Economic Incentives and Foster Child Adoption
Laura Argysa and Brian Duncana,*
a
Department of Economics, University of Colorado Denver, Campus Box 181, Denver,
CO 80217-3364, USA
Abstract
Every year a large number of children enter the foster-care system, many of whom are
eventually reunited with their biological parents or quickly adopted. However, a
significant number face long-term foster care, some of whom are eventually adopted by
their foster parents. A foster parent’s decision to adopt his or her foster child carries
significant economic consequences—forfeiting foster-care payments and assuming
responsibility for medical, legal, and educational expenses, to name a few. Since 1980,
states began to offer adoption subsidies to offset some of these expenses, significantly
lowering the cost of adoption from foster care. This article presents empirical evidence
of the role that these economic incentives play in a foster parent’s decision of when, or if,
to adopt his or her foster child. We find adoption subsidies increase adoptions through
two distinct price mechanisms: by lowering the absolute cost of adoption, and by
lowering the relative cost of adoption versus long term foster care.
Keywords: Adoption; Foster care; Child care; Child welfare.
JEL Classification: J130, I380.
*
Corresponding author. Tel.: (303) 315-2041
E-mail address: [email protected] (B. Duncan).
This study was funded by The National Institute of Child Health and Human Development (1 R03
HD049867-02). We would like to thank Christopher Clark for his excellent research assistance.
1
In 2008, there were approximately 463,000 children in the U.S. foster-care
system; with 273,000 of them entering in this year alone.1 Many of the children entering
foster care are reunited with their biological parents or are quickly adopted. However, a
significant number face long-term foster care. For these children, being adopted by their
foster parents represents their best chance of leaving the foster-care system.
Unfortunately, only 54,284 foster children were legally adopted in 2008, while 123,000
were waiting to be adopted.2 On average, these children have been waiting to be adopted
for nearly four years. Although the adoption rates for boys and girls are similar, the
adoption rate among black children is significantly lower than it is among white children.
Adoption rates are also significantly lower for older children, those placed with single
foster parents, and those placed with relatives.
A foster parent’s decision to adopt his or her foster child carries significant
economic consequences—forfeiting foster-care payments and assuming responsibility for
medical and educational expenses, to name a few. Recently states have offset, at least in
part, these economic consequences by offering adoption subsidies and credits for
adoption-related expenses. This effort began in 1980 with the passage of the Adoption
Assistance and Child Welfare Act (AACWA, P.L. 96-272) aimed at reducing the length
of stay in foster care and promoting adoptions. This act requires states to provide
adoption assistant payments to families who adopt children with special needs. Although
the AACWA provides an outline for the definition of special needs (including children
with a diagnosed disability, children in a sibling group, minority children, and older
children), the details of the adoption assistant program, and payment amounts, are left up
1
U.S. Department of Health and Human Services, Children’s Bureau. 2009. The AFCARS Report:
Preliminary FY 2008 Estimates as of October 2009 (16).
2
The U.S. Department of Health and Human Services, Children’s Bureau, defines children waiting to be
adopted as those whose parents’ rights have been terminated and/or with a stated case goal of adoption.
2
to the state. As a result, some states began to offer adoption assistance payments equal to
what the foster-care payments would have been if the child was not adopted, while others
offered a lower payment to adoptive parents than to foster parents. In all cases, these
state policies significantly lowered the cost of adopting a foster child, and provide us an
opportunity to study the impact that economic incentives have on family decisions.3
Because many of the specifics of a state’s adoption assistance program are under
the control of state and local governments, policymakers have the potential to alter the
probability and timing of the adoption of foster children. Ideally, we would like to
analyze foster-care adoptions before and after states enacted adoption subsidies in 1980
and before and after the passage of the Adoption and Safe Families Act of 1997.
Unfortunately, reliable data on large numbers of foster children does not exist for years
prior to 1998. Instead, we use data from the 1998 and 2006 Adoption and Foster Care
Analysis and Reporting System (AFCARS) to analyze the role that economic incentives,
in the form of foster-care and adoption subsidies, play in a foster parent’s decision to
adopt his or her foster child. The AFCARS foster-care data contain micro-level data on
children in the foster-care system, including information such as the child’s age, gender,
ethnicity, case goal, reason for removal, special needs status, length of stay, the
termination of parents rights and time of adoption. The data also contains information
about the foster caregivers.4 We link the AFCARS data on individual children to state
foster-care and adoption subsidy rates by the child’s age and state of residence to
3
Previous studies have found that economic incentives alter family decisions such as fertility (Grogger and
Bronars, 2001; Acs, 1996; and Kearney, 2004), unwed births (Hoffman and Foster, 2000), and abortions
(Argys, Averett, and Rees, 2000).
4
The AFCARS data contains information about the foster parents' age, race/ethnicity, marital status, and
whether they are related to the foster child. Unfortunately, the data does not contain any additional
demographic information about the foster parents, such as income, education, or number of children
(including other foster children) in the household.
3
examine the effects of these policies on the adoption rates of children waiting to be
adopted.
A standard cross-sectional estimation approach would not be appropriate if statelevel foster-care and adoption policies reflect differences in attitudes towards children in
general or towards foster care and adoption specifically. To address this possibility, we
control for unobserved differences between states and between children of different ages
by exploiting the variation in basic monthly foster-care and adoption payments within
each state-age group over time. For example, many states made significant changes in
the structure of their foster-care and adoption subsidies between 1998 and 2006. These
changes affected both the overall level of foster-care and adoption payments, and the
difference between the two payments. Furthermore, within individual states, the
magnitude of these changes often depended on the age of the child. Our analysis uses the
variation in payments over time within each age group in each state to identify the effect
that lowering the cost of adoption has on a parent’s decision to adopt a foster child. We
find that adoption subsidies significantly increase the adoption rate of children waiting to
be adopted. Specifically, we find that parents respond to both the level of payments and
to the difference between the foster-care and adoption payments in predictable ways. For
example, logit model estimates suggest that, holding constant foster-care payments, a
$100 increase in adoption payments is associated with a 4.6-percentage point increase in
the adoption rate of boys, and a 5.9-percentage point increase in the adoption rate of girls.
