A Sort of Homecoming: Incarceration and the housing security of urban men
Amanda Gellera
Marah A. Curtisb

a

Corresponding Author. Columbia University, Schools of Social Work and Law, 1255 Amsterdam
Avenue, New York, NY 10027, USA. Phone: (212)851-2380. Fax: (212)851-2206.
Email: abg2108@columbia.edu.
b
Boston University, School of Social Work, 264 Bay State Road, Boston, MA 02215, USA.
Email: mcurtis@bu.edu.
1

ABSTRACT
Securing housing is the most difficult and important barrier to successful re-entry faced by
individuals returning from prison. A safe and stable residence has long been recognized as a
prerequisite for steady employment, access to health care and social services, and other aspects of
individual and family functioning. Housing instability threatens to compound the legal problems of
ex-offenders, and increases their odds of re-incarceration. Persons released from prison face legal,
administrative and de facto restrictions on their housing options; however, little is known about the
extent of their housing instability, or whether they face greater instability than do other
socioeconomically disadvantaged populations. We analyze a longitudinal survey of urban families
and estimate a series of regression models to examine the experience of housing insecurity among
nearly 3,000 urban men, including 1,000 who have been to prison or jail. We find that men recently
incarcerated face significantly greater odds of housing insecurity in the years following their release.
Housing insecurities include serious hardships such as homelessness, as well as precursors to
homelessness such as residential turnover and relying on others for housing expenses. For other
housing outcomes, however, the increased risk associated with incarceration is not statistically
significant. The increase in housing insecurity among the formerly incarcerated is tied to reductions
in their annual earnings and to other factors. In particular, we find evidence of a link between
housing insecurity and the deliberate exclusions from public housing supported by Federal ―onestrike‖ policies.
Keywords: incarceration, housing, social exclusion

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1. Introduction
Housing security has long been recognized as an input into the economic, physical, and
emotional health of individuals and their communities, particularly for people vulnerable in other
aspects of their life, such as those in substance abuse or mental health treatment, or entitled to
public benefits such as Supplemental Security Income. (Bradley et al. 2001; Lee, Tyler and Wright
2010; Postmus et al. 2009). Access to stable housing has also been cited as a key support for women
facing intimate partner violence (Postmus et al. 2009), and a prerequisite to both obtaining and
maintaining employment (Bradley et al. 2001). Aspects of housing instability, on the other hand,
such as evictions, frequent moves, overcrowded conditions, or difficulty paying rent, have been
associated with adverse outcomes, including delayed medical care and increased use of acute services
among children and adults (Kushel et al. 2005; Ma, Gee and Kushel 2008; Reid, Vittinghoff and
Kushel 2008).
Despite the documented importance of secure and affordable housing, individuals returning
from prison, while known to be both a socially and economically vulnerable population (Petersilia
2003; Western 2006), face severe administrative and de facto barriers to attaining it. Landlords may
exclude them from the private housing market, through both cost constraints and background
checks. Further, the public housing system’s ―one strike and you’re out‖ laws grant wide discretion
to Public Housing Authorities (PHAs) to exclude or evict residents with criminal histories, and may
also place the family members of ex-offenders at risk of eviction if they welcome their formerly
incarcerated relative home after his sentence is served. Living with friends and family may also be
an unsustainable option, particularly if relationships were strained before or during the period of
incarceration (Comfort 2008; Edin, Nelson and Paranal 2004; Petersilia 2003; Roman and Travis
2006; Western 2006).

3

Recent years have seen substantial advances in our understanding of homelessness and
housing insecurity (Lee et al. 2010), and particularly our understanding of the potential reciprocal
relationship between homelessness and incarceration (Metraux, Roman and Cho 2007). However,
the literature to date is based largely on samples of individuals returning from prison and jail,
examining their experiences of homelessness, recidivism, and re-incarceration. Far less is known
about other aspects of housing insecurity, which may precede or follow homelessness, or how the
experience of housing insecurity differs between formerly incarcerated individuals and others facing
socioeconomic disadvantage.
In this analysis, we use a large longitudinal survey of urban families to assess the levels of
housing instability experienced by formerly incarcerated men, and the extent to which this instability
is unique to the formerly incarcerated. Using a series of cross-sectional and longitudinal regression
models, we estimate the associations between incarceration and men’s likelihood of homelessness or
eviction, ability to pay their rent or mortgage, frequent residential moves, or ―doubling-up‖ and
moving in with friends or relatives because of financial hardship. While we do not comment on the
extent to which these hardships reflect a causal effect of incarceration, we use detailed measures of
socioeconomic disadvantage, and controls for past housing insecurity, to reduce the likelihood that
observed relationships are confounded by factors other than incarceration. Any increased housing
risk observed among the formerly incarcerated would thus suggest a need for increased attention to
this population not only from housing authorities and social service providers, but also policymakers
involved in the re-entry process.

4

1.1. Background
1.1.1. Housing Security and Prisoner Re-Entry
The importance of housing security is well documented, and housing insecurity is viewed by
many as an indicator of severe social exclusion (Lee et al. 2010). Moreover, the stability that housing
provides is particularly salient for ex-prisoners. Returning prisoners have high rates of health,
mental health, and substance use problems (Roman and Travis 2006), and treatment for these
conditions is more easily accessible for those who have housing (Bradley et al. 2001). The National
Commission on Correctional Health Care estimated that 98,000 to 145,000 inmates with HIV were
released in the year 1996 alone. Returning prisoners also have high rates of tuberculosis, hepatitis B,
and hepatitis C. These illnesses, particularly HIV, require expensive and ongoing treatment, and
housing stability is often a prerequisite to obtaining continuous care (ibid).
Housing also takes on particular importance for returning prisoners because of their need
for employment, and the challenges they face in finding it. Employers generally require an address
on a job application, and need to be able to contact potential employees during the application
process. The difference between having stable and unstable housing can be the difference between
obtaining a job or not (Bradley et al. 2001), and can exacerbate the barriers to employment already
facing individuals returning from prison (Western, Kling and Weiman 2001).
Moreover, housing can have a direct impact on recidivism rates. Many violations of public
order, such as sleeping in public and loitering are common manifestations of homelessness, but
leave an individual at risk of summons or arrest (Center for Poverty Solutions 2002). Unstable
housing also has the potential to disrupt a returning prisoner’s contact with his parole officer.
(Roman and Travis 2006) cite a significant link between housing sustainability and recidivism, with
ex-prisoners facing an increased likelihood of rearrest with every change of residence. (Travis,
5

Solomon and Waul 2001) examine a small sample of returning prisoners in New York State and find
that individuals returning to a homeless shelter are seven times more likely to abscond from parole
than those who returned to a more stable situation. Likewise, (Metraux and Culhane 2004) examine
a cohort of nearly 50,000 New York State prison releasees, and find that those who become
homeless following their time in prison are at significantly greater risk of re-incarceration.
1.1.2. Barriers to Housing Security
There are a number of mechanisms through which incarceration risks compromising
prisoners’ housing security upon re-entry. Housing stability may be compromised by the stigma of
incarceration, lack of financial resources, difficulty securing employment, short or poor credit
history, restricted access to welfare benefits and subsidized housing, as well as strained familial
relationships (Metraux et al. 2007). Each of these challenges stand to increase the risk of housing
insecurity, above and beyond the precarious circumstances that commonly precede incarceration.
In the private rental market, property managers have the right to exclude individuals from
their buildings, and many use criminal history as a criterion for doing so. Whether having a criminal
record is a good proxy for being a ―risky‖ tenant or not, it is clear that the housing seekers would be
at a disadvantage compared to other low-income applicants; two-thirds of the 196 property
managers surveyed by (Helfgott 1997) reported requiring housing applicants to disclose any criminal
record information, and 43% indicated that they would be reluctant to accept the application of
anyone convicted of a crime, citing neighborhood safety and ―values‖ as key concerns (Helfgott
1997). In certain cases, such as those of sex offenders, individuals released from prison may also be
legally prohibited from living in circumscribed areas (Metraux et al. 2007).
In addition, the challenges that formerly incarcerated individuals face in the labor market
may limit their ability to pay for housing (Petersilia 2003; Western 2006). Even if employment is
6

secured, a limited credit and/or rental history may make the formerly incarcerated individual a less
desirable tenant than others with the same income.

Their ability to pay may be further

compromised by the welfare restrictions placed on ex-offenders.

