Child care subsidy programs and child care choices: Effects on the number and type of arrangements

Accepted Manuscript Child care subsidy programs and child care choices: Effects on the number and type of arrangements

Alejandra Ros Pilarz PII: DOI: Reference:

S0190-7409(18)30465-1 doi:10.1016/j.childyouth.2018.10.013 CYSR 4026

To appear in:

Children and Youth Services Review

Received date: Revised date: Accepted date:

8 June 2018 7 October 2018 8 October 2018

Please cite this article as: Alejandra Ros Pilarz , Child care subsidy programs and child care choices: Effects on the number and type of arrangements. Cysr (2018), doi:10.1016/ j.childyouth.2018.10.013

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ACCEPTED MANUSCRIPT Child Care Subsidy Programs and Child Care Choices: Effects on the Number and Type of Arrangements Alejandra Ros Pilarz [email protected] School of Social Work, University of Wisconsin-Madison 1350 University Avenue Madison, WI 53706

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Author Note

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The author would like to thank Julia Henly, Heather Hill, Rachel Gordon, and David Alexander for their helpful comments on

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earlier versions of this manuscript. This research was supported by the Child Care Research Scholars Grant Program (grant no.

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90YE0146) from the Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of

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Health and Human Services. The contents of this manuscript are solely the responsibility of the author. Declarations of interest: none.

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Abstract

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Despite strong evidence that stable, high-quality child care promotes young children’s development, low-income children are

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less likely to participate in formal and high-quality care than higher-income children and may be more likely to experience multiple, concurrent arrangements due to parents’ economic and employment constraints. Child care subsidy programs increase low-income

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children’s access to formal, center-based care, but little is known as to whether subsidies also influence the use of multiple

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arrangements. This study uses difference-in-difference techniques to estimate the effects of child care subsidy program spending on parents’ decisions about the number and type of care arrangements. Results show that state subsidy program spending is associated with a higher likelihood of using a single, center-based arrangement and a lower likelihood of using multiple arrangements. Findings

ACCEPTED MANUSCRIPT suggest that the unaffordability of child care likely contributes to low-income parents’ use of multiple arrangements, and that subsidy programs increase these families’ access to center-based care. Keywords: child care; child care decision-making; child care subsidies; child care type; multiple arrangements; multiplicity

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ACCEPTED MANUSCRIPT Child Care Subsidy Programs and Child Care Choices: Effects on the Number and Type of Arrangements Young children’s participation in non-parental child care is at historically high levels in the U.S. Approximately 61% of children under the age of 5 years regularly attend some form of non-parental care arrangement (Laughlin, 2013). Yet, children in

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lower-income families remain substantially less likely to be enrolled in any form of non-parental care (Bassok, Finch, Lee, Reardon,

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& Waldfogel, 2016; National Survey of Early Care and Education [NSECE] Project Team, 2016a) in comparison to higher-income

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families, as well as less likely to attend formal, center-based care (Magnuson & Waldfogel, 2016) and high-quality care (Ruzek,

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Burchinal, Farkas, & Duncan, 2014). Additionally, nearly 1 in 5 children under the age of 5 years regularly attends multiple,

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concurrent child care arrangements (Laughlin, 2013). Although this rate does not appear to differ by family income, qualitative

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research suggests low-income families often package together multiple care arrangements in order to accommodate their child care

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needs within employment and economic constraints, rather than due to parental preferences for particular types of care or for child

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development-related reasons (Chaudry, 2004; Henly & Lambert, 2005; Scott, London, & Hurst, 2005). Given the large body of

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evidence that experiencing stable, high-quality child care promotes healthy early childhood development (e.g., Bradley & Vandell, 2007; Loeb, Fuller, Kagan, & Carrol, 2004), these disparities in access to non-parental care have important implications for low-

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income children’s development.

To address disparities in access to non-parental child care for low-income families, the Child Care and Development Fund (CCDF) program was created to subsidize the cost of child care for low-income, working families. The CCDF child care subsidy program has dual goals of supporting parental employment and children’s development, and thus improving access to high quality and

ACCEPTED MANUSCRIPT stable child care arrangements is a key program objective (U.S. Department of Health and Human Services [DHHS], 2011). Prior studies suggest that child care subsidies are associated with higher rates of participation in formal, center-based care (e.g., Crosby, Gennetian, & Huston, 2005; Magnuson, Meyers, & Waldfogel, 2007; Ryan, Johnson, Rigby, & Brooks-Gunn, 2011), which tends to

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be higher cost than home-based care provided by relatives or nonrelatives (NSECE Project Team, 2015) and is more likely to be

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unaffordable to low-income families without a subsidy. However, little is known as to whether subsidy programs also influence

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parents’ child care decisions about the number of concurrent care arrangements to use.

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Researchers and policymakers have been concerned that the use of multiple, concurrent arrangements may represent instability in families’ lives that negatively impacts child and family wellbeing. Although several studies have found adverse associations

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between the use of multiple arrangements in early childhood and child behavioral outcomes (Bratsch-Hines, Mokrova, Vernon-

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Feagans, & The Family Life Project Key Investigators, 2017; De Schipper, Tavecchio, Van IJzendoorn, & Linting, 2003; De

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Schipper, Tavecchio, Van IJzendoorn, & Van Zeijl, 2004; De Schipper, Van IJzendoorn, & Tavecchio, 2004; Morrissey, 2009), recent

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research suggests that regular or consistent multiple arrangements that are stable over time are not associated with adverse behavioral outcomes (Claessens & Chen, 2013; Gordon, Colaner, Usdansky, & Melgar, 2013; Pilarz & Hill, 2014; Pilarz, 2018). Additionally,

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among preschoolers, combining center- and home-based care has been associated with positive academic outcomes (Gordon et al., 2013), but there is little evidence of similar benefits of multiple arrangements for infants and toddlers (Pilarz, 2018). One reason for these mixed findings may be that the effects of multiple arrangements may depend in part on parents’ reasons for using multiple arrangements. Whereas some parents use multiple arrangements with the intent of promoting their child’s development, others use

ACCEPTED MANUSCRIPT multiple arrangements due to employment or economic constraints (Gordon et al., 2013; Neilsen-Hewett, Sweller, Taylor, Harrison, & Bowes, 2014), which may lead to less-preferred and potentially more unstable arrangements. Moreover, multiple arrangements could negatively impact parental employment stability (Usdansky & Wolf, 2008), with negative implications for families’ economic well-

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being.

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Qualitative studies of low-income, working families suggest that the unaffordability of care in the formal child care market is

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one reason why low-income families rely on multiple care providers, particularly informal caregivers such as relatives or friends

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(Chaudry, 2004; Henly & Lambert, 2005; Lowe & Weisner, 2004; Scott et al., 2005). Thus, subsidizing the cost of care and reducing

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cost constraints for low-income families through the CCDF program may help parents access a single, preferred arrangement and

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reduce the need for multiple arrangements, particularly the use of multiple, informal care providers.

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The purpose of this study is to estimate the effects of child care subsidy program generosity on the number and type of

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arrangements parents use for their young children using a nationally-representative, birth cohort study of children born in the U.S. in 2001 and difference-in-difference techniques. Findings from this study can provide insight into parents’ decision-making with regard

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to parents’ reasons for using multiple arrangements, as well as the degree to which public policy choices may influence those

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decisions. Moreover, given the potential adverse effects of multiple arrangements on child behavioral development (e.g., Morrissey, 2009; Pilarz & Hill, 2014) and parental employment stability (Usdansky & Wolf, 2008), the findings have important implications for the subsidy program’s goals of improving access to stable, high-quality care and promoting children’s development. Background

ACCEPTED MANUSCRIPT The CCDF Child Care Subsidy Program The child care subsidy program funded through the CCDF constitutes the main source of child care assistance for low-income working families. The program is funded primarily through the Child Care and Development Block Grant (CCDBG), as well as

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through funds that states transfer from their Temporary Assistance for Needy Families (TANF) block grant. The federal government

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contributes the majority of program expenditures, but states administer the program and also contribute matching funds (Gish, 2002).

