When studying crime, if a researcher wishes to compare the amount of
crime over time or between communities of different sizes, it is not adequate to do a
gross count of the amount of crime because the population bases may be different.
To get around the problems involved with this, criminologists calculate
crime rates (or incarceration rates, conviction rates, recidivism
rates). This is done by dividing the amount of crime by the population size and
multiplying by 100,000. This produces a rate per 100,000, but occasionally it is useful to
calculate a rate per million or some other figure.
Rate is synonym of rhythm or frequency, such as heart rate or sample rate. In
statistics, a unit rate is a rate that is simplified so that it has a denominator of
The Effect of State Sentencing Policies on Incarceration Rates - Jon Sorensen, Don
Stemen, State Sentencing and Corrections Program, Vera Institute of Justice
This article explores the relationship between sentencing policies and the state
incarceration rate, prison admission rate, and average sentence length in the late 1990s.
Presumptive sentencing guidelines represent the only policy consistently related to
incarceration and admission rates, whereas three strikes laws may increase the rate of
admission to prison among those arrested for drug offenses. Determinate sentencing,
mandatory sentencing, and truth-in-sentencing laws have no effect on rates of
incarceration or admission. Crime rates, the percentage of the population that is Black,
and citizen ideology have the greatest influence on the rates of incarceration and
admission across states. The apparently limited effects of sentencing policies on
incarceration or admission rates should give pause to state policy makers seeking to
quickly alter prison populations through the adoption of such policies without considering
other factors that independently influence prison populations in their states. - Crime
& Delinquency, Vol. 48, No. 3, 456-475 (2002)
Variation in Incarceration Rates Across the Fifty States, Pritchard, Anita - Paper
examines variation in incarceration rates across the fifty states. As expected, states'
crime rates and the ideological identification of their leaders and citizens have the
greatest effect upon incarceration rates
Why are Immigrants' Incarceration Rates so Low? Evidence on Selective Immigration,
Deterrence, and Deportation - Kristin F. Butcher, Federal Reserve Bank of Chicago
Anne Morrison Piehl, Rutgers University - National Bureau of Economic Research (NBER)
Abstract: Much of the concern about immigration adversely affecting crime derives from the
fact that immigrants tend to have characteristics in common with native born populations
that are disproportionately incarcerated. This perception of a link between immigration
and crime led to legislation in the 1990s increasing punishments toward criminal aliens.
Despite the widespread perception of a link between immigration and crime, immigrants have
much lower institutionalization (incarceration) rates than the native born. More recently
arrived immigrants have the lowest comparative incarceration rates, and this difference
increased from 1980 to 2000.
We present a model of immigrant self-selection that suggests why, despite poor labor
market outcomes, immigrants may have better incarceration outcomes than the native-born.
We examine whether the improvement in immigrants' relative incarceration rates over the
last three decades is linked to increased deportation, immigrant self-selection, or
deterrence. Our evidence suggests that deportation and deterrence of immigrants' crime
commission from the threat of deportation are not driving the results. Rather, immigrants
appear to be self-selected to have low criminal propensities and this has increased over
Patterns and Predictors of County-Level Incarceration Rates Over Time - Schupp, Paul. and
Rivera, Craig - Annual meeting of the AMERICAN SOCIETY OF CRIMINOLOGY.
Abstract: This research relies on the semi-parametric group-based method of modeling
developmental trajectories, developed by Nagin and colleagues (e.g., Nagin, 1999), to
model trajectories of incarceration rates for New York counties in recent decades. Most
previous research has relied on state- and federal-level data to map imprisonment rates
over time (e.g., the imprisonment rate in the U.S. has increased dramatically for the past
thirty years), but this makes the assumption that there is one underlying pattern of
growth determining this trend. The current analysis will examine that assumption at the
county level by identifying distinct groups of counties that display within-group
homogeneity of incarceration patterns of over time, and by modeling a separate trajectory
for each group. Despite the fact that the overall trend in New York is one of increasing
incarceration rates, this method will allow us to identify whether or not there are
actually a variety of patterns displayed across counties. For example, some counties may
actually be decreasing or staying the same over time, while others are increasing. The
current study will also examine political, economic, and demographic predictors of the
different patterns of incarceration that are identified.
