Political Behavior, Vol. 27, No. 2, June 2005 (Ó 2005)
DOI 10.1007/s11109-005-3341-9
FAMILIES, DIVORCE AND VOTER TURNOUT
IN THE US
Julianna Sandell and Eric Plutzer
How large a role does the family play in civic development? This paper examines an
important aspect of family influence by tracing the impact of divorce on voter turnout
during adolescence. We show that the effect of divorce among white families is large,
depressing turnout by nearly 10 percentage points. Using data from the National
Education Longitudinal Study of 1988, we demonstrate that the impact of divorce
varies by racial group and can rival the impact of parents’ educational attainment,
which is generally regarded as the most important non-political characteristic of one’s
family of origin. We attempt to explain the divorce effect by examining the mediating
impacts of parental voter turnout, active social learning, income loss, child–parent
interaction, residential mobility, and educational attainment.
Key words: turnout; political participation; civic engagement; youth; family; divorce;
education; residential mobility.
How large a role does the family play in civic development? A generation
ago, political socialization scholars were divided on the question. Some, like
Levin (1961) believed the family, or family structure (Clarke, 1973) was
central; others, such as Connell (1972) thought that institutions such as the
schools and mass media had supplanted the family and relegated it to a
marginal role in political socialization.
Since that time, political scientists have shown that family characteristics
have important consequences for many aspects of political behavior. Adults’
current marital status has consequences for presidential voting (Weisberg,
1987) and political participation (Burns, Schlozman, and Verba 2001; Stoker
and Jennings, 1995); and early parenthood depresses turnout (Plutzer,
2002). Parents’ characteristics are important as well for their children. Parents’ education level and political activity are highly predictive of their chilJulianna Sandell and Eric Plutzer, 219 Pond Laboratory, Department of Political Science,
Pennsylvania State University, University Park, PA, 16802-6200.
133
0190-9320/05/0600-0133/0 Ó 2005 Springer ScienceþBusiness Media, Inc.
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SANDELL AND PLUTZER
dren’s political participation (Verba, Schlozman, and Burns, 2005) and parent marital status is associated with political knowledge and external efficacy
(Gimpel, Lay, and Schuknecht, 2003).
In this paper, we examine the impact of parental divorce on offspring
voter turnout. Although divorce is just one aspect of family structure and
marital transition, it has several characteristics that suggest its importance
for political participation. First, it is the most common marital transition
experienced when children are teenagers. It is estimated that more than
one million children experience divorce every year (US Bureau of the Census, 1998, Tables 160 cited in Amato, 2000) and Bumpass (1990) estimates
that about 40% of all children will experience parental divorce before
reaching adulthood. In our data, divorce is two and a half times as common
as marriage by a resident parent and more than three times as likely as the
death of a parent during the period of adolescence when children are especially likely to internalize a variety of civic orientations and norms (Nie,
Junn, and Stehlick-Barry, 1996; Schuman and Scott, 1989).
Second, the sociological literature shows that divorce has numerous consequences for children. Compared to those with continuously married parents,
children with divorced parents score lower on measures of academic success
(Astone and McLanahan, 1991; Teachman, Paasch, and Carver, 1996), psychological adjustment (Forehand, Neighbors, Devine, and Armistead, 1994),
self-concept (Wenk, Hardesty, Morgan, and Blair 1994), social competence
(Beaty, 1995; Brodzinsky, Hitt, and Smith, 1993), and long term health (Tucker et al., 1997). Divorce also produces economic stress in the short term (Holden and Smock, 1991; Peterson, 1996) and increased residential mobility
(Speare and Goldsheider, 1987). Divorce causes a loss of a potential civic role
model and, in principle, one might imagine cases in which this improves the
home environment and improves political socialization. However, the available research suggests that the impacts are almost always negative, with custodial parents investing less time with school work, being less supportive, and
engaging in more conflict with their children (Amato, 2000).
Third, divorce rates have risen during the last generation, which corresponds with falling voter turnout rates among 18–24 year olds. Figure 1
plots the percentage of children in single parent households because of
divorce against youth turnout rates based on the eligible electorate (as computed by McDonald and Popkin, 2001). The figure shows that divorce rates
rose steadily until 1992 and that (with large idiosyncratic shocks) turnout
shows a general downward trend through 1996 (we expect a lag because the
children represented by the lower line in the figure are not yet eligible to
vote). Of course divorce alone cannot explain the broader turnout decline
but we show that it is part of the explanation.
In this paper, we use longitudinal data on over 6,000 8th graders whose
parents were married when initially interviewed in 1988. As these 6,000 8th
Percentage
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
135
50
Voter Turnout 18-20
Children in Single
Parent Households
Because of Divorce
25
0
1960 19641968 1972 1976 19801984 1988 19921996 2000
Year
FIG. 1. Children in single parent households because of divorce and youth voter
pariticipation trends 1960–2000.
graders pass through middle school and High School, through the spring of
1992, over 450 experienced parental divorce. We estimate the impact of
these divorces on their electoral participation between 1992 and 2000.
Is our exercise simply one of common sense? And why should political
scientists care? We noted that divorce has been empirically linked with
many negative consequences, so it may seem obvious that divorce would
have a negative impact on later political participation. However, such a
common sense prediction does not provide much specificity: should we
expect a negative impact on all children or just a subset? Are the
impacts negligible in magnitude—perhaps dissipating so rapidly that they
are difficult to discern? Or are the effects large enough to stand alongside the traditional core variables in political participation research? Do
all of these negative consequences mediate the impact of divorce or just
one or two? Is the major impact proximate to the family or indirect
through the effects of educational attainment or other major determinants of turnout? It is our intention to provide this kind of specificity
and thereby show when and where the sociological consequences of
divorce also have political consequences.
As to importance, we will show that the impact of divorce can be surprisingly large. More generally, we see this as a first attempt to redirect
the attention of political behavior scholars back to the family. Family
structure does matter and helps us better understand how SES and residential mobility impact participation. The family need not be a ‘‘black
box’’ that is generally ignored in participation research but can be locus
of study that helps us better understand the mechanisms of political
socialization and variation in civic engagement we see in contemporary
politics.
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SANDELL AND PLUTZER
EXPECTATIONS
We expect divorce to contribute to lower turnout via two broad classes of
mechanisms. First are a set of general stresses and dislocations that often
accompany divorce and can impact later educational and income attainment. Second are the ways that divorce can disrupt political socialization via
the processes of social learning.
