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Beyond the Nuclear Family: Trends in Children Living in Shared Households
April 2018
Natasha V. Pilkauskas
Christina Cross
npilkaus@umich.edu
Gerald R. Ford School of Public Policy
734 S. State Street, Ann Arbor, MI 48109.
This is a post-peer-review, pre-copyedit version of an article published in Demography. The final
authenticated version is available online at: doi.org/10.1007/s13524-018-0719-y
Pilkauskas & Cross Children in Shared Households
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Abstract
Using data from the 1996-2008 panels of the Survey of Income and Program Participation and
the 2009-2016 American Community Survey, we examine trends in children living in shared
households (living with adults beyond their nuclear [parent/parent’s partner/sibling] family). We
find that although the share of children who lived in a shared household increased over this time
period, the rise was nearly entirely driven by an increase in three-generation/multigenerational
households (coresident grandparent(s), parent(s), and child). In 1996, 5.7% of children lived in a
three-generation household and by 2016, 9.8% did likewise, more than a 4 percentage point
increase. More economically advantaged groups (older, more educated mothers, married
households) experienced the largest percent increase in three-generation coresidence, although
correlates of coresidence remained largely stable over time. Decomposition analyses suggest that
a rise in social security receipt and changes in parental relationship status (less marriage, more
single parenthood) most strongly explained the increase in three-generation households over
time. Given the dramatic rise in three-generation households, more research is needed to
understand the consequences of these living arrangements for children, their parents, and their
grandparents.
Pilkauskas & Cross Children in Shared Households
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Many studies have shown the importance of economic, demographic, and policy factors
in determining family living arrangements (e.g. Ruggles 2007). Family change (such as high
divorce and non-marital fertility rates) and other demographic factors (such as increased
longevity) influence family dynamics and intergenerational relationships, including coresidence
(Bengtson 2001). Understanding family change is important because a robust body of research
documents strong links between children’s living arrangements, economic well-being and long-
term child outcomes (e.g. Cherlin 2010). Despite increasing recognition of the diversity in
children’s living arrangements (e.g. Carlson and Meyer 2014), to date, no research has studied
trends in household sharing (at least one resident adult who is not the child’s parent/parent’s
partner/sibling) among families with children and differences by type of household sharing1.
This is an oversight, as nearly 20%, or 15M children live in a shared household (Mykyta and
Macartney 2012) and adults in shared households play an important role in the lives of children
(Amorim et al. 2017; Cherlin and Seltzer 2014; Edin and Lein 1997; Pilkauskas 2012; Stack
1974) that can both positively and negatively affect children’s cognitive and socioemotional
wellbeing (e.g. Dunifon and Kowaleski-Jones 2007; Mollborn et al. 2012; Pilkauskas 2014).
Using data from the 1996, 2001, 2004, and 2008 panels of the Survey of Income and
Program Participation (SIPP), as well as the American Community Survey (2009-2016), we add
to the literature by examining the following questions: 1) What are the trends in household
sharing among families with children over time, and are there differences by type of shared
household (e.g. living with an aunt/uncle versus a grandparent versus a non-relative)? And 2)
what explains the changes in shared household living arrangements? To answer the first question
1 Research has documented prevalence of particular types of shared living arrangements such as extended family
households (children living with adult relatives; Kreider and Ellis 2011) or grandparent coresidence (e.g. Ellis and
Simmons 2014; Dunifon et al. 2014), but not examined trends over time comparing across types of shared living
arrangements for children.
Pilkauskas & Cross Children in Shared Households
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we plot trends in shared living arrangements by household type and find that the increase in
shared living arrangements over time is being driven by an increase in three-
generation/multigenerational (coresident grandparent, parent, child) households. We then focus
our analyses on three-generational households by examining which demographic groups have
increased coresidence, whether the correlates of coresidence have changed over time, and the
demographic/socioeconomic factors that help explain the increase. By understanding trends in
children’s living arrangements we can help inform policies and programs that support children.
Data, Measures and Method
We use the Survey of Income and Program Participation (SIPP), a nationally
representative survey of the non-institutionalized population collected by the U.S. Census
Bureau. Data come from the 1996, 2001, 2004, and 2008 SIPP panels.2 We use the Household
Relationships Topical Module (HRTM), which was collected as part of the second wave of each
panel and asked detailed information on all of the relationships of individuals in a household (we
can identify the relationship of every person in the household to each child in the household).
This household detail is uncommon in large nationally representative studies, which typically
rely on household rosters that provide data only on the relationship to the reference person, and
miss out on many relationships in the household (Kreider 2008). Data from the HRTM are
merged with the core data files and are restricted to the 4th reference month – the SIPP reporting
month (Moore 2008). The sample in each panel wave used ranges from 30-42,000 households
including 20-28,000 children.