These percentage point increases translate to an increase in the overall adoption rate of
27-percent for boys and 34-percent for girls over the 1998 rate. Moreover, increasing the
generosity of payments by increasing both foster-care and adoption payments by $100 is
associated with a 3.7-percentage point increase in the adoption rate of boys and a 6.2percentage point increase for girls. This corresponds to an increase in the overall
4
adoption rate of 17-percent for boys and 35-percent for girls over the 1998 rate. These
findings are consistent with the theory that lowering the cost of adoption increases the
number of adoptive parents through two mechanisms. First, increasing the generosity of
payments attracts more family foster care providers to the child welfare system. Second,
lowering the cost of adoption relative to the cost of foster care encourages more parents
to choose adoption over long-term foster care.
ADOPTION FROM FOSTER CARE
To address the needs of foster children, legal scholars and policy makers have
debated priorities in foster-care policies for the past three decades (Guggenheim, 1999).
The Adoption Assistance and Child Welfare Act of 1980 addressed some of these
concerns by providing federal guidelines for state child welfare agencies by mandating
that foster care be the option of last resort and that all “reasonable efforts” be made to
preserve or reunify the family (Lowery, 2000). The Act also established the adoption
assistance program designed to subsidize adoptions of special needs children. The 1980s
and 1990s saw a dramatic increase in both the number of children in foster care and the
average time children spent in foster care. A shift in foster-care philosophy came with
the passage of the Adoption and Safe Families Act of 1997, which replaced the
“reasonable efforts” requirement with a “fast track” to permanency requirement. The
1997 legislation expedited the termination of parent’s rights and mandated that states
move children toward adoption after a relatively brief period of time, shifting some of the
emphasis away from providing services to families in crisis and working toward
reunification (Pagano, 1999). The legislation also provided new financial incentives for
states to increase adoption rates above targeted levels.
Whether the goal is reunification or adoption, most observers agree that long-term
foster care is detrimental to the child. Policymakers and professionals dedicated to
5
ensuring a developmentally beneficial environment for foster children point to the need to
avoid foster-care “drift” that occurs when children are frequently moved from one fostercare setting to another. The American Association of Pediatrics released a statement
indicating that “[m]ultiple foster home placements can be injurious” to children (USA
Today, 2001). Child development researchers suggest that multiple placements result in
unstable adult-child relationships that deplete a child’s ability to form attachments to
significant others (Usher, Randolph and Gogan, 1999) and so the focus on adoption of
children out of foster care has intensified.
In keeping with the consensus that long-term foster care should be avoided, the
goal of current policy is to move foster children into the permanence of adoption if
reunification with the biological family cannot be achieved quickly. However, largescale research designed to identify factors associated with adoption and its timing has
only been conducted in the past few decades. For example, Finch et al. (1986) found that
only one-quarter of the children placed in out-of-home care in New York in the late
1970s and identified as available for adoption were adopted within two years. Their
findings, which are consistent with other studies conducted more recently in other states,
suggest that the probability of adoption is related to the child’s race and ethnicity. Finch
et al. also find that the probability of adoption declines with time spent in out-of-home
care. This is similar to the finding that adoption is most likely for younger children
(Barth, 1997).
It has been established that not only are children of color a larger proportion of
the out-of-home care population than of the population at large, but that they face a lower
probability of adoption than white children (Finch et al., 1986; Wulczyn and George,
1992; Courtney and Barth, 1996; Barth, 1997; Brooks and James, 2003). Specifically,
Finch et al. (1986) estimated that white children are nearly 11% more likely to be adopted
6
than children in other racial and ethnic groups, although the racial gap in adoptions may
be closing (Wulzyn, 2003). Concern about the overrepresentation of children of color
among the foster-care population, and low rates of adoption for these children prompted
the passage of Multiethnic Placement Act of 1994 and the Interethnic Adoption
Provisions of 1996 to remove barriers to interracial adoption and to move more quickly to
permanent families for children of color (Brooks et al., 1999).
The call to move children from temporary foster care to the permanence of
adoption is clear; however, the mechanism by which this goal might be achieved is not.
Research suggesting that the probability of adoption varies by race, ethnicity, age and
time in foster care provides policymakers with little insight into how to increase adoption.
Few studies have been conducted to identify factors that provide policymakers with the
leverage to alter the probability and timing of the transition from foster care to adoption.
In a report based on evaluation of the child welfare system in Washington state,
Thompson et al. (2001, p.13) suggest that “… an increase in the state adoption subsidy
ha[s] resulted in a substantial increase in foster family adoptions.” Although it is clear
that policymakers recognize that goals may be more easily achieved when “government
aligns financial incentives with the outcomes it hopes to achieve” (McDonald, et al.,
2003, p. 2) no large-scale national studies of the effect of these subsidies on adoption
have been conducted.
Previous studies have examined the impact of foster-care subsidies on placement
within the foster-care system. They found that more generous foster-care payments
increase the overall supply of foster-care providers (Doyle and Peters, 2007 and Simon,
1975), improves the retention of foster families (Chamberlain, Mooreland and Reid,
1992), increases kin placements (Doyle, 2007) and increases the probability of placement
with a foster-family rather than in a group setting (Duncan and Argys, 2007).
7
A few studies have addressed the impact of state subsidies on adoptions. Avery
and Mont (1992) collected data from counties in New York to identify the impact of
subsidy levels on the timing and probability of adoption of children with special needs.
They found that children with mental disabilities who qualified for greater adoption
subsidies (based both on their own characteristics and practices within their county of
residence) faced a greater probability of adoption. Their results also suggest that
subsidies have no effect on adoption for other special needs children. Hansen and
Hansen (2006) used aggregate data from the 1996 AFCARS to conduct cross-sectional
analysis of the association between a state’s monthly adoption assistance payments and
the number of children adopted out of foster care per 100,000 state populations. They
found a positive association between the monthly adoption subsidy for nine year-olds and
the total number of children adopted out of state foster care. Hansen (2007) extends her
previous work to include data from the 1996 to 2003 AFCARS. Her state fixed effects
estimates confirm her earlier findings that state assistant payments are positively
associated with adoptions of foster children. Finally, Buckles (2009) examines the
impact of adoption subsidies on the likelihood of adoption by exploiting variation
between states in the age at which children qualify for adoption assistance. Buckles
tracks individual children in the 2000-2006 AFCARS based on the child's state, date of
birth, and date of removal, allowing her to estimate the time-to-adoption in a hazard
model framework. She finds that the likelihood of adoption increases as children become
eligible for adoption subsidies. Moreover, she finds that adoption subsidies have a larger
impact on the likelihood that a child is adopted by an older relative. Both of these results
are consistent with our findings.
THEORETICAL FRAMEWORK
8
From the state child welfare agency’s point of view, adoption—because it
removes the child from the foster-care system and provides a more stable environment—
is more desirable than long term foster care. We assume this point of view even though
the foster-care agency may lose its maintenance payment when the child is adopted.