For example, the Personal

Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA) required states to at
least temporarily deny Temporary Assistance to Needy Families (TANF) benefits and food stamps
to anyone convicted of a drug-related crime (Petersilia 2003). Nearly half of states have used their
discretionary regulation to impose a lifetime ban on welfare receipt, while the remaining 28 states
deny benefits temporarily (Petersilia 2003) These regulations place individuals convicted of drug
crimes at even further disadvantage in their attempts to afford secure housing.
While many individuals unable to afford the private housing market turn to government
assistance and public housing, most returning from jail or prison have no such option. Three
amendments to the United States Housing Act of 1937 – the Anti-Drug Abuse Act of 1988, the
Housing Opportunity Extension (HOPE) Act of 1996, and the Quality Housing and Work
Responsibility Act of 1998 – led to a ―one strike and you’re out‖ style of enforcement in Public
Housing Authorities (PHAs). In these ―one strike‖ policies, PHA’s were permitted, and in many
cases required, to evict and exclude from the application process for a ―reasonable amount of time‖
any household containing a person with a felony conviction, a background of drug-related offenses
or violent criminal activity, or anyone with a background of criminal activity that the PHA believes
would endanger the health or safety of the community. The public safety risk of the tenants and
applicants is left to the discretion of the PHA, as is the length of time considered ―reasonable‖ for
exclusion. The 1996 ―One-Strike Policy‖ also mandated that all PHAs use a case review containing
stringent background checks on applicants and all household members. In addition, PHAs are
required to exclude households with a member who has been previously evicted for a drug-related
offense for a period of three years, and to evict and exclude those subject to lifetime sexual offender
7

registration (United States Department of Housing and Urban Development 1997). In Title V of
the Quality Housing and Work Responsibility Act of 1998, Congress recommended that PHAs use
data from the National Crime Information Center to screen applicants, and that they may evict or
bar admission if any member is using controlled substances (Lundgren, Curtis and Oettinger 2010).
While the total number of individuals excluded from public housing due to one-strike
policies is unknown, (Human Rights Watch 2004) finds 46,657 people denied public housing from
PHAs in 2002. Still more were excluded from Section 8 housing, and the total, provided by the US
Department of Housing and Urban Development (HUD) is likely to undercount individuals whose
PHAs do not report their numbers to HUD. Human Rights Watch (2004) estimates that more than
3.5 million people would be denied access to housing assistance as the result of One-Strike Policies.
(Venkatesh 2002) finds that these restrictions also have implications for family reunification, as
family members without criminal histories place their access to public housing in jeopardy by
welcoming formerly incarcerated relatives and partners back into their homes.
Formerly incarcerated individuals may also be precluded from moving in with friends and
family due to the strains that incarceration places on personal relationships. In addition to the
stigma of criminal involvement, incarceration incapacitates prisoners from their family lives, and
may preclude visitation (Comfort 2008; Edin et al. 2004). Women may form new relationships while
their partner is incarcerated, and incarceration frequently leads relationships to dissolve (Western
2006).

Living rent free with family or friends or ―doubling up‖ may be a temporary solution to

avoid homelessness but is not likely sustainable in the long term (Bolland and McCallum 2002).
Finally, even in the absence of such strain, individuals returning from prison may be subject to
parole restrictions against living with others who have been criminally involved, which may rule out
a move in with family or friends (Petersilia 2003).

8

1.1.3. Empirical Evidence
A substantial literature comments upon the difficulties faced by returning prisoners (See
Petersilia 2003 for a review), and housing insecurity frequently plays a role in these challenges.
Ethnographic research identifies a ―nexus‖ in which the risks of incarceration and homelessness
reinforce each other and exacerbate the marginalization faced by severely disadvantaged individuals
(Gowan 2002). However, little is known about the extent to which men returning from prison and
jail face greater housing challenges than other disadvantaged men. The incarcerated population is
overwhelmingly young, minority, and economically disadvantaged, with low levels of education, and
most would face substantial challenges even in the absence of incarceration (Petersilia 2003; Western
2006).
Much of the evidence documenting housing instability among ex-offenders is based on small
convenience samples of men and women recently released from jail and prison (Herbert 2005;
LaVigne and Parthasarathy 2005; Travis et al. 2001). These analyses are thus unable to distinguish
housing insecurities that are unique to the formerly incarcerated population, from those insecurities
related to pre-existing disadvantage, which may have also led to the individuals’ incarceration. Even
larger studies that focus on ex-prisoners, while able to predict housing risk with a variety of preincarceration conditions (Greenberg and Rosenheck 2008; Metraux and Culhane 2004), are limited
in their comparisons and unable to distinguish homelessness among the formerly incarcerated from
the risks of homelessness faced by other disadvantaged individuals.
A smaller set of analyses seeks to identify the effects of incarceration on housing instability
using individuals’ reports of their housing circumstances before, as well as after, their time
incarcerated. A (Center for Poverty Solutions 2002) study randomly samples individuals receiving
emergency food assistance at soup kitchens and drop-in centers, and finds high rates of current
9

homelessness (31%) and low rates of housing stability (30% in permanent housing) among those
with incarceration histories. More than 30% of formerly incarcerated respondents suggested that
their incarceration experience negatively impacted their ability to obtain stable housing, and many
indeed recalled more stable housing circumstances before their incarceration than after. Likewise,
(Dyb 2009) examines a group of recently incarcerated individuals in Norway, and finds reports of
homelessness (broadly defined) were significantly higher at the time of release from prison than
interviewees recalled from before their incarceration. However, the differences observed in this line
of research are based on retrospective measures of pre-incarceration housing, and participant recall
may compromise the validity of these findings.
1.2. This Study
The current analysis uses a detailed, population-based, longitudinal survey of urban families
to identify several housing hardships experienced by formerly incarcerated men. We examine the
extent to which post-incarceration hardships exceed those faced by other disadvantaged men, and
the extent to which formerly-incarcerated men face greater insecurity after their time in prison and
jail than they did before. We also assess two potential explanations for observed differences in
housing instability, each of which stands to suggest a different policy response: reductions in
earnings, and restrictions governing public housing residence. In so doing, we stand to substantially
advance our understanding of the links between incarceration and housing instability.
2. Material and Methods
2.1. Data Source
Data are drawn from the Fragile Families and Child Wellbeing study (―Fragile Families‖),
which follows a cohort of nearly 5,000 couples with children born between 1998 and 2000 in twenty
10

large U.S. cities, with a systematic oversample of unmarried parents. The survey’s oversample of
unmarried parents produces a sample that is highly disadvantaged, and incarceration is prevalent
among the fathers. More than 40% of the fathers, including more than half those unmarried at their
child’s birth, have spent time in prison or jail. However, the fathers with no history of incarceration
are also relatively low-income, with low levels of education, and provide a valuable comparison
sample for the assessment of incarceration’s unique risks.
The study surveys both men and their partners at the time of their child’s birth, with followup surveys conducted when the children are one, three, and five years old. The study was initially
designed to examine family formation and child wellbeing, and contains detailed questions on the
roles and circumstances of fathers and a variety of aspects of social and material disadvantage,
including both housing instability and experience in the criminal justice system.
2.2. Variables
2.2.1. Incarceration
Our measure of fathers’ incarceration is based on fathers’ self-reports, supplemented with
additional indicators to reduce the risk of measurement error associated with underreporting
(Groves 2004). At each follow-up wave, fathers are asked to self-report whether they have been
charged with a crime in the years leading up to the interview; if so, they are asked if they have been
convicted, and if so, they are asked if they have been incarcerated1. The repeated measurement of
incarceration allows the identification of incidents that occur during the period of the survey, and

Due to an error in survey development, parents are asked to self-report whether they have been charged and
convicted between years three and five, but are not asked to self-report incarceration. The vast majority of
fathers report to have not been arrested or convicted (and thus not incarcerated), and a handful are reported
by their partner or another source as having been incarcerated. Only 14 are left with ambiguous incarceration
status.
1

11

importantly, allows controls for socioeconomic disadvantage and housing insecurity before these
incidents take place.
Self-reports are enhanced by ―disposition data‖ recorded by the survey subcontractors,
indicating whether a father was incarcerated at the time that they contacted him for follow-up. The
disposition data identify 121 additional incarcerated fathers between baseline and year 3, and another
122 incarcerated fathers at year 5. The incarceration measure also considers mothers’ reports of
their partners’ incarceration: mothers report at years one and three whether their partner has ever
been incarcerated, and at year five whether he has been incarcerated in the past two years. Finally,
parents’ direct reports and disposition data are supplemented with indirect reports of incarceration,
in which either parent cites incarceration as a reason the father was separated from their child or was
unable to find a job, or some other way that incarceration affected their lives. Few fathers with
incarceration histories were identified from indirect reports alone (6% of those reporting any
incarceration before year 5).
2.2.2. Housing Insecurity
Housing security and insecurity exist along a continuum from consistent stable housing to
chronic homelessness.