We also use the 2009-2016 American Community Survey (ACS), a nationally
representative survey of the U.S. population that samples approximately 3M households annually
2 We do not use earlier waves of SIPP (pre-1996) or the 2014 SIPP because changes in sampling and questionnaire
design make comparisons difficult/inaccurate. !
Pilkauskas & Cross Children in Shared Households
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and is collected by the U.S. Census Bureau. The ACS, collected by the U.S. Census Bureau, uses
monthly rolling samples of households to produce annual estimates of the population for people
in housing units (and group quarters for most years)3. For our analyses, we exclude individuals
living in group quarters. The ACS data for this study were drawn from extracts made by the
Integrated Public Use Microdata Sample (IMPUS-USA; Ruggles et al 2017). The ACS collects
household information through a roster with reference to a single person in the household and
with less detailed information than the SIPP. We focus our analyses using the ACS on children
living with grandparents (three-generation and skipped-generation households).
Household Sharing
Household sharing is coded to examine many types of shared living arrangements.
Additional detail on how the measures were constructed is available in Appendix 1.
1) Shared household: a child living with an additional adult beyond their parent/step-
parent, sibling, or the cohabiting partner of the parent (following Pilkauskas et al.
2014, also known as doubled-up households).
2) Extended family: a child living with any adult relative beyond their parents/step-
parents/cohabiting partner or sibling. This includes grandparents, aunts/uncles,
nieces/nephews and other relatives (e.g. cousins).
3) Grandparents: children living with at least one grandparent.
4) Aunt/uncle: children living with at least one adult aunt/uncle.
5) Other relative: children living with at least one adult relative who was not the
grandparent, aunt/uncle, sibling, or parent/parent’s partner.
3!Additional details on the ACS is available here: https://www.census.gov/programs-
surveys/acs/methodology/design-and-methodology.html!
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6) Non-relative: children living with at least one adult non-relative.
Categories are not mutually exclusive; a child who lives with both a grandparent and non-relative
is included in both categories. In each case, a parent may or may not be present.
Prior research has noted large differences between three-generation/multigenerational
households (children living with at least one grandparent and at least one parent) and skipped-
generation households (at least one coresident grandparent and grandchild, no parent present;
Dunifon et al. 2014). Thus, we also examine these two households separately.
Correlates
We examine the following indicators in the correlates analysis and the Oaxaca-Blinder
decomposition (following previous research, e.g. Kamo 2000): child’s age (<5, 6-11, 12-17), sex,
and race/ethnicity (Non-Hispanic Black, Non-Hispanic White, Hispanic, Asian, other
race/ethnicity), mother’s relationship status (married, unmarried, divorced/widowed/separated),
age (<18, 18-29, 30-39, 40-49, 50+), education (less than high school, high school, some college,
college or higher), labor force participation (employed, unemployed, not in labor force), if she is
an immigrant, and family income-to-needs ratio (using Census bureau income-to-needs
thresholds <101% of poverty, 1-200%, 2-300%, 3-400% and 400% or greater)4. We also include
measures of whether the child lives in an urban area, the region of the country (Northeast,
Midwest, South, West), whether the home is owned, whether anyone in the household received
Temporary Assistance for Needy Families (TANF), food stamps/Supplemental Nutrition
Assistance Program, Social Security (also including survivors benefits), Supplemental Security
Income (SSI; including both children and adults), unemployment insurance, Veteran’s payments,
child support, Women, Infants and Children (WIC) or public housing/housing assistance.
4 If a child is not living with their mother we use information on their father.
Pilkauskas & Cross Children in Shared Households
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Further, we include measures of the child’s health insurance (Medicaid, private health insurance,
none), and whether the child received school lunch/breakfast. In Appendix 2, we provide
descriptive statistics on all the covariates for 1996 and 2009. Compared with 1996, in 2009,
fewer children were White, more mothers had college degrees, were over the age of 40, and were
immigrants. Children in 2009 were more likely to live in a household receiving public assistance
(especially Medicaid and school breakfast/lunch, although far fewer received TANF) but a
higher share also lived in households above 400% of poverty.
Method
To answer our first research question – what are the trends in household sharing among
families with children over time, we provide weighted descriptive statistics. To answer our
second research question, aimed at explaining the observed changes in household sharing
(specifically the increase in three-generation coresidence – the only shared living arrangement
that increased over this time period), we conducted three additional analyses. First, we examined
which demographic groups have increased three-generation coresidence using weighted
descriptive statistics and calculating the percent change by group. Second, we compared the
correlates of three-generation coresidence in 1996 to those in 2009 to see if different factors
predicted coresidence over time. To do this, we ran logistic regression models (reporting odds
ratios) where we regressed three-generation coresidence on the covariates detailed above
separately for 1996 and for 2009.5 We ran Chow tests to test for significant differences in beta
coefficients across the two time periods. Last, to examine which factors might explain the change
in coresidence over time we conducted Oaxaca-Blinder decomposition (the Fairlie extension for
binary outcomes; Fairlie, 2005) using the same covariates detailed above (those used in the
5 Note, we checked for high correlations between the variables and where we found high correlations we ran
extensions excluding those variables. The findings were unchanged.
