trajectories of economic disconnection among families in the child welfare system

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Trajectories of Economic Disconnection among Families in the Child Welfare System Jennifer L. Hook 1 , Jennifer L. Romich 2 , JoAnn S. Lee 3 , Maureen O. Marcenko 2 , and Ji Young Kang 2 1 University of Southern California, 2 University of Washington, and 3 George Mason University ABSTRACT This study examined economic disconnection, an extreme case of economic exclusion in which families lack both employment and cash assistance, among families in the child wel- fare system. To build hypotheses about the intersection of the child welfare system and eco- nomic disconnection we used a multilevel framework that considers federal policy, local practice, and processes within families. We hypothesized that child welfare intervention has the potential to be a mechanism of economic inclusion or exclusion for vulnerable families, with implications for family reunification. We utilized a novel administrative data set con- taining data from three state agencies to construct income histories of parents relative to their child’s placement in foster care (N ¼ 15,159 parents). We identified eight trajectories using group-based trajectory modeling. About two-thirds of parents experience economic disconnection over a three-year period; these families are least likely to reunify. Although providing economic resources to families is typically beyond the scope of child welfare, ef- forts to minimize the negative impact of child placement on parents’ economic connection is likely to improve both the economic inclusion of poor families and family reunification. KEYWORDS : child-related family policy; welfare; low-income families; poverty; child welfare. Scholars of stratification have noted increasing economic insecurity among U.S. families. The growth of precarious employment and single parent families accompanied by sizable public policy shifts— namely welfare reform in the 1990s—have made stable economic connection more tenuous, The UC Davis Center for Poverty Research funded this analysis through a grant to Jennifer Hook. The U.S. Department of Health and Human Services/Administration for Children and Families funded data acquisition through a grant to the University of Washington West Coast Poverty Center and final writing through Romich’s Family Self Sufficiency and Stability Research Scholars award (90PD0279). Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant, R24 HD042828, to the Center for Studies in Demography & Ecology at the University of Washington. The authors wish to acknowledge the contributions of Partners for Our Children, the Washington State Department of Social and Health Services Research and Data Analysis Division, Children’s Administration, and the Employment Security Department. The authors also wish to thank Mark Eddy, Matt Orme, Sharon Estee, David Mancuso, Rebecca Yette, Roger Calhoun, Maija Sandberg, Dori Shoji, Susan Barkan, Maureen Newby, Joe Mienko, Betsy Feldman, Kathy Brennan, and Emily Putnam-Hornstein. Direct correspondence to: Jennifer L. Hook, Associate Professor, Department of Sociology, University of Southern California, 851 Downey Way, Hazel Stanley Hall 314, Los Angeles, CA 90089-2539. E-mail: [email protected]. V C The Author 2016. Published by Oxford University Press on behalf of the Society for the Study of Social Problems. All rights reserved. For permissions, please e-mail: [email protected] 161 Social Problems, 2016, 63, 161–179 doi: 10.1093/socpro/spw006 Article by guest on May 3, 2016 http://socpro.oxfordjournals.org/ Downloaded from

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Trajectories of Economic Disconnectionamong Families in the Child Welfare

SystemJennifer L. Hook1, Jennifer L. Romich2, JoAnn S. Lee3,

Maureen O. Marcenko2, and Ji Young Kang2

1University of Southern California, 2University of Washington, and 3George Mason University

A B S T R A C T

This study examined economic disconnection, an extreme case of economic exclusion inwhich families lack both employment and cash assistance, among families in the child wel-fare system. To build hypotheses about the intersection of the child welfare system and eco-nomic disconnection we used a multilevel framework that considers federal policy, localpractice, and processes within families. We hypothesized that child welfare intervention hasthe potential to be a mechanism of economic inclusion or exclusion for vulnerable families,with implications for family reunification. We utilized a novel administrative data set con-taining data from three state agencies to construct income histories of parents relative totheir child’s placement in foster care (N ¼ 15,159 parents). We identified eight trajectoriesusing group-based trajectory modeling. About two-thirds of parents experience economicdisconnection over a three-year period; these families are least likely to reunify. Althoughproviding economic resources to families is typically beyond the scope of child welfare, ef-forts to minimize the negative impact of child placement on parents’ economic connectionis likely to improve both the economic inclusion of poor families and family reunification.

K E Y W O R D S : child-related family policy; welfare; low-income families; poverty; childwelfare.

Scholars of stratification have noted increasing economic insecurity among U.S. families. The growthof precarious employment and single parent families accompanied by sizable public policy shifts—namely welfare reform in the 1990s—have made stable economic connection more tenuous,

The UC Davis Center for Poverty Research funded this analysis through a grant to Jennifer Hook. The U.S. Department of Healthand Human Services/Administration for Children and Families funded data acquisition through a grant to the University ofWashington West Coast Poverty Center and final writing through Romich’s Family Self Sufficiency and Stability Research Scholarsaward (90PD0279). Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health andHuman Development research infrastructure grant, R24 HD042828, to the Center for Studies in Demography & Ecology at theUniversity of Washington. The authors wish to acknowledge the contributions of Partners for Our Children, the Washington StateDepartment of Social and Health Services Research and Data Analysis Division, Children’s Administration, and the EmploymentSecurity Department. The authors also wish to thank Mark Eddy, Matt Orme, Sharon Estee, David Mancuso, Rebecca Yette, RogerCalhoun, Maija Sandberg, Dori Shoji, Susan Barkan, Maureen Newby, Joe Mienko, Betsy Feldman, Kathy Brennan, and EmilyPutnam-Hornstein. Direct correspondence to: Jennifer L. Hook, Associate Professor, Department of Sociology, University ofSouthern California, 851 Downey Way, Hazel Stanley Hall 314, Los Angeles, CA 90089-2539. E-mail: [email protected].

VC The Author 2016. Published by Oxford University Press on behalf of the Society for the Study of Social Problems. All rights reserved.For permissions, please e-mail: [email protected]

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particularly for low-income families with children (Hacker 2008; Kalleberg 2011; McLanahan 2004;Western, Bloome, and Percheski 2008). One consequence of increasing insecurity is a rise in eco-nomically disconnected families, that is, families without income from either work or welfare(Danziger 2010; Turner, Danziger, and Seefeldt 2006). Economic disconnection is economic exclu-sion at its extreme. National estimates show that economic disconnection among low-educated singlemothers has increased from 13 percent or less in the two decades prior to welfare reform to 25 per-cent in 2008 (Danziger 2010).

Economic disconnection emerged as a topic of policy concern in the wake of welfare reform inthe 1990s (Blank and Kovak 2007; Turner et al. 2006). Welfare reform eliminated the concept of fi-nancial entitlement to benefits and replaced it with time-limited benefits with a work-first focus.Following welfare reform, caseloads declined, employment increased, and the number of economic-ally disconnected families grew (Danziger 2010). Economic disconnection has been of particular con-cern because the consequences of extreme poverty, including difficulties meeting basic needs such ashousing and food, pose significant risks to child development (Duncan and Brooks-Gunn 2000).