Where researchers and policymakers draw the line is important both

conceptually and analytically. The most severe form of insecurity, homelessness, is most commonly
defined using the federal guidelines (42 USC Sec. 11302), by which one is homeless if he or she lacks
a ―fixed, regular, and adequate nighttime residence‖, lives in temporary accommodations (e.g,
shelters, transitional housing, or welfare hotels), or sleeps in public or private spaces not intended
for sleeping (e.g., cars or abandoned buildings). However, other housing conditions may also
represent a ―manifestation of the same underlying relationship between housing costs and
household resources‖ (Honig and Filer 1993). Researchers have variously used eviction, frequent
12

moves, difficulty paying rent, spending more than 50% of household income on housing, doubling
up, and living in overcrowded conditions, as symptoms of housing instability (Gilman et al. 2003;
Kushel et al. 2005; United States Department of Housing and Urban Development 2003). An
examination of homelessness reveals several risks posed by severe housing insecurity, and links
between homelessness and other housing hardships. The majority of homeless people experience
other forms of housing instability prior to becoming homeless; likewise, many people who are
formerly homeless return to situations that continue to be insecure. Those experiencing housing
insecurity are more likely to have been homeless at some point, or to become homeless in the future,
compared to the stably housed (Reid et al. 2008).
In order to capture the full continuum of housing insecurity and the relevance of its
component parts for the formerly incarcerated, we measure housing insecurity based on
respondents’ living condition at the time of each follow-up survey, and whether he indicates any
housing hardships in the year leading up to his survey. For example, respondents are considered
insecure if they indicate homelessness (per the federal definition), eviction, or living with others but
paying no rent. 2 Doubling up and living with others without paying rent often precedes spells of
homelessness (Bolland and McCallum 2002; Rossi 1989) and is increasingly recognized as a
potentially unstable arrangement (Homeless Emergency Assistance and Rapid Transition to Housing
Act 2009). They are also considered insecure if they indicate that they had been forced, due to
financial constraints, to move in with family or friends, were unable to pay their full rent or
mortgage, or if they moved residences more than once per year in the last wave. Frequent moves
2

The Hearth Act PL 111-222 (2009) expands the definition of homelessness to include individuals or families
who are losing their housing in 14 days and lack support networks or resources to obtain housing (those
living with others and not paying rent or doubling up who face imminent loss of this arrangement are
explicitly included) as well as those who have moved very frequently and are likely to continue to do so
because of chronic physical health or mental health conditions. Particularly important for individuals recently
released from prison, the new definition of homelessness includes individuals or families who resided in a
shelter or in a venue not intended for habitation or are exiting an institution where temporarily living.
13

are destabilizing and associated with negative outcomes (Gilman et al. 2003). We examine each of
these hardships as a separate, but related dimension of housing insecurity.
We limit our analysis sample to those individuals responding to all questions indicating
housing insecurity at year 5, and not reporting incarceration as their living situation at the time of
their five-year survey, leaving a full analysis sample of 2,768. We anticipate that both incarceration
and housing insecurity are less prevalent among our analysis sample than those who we fail to
observe. Not only are more disadvantaged survey respondents more likely to attrite, the housinginsecure in particular are difficult for surveyors to locate and contact. The possibility therefore
exists that our estimates are actually a lower bound on the insecurity experienced by both our
incarcerated and never-incarcerated sample.
Table 1 details the prevalence of each type of housing security among our analysis sample.
The first column suggests a de facto rank-ordering of each type of housing instability: while 21% of
those in our analysis sample experience some sort of insecurity in the fifth year of the survey, some
forms of housing insecurity are far more common than others. More than 10% of the men
interviewed report having skipped a mortgage or rent payment in the past year, and approximately
6% report having moved in with others to save money (or ―doubling up‖). 5% report having
moved at least three times in the two years leading up to the survey, 3% report living with others but
not paying rent, and 2% each report having been evicted or homeless (i.e., living in a shelter or
elsewhere not intended for residence) in the past year. The relative rarity of events such as eviction
and homelessness underscore the severity of the conditions. Table 1 also shows that housing
insecurity is significantly more prevalent among respondents with histories of incarceration.
Overall insecurity rates are more than twice as high among formerly incarcerated respondents, and
the disparities are even more pronounced for the most serious types of hardship.

14

[Table 1 about here]
2.2.3. Control Variables
Although men with incarceration histories experience greater housing insecurity than those
never incarcerated, formerly-incarcerated and never-incarcerated men also differ on a number of
other dimensions that are likely to influence both their probability of incarceration and their housing
stability. We identify a number of demographic and socioeconomic factors, listed in Table 2, that
have been tied to both incarceration risk and housing instability, and assess differences on these
measures between men with and without incarceration histories. The first set of covariates are those
established early in life, including demographic characteristics such as race, immigrant background,
and family history, as well as behavioral traits such as cognitive ability and impulsivity, which are
linked by control theorists to criminal activity (Farrington 1998; Gottfredson and Hirschi 1990), and
may increase or impede the ability to manage finances and remain stably housed (Dickman 1990).
We define family history as whether respondents were living with their two biological parents at age
15, and whether their own mother had a history of mental health problems. Challenges in one’s
family of origin, such as parental mental illness or growing up without both biological parents, have
been tied to negative adult outcomes, which may be correlated with the risk of both incarceration
and housing insecurity (Garfinkel and McLanahan 1986).
Respondents’ cognitive ability is measured with the Wechsler Adult Intelligence ScaleRevised (Wechsler 1981), and impulsivity is measured with the Dickman (1990) scale of
dysfunctional impulsivity.

Although the measures were administered during follow-up data

collections, they are considered stable constructs, unlikely to be affected by previous incarceration
spells. If, however, impulsivity and cognitive ability are altered by an incarceration experience,
including them in the analyses will underestimate the effects of incarceration.
15

The second set of covariates contains those observed at or around the time the respondents’
focal child was born. These include age and education, and a rich set of employment, behavioral,
and family characteristics. We control for their relationship status (married vs. cohabiting vs.
nonresident) at the time of the birth, since unmarried men tend to be at greater risk for criminal
behavior (Sampson and Laub 1990), and because family structure, and partnership instability in
particular, may result in fathers moving in and out of the household with their partner and child.
Nonresident fathers may also lack the family supports that are often pivotal for men returning from
jail and prison. We also control for several factors reflecting parents’ labor market potential, health,
and substance use patterns. Each of these measures is both associated with incarceration risk
(Western 2006) and likely to compromise housing security.

Finally, because an individual’s

likelihood of incarceration is tied not only to their own behavior but to the policies governing their
local criminal justice system, and because their likelihood of housing insecurity is tied to the
conditions of local housing markets, we include city fixed effects in all models.
[Table 2 about here]
As Table 2 indicates, respondents with incarceration histories face considerable disadvantage
when compared to those who have never been to prison or jail. They are far more likely to be racial
and ethnic minorities, less likely to have grown up in a two-parent household, and more likely to
have a history of depression in their families.

They score higher on the Dickman scale of

impulsivity, are younger and in worse health when their focal child is born, and are less likely to be
married to or living with the child’s mother.

Further, they are markedly less educated, less likely to

be employed, and are more likely to report problems with substance abuse. These differences, with
few exceptions, are highly statistically significant, and each would, even in the absence of
incarceration, likely compromise their ability to remain stably housed.