From the parent and child’s point of view, adoption may be emotionally and
psychologically desirable (Mulligan, 2003). However, parents take on increased
financial and legal responsibilities when they adopt, and they must weigh these factors
against the potential benefits of adoption.5
For the purposes of this study, we assume that parents act as rational agents with
preferences that value their own consumption and the overall well-being of their foster
child. This implies that a foster parent will consider both the emotional and financial
impacts that an adoption will have on the foster child’s well-being and home
environment. Many financial benefits and obligations are altered when a foster child is
legally adopted. For instance, although basic expenditures for food, clothing and other
provisions for the child are made by parents regardless of whether or not the child is
adopted, foster parents do receive a basic monthly subsidy for providing care for the
foster child. In many states, adoptive parents will receive a reduced monthly subsidy
when they adopt their foster child (Barth, 1997). There are also legal costs of adoption,
although some states have implemented one-time adoption transfers to help offset these
legal expenses. Furthermore, adoptive parents may become financially responsible for
the child’s future medical expenses, and may be liable for any legal costs or damages
caused by the actions of the child.
5
In addition to long-term foster care, other possible outcomes for parents who fail to adopt their foster
child include the child welfare agency removing the child to place in a pre-adoptive home, or the child
running away.
9
In light of this, foster parents must weigh the benefits to the child and to
themselves that come from adoption against the increased risk and financial obligations.
We do, however, assume a downward sloping demand for adoptions, meaning that, all
else equal, a parent will be more likely to adopt a foster child as the cost of adoption goes
down. Although there are many components to the cost of adoption, the specific
components that we study in this paper are the monthly foster-care subsidy and the
monthly adoption subsidy. Before 1980, foster parents typically forfeited their monthly
foster-care payments entirely when they adopted their foster child. After the Adoption
Assistance and Child Welfare Act of 1980, states began to provide a monthly adoption
subsidy, effectively lowering the cost of adoption.
Calculating exactly how much the adoption subsidy lowers the cost of adoption is
complicated by the nature of adoptions and by the structure of foster-care and adoption
payments. At any point in time, the adoption decision faced by foster parents is a
dichotomous one, either to continue with the permanent foster care arrangement or to
legally adopt the child. However, the timing of the adoption is not dichotomous. In
many states, both foster-care payments and adoption payments vary by the age of the
child. Other states pay a flat rate regardless of the age of the child. Moreover, some
states match their adoption subsidies to their foster-care payments, where other states set
their adoption subsidies below the foster-care payments. Our analyses address the
following questions: (i) do parents weigh current benefits against current costs, or are
they more forward looking? and (ii) do parents respond to the size of adoption payments
or to the difference between adoption and foster-care payments, or to both?
DATA
Our primary data are from the 1998 and 2006 Adoption and Foster Care Analysis
and Reporting System (AFCARS), which contains basic information on all children in
10
foster care in 43 states.6 Although AFCARS began in 1995, it was not until 1998 that
states faced financial penalties for failure to submit AFCARS data. Thus, the 1998
AFCARS is unique, not only because it is the first year in which we have data on large
numbers of foster children, but also because it comes on the heels of the Adoption and
Safe Families Act of 1997. We utilize the 2006 AFCARS data for two reasons. First,
many states altered their adoption payments in the intervening eight years and our longdifference estimation captures changes in this relatively slow-moving process. Second,
as described in the following paragraph, information is available in both 1998 and 2006
on the monthly state foster-care and adoption maintenance payments for children of all
ages in each states. From these data sets, we extract all children between the ages of 4
and 16 years of age who were eligible for adoption in the fiscal years 1998 and 2006.7
Following AFCARS guidelines, we consider a child to be eligible for adoption if both
parents’ rights have been terminated, or if the child’s stated case goal is adoption. Our
primary goal is to understand the factors that influence a foster parent’s decision to adopt
his or her foster child, and so we exclude children who are in supervised independent
living, participating in trial home visits with their parents, in group homes or institutions,
or who have run away. Only a small percentage of foster children eligible for adoption
fall into these placement settings, and many of the records for these children contain
incomplete information. Children in an additional fifteen states were dropped because
the state failed to report key information in 1998, such as the year the child entered foster
care, or because the state does not set a basic monthly foster-care payment.8 A small
6
Kentuckey, Massachusetts, Nebraska, Nevada, New Hampshire, Ohio, South Dakota, and Tennessee are
not included in the 1998 AFCARS data.
7
We exclude children under 4 because in many states they may not qualify as special needs and, therefore,
would not be eligible for the adoption subsidy.
8
Children in Colorado, Indiana, Kansas, New York, and Pennsylvania are excluded because a basic
monthly subsidy rate is not set by the state. Children in Alabama, Alaska, Arizona, Arkansas, Delaware,
11
number of additional children were excluded due to missing or impossible age entering
foster care, gender, or race. The resulting sample includes 118,452 children (60,038 boys
and 58,414 girls) living in 29 states in 1998 and 2006.
Although the AFCARS data identifies the state in which the child resides, it
contains no information about state policy. Therefore, to measure the effect of economic
incentives on the adoption rates of foster children, we link the child-level AFCARS data
with measures of the basic monthly foster-care and adoption subsidy rates by the child’s
state, age and year. We obtained this data from a variety of sources, including the Child
Welfare League of America, the North American Council on Adoptable Children, state
statues and publications, and direct contact with state employees. These subsidy rates are
basic minimum guidelines which can be supplemented depending on the child’s needs.
They do not include any special subsidies for care by relatives or adoption-related
expenses. By 1998, every state had some form of adoption subsidy program. Some
states simply match their adoption subsidy payments to their foster-care payments. In
these states, foster parents will generally receive the same monthly payment if they
choose to adopt their foster child, provided that the child meets the state definition of
special needs. However, several states negotiate adoption payments with prospective
adoptive parents under the condition that the adoption subsidy cannot exceed the fostercare payment. In other states, foster parents could, according to the basic guidelines,
forgo up to $302 in 1998 or $343 in 2006 per month in basic foster-care payments by
adopting their foster child. This difference varies by state, year, and child’s age.