While welfare reform was changing the landscape of cash assistance for poor families, the 1997Adoption and Safe Families Act (ASFA) made similar changes in the child welfare system. ASFAshared some of the same principles as welfare reform, instituting timelines within which parents’rights to their children should be terminated, diminishing the emphasis on preserving families andproviding incentives for states to increase adoptions (Reich 2005; Roberts 2002). The combinationof welfare time limits and shortened timelines to family reunification has created enormous pressureson families and reshaped child welfare practice.

Although there is a long tradition of poverty research in the field of child welfare (Pelton 1989),little is known about the extent and nature of economic disconnection among child welfare–involvedfamilies or its relationship to family outcomes. Poverty scholars have focused attention on adverseevents causing spells of poverty or economic disconnection, including job loss, relationship dissol-ution, and public benefits interruption (Bane and Ellwood 1986; Blank and Kovak 2007; Turneret al. 2006). For a particularly vulnerable subgroup of largely poor single mothers, child welfare in-volvement may trigger such an event.

We hypothesize that child welfare intervention may be a mechanism of economic inclusion or ex-clusion for families, with important consequences for family reunification, which has ramifications forchildren, families, and the child welfare system. In order to explore our hypotheses we examine trajec-tories of economic disconnection relative to child welfare involvement and the association betweentrajectories and family reunification using linked administrative data from three state agencies. Thenature and relative size of trajectory groups identified provide useful detail about the relationship be-tween entry to child welfare and economic disconnection. In this article, we (1) discern patterns offamily income dynamics relative to spells of child welfare involvement; (2) describe which familiesare most likely to follow each trajectory; and (3) assess the association between trajectories and fam-ily reunification. We begin with a brief overview of the child welfare system and the literature on eco-nomic disconnection and then build hypotheses about the intersection of the two using a multilevelframework that considers federal policy, local practice, and processes within families.

C H I L D W E L F A R E S Y S T E MThe child welfare system is designed to “promote the well-being of children by ensuring safety,achieving permanency, and strengthening families . . .” (Child Welfare Information Gateway 2013).To achieve these goals, state public child welfare agencies are responsible for investigating reports ofabuse and neglect, providing services to assist families, arranging for children to live with kin or fosterfamilies when they cannot live safely at home, and establishing a permanent home for childrenthrough reunification, adoption, or other permanent connections.

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Family reunification is the preferred permanency outcome of child welfare intervention, and ex-cept in rare circumstances, the state must make reasonable efforts to reunify the family. Reunificationservices are generally offered to parents for 12 months, at which point parents are expected to dem-onstrate significant progress ameliorating the risks that brought their children into care. If the riskspersist, typically proceedings are initiated to terminate parental rights. Over half of children removedfrom home will eventually reunify with a parent (Children’s Bureau 2011).

Recent estimates indicate that by adulthood 12.5 percent of U.S. children will experience maltreat-ment confirmed by Child Protective Services (Wildeman et al. 2014) and up to 5.9 percent of chil-dren will be placed in foster care (Wildeman and Emanuel 2014).1 The risk of maltreatment andchild welfare involvement, however, are not distributed evenly. Poverty is an enduring characteristicof families who come to the attention of the child welfare agency and is associated with greater vul-nerability at every step in the child welfare process. Poor families are significantly more likely to bereferred to child welfare (Slack, Lee, and Berger 2007), have their children placed out of home(Paxson and Waldfogel 2002; Rivaux et al. 2008; Shook 1999), and once in placement, their childrenare slower to reunify (Kortenkamp, Geen, and Stagner 2004; Wells and Guo 2003) and more likelyto reenter the system (Courtney 1995). Although poverty alone is not sufficient grounds for“screening in” to child welfare services (Pelton 1989), it has obvious links to the most common typeof maltreatment, child neglect. Given that neglect is defined as “the failure . . . to provide neededfood, clothing, shelter, medical care, or supervision to the degree that the child’s health, safety, andwell-being are threatened with harm” (Child Welfare Information Gateway 2011), it is not surprisingthat child neglect is highly correlated with poverty (Connell-Carrick 2003). By way of context for thecurrent study, a 2008 survey found that over half of caregivers in Washington State with children inout-of-home care reported household incomes of less than $10,000 per year (Marcenko et al. 2012).

E C O N O M I C D I S C O N N E C T I O NEfforts to understand economic disconnection have focused on two overlapping populations: welfareleavers and low-income single mothers (Blank 2007; Blank and Kovak 2007; Danziger 2010;Ovwigho, Kolupanowich, and Born 2009; Rangarajan and Wood 2000; Turner, Danziger, andSeefeldt 2006). Estimates of disconnection range from about 10 to 30 percent, depending on theperiod of observation, measure, and population. For example, lower estimates come from studies ofwelfare leavers shortly after leaving welfare or from estimates of the long-term chronically discon-nected. There is some variation in how economic disconnection is measured due to data differences,but generally researchers consider employment or a working spouse as connection to the labor mar-ket, and cash benefits from TANF as connection to government cash assistance. UnemploymentInsurance and Supplemental Security Income (SSI) are also considered when data are available, asare household income and duration of unemployment. Food assistance from the SupplementalNutrition Assistance Program (SNAP) and in-kind transfers are usually excluded as forms of cash as-sistance (Loprest 2003; Ovwigho et al. 2009; Turner et al. 2006; Wood and Rangarajan 2003;Zedlewski et al. 2003). Although SNAP is an important resource, it does not provide a steady sourceof monetary income.

The study of economic disconnection has evolved over the past decade, which has yielded import-ant insights and pointed to the need for increasingly nuanced understandings of this complex phe-nomenon. Early studies relied on cross-sectional survey data (Blank 2007; Farrell 2009; Loprest2003; Wood and Rangarajan 2003), which provided point-in-time prevalence but not incidence over

1 Research documents that primary caregivers whose children had been placed in out-of-home care were more disadvantagedand harder to serve than those whose children were served in home. They were more likely to be single and never married, tohave only a high school education or less, to have yearly incomes less than $10,000, to live someplace other than their ownhome or apartment, to have substance abuse issues and co-occurring substance abuse and mental health disorders, and to haveexperienced domestic violence. They were less likely to be employed (Marcenko, Lyons, and Courtney 2011).

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time or duration. Subsequently, researchers used longitudinal data and categorized families using de-cision rules, identifying families as sometimes or chronically disconnected (Ovwigho et al. 2009;Turner et al. 2006). These studies demonstrate the importance of when and how economic discon-nection is measured. These ad hoc categorizations are useful, but risk failing to identify unexpectedor rare trajectories (Nagin and Tremblay 2005). Research on mothers of young children, for example,reveals that employment trajectories are much more complex than choosing to remain employed orto exit the labor market (Hynes and Clarkberg 2005).