Convictions Versus Conviction Rates: The Prosecutor's Choice
J. Mark Ramseyer, Harvard Law School, Eric Bennett Rasmusen, Indiana University
Manu Raghav, Washington and Lee University; Indiana University Bloomington
Harvard Law and Economics Discussion Paper No. 611
Abstract: It is natural to suppose that a prosecutor's conviction rate - the ratio of
convictions to cases prosecuted - is a sign of his competence. Prosecutors, however,
choose which cases to prosecute. If they prosecute only the strongest cases, they will
have high conviction rates. Any system which pays attention to conviction rates, as
opposed to the number of convictions, is liable to abuse. As a prosecutor's budget
increases, he allocates it between prosecuting more cases and putting more effort into
existing cases. Either can be socially desirable, depending on particular circumstances.
We model the tradeoffs theoretically in two models, one of a benevolent social planner and
one of a prosecutor rewarded directly for his conviction rate as well as caring about
convictions and personal goals. We also look at anecdotal evidence from Japan and detailed
U.S. data drawn from county-level crime statistics and a survey of all state prosecutors
by district. We find that prosecution rates vary little with budget, but conviction rates
do increase, and that the conviction rate declines in the number of cases prosecuted and
with the crime rate of a district.
Analysis of Recidivism Rates Based on Risk and Needs Assessments, Foster, Michelle
Paper presented at the annual meeting of the Midwest Political Science Association.
Abstract: The focus of this work is on analyzing recidivism rates for offenders who have
received risk and needs assessments. This study uses secondary data obtained from ICPSR
and collected by the Los Angeles Probation Department from April 1997 to December 1997 for
offenders placed on probation. The reoffending rates over there time periods are examined.
The results of the logistic regression analysis are that offenders who have a drug abuse
problem are more likely to offend at 12 months and 18 month timeframes rather than
initially at 6 months. These results suggest a greater need for treatment services the
longer an offender is probation instead of a shorter time period for treatment.
Recidivism Among Youth Released From The Youth Leadership Academy To The City Challenge
Intensive Aftercare Program - by Bruce Frederick and Dina Roy
The present study examined recidivism among 323 male juvenile delinquents from New York
City who were released from the Sergeant Henry Johnson Youth Leadership Academy (YLA) to
the City Challenge Intensive Aftercare Program (CCh) from May 1992 through June 1999. The
primary purpose of the study was to determine whether efforts to improve the design and
implementation of the YLA/CCh sequence had been accompanied by reductions in post-release
Analyses of changes in recidivism rates controlled for changes in the distribution of
youth characteristics and circumstances, including age, race, length of residential stay,
time at risk, 2 measures of academic achievement, 4 measures of prior record, 4 measures
of youth attitudes and behavior, 4 measures of youth's home environment, 5 measures of
local crime and arrest rates, and 6 measures of local population and housing
characteristics. These measures were combined in multivariate statistical models to
produce scores reflecting the a priori risk of recidivism for each individual.
After controlling for changes in a priori risk, the study found no reduction in overall
recidivism, as measured by post-release arrests for any criminal offenses. The study did
find a statistically significant reduction between the second and third phases for certain
measures of violent recidivism. The effects were strongest for short-term recidivism, that
is, for rearrests for violent crimes within the first 6 months following release. During
the second phase, the observed rate of violent recidivism within six months at risk had
been more than double the rate expected on the basis of average a priori risk, but it
dropped to levels slightly below a priori risk during the third and fourth phases. Despite
this relative reduction, though, the absolute level of violent recidivism for the fourth
phase was still high-17% within 6 months and 31% within 12 months.
Patterns in the detailed findings suggest that the relative reduction in violent
recidivism was probably not due to changes in the characteristics and circumstances of
participants, changes in pre-arrest revocation rates, changes in local arrest rates, or
improvements in the YLA component. Among the most salient explanations, the most plausible
is that the reduction was due primarily to improvements in the City Challenge Intensive