Figure 1 shows the average monthly foster-care payments and adoption subsidies
across all of the states in our sample in 1998 and 2006, by the child’s age. Payments in
District of Columbia, Florida, Michigan, and New Mexico are excluded because of missing data in the
1998 AFCARS data.
12
1998 have been converted into 2006 dollars using the Consumer Price Index for All
Urban Consumers (CPI-U). As can be seen in Figure 1, states typically designate age
ranges and pay one monthly subsidy for children under the age of 5 or 6, another, usually
higher rate for children between the ages of about 6 and 12, and a higher rate yet for
children over the age of 11 or 12. However, not all states increase their payments with
age. Comparing the 1998 rates to the 2006 rates, it appears that average foster-care
payments kept pace with inflation. In contrast, average adoption payments, in real terms,
fell between 1998 and 2006, widening the gap between foster-care and adoption
payments.
The averages shown in Figure 1 obscure a significant amount of policy variation
between states. Some examples of this variation can be seen in Figure 2, which shows
the 1998 and 2006 monthly foster-care and adoption payments in six selected states.
Some states, like California, set the adoption payment equal to the foster-care payment,
indexing both to inflation. Eight additional states set the adoption payment equal to the
foster-care payment in both 1998 and 2006, but unlike California, adjusted the overall
level of these rates either up or down. Other states reformed the value their adoption
payments relative to foster-care payments between 1998 and 2006. Some of these
reforms were modest, like in Connecticut, where real payments were equal in 1998, but
both were reduced across the board by 2006 (although adoption subsidies were reduced
more than foster-care payments), or South Carolina where real payments started off
equal, but were increased across the board (although foster-care payments were increased
more than adoption payments). Others, like Georgia, moved from a system of equal
payments for all children, to the more common system that pays different amounts based
on the age of the child, with lower payments for adopted children. In all, 14 states in our
sample in 1998 matched their adoption payments to their forester care payment, with five
13
of these states offering different rates by 2006. Although most states lowered adoption
subsidies relative to the foster-care payments between 1998 and 2006, others, like New
Jersey, increased adoption subsidies relative to foster-care payments. In the empirical
analysis below, we exploit the within state variation in payments over time to examine
the effect that both the level of foster-care and adoption payments and the difference
between two has on the adoption rate of eligible children.
Basic Patterns
Table 1 lists the characteristics of children eligible for adoption in 1998 and 2006,
by the child’s gender. Table 2 lists the percent of these eligible children that were
adopted out of foster care in 1998 and 2006. In both years, there are nearly an equal
number of boys and girls waiting to be adopted, and the adoption rates for boys and girls
are similar. However, there was a significant increase in the adoption rate overall
between 1998 and 2006. The adoption rate grew from little more than 17-percent of
eligible children in 1998 to over 29-percent in 2006. The adoption rate is lower for older
children than for younger ones, falling to about 14-percent for children aged 12 to 16 in
1998 and 21-percent in 2006. Black children are overrepresented among children waiting
to be adopted in both 1998 and 2006, although the gap is smaller in 2006. In fact, in
1998 over half of the children waiting to be adopted were black (56-percent of boys and
54-percent of girls). By 2006, this number had fallen to less than a third (30-percent of
boys and 28-percent of girls). The adoption rate among black children at about 15percent for both boys and girls in 1998 and about 26-percent in 2006 contributes to this
overrepresentation. At about 21-percent for both boys and girls in 1998 and 32-percent
in 2006, a white child was nearly 1.4 times as likely in 1998 and 1.2 times as likely in
2006 to be adopted out of foster care as was a black child.
14
A foster child is considered disabled in the AFCARS data if he or she has a
diagnosed disability including mental retardation, visual/hearing impairment, physical
disability, emotional disability, and other diagnosed disability. The disability rate among
children eligible for adoption was 25-percent for boys and 20-percent for girls in 1998.
The number of foster children identified with a diagnosed disability increased sharply in
2006 to 41-percent for boys and 34-percent for girls. Whereas disabled children had
higher than average adoption rates in 1998, they had lower than average adoption rates in
2006.
Certain children may be less suited for adoption because of difficult to measure
characteristics of the child. To capture some of these characteristics, we construct a
dichotomous variable equal to one if the child’s behavior or condition was listed as a
reason for removal from his or her home. Child-related reasons for removal include child
alcohol or drug addiction, child disability, and child behavior problems. In 1998,
approximately 12 percent of boys and 11 percent girls report a child reason for removal.
These percentages grew slightly in 2006 to 14-percent of boys and 12-percent girls. The
adoption rate among this group is close to the overall rate in 1998, but is lower than the
overall average in 2006.
Table 3 lists the characteristics of the foster parents of children eligible for
adoption in 1998 and 2006, by the child’s gender, and Table 4 lists the adoption rates of
these children. In 1998, black parents, older parents, single parents and parents who are
related to their foster child are the least likely to adopt. For example, 1998 the adoption
rate was 7-percent among black foster parents, 9-percent among foster parents over the
age of 51, 4-percent among foster parents related to the foster child, and 8-percent among
single female foster parents. These patterns suggest a possible explanation for the low
adoption rate among black children. Black children are more likely to be placed with
15
black foster parents, with single foster parents, and with relatives, all of whom have
lower adoption rates. For instance, in our 1998 sample, 74-percent of black boys are
placed with a single foster parent; whereas, this number is only 41-percent for white
boys. Also in 1998, 30-percent of black boys, and 12-percent of white boys, were placed
with a relative.
METHODS
Although informative, the basic patterns described in Section 5 do not answer the
underlying question of how the level of, and difference between, state foster-care and
adoption payments influence adoption rates. To answer this question, we begin by
estimating univariate logit regressions separately for boys and girls taking the form9:
29
13
Adoptktji     X ktji   1 AD ktj   2 FC ktj    kj   t   ktji ,
(1)
k 1 j 1
where Adoptktji is a dichotomous variable equal to one if child i of age j in state k at year
t is adopted in fiscal year t, and zero otherwise. The vector X ktji represents a set of
control variables, including child characteristics, such as the child’s race/ethnicity,
months spent in foster care, disability status, and reason for removal; as well as parent
characteristics, such as the foster parent’s marital status, age, race/ethnicity, and
relationship to the foster child. The basic monthly adoption subsidy and foster-care rates,
ADktj and FCktj , are measured in hundreds of dollars for children of age j living in state
k in year t, respectively. Note that these variables are subscripted by k, t and j because
basic foster-care and adoption subsidies vary by state, year, and child’s age. However,
9
Although the adoption rates are similar among boys and girls, we are nevertheless concerned that
lowering the cost of adoption, as well as other demographic controls, may have different influences on the
adoption rates of boys and girls.