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In fiscal year (FY) 2016, CCDF child care expenditures totaled $11.6 billion in federal and state funds combined, and 1.37 million

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children received a subsidy in an average month (Center for Law and Social Policy [CLASP], 2018). To be eligible for a child care subsidy, parents must meet their state’s subsidy program eligibility requirements. Federal rules

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require that parents be employed or enrolled in an educational program, and have a family income below 85% of the state median

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income. States may set the income eligibility threshold below the federal maximum and most cap eligibility at between 100% and

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200% of the federal poverty line (Adams & Rohacek, 2002; Schulman & Blank, 2014). During the study period (2001-2003), states

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had substantial discretion over many other program parameters, including the length of the eligibility period after which parents must redetermine their eligibility, provider reimbursement rates, parent co-payment amounts, and whether or not they have a wait list or

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serve all eligible families who apply (Schulman & Blank, 2014). For example, in FY2000-FY2001, 28 states set provider reimbursement rates at or above the 75th percentile of market rates, as recommended by federal guidelines, and 16 states had varying reimbursement rates for different levels of quality or types of care (U.S. DHHS, 2001). Parents may use the subsidy to purchase both licensed center- and home-based care and unlicensed, informal care, but states may limit the use of informal care by restricting

ACCEPTED MANUSCRIPT eligibility for informal providers and requiring informal providers to meet similar health and safety standards as licensed providers (Adams & Rohacek, 2002). For example, in FY2000-FY2001, 26 states limited in-home care (i.e., provided by an individual in the child’s home) while 22 states exempted or had different health and safety requirements for relatives care providers (U.S. DHHS 2001).

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Due to funding constraints, states face trade-offs between serving as many eligible families as possible (e.g., by setting high income

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eligibility limits) versus serving a smaller pool of eligible families but spending more per child (e.g., by setting high reimbursement

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rates).

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The CCDBG Reauthorization Act of 2014, which reauthorized the CCDF program for the first time since it was created in 1996, made several important changes to the federal requirements for states’ programs with the goal of improving the safety, quality,

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and stability of child care and fostering children’s development. These changes included setting the minimum eligibility period to 12

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months; increasing requirements for background checks, health and safety trainings, and inspections of child care providers; and

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requiring states to spend 3% of CCDBG funds on improving the quality of care for infants and toddlers (Matthews, Schulman,

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Vogtman, Johnson-Staub, & Blank, 2017). These changes resulted in higher costs administrative costs for states and higher subsidy costs per child served, and Congress recently increased federal funding for CCDBG by $2.4 billion in FY2018 to fully fund the 2014

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reauthorization (CLASP, 2018).

Child Care Subsidies and Parental Child Care Decision-Making Meyers and Jordan’s (2006) accommodations framework of parental child care decision-making proposes that parents’ child care choices can be viewed as a set of accommodations to multiple competing demands—including families’ needs (e.g., resulting

ACCEPTED MANUSCRIPT from parental employment demands) and resources (e.g., income) for providing child care, the availability and affordability of care in their community, and social and cultural expectations. As a result, the arrangements parents use can be seen as an accommodation to their own preferences and to the opportunities and constraints they face in the child care options available to them (Chaudry, Henly, &

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Meyers, 2010; Meyers & Jordan, 2006; Weber, 2011). Although research suggests that low-income families engage in similar

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decision-making processes as higher-income families (Meyers & Jordan, 2006), they do so with greater constraints, especially fewer

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financial resources, and they use more expensive center-based care at lower rates than higher-income families (Capizzano & Adams,

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2004).

Parents’ decisions about the number and type of child care arrangements to use may be driven by both by their preferences for

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particular type(s) or amounts of care and by different types of constraints resulting from employment demands or the availability and

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affordability of child care providers in their community. Due to economic and cost constraints, low-income parents are typically

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unable to afford care in the formal child care market without financial assistance. Those who turn to friends and relatives to provide

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child care often worry about overburdening them, and this may lead them to rely on multiple caregivers to distribute the burden and also cover all of their work hours (Henly & Lyons, 2000; Lowe & Weisner, 2004). The high cost of formal care may also lead some

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parents to use a combination of center-based and informal care to reduce child care costs. With regard to employment constraints, parents who work nonstandard or variable schedules may rely on multiple care arrangements because they cannot find a single provider to cover all of their working hours, especially child care centers, which are typically open during weekday, daytime hours only (Henly & Lambert, 2005). Parents may also prefer and choose to use multiple care arrangements because they want to expose

ACCEPTED MANUSCRIPT their child to multiple types of care, such as center-based care and relative care, or wish to limit center-based care (Gordon et al., 2013; Neilsen-Hewett et al., 2014). Although both low-income and higher-income families experience constraints in their child care decisions, qualitative studies of child care decision-making among low-income, working families suggest that the use of informal care

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and the use of multiple arrangements are often the result of market and employment constraints rather than parental preferences

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(Chaudry, 2004; Henly & Lambert, 2005; Scott et al., 2005).

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Child care subsidy programs are expected to reduce the use of multiple care arrangements that are driven by low-income

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parents’ cost constraints. Given the high cost of center-based care, subsidies should be particularly likely to increase parents’ access to

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a single center-based arrangement and to reduce the need for multiple providers. To the extent that multiple arrangements are driven

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by parents’ employment constraints or preferences, subsidies may not substantially decrease the use of multiple arrangements. In

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particular, although subsidies are expected to reduce the need for multiple home-based arrangements, they may be associated with a

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smaller (or no) reduction in multiple arrangements combining center- and home-based care.

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Prior Research

Prior studies have consistently found a relationship between child care subsidies and enrollment in center-based child care by

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examining increases in subsidy spending over time and within states (Greenberg, 2010; Magnuson et al., 2007; Weber, Grobe, & Davis, 2014). These studies find that large increases in subsidy program spending are associated with small increases in the rate of center-based care. For example, Weber and colleagues (2014) examined the impact of a $40 million increase in subsidy program spending in the state of Oregon in 2007, which increased provider reimbursement rates, decreased parent copayments, increased

ACCEPTED MANUSCRIPT income eligibility limits, and increased the length of eligibility periods. By comparing families who entered the program prior to and after the policy change, the authors estimated that the policy change led to small increases of 3 to 5 percentage points in center-based care enrollment for children under age 5 among families who entered the subsidy program under the new policy regime, suggesting

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that increases in program generosity led to higher rates of center-based care.

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Two additional studies have examined how variation in subsidy program spending across states relates to the type of care

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families use. Using difference-in-difference methods, Washbrook, Ruhm, Waldfogel, and Hahn (2011) found that a $1,000 increase in

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state subsidy spending predicted a 3 percentage point lower rate of exclusive parental care and a 2.8 percentage point higher rate of

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center-based care (as the primary care arrangement) among 9-month-old children in subsidy-eligible families, but no relationship

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between subsidy spending and the use of home-based care. Similarly, Rigby, Ryan, and Brooks-Gunn (2007) found that state subsidy

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spending—but not income eligibility limits—was associated with a higher likelihood of using center-based care versus any other care

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type among 3-year-old children.

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Several additional studies have used a variety of experimental and quasi-experimental methods to estimate the effects of using a subsidy on parents’ decisions about type of care (Brooks, 2002; Crosby et al., 2005; Ryan et al., 2011; Tekin, 2005). These studies

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consistently find that subsidy receipt is associated with a greater likelihood of using center-based care for young children between the ages of 0 to 5 years, but they find limited evidence that subsidy use is related to the use of home-based care. Only one prior study has considered the relationship between child care subsidies and parents’ decisions about the number of arrangements. Using data from a longitudinal study of low-income families in Minnesota, Krafft, Davis, and Tout (2017) estimate the

ACCEPTED MANUSCRIPT associations between receiving a subsidy and the quality and stability of child care arrangements, including the number of concurrent arrangements used. Results from child-level fixed effects models show no relationship between a change in subsidy receipt and a change in the number of concurrent arrangements used; however, the study did not consider the type of care used. It is possible that

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subsidy receipt is related to increases in the use of particular types of single arrangements (e.g., single center-based arrangement)

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relative to multiple arrangements (e.g., multiple home-based arrangements), especially since subsidies are consistently associated with

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increasing the use of center-based. Additionally, whereas Krafft and colleagues (2017) considered the effects of subsidy receipt on

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subsidy recipients’ child care arrangements in one particular state, the effects of cross-state variation in state subsidy program generosity—the focus of this study—on subsidy-eligible parents’ child care arrangements may differ.