Research highlights the role that employment difficulties and welfare sanctions play in initiatingspells of economic disconnection. Studies of welfare leavers have found that disconnected leavers(those who exit welfare to economic disconnection) were more likely to leave due to a sanction orbecause they thought TANF was “a hassle,” and disconnected leavers experienced more hardship andmore barriers to employment, such as health, transportation, or caregiving limitations, than other for-mer welfare recipients (Acs and Loprest 2004; Turner et al. 2006; Wood and Rangarajan 2003;Zedlewski et al. 2003). Job loss has been found to be more common than welfare loss in triggering aspell of economic disconnection (Blank and Kovak 2007; Turner et al. 2006) and the expiration ofunemployment benefits also plays a role (Moore, Wood, and Rangarajan 2012). In the next sectionwe describe how child welfare involvement can complicate this picture.

C H I L D W E L F A R E A N D E C O N O M I C D I S C O N N E C T I O NSeveral potential relationships link economic disconnection and child welfare involvement. We use amultilevel framework to consider the mandates of federal policy, local practices on the ground, andprocesses within families. Our first hypothesis—that families will become economically disconnectedafter contact with the child welfare system—is derived from considering the misalignment of the in-stitutional logics of welfare and child welfare. Given that scholars have noted the competing goals ofwelfare’s “work first” and child welfare’s “child first” orientation (Courtney 1998; Roberts 2002),child welfare involvement may increase economic disconnection either through a direct loss of child-dependent benefits or because of the difficulty of maintaining connection to benefits or employmentwhile complying with reunification services. Child welfare involvement may also increase economicdisconnection because participation in both the welfare and child welfare systems often imposes com-peting mandates on families, impeding their ability to fully comply with the requirements of eithersystem. Parents may be required to attend child welfare meetings, appear in court, and attend servicesaddressing such issues as parenting skills and substance abuse, while balancing the demands of thewelfare system to seek and maintain employment. Consequently, parents may have to choose be-tween missing a child welfare court date and being absent from work or meeting recertification re-quirements for benefits (Geen et al. 2001; Reich 2005). States have the option to allow parents tocontinue receiving TANF for up to 180 days if their child welfare worker attests that children are ex-pected to return home within that window, but in the years following welfare reform few states haveinstituted this policy (Ehrle, Andrews Scarcella, and Geen 2004). As a result of clash between thelogic and priorities of the two systems, we expect that some previously connected families will be-come disconnected after their child is placed out of home (H1).

These tensions, however, are not lost on program administrators and frontline staff. Our secondhypothesis considers how these federal rules are translated into local policies and practices. At thestate and local levels, there are some efforts to align these agencies through cross-system collabor-ation, which could include coordination of case plans, information sharing, and/or collocation of of-fices (Ehrle et al. 2004). If cross-system collaboration is successful, involuntary child welfareinvolvement may lessen economic disconnection by helping caregivers connect to benefits and po-tentially to employment. Thus we expect that some previously disconnected families may becomeconnected to benefits or employment after contact with the child welfare system (H2).

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Our third hypothesis focuses on the dynamics within families and is derived from the FamilyEconomic Stress Model, which posits that economic hardship adversely impacts parental functioning(Conger and Donnellan 2007). Thus, economic disconnection could lead to child welfare involve-ment through impaired parenting or a failure to meet basic needs. Economic disconnection createseconomic hardship, defined as the inability to consistently meet the family’s needs for food, clothing,and shelter, which creates stress for parents and children. Furthermore, documented maltreatmentrisk factors including parental substance abuse, depression, and domestic violence (Connell-Carrick2003; Edleson 1999) are often exacerbated by stress. Research has found that families with an invol-untary exit from TANF were at heightened risk of a substantiated maltreatment report in the follow-ing two years (Beimers and Coulton 2011). In this case, economic disconnection will precedeplacement (H3).

Although causal chains of possible events motivate these three hypotheses we also believe selec-tion could drive any observed relationships. That is, economic disconnection and child welfare in-volvement may both be caused by another factor. Maltreatment risk factors, such as substance abuse,cognitive impairment, or chronic disabling mental health conditions, overlap with barriers to work(Danziger and Seefeldt 2002; Pandey et al. 2003) and could impede parents’ ability to comply withTANF requirements. The timeframes by which these other factors destabilize employment or welfarecompliance and the extent and timing of related help seeking could account for any of the threehypotheses above. Furthermore, families with substance abuse or severe chronic mental health condi-tions might appear as chronically disconnected before and after child welfare intervention.

E C O N O M I C D I S C O N N E C T I O N A N D T H E L I F E C O U R S EOur next two hypotheses concern the distribution of patterns and the relationship between economicconnection and reunification. We anticipate that the risk of economic disconnection is not distributedevenly across families. Rising economic insecurity, with lower paid and less stable jobs, has length-ened the transition to adulthood and made it more tenuous for many young adults (Fussel andFurstenberg 2005). Young adults with less human and social capital are more likely to become par-ents early, and those who do so prior to acquiring work skills are likely to experience ongoing in-stability (Berzin and De Marco 2010). Younger parents, and parents with young children, have lesspractice at parenting and balancing the demands of meeting children’s needs while sustaining a familyeconomically and may also be less experienced at navigating public systems. Parents with young chil-dren, prior to school-age, are also more dependent on the availability of reliable and affordable childcare in order to work. Thus, we expect that younger parents will experience more economic instabil-ity than older parents (H4).

E C O N O M I C D I S C O N N E C T I O N A N D F A M I L Y R E U N I F I C A T I O NConsidering the role that economic resources play in family stability, we hypothesize that familiesexperiencing economic disconnection are less likely to reunify (H5). For family reunification to occurparents must demonstrate to the court that the original deficiencies necessitating placement have beenameliorated. Loss of public cash benefits once children are removed from the home may further im-pede parents’ ability to address any material conditions that may have contributed to placement(Eamon and Kopels 2004). Furthermore, child welfare workers have limited resources to address par-ents’ material needs. Research shows that relative to other child welfare involved families, economic-ally disconnected parents report higher levels of unmet needs and lower levels of investment inworking with child welfare services, making them a harder group of parents for the child welfare sys-tem to serve and jeopardizing their ability to safely reunify with their children (Marcenko et al.2012).

In sum, we have three competing predictions about the relationship between child welfare involve-ment and economic disconnection. Involvement, particularly out-of-home placement, could cause

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economic disconnection (H1) or ease disconnection (H2). Alternately, disconnection could causeplacement (H3). Additionally, we expect that younger caregivers are more vulnerable to periods ofeconomic disconnection than are older caregivers (H4) and that disconnection impedes reunification(H5).