Pilkauskas & Cross Children in Shared Households
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correlates model). This statistical method decomposes how changes in various factors (say share
of children living with single parents) might explain mean differences in household composition
over time (see Van Hook et al., 2004 for a detailed application of the Oaxaca-Blinder
decomposition). We report results using a pooled sample for 1996 and 2009 so that the results
are not affected by the selection of comparison year (Neumark 1988; Oaxaca and Ransom 1994);
however, extensions using a shift share approach (for either year) were nearly identical to those
presented here. We compute the decomposition using normalized effects (deviations from a
grand mean), which allows us to calculate effects for every category (including the excluded
category; see Yun 2005a,b; Jann 2006 for more details) but substantive findings were the same
when we ran models excluding a reference category.
Results
What Are the Trends in Household Extension?
Figure 1 displays trends in children’s household extension between 1996 and 2009.
Overall, there was a 3-percentage point increase in the proportion of children living in shared
households during this time period (from 17.6% to 20.8%). This increase did not occur evenly
across all types of shared households. The largest growth in household sharing took place among
children living with grandparents (from 7.5% to 10.5%), whereas the share of children living
with aunts/uncles (about 5%), other relatives (7%), and nonrelatives (5%) remained relatively
stable during these years.
To further explore trends in grandparent coresidence, Figure 2 plots skipped-generation
and three-generation coresidence over time. Although skipped-generation households increased
somewhat over this time period, we find that nearly the entire rise in household extension was
attributable to a growth in three-generation households (5.7% to 8.0%). To study whether the
Pilkauskas & Cross Children in Shared Households
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upward trend in grandparent coresidence continued beyond 2009, in Figure 3 we used the ACS
to examine trends in three-generation and skipped-generation coresidence through 2016.6 The
share of children living in three-generation households continued to rise, from 8.1% in 2009
(8.0% in the SIPP) to 9.8% in 2016. To better understand this trend, the remainder of our
analyses focus on three-generation households.
Who is More Likely to Live in a Three-Generation Household?
To further unpack the rise in three-generation households, we examined whether
particular demographic groups were more likely to live in such a household over time. In Table 1
we examine which demographic groups experienced the largest increase in three-generation
coresidence (by row).7 In keeping with the fact that three-generation households increased over
this time period, we see that most demographic groups experienced an increase in coresidence,
but a few trends stand out. Black and Asian children experienced the smallest percent increase in
coresidence, despite more generally having the highest rates of three-generation coresidence
(Pilkauskas 2014). Hispanic and children of “other” race/ethnicity experienced the largest
increase in coresidence. Mothers with high school or greater education experienced much larger
percent increases than those with less than a high school degree. Interestingly, the share of young
mothers (under 18) living in a three-generation household declined (as did mothers over 50),
whereas the share of coresident mothers aged 40-49 in three-generation households nearly
doubled. Children in married parent households increased three-generation coresidence by 45%
(2 percentage points), whereas children in unmarried parent households increased by 15% (3
percentage points). Households with income above poverty experienced greater percent increases
6 We do not use the ACS for our main analyses because we cannot distinguish as many household types and the
(non-pilot) data only start in 2005.
7 Percent/percentage point inconsistencies in the table are due to rounding.
Pilkauskas & Cross Children in Shared Households
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in three-generation coresidence. In terms of government assistance, households receiving school
lunch, unemployment income, and housing assistance experienced the largest percent increases,
although change in percentage point terms was relatively small (2-3 percentage points).
Have Correlates of Three-Generation Coresidence Changed over Time?
It is possible that the rise in three-generation households is in part explained by a change
in the characteristics that are correlated with coresidence. In Table 2 we examine whether the
correlates of three-generation coresidence changed over time. Concordant with prior research,
we find that children living in families with greater economic need (income or social safety net
participation), younger children, racial/ethnic minorities, those with unmarried and younger
mothers (especially teenage mothers), had higher odds of living in a three-generation household.8
We find that only three predictors changed over time; Chow tests suggested that being Asian and
receiving SNAP/food stamps was less predictive of coresidence, whereas having an immigrant
mother became more predictive.
What Factors Explain the Observed Changes in Three-Generation Households?
To examine factors that explain the increase in three-generation households, Table 3
displays the results from Oaxaca-Blinder decomposition which details the percent of the
difference in three-generation households between 1996 and 2009 (8.38%-5.72%=2.66%; this
analysis is restricted to children living with at least one parent, thus the rate in 2009 is slightly
higher than that for all children) that can be attributed to observable differences in characteristics
of households with children between these two time points.