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Together, this prior research provides substantial evidence that child care subsidies, and in particular, state subsidy program

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generosity, increase the use of center-based care among subsidy-eligible and subsidy-receiving families and suggests that reducing

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cost constraints helps at least some low-income families better accommodate their preferences for center-based care. With few exceptions, studies have focused on the relationship between child care subsides and a child’s primary care arrangement. No prior

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studies have examined whether child care subsidies relate to both the type and number of arrangements parents use. Yet, to the extent

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that low-income families’ use of multiple arrangements is driven by cost constraints, subsidies may also influence parents’ decisions to use a single arrangement versus multiple arrangements. The Current Study

ACCEPTED MANUSCRIPT This study aims to further knowledge on how child care subsidy programs influence parents’ child care decisions by examining how the generosity of state subsidy programs relates to parents’ decisions about both the number and type of child care arrangements. Using data from a nationally-representative study of children born in 2001, the analyses use difference-in-difference techniques to

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estimate the effects of state subsidy program spending on the use of parental care only, a single arrangement (home-based or center-

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based), and multiple arrangements among subsidy-eligible families (defined as low-educated families). This study focuses on young

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children ages 9 months and 2 years, in order to examine how subsidies impact parents’ decisions prior to children being eligible for

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other publicly-available early care and education programs, like Head Start and public prekindergarten, and because child care subsidy

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programs may be particularly salient to parents of infants and toddlers, who have fewer alternatives for subsidized care. The study

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hypotheses are that higher levels of state subsidy spending will be associated with higher rates of enrollment in a single center-based

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arrangement but not a single home-based arrangement, and that higher levels of subsidy spending will be associated with lower rates

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of multiple arrangements, particularly multiple home-based arrangements, among low-educated families. It is also expected that

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subsidy spending will be associated with a greater likelihood of using a single center-based arrangement relative to multiple arrangements. Examining the effects of child care subsidy program generosity on both the number and type of arrangements can

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improve our understanding of parents’ child care decision-making by providing an estimate of the extent to which cost constraints may contribute to low-income parents’ decisions about the number and type of arrangements to use, as well as how child care subsidy programs may influence these decisions. Method

ACCEPTED MANUSCRIPT Data and Sample This study uses data from the Early Childhood Longitudinal Study—Birth Cohort (ECLS-B), a nationally-representative longitudinal study of children born in the U.S. in 2001. The ECLS-B obtained a sample of 14,000 children by sampling birth

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certificates from primary sampling units. Children who died or were adopted before age 9 months and children who were born to

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mothers who were 15 years or younger were excluded.

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In-home interviews with the child’s primary caregiver (95% biological mothers) were conducted when children were

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approximately 9 months (wave 1; 2001-2002), 2 years (wave 2; 2003-2004), and 4 years of age (wave 3; 2005-2006), and during the

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fall of their kindergarten year (waves 4 and 5; 2006-2007). In-home interviews collected self-reported, detailed information about the

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use of non-parental child care arrangements, characteristics of the focal child, the child’s parents, and household members. This study

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used data from the first two waves of the study. At wave 1, interviews took place between October 2001 and December 2002, and at

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wave 2, from January to December 2003. Response rates were high at both waves: of the 14,000 families who were sampled, 10,700

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participated in the first wave of data collection (wave 1; 74% response rate), and at wave 2, 9,850 families participated (93% response rate).1 As there were a relatively small percentage of children in multiple arrangements at waves 1 and 2 (8-10%), the first two waves

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of the study were pooled in order to conserve power and because the effects of child care subsidy program generosity were expected to be similar at both ages.

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The ECLS-B study requires that sample sizes be rounded to the nearest 50.

ACCEPTED MANUSCRIPT The analytic sample for this study was limited to children who lived with their biological mother at the time of the interview and whose biological mother participated in the interview. Eligibility for and use of child care subsidies may differ between children who live with their biological mother and those who do not, particularly if they live with foster parents. Also, key control variables,

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such as whether or not the mother worked in the 12 months prior to the child’s birth, were only asked if the respondent was the child’s

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biological mother. The analytic sample excluded 150 cases at wave 1 and 250 cases at wave 2 that did not meet these criteria.

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Cases with missing data on variables used in the analyses were dropped from the sample using listwise deletion, which resulted

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in a loss of 5.8% of cases in the sample (n=1150). Most variables had fewer than 1% of missing cases with the following exceptions: child age at wave 1 (4.3% missing); whether the biological mother worked prior to child’s birth (1.6% missing); and whether the

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mother received welfare in childhood (1.4% missing). Overall, cases that were excluded from the sample tended to: be younger; have

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lower levels of education; be less likely to identify as white; be more likely to be single and less likely to be married; be less likely to

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have worked prior to the child’s birth; be more likely to have received WIC during pregnancy; and be less likely to live in a small

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urban area (with population 2,500-49,999). Additionally, because the study focuses on state-level child care subsidy spending, five states with very few cases (DE, DC, NH, VT, WV) were excluded, which resulted in dropping approximately 50 cases. The final

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analytic sample (after pooling data from waves 1 and 2) consisted of 18,900 children, of which 6,900 were in low-educated households and 12,000 were in higher-educated households. Treatment and Comparison Group Definitions

ACCEPTED MANUSCRIPT To estimate the effects of child care subsidy program generosity on the number and type of child care arrangements, this study used a cross-sectional difference-in-differences (DD) approach. The effect of the policy was estimated by assessing differences in the outcome across different policy treatments (the first difference) and between treatment and comparison groups (the second difference).

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The policy treatment was state child care subsidy program spending, which was used as a proxy for subsidy program generosity.

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The DD approach requires identifying a treatment group that is likely eligible for child care subsidies and a comparison group

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that is likely ineligible and thus unaffected by child care subsidy spending. It is also important that the treatment and comparison

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groups would have had conceivably similar outcomes (i.e., the use of multiple arrangements) in absence of the policy. Although

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eligibility for child care subsidies is determined by family income, using family income to identify treatment and comparison groups is

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problematic because family income is endogenous to subsidy receipt (i.e., receiving a subsidy is expected to influence employment

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and earnings). Therefore, family characteristics—like parental education—that are strongly correlated with income and employment

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but not endogenous to subsidy receipt can be used as proxies. One study that used a DD approach to estimate the effects of child care

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subsidies on child care arrangements used parental level of education as a proxy for eligibility and defined the treatment group eligible for subsidies as very low-educated households in which neither parent has a high school degree and the comparison group as higher-

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educated households with at least a high school degree (Washbrook et al., 2011). Another study that also used a DD framework to estimate the effects of subsidy program spending on maternal employment used family structure as a proxy for eligibility by defining the treatment group as single mothers with young children and the comparison group as single mothers with teenage children, who are age-ineligible for subsidies (Bainbridge, Meyers, & Waldfogel, 2003).

ACCEPTED MANUSCRIPT Because this study was interested in estimating the effects of subsidy spending on child care arrangements and the sample is limited to families with young children, this study followed Washbrook and colleagues’ (2011) approach and used parents’ highest level of education as a proxy for subsidy eligibility. Low-educated families with a high school degree or lower level of education

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formed the treatment group, and higher-educated families with more than a high school degree (i.e., some college or a college degree)

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formed the comparison group.

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These definitions were utilized for both conceptual and practical reasons. First, families with a high school degree or less

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education are most likely to be able to eligible for subsidies based on state subsidy programs’ income and employment eligibility

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criteria. Although families with less than a high school degree (the treatment group used by Washbrook and colleagues [2011]) are

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more likely to be income-eligible, they may have a more difficult time finding a job that meets the program’s employment

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requirements, especially stable jobs that provide sufficient hours, as they face higher unemployment rates than higher-educated

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families (U.S. Bureau of Labor Statistics, n.d.b). Conversely, families with some college education may have an easier time meeting subsidy programs’ employment requirements—and recent research from Illinois suggests that families with some college education

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are over-represented among subsidy recipients compared to non-recipients (NSECE, 2016b)—but due to their higher wages, may earn

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too much to be income-eligible. Moreover, the treatment and comparison groups used in this study appear similar on the key outcomes of interest. On average, children in low- and higher-educated families used multiple arrangements at similar rates (see Table 1). Second, despite the large sample size, there were a relatively small number of children in multiple arrangements. By using all families in the sample and not limiting the analysis to single mother families (like Bainbridge and colleagues [2003]), this study

ACCEPTED MANUSCRIPT utilized the full ECLS-B sample and maximized the power to detect statistically significant differences. There was also a larger difference in the rate of multiple arrangements between non-married, low-educated households and non-married, higher-educated households (10.5% versus 14.4%, respectively) than between low- and higher-educated households.

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To assess the robustness of the findings to using these treatment and comparison group definitions, the analyses included

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several sensitivity tests. First, two alternative treatment group specifications were used to examine whether the results are sensitive to

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the level of education used to identify the treatment and comparison groups: 1) limiting the treatment group to include only

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households with less than a high school degree; and 2) expanding the treatment group to include households with some college

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education. Next, subgroup analyses were used to test the sensitivity of the findings to subgroups of mothers who may be more likely to

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be eligible for and incentivized to taking up a child care subsidy: non-married (i.e., single mother) households, who have a greater

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need for non-parental care and may have an easier time meeting the subsidy program’s income eligibility limits compared to married

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households; mothers ages 25 or older, who may be more likely to use the subsidy for employment than education; and mothers who worked during the 12 months prior to the child’s birth, who are more likely to return to work after the child’s birth and therefore, more

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likely to be eligible for and take up a subsidy. Measures

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Number and type of child care arrangements. At each wave, mothers reported the total number of regular, non-parental child care arrangements by each of the following types of care: home-based care provided by a relative; home-based care provided by a non-relative (including family child care homes); and center-based care. Mothers were instructed to consider only providers used on a regular basis and to exclude occasional babysitting or back-up providers.

