Ludwig, Jens, Greg J. Duncan, and Paul Hirschfield, “Urban
Poverty and Juvenile Crime: Evidence from a Randomized Housing-Mobility
Experiment.” Final version published in the Quarterly Journal of
Economics (May 2001), 655-679.
This paper uses data from a randomized housing-mobility experiment to study
the effects of relocating families from high- to low-poverty neighborhoods on
juvenile crime. Outcome measures come from juvenile arrest records taken from
government administrative data. Our findings seem to suggest that providing
families with the opportunity to move to lower-poverty neighborhoods reduces
violent criminal behavior by teens.
DATA AND DESIGN
This study uses
HUD MTO baseline survey, completed by all participants in Section 8-only,
Experimental, and Control groups of the MTO program, and
arrest records obtained from the Maryland Department of Juvenile Justice (DJJ). The DJJ records
include three categories of crime: violent crimes, property crimes, and
"other" crimes. Data are used for those MTO teens who are
between the ages of 11 and 16 at the time of assignment, excluding
person-quarters that follow a participant's 18th birthday.
These data are used to show the effect of assignment in the
experimental group on a dependent variable (the “supply” of criminal offenses),
controlling for pre-program characteristics, and including dummy variables for
calendar quarter and quarters since randomization. The use of panel data allows
for the control of common trends in crime. The researchers also gauge the
effect of “Treatment on the Treated” (TOT), assuming that assignment to the
experimental or Section 8-only groups has no effect on families who did not
relocate through MTO.
indicate that starting 4 to 6 quarters after assignment to the
experimental or Section 8-only groups, juvenile arrests for violent crime decline
relative to the control group. Reductions in robbery account for about
half this decline. The figures also suggest that teens in the experimental
group may have higher rates of property crime arrest relative to the
control group. This latter result is ambiguous, however, and is not
statistically significant when controlling for pre-program
effects of treatment on the treated are slightly greater for the
experimental group than for the Section 8-only group. For both these
groups, the post-program arrest rates for violent crime are slightly
higher for compliers than non-compliers. However, pre-program arrest rates
also have a positive affect on a family's probability of making an MTO
move, suggesting that it is not simply families with “better” outcomes
that chose to relocate to low-poverty areas.
evidence in this paper suggests that the offer to relocate families from
high- to low-poverty neighborhoods reduces juvenile arrests for violent
offenses by 30 to 50 percent, with some indications that there is a
concomitant increase in property crimes in these groups.
the results presented here reflect both criminal behavior and the behavior
of the local justice systems, the authors persuasively argue that the
latter would tend to understate reductions in offending and overstate
increases, thus adding weight to the finding of lower levels of violent
crime among the treated groups.
it should be kept in mind that MTO participants are a self-selected group,
these results at least suggest that policies which reduce the spatial
concentration of poverty may affect overall levels of violent crime.
Ludwig, Jens, Greg J. Duncan, and Joshua C. Pinkston, “Neighborhood
Effects on Economic Self-Sufficiency: Evidence from a Randomized
Housing-Mobility Experiment.” Draft date: January 31, 2000.
The paper examines whether residence within high-poverty urban neighborhoods
affects individual economic outcomes. Our data are generated by a randomized
housing-mobility experiment, with measures of economic self-sufficiency taken
from state administrative records. We find that providing low-income families
living in public housing units with private-market rental subsidies that can
only be redeemed in very low-poverty neighborhoods reduces rates of welfare use
by around 15 percent. Most of this reduction appears to be explained by
differences in welfare-to-work transitions. We also find that providing
families with unrestricted housing vouchers has little effect on economic
outcomes beyond the first year.
- Do the
characteristics of one’s neighbors affect behavior?
the location of a neighborhood affect labor market outcomes; that is, is
there a spatial mismatch between inner city dwellers and suburban job
Four sources of Baltimore
area data are used in this paper:
HUD MTO baseline survey, completed by all participants in Section 8-only,
Experimental, and Control groups of the MTO program.
addresses, as collected by Abt Associates in phone surveys between July
and December of 1997 (91% response rate).
data on public assistance from the Maryland Department of Human Resources.
These data are current as of August 1998, an average of 3.2 years after
random assignment. There was some disagreement between self-reported
welfare receipt at the time of entry and these state public assistance
records. The authors find the match rate to be on the order of
employment and earnings histories from the Maryland Department of Labor,
Licensing and Regulation, covering under the Unemployment Insurance (UI)
program those employers who pay more than $1,500 in a quarter to one or
more employees. These data are less susceptible to misreporting problems
such as recall error or self-presentation bias than self-reported data,
but they also miss income from off-the-books work. This may bias findings,
particularly if opportunity for such off-the-books work varies across
MTO allows the authors to test the joint hypothesis that neither the
location nor the social composition of inner-city neighborhoods affects
economic self-sufficiency. Controlling for family and neighborhood
characteristics, this study compares mean economic outcomes for families
assigned to each of the three treatment groups, known as "Intent To Treat
" (ITT). The random assignment to the MTO groups also allows for the
inference of the effects of "treatment on the treated" (TOT), by
comparing economic outcomes of the MTO families who complied with the treatment
to those assigned to the control group who would have complied with the
average, the proportion of experimental group families on welfare during
the post-program period is 6 percentage points lower than for the control
group (equal to about 15 percent of the control group’s welfare receipt
rate). The Section 8-only group rate of welfare receipt is 5 percentage points
lower than the control group in the first program year. This margin
dissipates in subsequent years, while the gap between the experimental and
control groups actually grows to nearly 10 percentage points in the third
year. The central finding is that assignment to the experimental group
reduces welfare receipt relative to controls, but assignment to the
Section 8-only group has little effect beyond the first year.