16
they are not subscripted by i because basic state payments do not vary among children
who are the same age and live in the same state in the same year.
The parameters  kj in (1) are 377 state-age fixed effects (13 age categories in 29
states) capturing the influence of any state and/or age specific factors that are unobserved
but do not change over time. The advantage of (1) is that the relationship between
payments and adoption rates are identified using only the variation observed within a
state-age group.10 That is, nine-year-olds in Connecticut in 1998 are compared to nineyear-olds in Connecticut in 2006, but not to any other group of children either in
Connecticut or in any other state. Another advantage of this level of fixed effect is that it
corresponds to the level at which states set their foster-care and adoption payments.
Estimating the effects of aggregate policy variables on micro data can lead to standard
errors that are biased downwards (Moulton, 1990). As a result, we correct the standard
errors for clustering at the state-age group level in all of our logit regressions (Bertrand,
Duflo and Mullainathan, 2004).11
The interpretation of  1 in (1) is the marginal effect of increasing the adoption
subsidy, holding constant foster-care payments. This is equivalent to increasing the
difference between the adoption subsidy and foster-care payment, which reflects the
amount a foster parent must give up to adopt his or her foster child. From a financial
point of view, this is an important calculation for a foster parent, because it represents the
10
An intermediate step would be to simply include twenty-nine state fixed effects and thirteen age fixed
effects in (1). State fixed effects regressions produce similar estimates to the state-age fixed effects
regressions reported in this paper (see footnote 15).
11
Our policy of interest varies at the state-age level, and so we include state-age fixed effects and cluster
the standard errors at the state-age level. As a robustness check, we also estimate models with state-age
fixed effects, but with standard errors clustered at the state level. For both boys and girls, clustering at the
state level approximately doubles the standard errors reported here. When clustered at the state level, the
“difference in payments” marginal effects remain statistically significant, but the “generosity of payments”
marginal effects become statistically insignificant.
17
cost of becoming an adoptive parent compared to continuing as a foster parent.12
Increasing the adoption payment while holding constant the foster-care payment
incentivizes adoptions over long term foster care, and so we expect  1 to be positive.
However, for individuals who are considering becoming a foster parent, the overall level
of payments, rather than the difference between the two payments, may be the relevant
calculation. The effect of increasing the level of adoption payments, holding constant the
difference in payments, is captured in (1) by  1   2 . This reflects the overall generosity
of the state child welfare system. In theory, simultaneously increasing the generosity of
foster-care and adoption payments could increase or decrease the adoption rate. On one
hand, it lowers the cost of becoming an adoptive parent. On the other hand, it lowers the
cost of becoming a long-term foster parent. In effect, increasing the generosity of
payments can attract more individuals planning to be adoptive parents, but it can also
attract more individuals planning to be long-term foster parents. Presumably, state child
welfare agencies are able to sort this out and identify which parents are more likely to
become adoptive parents. If so, we would expect  1   2 to be positive, but this is
ultimately an empirical question.
In order to calculate how the level of, and difference between, state foster-care
and adoption payments are associated with adoption rates directly, we estimate a
mathematically equivalent version of (1) in the form:
29
13
Adoptktji    X ktji   3 ( ADktj  FC ktj )   4 FC ktj    kj   t   ktji , (2)
k 1 j 1
12
If parents are forward looking, then it may not be current payments that matter, but the value of all future
payments. To investigate this possibility, we estimated additional regressions that include the net present
value of basic foster care and adoption subsidies in place of the monthly rates. These regressions yield
similar results as those reported in this article, which is not surprising given that the present values and the
monthly rates are highly correlated and that state-age fixed effects are included in the regressions.
18
where  3   1 captures the effect of changing the difference in payments, and
 4   1   2 captures the effect of changing the overall generosity of payments.
FINDINGS
Marginal Effects
Table 5 lists our estimates of (2) separately for boys and girls, with the logit
coefficients converted into average marginal effects so that they can be compared directly
with the summary statistics given in Tables 2 and 4.13 The average marginal effects
labeled as "difference in payments" measure the association between a $100 increase in
basic monthly adoption subsidy, holding constant foster-care payments, and the adoption
rate (  1 ). The average marginal effects labeled as "generosity of payments" measure the
association between a $100 increase in both the foster-care and adoption payments and
the adoption rate (  1   2 ). Increasing the adoption payments by $100 a month, holding
constant foster-care payments, is associated with a 4.6-percentage point increase in the
adoption rate of boys, and a 5.9-percentage point increase in the adoption rate of girls.
This corresponds to a 27-percent increase in the adoption rate for boys and a 34-percent
increase in the adoption rate of girls compared to their 1998 rates. Increasing the
generosity of payments by increasing both the adoption and foster-care payments by $100
a month is associated with a 3.7-percentage point increase in the adoption rate of boys,
and a 6.2-percentage point increase in the adoption rate of girls. This corresponds to a
17-percent increase in the adoption rate for boys and a 35-percent increase in the
adoption rate of girls compared to their 1998 rates.14 The positive effect of the
13
Ordinary least squares estimates of (2) produce nearly identical marginal effects.
As a robustness check, we estimated several alternative models that use different identification strategies.
For example, models that include state fixed effects and age fixed effects separately, rather than the stateage fixed effects models presented here, produce similar results. Specifically, the corresponding
“difference in payments” marginal effects are .040 for boys and .050 for girls. The corresponding
14
19
generosity of payments on the adoption rate is consistent with the idea that lowering the
cost of foster care and adoption will increase the number of families willing and financial
able to take in a child, making it easier for state child welfare agencies to find adoptive
homes. Moreover, the fact that increasing the adoption subsidy, holding constant fostercare payments, is associated with an increase in the adoption rate is consistent with the
idea that reducing the financial penalty associated with switching from a foster parent to
an adoptive parent will make it more likely that foster parents will adopt their foster
children.
Foster Child and Parent Characteristics
According to the summary data presented in Table 2, male black children were
6.75-percentage points (21.01 - 14.26) less likely be adopted than male white children in
1998 and 5.89-percentage points less likely to be adopted in 2006. However, the
marginal effects presented in Table 5 reveal that the racial difference in adoption
disappears when controlling for parent and child characteristics. Although we use a
different sample of foster children, this is consistent with Duncan and Argys (2008) who
find that nearly all of the difference in the adoption rates between black and white
children can be explained, not by difference in the characteristics of children, but by the
characteristics of the foster parents. In fact, a significant reason why black children have
a relatively low adoption rates is that black children are more likely to be taken in by
relatives, and relatives are less likely to adopt their foster child.