8!Mother’s education was not consistently related to coresidence, likely due to collinearity with income. In an
extension, we excluded family income from the models and found that greater education was strongly and
negatively associated with three-generation coresidence.!
Pilkauskas & Cross Children in Shared Households
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Two factors stand out as major contributors to the increase in three-generation
households; the change in the relationship status of parents and the share of households receiving
social security (note, a negative coefficient suggests that had compositional changes not occurred
over this time period, the share of children in three-generation households would have been
lower, or in other words, this compositional shift contributes to the increase in coresidence). The
change in parent’s relationship status accounts for approximately half a percentage point of the
increase (sum of the individual beta coefficients for each union status) in three-generation family
households (or about 20% of the total 2.66 percentage point change over time). Likewise, social
security receipt accounts for a half a percentage point increase in three-generation family
households (19% of the total percentage point change). Changes in the racial/ethnic make of up
children also increased the share of three-generation households, as did the decline in the share
of households with private health insurance.
Although most compositional changes suggest that three-generation households should
have increased over this time period, a few changes also work against the observed increase. In
particular, the increase in Medicaid receipt over this time period worked to decrease three-
generation coresidence by nearly half a percentage point (.46, had Medicaid not increased, the
share of children living in three-generation households likely would have been even higher).
Likewise, shifts in maternal age composition (towards an older age) reduce coresidence slightly
(0.21 percentage points).
Discussion
This study examined trends in shared households among children. We found that
although the share of children living in a shared household increased between 1996 and 2009, the
increase was driven by a rise in the share of children living in three-generation households. The
Pilkauskas & Cross Children in Shared Households
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share of children living in such households increased from 5.7% in 1996 to 8.0% in 2009. We
may be concerned that the Great Recession drove the increase, but this study shows that the
increase started well before the recession (before 2007) and continued beyond its end (2010),
increasing to 9.8% of children in 2016 (7.1 million children).
The correlates analyses showed few correlates had changed over time and that three-
generation coresidence was more common among lower income households, yet we found that
more economically advantaged groups had experienced the largest percent increases in three-
generation coresidence: children in married households, with mothers who were more educated,
and who were older. Future research should examine why this might be the case.
The decomposition suggested that changes in parent’s relationship status was the
strongest explanatory factor in the increase in three-generation coresidence over time; however,
an increase in the share of households receiving social security also explained a large share of the
increase. Like reduced marriage and increased single parenthood, increased receipt of social
security explained almost half a percentage point increase in three-generation coresidence.
The increase in three-generation coresidence associated with increased social security receipt
may be because individuals who receive social security are likely to be a source of economic
stability (and compared with many other government programs, social security payments are
generally larger, and more stable over time). Children and grandchildren may move in with
grandparents receiving social security if they are more economically stable.
Although most public assistance programs explained little of the change over time,
increased Medicaid receipt reduced three-generation coresidence by almost half a percentage
point. Similar to social security, and unlike most public assistance programs, which have smaller
economic value and often have shorter recertification periods (e.g. an individual may lose
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eligibility month-to-month on food stamps), Medicaid provides families with children with a
relatively significant in-kind income transfer, which may permit families to live independently,
thus, reducing coresidence. The difference in direction of the effect of social security and
Medicaid may in part be driven by differences in who receives the assistance. If mothers or
children receive Medicaid the economic benefit may allow them to live independently. In
comparison, social security is largely received by the grandparent generation; thus these
grandparents may be able to provide assistance to their children and grandchildren through
coresidence.
Although our analysis included a large set of characteristics likely related to three-
generation coresidence, other unmeasured factors (such as preferences, health of members of the
household, or housing markets) may also be important drivers of coresidence. Increased
coresidence with grandparents may in part be explained by increased longevity (World Bank
2018), the greater share of individuals who are grandparents (Monte 2017) or step-grandparents
(Yahirun et al. 2018), or an increased length of grandparenthood (Margolis and Wright 2017),
factors we could not observe here. Future research that can examine these factors would be a
useful next step. Nonetheless, these findings suggest that public policies likely shape the living
arrangements of children.
Given the large increase in the share of children living in three-generation households
over the last 20 years, more research should study the implications of these living arrangements.
Prior research has linked coresidence with positive outcomes for older children (e.g. Deleire and
Kalil 2002), but for younger children the evidence is mixed (e.g. Mollborn et al. 2011, 2012;
Pilkauskas 2014). Understanding how policy and demographic changes influence coresidence
and the implications for children will be important areas for future research.