M E T H O DIn order to investigate these hypotheses we use unique data on a hard to study population, not wellcaptured in surveys. We use 11 years (July 1998–June 2009) of Washington State administrative datacollected by three state agencies—child welfare, economic services, and employment security—toconstruct income histories of families prior to and following out-of-home placement. This provides alarge sample of a low incidence phenomenon allowing us to identify even rare trajectories, and threeyears of continuous longitudinal data for each individual, which would be difficult to collect via surveyfor such an extended period (Goerge and Lee 2002), particularly with the documented underreport-ing of benefit receipt (Hotz and Scholz 2002). We identify trajectories using group-based trajectorymodeling then compare demographic, case, and outcome differences across groups. The research isapproved by the Washington State Institutional Review Board.

Washington is a compelling site to study this issue because it is one of the few states that has aconcurrent benefit policy (Ehrle et al. 2004), allowing parents to continue receiving TANF for 90days (180 days as of August 2008) after children are removed from their care if their child welfarecaseworker attests that reunification is imminent (WAC 388-454-0015). Hence, Washington hasmore variation in the timing of benefit loss and may provide a conservative account of economic dis-connection among child welfare-involved parents. Washington is also more lenient in TANF eligibil-ity than the national average (De Jong et al. 2006). Nonetheless, Washington has experienced similareconomic cycles and the same federally mandated changes to child welfare and TANF policy as otherstates. It also resembles the national average on many child welfare barometers, including reunifica-tion. It diverges in that it has a larger proportion of non-Hispanic white and Native American chil-dren and a smaller proportion of black children than average (Children’s Bureau 2011).

DataData come from three sources. First, we begin with administrative data on all children entering out-of-home placement for the first time in Washington State from 2000 through 2007.2 Data are pro-vided by the Department of Social and Health Services (DSHS) to Partners for Our Children at theUniversity of Washington and have been used in previous analyses (Courtney and Hook 2012).From here, we identify the primary caregiver of each child as identified by the social worker. We re-strict our analysis to birth and adoptive parents who comprise 95 percent of primary caregivers. Birthand adoptive parents are indistinguishable in the data. We omit the remaining 5 percent of primarycaregivers, who are typically grandparents or other relatives, because they are much less likely to belocated in the linked data sources. We anchor caregivers to a placement date by selecting their firstchild to be placed out of home. To minimize non-matches we remove caregivers of children placedfor reasons of parental death or removed from out of state, and caregivers under age 18 or over age64 at the time of placement. Finally, we restrict the sample to placements lasting over seven days.This is consistent with Federal accountability measures (Children’s Bureau 2011) and studies of fam-ily reunification (Courtney and Hook 2012). Child behavior is the only reason for removal in 79 per-cent of placements lasting less than eight days. This yields 15,159 primary caregivers.

2 We do not have child welfare data on families prior to placement or about caregivers’ compliance with case plans. We do haveaccess to data on a sample of families who participated in a statewide survey during the same time period. In that sample, themedian time from referral to placement was seven days. Based on the length of time between referral and placement, we esti-mate that approximately 25 percent of families with children placed out of home receive in-home services prior to out-of-home placement, some for two months or longer (author’s calculations).

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We retain primary caregivers (6.7 percent) who have “jail” listed as a reason for removal. Perhapssurprisingly, parents with jail as a reason for removal appear in all of the trajectories we identify andare more likely to reunify with their children than are other parents. We do not have access to dataon sentencing, but suspect that for many parents jail is a short stay in county jail.

After identifying caregivers, data were linked to other administrative records by using the agency’sIntegrated Client Database (ICDB). The ICDB is a longitudinal client database that draws informa-tion from over 30 data systems, including the agency databases with detailed information on childwelfare, public economic support, and employment. DSHS uses a probabilistic matching process tolink its clients to those served by other state agencies based on given name, family name, social secur-ity number, date of birth, and administrative IDs. Each identifier type is assigned a weight for a posi-tive match with minimum weights used to define probable links based on agency experience withmatching client data (Kohlenberg 2009). Probabilistic matching is preferred over deterministicmatching because it reduces the incidence of false negatives (true matches not identified) (Goergeand Lee 2002).

Administrative data presents a number of challenges, which we address. First, California (CA) per-son IDs that are not matched to employment or economic services data may be genuinely chronicallydisconnected parents or false negatives; in the latter scenario economic disconnection would be over-estimated. Caregivers are considered matched if they have any record of employment or benefit re-ceipt (including SNAP) anywhere in the 11 years of data. We match 97.6 percent of primarycaregivers. If we also consider a matched opposite sex adult who is related to the focal child as birth,adoptive, or stepparent as a match, this reduces our non-match from 2.4 to 1.6 percent (n ¼ 247).We include these cases, which all appear to be chronically disconnected, in our estimation proced-ures, but we break this subgroup out in descriptive statistics to examine whether non-matches sharesimilar characteristics with the chronically disconnected or whether they appear to be a distinctgroup.

A second challenge is that subjects who become disconnected cannot be differentiated fromthose who have left the data (e.g., through incarceration, death, or out-of-state move), since, inboth cases, we would observe a terminal run of zeros (e.g., no record of employment or benefits).Out-of-state moves should be rare while parents have an open case with child welfare and thecourts. We use supplemental data on SNAP receipt, which is much more prevalent than TANF re-ceipt, to help distinguish between attrition and disconnected parents (Grogger 2012). Using SNAPreceipt we estimate upper and lower bounds on the true connection rates in each trajectory(Manski 1995). We conclude that we can reasonably rule out attrition as a cause for concern in theyear following placement because upper and lower bounds are extremely similar. For the final twoquarters, however, we may be overestimating disconnection for several trajectories (see onlineAppendix A for details).

Finally, Unemployment Insurance (UI) administrative records do not contain information on allemployment, thus we underestimate employment. UI administrative records contain quarterly earn-ings for each employee as reported by employers for tax purposes under the Federal UnemploymentTax Act (FUTA). Although UI generally underestimates employment by up to 10 to 15 percent(Hotz and Scholz 2002), a study of welfare leavers in Washington state found that employment rateswere only six percentage points higher with survey data (Isaacs and Lyon 2000), which is a popula-tion similar to ours.

MeasuresWe construct quarterly employment and benefit receipt indicators for all caregivers. Monthly bene-fit data is aggregated to the quarter to match the employment data. We anchor our analysis to 18months prior to the quarter of out-of-home placement and 18 months following. Thus, we beginfollowing our first entries (January 2000) in July 1998 and follow our last entries (December 2007)

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through June 2009. Three years of data (covering 13 quarters) is enough to establish chronic orepisodic disconnection and follow the families through the standard window of reunification(Courtney and Hook 2012) without creating excessive attrition. Caregivers are coded as connectedif they have any reported earnings or UI receipt or if they received cash assistance (TANF, SSI, orGA) during a calendar quarter. Thus, this measure of economic disconnection is conservative, onlyrequiring that a caregiver has a connection to income at some point during each three-monthperiod.