Stress and Dislocation
Divorce typically leads to a loss of income and reduced standard of living
in the short term (Peterson, 1996) and contributes to longer term economic
loss for children of divorced parents (McLanahan and Sandefur, 1994).
Since the SES of one’s family of origin is strongly related to political participation (Verba et al., 2005) and current SES is a powerful predictor of participation, divorce could contribute to lower turnout through decreased
family income. More generally, divorce is stressful and results in less parental involvement in children’s lives and the interactions they do have are
more likely to be conflictual (Amato, 2000), leaving less opportunity for
positive parental involvement in school and the adolescent’s life in general.
Divorce is disruptive and often leads to residential mobility, uprooting
entire families from their previous neighborhood and political contexts
(Speare and Goldscheider, 1987; South, Crowder and Trent, 1998). Residential mobility greatly reduces turnout (Squire, Wolfinger, and Glass,
1987) and, in particular, of voting in one’s first eligible election (Plutzer,
2002). Mobility can have indirect effects as well, because children from
families who move frequently have lower academic achievement (Ingersool
et al., 1989), more behavioral problems (Wood et al., 1993), and less educational attainment (Aston and McLanahan, 1994; Hagan et al., 1996).
Finally, it is possible that these stressful consequences of divorce act on
turnout indirectly, through lowered educational attainment, typically the
strongest predictor of voting. There is evidence to suggest that parental
divorce is associated with low socioeconomic attainment among children
(Amato, 1999) and the economic hardship associated with divorce leads
some children to abandon plans to attend college (Amato, 2000). Likewise,
Keith and Finlay (1988) estimate that white children whose parents
divorced before age 16 had significantly fewer years of education than similar children who did not experience divorce.
Social Learning
Divorce has been shown (and we will show again below) to reduce the
turnout levels of adults (Stoker and Jennings, 1995). This is likely due to a
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
137
combination of factors including economic stress (Rosenstone, 1982) and
residential mobility (Squire et al., 1987). Whatever the cause, when parents
do not vote the potential for teens to identify with a positive civic role model should be diminished (Hess and Torney, 1968; Jennings, Stoker, and
Bowers, 2001; Verba et al., 2005). This should ultimately reduce youth voter
turnout.
In addition, parents may actively transmit norms of political involvement
to their children (e.g., Jennings and Niemi, 1981; Jennings et al., 2001;
Plutzer, 2002). One important avenue for such direct transmission is
through explicit discussion of politics and public affairs. Divorce reduces
the opportunities for child–parent interaction because one parent is
absent. Research shows that the opportunity of political discussions is
enhanced by the presence of adult household members (Straits, 1991),
suggesting that children living in divorced families simply have fewer
opportunities to discuss politics with their parents than children living in
two-parent households.
In addition, divorce has also been shown to reduce the quality and
amount of youth interaction with the custodial parent (Amato, 2000).
Therefore, even with the parent in residence, political discussion should decrease in frequency and quality.
The impact of race
We have reasons to believe that divorce’s impact may differ across racial
groups but the extant literature provides less specific guidance. Marriage is
less common among African Americans than it is among whites and married
blacks are more likely to divorce. At least since Carol Stack’s (1974) path
breaking work on the black family, it is widely accepted that black families
are more adaptive to the economic and social consequences of single parenthood due to the support given by extended family networks, which also
contribute positively to child development (McAdoo, 1988; Wilson, 1989).
More specifically, divorce has a less harmful effect on the psychological
well-being of black females than on white females (Gove and Shin, 1989),
blacks have fewer problems adjusting to divorce than whites (Monaghan
and Lieberman, 1986), and divorced black women receive more support
from family members than divorced white women (Cherlin, 1981). Subjectively, married African Americans also perceive fewer negative consequences than whites (Rank and Davis, 1996). Research also shows that
negative consequences associated with divorce are less for black children
than white children such that family demographic variables contribute little
to the achievement orientation for African American youth (Ford, 1993) and
family configuration, while important for white students’ achievement, is not
138
SANDELL AND PLUTZER
a factor for black students’ academic achievement (Brady, Tucker, Harris,
and Tribble 1992).
The sociological literature is more mixed for Hispanics, a diverse
pan-racial group with multiple cultures. Our sample size does not permit
separating Hispanics by national subcultures (e.g., separate analyses for
Mexicans and Puerto Ricans) or by race. This too limits our ability to form
specific hypotheses about divorce which may have a differential impact on
(or among) Hispanics. In addition, Cho (1999) has shown that the impact of
standard socioeconomic predictors on voter turnout varies substantially
across racial and cultural groups. Using a 1984 survey of CA residents, Cho
found that the positive effect of education for Latinos on political participation is twice that of the general population while it is completely absent for
Asian Americans suggesting the importance of English proficiency for Latino turnout. An important implication of Cho’s work is that models combining all racial groups must allow the impact of education to vary across
groups (either through interactions or by splitting the samples). Since we
expect that the impact of divorce and SES will vary across groups, we chose
to investigate our expectations for divorce separately for non-Hispanic
whites, non-Hispanic blacks, and Hispanics (of all races).
Previous study
The impact of family transitions generally on political participation was
examined by Dolan (1995) who found that no form of family change—
whether divorce, remarriage or death of a parent—had a significant impact on an index of voting related activities. Dolan’s conclusions were
based on her 1989 survey of 1,352 students enrolled at one of 36 participating colleges and consequently her sample over-represents (future)
college graduates. Most of these students had little political experience beyond the previous fall’s presidential election (60% were under 21 years
old) and the measures of family structure were composites based on retrospective accounts of family transitions when respondents were as young as
5 years old. While Dolan combined all types of family transitions into one
dummy variable, we isolate divorce from other transitions, such as a death
of a parent or remarriage, which may have rather different social, economic, residential and psychological consequences (Amato, 2000). For
these reasons, we believe that the possible impact of divorce impact merits additional investigation. Our data set is generally better to test these
concerns. The sample is much larger, nationally representative (and therefore more racially and economically diverse), has multiple reports of political participation, and nearly contemporaneous reports of family transitions.
Moreover, the detailed set of independent variables allows us to explain
the effects that we do find.