Table 5 also reveals that, controlling for other factors, disabled children are less
likely to be adopted as are children with a child reason for removal. These variables may
“generosity of payments” marginal effects are .028 for boys and .040 for girls. In addition, we estimated
models that include state-year fixed effects. These models use only the variation in payments within a
state-year by child age, and produce marginal effects that are smaller in magnitude and are not statistically
significant.
20
be a measure of difficult to place children. Months in foster care, which measures the
time since the child's most recent home removal, is also positive and statistically
significant. All three of these variables are potentially endogenous, but omitting them as
control variables from the regression does not change the coefficients on the subsidy
variables in any meaningful way.
Marginal Effects by Child and Parent Characteristics
In addition to estimating the overall effect of lowering the cost of adoption on the
adoption rate, we also estimate models that allow these effects to vary by the
characteristic of the child and foster parent. This is accomplished by estimating separate
logit regressions of (2) that include interaction terms between the specific child or parent
characteristic and the foster-care and adoption payment variables. For example, we
estimate a model that interact the difference in payment and the generosity of payment
variables with three age categories to examine if lowering the cost of adoption has
different effects on older children than on younger ones. We also estimate models that
interact the payment variables with the child’s race/ethnicity, disability status, reason for
removal, as well as with the foster parents marital status, age, race/ethnicity, and relation
to the child.15
Tables 6 and 7 presents marginal effects calculated separately for various child
and parent characteristics, respectively. All of the regressions include state-age fixed
effects and the same control variables as those presented in Table 5.
15
The resulting marginal effects reported in Table 6 and 7 can be interpreted as if they were produced from
twenty-two separate estimates of (2), one overall, and twenty-one more for each child and parent
characteristic (i.e. a regression for children aged 4-6, another for children 7-11, another for white children,
for back children, and so on). Limited by sample sizes, we actually estimated nine regressions, one overall,
and eight that include interactions with the child characteristics (age, disability, race, reason for removal) or
the foster parent characteristics (age, family structure, race, related). Each regression was estimated
separately for boys and girls.
21
The first row in Table 6 is labeled "overall" and is the same regression model that
is presented in more detail in Table 5. The remaining marginal effects reported in Table
6 suggest that lowering the cost of adoption increases the adoption rate of all children by
similar amounts, regardless of the child's observed characteristics. Possible exceptions
include the adoption rates of black girls and disabled boys. For example, a $100 increase
in the adoption subsidy, holding constant the foster-care payment, is associated with a
5.9-precentage point increase in the adoption rate of white girls and a 7.6-percentage
point increase in the adoption rate of black girls. With a t-value of 2.15, this difference is
statistically significant at the 5-percent significance level. A $100 increase in the
generosity of payments is associated with a 1.9-percentage point increase in the adoption
rate of disabled boys, but a 4.5-percentage point increase in the adoption rate of nondisabled boys. The difference is also statistically significant at the 1-percent level
(t=4.46). However, the remaining marginal effects presented in Table 6 show that
lowering the cost of adoption has fairly consistent effects across children with different
child characteristics. For example, increasing the adoption subsidy by $100, holding
constant the foster-care payment, has a slightly larger effect on girls aged 4 to 6 (6.8percentage points) than on girls aged 12 to 16 (5.1-percentage points). However, this
difference is not statistically significant. Reducing the cost of adoption has a slightly
smaller effect on troubled children than those without a child reason for removal, but
again these differences do not reach conventional levels of statistical significance.
Conversely, the marginal effects presented in Table 7 suggest that lowering the
cost of adoption affects some foster parents differently than others. Specifically,
reducing the cost of adoption has a larger effect on older foster parents, black foster
parents, and those related to the foster child. For example, $100 increase in the adoption
subsidy is associated with a 5.2-percentage point increase in the adoption rate of boys
22
placed with black foster parents, compared to a 2.9-percentage point increase in the
adoption rate of boys placed with white foster parents. The difference, 2.2, is statistically
significant at the 5-percent significant level. A similar pattern is seen for girls. The last
model in Table 7 indicates that a $100 increase in the adoption subsidy is associated with
a 15.8-percentage point and a 16.5-percentage point increase in the adoption rates of
children placed with related individuals for boys and girls, respectively. These are the
largest marginal effects we calculate for any parent or child characteristic.
CONCLUSIONS
Beginning with the Adoption Assistance and Child Welfare Act of 1980, states
began to offer adoption subsidies designed to lower the cost of adopting a child out of
foster care. Some states went so far as to offer a monthly adoption subsidy that is equal
to the child’s foster-care payment. Other states set adoption subsidies below the fostercare payment. Over the years, many states have revised their foster-care and adoption
payment rates, with some increasing or decreasing both rates overall, and others
increasing or decreasing one rate relative to the other. In this article, we examine the
effect that lowering the cost of adoption has on the adoption rate of foster children
waiting to be adopted. We consider the effect of lowering the cost of adoption in two
ways: by increasing the adoption payments while holding constant the foster-care
payments, and by increasing the generosity of both payments. Using the 1998 and 2006
AFCARS data, we find that lowering the cost of adoption increases adoption rates
through both channels. First, increasing adoption payments, holding constant foster-care
payments (effectively reducing the difference between foster-care and adoption
payments) makes adoption more attractive to a current foster parent. Second, increasing
the generosity of both payments makes foster care and adoption more attractive to
23
prospective parents, making it easier for child welfare agencies to place children in
homes that are more likely to adopt.
Our difference-in-differences estimation strategy identifies the relationship
between adoption rates and foster-care/adoption subsidies using the variation observed
between two points in time within a state-age group. Any unobserved time-invariant
factors specific to children of a particular age in a given state are implicitly accounted for.
However, an important limitation of this study is that we are unable to control for state
specific trends in the adoption rate and in the foster-care/adoption subsidies. Furthermore,
although we find that lowering the cost of adoption has a slightly larger effect on foster
parents who are related to their foster child compared to those who are unrelated, states
differ in their policies towards kinship care. Further research is needed to investigate the
role that such policies have on the adoption rates of children from kinship care.
While lowering the cost of adoption appears to have similar effects on the
adoption rates of children regardless of the individual characteristics of the child, it has a
stronger impact on children placed in some homes than in others. For example, reducing
the cost of adoption has a relatively larger impact on the adoption rates of older foster
parents, black foster parents, and foster parents who are related to their foster child.
Moreover, these are the foster parents who, in 1998, had the lowest adoption rates.