Once we have created trajectory groups we examine characteristics of the primary caregiver (ageand sex), focal child (age at placement), and case. We do not report race-ethnicity because there areonly minor racial-ethnic differences across groups in this relatively homogenous state (caregivers are:71.3 percent white non-Hispanic; 9.3 percent any Native American; 7.7 percent any AfricanAmerican; 7.5 percent Hispanic; 1.8 percent Asian/Pacific Islander, and 2.4 percent other/missing).Case characteristics include reasons for removal and case outcome. Social workers could select mul-tiple reasons for removal. The reasons, in order of prevalence, are: neglect (59.3 percent); parentalsubstance abuse (33.3 percent); physical abuse (17.2 percent); parent unable/disability (10.5 per-cent); child behavior only (7.6 percent); parent incarcerated (6.7 percent); sexual abuse (5.4 per-cent); and abandonment (3.8 percent). Outcomes are family reunification (59.3 percent); adoption(15.5 percent); guardianship (5.5 percent); age of majority/emancipated (3.7 percent); transferredto another authority (1.9 percent); and still in care as of June 2009/censored (14.2 percent). Tosome extent, the case outcome predicts the post-placement trajectory. That is, if parents reunify theycan reinstate their benefits and become connected; we are unable to disentangle the timing of reunifi-cation and benefit reinstatement.

Research StrategyWe make a methodological advance in the study of economic disconnection by employing group-based trajectory modeling (GBTM), a method widely used in a number of disciplines and for similaroutcomes (George 2009; Hynes and Clarkberg 2005; Nagin 1999). GBTM is particularly useful foridentifying rare or unexpected trajectories, and allows for a refined classification of temporal orderoften missed in classifications employing decision rules (Nagin and Tremblay 2005). GBTM identi-fies clusters of individuals who follow similar trajectories over time (here economic connection over13 quarters). The objective is to summarize the data in the most parsimonious and useful way pos-sible. Essentially, GBTM uses maximum likelihood estimation to jointly estimate the shape of trajec-tories and the proportion of the sample in each trajectory. Each respondent is assigned a probabilityof belonging to each group.

GBTM fit statistics help guide researchers to the optimal number of groups by showing if the add-ition of one more trajectory improves the fit of the model. Researchers use supplemental data (heredemographics and case outcomes) to explore the distinctness and usefulness of each group. As shownin Table 1, the Bayesian information criterion (BIC) preferred increasingly complex models. Wechose the eight-group model because additional groups did not substantially add to our understand-ing of trajectories and we already identify rare trajectories, the smallest of which includes 6.1 percentof the sample.3 We explore characteristics of the groups by assigning each individual to the groupthey are most likely to belong to given generated probabilities. The model’s relative entropy (RE)statistic supports this; our RE metric of .87 approaches 1, indicating a clear delineation of classes(Celeux and Soromenho 1996). The model performs well on additional diagnostics of assignment ac-curacy (see online Appendix B). We present models covering 13 quarters with the placement quartercentered, but models are robust to off-centering the placement quarter.

3 In a nine-group model, five groups were under 10 percent with the smallest representing 5.4 percent of the sample. In a ten-group model, seven groups were under 10 percent with the smallest representing 4.6 percent of the sample.

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LimitationsThere are factors that cause us to both over- and underestimate economic disconnection. On onehand, we underestimate sporadic disconnection by smoothing benefit receipt and employment over athree-month period. The administrative data cannot look at employment any more granularly, butmonthly benefit data show that of those receiving benefits in the placement quarter, only 60 percentreceived benefits in all three months. Furthermore, although a caregiver may be classified as con-nected, they could earn a very minimal income, potentially so little that “connection” is misleading.

On the other hand, the administrative data captures less than 100 percent of formal employmentand excludes “off the books” employment. Whether off the books work should be considered eco-nomic connection is open to interpretation. Although rates of informal work are high (about half ofdisconnected welfare leavers in a Louisiana sample reported informal work such as babysitting, pawn-ing items, and illegal activities), it is unlikely to be a reliable and substantial source of connection formost (Powers, Livermore, and Creel Davis 2013). In their qualitative study of 95 poor, disconnectedfamilies, Sheila Zedlewski and colleagues (2003) found that about one-third of the respondents ortheir partners did side jobs. Most side jobs were occasional and contributed little to the family’s in-come (only six respondents reported income of $100 or more per month). The most common typesof side jobs were babysitting, cleaning houses, and doing hair or nails. Receiving help from family,friends, or charities were more common strategies than working side jobs, primarily because the samebarriers that prevented formal work (e.g., lack of a babysitter, poor health, attending school) also pre-vented finding and doing side work (Zedlewski et al. 2003).

Furthermore, estimates based on primary caregivers do not include the contributions of support-ing partners, either from a current relationship or child support and thus provide an upper-bounds es-timate of disconnection. The data do not let us distinguish whether other adults such as spouses areliving with the primary caregiver and providing financial support to the household. We provide sup-plemental analysis in online Appendix C of potentially supporting partners to address this limitation.Our point-in-time estimate of economic disconnection during the placement quarter is 29.1 percent.Including all potentially supporting partners decreases this estimate to 21.6 percent. This is consistentwith other research that includes household composition and partner earnings. In an analysis ofAfrican American and Hispanic women receiving TANF in 1999 and surveyed in 2005, AndrewCherlin and colleagues (2009) found that 28 percent were disconnected at the time of interviewusing the definition we employ. Including income from employed co-resident partners reduced theestimate to 22 percent. Partner support is an important area of research that requires additional, andmore refined, data.

Table 1. Group-Based Trajectory Models, Fits Statistics, and Entropy

Number of Groups BIC Null Model 2(DBIC) Entropy

1 �128,826.41 1.0002 �100,580.04 1 56,492.74 .8893 �92,377.81 2 16,404.46 .9044 �86,699.37 3 11,356.88 .9015 �85,287.95 4 2,822.84 .9066 �84,160.64 5 2,254.62 .8967 �83,103.98 6 2,113.32 .8838 �82,200.99 7 1,805.98 .8699 �81,380.81 8 1,640.36 .87710 �81,065.87 9 629.88 .876

Notes: 2(DBIC) is the BIC log Bayes factor approximation. Values over ten provide “very strong” evidence against the null hypothesis (Jones,Nagin, and Roeder 2001).

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Our hypotheses imply causal relationships between economic disconnection and child welfare in-volvement. We do not directly observe these relationships, but our hypotheses relate to the directionand timing of change in relation to child welfare involvement, which illuminates potential causal con-nections from one status to another.

R E S U L T SBefore turning to trajectories, we report point-in-time estimates of economic disconnection. Eighteenmonths prior to placement 36.9 percent of primary caregivers are economically disconnected; thisreaches a low of 29.1 percent the quarter prior to placement and the placement quarter, and increasesto 40.7 percent the quarter after placement and remains above 40 percent for the rest of the observa-tion period. These estimates are higher than Sandra Danziger’s (2010) 25 percent national estimateof economic disconnection among low-educated single mothers, suggesting that rates of economicdisconnection are higher among child-welfare involved families. Point-in-time estimates are inform-ative but conceal substantial movement into and out of economic connection. Overall, three-quarters(75.5 percent) of primary caregivers are disconnected in at least 1 of 13 quarters.