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
139
RESEARCH DESIGN AND METHODOLOGY
To examine the impact of divorce, we utilize the National Education
Longitudinal Survey, 1988–2000 (NELS) produced and distributed by the
National Center for Education Statistics (NCES). The spring 1988 NELS
baseline survey is a nationally representative sample of 8th-graders attending 1,052 schools, both public and private, across the fifty states and the
District of Columbia. The completion rate for the initial wave was 93%
(Curtin, Ingels, Wu, and Heuer, 2002, p. 195). A random subset of the
respondents was selected for follow-up interviews in 1990, 1992, 1994, and
2000 and 79% of those students selected for follow-up actually completed
the entire panel (Curtin et al., 2002, p. 205). Students were asked about
numerous topics including family situation, family relations, and political
participation. In addition to surveying the students, NCES also surveyed
one of the child’s parents in 1988 (87% response rate) and again in 1992
(with a 92% retention rate). Like the students, parents were asked about
family situation, family relations, school characteristics, and socio-economic
status.
To isolate divorce’s impact, our sample is comprised of all 8th graders
whose parents were married—at risk of divorce—at the time of the 1988
interview, who gave valid responses to the turnout questions, and who were
in high school at the time of the second follow-up interview in 1992 (only
these respondents were asked family communication questions detailed
below). Of these 6,894 respondents 458 reported divorce at least once
between 1988 and 1992. In terms of gender, race and parental education, the
students whose parents were married at the time of the initial interview are
slightly more affluent but otherwise similar to the larger sample (see Table 1).
DEPENDENT VARIABLE
Our dependent variable is based on questions during the third and
fourth follow-ups in the spring of 1994 and 2000. Respondents were asked
TABLE 1. Descriptive Statistics for Nationally Representative Sample and
the Subset at Risk of Divorce
Female
Non-white
Parents > HS but < 4 Years of College
Familes with 1987 Income >$35,000
Entire Sample (%)
Respondents at
Risk for Divorce (%)
52.0
28.0
40.7
40.8
52.0
28.0
40.6
50.0
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SANDELL AND PLUTZER
about their voter participation in the 1992 and 1996 presidential elections,
1993 local/state elections, and any elections during 1998/1999. Respondents
were also asked about their voter registration during the fourth follow-up.
Each respondent could report participation in up to four elections plus
being registered in the spring of 2000, yielding a zero to five index. We
multiplied the index by 20 in order to get a dependent variable that ranges
from zero to 100 and reflects the percentage of the five acts with an affirmative report. Table 2 reports the variation in scale scores separately for
each racial/ethnic group in the analysis. In general, there is considerable
variation within each group, with Hispanics having somewhat lower reported turnout than non-Hispanic whites and blacks. Details on question
wording and coding decisions for this and all other variables are contained
in Appendix A.
INDEPENDENT VARIABLES
The main independent variable is reported divorce between 1988 and
1992, a dummy variable coded with a 1 indicating at least one report of
parental divorce in the time span. To minimize missing data, we combined
questions from both student and parent questionnaires. If either the parent
or the child reported a divorce, it is coded as a 1 with all other cases coded
zero. This preserves information in cases where a student or parent did not
complete all questions or was not interviewed in a particular wave of the
survey. Table 3 shows that the incidence of divorce varies by race and ethnicity with non-Hispanic blacks having the highest incidence and Asians the
lowest. Because there were 20 or fewer reported divorces among Native
TABLE 2. Distribution of the Voting Participation Index by Race among
Students at Risk of Parental Divorce in 1988
Whites, not of Hispanic
Origin
Score
0
20
40
60
80
100
Total
Mean
SD
f
652
695
763
1089
1074
1023
5296
56.3
32.9
Blacks, not of Hispanic
Origin
Hispanics, Regardless of
Race
%
Score
f
%
Score
f
%
12.3
13.1
14.4
20.6
20.3
19.3
0
20
40
60
80
100
Total
Mean
SD
60
74
89
125
154
104
606
56.1
32.3
9.9
12.2
14.7
20.6
25.4
17.2
0
20
40
60
80
100
Total
Mean
SD
125
86
94
138
76
69
588
47.4
33.7
21.3
14.6
16.0
23.5
12.9
11.7
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
141
TABLE 3. Incidence of Divorce Among Married Families, By Race and
Ethnicity among Students at Risk of Parental Divorce in 1988
Percent reporting Divorce
between 8th and 12th Grades
N
6.4
10.7
5.7
3.5
8.0
6.6
5,220
590
576
258
250
6,894
White, not of Hispanic Origin
Black, not of Hispanic Origin
Hispanic, regardless of Race
Asian or Pacific Islander
American Indian or Alaskan Native
Total
Americans and Asians, we will restrict our analysis to whites, blacks and
Hispanics.
Variables Prior to Exposure to Divorce
We control for sex (female = 1), 1987 family income, and the average
educational attainment of the respondent’s parents. The parental education
variable indicates the highest degree earned by a parent, and runs from 1
(less than high school) to 6 (PhD, MD, or other advanced degree). Family
income is an ordinal measure with values ranging from 1 (no income) to 15
($200,000 or more). We also created an index of parent–child communication based on a series of questions beginning ‘‘Since the beginning of the
school year, how often have you discussed the following with either or both
of your parents or guardians?’’ This was followed by questions about programs at school, school activities, and curriculum topics. Each communication type is coded with a 0 indicating ‘‘Not at all,’’ a 1 indicating ‘‘Once or
twice,’’ and a 2 indicating ‘‘Three or more times.’’ The scale ranges from 0
(no communication) to a 6 (very frequent communication on all topics). The
reliability of the scale, as indicated by Cronbach’s alpha, is .60. We regard
this measure as an indicator of the overall quality of child–parent interactions and expect scores to decline as a result of stresses brought about by
divorce or other dislocations.
Stresses and Dislocations between 8th and 12th Grade
To assess changes that might result from divorce we include a measure of
1991 family income, the same family communication scale asked in spring
1992 (reliability in 1992 is .78), and an indicator of residential mobility. We
assess mobility by questions asked of both students and parents in the 1992
interview about the number of moves since 1988. This variable is coded 0 if
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SANDELL AND PLUTZER
the family did not move any times, 1 if there was one move, 2 if there were
two moves, and 3 if there were three or more moves within the time span.
Resources for Social Learning
Hess and Torney (1968) suggest that young people may identify with parents such that parents who are politically active will serve as positive role
models. Others have shown that parental political participation is a powerful
predictor of offspring participation (Verba et al., 2005) and especially in the
first eligible election (Plutzer, 2002).