16

While these covariates provide a detailed description of respondents’ life circumstances at
the time of their focal child’s birth, these descriptors may not be entirely exogenous, and may be
affected by earlier contact with the criminal justice system. Men enter our sample upon the birth of a
child, but among those men who have been to jail or prison, their median reported age of first
incarceration is 20, an average of six years before the focal child’s birth. To the extent that earlier
incarceration precludes men from fatherhood or education, or affects their relationship or other
characteristics at the child’s birth, models including these covariates may underestimate the true
effect of having been to jail or prison. To better estimate incarceration’s causal effects, net of
exogenous life circumstances, we focus our analyses, detailed below, on incarceration spells that
follow the first-year survey.
2.3. Modeling Strategy
2.3.1. Basic Estimation
Table 1 shows significantly higher rates of housing insecurity among men with incarceration
histories, and we assess the extent to which this relationship can be explained by demographic,
socioeconomic, and behavioral conditions that influence the likelihood of both incarceration and
instability. To do this, we estimate a series of logistic regression models, predicting whether
respondents indicate experiencing any insecurity in the year leading up to the five-year survey with
their lifetime incarceration history and the ―early-life covariates‖ listed in Table 2, denoted here as

X1. We then replicate Model 1 for each of the individual housing instability items listed in Table 1.
Logit (INSECURE5) =

+ 1LIFETIMEINC+ 2X1+ EE

0

(1)

Model 1 estimates disparities in housing insecurity between men with and without histories
of incarceration, and adjusts for several important correlates of both incarceration and
17

socioeconomic disadvantage—however, the possibility remains that

, the estimated relationship

1

between incarceration and housing insecurity, is biased by the omission of other factors that might
be correlated with both lifetime incarceration and insecurity. We therefore estimate a second model
that includes a second set of variables, X2, measured at baseline and the one-year survey. These
variables, the ―contemporaneous covariates‖ in Table 2, are likely to be correlated with both
incarceration and housing insecurity.

In fact, these covariates (particularly factors such as

employment or education) could themselves be influenced by early incarceration incidents (if, for
example, an early incarceration affects later labor market prospects). To avoid bias resulting from
this influence, we consider our lifetime incarceration variable in two stages: we define a variable
INC15 to indicate whether the respondent reports having been incarcerated between years 1 and 5,
and a variable INC1 to indicate whether the respondent reports having been incarcerated prior to
year 1. Because INC1 could be causally linked to the covariates in either direction, our focus in
interpretation will be on INC15.
Logit (INSECURE5) = ~ 0+ ~ 1INC15+ ~ 2INC1 + 3X1 + 4X2+ E (2)
To further isolate the relationship between incarceration and housing insecurity, we examine
the extent to which housing security changes following time spent in prison or jail. In Model 3 we
predict men’s likelihood of insecurity at year five based not only on their incarceration history and
socioeconomic covariates, but also on their experience of housing insecurity at the one-year survey.
In this model,

1

represents not the level difference in the likelihood of housing insecurity, but the

extent to which the likelihood of insecurity changes for incarcerated men, beyond the change
experienced by men not incarcerated. Where possible, the vector INSECURE1 contains indicators
of each type of insecurity presented in Table 1, measured at year 1. In cases where including each

18

aspect of insecurity prevented the model estimation from converging, INSECURE1 contains a
single indicator of whether the respondent experienced any of the six hardships.
Logit (INSECURE5) =

+ 1INC15+ 2INC1 + 3X1 + 4X2+ 5INSECURE1 +

0

(3)

2.3.2. Income and Insecurity
After estimating an average relationship between incarceration and housing insecurity in
Models 1 through 3, we next examine the extent to which this relationship is driven by a reduction
in earnings, and the extent to which it is driven by other factors. The labor market challenges
associated with incarceration are well established, and are likely to contribute to the inability of
formerly incarcerated men to remain stably housed. In Model 4, we replicate the estimation of
Model 3, but include an additional control for annual earnings at year five, after any incarceration
has occurred. An insignificant

1

in this model would indicate that at equal earnings, men with and

without incarceration histories have similar risks of insecurity, and suggest that income support
might be the best mechanism for overcoming the housing instability associated with incarceration.
Logit(INSECURE5)= 0+ 1INC15+ 2INC1+ 3X1+ 4X2+ 5INSECURE1+ 5EARN5+

(4)

2.3.3. Incarceration and Public Housing
In addition to examining the relationship between incarceration, housing, and earnings, we
also test another potential link between incarceration and housing insecurity: the administrative and
legal barriers facing ex-offenders. Specifically, in Model 5 we examine the ―one-strike‖ policy
governing criminal activity in public housing projects, and examine if incarceration is associated with
greater instability for those men whose families were in public housing prior to his time in prison or
jail. We define a binary variable PH1, which takes on a value of 1 for the 456 men who were either

19

living in public housing at year 1, or whose partners were living in public housing at that time (216
of the men in our analysis sample report living in public housing themselves, the other 240 had
partners report living in public housing).
Logit(INSECURE5)= 0+ 1INC15+ 2INC1+ 3X1+ 4X2+ 5INSECURE1+ 5PH1+ 6INC15*PH1+
(5)
In Model 5, the coefficient

5

represents the average increased (or reduced) likelihood of housing

insecurity faced by men in public housing at year 1, and the coefficient

6

represents the increase (or

reduction) in the relationship between incarceration and housing insecurity for men whose families
were in public housing before their incarceration. A positive and significant

6

would suggest that

incarceration presents a greater risk of insecurity for men in public housing, perhaps related to ―onestrike‖ policies and related factors.
3. Results and Discussion
3.1. Incarceration and Housing Insecurity
Table 1 suggests significantly higher rates of housing insecurity among men who have been
incarcerated, and our regression models further support this relationship. Table 3 presents odds
ratios indicating the increased odds of insecurity faced by incarcerated men, and associated with
other socioeconomic conditions. As shown in column 1, men who have been incarcerated at some
point in their lives face odds of insecurity that are nearly twice as high as those faced by men never
incarcerated.

In addition to this difference being statistically significant, it is of considerable

magnitude; the gap in likelihood of insecurity is greater between the formerly and never incarcerated
than it is between either blacks and whites, or Hispanics and whites.

20

Examining the individual components of insecurity, we see that formerly incarcerated men
face increased odds of insecurity by any of the six measures listed above. Moreover, the increased
risk that formerly incarcerated men face is highest for the most severe forms of instability – men
with incarceration histories face more than three times the odds of past-year eviction, and of pastyear homelessness than do comparable men who have never been incarcerated. While it is possible
that the increased odds of housing insecurity among formerly incarcerated men reflects unobserved
heterogeneity, they face drastically increased odds of serious hardship, suggesting the need for
improved re-entry assistance for those released from prison.
[Table 3 about here]
Table 4 presents the estimates of Model 2, which further limits the influence of confounding
factors in the incarceration-insecurity relationship. As the first column of Table 4 suggests, housing
insecurity is significantly more prevalent among formerly incarcerated men, though the disparity is
less pronounced when focusing on more recent incarceration, and controlling for pre-incarceration
socioeconomic status. Maternal depression and impulsivity are also associated with increased risk of
insecurity, while higher education (specifically, completing college) is associated with diminished risk.
As in Table 3, the inclusion of city fixed effects does not significantly change the increased risk faced
by formerly incarcerated men.
[Table 4 about here]
Unlike in Table 3, however, Table 4 suggests that the relationship between incarceration and
housing insecurity is not statistically significant across all outcome measures. The increased risk of a
skipped mortgage payment faced by recently-incarcerated men is statistically insignificant, as is the
increased risk of eviction. The odds of eviction are significantly higher among men incarcerated in
the more distant past, as are the odds of living with others to save money. However, because the
21

respondents were not observed before these distal incarceration incidents, we cannot determine the
extent to which this relationship is spurious, and driven by pre-incarceration disadvantage.
Table 5 presents estimates of the extent to which the odds of housing instability change
following time spent in prison or jail. As shown, the odds of instability at year 5 tend to be
significantly tied to men’s experience of instability four years earlier. Men experiencing instability at
year 1 are more likely to skip a rent or mortgage payment at year 5, while men who report skipping a
rent or mortgage payment, or moving more than once per year, are significantly more likely to
―double up‖ in later years, and move in with others to save money. Finally, the experience of
housing insecurity at year 1 is significantly related to the odds of relying on others for rent expenses
at year 5. Table 5 also suggests that incarceration has the potential to exacerbate housing insecurity
even further. Men incarcerated between the first and fifth-year surveys are significantly more likely
to experience frequent residential moves and to rely on others for their housing expenses, and are
more than twice as likely to experience a spell of homelessness at the five-year survey. They also
experience more than 20% greater odds of skipping a rent or mortgage payment, doubling up, and
being evicted, though these differences are not statistically significant.
[Table 5 about here]
Tables 3 through 5 suggest that men returning from prison or jail face substantial hardships,
above and beyond those faced by other men with low education and limited labor market histories.
We stress that our statistical models, on their own, do not necessarily imply a causal relationship
between incarceration and housing insecurity; however, the increased odds of housing insecurity
among formerly incarcerated men suggests a need to improve re-entry conditions to mitigate the
accompanying risks.