Table 2 shows a two-by-two table of economic connection comparing “baseline” quarters 1 and 3to pre- and post-placement quarters 6 and 8. From Q1 to Q3, 17.0 percent of caregivers moved fromone status to another, with slightly more gaining (9.4 percent) than losing (7.6 percent) connection.In contrast from Q6 to Q8, 26.5 percent of caregivers moved from one status to another, with morelosing (19.1 percent) than gaining (7.4 percent) connection. This suggests that placement is associ-ated with increased negative economic instability. Pre- and post-placement comparisons are inform-ative but conceal substantial heterogeneity in individual trajectories.

Primary Caregivers’ Economic TrajectoriesWe identified eight trajectories shown in Figure 1. The x-axis provides the quarter of observation,with seven indicating the quarter of placement into out-of-home care. The y-axis indicates the pro-portion of those in each group who are economically connected—either employed or receiving cashbenefits—in each quarter. We give each trajectory a descriptive name. The percentage labeled in thefigure represents the share of individuals in a given group.

The largest group, Consistently Connected (35.8 percent), is nearly 100 percent connected foreach quarter. At the other extreme is the Chronically Disconnected group (13.1 percent, including1.6 percent unmatched), which shows nearly 0 percent connection for each quarter, reaching a highof 5.7 percent of the group connected in the last quarter. Our estimate of chronic disconnection issimilar to studies of welfare leavers, with quarterly rates from 9.1 to 10.4 percent (Ovwigho et al.2009; Turner et al. 2006).

The remaining groups show instability in economic connection and can be grouped into six pat-terns based on their level and timing of connection.

Two groups correspond to Hypothesis 1, that some previously connected families will become dis-connected after contact with the child welfare system. The Disconnection Begins at Placement group(10.3 percent) shows a steep decline over the six quarters after children are placed in out-of-homecare. Similarly the Immediate Disconnection group (6.3 percent) shows disconnection, but muchmore quickly, as in "falling off a cliff." Nearly all cases in this group are connected prior to placementand by two quarters after placement, none are connected. The difference between these two groupscould result from the use of concurrent benefits; those in the immediate disconnection show a muchsteeper decline in benefits upon placement indicating that they were not authorized to continuereceiving TANF under the concurrent benefits policy.

Hypothesis 2 predicted that some previously disconnected families would become connected tobenefits or employment after contact with the child welfare system. The group, which we nameConnection Precedes Placement (13.4 percent), shows this pattern beginning with low levels of

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connection and gaining connection over time. The Disconnection Precedes Placement group (7.3percent) corresponds with Hypothesis 3, that economic disconnection may prompt child welfare in-volvement. This group begins to lose economic connection well before placement.

Finally, two groups reveal unexpected—or hybrid—trajectories. The Gain/Loss (6.1 percent)group begins with low levels of connection and gains connection up to the time of out-of-homeplacement, then shows a sharp loss of connection at the time of placement and ends our observationwindow largely disconnected from employment or benefits. This is a combination of Hypotheses 2and 1, whereby the child welfare system may help a parent connect to benefits, possibly while receiv-ing in-home services, but benefits are lost upon child placement. The final group, which we nameLoss/Gain (7.7 percent), begins connected, loses connection prior to and after placement, but re-gains connection by the end of the observation period. This group appears to be a combination of allthree hypotheses, showing declining employment prior to placement (H3), declining benefits uponplacement (H1), and a rise in both two quarters after placement (H2). Both trajectories are consist-ent with Hypothesis 1 as both lose connection to benefits upon placement.

Benefits versus EmploymentFor all groups connection to benefits is more common than employment. Figure 1 shows the propor-tion of each group who are connected to benefits (short dash) and to employment (long dash). Overhalf (51.5 percent) of primary caregivers are benefit connected at the time of placement and overone-quarter (27.5 percent) are employment connected. There is more instability in benefits than inemployment, and for most groups, benefits show clear movement around the time of placement.Generally, we see an upward bump in benefits around placement, and for groups that lose connectionwe see a steep decline thereafter. For some groups we also observe a drop in employment near thetime of placement, but this is relatively modest.

Table 2. Percent of Primary Caregivers by Economic Connection, Comparing Quarters 1and 3 (Panel A) and Quarters 6 and 8 (Panel B)

Panel A

Quarter 3

Quarter 1 Disconnected Connected Total(%) (%) (%)

Disconnected 27.5 9.4 36.9Connected 7.6 55.4 63.1Total 35.2 64.8 100.0

Panel B

Quarter 8

Quarter 6 Disconnected Connected Total(%) (%) (%)

Disconnected 21.7 7.4 29.1Connected 19.1 51.9 71.0Total 40.7 59.3 100.0

Note: Quarter 7 is the quarter of out-of-home placement.

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Differences across GroupsTable 3 presents a comparison of group characteristics. In comparison to those caregivers in stablepatterns—the Consistently Connected or Chronically Disconnected—caregivers exhibiting economicinstability tend to be younger, have younger children, and have children removed for reasons of neg-lect/substance abuse. Those caregivers in trajectories that end in economic connection—Consistently Connected, Connection Precedes Placement, and Loss/Gain—are most likely to reunifywith their children.

The Chronically Disconnected group is older, on average, than all other groups. Older caregiversmay be more likely to have exhausted TANF time limits, but this would require additional data toconfirm. They are more likely than other groups to have older kids and more likely to have children

Figure 1. Economic Connection, by Trajectory Group

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Tab

le3.

Cha

ract

eris

tics

ofC

areg

iver

s,C

ases

,and

Out

com

esby

Tra

ject

ory

Gro

up

Stab

leH

2H

ybri

dH

ypot

hesis

1H

3

Con

siste

ntC

onne

ct(3

5.8%

)

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onic

Disc

on.

(11.

5%)

Con

nect

Prec

edes

Plac

e(1

3.4%

)

Gai

n/L

oss

(6.1

%)

Los

s/G

ain

(7.7

%)

Disc

on.

Beg

insa

tPl

ace

(10.

3%)

Imm

edia

teD

iscon

.(6

.3%

)

Disc

on.

Prec

edes

Plac

e(7

.3%

)

Not

Mat

ched

(1.6

%)

Car

egiv

erch

arac

teri

stic

sFa

ther

(%)

9.2

9.3

15.0

*6.

3*6.

96.

0*8.

38.

98.

925

.5*

Age

(yea

rs)

31.5

32.3

34.6

*29

.8*

29.0

*29

.7*

29.7

*30

.7*

31.1

*38

.4*

You

nger

than

25(%

)28

.023

.619

.5*

35.0

*39

.1*

33.1

*35

.1*

30.3

*27

.08.