Unfortunately, the NELS-88 did not ask parents any questions about
their turnout or campaign participation. We therefore created a proxy variable that we interpret as the probability that parents voted in the most
recent presidential election. We start by estimating a logistic regression
equation of voter turnout in the previous presidential election from the
General Social Survey. The independent variables are the major predictors of adult turnout that are available in both data sets: sex, age, race,
education, income, employment status, and southern residence (we were
unable to measure homeownership or frequency of religious attendance).
All variables were coded in a way that permits precise replication using
the NELS-88 (see Appendix A). Since we want to account specifically for
the effect of divorce on parents, we also include a GSS divorce variable
that asks whether the respondent has gotten divorced within the past
5 years. We limited our analysis to respondents who have a teen living
within their household in order to closely match the parent sample of the
NELS-88.
The results for the logistic regression are reported in Appendix Table A.1
and the results for the major SES and demographic variables are quite similar to more comprehensive models reported by Wolfinger and Rosenstone
(1980) and Rosenstone and Hansen (1993) on nationally representative samples. The GSS model indicates that turnout is lowered by recent divorce,
living in the south, and being black and is increased with higher age, income and education.
We then use the prediction equation estimated from the GSS sample, to
yield a prediction equation that we apply to the NELS-88 parental sample.
Each NELS-88 parent is then assigned a probability of voting in the most
recent presidential election (an out-of-sample Ŷ). These probabilities range
from 6% to 100%, with a mean of 72% and a standard deviation of 18%.
The high mean reflects overreporting but the measure has considerable variance allowing us to rank parents from least likely to have voted to those
who were nearly certain to report a vote, had they been asked.
Hess and Torney (1968) also discuss more active socialization by parents
that leads to an accumulation of resources that facilitate participation. The
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
143
NELS-88 includes one measure from the 12th grade follow-up that allows
us to measure this. Teens were asked how frequently (never, sometimes, often) they discussed current events with their parents, which is our second
measure of social learning. Unlike the communication scale, this explicitly
taps into political content and, after controlling for the overall level of communication, should provide a good measure of active transmission of political ideas and information.
Educational Attainment
One possible causal path is for divorce to reduce the later educational
attainment of the children. Students who completed 4 years of higher
education in 4 years plus a summer would have attained their degree a
few months before the 1996 presidential election. We can calculate whether or not each respondent earned a college degree before any particular event in our participation scale but we developed alternative
measures that we think do a better job of capturing education at a time
it might impact participation. We utilized a detailed set of monthly status
questions from the 1994 interview to create a measure of educational
attendance during the 1993–1994 academic year—what would be the
sophomore year of college if a student continued on to higher education
directly after high school.
This measure is based on status reports during September, October,
and November of 1993 and February, March and April of 1994. A student who reported full-time attendance at a 4-year college or university
during all 6 months received a score of 100%. A student, who reported
half time attendance during all 6 months, or full time attendance for
3 months, would receive a score of 50%. Students attending less than
half time are scored as 25% for that particular month. Thus the scale
ranges from 0% to 100%. The scale has a high correlation with parents’
education (r=.45) and, as we will show, is a powerful predictor of turnout. We created a similar score for attendance at two year colleges. This
is negatively correlated with parents education (e.g., if a parent completed college, children tend to score zero on this measure) but is also a
powerful predictor of turnout.
We believe these measures are better than traditional indicators of
degrees earned because they capture educational experiences before
respondents would have had a chance to graduate from college, which for
most respondents would have been after two, or even three of the elections
tapped by our dependent variable. As we note below (endnote 4), earning a
degree explains no additional variation in political participation beyond that
captured by these two measures.
144
SANDELL AND PLUTZER
RESULTS
We first estimate a baseline regression model separately for whites, blacks
and Hispanics. In this baseline model, we control for sex, parental education, family income and frequency of child–parent discussions about school
during 1988. Because schools served as primary sampling units, we report
Huber-White robust standard errors that adjust for clustering within
schools.
Finally, it is useful to be cognizant of the fact that the NELS oversamples
certain minority groups and school types. Because education researchers
were especially interested in having a sufficient number of private schools
in the data set, these were oversampled. In addition, Asians and Hispanic
students within selected schools had a higher probability of selection. To account for deliberate oversampling of both schools and students, and differential non-response, the NCES calculated a series of weights to apply to
different types of subsamples and analyses. We utilize their longitudinal
weight (F4PNLWT), which is intended to allow the sample to generalize to
the population of all students eligible to be interviewed in 1988 (see Curtin
et al., 2002, chapter 3, especially pp. 64–93). Thus, our analytic sample
should be representative of that proportion of the roughly 2.9 million children enrolled in 8th grade in 1988 who completed high school. Table 4
presents the OLS regression slopes, robust standard errors, and statistical
significance.
The results show that divorce has a powerful, negative impact on turnout
among whites but has no significant impact among either African Americans
or Hispanics. We will return to the non-findings for minorities below. In
the following sections, we seek to understand why the experience of divorce
during adolescence has such a profound impact on white youth.
TABLE 4. Baseline Models Examing the Impact of Divorce by Race
on Voter Turnout
Whites (N=4,840)
B
Divorce
Parental Education
Female
Parent–Child
Communication
Family Income
Constant
R2
Blacks (N=392)
Robust
S.E.
p
B
Robust
S.E.
9.93
3.64
.54
3.42
2.46
.61
1.25
.47
**
**
9.70
1.97
1.16
1.57
7.31
2.37
5.14
1.68
1.52
13.65
.08
.40
5.43
**
**
2.36
32.01
.04
1.01
11.64
**
Hispanics (N=686)
p
*
**
B
Robust
S.E.
p
.64
1.88
.53
2.33
5.84
1.60
3.18
1.15
*
1.68
16.86
.05
.84
8.05
*
*
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
145
Before we attempt to explain the impact of divorce it is useful to appreciate how large the effect is among white youth. Holding parental education,
family income, sex, and parent–child communications constant, divorce decreases voting participation by roughly 10%. For comparison, the estimated
effect of having a college educated parent compared to one who only finished high school (two steps on the education measure) would be just over
7%. Thus the effect of divorce is comparable to the net impact of parental
education for white youth.