22

3.2. Incarceration and Earnings
Table 6 presents estimates from Model 4, which examines the link between incarceration and
housing in the context of post-incarceration income. To the extent that the housing insecurity faced
by formerly incarcerated men is tied to their limited earning potential, transitional jobs programs,
and other initiatives to improve the labor market prospects of ex-prisoners, are likely to have the
added benefit of improving their housing security. The findings in Table 6 indeed suggest a
protective relationship between income and housing insecurity: men with greater annual earnings at
year 5 are significantly less likely to skip a rent or mortgage payment, be evicted, rely on others for
housing expenses, or experience housing instability by our aggregate measure. However, even at
equal levels of income, men incarcerated between years 1 and 5 experienced considerably more
housing insecurity in terms of residential turnover, eviction, or the combined measure. This
marginal incarceration relationship, beyond the earnings mechanism, suggests that while income and
employment supports have the potential to reduce the hardships associated with prison re-entry,
housing circumstances might still warrant dedicated attention.
3.3. Incarceration, Insecurity, and Public Housing
Table 7 further explores mechanisms through which an incarceration effect might
compromise housing security by examining the implications of incarceration for public housing
residents and their families. The first row of Table 7 suggests, that incarceration is associated with
the risk of housing insecurity as measured by residential turnover, homelessness, and the aggregate
measure. Given the inclusion of an interaction term in this estimation suggests hardships for the
non-public housing population. The extent of insecurity among the public housing population is
measured using both the ―main effect‖ of incarceration and the interaction term. Among those men
who lived, or had partners, in public housing at year 1, incarceration in subsequent years is
23

significantly associated with an increased likelihood of skipping a rent or mortgage payment, an
increased likelihood of eviction, and increased hardship by the aggregate measure.
Most notably, the relationship between incarceration and subsequent eviction is present only
for men who were living, or had partners, in public housing prior to their incarceration. The
increased risk associated with public housing suggests that Federal one-strike policies meet their
stated goal of excluding criminally involved individuals from public housing residence. On the other
hand, while several of the other hardships faced by men following time incarcerated are more severe
among men with previous public housing ties, this relationship is not statistically significant.
4. Conclusions
4.1. Summary of Findings
As shown in Table 1, and further demonstrated in the regression analyses that follow,
housing insecurity is significantly more prevalent among men with histories of incarceration than
those who have never been incarcerated. This relationship is robust to controls for a rich array of
potential confounders, including, in some cases, pre-incarceration insecurity, and suggests that the
housing circumstances of ex-prisoners are likely to be severely compromised upon re-entry. The
increased insecurity associated with incarceration is particularly significant among some of the more
serious dimensions: formerly incarcerated men face more than twice the odds of homelessness as
men who have not been incarcerated.

Likewise, they face nearly twice the odds of moving

residences more than once per year, and of relying on others for their living expenses. On the other
hand, the odds of skipping a mortgage or rent payment, the odds of ―doubling up‖ to save money,
and the odds of eviction, are not significantly higher among recently incarcerated men when other
forms of social disadvantage are controlled for.

24

We find that housing insecurity and its relationship with incarceration are closely tied to the
limited labor market options available to ex-offenders, with post-incarceration earnings nearly
universally associated with reduced housing insecurity. However, the tie between incarceration and
housing is also related to factors beyond the labor market: even at equal levels of annual earnings,
recently incarcerated men face significantly more residential turnover and are more likely to be
evicted than their counterparts with no history of recent incarceration. In addition, we find that
men living in public housing (or with romantic partners in public housing) before their incarceration
are more likely to be evicted upon their return, suggesting that targeted housing policy may play a
role in the instability facing ex-prisoners.
4.2. Limitations and Directions for Future Research
While our analysis represents a major advance in the literature examining the nexus of
incarceration and housing insecurity, much remains to be learned. The family focus of the Fragile
Families study, and the non-incarcerated comparison sample that it provides, is an important
strength of our data; however, the study’s focus on parents rather than prisoners limits its
generalizability.

The vast majority of incarcerated men have children (Western 2006), but

incarcerated men without children are likely to differ from incarcerated fathers on many dimensions.
Our findings are unlikely to generalize to the approximately 30% of incarcerated men without
children. In addition, while the Fragile Families Study is well-equipped to identify differences
between men with and without histories of incarceration, the data are not able to distinguish jail
incarcerations from prison incarcerations.

(Metraux et al. 2007) suggest that patterns of

homelessness among individuals released from prison differ substantially from patterns of
homelessness among those released from jail. Further research and additional data are needed to
identify the extent to which these differences exist in other dimensions of housing insecurity.

25

Our analyses are also limited by the inherent difficulties in ascertaining causal relationships
from observational data. While we find that men’s odds of housing insecurity are significantly
higher among the formerly incarcerated, these differences might be driven by unobserved
heterogeneity between men with and without incarceration histories, rather than by a causal effect of
incarceration. The diminished magnitude and significance of the incarceration-insecurity relationship
in Model 2, which controls more completely for pre-incarceration disadvantage than does Model 1,
suggests that other aspects of social disadvantage contribute to the relationship. Even including
controls for pre-incarceration housing does not completely protect against a spurious relationship; if,
for example, a job loss or other life shock between the first and fifth-year surveys contributes to
both incarceration risk and housing insecurity, even the relationship measured in Model 3 will
overstate incarceration’s causal effect.
4.3. Policy Implications
Nontheless, our analyses to date reinforce the notion that men returning from prison and jail
are a highly vulnerable population. Specifically, our findings suggest that ex-prisoners are at great
risk of housing insecurity, and that this risk is tied, but not limited to, their challenges in securing
stable employment. Our findings therefore suggest the need for policy solutions both within and
beyond the labor market. Many programs have been suggested to try to raise the earnings of people
entering the labor market after prison. Most prisons provide at least some education, job training,
and work programs, and a recent round of evaluation results suggest that transitional jobs programs,
immediately after prison release, are associated with higher earnings (Bloom 2006; Jacobs and
Western 2007).

Policy advocates have also suggested limiting disqualifications on licensed

employment for ex-felons, and promoting incentives to hire ex-felons with tax incentives to

26

employers. To the extent that these suggestions increase employment among ex-offenders, and
improve their financial stability, they also stand to reduce their risk and extent of housing insecurity.
Barriers to affordable housing for men returning from prison can also be addressed directly,
through modifications to the ―one-strike‖ restrictions administratively barring ex-offenders from
public housing. Although public housing authorities are already granted very wide discretion to
consider the individual circumstances of applicant families, the complexity of and financial
incentives to enforce (data on one-strike implementation is collected and tied to funding allocations
for certain programs) ―one strike policies‖ is likely simplified in implementation by instituting a de
facto ban on individuals with an incarceration record. Given that public housing is a very scarce
resource, one strike implementation guidelines suggest that reserving this benefit for ―those who
play by the rules‖ is consistent with a practice of evicting or pushing applicants with a criminal
history to the back of a long queue (HUD 1997, p. 7-8). These policies, and the link between onestrike implementation and more general funding, must be comprehensively evaluated to balance the
social costs of this restriction with the risk posed by potential public housing tenants, and the
presumed public safety benefits associated with their exclusion.
Finally, the challenges facing individuals returning from prison must also be considered at
earlier stages of the processing of criminal cases, both when sentencing decisions are made, and
throughout the time that prisoners spend incarcerated. Housing instability and other consequences
of time spent incarcerated must be considered, along with the need for incapacitation, drug
treatment, and other rehabilitative needs, when determining appropriate treatment of convicted
offenders.

27

Table 1: Fathers’ Housing Instability (Year 5) by Incarceration History
Full Sample

Ever
Incarcerated

Never
Incarcerated

Incarceration
History
Unknown

N=2,763

N=1,052

N=1,584

N=127

Any Instability

21%

31%

14%

22%

Skipped Mortgage

11%

15%

8%

11%

Moved in with others to save
money

6%

11%

3%

4%

Moved more than once per
year

5%

8%

2%

8%

Lived with others, not paying
rent

3%

5%

2%

2%

Lived in shelter

2%

4%

1%

4%

Evicted

2%

3%

1%

2%

Analysis sample includes respondents answering all instability questions at Year 5, excluding
those incarcerated at Year 5. All differences between formerly incarcerated and never
incarcerated are statistically significant at P<.001.