24
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28
Figure 1: Average Foster Care and Adoption Subsidies, by Child’s Age
1998 Foster Care Payments
1998 Adoption Payments
2006 Foster Care Payments
2006 Adoption Payments
$550
Monthly Payment
$525
$500
$475
$450
$425
$400
$375
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17
Child's Age
Source: Data obtained from the Child Welfare League of America, the North American Council on Adoptable
Children, a variety of state publications, and direct contact with state employees. Payments have been converted to
2006 dollars using the Consumer Price Index for All Urban Consumers (CPI-U). Louisiana, Massachusetts, Nebraska,
Nevada, New Hampshire, Ohio, South Dakota, and Tennessee are not included in the 1998 AFCARS data, and so are
excluded in both years. Children in Colorado, Indiana, Kansas, New York, and Pennsylvania are excluded because the
state does not set a basic monthly subsidy rates. Children in Alabama, Alaska, Arizona, Arkansas, Delaware, District
of Columbia, Florida, Michigan, and New Mexico are excluded because of missing data in the 1998 AFCARS data.
29
Figure 2: Monthly Basic Foster Care and Adoption Subsidies in 1998 and 2006 for
Six Selected States, by Child’s Age
B. Connecticut
A. California
$900
Monthly Payment
Monthly Payment
$600
$550
$500
$450
$750
$700
$650
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Child's Age
Child's Age
C. Georgia
D. Illinois
$550
$550
Monthly Payment
Monthly Payment
$800
$600
$400
$500
$450
$400
$350
$500
$450
$400
$350
$300
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Child's Age
Child's Age
E. New Jersey
F. South Carolina
$600
$450
$550
Monthly Payment
Monthly Payment
$850
$500
$450
$400
$350
$300
$400
$350
$300
$250
$200
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Child's Age
Child's Age
Source: Data obtained from the Child Welfare League of America, the North American Council on Adoptable
Children, a variety of state publications, and direct contact with state employees. Payments have been converted to
2006 dollars using the Consumer Price Index for All Urban Consumers (CPI-U).
30
Table 1: Characteristics of Children Eligible for Adoption in 1998 and
2006, by Gender
Boys
Girls
Child Characteristic:
1998
2006
1998
2006
Ages 4-6
Ages 7-11
Ages 12-16
35.86
45.59
18.55
34.80
38.69
26.52
34.18
46.47
19.35
34.24
39.12
26.64
White
Black
Hispanic
Other
32.95
55.99
8.17
2.90
38.89
29.85
22.49
8.77
34.15
54.38
8.55
2.92
39.45
28.24
23.54
8.77
Disabled
Child reason for removal
Months in foster care
24.56
12.03
48.92
(0.17)
40.54
14.31
43.32
(0.18)
19.86
11.20
47.88
(0.17)
33.80
11.82
40.47
(0.17)
Sample Size
30,004
30,034
29,384
29,030
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006
version 1.
Table notes—All number are percentages except for months in foster care. The sample includes four to
sixteen year-old children in foster care in 1998 and 2006. See Figure 1 notes for state restrictions.
Standard errors in parenthesis. Children in supervised independent living, group homes/institutions,
trial home visits, or who have runaway are not included in the sample. Child disabilities include mental
retardation, visual/hearing impairment, physical disability, emotional disability, and other diagnosed
disability. Child reasons for removal include alcoholic child, drug addicted child, child disability, and
child behavior problems.
31
Table 2: Adoption Rates Among Children Eligible for Adoption in 1998
and 2006, by Child Characteristics
Boys
Girls
Child Characteristic:
1998
2006
1998
2006
Overall
17.24
29.36
17.57
29.44
Ages 4-6
Ages 7-11
Ages 12-16
19.83
16.77
13.40
35.98
29.17
20.96
20.21
17.24
13.70
35.22
29.84
21.43
White
Black
Hispanic
Other
21.02
14.27
19.96
24.02
32.13
26.28
29.22
27.91
21.08
14.53
21.86
20.61
32.55
26.41
28.27
28.36
Disabled
Child reason for removal
19.25
17.10
28.09
25.31
19.06
18.66
28.67
26.12
30,004
30,034
29,384
29,030
Sample Size
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and
2006 version 1. See Table 1 notes for sample description.
Table notes—All number are percentages.
32
Table 3: Characteristics of the Foster Parents of Children Eligible for
Adoption in 1998 and 2006, by Child Gender
Boys
Girls
Foster Parent Characteristic:
1998
2006
1998
2006
White
Black
Hispanic
Other race/ethnicity
Unknown race/ethnicity
30.73
41.09
4.13
1.83
22.22
41.43
23.88
12.18
3.53
18.99
32.00
40.57
4.32
1.81
21.29
42.07
23.37
12.91
3.56
18.09
Ages 35 and under
Ages 36 to 50
Age 51 and older
Age unknown
10.28
35.01
26.19
28.52
11.28
38.54
27.46
22.72
10.16
35.49
26.29
28.05
11.93
38.70
26.88
22.50
Unrelated foster family
Kinship care
Pre-Adoptive family
51.66
23.21
25.13
47.26
19.48
33.26
50.15
24.61
25.24
45.38
21.27
33.35
Couple
Single Female
Single Male
Unknown family structure
39.69
32.36
2.91
25.03
60.25
21.46
3.58
14.71
38.97
34.74
1.66
24.63
59.85
23.60
1.68
14.86
30,004
30,034
29,384
29,030
Sample Size
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006
version 1. See Table 1 notes for sample description.
Table notes—All number are percentages. Race and Age represent the characteristics of the first foster
parent. Couple represents both married and unmarried two foster parent households.
33
Table 4: Adoption Rates Among Children Eligible for Adoption in 1998
and 2006, by Foster Parent Characteristics
Boys
Girls
Foster Parent Characteristic:
1998
2006
1998
2006
White
Black
Hispanic
Other race/ethnicity
Unknown race/ethnicity
18.49
7.06
16.32
22.99
34.04
32.78
23.87
26.99
22.81
31.53
18.34
6.63
18.93
19.14
36.85
32.94
23.68
26.89
22.75
31.88
Ages 35 and under
Ages 36 to 50
Age 51 and older
Age unknown
16.02
15.25
8.86
27.83
34.50
33.58
27.32
22.11
14.87
15.32
8.98
29.44
32.47
34.08
27.95
21.63
Unrelated foster family
Kinship care
Pre-Adoptive family
7.46
4.47
49.15
9.16
10.12
69.34
7.72
4.38
50.01
9.53
9.86
69.01
Couple
Single Female
Single Male
Unknown family structure
16.80
8.49
9.27
30.18
32.21
23.11
23.44
28.26
17.36
8.41
5.54
31.62
32.49
23.15
20.65
28.16
30,004
30,034
29,384
29,030
Sample Size
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006
version 1. See Table 1 notes for sample description.