We should also note that children who talk frequently with their parents about their school work have considerably higher turnout, an effect
that is strong and significant among whites and Hispanics. As we will
show, falling communication levels do not account for the divorce effect
but suggest that the internal dynamics of family life have important impacts that are independent of socioeconomic status and merit further
attention.1
Social Learning, Stress & Dislocation, and Educational
Attainment
Among white youth whose parents were married in 1988, divorce significantly lowered parental voter turnout by 9% and decreased current events
discussion by 8%. Divorce also led to reduced scores on the communication
scale by about a fifth of a point, diminished income by more than a full category (roughly $10,000), and increased the probability of moving from 16%
to 33%. Divorce was especially associated with multiple moves, more than
tripling the likelihood of moving more than once between 8th and 12th
grade. Clearly, the white teenagers in divorced families experienced a drop
in their home politics and resources for social learning, the stress of mobility, income loss, and found themselves communicating less frequently with
their parents than would have been expected based on their base year communication scores.
Do these changes account for their lower voter turnout? To see we
added these measures to our baseline model. The results are reported in
Table 5. The first column reports the social learning model containing all
previous regressors plus the estimated probability of parental voter turnout
in the most recent presidential election and the frequency of discussion
about current events. The parental voter turnout variable, scaled from zero
to one hundred, has a positive effect and is statistically significant. Having a
parent with a 75% probability of voting results in a 19% increase on offspring turnout compared with a parent with a 25% probability of voting.
Likewise, the amount of current events discussion has a large positive effect
on voter turnout and achieves statistical significance. Of special interest is
that the addition of these variables reduces the divorce effect from 9%
B
p<.05,
*
p<.01,
**
p<.001.
***
Divorce
2.32
Parental Education
.62
Female
1.69
Parent–Child Communication 1988
1.96
Family Income 1987
.30
Parental Voter Turnout
.35
Current Events Discussion 1992
7.53
Family Income 1991
–
Parent–Child Communication 1992
–
Number of Moves 1988–1992
–
1993–1994 Enrollment Status in 2 Year College
–
1993–1994 Enrollment Status in 4 Year College
–
Constant
10.79
Adjusted R2
.09
Number of Cases
4081
Independent Variables
2.63
.69
1.30
.47
.42
.08
.93
–
–
–
–
–
7.15
–
–
–
–
–
–
–
–
–
–
***
***
–
***
–
–
–
Robust S.E. p
3.43
2.58
.46
2.17
.79
–
–
.08
2.73
5.22
–
–
27.04
.09
4215
B
2.85
.59
1.18
.46
.60
–
–
.58
.42
1.17
–
–
4.12
–
–
–
–
***
–
–
***
***
–
–
–
–
***
–
***
–
Robust S.E. p
8.37
2.24
.09
2.86
.97
–
–
.14
–
–
.15
.12
19.91
.11
4840
B
2.30
.62
1.23
.47
.41
–
–
.56
–
–
.02
.02
5.24
–
–
–
–
***
***
***
–
–
–
–
–
*
***
–
***
***
Robust S.E. p
OLS Regression Slopes and Robust Standard Errors
TABLE 5. Explaining The Impact of Divorce on the Electoral Participation of White Respondents
1.46
4.04
.10
.07
20.66
.12
4038
.75
.19
.64
1.37
.48
.27
5.56
B
.46
1.12
.02
.02
4.87
–
–
(2.30)
.68
1.19
.45
.57
.07
.99
–
–
***
***
***
***
**
***
***
–
**
–
–
–
Robust S.E. p
146
SANDELL AND PLUTZER
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
147
to 2%. To see which variable had a larger mediating effect on divorce, we
ran the model separately for parental voter turnout and current events discussion. The results indicate that, though the variables combined have a
large effect on divorce, current events discussion has a bigger mediating
effect on voter turnout.2 This suggests that divorce, by reducing parental
turnout and, especially current events discussion, influences offspring turnout through social learning.
The second column reports the stress and dislocation model that adds the
1992 parent–child communication scale, 1991 family income, and residential
mobility. The results indicate that the communication scale has a positive
impact on electoral participation; that is, more communication is associated
with higher turnout. Family income in 1991 has no impact on youth voter
turnout, while the number of residential moves has a depressing effect.
Most importantly, the addition of these three variables causes the net effect
of divorce to decrease from 9% to 3% and become insignificant. To precisely identify which of the three variables mediate the effect of divorce, we
estimated three additional models with each explanatory variable added
alone. These show that the large impact of divorce among white students
acts primarily through the disruptions associated with residential mobility.
Including the significant communication scale alone did not appreciably
reduce the divorce effect.3
We also explore the impact of the young citizens’ own educational
attainment. In our data, 41% of teenagers whose parents did not divorce
were enrolled full time in a four year college in 1993–1994; in contrast,
only 31% of those who experienced divorce in adolescence were similarly
enrolled. To see if this difference further erodes the impact of divorce
we added two measures of enrollment status to the model in the third
column. Although both educational attainment variables were powerful
predictors of turnout, the slope estimate for divorce is relatively
unchanged. Thus, education matters a great deal but does not help us
explain the impact of divorce.4
The final column in Table 5 presents a comprehensive model. Within the
comprehensive model both the social learning variables (parental voter
turnout and current events discussion) remain highly significant as does residential mobility. Most notably, the divorce effect decreases close to zero
(.75) and is no longer significant. While the education variables remain
significant, the divorce effect is mediated most by parental voter turnout,
current events discussion, and residential mobility. These results provide
strong evidence that divorce acts through two pathways: social learning
through decreased parental voter turnout and current events discussion; and
stress and dislocation through increased mobility.
To more precisely examine the relative importance of these two pathways we also estimated a structural equation model. This model is
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SANDELL AND PLUTZER
described in Appendix B and permitted decomposing the total effect of
divorce into 15 specific indirect paths. The total effect of divorce is calculated net of antecedent variables for sex, parent education, 1987 family
income and 1988 communication (i.e., comparable to the white sub-sample in Table 4). Our model, estimated by AMOS, fit the data well (GFI
= .990, CFI = .981) and shows that 39% of divorce’s impact flows
through the stressors, 50% through the two social learning indicators,
and 11% through educational attainment (two-step paths through stressors or social learning variables and subsequently through education measures). Like estimates from all structural equation models, this
partitioning is sensitive to causal assumptions but is consistent with the
inferences that we draw from the sequence of OLS regression models in
Table 5.
