Delinquency variety, age 12a | 56.2 | 49.4 | 6.0 | 4.9 | −19.2 | −19.5 | −9.9 | 18.3 | 1.1 | 12.9 |
House burgled before age 12b | 12.0 | 9.0 | −3.7 | −0.2 | −3.4 | −14.1 | −2.5 | 1.9 | −6.1 | 5.8 |
Saw someone shot before age 12b | 36.6 | 44.2 | 15.5 | 31.6 | −3.3 | 36.7 | −2.5 | −11.0 | −6.6 | −3.7 |
Was bullied before age 12b | 6.2 | 15.1 | −18.2 | 8.9 | −12.5 | 8.8 | −4.7 | 13.5 | −18.2 | 9.6 |
Threatened at school, w1b | 25.8 | 27.0 | −5.8 | 5.1 | −20.0 | 1.7 | −12.9 | 16.0 | −14.1 | 8.5 |
Stolen from at school, w1b | 13.3 | 15.9 | 1.2 | −4.6 | 11.3 | 0.1 | −19.2 | 21.9 | −10.0 | 7.2 |
Fought at school, w1a | 88.7 | 54.0 | 49.8 | 24.3 | 39.7 | 20.5 | −12.9 | 21.0 | 3.0 | 7.2 |
School late twice in last year, w1b | 51.4 | 37.8 | 7.7 | 13.4 | −12.8 | 2.2 | 18.2 | 0.0 | 17.1 | 2.9 |
10+ school absences in year , w1b | 38.1 | 47.4 | 21.7 | 30.6 | −1.9 | 20.1 | 4.9 | 15.2 | 1.3 | 12.5 |
School attachment scale, w1b | −36.7 | −38.9 | −7.6 | −18.4 | 5.9 | −13.4 | 4.3 | −2.3 | −2.0 | −9.9 |
Low grades (Cs or worse)b | 62.1 | 50.9 | 19.6 | 22.2 | 9.1 | 20.4 | −4.1 | −13.6 | 8.7 | 0.4 |
High grades (Bs or better) b | −53.4 | −66.3 | −4.3 | −28.0 | 10.4 | −36.7 | −2.3 | 5.2 | 0.3 | −9.5 |
Low math knowledge, w1a | 49.4 | 30.8 | 40.1 | 24.0 | 10.4 | 26.9 | 8.8 | −20.2 | 9.9 | −5.7 |
High math knowledge, w1 | −47.7 | −36.9 | −16.2 | −16.5 | −15.6 | −11.6 | −8.9 | 8.6 | −11.9 | −4.5 |
Missing math knowledge test, w1 | 24.3 | 21.4 | 18.8 | 11.3 | 32.3 | 0.3 | −16.0 | 9.9 | −2.4 | 10.5 |
Low paragraph comprehension,w1a | 46.1 | 44.1 | 24.7 | 43.3 | 25.5 | 52.9 | 2.2 | 0.0 | 6.3 | 9.4 |
High paragraph comprehension,w1 | −45.9 | −34.1 | −9.2 | −16.5 | −10.2 | −22.3 | −4.0 | 5.6 | −10.8 | −3.8 |
Missing paragraph comp. test, w1 | 24.7 | 21.7 | 19.7 | 13.2 | 32.3 | 3.6 | −11.4 | 10.0 | −1.4 | 11.0 |
Low word knowledge, w1a | 28.6 | 24.4 | 13.4 | 26.5 | 19.3 | 39.9 | −11.6 | −13.8 | 7.7 | −2.7 |
High word knowledge, w1 | −31.9 | −34.4 | −11.0 | −21.7 | −11.6 | −20.8 | −11.6 | 0.0 | −6.4 | −10.5 |
Missing word knowledge test, w1 | 24.9 | 21.8 | 19.8 | 13.2 | 32.3 | 3.6 | −11.4 | 10.0 | −1.4 | 11.0 |
Low arithmetic reasoning, w1a | 44.4 | 28.8 | 33.5 | 31.1 | 33.6 | 42.3 | 2.3 | −7.0 | 8.2 | −2.6 |
High arithmetic reasoning, w1 | −40.1 | −38.3 | −20.5 | −24.2 | −6.0 | −18.4 | −4.3 | 6.1 | −8.1 | −9.3 |
Missing arithmetic reas. test,w1 | 25.0 | 21.9 | 19.8 | 13.3 | 32.3 | 3.6 | −11.4 | 10.0 | −1.3 | 11.3 |