28

Table 2: Demographic and Socioeconomic Characteristics by Incarceration History
Full
Sample

Ever
Incarcerated

Never
Incarcerated

Incarceration
History
Unknown

White***

22%

13%

29%

13%

Black***

47%

60%

38%

49%

Hispanic**

23%

20%

25%

28%

Other

7%

7%

7%

9%

Foreign-Born***

15%

6%

20%

24%

Lived with both parents at age 15***

44%

31%

53%

36%

Mother experienced depression***

24%

28%

22%

24%

Cognitive Score (0=low, 15=high)***

6.64

6.37

6.85

6.12

Impulsivity (0=low, 6=high)***

0.94

1.28

0.78

1.08

Age at baseline***

28.3

26.2

29.3

29.3

Married at baseline***

31%

10%

45%

32%

Cohabiting at baseline***

39%

47%

35%

37%

Nonresident at baseline***

30%

44%

20%

31%

Baseline education: <HS***

29%

41%

22%

29%

Baseline education: HS grad**

37%

40%

34%

43%

Baseline education: Some college***

20%

16%

23%

14%

Baseline education: College grad***

13%

2%

21%

9%

Employed at baseline***

85%

76%

90%

88%

Substance abuse at baseline***

10%

17%

5%

8%

Father in good health at baseline***

73%

68%

75%

76%

Early Life

Contemporaneous covariates

***P .001, **P .01, *P .05

29

Table 3: Housing insecurity at year 5, by lifetime incarceration history and demographic and socioeconomic covariates
(1)
(2)
(3)
(4)
(5)

VARIABLE

Any Insecurity
Odds Ratio, SE
1.93 [0.111]***
1.60 [0.152]**
1.63 [0.193]*
1.40 [0.242]
0.74 [0.190]
0.99 [0.020]
0.81 [0.108]*
1.32 [0.115]*
1.32 [0.064]***

Skipped Mortgage
or Rent Payment
Odds Ratio, SE
1.42 [0.143]*
1.46 [0.195]
1.54 [0.250]
1.05 [0.338]
0.83 [0.242]
0.97 [0.026]
0.63 [0.143]**
1.53 [0.140]**
1.24 [0.083]**

Lifetime Incarceration
Black
Hispanic
Other
Foreign born
Cognitive Ability
Grew up with both parents?
Maternal history of depression?
Impulsivity
* p<0.05, **p<0.01, ***p<0.001
City FE and missing data indicators included in model, but not table.

"Doubled Up"
Odds Ratio, SE
2.17 [0.192]***
1.94 [0.267]*
1.52 [0.337]
2.10 [0.386]
0.38 [0.466]*
1.04 [0.033]
0.77 [0.188]
1.65 [0.181]**
1.36 [0.106]**

30

Moved >1x per
year
Odds Ratio, SE
2.56 [0.239]***
1.13 [0.270]
1.27 [0.363]
1.38 [0.418]
0.89 [0.349]
1.01 [0.038]
1.00 [0.205]
2.15 [0.201]***
1.42 [0.127]**

Lived with others,
did not pay rent
Odds Ratio, SE
1.85 [0.249]*
1.72 [0.365]
1.19 [0.471]
1.28 [0.568]
0.87 [0.488]
1.01 [0.037]
1.36 [0.235]
0.63 [0.315]
1.32 [0.137]*

(6)

Lived in shelter or
other place not
intended for
residence
Odds Ratio, SE
3.99 [0.386]***
2.29 [0.463]
1.81 [0.578]
1.29 [0.757]
0.52 [0.560]
1.08 [0.049]
1.18 [0.283]
2.82 [0.267]***
1.55 [0.187]*

(7)

Evicted
Odds Ratio
3.21 [0.408]
1.73 [0.611]
1.34 [0.668]
1.17 [0.867]
1.24 [0.493]
0.97 [0.072]
0.47 [0.359]
1.72 [0.322]
0.79 [0.247]

Table 4: Housing insecurity at year 5, by incarceration history (Y1-Y5) and demographic and socioeconomic covariates
(1)
(2)
(3)
(4)
(5)

VARIABLE

Any Insecurity
Odds Ratio, SE
1.69 [0.129]***
1.22 [0.122]
1.41 [0.164]*
1.33 [0.200]
1.23 [0.246]
0.80 [0.197]
0.99 [0.008]
1.00 [0.021]
0.94 [0.113]
1.27 [0.118]*
1.23 [0.066]**
1.25 [0.145]
1.04 [0.165]
0.99 [0.124]
1.04 [0.138]
0.28 [0.299]***
1.11 [0.146]
1.46 [0.155]*
0.87 [0.117]

Skipped Mortgage
or Rent Payment
Odds Ratio, SE
1.24 [0.168]
1.20 [0.162]
1.40 [0.211]
1.39 [0.257]
0.98 [0.333]
0.85 [0.249]
1.00 [0.009]
0.98 [0.027]
0.65 [0.149]**
1.47 [0.143]**
1.22 [0.085]*
1.13 [0.183]
0.79 [0.208]
0.95 [0.160]
1.25 [0.170]
0.24 [0.426]***
1.24 [0.192]
1.45 [0.193]
0.83 [0.149]

Incarceration (Y1-Y5)
Incarceration (before Y1)
Black
Hispanic
Other
Foreign born
Age (at baseline)
Cognitive Ability
Grew up with both parents
Maternal history of depression
Impulsivity
Cohabiting at baseline
Nonresident at baseline
Baseline education: <HS
Baseline education: some college
Baseline education: college grad
Employed at baseline
Substance use at baseline
Reports good health at baseline
* p<0.05, **p<0.01, ***p<0.001
City FE and missing data indicators included in model, but not table.

31

"Doubled Up"
Odds Ratio, SE
1.48 [0.198] *
1.64 [0.194] *
1.60 [0.282]
1.19 [0.352]
1.75 [0.409]
0.42 [0.484]
0.98 [0.013]
1.06 [0.034]
0.96 [0.195]
1.56 [0.185]*
1.23 [0.109]
1.23 [0.278]
1.16 [0.305]
1.00 [0.196]
0.69[0.255]
0.16 [0.735] *
0.81 [0.225]
1.12 [0.248]
1.00 [0.200]

Moved >1x per
year
Odds Ratio, SE
1.99 [0.230]**
0.95 [0.241]
1.20 [0.287]
1.16 [0.385]
1.33 [0.430]
0.81 [0.383]
0.97 [0.015]*
1.02 [0.040]
1.20 [0.217]
2.03 [0.207]***
1.31 [0.131]*
1.25 [0.310]
1.01 [0.341]
1.67 [0.223]*
1.00 [0.299]
0.52 [0.572]
1.08 [0.268]
1.81 [0.253]*
1.51 [0.231]

Lived with others,
did not pay rent
Odds Ratio, SE
1.86 [0.273]*
1.21 [0.258]
1.13 [0.409]
0.71 [0.472]
0.83 [0.592]
1.14 [0.522]
0.95 [0.026]*
1.01 [0.040]
2.28 [0.265]**
0.61 [0.323]
1.14 [0.138]
1.17 [0.364]
1.74 [0.410]
0.78 [0.267]
0.84 [0.337]
0.40 [0.652]
0.64 [0.296]
0.62 [0.438]
0.77 [0.271]

(6)

Lived in shelter
or other place
not intended for
residence
Odds Ratio, SE
2.81 [0.349]**
0.95 [0.335]
1.87 [0.496]
1.61 [0.606]
1.19 [0.767]
0.50 [0.553]
1.00 [0.019]
1.10 [0.052]
1.18 [0.309]
2.79 [0.277]***
1.53 [0.199]*
1.32 [0.500]
1.65 [0.532]
0.95 [0.324]
0.81 [0.375]
0.23 [1.166]
0.93 [0.322]
1.77 [0.373]
1.30 [0.346]

(7)

Evicted
Odds Ratio
1.79 [0.422
2.08 [0.400
1.68 [0.663
1.36 [0.720
1.10 [0.883
1.32 [0.505
1.01 [0.018
0.98 [0.072
0.49 [0.362
1.72 [0.320
0.69 [0.241
1.30 [0.489
1.62 [0.554
2.04 [0.403
1.39 [0.516
1.05 [0.797
0.67 [0.395
1.03 [0.471
1.20 [0.393

Table 5: Incarceration and Housing Instability, Controlling for Y1 Instability
(1)
(2)
(3)
(4)

VARIABLE

Any Insecurity
Odds Ratio, SE
1.65 [0.131] ***
1.24[0.124]
1.76 [0.149] ***
0.80 [0.359]
1.39 [0.185]
1.77 [0.310]
1.59 [0.230] *
1.46 [0.164] *