Table notes—All number are percentages.
34
Table 5: Marginal Effects on the Adoption Rate of Eligible Foster Children Calculated from Logit Regressions, by Child’s
Gender
Boys
Girls
Boys
Girls
Difference in Payments
†
Generosity of Payments‡
Year 2006
Child’s Race:
Black
Hispanic
Other
Months in Foster Care
Disabled
Child Reason for Removal
Foster Parent Marital Status:
Married Couple
Unknown
(1)
.046***
(.010)
.037**
(.016)
.135***
(.009)
(2)
.059***
(.011)
.062***
(.016)
.142***
(.009)
-.001
(.008)
-.016***
(.006)
-.012
(.008)
.007
(.008)
-.016***
(.005)
-.016**
(.008)
.0009***
(.0001)
-.029***
(.006)
-.034***
(.007)
.0012***
(.0001)
-.034***
(.006)
-.026***
(.007)
.042***
(.009)
.188***
(.025)
.047***
(.008)
.187***
(.024)
Related foster parent
Foster Parent Age:
Ages 36 to 50
Ages 51 and older
Age unknown
Foster Parent Race/Ethnicity:
Black
Hispanic
Other
Unknown
Sample Size
(1) Continued
-.238***
(.022)
(2) Continued
-.247***
(.022)
-.005
(.006)
-.032***
(.008)
-.088***
(.023)
.004
(.005)
-.023***
(.007)
-.070***
(.024)
-.076***
(.011)
.003
(.008)
-.016
(.013)
.034
(.022)
-.087***
(.011)
.014*
(.008)
-.036**
(.014)
.032
(.023)
60,038
58,414
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006 version 1. See Table 1 notes for additional sample restrictions.
Table notes—Statistically significant at the ***99%, **95%, and *90% confidence levels. All regressions include state-age fixed effects. Standard errors clustered by state-age
group in parenthesis. Ordinary least squares produce nearly identical marginal effects.
†
This measures the association between a $100 increase in the basic monthly adoption payment and the adoption rate, holding constant foster care payments.
‡
This measures the association between a $100 increase in both the adoption and foster care payment and the adoption rate.
35
Table 6: Marginal Effects of Foster Care and Adoption Payments on the Adoption Rate of
Eligible Foster Children Calculated from Logit Regressions, by Child’s Characteristic
Difference in Payments†
Generosity of Payments‡
Boys
Girls
Boys
Girls
***
***
**
Overall
.046
.059
.037
.062***
(.010)
(.011)
(.016)
(.016)
Ages 4-6
Ages 7-11
Ages 12-16
Disabled
Not-Disabled
White
Black
Hispanic
Other Race/ethnicity
Child removal reason
No child removal reason
.045***
(.012)
.048***
(.012)
.041***
(.013)
.068***
(.014)
.054***
(.013)
.051***
(.015)
.013
(.029)
.036
(.023)
.069**
(.027)
.054*
(.030)
.058**
(.024)
.078***
(.023)
.038***
(.011)
.046***
(.010)
.041***
(.013)
.063***
(.011)
.019
(.017)
.045***
(.016)
.035**
(.017)
.072***
(.016)
.041***
(.011)
.059***
(.013)
.041***
(.010)
.056***
(.014)
.059***
(.011)
.076***
(.013)
.048***
(.011)
.052***
(.014)
.033**
(.017)
.042**
(.017)
.042**
(.017)
.044***
(.017)
.065***
(.017)
.068***
(.018)
.061***
(.016)
.061***
(.018)
.031**
(.012)
.049***
(.010)
.038***
(.014)
.062***
(.011)
.025
(.018)
.040**
(.016)
.048***
(.018)
.066***
(.016)
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006 version 1. See Table 1
notes for additional sample restrictions.
Table notes—Statistically significant at the ***99%, **95%, and *90% confidence levels. All regressions include state-age fixed
effects and the same controls as the regressions reported in Table 5. Standard errors clustered by state-age group in parenthesis.
Ordinary least squares produce nearly identical marginal effects.
†
This measures the association between a $100 increase in the basic monthly adoption payment and the adoption rate, holding
constant foster care payments.
‡
This measures the association between a $100 increase in both the adoption and foster care payment and the adoption rate.
36
Table 7: Marginal Effects of Foster Care and Adoption Payments on the Adoption Rate of
Eligible Foster Children Calculated from Logit Regressions, by Foster Parent Characteristic
Difference in Payments†
Generosity of Payments‡
Boys
Girls
Boys
Girls
***
Ages 35 and under
-.013
.011
.075
.099***
(.010)
(.011)
(.015)
(.017)
***
Ages 36 to 50
.005
.012
.076
.103***
(.009)
(.009)
(.015)
(.017)
**
***
***
Age 51 and older
.025
.030
.080
.093***
(.010)
(.010)
(.016)
(.016)
.037***
(.009)
.030***
(.011)
.046***
(.009)
.044***
(.011)
.095***
(.017)
.109***
(.019)
.113***
(.017)
.132***
(.019)
.029***
(.011)
.052***
(.015)
.038***
(.011)
.063***
(.015)
.077***
(.016)
.085***
(.017)
.098***
(.017)
.112***
(.019)
Hispanic
.029**
(.012)
.055***
(.011)
.073***
(.019)
.118***
(.018)
Related (kinship care)
.158***
(.038)
.034***
(.009)
.165***
(.038)
.047***
(.009)
.069***
(.026)
.030**
(.015)
.078***
(.027)
.058***
(.015)
Married/Couple
Single
White
Black
Not Related
Source: Adoption and Foster Care Analysis and Reporting System (AFCARS) 1998 version 6 and 2006 version 1. See Table 1
notes for additional sample restrictions.
Table notes—Statistically significant at the ***99%, **95%, and *90% confidence levels. All regressions include state-age fixed
effects and the same controls as the regressions reported in Table 5. Standard errors clustered by state-age group in parenthesis.
Ordinary least squares produce nearly identical marginal effects.
†
This measures the association between a $100 increase in the basic monthly adoption payment and the adoption rate, holding
constant foster care payments.
‡
This measures the association between a $100 increase in both the adoption and foster care payment and the adoption rate.
37