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Table 1: Proportion of Children Living in Three-Generation Households by Demographic
Characteristics and Change Over Time
1996
2009
% change
Percentage
Point Change
Child's Age
Age 5 or below*
0.09
0.12
28
3
Ages 6-11*
0.05
0.07
49
2
Ages 12-17*
0.03
0.05
65
2
Male*
0.06
0.08
40
2
Child's Race/Ethnicity
Black
0.10
0.11
6
1
White*
0.04
0.05
44
2
Hispanic*
0.07
0.11
53
4
Asian
0.13
0.13
3
0
Other*
0.04
0.10
155
6
Mother's Education1
Less than high school*
0.08
0.09
18
1
High school*
0.06
0.11
77
5
Some college*
0.05
0.08
55
3
Bachelor's degree or higher*
0.03
0.04
41
1
Mother's Age1
Below 18*
0.08
0.02
-73
-6
18-29*
0.12
0.16
35
4
30-39*
0.04
0.07
69
3
40-49*
0.03
0.06
77
2
50 and above
0.06
0.05
-13
-1
Mother's Labor Force Participation1
Employed*
0.05
0.08
50
3
Unemployed
0.09
0.11
22
2
Not in labor force*
0.06
0.09
43
3
Mother is an immigrant*,1
0.07
0.11
44
3
Region
Northeast*
0.06
0.08
25
2
Midwest*
0.04
0.06
41
2
South*
0.06
0.08
34
2
West*
0.06
0.10
55
3
Urban*
0.06
0.08
39
2
Mother's Union Status1
Mother is married*
0.03
0.05
45
2
Mother is unmarried*
0.18
0.20
15
3
Mother is divorced/separated/widowed*
0.08
0.11
39
3
Pilkauskas & Cross Children in Shared Households
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Table 1: Proportion of Children Living in Three-Generation Households by Demographic
Characteristics and Change Over Time Continued
Family Income as a Percent of Poverty
<101% *
0.05
0.07
22
1
101-200%*
0.07
0.11
52
4
201-300%*
0.07
0.10
40
3
301-400%
0.06
0.09
54
3
401+%*
0.04
0.06
58
2
Child support receipt*
0.07
0.11
55
4
Own home*
0.06
0.09
35
2
Government Programs
Temporary Assistance to Needy Families
0.11
0.13
15
2
Food stamps/SNAP*
0.11
0.13
14
2
School breakfast/lunch*
0.04
0.07
60
3
Social security
0.28
0.31
9
3
Supplemental security income
0.22
0.24
8
2
Unemployment income*
0.07
0.11
50
4
Veterans payments
0.20
0.17
-15
-3
Women Infants and Children*
0.15
0.20
29
4
Housing assistance
0.03
0.06
63
2
Medicaid*
0.10
0.11
19
2
Private health insurance*
0.04
0.05
18
1
N
24,627
24,097
Note: Sample is restricted to children who live with at least one parent. Source - 1996 and 2009 Survey
of Income and Program Participation. Percentage point inconsistencies are due to rounding.
1 Father's information is used when mother's information is unavailable.
* Indicates significant differences at p<0.05 from Chi square tests between 1996 & 2009
Pilkauskas & Cross Children in Shared Households
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Table 2: Correlates of Three-Generation Family Coresidence, 1996 and 2009
1996
2009
Odds Ratio
Z-Stat
Odds Ratio
Z-Stat
Child's Age (vs. age 5 or below)
Ages 6-11
0.635***
(-4.317)
0.717***
(-3.317)
Ages 12-17
0.312***
(-8.668)
0.398***
(-7.712)
Male
0.984
(-0.233)
0.959
(-0.716)
Child's Race/Ethnicity (vs. White)
Black
1.557**
(3.308)
1.364*
(2.141)
Hispanic
1.782***
(3.499)
1.370*
(2.583)
Asian^
5.188***
(6.471)
2.926***
(5.575)
Other
1.761
(1.512)
1.307
(1.516)
Mother's Education (vs. Bachelor's degree or higher) 1
Less than high school
0.707†
(-1.713)
1.134
(0.675)
High school
0.958
(-0.251)
1.332*
(2.054)
Some college
0.950
(-0.299)
1.045
(0.346)
Mother's Age (vs. 50 or above)1
Below 18
4.702**
(3.301)
5.725**
(3.157)
18-29
2.545**
(3.264)
3.999***
(5.285)
30-39
1.146
(0.497)
1.758*
(2.258)
40-49
0.958
(-0.157)
1.720*
(2.231)
Mother's Labor Force Participation (vs. not in labor force) 1
Employed
1.502***
(3.447)
1.520***
(3.891)
Unemployed
1.271
(1.251)
1.062
(0.351)
Mother is an immigrant^ ,1
1.117
(0.690)
1.686***
(4.002)
Region (vs. South)
Northeast
1.446**
(2.732)
1.181
(1.340)
Midwest
0.741*
(-2.213)
0.820
(-1.471)
West
1.204
(1.417)
1.267*
(2.066)
Urban
1.571***
(3.593)
1.379**
(2.725)
Mother's Union Status (vs. married)1
Unmarried
3.637***
(8.704)
3.558***
(10.468)
Divorced/separated/widowed
1.930***
(4.661)
2.143***
(5.707)
Family Income as a Percent of Poverty (vs. >401% of poverty threshold)
<101%
5.160***
(6.549)
4.397***
(8.173)
101-200%
3.510***
(5.239)
3.160***
(6.509)
201-300%
2.364***
(3.497)
1.553*
(2.317)
301-400%
1.722*
(2.031)
1.158
(0.692)
Child support receipt
1.185
(1.259)
1.144
(1.041)
Own home
4.596***
(11.883)
4.408***
(12.135)
Pilkauskas & Cross Children in Shared Households
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Table 2: Correlates of Three-Generation Family Coresidence, 1996 and 2009 Cont.