ACCEPTED MANUSCRIPT Outcome variables were defined by the number and type of child care arrangements used at each wave according to the following categories (see Table 1 for descriptive statistics): (1) parent care only; (2) single home-based arrangement (i.e., care provided by relatives or non-relatives in a home-based setting); (3) single center-based arrangement; and (4) multiple arrangements (of

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any type). Some analytic models also disaggregated the multiple arrangements category into multiple home-based arrangements and

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multiple home- and center-based arrangements. Multiple home-based arrangements included care provided by multiple relatives, by

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multiple non-relative care providers, or by a combination of relatives and non-relatives in a home-based setting. The most common

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types of multiple home-based arrangements were care provided by multiple relatives (4.7% of children in low-educated and 3.1% in

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higher-educated households) and a combination of relative and non-relative care providers (1.6% of children in low-educated and

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2.8% in higher-educated households). Multiple home- and center-based arrangements included center-based care plus care provided

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by relatives or non-relatives in a home-based setting. The most common type of multiple home- and center-based arrangements

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consisted of center-based care and relative care (1.5% of children in low-educated and 1.8% in higher-educated households). There

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were approximately zero children in multiple center-based arrangements; these few cases were included in the single center-based arrangement category.

C A

As shown in Table 1, there were significant differences in both the number and type of arrangements across the treatment and comparison groups. In particular, compared to children in higher-educated households, children in low-educated households were more likely to be in parent care only and less likely to be in a single center-based arrangement. Children in low-educated households were also less likely to be in multiple arrangements, but the magnitude of this difference was small (1.3 percentage points) and was

ACCEPTED MANUSCRIPT driven by differences in the use of multiple home- and center-based arrangements, with no differences between groups in the use of multiple home-based arrangements. Child- and family-level control variables. The analytic models adjust for a large set of child, maternal, and household

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characteristics that could plausibly be related to selection into the number and type of care arrangements used and selection into the

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child care subsidy program, as well as differences in the composition of the treatment and comparison groups. Control variables that

C S

were included in all models are shown in Table 2.

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Child characteristics included child’s age at time of the interview measured in months; child gender; and an indicator for low birth weight (<2500g). Maternal characteristics included: mother’s age at the time of the child’s birth and race and ethnicity measured

A

M

with a set of categorical variables for: non-Hispanic white; non-Hispanic black; Hispanic; and other race or ethnicity, including Asian

D E

or Pacific-Islander, Native-American, or multiracial. The models also controlled for the mother’s marital status at each wave with a set

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of indicator variables for currently living without a partner (i.e., single), cohabiting with a partner, and married. Mother’s current employment status and job characteristics (i.e., nonstandard work schedules) were not included in the models

E C

because subsidy program generosity is expected to influence whether, how much, and what type of job the mother works and

C A

therefore, is likely endogenous to subsidy program generosity (Bainbridge et al., 2003; Washbrook et al., 2011). Instead, the models controlled for whether or not the mother worked at any time in the 12 months prior to the child’s birth, which is predictive of postbirth employment status. To capture potential differences in the propensity to use public assistance programs, the models included indicators for whether or not the mother used the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) to

ACCEPTED MANUSCRIPT purchase food for herself during her pregnancy, and whether the mother reported residing in a household that received welfare when she was a child. To capture potential differences in mothers’ child care preferences between the treatment and comparison groups, mother-

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reported priorities for choosing child care collected at the 9-month wave were included as a proxy for preferences. These included six

I R

indicators for the mother reported that the following aspect of care was (or would be) very important when choosing a child care

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arrangement: a caregiver with special training in taking care of children; a small number of children in the group/class; a caregiver

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who speaks English with the child; a place where children will be cared for when sick; a place close to home; and a reasonable cost.

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Household composition at each wave included: the number of non-parental adults in the household; the number of children

M

ages 0 to 5 years in the household (including the focal child); and the number of children ages 6 to 17 years. The models also

D E

controlled for urbanicity, which was constructed by the ECLS-B study using the household ZIP code and 2000 Census definitional

T P

criteria for urban and rural areas, since access to child care providers and child care assistance may be more limited in less densely

E C

populated areas. The household was classified as residing in an urban or rural area using the following three categories: residing in an urbanized area with a population of 50,000 or more; urban cluster with a population of 2,500 to 49,999; and rural area with less than 2,500 people.

C A

The treatment and comparison groups were statistically significantly different on most sample characteristics, although the magnitude of these differences was small in many cases (see Table 2). The only child characteristic that was statistically significantly different between both groups was low birth weight, with low-educated households having slightly higher rates of low birth weight

ACCEPTED MANUSCRIPT children. Compared to higher-educated households, mothers in low-educated households were younger, more likely to identify as Black or Hispanic, and less likely to be married. They were also less likely to have worked prior to the child’s birth and were more likely to have received public assistance (both WIC during pregnancy or welfare in childhood). With regard to child care priorities,

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rates of endorsing quality-related aspects of care (e.g., caregiver with special training) were similar across the groups, but mothers in

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low-educated households were more likely to report that practical aspects of care were very important when selecting an arrangement

C S

(e.g., reasonable cost). Finally, low-educated households had a greater number of children and non-parental adults living in the

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household and were more likely to reside in rural areas compared to higher-educated households.

A

State-level child care subsidy program generosity. Child care subsidy program spending was used as a proxy for overall

M

program generosity and was measured as the total amount of federal and state expenditures on CCDF child care subsidies from the

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CCDBG and TANF block grants. Total spending by state was compiled by the Center for Law and Social Policy (CLASP) in their

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Child Care Assistance State Profiles 2006, which include spending by year for FY2001 to FY2006 (CLASP, 2008). Spending from

E C

FY2001 was used for wave 1, since children were born in 2001 and interviews were conducted between October 2001 and December 2002.2 Spending from FY2003 was used for wave 2 since interviews were conducted between January and October 2003. To adjust

C A

for varying levels of need for child care subsidies across states, the total amount of state subsidy program spending was divided by the number of poor children under age 6 in the state.3 This was done because poor children are most likely to be eligible for and receive

2 3

Note that FY2001 begins on October 1, 2000 and ends on September 31, 2001. See Table A2 in the appendix for the definition of and source for estimates of the number of poor children under age 6 in each state.

ACCEPTED MANUSCRIPT subsidies, most CCDF funds go to children ages 0-5 years (Chien, 2015), and in order to be consistent with prior studies of child care subsidy program spending and child care choices (Greenberg, 2010; Washbrook et al., 2011). Spending in FY2001 was adjusted for inflation to 2003 dollars using the Consumer Price Index (CPI). The level of state subsidy spending per poor child under age 6

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(henceforth, state subsidy program spending) varied widely across states in FY2001 and FY2003 but remained relatively stable across

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years (see Table 3). Median state subsidy program spending was approximately $2,000 in both years. Because state-level variation in

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the cost of living—including child care prices—may impact the value of the subsidy across states, subsidy program spending was

U N

adjusted for cost-of-living differences across states using a state CPI index created by Berry, Fording, and Hanson (2000) prior to

A

estimating the analytic models.

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State subsidy program spending captures two distinct aspects of generosity: 1) the inclusiveness of the program (i.e.,

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proportion of eligible children who are served); and 2) the value of the subsidy to families who use the program (i.e., amount spent per

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child served). It was expected that both of these aspects of generosity would influence parents’ decisions about the number and type of

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arrangements among subsidy-eligible families by reducing cost constraints for parents to access more expensive and potentially more preferred care arrangements. However, higher subsidy values are likely to provide participating parents access to a greater number of

C A

options, and thus, may have a larger impact on reducing the use of multiple arrangements and increasing the use of center-based care. To examine how this measure of overall program generosity relates to these two aspects of generosity, Table A1 in the appendix shows how proxies for program inclusiveness (i.e., number of children served by the subsidy program divided by the number of poor children under age 6 years in the state) and value of the subsidy (i.e., total state subsidy program spending divided by the number of

ACCEPTED MANUSCRIPT children served by the subsidy program) compare among states at the top, middle, and bottom of the distribution on overall program generosity. States with the highest levels of subsidy spending also had the highest subsidy values and levels of program inclusiveness; however, there was much more variation in the value of the subsidy (ranging from about $3,700-$4,000 per child among the lowest

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spending states to $10,300-$12,600 among the highest spending states) than in the level of program inclusiveness (ranging from about

I R

30-50% of eligible children).4 Additionally, most states did not serve all eligible children in 2001 (i.e., had a waiting list), and among

C S

the highest spending states, only Wisconsin reported that they did not have a wait list. Thus, the associations between subsidy program

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generosity and child care choices in this study are most likely driven by differences across states in the value of the subsidy rather than

A

in program inclusiveness.