DISCUSSION & IMPLICATIONS
Divorce is one of those factors that Miller and Shanks (1996) refer to as
‘‘non-political.’’ Yet it has important political consequences. Earlier in this
paper we argued that common sense inferences about divorce were not
very specific and, in any case, merited empirical testing. The results show
that two common sense inferences turned out to be invalid. Parental
divorce is related to lower family incomes and lower educational attainment—the core elements to the traditional SES model of participation.
Yet neither accounted for the very large impact of divorce among young
white citizens.
In contrast, we find strong evidence that divorce acts through three
other core variables in participation research: parental political participation,
current events discussion, and residential mobility. Jennings et al. suggest
that parental participation is directly linked to the frequency of political
discussion between parents and children and as political discussion increases so does the transmission rates, ‘‘particularly on topics of general
political significance and salience’’ (2001, 21; see also Verba et al., 2005).
As a result, children become politically knowledgeable if they live in a
highly politicized environment, which encourages adult voter turnout. Our
results bear this out, with current events discussions explaining a large
portion of the total effect of divorce. We could not measure parental turnout directly but our results suggest at least a modest role for this aspect of
the home environment as well.
The Role of Residential Mobility
Though residential mobility is a primary stressor of divorce leading to decreased voter turnout, we are unsure as to what exactly it is about residen-
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
149
tial mobility that disrupts participation. Here we measure the exact number
of moves the respondent’s family experienced between 1988 and 1992, but
what is it that is crucial to voting? The extant literature suggests four possible explanations. The literature on mobility and turnout would lead us to
imagine that residential mobility would lead to a decline in the parents’ voter participation, which would then be ‘‘inherited’’ by the children. Squire
et al. (1987) show that adults who moved in the previous 6 months had
turnout rates 16% lower than those who had been in the same residence
for more than 6 years. Plutzer (2002) shows that when parents do not report voting, the probability of twenty-something citizens voting in their first
eligible election declined by 21%. As a rough approximation, we can
combine these two empirical findings and they suggest as much as a 3%
decline in turnout via parents’ participation (i.e., P(A and B) =
P(A)*P(B) = .16*.21 = .034). We lack a direct measure of parental political
participation but it seems plausible that this is a major explanation for the
strong mediating impact of residential mobility.
Second, moving places considerable stress on the student, decreasing the
child’s short and long term well-being and eventual participation. Amato
and Sobolewski (2001) cite a dozen recent studies that show that ‘‘adults
with divorced parents, when compared with adults with continuously
married parents, report greater unhappiness, less satisfaction with life, a
weaker sense of personal control, more symptoms of anxiety and depression, and greater use of mental health services.’’ Rosenstone (1982) showed
that citizens rebound quickly from the short term stresses of unemployment
but there is little empirical work on the impact of chronic hardships and
stresses on political participation. We lack the data to empirically assess this
idea here but, again, we believe that it may account for at least a part of
the impact of residential mobility.
Third, sociological literature suggests that children of divorce are much
more likely to move to a significantly poorer neighborhood than children in
stable, two-parent families due to the decline in family income (South et al.,
1998). Consequently, the presence of poor neighborhoods has been shown
to reduce educational attainment (Brooks-Gunn, Duncan, Klebanov, and
Sealand, 1993; Crane 1991; Duncan 1994; Garner & Raudenbush 1991),
school performance (Dornbusch et al., 1991), cognitive development
(Brooks-Gunn, Duncan, Klebanov, and Sealand, 1993), increase delinquent
behavior (Elliott et al., 1996), and increase teenage childbearing (Billy and
Moore, 1992), all of which could also be linked to voter turnout.
Lastly, frequent mobility may cut community ties. South et al. (1998)
suggest that residential mobility ‘‘places the children of divorce at a dual
disadvantage, because it disrupts both the social capital of the family
(when one parent leaves the household) and the child’s access to community-based social capital, as neighborhood ties are severed upon
150
SANDELL AND PLUTZER
moving’’ (669). We do not have direct reports from the main respondents but have some suggestive data from the parental interviews. Parents who moved during the 1988–1992 period were 10% less likely to
report feeling ‘‘a part of the neighborhood.’’ Whether or not this is an
indicator of a broader sense of community alienation, and whether this
would be transferred to a similar feeling held by the children is impossible
to say, but might be illuminated by other data sets.
The Puzzle of Minorities
We found large effects among whites but no impact of divorce among
minorities. We believe this is because divorce has differential consequences
across racial and ethnic groups. For example, Amato and Keith (1991) find
that divorce has consistently negative impacts among whites but less consistent impacts among African Americans and Hispanics.
In the NELS data we find evidence of the conditional impact of divorce.
While divorce doubles the likelihood of residential mobility for whites and
Hispanics, it is actually associated with greater stability among African
Americans (only 11% of African American adolescents experiencing divorce
moved compared to 22% of those whose married parents remained
married). Similarly divorce leads to a drop in parent–child communication
among whites (.40) and blacks (.25) but not among Hispanics who show a
statistically insignificant increase. Thus, divorce has more consistently negative consequences for white adolescents and this may account for its greater
impact among whites.
CONCLUSION
White citizens comprise roughly three quarters of the electorate and the
turnout rate of young voters has been falling steadily since the mid-1970s. We
have shown that the experience of divorce is sufficiently consequential to result
in a very large drop in voter turnout among young white citizens. Indeed, the
impact of divorce rivals the large impact of parent’s education. As such this research provides a small piece of the puzzle of declining youth turnout.
Previous literature on parental voter turnout, education attainment, current events discussion, income, parent–child communication, and residential mobility suggested possible causal paths through which divorce could
lower turnout. Only three of these, parental voter turnout, current events
discussion, and residential mobility, were shown empirically to mediate the
effect of divorce. If policy makers are unable to lower the rate of divorce,
those interested in fostering civic engagement might effectively target
young people who have recently moved or experienced divorce. Certainly,
civic engagement programs based in schools may be able to identify both
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
151
recent migrants and children living with a single parent or, alternatively,
target schools with high percentages of children from such families.
More broadly, this research illustrates how one aspect of family dynamics has important political consequences. Twenty five years ago, Jennings
and Niemi acknowledged that the political consequences of the family
‘‘were more variable than had been assumed’’ (1981, p. 76) and this variability has prevented the development of anything approaching a unified
view of how the family operates to enhance or retard civic development.