Missing any AFQT test, w1a | 24.3 | 21.4 | 18.8 | 11.3 | 32.3 | 0.3 | −16.0 | 9.9 | −2.4 | 10.5 |
Mother 18 or below at first birthb | 15.4 | 6.2 | 6.4 | −3.1 | 0.2 | −2.8 | 9.5 | 5.4 | −4.5 | 4.6 |
No health insurance, w1b | 2.0 | 29.4 | −2.7 | 22.6 | −8.9 | 28.2 | −11.6 | 14.8 | −18.7 | −1.5 |
Attachment to mother, w1b | −22.1 | −39.9 | −4.0 | −29.9 | 3.6 | −13.3 | −11.4 | −10.3 | −1.5 | −11.4 |
Mother’s support, w1b | −19.9 | −19.8 | −7.2 | −11.3 | 0.5 | −4.3 | 3.4 | −22.8 | −5.3 | −9.2 |
One parent is dropoutb | 41.5 | 20.4 | 35.7 | 12.0 | 24.4 | 9.3 | 8.3 | 0.0 | 13.1 | −2.2 |
One parent is college gradb | −26.3 | −57.2 | −16.9 | −47.4 | −11.5 | −57.5 | 12.1 | −16.3 | 3.6 | −11.6 |
Below poverty level, w1 | 28.2 | 37.0 | 30.2 | 34.0 | 7.8 | 21.5 | 0.0 | 21.6 | 6.1 | 12.1 |
1–2 times poverty level, w1 | 5.4 | 22.3 | −0.3 | 15.8 | −5.3 | 16.1 | −10.1 | 12.3 | −7.8 | 14.2 |
2–3 times poverty level, w1 | −2.0 | −4.8 | −12.7 | −1.7 | −3.2 | −4.8 | −10.7 | −12.2 | 2.5 | 1.0 |
3–4 times poverty level, w1 | −20.4 | −12.3 | −18.4 | −2.7 | −12.8 | −2.9 | 7.0 | 9.7 | −9.6 | 3.1 |
4+ times poverty level, w1 | −20.3 | −40.3 | −7.9 | −35.7 | 3.8 | −28.6 | 5.8 | −14.2 | 1.4 | −13.1 |
Household income unreported, w1 | −2.0 | −17.6 | −0.9 | −20.3 | 4.9 | −10.9 | 8.8 | −20.1 | 3.9 | −19.3 |
Parent received AFDC, w1 | 32.6 | 35.5 | 15.9 | 16.0 | −6.4 | 20.4 | −12.2 | −6.0 | −2.9 | 2.2 |
Parent received Medicaid, w1 | 29.7 | 21.6 | 20.3 | 5.8 | 18.9 | 7.6 | −8.2 | −9.3 | −1.5 | −0.6 |
Parent received SSI, w1 | 2.9 | 20.9 | −15.7 | 9.8 | 12.5 | −0.9 | −32.1 | 7.5 | −14.9 | 4.5 |
Parent received food aid, w1 | 17.8 | 34.5 | −1.8 | 22.9 | −24.8 | 16.0 | −21.2 | 2.8 | −9.8 | 10.0 |
Anti-social peer scale, w1a | 49.4 | 30.7 | 7.7 | 6.6 | −11.7 | −9.4 | 4.0 | 2.5 | 1.9 | 0.5 |
Rural | −1.7 | −2.4 | 13.3 | 0.0 | 31.5 | −6.0 | −6.7 | −4.9 | 5.3 | 1.2 |
Urban | −2.6 | 5.3 | −20.3 | 2.3 | −34.3 | 15.4 | 2.1 | 4.8 | −2.4 | 2.1 |
Northeast regiona | −27.8 | −0.9 | −22.2 | −5.3 | −25.9 | −10.1 | −5.8 | −7.4 | −0.7 | −6.7 |
North-central region | 3.2 | 1.6 | −0.3 | 4.6 | 0.2 | 2.2 | −6.8 | 6.7 | −3.2 | 7.1 |
West region | 14.0 | −16.9 | 10.3 | −12.1 | 7.5 | −20.4 | 13.1 | −12.5 | 10.5 | −2.4 |
Out of United States | −5.1 | −5.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | −1.9 | −2.1 |
Delinquency varietya | 88.7 | 72.4 | 24.3 | 13.3 | −22.7 | −28.3 | 3.8 | 9.8 | 8.5 | 11.5 |