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State-level control variables. The analytic models included controls for various state demographic and policy characteristics

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to adjust for differences across states that may be related to both child care subsidy spending and child care arrangements. State

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characteristics were selected that could conceptually be related to states’ child care subsidy program generosity and that have been

E C

used in prior research on child care subsidies. For example, state policies that are thought to influence maternal employment, and in turn, child care decisions, were included (e.g., EITC), and state demographic characteristics were included that have been used in prior

C A

studies of subsidy program generosity and child care choices (Magnuson et al., 2007; Washbrook et al., 2011). State policy characteristics included the maximum TANF benefit levels for a family of three, whether or not the state had a refundable EITC or a 4

Estimates of the value of the subsidy and program inclusiveness are proxies and are used here to compare program generosity across states. Estimates of program inclusiveness that are based on state and federal eligibility rules are lower and suggest that 15-25% of eligible children receive a subsidy (Chien, 2015).

ACCEPTED MANUSCRIPT refundable Child and Dependent Care (CDC) tax credit, and whether or not the state had a Temporary Disability Insurance (TDI) program (see Table A2 in Appendix for sources). State demographic characteristics included: log of the state population, the percentage of the population that is African American and the percentage that is Hispanic, the state poverty rate, the state

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unemployment rate, and the census region in which the state is located: Northeast, Midwest, West, and South. State political climate

I R

was measured with an indicator for whether Republicans held a majority in the state House of Representatives and state Senate and

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with the percentage of workers covered by a union.

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Analytic Approach

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The cross-sectional difference-in-differences (DD) approach used in this study estimates the effects of subsidy program

M

generosity by leveraging differences in subsidy spending across states at one point-in-time (following a similar approach as

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Washbrook and colleagues [2011]). Since the ECLS-B is a birth cohort study that follows the same children over time, it was not

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possible to use a longitudinal DD approach to leverage within state variation in subsidy spending over time because changes in

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subsidy spending over time would be confounded with the aging of the sample. It was not possible to compare treatment and comparison group families within the same state because there was very little variation in subsidy spending across waves 1 and 2, and

C A

this prohibited the inclusion of state fixed effects. This cross-sectional approach relies on arguably stronger assumptions than the traditional, longitudinal DD approach since the effects of the policy are being estimated across (and not within) states. The main assumption of this approach is that there are no other state-specific factors that differentially affect the treatment and comparison groups and that are also related to child care usage. In other words, differences in child care arrangements between treatment and

ACCEPTED MANUSCRIPT comparison groups would be the same across states in absence of the policy. Of course, states may differ in ways that are both related to children’s child care arrangements and that differentially affect subsidy-eligible and non-eligible families, such as the generosity of other work support programs for low-income families like TANF and the Earned Income Tax Credit (EITC). In order to minimize

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threats to this assumption, the analytic models controlled for a wide range of child- and family-level characteristics to adjust for

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differences between treatment and comparison groups across states, and the analyses estimated models that adjust for potentially

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confounding state policies and state demographic characteristics (see next section, “Estimation model,” for details).

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Estimation model. This study used multinomial logistic regression models to estimate the effects of state subsidy spending on

A

the relative odds of using parent care only or a single arrangement (single home-based or single center-based arrangement) compared

M

to using any multiple arrangements. Results are presented using the exponentiated coefficients, called relative risk ratios (RRRs), from

D E

these models. RRRs can be interpreted similarly to odds ratios and represent the relative odds of using parent care or a single

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arrangement compared to using multiple arrangements. Values greater than one represent higher odds of using a particular type of care

E C

relative to multiple arrangements, and values lower than one represent lower odds of using a particular type of care relative to multiple arrangements. These multinomial logistic regression models were also used to estimate the predicted probabilities and average

C A

marginal effects (i.e., the average of the partial effects across all observations) of subsidy spending on each type of care. Models that disaggregated the any multiple arrangements category into multiple home-based arrangements and multiple home- and center-based arrangements were also estimated to examine whether the results differ depending on the type(s) of care combined. The estimation model is:

ACCEPTED MANUSCRIPT Yis = β0 + β1CCSs + β2 LOWEDUis + β3(CCSs x LOWEDUis) + Xisβx + Psβp + εis , where i indexes individuals and s states. The outcome, Yis , is a categorical variable measuring the number and type of arrangements (i.e., parent care only, single home-based arrangement, single-center based arrangement, and any multiple

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arrangements). The coefficient of primary interest is the interaction between treatment group status and child care subsidy spending,

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β3(CCSst x LOWEDUist), which represents the DD estimate. Model 1 included a vector of child- and family-level controls, Xisβx;

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Model 2 added a vector of state policies and characteristics, Psβp,; and Model 3 allowed state characteristics that may differentially

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affect the treatment and comparison groups to vary across groups by adding a set of interaction terms between these state

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characteristics and the treatment group indicator: TANF maximum benefit, refundable EITC, refundable CDC, TDI program, poverty

M

rate, unemployment rate, majority Republican in state legislature, and region. Models did not control for states’ child care supply

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because this may act as a mechanism linking subsidy program generosity and parents’ child care choices since we would expect

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subsidy spending to increase the child care supply in a state. Sensitivity analyses that added a measure of states’ child care supply— defined as the number of child care establishments (from the U.S. Census Bureau’s 2002 Economic Census) divided by the number of

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children ages 0-5 in the state—found very similar results as the main models.

C A

All models were weighted using the ECLS-B survey weights to adjust for differential sampling probability, stratification in the sampling design, and clustering within probability sampling units (PSUs), and provide robust standard errors. Models that adjusted for clustering by child ID to account for multiple observations per child and models that adjusted for clustering by state ID to account for

ACCEPTED MANUSCRIPT clustering of observations within states were also estimated. In both cases, the results were very similar and did not change the interpretation of the findings. Results

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Predicting Number and Type of Child Care Arrangements

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Results from multinomial logistic regression models predicting the number and type of care arrangements show that subsidy

C S

program spending was associated with higher odds of using a single center-based arrangement relative to multiple arrangements

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among low-educated households (see Table 4). The relative odds of using a single center versus multiple arrangements increased in

A

magnitude as more controls were added in Models 2 and 3. A $1,000 increase in subsidy spending was associated with 86% higher

M

odds of using a single center-based arrangement rather than multiple arrangements among low-educated households (in Model 3). This

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suggests that low-educated households in higher spending states were more likely to use a single center-based arrangement than to use

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multiple arrangements in comparison to higher-educated households. There were no statistically significant differences in the use of

E C

parent care or a single home-based arrangement versus multiple arrangements for low-educated households. The next set of analyses disaggregated the multiple arrangements category into multiple home-based and multiple home- and

C A

center-based arrangements. Due to the smaller number of observations in the disaggregated categories—particularly in multiple homeand center-based arrangements—these results are interpreted with caution. Results from a multinomial logistic regression model (Model 3) with multiple home-based arrangements as the contrast category were similar to those presented above with any multiple arrangements as the contrast category (see Appendix Table A3). A $1,000 increase in subsidy spending was associated with

ACCEPTED MANUSCRIPT approximately two times higher odds of using a single center-based arrangement relative to multiple home-based arrangements among low-educated households. Additionally, subsidy spending was associated with 40% higher odds of using a single home-based arrangement relative to multiple home-based arrangements among low-educated households. None of the DD estimates were

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statistically significant for multiple home- and center-based arrangements. These results provide suggestive evidence that the

I R

associations between subsidy spending and multiple arrangements depend on the type(s) of care combined in multiple arrangements.

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Predicted probabilities. In order to ease interpretation of the findings from the multinomial logistic regression models,

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estimates of the adjusted predictions (i.e., predicted probabilities) from multinomial logistic regression Model 3 are shown in Figures

A

1 and 2 to illustrate trends in the probability of using each care type as state subsidy program spending increases (from $1,000 to

M

$4,000 in $500 intervals) among the treatment and comparison groups.

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In states with low levels of subsidy spending, low-educated households were more likely than higher-educated households to

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use parent care only, but at high levels of subsidy spending there were no statistically significant differences between the two groups

E C

(see Figure 1). The adjusted predictions for using a single center-based arrangement show that in low-spending states lower-educated households were less likely to use a single center-based arrangement than higher-educated households; this gap closes as state subsidy

C A

spending increases so that in high-spending states there were no longer statistically significant differences between the two groups. For the adjusted predictions of a single home-based arrangement, there were no statistically significant differences between the two groups at any level of spending.