Our research reinforces the conditional nature of family effects—in this
case we find that the negative consequences are restricted to whites. It
also provides an illustration of why the family merits considerably more
attention from scholars of political participation. In a recent paper, Verba
et al. (2005) use key aspects of the Civic Voluntarism Model to help clarify how the SES of one’s family of origin influences political participation.
We believe it shall be equally fruitful to focus on the complexities of family structure and family transitions. We have examined an important, but
not the only, type of family transition and divorce is often seen as the first
stage of many family changes (Amato and Sobolewski, 2001). We believe
that future work should carefully examine family formation—the timing
and the number of children along with whether or not that formation is
accompanied by marriage. These events have the potential to also set in
motion consequences that could substantially increase or decrease turnout
for children raised in those families. In this sense, we see opportunities in
developing theories, concepts, and data that allow detailed examination of
family characteristics that exert influence well before the establishment of
social and economic status in young adulthood and alongside the dynamics
of socioeconomic status in the family of origin.
Acknowledgments. The authors gratefully acknowledge that this research was
supported by a grant from The Russell Sage Foundation and we thank three
anonymous referees for their helpful comments and suggestions. Of course, all
conclusions and interpretations are that of the authors.
APPENDIX A: CODING OF VARIABLES USED IN STUDY
Dependent Variable
Voter Turnout: VOTEPCT, created by combining answers from NATELEC, VOTEPRES, F4IVPRE, F4IVANY, and F4IRVOTE. NATELEC
asked during the F3 follow-up study used the following ‘‘During the past
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SANDELL AND PLUTZER
12 months, have you voted in a local, state, or national election?’’ 0 = No,
1 = Yes. VOTEPRES asked F3 respondents ‘‘Did you vote in the 1992
Presidential election?’’ 0 = No, 1 = Yes. F4IVPRE asked during the F4
follow-up study asked respondents the following: ‘‘Did you vote in the
1996 Presidential election?’’. 0 = No, 1 = Yes. F4IVANY asked F4 respondents ‘‘In the last 2 years, have you voted in any local, state, or national
election?’’ 0 = No, 1 = Yes. F4IRVOTE asked F4 respondents ‘‘Are you
currently registered to vote?’’ 0 = No, 1 = Yes. All variables were added
together to create, ALLVOTE_, a five point scale and 1 was subtracted
from F4IRVOTE in order to separate those who abstained from voting
but were registered .1 was added to ALLVOTE_ and then it was multiplied by 20 in order to create VOTEPCT, a 0–100% voter participation
range.
Independent Variables
Parental Divorce from 1988 to 1992: F2DIVOR created by combining
answers from F2PDIV, F1S99C, and F2S96B. F2PDIV was created from
the variable F2P7, which asked parents in the F2 survey ‘‘What is your current marital status?’’. 0 = Not divorced 1 = Divorced. To save cases,
answers from student questions were also used. F1S99C asked students
during the F1 wave ‘‘Lots of things happen in families that may affect
young people. In the last 2 years, have any of the following happened to
your family? C. My parents got divorced or separated’’. 0 = No, 1 = Yes.
F2S96B asked students during the F2 survey the same question again and
answers were coded identical to F1S99C. The F2DIVOR variable first was
equaled to the F2PDIV variable and then was coded as the following:
0 = No reports of divorce and 1 = At least 1 report of divorce: 0 if F2PDIV
was missing and F1S99C and F2S96B both were 0, 1 if F2PDIV was missing and F1S99C or F2S96B were 1.
Parental Voter Turnout: Created from the GSS. Variables included in
the regression analysis to predict parental voter turnout include DIVOR5
indicates divorce in the last 5 years and is measured as a dummy variable
where 1 = Yes 0 = No; AGE measured as a dummy variable with 20–
28 years old as the omitted dummy; SOUTH measured as 1 = south
0 = other region; EDUCATION measured as a dummy variable where less
than HS diploma is the omitted variable; FULLTIME employment where
1 = Yes, 0 = No; PARTIME employment where 1 = Yes 0 = No; BLACK,
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
153
OTH, and HISP as three separate race dummy variables; and FAMINCOME as a continuous variable measured in $1,000s. The regression analysis
from the GSS is shown below.
Current Events Discussion: F2S99H, which asked students in 1992 ‘‘In
the first semester or term of this school year, how often did you discuss the
following with either or both of your parents or guardians? Community,
national, and world events?’’ 1 = Never 2 = Sometimes 3 = Often.
Total Family Income during 1987/1991: BYP80 and F2P74, the question
asked parents during the BY (F2) study the following: ‘‘What was your total
family income from all sources in 1987 (1991)? (If you are not sure about the
amount please estimate)’’ .1 = None, 2 = Less than $1,000, 3 = $1,000–2,999,
4 = $3,000–4,999, 5 = $5,000–7,499, 6 = $7,500–9,999, 7 = $10,000–14,999,
8 = $15,000–19,999, 9 = $20,000–24,999, 10 = $25,000–34,999, 11 = $35,000–
49,999, 12 = $50,000–74,999, 13 = $75,000–99,999, 14 = $100,000–199,999,
15 = 4$200,000 or more. In the event that F2P74 was missing, the mean was
used.
Parental Education: BYPARED by the creators of NELS-88 and was
constructed using the parent variables BYP30 and BYP31 and the student
variables BYS34A and BYS34B, which all asked about parental education.
With the parent and student information, BYPARED captured the highest
degree earned by either parent. BYPARED was then coded as 1 = Did not
finish High school, 2 = High School grad or GED, 3 => High School &
<4 Year Degree, 4 = College Graduate, 5 = MA/Equivalent, 6 = PhD, MD,
or other, 7 = Don’t Know.
BY (F2) Communication Scale: BYCOMM and F2COMM created from
BYS36A (F2S99A), BYS36B (F2S99B), and BYS36C (F2S99C), which asked
students the following questions in both the BY and F2 waves: BYS36A
(F2S99A) = ‘‘Since the beginning of the school year, how often have you discussed the following with either or both of your parents or guardians? A.