Government Programs
Temporary Assistance to Needy Families
1.085
(0.447)
1.022
(0.093)
Food stamps/SNAP^
1.811***
(3.586)
1.129
(0.908)
School breakfast/lunch
0.696*
(-3.135)
0.836†
(-1.619)
Social security
11.946***
(18.409)
10.842***
(19.449)
Supplemental security income
2.844***
(5.583)
2.040***
(3.854)
Unemployment income
1.210
(0.729)
1.231
(1.243)
Veterans payments
2.943***
(3.280)
3.005***
(4.255)
Women Infants and Children
1.349*
(2.210)
1.466**
(3.207)
Housing assistance
0.283***
(-5.179)
0.376***
(-4.707)
Medicaid
0.652**
(-3.044)
0.554***
(-5.504)
Private health insurance
0.816†
(-1.690)
0.701**
(-2.927)
Constant
0.001***
(-15.659)
0.002***
(-17.145)
Observations
24,627
24,097
Note: Sample is restricted to children who live with at least one parent. Source - 1996 and 2009 Survey of
Income and Program Participation.
1 Father's information is used when mother's information is unavailable.
^ Indicates significant differences at p<0.05 from Chow tests between 1996 & 2009
*** p<.001, ** p<0.01, * p<0.05, † p<0.1
Pilkauskas & Cross Children in Shared Households
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Table 3: Non-Linear Oaxaca Decomposition of Difference in Prevalence of Three-Generation
Coresidence Among Children: 1996 and 2009.
Coefficient
Percent Explained
Child's Age
Ages 0-5
0.0000
0.00
Ages 6-11
0.0000
0.00
Ages 12-17
0.0003
0.01
Male
0.0000
0.00
Child's Race/Ethnicity
White
-0.0025
-0.09
Black
-0.0002
-0.01
Hispanic
0.0003
0.01
Asian
0.0000
0.00
Other
0.0003
0.01
Mother's Education1
Less than high school
-0.0005
-0.02
High school
0.0007
0.03
Some college
-0.0001
0.00
Bachelor's degree or higher
0.0001
0.00
Mother's Age1
Below 18
0.0002
0.01
18-29
0.0003
0.01
30-39
-0.0017
-0.07
40-49
0.0013
0.05
50+
0.0020
0.08
Mother's Labor Force Participation1
Employed
0.0001
0.00
Unemployed
0.0000
0.00
Not in labor force
-0.0001
0.00
Mother is an immigrant
-0.0007
-0.03
Region
Northeast
0.0000
0.00
Midwest
-0.0004
-0.01
South
0.0001
0.00
West
-0.0001
0.00
Urban
-0.0003
-0.01
Mother's Union Status1
Married
-0.0022
-0.08
Unmarried
-0.0031
-0.12
Divorced/separated/widowed
-0.0001
0.00
Pilkauskas & Cross Children in Shared Households
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Table 3: Non-Linear Oaxaca Decomposition of Difference in Prevalence of Three-Generation
Coresidence Among Children: 1996 and 2009. Cont.
Family Income as a Percent of Poverty (vs. >401% of poverty threshold)
<101%
-0.0009
-0.04
101-200%
0.0004
0.01
201-300%
-0.0004
-0.01
301-400%
-0.0003
-0.01
400%+
0.0014
0.05
Child support
-0.0002
-0.01
Own home
0.0005
0.02
Government Programs
Temporary Assistance to Needy Families
0.0002
0.01
Food stamps/SNAP
-0.0004
-0.02
School breakfast/lunch
0.0008
0.03
Social security
-0.0050
-0.19
Supplemental security income
-0.0007
-0.03
Unemployment income
-0.0004
-0.02
Veterans payments
-0.0002
-0.01
Women Infants and Children
-0.0006
-0.02
Housing assistance
-0.0003
-0.01
Medicaid
0.0046
0.17
Private health insurance
-0.0022
-0.08
Total percent
-37%
Total difference in three-generation households2
0.0266
N
48,722
Note: Pooled models. Share explained by characteristics. Sample is restricted to children who live
with at least one parent. Effects represent what would happen to the share of three-generation
households were compositional changes not to have occurred.