Skipped Mortgage
or Rent Payment
Odds Ratio, SE
1.22 [0.169]
1.19 [0.164]

Incarceration (Y1-Y5)
Incarceration (before Y1)
Y1 instability: skipped payment
Y1 instability: evicted
Y1 instability: "doubled up"
Y1 instability: homeless
Y1 instability: lived with others, no rent
Y1 instability: moved >1x/year
Y1 instability: Any instability
1.55 [0.148]
Black
1.45 [0.167] *
1.40 [0.210]
Hispanic
1.31 [0.203]
1.37 [0.256]
Other
1.19 [0.249]
0.98 [0.331]
Foreign born
0.88 [0.200]
0.89 [0.249]
Age (at baseline)
0.99 [0.008]
1.01 [0.010]
Cognitive Ability
1.00 [0.021]
0.98 [0.027]
Grew up with both parents
0.91 [0.115]
0.64 [0.148]
Maternal history of depression
1.24 [0.120]
1.45 [0.144]
Impulsivity
1.26 [0.068] ***
1.23 [0.086]
Cohabiting at baseline
1.19 [0.146]
1.09 [0.183]
Nonresident at baseline
0.96 [0.166]
0.76 [0.207]
Baseline education: <HS
0.99 [0.125]
0.95 [0.161]
Baseline education: some college
1.04 [0.140]
1.25 [0.171]
Baseline education: college grad
0.30 [0.300] ***
0.25 [0.424]
Employed at baseline
1.15 [0.148]
1.29 [0.194]
Substance use at baseline
1.39 [0.158] *
1.40 [0.196]
Reports good health at baseline
0.87 [0.119]
0.81 [0.149]
* p<0.05, **p<0.01, ***p<0.001
City FE and missing data indicators included in model, but not table.

"Doubled Up"
Odds Ratio, SE
1.38 [0.204]
1.61 [0.202] *
1.73 [0.242] *
1.13 [0.517]
1.28 [0.265]
2.18 [0.419]
0.63 [0.409]
2.22 [0.238] ***

**

**
**
*

***

32

1.77 [0.291] *
1.19 [0.362]
1.88 [0.412]
0.50 [0.485]
0.98 [0.013]
1.06 [0.035]
0.91 [0.201]
1.48 [0.190] *
1.27 [0.112] *
1.17 [0.279]
1.07 [0.307]
1.00 [0.199]
0.72 [0.256]
0.18 [0.738] *
0.79 [0.228]
1.01 [0.262]
1.02 [0.204]

Moved >1x per
year
Odds Ratio, SE
1.96 [0.231] **
0.95 [0.246]

1.28 [0.212]
1.19 [0.286]
1.14 [0.384]
1.33 [0.430]
0.83 [0.383]
0.97 [0.015]
1.02 [0.040]
1.18 [0.215]
2.01 [0.208]
1.31 [0.131]
1.22 [0.309]
0.99 [0.339]
1.67 [0.222]
1.00 [0.298]
0.53 [0.570]
1.09 [0.266]
1.76 [0.254]
1.51 [0.232]

*

***
*

*

*

(5)

(6)

Lived with
others, did not
pay rent
Odds Ratio, SE
1.78 [0.274] *
1.29 [0.267]
0.84 [0.377]
0.07 [0.905] **
2.49 [0.337] **
3.73 [0.545] *
4.73 [0.338] ***
1.09 [0.351]

Lived in shelter
or other place not
intended for
residence
Odds Ratio, SE
2.68 [0.342] **
0.96 [0.344]
1.53 [0.409]
0.27 [1.345]
1.23 [0.438]
1.09 [0.777]
0.59 [0.812]
1.79 [0.393]

1.08 [0.414]
0.58 [0.492]
0.60 [0.604]
1.57 [0.518]
0.96 [0.026]
1.02 [0.043]
2.21 [0.266] **
0.62 [0.333]
1.17 [0.143]
1.12 [0.358]
1.44 [0.410]
0.87 [0.268]
0.80[0.339]
0.45 [0.661]
0.72 [0.311]
0.53 [0.483]
0.74 [0.272]

2.04 [0.476]
1.67 [0.601]
1.29 [0.743]
0.53 [0.553]
1.00 [0.019]
1.11 [0.052] *
1.14 [0.319]
2.80 [0.278] ***
1.56 [0.198] *
1.29 [0.499]
1.62 [0.519]
0.95 [0.331]
0.79 [0.374]
0.23 [1.165]
0.95 [0.320]
1.56 [0.411]
1.26 [0.342]

(7)

Evicted
Odds Ratio,
1.81 [0.422]
2.11 [0.408]

0.88 [0.413]
1.67 [0.659]
1.35 [0.718]
1.09 [0.887]
1.30 [0.501]
1.01 [0.018]
0.98 [0.072]
0.50 [0.363]
1.74 [0.317]
0.69 [0.245]
1.32 [0.494]
1.63 [0.555]
2.06 [0.400]
1.39 [0.517]
1.04 [0.799]
0.66 [0.392]
1.05 [0.475]
1.20 [0.391]

Table 6: Housing insecurity at year 5, examining incarceration and earnings
(1)
(2)
(3)
(4)

VARIABLE

Any Insecurity
Odds Ratio, SE
1.50 [0.134]**
1.21 [0.126]
0.90 [0.016]***
1.79 [0.150]***
0.81 [0.361]
1.40 [0.185]
1.79 [0.314]
1.58 [0.227]*
1.43 [0.165]*

Incarceration (Y1-Y5)
Incarceration (before Y1)
Earnings (Y5, logged)
Y1 insecurity: skipped payment
Y1 insecurity: evicted
Y1 insecurity: "doubled up"
Y1 insecurity: homeless
Y1 insecurity: lived with others, no rent
Y1 insecurity: moved >1x/year
Y1 insecurity: any insecurity
Black
1.40 [0.167]*
Hispanic
1.29 [0.202]
Other
1.07 [0.258]
Foreign born
0.91 [0.200]
Age (at baseline)
0.99 [0.008]
Cognitive Ability
1.00 [0.022]
Grew up with both parents
0.92 [0.117]
Maternal history of depression
1.24 [0.121]
Impulsivity
1.22 [0.069]**
Cohabiting at baseline
1.14 [0.148]
Nonresident at baseline
0.91 [0.167]
Baseline education: <HS
0.95 [0.127]
Baseline education: some college
1.07 [0.142]
Baseline education: college grad
0.33 [0.299]***
Employed at baseline
1.34 [0.157]
Substance use at baseline
1.40 [0.158]*
Reports good health at baseline
0.90 [0.120]
* p<0.05, **p<0.01, ***p<0.001
City FE and missing data indicators included in model, but not table.

Skipped
Mortgage or Rent
Payment
Odds Ratio, SE
1.10 [0.174]
1.16 [0.166]
0.90 [0.018]***

1.57 [0.149]**
1.33 [0.210]
1.33 [0.256]
0.83 [0.341]
0.93 [0.249]
1.00 [0.010]
0.97 [0.028]
0.64 [0.151]**
1.46 [0.145]**
1.18 [0.087]
1.03 [0.186]
0.72 [0.209]
0.90 [0.163]
1.29 [0.173]
0.28 [0.425]**
1.57 [0.206]*
1.39 [0.195]
0.84 [0.151]

33

"Doubled Up"
Odds Ratio, SE
1.29 [0.209]
1.57 [0.202]*
0.92 [0.022]***
1.76 [0.241]*
1.16 [0.513]
1.30 [0.264]
2.33 [0.408]*
0.64 [0.399]
2.19 [0.237]***
1.71 [0.293]
1.13 [0.361]
1.65 [0.421]
0.53 [0.488]
0.97 [0.013]
1.06 [0.036]
0.93 [0.203]
1.48 [0.192]*
1.24 [0.113]
1.13 [0.279]
1.04 [0.307]
0.96 [0.200]
0.75 [0.255]
0.20 [0.737]*
0.87 [0.235]
1.01 [0.267]
1.04 [0.204]

Moved >1x per
year
Odds Ratio, SE
1.93 [0.238]**
0.94 [0.246]
0.98 [0.028]

1.28 [0.211]
1.18 [0.288]
1.14 [0.383]
1.30 [0.434]
0.84 [0.382]
0.97 [0.015]*
1.02 [0.040]
1.19 [0.218]
2.00 [0.208]***
1.30 [0.131]*
1.22 [0.309]
0.98 [0.340]
1.66 [0.221]*
1.00 [0.298]
0.54 [0.570]
1.11 [0.271]
1.77 [0.253]*
1.53 [0.234]