ACCEPTED MANUSCRIPT With regard to the use of any multiple arrangements, in states with low levels of subsidy spending there were no differences in the use of multiple arrangements between low- and higher-educated households; however, in higher-spending states, low-educated households were less likely than higher-educated households to use multiple arrangements (see Figure 1). This appears to be due to

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diverging trends in the use of multiple arrangements between low- and higher-educated households: low-educated households become

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slightly less likely to use multiple arrangements as spending increases while higher-educated households become slightly more likely

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to use multiple arrangements as spending increases. Additionally these trends appear to be primarily driven by the use of multiple

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home-based arrangements (see Figure 2); there were no differences between the two groups in the predicted probabilities of using

A

multiple home- and center-based arrangements at any level of subsidy spending as the trends appear nearly identical.

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In order to better compare how the distribution of the predicted probabilities of different care types in low- and high-spending

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states differs between the treatment and comparison groups, Figure 3 graphs the predicted probabilities for each configuration of care th

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th

arrangements at the 10 and 90 percentiles of state subsidy spending for low-educated and higher-educated households. Both groups

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were most likely to use parent care only and were second most likely to use a single home-based arrangement regardless of state subsidy spending. In low-spending states, low-educated households were about as likely to use multiple arrangements as a single

C A

center-based arrangement (as evidenced by overlapping confidence intervals), but, in high-spending states, low-educated households were much more likely to use a single center-based arrangement than multiple arrangements (as indicated by non-overlapping confidence intervals). By comparison, higher-educated households were equally likely to use a single center as multiple arrangements in both low- and high- spending states. Overall, these findings suggest that more generous state subsidy spending leads to low-

ACCEPTED MANUSCRIPT educated families being more likely to use a single center than multiple arrangements and that this is driven primarily by higher rates of using a single center in high- versus low-spending states as well as slightly lower rates of using multiple arrangements, particularly multiple home-based arrangements.

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Marginal effects. To provide a further understanding of the findings from the multinomial logistic regression models and

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produce estimates comparable to prior studies (i.e., Washbrook et al., 2011), the average marginal effects of state subsidy spending on

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the use of each type of care using estimates from Model 3 are shown in Appendix Table A4. The DD estimate from marginal effects

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represents the effect of subsidy spending on the overall probability of using a particular type of care among low-educated households.

A

These results suggest that a $1,000 increase in subsidy spending was associated with a 3.8 percentage point (p=.002) increase in the

M

probability of using a single center-based arrangement among low-educated households. With regard to the use of any multiple

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arrangements, the DD estimate was in the expected direction—a decrease of 1.8 percentage points—but was statistically significant at

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a .10 significance level only (p=.09). When looking at the specific types of multiple arrangements, a $1,000 increase in subsidy

E C

spending was associated with a marginally statistically significant decrease of 1.9 percentage points (p=.05) in the use of multiple home-based arrangements among low-educated households, but was not associated with multiple home- and center-based

C A

arrangements. There was no association between subsidy spending and the probability of using parental care only or a single homebased arrangement. Sensitivity Tests

ACCEPTED MANUSCRIPT Alternative treatment group specifications. Two alternative treatment group specifications were used to test the sensitivity of the findings to altering the definition of the treatment and comparison groups. First, the treatment group was limited to very loweducated households with less than a high school degree, and households with a high school degree or more were included in the

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comparison group. The DD estimate (RRR) of using a single center-based arrangement versus multiple arrangements was in the

I R

expected direction but smaller, more imprecisely estimated, and not statistically significant (p=.20), which may be due in part to fewer

C S

cases in the treatment group (see Appendix Table A5). Marginal effects and predicted probabilities from this model suggest that very

U N

low-educated households in high spending states were less likely to use parental care only and more likely to use a single center

A

compared to those in low spending states; very low-educated households were not less likely to use multiple arrangements overall or

M

compared to higher-educated households in high spending states, unlike findings from the main models (see Appendix Tables A6 and

D E

A7).

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Second, the treatment group was expanded to include households with some college or less education in the treatment group

E C

and households with a college degree or more education in the comparison group. Multinomial logistic regression results were very similar to the main model findings, suggesting that a $1,000 increase in subsidy spending was associated with 72% higher odds of

C A

using a single center-based arrangement compared to multiple arrangements among some college-educated households (see Appendix Table A5). DD estimates using marginal effects and predicted probabilities also show very similar patterns to the main model findings (see Appendix Tables A6 and A7).

ACCEPTED MANUSCRIPT Subgroup analyses. The final set of analyses estimated the effects of subsidy spending on the number and type of arrangements for three subgroups of mothers in order to examine whether the findings differ by mothers’ marital status, age, and employment prior to the child’s birth. The subgroup analyses were conducted in two steps. First, a multinomial logistic regression

T P

model was estimated with the sample limited to each subgroup and using the same covariates from Model 3. This allows us to easily

I R

interpret the relationship between subsidy spending and the number and type of arrangements for each subgroup. Second, in order to

C S

test whether the effects of subsidy spending were statistically significantly different for each specific subgroup, a multinomial logistic

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regression model with the full sample and with a three-way interaction between subsidy spending, treatment group status, and

A

subgroup status was used.

M

For the subgroup of non-married mothers (n=6100), the results were similar to the full sample findings in that DD estimate

D E

(RRR) of using a single center-based arrangement versus multiple arrangements was positive, but was slightly smaller (1.54 versus

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1.86) and was not statistically significant (p=.11; see Appendix Table A5). However, the three-way interaction term was not

E C

statistically significant, suggesting that the effects of subsidy spending did not vary at a statistically significant level by marital status (results not shown).

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For the subgroup of mothers ages 25 and older (n=12,250), a $1,000 increase in subsidy spending was associated with 2.7 times higher odds of using a single center-based arrangement relative to multiple arrangements among low-educated mothers and with 75% higher odds of using a single home-based arrangements relative to multiple arrangements (see Appendix Table A5). Although the

ACCEPTED MANUSCRIPT effects of subsidy spending appear larger than in the full sample, the three-way interaction term was not statistically significant, suggesting that these effects did not vary at a statistically significant level (results not shown). For the subgroup of mothers who were employed prior to the birth of their child (n=13,500), a $1,000 increase in subsidy

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spending was associated with 1.7 times higher odds of using a single center-based arrangement relative to multiple arrangements

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among low-educated mothers. The three-way interaction term (coefficient from multinomial logistic regression model) was negative

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and marginally statistically significant (p=.08), suggesting that the effects of subsidy spending on the use of a single center-based

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arrangement versus multiple arrangements may be slightly smaller among this group. Marginal effects and predicted probabilities

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were also estimated for each subgroup analysis, and the pattern of findings was similar to the main model findings (see Tables A6 and A7 in Appendix).

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M

Discussion

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This study examined the relationship between states’ subsidy program generosity and the number and type of care

E C

arrangements used by infants and toddlers. Using data from a nationally-representative study of children born in 2001, the study found that higher levels of subsidy spending were associated with higher odds of using a single center-based arrangement relative to using

C A

multiple arrangements among low-educated families, who were likely eligible for child care subsidies. In low-spending states, children in low-educated families were as likely to use a single center-based arrangement as they were to use multiple arrangements, whereas in high-spending states, they were more likely to use a single center-based arrangement than multiple arrangements. Additionally, higher levels of state subsidy spending were associated with overall higher rates of enrollment in a single center-based

ACCEPTED MANUSCRIPT arrangement among low-educated families, and there was suggestive evidence that higher levels of spending were associated with lower rates of multiple arrangements, particularly multiple home-based arrangements. These findings are consistent with the study expectations and with prior research (Magnuson et al., 2007; Washbrook et al.,

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2011; Weber et al., 2014). The marginal effect of a $1,000 increase in state subsidy spending per poor child under age 6 on enrollment

I R

in a single center-based arrangement among low-educated families was 3.8 percentage points, representing a 35% increase over the

C S

base rate of enrollment (10.8%). This is consistent with prior studies that find a $1,000 increase in state spending on child care and

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early education per poor child is associated with 33% to 44% increase over the base rate of enrollment (Magnuson et al., 2007;

A

Washbrook et al., 2011). A $1,000 increase in state subsidy spending per poor child under age 6 is a relatively large increase in

M

spending (equivalent to approximately .75 standard deviations in subsidy spending). Thus, these studies suggest that a large increase

D E

in subsidy spending is associated with a modest effect on the use of center-based care.