1 Father's information is used when mother's information is unavailable.
2 The difference in prevalence of three-generation households is 0.0266, slightly higher than the full
sample difference of 0.023. This arises because children who live without a parent present are
excluded from these analyses as information on their parents is not available.
Pilkauskas & Cross Children in Shared Households
!23
Fig. 1 Percent of Children Living in Different Types of Shared Households by Year, SIPP 1996,
2001, 2004, 2008
17.6%
19.1% 18.4%
20.8%
13.1%
14.8% 14.2%
16.1%
7.5% 8.5% 8.8%
10.5%
4.7% 5.1% 4.8% 5.3%
6.5% 6.6% 6.9% 7.0%
5.4% 5.5% 5.2% 5.8%
0%
5%
10%
15%
20%
25%
1996%
2001%
2004%
2009%
%"
Year"
Shared
Household%
Extended Family%
Grandparents%
Aunts/Uncles%
Other Relatives%
Non-Relatives%
Pilkauskas & Cross Children in Shared Households
!24
Fig. 2 Percent of Children Living in Three-Generation and Skipped-Generation Households by
Year, SIPP 1996, 2001, 2004, 2008
5.7$
6.6$ 6.7$
8.0$
1.8$ 2.0$ 2.2$ 2.5$
0$
1$
2$
3$
4$
5$
6$
7$
8$
9$
10$
1996$ 2001$ 2004$ 2009$
%$
Year$
Three-
Generation$
Skipped-
Generation$
Pilkauskas & Cross Children in Shared Households
!25
Fig. 3 Percent of Children Living in Three-Generation and Skipped-Generation Households by
Year, ACS 2009-2016
8.1$ 8.5$ 8.5$ 8.7$ 8.8$ 9.1$ 9.3$ 9.8$
2.1$ 2.1$ 2.1$ 2.2$ 2.2$ 2.2$ 2.3$ 1.9$
0$
1$
2$
3$
4$
5$
6$
7$
8$
9$
10$
2009$ 2010$ 2011$ 2012$ 2013$ 2014$ 2015$ 2016$
%$
Year$
Three-
Generation$
Skipped-
Generation$
Pilkauskas & Cross Children in Shared Households
!26
Appendix 1 – Additional Information on Coding of Household Sharing.
Using the Household Relationships Topical Module (HRTM) in the Survey of Income
and Program Participation (SIPP) we construct six shared living arrangements for children. A
shared living arrangement is defined as a child living with an adult who is not the child’s mother,
father or sibling. Following prior research (Mykyta and Macartney 2012; Pilkauskas, Garfinkel
and McLanahan 2014), we do not consider children who live with their parent’s partner to be in a
shared living arrangement.
The HRTM allows us to identify the relationship of each person in the household to each
other; thus, in the SIPP we can identify an extensive range of living arrangements not typically
possible in most surveys, which use a household roster with reference to a single person in the
household. The living arrangements are not mutually exclusive. For example, it possible for a
child to live with both a grandparent and an aunt or uncle.
Types of Shared Living Arrangements.
Shared households. Children are identified as living in a shared household if the child
living with any adult – related or unrelated – beyond their mother, father, sibling, or the
cohabiting partner of the parent. This category is the most inclusive and may include children
who live with no parent present. This type of household is sometimes referred to as a doubled-up
household.
Extended family. Children living in an extended family household include those children
who live with any adult relative beyond their parents, step-parents, parent’s cohabiting partner,
or sibling. This category includes grandparents, aunts/uncles, nieces/nephews and other relatives
(e.g., cousins). A child who lives without a parent, but lives with at least one adult relative will
be considered to be living in an extended family household.
Pilkauskas & Cross Children in Shared Households
!27
Grandparents. Children living in a household with at least one grandparent present (or
more) are considered to be living with a grandparent. These households include both those where
the child is living with their own parent (or the parent’s partner) and those without a parent.
Aunt/uncle households. Children who live with at least one aunt or uncle will be
considered living in an aunt/uncle household. These children may also live with other adults,
including their parents (or not).
Other relative. Children living with at least one other adult relative who is not the
grandparent, aunt/uncle, parent/parent’s partner or sibling are considered to be living with other
relatives.
Non-relative. Children who live with at least one adult non-relative, regardless of who
else is in the household, are considered to be living in a non-relative household.
Children living with Grandparents.
In both the SIPP and the American Community Survey (ACS) we further examine
children living with grandparents by examining three-generational/multigenerational households
separately from skipped-generation/grandfamily households. Three-
generational/multigenerational households refer to children who live with at least one parent (or
the parent’s partner) and at least one grandparent. Skipped-generation/grandfamily households
refer to children who live with at least one grandparent with no parent (parent’s partner) present.