decline in welfare caseloads appears to be due to increased earnings in
the formal labor market: the differences in welfare-to-work transitions
between experimentals and controls appears to account for most of the
differences in welfare receipts. The UI program does not show consistent
differences in employment levels between the experimental and controls
groups. The authors suggest that this is because income increases enjoyed
by the experimental group may be "under the table", or otherwise
unreported through the UI program.
matter for economic self-sufficiency, at least for the Baltimore MTO
population. The specific mechanisms through which this happens are
unclear. They may involve changes in social capital, increased proximity
to job opportunities, or improvements in social services or other local
Ludwig, Jens, Helen F. Ladd, and Greg J. Duncan, “Urban Poverty
and Educational Outcomes.” Brookings-Wharton Papers on
Urban Affairs (2001), 147-201.
Using data from a randomized housing-mobility experiment, this paper
examines the effects of neighborhood poverty on the educational outcomes of
children as reported in school administrative records. We find that the
opportunity for public housing residents to move from high-poverty to
low-poverty neighborhoods improves reading and math scores by about one-
quarter of a standard deviation compared to their control group counterparts.
The opportunity for residents of public housing to move using traditional
Section 8 housing vouchers also generates positive impacts on some reading
outcomes for young children, but no impact on math outcomes. Data limitations
kept us from concluding much about the impacts of residential mobility on the
academic achievement of older children. However, compared to the control group,
adolescents in the two experimental groups appear to be retained in grade more
frequently, and may experience greater disciplinary problems and higher dropout
Though it is theorized that neighborhood conditions are directly related to
children's educational outcomes, currently, there exists little empirical data
to support this claim. Because most families have at least some degree of
choice over where they live, observed correlations between neighborhood
characteristics and child outcomes may be due either to the causal effects of
the neighborhood environment, or to unmeasured family attributes that affect
both residential choices and children's outcomes.
In this paper the authors estimate the effects of neighborhood conditions on
children’s educational outcomes using data from the U.S. Department of Housing
and Urban Development’s (HUD) Moving to Opportunity (MTO) residential-mobility
program. Families applying for the program were randomly assigned into one of
three treatment groups. Members of the experimental group were offered
rental subsidies which could be used only for private-market housing in census tracts
with very low poverty rates, as well as counseling services and assistance in
their housing search from a local non-profit agency. Members of the Section
8-only comparison group were also offered rental subsidies, but were not
required to move to a low-poverty census tract and were not provided any
additional services. Members of the control group received no rental subsidies.
Impacts of the MTO program on
children's educational outcomes were estimated in regressions using a panel of
person-year observations for MTO children and controlling for a vector of
pre-program child and family characteristics. The randomized
experimental design of MTO breaks the link between family preferences and
neighborhood conditions, helping to overcome the self-selection problem
inherent in previous studies of neighborhood effects.
The study uses three sources of data, as follows:
HUD MTO baseline survey, completed at the time of enrollment by household
heads of all families in the program.
addresses at two time points: during the immediate post-program period
(reflecting the initial post-program moves of families), and during the
second half of 1997. The address data were obtained from local housing
authorities, change-of-address registries, credit bureaus, and a brief
follow-up survey of MTO families.
outcome data obtained from school administrative records. The main outcome
measures for the study are based on student performance on two sets of
standardized achievement test scores, the Comprehensive Test of Basic
Skills (CTBS) for elementary and middle-school
students, and the Maryland Functional Tests (MFT)
for middle- and high-school students. Other outcome measures include the
number of school absences, an indicator for disciplinary actions, and
indicators for whether the student received special education services,
dropped out of school, or was retained in grade.
Please note that there is a substantial amount of missing
data for some students in some years. This includes missing information
for children who are absent from school on standardized achievement testing
days or who are classified as having significant learning disability as well as
for children whose records the school system could not find either because of
misreporting of their name, date of birth, or social security or because they
were enrolled in a private school. Data attrition might have also occurred
because many school data-management systems are better at identifying
current-year information than historical student data. All of these
things could have certainly affected the study's results.
- The control group's educational outcomes
generally deteriorate either absolutely or relative to the national
average as children age. The MTO experimental and Section 8-only
comparison treatments seem to slow the rate of relative decline in
children’s test scores as they age, at least for younger children.
to the Section 8-only comparison treatment appears to improve young
children’s CTBS reading scores by about 6
percentile points relative to controls, equal to about one-quarter of
either the control group average or the standard deviation for reading
scores. The Section 8-only group also appears to pass the MFT reading test at a rate that is around 6 percentage
points higher than that of controls, but the difference is not
statistically significant. The authors also observe no statistically
significant difference between Section 8-only and control children in CTBS math scores.
older children (age 12 and up at random assignment) the MFT reading test reveals no statistically significant
differences across MTO treatment groups.
study observe a substantial increase in grade retentions for experimental
and Section 8-only teens relative to controls. The data are insufficient
to allow authors to conclude whether the difference in grade retentions
across groups changes over time.
the study observes relatively large increases in the proportion of
experimental and Section 8-only teens who are suspended or expelled in
school relative to control teens, although only the experimental
intent-to-treat effect is statistically significant (and at only the 10
Brennan, Brian and Manisha Modi.
“Baltimore.” Moving To Opportunity Research. Created August 30,
2000. Last modified February 25, 2004. http://www.nber.org/mtopublic/baltimore.htm.
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