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This study adds to the existing literature on the effects of child care subsidy programs on parents’ child care decisions by

E C

examining whether and how state subsidy program spending relates to the number of child care arrangements used. The results suggest that in higher-spending states subsidy-eligible families are less likely to use multiple arrangements relative to using a single

C A

center-based arrangement. At the 90th percentile of subsidy spending, low-educated families were about twice as likely to use a single center than to use multiple arrangements. The results provide suggestive evidence that a $1,000 increase in state subsidy spending is associated with a 1.8 percentage point decrease in the overall rate of multiple arrangements among low-educated families (the estimate

ACCEPTED MANUSCRIPT was marginally statistically significant), a small effect that corresponds to an approximately 20% decrease in the use of multiple arrangements over the base rate. This study tested the robustness of these findings to using alternative treatment and comparison group definitions and to

T P

subgroup analyses. The results are robust to expanding the treatment group definition to include households with some college

I R

education in the treatment group. However, there was no evidence that subsidy spending was associated with the number of

C S

arrangements used among very low-educated households, although subsidy spending was associated with significant increases in the

U N

rate of using a single center-based arrangement. It is possible that very low-educated households face greater employment

A

constraints—such as precarious and nonstandard work schedules (Lambert, Fugiel, & Henly, 2014; Presser & Ward, 2011) that

M

increase these families’ need for multiple arrangements (Folk & Yi, 1994; Henly & Lambert, 2005)—and make different child care

D E

decisions than more highly-educated households. There is also evidence that more highly-educated, low-income households are more

T P

likely to take up a subsidy (NSECE, 2016b), suggesting this more limited treatment group leaves out many subsidy-eligible families.

E C

The main model results were similar when limiting the sample to three subgroups of mothers who are more likely to be eligible for and incentivized to take-up a subsidy: non-married mothers, older mothers ages 25 and older, and mothers who were employed prior

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to the child’s birth. There was suggestive evidence that the associations between subsidy spending and the number and type of arrangements used may be stronger among older mothers and weaker among single mothers and previously employed mothers. Further research is needed to confirm these findings.

ACCEPTED MANUSCRIPT Findings from this study showing that child care subsidy program generosity is associated with a lower likelihood of using multiple arrangements differ from one prior study that examined the association between child care subsidy receipt and multiple care arrangements. Using child-level fixed effects models, Krafft and colleagues (2017) found no relationship between changes in subsidy

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receipt and changes in the number of concurrent arrangements used. One key reason why findings from these studies may differ is that

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whereas Krafft and colleagues (2017) examined the effects of a change in subsidy receipt among subsidy recipients in one particular

C S

state (Minnesota), the current study examined the effects of cross-state differences in subsidy program generosity among low-educated

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families, who were likely eligible for subsidies. Subsidy program generosity may influence families’ decisions about the number and type of arrangements by increasing take-up or by increasing subsidy recipients’ child care options (e.g., through higher reimbursement

A

rates).

D E

M

Another reason why findings from these studies may differ is that the effects of child care subsidy programs on the number of

T P

concurrent arrangements may differ by child age and the type(s) of care combined in multiple arrangements. Whereas the current study focused on infants and toddlers, Krafft and colleagues’ (2017) sample included children ranging in age from infancy to school-

E C

age, with nearly half of preschool age, and the analyses were unable to consider the type of care used by children who experienced an

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increase in concurrent arrangements. The use of multiple arrangements that combine home- and center-based care increases substantially between the toddler and preschool periods (Pilarz, 2018), and parents of older children express different child care preferences and face a different child care market when making child care decisions (Chaudry, 2004; Chaudry et al., 2011; Davis & Connelly, 2005; Fuller, Holloway, Rambaud, & Eggers-Piérola, 1996; Kim & Fram, 2009). Parents of preschoolers may be more

ACCEPTED MANUSCRIPT likely to use multiple arrangements at older ages due to their preferences for combining multiple types of care rather than due to cost constraints, given the greater availability of free and low-cost center-based options, like Head Start, for preschoolers (Gordon et al., 2013). Thus, cost constraints may play a larger role in parents’ decisions to use multiple arrangements when children are younger.

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This study found suggestive evidence that the associations between subsidy spending and multiple arrangements depend on the type(s)

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of care combined, but due to the small number of children experiencing multiple- home- and center-based arrangements, these finding

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are interpreted with caution. Future research should consider how the associations between subsidy spending and parents’ child care

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choices differ by child’s age and type of care.

Findings from this study suggest that child care subsidy programs may influence parents’ decisions about the number and type

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of care arrangements to use for their young children. By reducing cost constraints, it appears that more generous subsidy programs

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allow parents to access a single center-based arrangement rather than relying on multiple arrangements, especially multiple home-

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based arrangements. Also, subsidy program generosity was associated with a higher likelihood of using a single home-based arrangement than multiple home-based arrangements. This suggests that parents’ use of multiple arrangements is due, at least in part,

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to the unaffordability of care. This is consistent with prior qualitative research that suggests that parents rely on multiple informal,

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home-based providers due to being unable to afford formal, center-based care or to pay a single provider to cover all of their working hours (Henly & Lyons, 2000; Lowe & Weisner, 2004). Although subsidy programs reduce cost constraints, they do not reduce other constraints that may also lead low-income parents to use multiple arrangements, such as employment constraints. Prior research suggests that working variable or nonstandard schedules increase parents’ need for multiple arrangements due to inflexible and

ACCEPTED MANUSCRIPT standard, daytime schedules in the formal child care market (Chaudry, 2004; Henly & Lambert, 2005; Lowe & Weisner, 2004; Scott et al., 2005). For these parents, increasing child care subsidy program generosity may allow them to access otherwise unaffordable center-based care, but they may need to supplement center-based care with informal, home-based care in order accommodate their

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work schedules. This is consistent with suggestive findings from this study that subsidy program generosity is not associated with

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parents’ decisions to use multiple home- and center-based arrangements.

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This study used total state subsidy program spending per poor child under age 6 as a measure of overall subsidy program

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generosity. This measure has commonly been used in prior studies that have examined the effects of state-level variation in subsidy programs on parents’ child care decisions (Greenberg, 2010; Magnuson et al., 2007; Rigby et al., 2007; Washbrook et al., 2011).

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Conceptually, this measure of generosity captures two distinct aspects of program generosity, namely program inclusiveness and the

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value of the subsidy to families; however, results from this study suggest that the findings are likely driven by more generous states

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providing higher subsidy values as most of the highest-spending states did not serve all eligible families and there was less variation in

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program inclusiveness across high- and low-spending states. Indeed, increasing the value of the subsidy may have a larger impact on parents’ child care decisions than increasing program inclusiveness by increasing parents’ access to a greater range of child care

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choices. It is also possible that specific subsidy program parameters (i.e., provider reimbursement rates) may be particularly important for parents’ decisions about the number and types of arrangements, and that higher levels of subsidy spending may reflect different combinations of subsidy program parameters depending on states’ priorities. Changes to states’ subsidy programs due to the CCDBG Reauthorization Act of 2014—such as longer eligibility periods and setting higher income eligibility limits for families who are

ACCEPTED MANUSCRIPT redetermining their assistance—have likely resulted in higher subsidy costs per child, making it difficult for states to increase or maintain access to the program for eligible families (Matthews et al., 2017). Understanding how changes due to the 2014 CCDBG reauthorization and how specific policy parameters impact parents’ child care choices are important questions for future research.

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In studies such as this one that use survey data to examine the effects of child care subsidy programs on child care choices, it is

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a challenge to identify a precise treatment group of subsidy-eligible families and comparison group of subsidy-ineligible families. This

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study uses parental level of education as a proxy for subsidy eligibility, similar to prior research (Washbrook et al., 2011), because

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parental education is highly correlated with parental employment and income but is not endogenous to subsidy program generosity.

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Nevertheless, this approach has limitations. Because parental education is an imprecise proxy for subsidy eligibility, there will

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inevitably be families in the treatment group who are ineligible for a subsidy and families in the comparison group who may be

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eligible. This measurement error would likely bias the estimates towards zero. Although results from this study were generally robust

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to alternative treatment and comparison group definitions and subgroup analyses, future research with similar, detailed measures of

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the number and type of care arrangement and using more precise treatment and comparison groups is needed to provide support for these findings.