1*C

hild

age

atpl

acem

ent

Mea

n5.

96.

67.

4*4.

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7*5.

3*5.

2*5.

4*5.

8*11

.3*

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nt(%

)25

.620

.325

.2*

38.6

*46

.3*

19.8

24.5

20.2

27.5

*10

.1*

1-4

24.5

24.5

15.4

*22

.923

.234

.1*

30.6

31.0

*22

.010

.5*

5-8

16.7

17.4

13.7

*14

.611

.3*

19.9

18.7

*21

.318

.87.

7*9-

1214

.215

.915

.911

.3*

10.5

*13

.813

.4*

14.7

13.8

10.5

13an

dol

der

18.9

21.9

29.9

*12

.7*

8.8*

12.4

*12

.812

.8*

17.9

61.1

*R

easo

nsfo

rre

mov

al(%

)N

egle

ct59

.357

.249

.4*

59.1

66.4

*70

.6*

63.4

*69

.5*

60.5

*27

.1*

Subs

tanc

eab

use

33.3

27.4

29.3

38.2

*41

.3*

40.1

*39

.5*

39.3

*37

.3*

7.3*

Phy

sica

labu

se17

.220

.018

.216

.2*

13.9

*13

.0*

16.7

12.7

*14

.6*

23.9

Sexu

alab

use

5.4

6.6

7.5

4.0*

3.9*

3.6*

3.8*

4.8

4.1*

10.1

Par

ent

unab

le/d

isab

le10

.512

.610

.611

.210

.17.

6*7.

7*8.

7*8.

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il6.

75.

06.

47.

1*5.

59.

3*8.

2*9.

8*8.

8*5.

3A

band

onm

ent

3.8

2.7

4.8*

3.0

4.0

3.8

4.1

5.1*

6.4*

5.7

Onl

ych

ildbe

havi

or7.

69.

213

.3*

5.1*

2.6*

2.5*

5.6*

3.4*

6.1*

30.8

*R

euni

fied

59.3

66.5

54.8

*66

.644

.8*

58.8

*52

.8*

43.5

*49

.6*

75.7

Ado

pted

15.5

10.9

14.5

*13

.228

.5*

14.3

21.2

*25

.4*

19.9

*5.

7G

uard

ians

hip

5.5

4.8

5.9

2.8*

5.9

6.5

6.7

7.4*

8.2*

3.6

Age

ofm

ajor

ity3.

73.

96.

4*1.

8*2.

12.

0*2.

94.

24.

110

.1*

Tra

nsfe

rred

1.9

1.4

2.6

1.8

2.8

1.4

2.1

1.9

2.6

3.2

Still

inca

re(c

enso

red)

14.2

12.4

15.8

*13

.815

.917

.1*

14.4

17.7

*15

.61.

6*

N15

,159

5,42

71,

742

2,03

091

91,

171

1,56

395

01,

110

247

*One

-way

AN

OV

Ain

dica

tes

sign

ifica

ntdi

ffere

nce

com

pare

dto

the

Con

sist

ently

Con

nect

ed(p<

.05)

.

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removed for child behavior only. Perhaps surprisingly, the Chronically Disconnected group is leastlikely to have neglect as a reason for removal and is below average on family reunification, but notlowest.

The two groups—Gain/Loss and Connection Precedes Placement—that begin with low levels ofconnection and gain connection up to the time of out-of-home placement are the groups most likelyto include primary caregivers of infants. Nearly half (46.3 percent) of the Gain/Loss group has an in-fant placed into out-of-home care as does 38.6 percent of the Connection Precedes Placement group.Primary caregivers in these groups are also younger on average and more likely to be mothers. Bothgroups are also higher than average on substance abuse as a removal reason. Although these groupsshare some similarities, it is not surprising that they differ in case outcomes. Only 44.8 percent of theGain/Loss group reunifies with their children. This group is the most likely to have their child placedfor adoption. In contrast, those who maintain their connection—Connection Precedes Placement—have above average rates of reunification and among the lowest rates of adoption. Employment is asubstantial component of connection for the Connection Precedes Placement group, but is a smallcomponent for the Gain/Loss group, which primarily derives connection through benefits.

The other hybrid trajectory, Loss/Gain, ranks highest on neglect and near highest on substanceabuse. Jail as a reason for removal is also higher than average. They are least likely to have their childplaced out of home as an infant, with placement from ages 1 to 4 and 5 to 8 being higher than aver-age. Perhaps surprisingly, reunification is lower than the average, but higher than all other groupsending in disconnection, including the Chronically Disconnected.

The three groups—Disconnection Begins at Placement, Immediate Disconnection, andDisconnection Precedes Placement—that begin with high levels of connection and lose connectionover the observation period share many characteristics. They are higher than average on neglect, sub-stance abuse, jail and abandonment. All end the observation period disconnected, but the timing ofdisconnection differs. Not surprisingly, they have lower reunification rates than average. Perhaps sur-prisingly, the Disconnection Precedes Placement group (corresponding to Hypothesis 3) does notdiffer markedly from the other two groups.

Primary caregivers who are not matched in our data appear to be a distinct group. The majorityhave children age 13 and older and nearly one-third have child behavior listed as their only reason forremoval. The caregivers are also older and are more likely to be fathers. The rate of family reunifica-tion is higher than any of the eight identified groups. They are also the most likely to be missing in-formation on race-ethnicity. Although some non-matched caregivers may be chronicallydisconnected, based on descriptive data it is likely that they represent a group of caregivers with lessextensive involvement in child welfare and thus missing data.

D I S C U S S I O NBy examining the extent to which families who have a child removed from their care are also discon-nected from formal earnings or public assistance, this study provides new evidence on overlap be-tween these forms of exclusion. Consistent with research on the economic insecurity of low-incomefamilies, we find that the majority of caregivers experiencing an out-of-home child welfare placementhave at least one quarter of economic disconnection over a three-year period. About one in nine ischronically disconnected. Only about one-third are consistently connected to employment or cashbenefits over a three-year period.

Although this analysis cannot show causality, one interpretation of our findings is that child re-moval leads to economic destabilization for some—but not all—families. The most common patternof instability is a loss of economic connection beginning around the time of out-of-home placement.About one in three caregivers is in a trajectory that loses benefits or jobs in the months followingout-of-home placement. This is consistent with Hypothesis 1derivied from considering the conflictingmandates of “child-first” and “work-first” policies for poor mothers (Courtney 1998; Roberts 2002).

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The next largest group is caregivers with increasing connection prior and upon child welfare involve-ment, who appear to be economically aided by child welfare involvement. This is broadly consistentwith efforts at cross-system collaboration from state-level administrators and frontline workers. An al-ternate hypothesis is that benefit receipt increased surveillance, which led to child removal.Caregivers in this trajectory, however, continue an upward trajectory even after removal. Finally, weidentify a small group for which economic disconnection precedes and may prompt involvement,which is consistent with our Hypothesis 3 predictions based on Rand Conger and M. BrentDonnellan’s (2007) Family Economic Stress Model. We also find that loss of cash assistance is a big-ger source of instability among families experiencing child removal, in contrast to findings that jobloss is more common than welfare loss in triggering disconnection among welfare leavers or low in-come single mothers (Blank and Kovak 2007; Turner et al. 2006).