Delinquency frequency | 46.4 | 38.6 | 32.8 | 22.6 | 13.8 | −3.4 | 11.7 | 11.2 | 9.9 | 7.5 |
Property offenses | 39.4 | 23.6 | 30.8 | 14.9 | 26.9 | −5.7 | 21.6 | −9.7 | 15.2 | −2.9 |
Theft | 38.2 | 25.0 | 32.0 | 14.4 | 18.1 | −3.5 | 5.9 | 7.9 | 4.2 | 2.6 |
Attacking others | 45.7 | 33.8 | 15.0 | 26.7 | −18.9 | 20.8 | 8.3 | 11.7 | 1.5 | 18.2 |
Drug sales | 34.9 | 42.9 | 17.6 | 21.9 | −15.6 | −8.2 | −4.6 | 23.1 | 4.3 | 11.7 |
Arrestsb | 65.2 | 59.1 | 0.0 | −0.4 | −80.8 | −42.2 | 23.8 | 12.5 | 20.7 | 17.1 |
Ever arresteda | 67.9 | 69.8 | 3.2 | 22.5 | −99.5 | −16.3 | 12.6 | 13.8 | 14.5 | 16.4 |
Chargedb | 63.5 | 60.8 | −26.9 | −27.2 | −184.6 | −145.3 | 13.4 | 8.6 | 20.3 | 15.8 |
Ever charged | 66.9 | 69.0 | −20.0 | 2.0 | −187.0 | −90.1 | 12.5 | 13.6 | 17.7 | 17.7 |
Court appearance | 64.5 | 58.4 | −15.5 | −70.9 | −246.3 | −252.6 | 12.1 | 4.5 | 22.6 | 11.3 |
Ever appeared in court | 66.1 | 67.7 | −10.7 | −45.1 | −232.1 | −193.5 | 14.6 | 13.5 | 21.9 | 14.9 |
Convictedb | 46.8 | 47.1 | −19.5 | −44.8 | −336.0 | −322.9 | 7.4 | 0.0 | 13.7 | 9.7 |
Ever convicted | 45.1 | 53.7 | −20.8 | −28.8 | −332.3 | −253.2 | 3.7 | 6.7 | 7.9 | 7.3 |
High school dropoutb | 27.1 | 46.8 | 8.8 | 26.1 | 19.6 | 19.0 | −20.4 | 24.4 | −17.4 | 12.1 |
Suspendeda | 108.3 | 62.7 | 29.6 | 16.0 | 16.3 | 6.0 | −2.2 | 14.6 | 1.5 | 8.9 |
Lives with both biological parentsb | −51.9 | −62.4 | −9.6 | −38.0 | −5.4 | −28.5 | −10.1 | 3.1 | −17.8 | 0.2 |
Independent from parentsa | 55.1 | 46.2 | 42.9 | 31.4 | 26.5 | 27.4 | 10.7 | 22.8 | 3.2 | 8.9 |
Household size | 14.1 | −0.6 | 17.4 | 3.4 | 18.1 | 9.3 | −0.6 | −1.2 | 7.6 | 1.8 |
Sibling/peer in gangb | 38.2 | 33.8 | −2.7 | 11.4 | −39.2 | −4.9 | 6.6 | 21.3 | 1.3 | 18.0 |
Ever belonged to ganga | 62.8 | 48.2 | 34.7 | 24.0 | −3.2 | 6.1 | 13.1 | 21.0 | 5.8 | 15.5 |
Belonged to gang in last yearb | 42.1 | 37.1 | 18.9 | 25.7 | −16.1 | 13.4 | 17.9 | 5.8 | −0.7 | 13.7 |
Years sexually activea | 88.4 | 82.8 | 61.7 | 45.5 | 22.7 | 43.4 | −21.6 | 4.0 | −9.2 | −0.9 |
Drank alcoholb | 35.8 | 24.7 | −21.4 | −15.7 | −33.5 | −40.2 | 11.6 | 0.0 | 4.9 | 8.2 |
Smokedb | 65.8 | 67.9 | −6.0 | 3.1 | −21.0 | −13.5 | 0.0 | −7.4 | 9.4 | −1.0 |
Used marijuanaa | 64.7 | 70.5 | 4.9 | 7.0 | −42.1 | −19.0 | 10.6 | 22.4 | 5.1 | 13.8 |
Used cocaineb | 35.7 | 23.4 | 30.2 | 2.0 | 12.5 | −18.5 | 15.7 | 12.7 | 18.7 | −6.5 |
Days of last 30 drank alcohol | 31.2 | 40.0 | 6.9 | 12.5 | −5.9 | −7.8 | 11.6 | 23.1 | 6.9 | 18.3 |