Three-generation family households. In the SIPP, we use the HRTM to identify whether
the child is living with at least one parent (including biological, step, adopted or foster parents)
and at least one grandparent. In the ACS, because we do not have information on the
relationships of each person in the household to each other, we have to use the household roster,
which only identifies individuals with relationship to the reference person. We identify three-
Pilkauskas & Cross Children in Shared Households
!28
generation households as instances in which the reference person is the child’s grandparent (and
reports that a grandchild is in the household) and parent pointers developed by IPUMS (Ruggles
2010) that identify whether a mother or father is in the household and which individual is the
mother/father.9
We also identify three-generation households if the parent is the reference person and
reports living with their own child under 18 and their own parent (or parent in-law).
We may miss some three-generation living arrangements in the ACS. If a three-generation
family is living with an unrelated adult who is the reference person, the entire three-generation
family would all be included as “other non-relative”. Given the similarity in estimates between
the ACS and the SIPP in 2009, we do not think this is a major problem. However, this issue
suggests that our ACS estimates are likely lower bound estimates.
Skipped-generation households. We identify a child in the SIPP as living in a skipped-
generation household if the child lives with any grandparent with no parent present, regardless of
whether the grandparent was the reference person. In the ACS we identify skipped-generation
households as households in which the reference person reports living with a grandchild with no
parents of the child present in the household (has no parent pointers). In the ACS, we may
undercount skipped-generation households if the grandparent is not the reference person10.
9 These recodes are based on a number of assumptions, as this information was not directly asked. For
more details see https://usa.ipums.org/usa/chapter5/chapter5.shtml.
10 There is a question in the ACS that asks adults (over 15) if they are responsible for most of the basic
care of a coresident grandchild based on a question asking whether their own grandchild lives in the
household. We do not use this variable because although we can see whether people who are not the
reference person have a grandchild in the house, we cannot identify which child in the household is their
grandchild without making many assumptions. The main limitation with this approach is that there are
frequently numerous children in a household who are not siblings, especially in grandfamilies. Thus,
identifying which grandchild (or how many of the coresident potential grandchildren) belongs to the adult
respondent and then ensuring that child does not have a parent in the household is difficult to do
accurately.
Pilkauskas & Cross Children in Shared Households
!29
Appendix 2: Sample Characteristics, 1996 and 2009
1996
2009
Child's Age
Age 5 or below
0.34
0.34
Ages 6-11*
0.34
0.32
Ages 12-17*
0.33
0.34
Male
0.51
0.51
Child's Race/Ethnicity
Black*
0.15
0.14
White*
0.65
0.56
Hispanic*
0.15
0.22
Asian
0.03
0.03
Other*
0.01
0.05
Mother's Education1
Less than high school*
0.21
0.16
High school*
0.30
0.23
Some college*
0.30
0.35
Bachelor's degree or higher*
0.19
0.27
Mother's Age1
Below 18
0.05
0.04
18-29*
0.21
0.19
30-39*
0.47
0.42
40-49*
0.25
0.29
50 and above*
0.02
0.05
Mother's Labor Force Participation1
Employed
0.62
0.62
Unemployed*
0.04
0.06
Not in labor force*
0.29
0.28
Mother is an immigrant*
0.15
0.19
Region
Northeast*
0.18
0.17
Midwest*
0.24
0.22
South*
0.35
0.37
West*
0.23
0.24
Urban*
0.78
0.80
Mother's Union Status1
Married*
0.70
0.66
Unmarried*
0.10
0.15
Divorced/separated/widowed*
0.16
0.15
Pilkauskas & Cross Children in Shared Households
!30
Appendix Table 2: Sample Characteristics, 1996 and 2009, Continued
1996
2009
Family Income as a Percent of Poverty
<101%
0.22
0.23
101-200%*
0.23
0.22
201-300%*
0.20
0.17
301-400%*
0.14
0.13
401+% *
0.21
0.26
Child support receipt*
0.10
0.13
Own home
0.64
0.64
Government Programs
Temporary Assistance to Needy Families*
0.11
0.04
Food stamps/SNAP*
0.17
0.19
School breakfast/lunch*
0.39
0.46
Social security*
0.08
0.10
Supplemental security income*
0.04
0.05
Unemployment income*
0.02
0.06
Veterans payments*
0.01
0.02
Women Infants and Children*
0.07
0.08
Housing assistance*
0.07
0.07
Medicaid*
0.19
0.30
Private health insurance*
0.68
0.58
N
25,843
25,197
Note: Sample is restricted to children. Source - 1996 and 2009 Survey of Income and
Program Participation.
1 Father's information is used when mother's information is unavailable.
* Indicates a significant difference at p<0.05 from chi-square tests between 1996 & 2009