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This study included controls for a large set of child- and family-level factors and state-level factors in order to account for differences between the treatment and comparison groups and between states that may bias estimates of the effects of subsidy spending on parents’ child care decisions. Adding interactions between state-level factors and treatment group status to the models, which allows the effects of state policies and characteristics to vary between the treatment and comparison groups, typically produces

ACCEPTED MANUSCRIPT larger and statistically significant estimates of the effects of subsidy spending. Nevertheless, the difference-in-difference estimates may still be biased by unobserved state-level factors that influence parents’ child-care decisions and that differentially affect the treatment and comparison groups, and these estimates should be interpreted as associations. Although the models control for the state-

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level unemployment rate and union coverage rate, it is possible that there are other labor market differences between states that may

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be related to both subsidy spending and parents’ child care decisions. For example, if states with higher levels of subsidy spending

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also have more highly-regulated low-wage labor markets, which could plausibly be associated with low-income, working families’

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child care choices, then the estimated effects of subsidy spending could be capturing the effect of low-wage labor market regulations

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and would overestimate the effects of subsidy spending. Additionally, it is possible that states with higher child care subsidy spending

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also invest more in other early care and education programs for infants and toddlers, like Early Head Start. Not controlling for Early

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Head Start spending in the models may overestimate the relationship between child care subsidy spending and child care choices;

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however, because only about 7% of eligible children ages 0-3 are served by Early Head Start (Cosse, 2017), it seems unlikely that

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omitting this variable would substantively change the findings from this study. Findings from this study have several implications for child care subsidy programs and parental child care decision-making.

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This study adds to the considerable evidence that the high cost of center-based care is prohibitive to families with limited economic resources and that subsidizing the cost of care increases these families’ access to center-based programs. A novel finding from this study is that cost constraints may be important factor in how low-income families, make decisions about the number and types of arrangements to use for their young children. Findings suggest that reducing child care cost constraints through more generous subsidy

ACCEPTED MANUSCRIPT programs increases the probability that low-income families will use a single center-based arrangement and reduces parents’ need to rely on multiple care providers. In particular, the unaffordability of care may be an important reason as to why low-income families use multiple home-based arrangements. Finally, this study suggests that future research on child care subsidy programs should

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consider parents’ decisions about both the number and type(s) of arrangements.

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ACCEPTED MANUSCRIPT References Adams, G., & Rohacek, M. (2002). More than a work support?: Issues around integrating child development goals into the child care subsidy system. Early Childhood Research Quarterly, 17(4), 418–440.

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Bainbridge, J., Meyers, M. K., & Waldfogel, J. (2003). Child care policy reform and the

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employment of single mothers. Social Science Quarterly, 84(4), 771–791.

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ACCEPTED MANUSCRIPT Table 1. Number and type of child care arrangements by treatment and comparison groups Low-educated HHs

Higher-educated HHs

Parent Care Single Home Single Center Multiple Multiple, Home-based

% 54.9 28.5 8.2 8.4 6.7

N 3,750 1,950 550 650 500

Multiple, Home-based and center-based

1.8

150

% 47.5 30.4 12.4 9.7 6.8

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2.8

Sig.

N 5,750 3,800 1,350 1,150 800

*** + *** *

350

**

N 6,900 12,000 Note. Analyses are weighted. Sig. column indicates statistically significant differences between low-educated and higher-educated households.

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+p<.10; *p<.05; **p<.01; ***p<.001

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ACCEPTED MANUSCRIPT Table 2. Sample characteristics by treatment and comparison groups

Child Characteristics: Child age (months) Child male gender Low birth weight Maternal characteristics: Mother's age at child's birth (years) Mother race and ethnicity Non-Hispanic white Non-Hispanic black Hispanic Other race or ethnicity Marital status Married Cohabiting Single (living without a partner) Worked in 12 months prior to birth Used WIC during pregnancy Received welfare in childhood Mothers' child care priorities Special training Small number in group Speaks English with child Cares for child when sick Close to home Reasonable cost

Higher-educated HHs Mean(SD) or %

17.6 (7.0) 51.5 8.7

17.5 (7.2) 51.2 6.5

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***

29.3 (5.6)

***

69.7 9.5 13.9 6.9

*** *** *** ***

43.6 21.7 34.7 61.3 68.4 16.3

83.0 8.5 8.5 78.3 23.3 7.4

*** *** *** *** *** ***

89.5 70.8 75.6 81.9 67.0 75.0

87.4 81.3 76.6 58.9 58.7 58.0

+ ***

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37.9 20.7 37.3 4.1

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24.3 (5.7)

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Household Characteristics:

Low-educated HHs Mean(SD) or %

Sig.

*** *** ***

ACCEPTED MANUSCRIPT Number of children ages 0-5 Number of children ages 6-17 Number of non-parental adults Urbanicity Urbanized area (population 50,000+) Urban cluster (population 2,500-49,999) Rural (population <2,500)

1.62 (.74) .76 (1.0) .63 (.99)

1.58 (.68) .46 (.83) .22 (.64)

* *** ***

70.0 13.3 16.7

75.5 11.2 13.3

*** + **

N

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6,900

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12,000

Note. Analyses are weighted. HHs=households. Low-educated HHs=Parents' highest level of education is high school degree or lower; Highereducated HHs=Parents' highest level of education is some college or higher. Sig. column indicates statistically significant differences between low-educated and higher-educated households. +p<.10; *p<.05; **p<.01; ***p<.001

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Table 3. State-level child care subsidy spending (US $) Mean (SD) FY2001 (Wave 1) FY2003 (Wave 2)

Median

Range

10th percentile

90th percentile

2496

(1347)

2127

725-7113

1164

4123

2576

(1361)

2280

970-6864

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Source. Center for Law and Social Policy (2008); KIDS COUNT Data Center (2014) Note. N=46 states. Four states excluded from the sample are: DE, DC, NH, VT, and WV. State-level subsidy spending is defined as the total amount of state spending on child care subsidy program divided by the total number of poor children in the state. Units are in 2003 U.S. dollars.

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ACCEPTED MANUSCRIPT Table 4. Multinomial logistic regression models predicting the number and type of child care arrangements Contrast category= Multiple arrangements Model CC Subsidy Spending Low-educated HH Low-edu. x Spending

Parent 1

Parent 2

Parent 3

Single Home 1

Single Home 2

Single Home 3

0.938 (0.054) 1.425 (0.312) 1.060 (0.079)

0.897 (0.062) 1.468+ (0.316) 1.047 (0.077)

0.885 (0.073) 0.682 (0.527) 1.130 (0.167)

0.946 (0.071) 0.997 (0.217) 1.095 (0.081)

0.929 (0.081) 1.055 (0.223) 1.070 (0.077)

0.885 (0.086) 0.458 (0.335) 1.272 (0.186)

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Single Ctr. 1 0.784** (0.070) 0.653+ (0.155) 1.241* (0.103)

Single Ctr. 2

Single Ctr. 3

0.953 (0.103) 0.617* (0.141) 1.261** (0.099)

0.860 (0.104) 0.931 (0.836) 1.856*** (0.280)

Note. N=18,900. Relative risk ratios (exponentiated coefficients) and standard errors are shown. Analyses are weighted. Model 1 includes child and family controls only; Model 2 adds state-level controls to Model 1; Model 3 adds interactions between the treatment group and a select group of state-level controls to Model 2. Low-educated HHs=Parents' highest level of education is high school degree or lower; Higher-educated HHs=Parents' highest level of education is some college or higher. CC= Child-care; Low-edu.=Low-educated; HH=Household; Ctr=Center; Unemp=Unemployment. +p<.10; *p<.05; **p<.01; ***p<.001

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ACCEPTED MANUSCRIPT Figure 1. Adjusted Predictions for Low-Educated and Higher-Educated Households by Level of Subsidy Spending

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Note. Adjusted predictions and 95% confidence intervals from Model 3 are shown. Graphs are not all on the same scale. Low-edu. HHs=Low-educated households; Higher-edu. HHs=Higher-educated households; Arr.=arrangements

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Note. Adjusted predictions and 95% confidence intervals from Model 3 are shown. Graphs are not all on the same scale. Low-edu. HHs=Low-educated households; Higher-edu. HHs=Higher-educated households; Arr.=arrangements

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ACCEPTED MANUSCRIPT Figure 3. Adjusted Predictions for Low-Educated and Higher-Educated Households at 10th and 90th Percentiles of Child Care Subsidy Spending 0.70 0.59***

0.60 0.50 0.48

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Note. Adjusted predictions and 95% confidence intervals from Model 3 are shown. Statistically significant differences between low- and higher-educated households at the 10th or 90th percentile of spending are indicated next to the estimate for low-educated households. Low-edu. HHs=Low-educated households; Higher-edu. HHs=Higher-educated households; Arr.=arrangements. +p<.10; *p<.05; **p<.01; ***p<.001

ACCEPTED MANUSCRIPT Highlights for “Child Care Subsidy Programs and Child Care Choices: Effects on the Number and Type of Arrangements” Subsidy program spending was associated with number and type of arrangements

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Subsidy spending predicted a higher likelihood of a single center arrangement

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Subsidy spending predicted a lower likelihood of multiple arrangements

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