Alcoholic drinks/day, last 30 days | 25.9 | 32.4 | 9.1 | 9.4 | 6.7 | −6.1 | 4.7 | 24.8 | 4.7 | 16.5 |
Alcohol before/at school/work | 28.0 | 28.0 | 13.4 | 19.2 | 20.6 | 1.2 | 1.5 | 9.9 | 5.3 | 7.4 |
Days of last 30 binged | 27.6 | 37.2 | 4.4 | 11.4 | 1.5 | −19.3 | −0.9 | 14.0 | 0.5 | 9.5 |
Days of last 30 used cigarettes | 63.4 | 66.5 | 20.6 | 20.1 | −11.2 | −16.1 | 6.8 | −1.7 | 4.5 | 13.0 |
Cigarettes/day, 30 daysa | 63.2 | 54.3 | 31.4 | 21.3 | 9.0 | −7.9 | 12.6 | 2.9 | 7.7 | 10.6 |
Days of last 30 used marijuana | 41.4 | 63.4 | 19.6 | 34.0 | −13.7 | 12.7 | 9.5 | 25.8 | 10.3 | 19.2 |
Marijuana before/at school/work | 34.5 | 49.3 | 24.3 | 33.6 | −11.6 | 28.9 | 7.2 | 17.5 | 18.4 | 23.0 |
Times used cocaine in last year | 18.0 | 11.2 | 12.4 | −6.5 | 3.4 | −21.2 | 18.0 | −0.3 | 10.1 | −6.6 |
Cocaine before/at school/work | 15.1 | 18.7 | 14.9 | 9.2 | −14.9 | 14.8 | 5.8 | 11.1 | 2.4 | 5.5 |
Interior of house: niceb | −44.6 | −35.4 | −21.1 | −22.3 | −0.3 | −18.6 | 11.7 | −4.3 | −5.4 | 0.2 |
Interior of house: fairb | 20.4 | 9.2 | 7.2 | 3.0 | 5.3 | −6.0 | −4.1 | 9.2 | 4.9 | 1.5 |
Interior of house: poorb | 29.0 | 32.0 | 9.8 | 14.7 | −22.4 | 21.3 | −20.4 | 4.1 | −6.9 | 6.2 |
Exterior of house: nicea | −45.6 | −40.7 | −26.4 | −33.6 | −4.0 | −27.1 | −2.0 | 11.4 | −6.9 | 4.0 |
Exterior of house: fairb | 9.7 | 22.6 | −1.1 | 20.0 | −7.6 | 9.8 | −2.0 | −5.9 | −2.3 | −4.7 |
Exterior of house: poora | 38.8 | 25.3 | 26.3 | 13.9 | 4.0 | 19.8 | −5.3 | 4.2 | 2.9 | 7.5 |
Missing victimizationb | 5.3 | 20.9 | −37.6 | −14.4 | −22.1 | −17.1 | −13.2 | −7.6 | −6.0 | −2.7 |
Missing school attachmentb | 10.9 | 19.7 | 9.4 | 14.4 | 16.5 | 19.3 | −8.7 | −5.0 | 10.4 | 0.3 |
Missing attachment to motherb | 17.2 | 12.7 | −2.4 | −9.2 | −7.4 | −13.2 | 13.3 | 8.4 | 6.2 | 3.6 |
Missing mother’s supportivenessb | 30.4 | 22.6 | 22.4 | 10.6 | 27.5 | −9.2 | 28.8 | −5.6 | 20.7 | −0.1 |
Missing gang membershipb | 15.7 | 7.3 | 14.1 | 10.3 | 6.9 | 10.3 | −9.5 | −42.2 | 12.5 | −42.5 |
Unbalanced (%) | 69.40 | 71.80 | 31.50 | 37.30 | 33.30 | 33.60 | 7.20 | 16.40 | 4.50 | 1.80 |
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Sweeten, G., Apel, R. Incapacitation: Revisiting an Old Question with a New Method and New Data. J Quant Criminol 23, 303–326 (2007). https://doi.org/10.1007/s10940-007-9032-4
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DOI: https://doi.org/10.1007/s10940-007-9032-4