(5)

(6)

Lived with
others, did not
pay rent
Odds Ratio, SE
1.56 [0.271]
1.25 [0.261]
0.91 [0.033]**
0.91 [0.377]
0.05 [0.864]***
2.33 [0.340]*
3.92 [0.547]*
4.70 [0.328]***
1.10 [0.354]

Lived in shelter
or other place not
intended for
residence
Odds Ratio, SE
2.29 [0.357]
0.90 [0.344]
0.86 [0.029]
1.51 [0.404]
0.27 [1.371]
1.38 [0.420]
1.23 [0.734]
0.57 [0.857]
1.74 [0.395]

1.06 [0.419]
0.57 [0.501]
0.61 [0.606]
1.60 [0.513]
0.95 [0.027]
1.02 [0.045]
2.21 [0.265]**
0.62 [0.329]
1.12 [0.145]
1.02 [0.365]
1.35 [0.414]
0.87 [0.267]
0.82 [0.339]
0.49 [0.660]
0.84 [0.319]
0.56 [0.472]
0.75 [0.271]

1.88 [0.490]
1.51 [0.616]
0.89 [0.789]
0.59 [0.551]
0.99 [0.021]
1.09 [0.054]
1.22 [0.332]
2.84 [0.283]
1.48 [0.205]
1.33 [0.525]
1.62 [0.537]
0.87 [0.321]
0.81 [0.374]
0.31 [1.126]
1.29 [0.346]
1.64 [0.423]
1.38 [0.351]

(

Ev
Odds R
1.71 [0.4
2.10 [0.4
0.94 [0.0

0.88 [0.4
1.61 [0.6
1.37 [0.7
1.03 [0.8
1.33 [0.5
1.01 [0.0
0.98 [0.0
0.50 [0.3
1.72 [0.3
0.67 [0.2
1.26 [0.4
1.58 [0.5
2.00 [0.4
1.37 [0.5
1.07 [0.8
0.73 [0.4
1.05 [0.4
1.21 [0.3

Table 7: Housing insecurity at year 5, examining Incarceration and Public Housing Interaction
(1)
(2)
(3)
(4)
(5)

VARIABLE

Any Insecurity
Odds Ratio, SE
1.60 [0.146]**
0.83 [0.163]
1.14 [0.285]
1.24 [0.125]
1.74 [0.149]***
0.79 [0.362]
1.38 [0.185]
1.80 [0.312]
1.61 [0.231]*
1.47 [0.164]*

Incarceration (Y1-Y5)
Public Housing (Y1)
Incarc (Y1-Y5) x PH (Y1)
Incarceration (before Y1)
Y1 insecurity: skipped payment
Y1 insecurity: evicted
Y1 insecurity: "doubled up"
Y1 insecurity: homeless
Y1 insecurity: lived with others, no rent
Y1 insecurity: moved >1x/year
Y1 insecurity: any insecurity
Black
1.49 [0.169]*
Hispanic
1.33 [0.203]
Other
1.21 [0.250]
Foreign born
0.88 [0.200]
Age (at baseline)
0.99 [0.008]
Cognitive Ability
1.00 [0.021]
Grew up with both parents
0.91 [0.115]
Maternal history of depression
1.24 [0.120]
Impulsivity
1.26 [0.068]***
Cohabiting at baseline
1.19 [0.147]
Nonresident at baseline
0.97 [0.168]
Baseline education: <HS
1.00 [0.125]
Baseline education: some college
1.03 [0.141]
Baseline education: college grad
0.30 [0.299]***
Employed at baseline
1.15 [0.148]
Substance use at baseline
1.38 [0.159]*
Reports good health at baseline
0.87 [0.119]
* p<0.05, **p<0.01, ***p<0.001
City FE and missing data indicators included in model, but not table.

Skipped
Mortgage or
Rent Payment
Odds Ratio, SE
1.07 [0.191]
0.80 [0.214]
1.76 [0.349]
1.18 [0.165]

1.56 [0.148]**
1.40 [0.212]
1.36 [0.256]
0.98 [0.332]
0.89 [0.249]
1.01 [0.010]
0.98 [0.027]
0.64 [0.148]**
1.45 [0.144]**
1.23 [0.086]*
1.10 [0.183]
0.78 [0.208]
0.95 [0.161]
1.25 [0.171]
0.24 [0.423]***
1.30 [0.193]
1.41 [0.196]
0.81 [0.149]

34

"Doubled Up"
Odds Ratio, SE
1.38 [0.235]
0.98 [0.274]
1.01 [0.441]
1.61 [0.203]*
1.73 [0.241]*
1.13 [0.520]
1.28 [0.265]
2.19 [0.421]
0.63 [0.409]
2.22 [0.240]***
1.78 [0.292]*
1.19 [0.363]
1.91 [0.413]
0.50 [0.486]
0.98 [0.013]
1.06 [0.035]
0.91 [0.201]
1.48 [0.191]*
1.27 [0.113]*
1.17 [0.280]
1.06 [0.309]
1.00 [0.200]
0.72 [0.257]
0.18 [0.738]*
0.79 [0.229]
1.01 [0.262]
1.02 [0.204]

Moved >1x per
year
Odds Ratio, SE
2.07 [0.248]**
0.73 [0.350]
0.75 [0.534]
0.97 [0.247]

1.25 [0.215]
1.28 [0.284]
1.18 [0.381]
1.37 [0.430]
0.83 [0.382]
0.97 [0.015]*
1.02 [0.040]
1.18 [0.216]
2.04 [0.207]***
1.30 [0.132]*
1.23 [0.313]
1.00 [0.345]
1.70 [0.222]*
0.97 [0.301]
0.52 [0.572]
1.07 [0.268]
1.75 [0.254]*
1.51 [0.232]

Lived with
others, did not
pay rent
Odds Ratio, SE
1.56 [0.325]
0.88 [0.399]
1.66 [0.608]
1.28 [0.268]
0.85 [0.377]
0.07 [0.928]**
2.55 [0.336]**
3.76 [0.540]*
4.68 [0.340]***
1.11 [0.355]
1.05 [0.421]
0.57 [0.493]
0.60 [0.597]
1.59 [0.525]
0.96 [0.026]
1.02 [0.043]
2.23 [0.267]**
0.62 [0.332]
1.18 [0.146]
1.13 [0.360]
1.45 [0.416]
0.87 [0.271]
0.80 [0.340]
0.44 [0.656]
0.72 [0.311]
0.53 [0.485]
0.74 [0.272]

(6)
Lived in shelter
or other place
not intended for
residence
Odds Ratio, SE
2.57 [0.367]*
0.82 [0.554]
1.24 [0.779]
0.96 [0.346]
1.52 [0.409]
0.27 [1.350]
1.22 [0.444]
1.09 [0.778]
0.59 [0.802]
1.80 [0.397]
2.06 [0.478]
1.69 [0.603]
1.30 [0.751]
0.53 [0.554]
1.00 [0.020]
1.11 [0.052]*
1.14 [0.319]
2.80 [0.278]***
1.56 [0.199]*
1.29 [0.505]
1.63 [0.527]
0.96 [0.335]
0.78 [0.376]
0.22 [1.161]
0.96 [0.321]
1.56 [0.411]
1.26 [0.343]

(7)

Evicte
Odds Rat
0.96 [0.5
0.27 [0.7
11.10 [0.9
2.09 [0.4

0.90 [0.4
1.63 [0.6
1.26 [0.7
1.07 [0.8
1.36 [0.5
1.01 [0.0
0.98 [0.0
0.50 [0.3
1.82 [0.3
0.67 [0.2
1.37 [0.4
1.74 [0.5
2.10 [0.4
1.38 [0.5
0.83 [0.7
0.65 [0.3
1.04 [0.4
1.20 [0.3

Acknowledgments
This work was supported by a grant from the Robert Wood Johnson Foundation. The Fragile
Families and Child Wellbeing Study was supported by Grant R01HD36916 from the National
Institute of Child Health and Human Development. The contents of the article are solely the
responsibility of the authors and do not necessarily represent the official views of the National
Institute of Child Health and Human Development. Tim Smeeding, Melinda Sandler Morrill, and
Christopher Wildeman provided valuable feedback on earlier versions of this analysis. Allyson
Walker and Alexander Ramani provided excellent research assistance. All errors and conclusions are
those of the authors alone.

35

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39