At greatest risk for economic instability are caregivers who are younger, have younger children,and have children removed for reasons of neglect and substance abuse. Our findings are consistentwith prior research that shows that infants are less likely to be reunified, more likely to adopted, andtheir caregivers more often have problems of substance abuse (Wulczyn, Ernst, and Fisher 2011).Interestingly, instability in this group is driven almost entirely by the loss of benefits; only a smallproportion of caregivers is employed across the study period. It is possible that many of these care-givers only became eligible for TANF upon the birth of the child who was placed and lost those bene-fits at placement. Given that infants have the longest length of stay in foster care (Wulzcyn et al.2011), workers may be less likely to activate the 90- or 180-day TANF benefit because reunificationis not expected, or certainly not in the next several months.

The combination of caregiver developmental stage, substance abuse, and limited work historymakes this group of caregivers particularly vulnerable to instability. We hypothesized that life condi-tions associated with lack of experience with work or pubic systems pose challenges to employmentor meeting TANF requirements. Efforts to assist young parents might focus on increasing their em-ployability through education or job training and substance abuse treatment. Incorporating principlesof a “two generation” approach (Haskins, Garfinkel, and McLanahan 2014) whereby service and pol-icy design simultaneously addresses the needs of children and parents could have the synergistic ef-fect of increasing both economic connection and reunification for this group of families.

Economic exclusion occurs alongside—and may extend—separations between children and par-ents. Families experiencing any type of economic disconnection are less likely to reunify than familiescontinuously connected. The links we establish between trajectories and family outcomes, however,are correlational. Recent research in Washington State, however, suggests a causal relationship. About80 percent of families on TANF with children removed (in 2008 to 2011) received concurrent bene-fits, on average for 5 months, although there was wide variability. Using propensity score matching re-searchers found that families that received concurrent benefits reunified more quickly than those thatdid not (Marshall et al. 2013). In addition to maintaining benefits upon placement, we find some evi-dence that caregivers who become connected prior to and upon placement fare better in family reuni-fication than other parents. We expect that for families who become connected around placement,the child welfare system is the means to accessing needed supports, which may increase parental buy-in and engagement.

One way to gauge the possible impact of increasing economic connection via extending benefitsor more effectively promoting employment is to assume that the entire relationship between eco-nomic disconnection and reunification is causal. Comparing this assumption to the alternative—thatnone of the relationship is casual—allows us to estimate upper and lower bounds on the likelihoodof reunification. If all caregivers who experienced a spell of economic disconnection had either main-tained or established connection at the time of placement we would expect that reunification rateswould increase to the level of the consistently connected and connection precedes placement groups(�66.5 percent). Raising the average reunification rate from 59.3 percent to 66.5 percent results inan increase of 7.2 percentage points, amounting to over 1,000 additional family reunifications over

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the study period (n ¼ 1,091). Conversely, if none of the relationship is causal the average reunifica-tion rate would remain at 59.3 percent and no additional families would reunify.4 If resources andpolitical will permitted promoting connection, we presume that the likely outcome would fall in be-tween these extremes.

We find that the Chronically Disconnected group fares better in terms of family reunification thanthose experiencing more volatile trajectories. This may be unexpected, but a newly disconnected fam-ily may be less likely to positively engage with a system that they hold responsible for their loss ofeconomic supports and that is largely unresponsive to their economic needs (Marcenko et al. 2012).Alternately, chronically disconnected families may have established other ways to “make ends meet”unlike a newly disconnected family that must simultaneously navigate two unfamiliar states—discon-nection and child welfare involvement. Researchers have found that low-income mothers often relyon “off the books” jobs and social support to get by (Edin and Lein 1997; Pandey et al. 2003). Webelieve many families who show no income in official records probably have some income that is notin our data.

A transition in Washington’s child welfare information system prevents easy comparison betweenour data and later records, but if we were to extend this study through the Great Recession, we wouldexpect to find that even more families experienced periods of economic disconnection. Low-incomefamilies, including those in the child welfare system, have been disproportionately affected by the re-cent recession. Furthermore, states have responded to the fiscal crisis with deep cuts to human ser-vices and limits to TANF eligibility (Laird, Derr, and Lyskawa, 2013). The combination of highunemployment, limited TANF, and contracting services is especially problematic for child welfareinvolved families, likely eroding their ability to safely care for their children.

In sum, the child welfare system is a lesser noted institutional mechanism that impacts the eco-nomic inclusion of poor families. We find that out-of-home placement precedes economic disconnec-tion for up to one-third of families with children in out-of-home care, complicating efforts of parentsto reunify their families. We do find evidence, however, of a small group of parents who appear to beeconomically assisted both before and after child placement, illustrating the potential of interventionand cross-systems collaboration to promote economic inclusion. Future research should examine theimpact of cross-systems collaboration on economic connection and family reunification. Althoughproviding economic resources to families is typically beyond the scope of the child welfare system, ef-forts to minimize the negative impact of child placement on parents’ economic connection is likely toimprove both the economic inclusion of vulnerable families and family reunification.

R E F E R E N C E SAcs, Gregory and Pamela Loprest. 2004. Leaving Welfare: Employment and Well-Being of Families That Left Welfare in

the Post-Entitlement Era. Kalamazoo, MI: W. E. Upjohn Institute for Employment Research.Bane, Mary Jo and David T. Ellwood. 1986. “Slipping Into and Out of Poverty: The Dynamics of Spells.” Journal of

Human Resources 21:1–23.Beimers, David and Claudia J. Coulton. 2011. “Do Employment and Type of Exit Influence Child Maltreatment among

Families Leaving Temporary Assistance for Needy Families?” Children and Youth Services Review 33:1112–19.

4 Because different groups have different characteristics, this simple approach might under or overestimate the bounds on themagnitude of the relationship between economic disconnection and reunification. Multivariate-informed analyses suggest thisis not the case. We used logistic regression to predict reunification among the Consistently Connected and ConnectionPrecedes Placement groups. We included the characteristics listed in Table 3 (parent’s sex, parent and child age at placement,and eight removal reasons). We then created an out-of-sample prediction using the full sample. The predicted value was .6652,nearly identical to the prediction restricted to the Consistently Connected and Connection Precedes Placement groups(.6650). The predicted reunification rate ranged from a low of .6486 for the Gain/Loss group to a high of .6768 for theChronically Disconnected. While there may be unobserved factors that explain the variation in reunification rates found acrossthe eight economic trajectory groups, differences in parent and child demographics and removal reasons explain little of thevariation.

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