Selecting courses or programs at school’’. BYS36B (F2S99B) = ‘‘Since the
beginning of the school year, how often have you discussed the following with
either or both of your parents or guardians? B. School activities or events of
particular interest to you’’. BYS36C (F2S99C) = ‘‘Since the beginning of the
school year, how often have you discussed the following with either or both of
your parents or guardians? C. Things you’ve studied in class’’. All variables
were coded as 0 = Not at all, 1 = Once or Twice, 2 = Three or more times. To
154
SANDELL AND PLUTZER
TABLE A.1. Logistic Regression of Most Recent Presidential Turnout, GSS
(N¼7,448)
OLS Regression Slopes and Standards Errors
B
Divorce in last 5 Years
29–33 Years Old
34–38 Years Old
39–43 Years Old
44–48 Years Old
49–58 Years Old
59 Years and Older
South
HS Education
Junior College
College
Graduate
Female
Full Time Employment
Part Time Employment
Black
Other Race
Hispanic
Family Income in $1,000s
Constant
.32*
.61*
.82**
1.22**
1.41**
1.71**
1.76**
.16
1.22**
1.53**
2.13**
2.52**
.11
.07
.17
.07
.99**
.16
13.41**
1.82**
S.E.
.15
.25
.20
.20
.22
.23
.29
.11
.12
.28
.25
.41
.11
.13
.18
.15
.26
.20
2.45
.25
save cases, if one question was missing, the average of the other two valid
questions was used as a replacement. For example, if BYS36A was missing, but
BYS36B and BYS36C was valid, then BYS36A = (BYS36B+BYS36C)/2. In the
event that any of the three values was missing, the midpoint was used instead.
The same process was completed for the F2 communication variables.
Residential Mobility from 1988 to 1992: NUMMOVES created from
combining F1S99A, F2S96A, and F2S102. F1S99A (F2S96A) asked students
during the F1 (F2) wave the following ‘‘Lots of things happen in families that
may affect young people. In the last 2 years, have any of the following happened to your family? A. My family moved to a new home’’. 0 = No, 1 = Yes.
F2S102 asked students during the F2 survey ‘‘How many times have you
moved since January 1, 1988’’ 1 = None, 2 = 1 time, 3 = 2 times, 4 = 3 or
more times. NUMMOVES was created first by equaling it to F2S102. If either
F1S99A or F2S96A = 1, then NUMMOVES = 2 (meaning 1 move). If
F1S99A and F2S96A = 1, the NUMMOVES = 3 (2 moves). NUMMOVES
was then recoded to the following 0 = No moves, 1 = 1 move, 2 = 2 moves,
3 = 3 or more moves.
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
155
Sophomore status in 4 year College (Sophomore status in a 2 year
College): SOPH4/SOPH2 created from combining answers from
ENRL0993 ENRL1093 ENRL1193 ENRL0294 ENRL0394 and
ENRL0494, which asked respondents in F3 about their full and part time
TABLE A.2. Structural Coefficients
Endogenous Variable
Predictor Variable
Standardized Estimate S.E.
p
Divorce
Parental Education
Female
Family Income 1987
Parent–Child Communication 1988
0.02
0.06
0.01
0.01
0.00 0.19
0.01 ***
0.00 0.70
0.00 0.58
Parental Education
Family Income 1987
Divorce
Parent–Child Communication 1992
Parental Education
Female
Family Income 1987
Parent–Child Communication 1988
Divorce
Number of Moves 1988–1992
Parental Education
Family Income 1987
Divorce
Current Events Discussion 1992
Parental Education
Female
Family Income 1987
Parent–Child Communication 1988
Divorce
Enrollment in 2 Year College
Parental Education
Female
Family Income 1987
Divorce
Family Income 1991
Parent–Child Communication 1992
Number of Moves 1988–1992
Current Events Discussion 1992
Enrollment in 4 Year College
Parental Education
Female
Family Income 1987
Divorce
Family Income 1991
Parent–Child Communication 1992
0.15
0.58
0.17
0.02
0.01
0.10
0.18
0.16
0.05
0.23
0.05
0.02 ***
0.05 ***
0.02 0.01
0.02 ***
0.10 0.00
0.07
0.15
0.14
0.01
0.01
0.05
0.14
0.01
0.07
0.23
0.04
0.01 ***
0.02 0.75
0.01 ***
0.01 ***
0.05 0.00
0.07
0.03
0.02
0.02
0.02
0.00
0.06
0.02
0.54
1.07
0.40
2.40
0.38
0.40
0.72
0.91
0.25
0.03
0.11
0.01
0.07
0.12
0.70 ***
1.40 0.03
0.53 ***
3.13 0.46
0.50 ***
0.52 ***
Family Income 1991
***
***
***
***
***
***
***
0.09
0.29
0.15
0.50
0.98
***
0.42
156
SANDELL AND PLUTZER
Table A.2. Continued.
Endogenous Variable
Predictor Variable
Standardized Estimate S.E. p
Number of Moves 1988–1992
Current Events Discussion 1992
0.12
0.06
0.94
1.19
***
***
Parental Education
Family income 1987
Divorce
0.46
0.44
0.11
0.15
0.09
0.66
***
***
***
Parental Education
Female
Family Income 1991
Parent–Child Communication 1992
Number of Moves 1988–1992
Current Events Discussion 1992
Parental Turnout
Enrollment in 2 Year College
Enrollment in 4 Year College
Divorce
0.01
0.02
0.02
0.08
0.10
0.12
0.12
0.11
0.11
0.00
0.60 0.64
1.00 0.31
0.31 0.31
0.37 ***
0.67 ***
0.85 ***
0.05 ***
0.02 ***
0.01 ***
Parental Turnout
Electoral Participation
TABLE A.3. Unanalyzed Correlations & Correlated Errors
Exogenous Variables
r
Parental Education & Parent–Child Communication 1988
Parental Education & Family Income 1987
Family Income 1987 & Female
Parental Education & Female
Parent–Child Communication 1988 & Family Income 1987
Parent–Child Communication 1988 & Female
.21
.52
.01
.02
.18
.14
Residuals
e (1988 communication) & e (1992 communication)
e (2 yr college) & e (4 yr college)
.44
.43
Table A.3 reports the unanalyzed and residual correlations while table A.4 reports the variance
explained for each endogenous variable.
TABLE A.4. R2 for Each Endogenous Variable
Endogenous Variable
Divorce
Current Events Discussion
Number of Moves 1988–1992
Parent–Child Communication 1992
Family income 1991
Enrollment in 2 Year College
Enrollment in 4 Year College
Parental Turnout
Electoral Participation
R2
0.00
0.11
0.06
0.15
0.48
0.01
0.23
0.63
0.11
0.00
0.00
0.00
0.15
0.05
0.58
0.02
0.11
0.44
0.00
0.00
0.16
0.00
0.03
0.03
0.00
0.02
0.00
0.00
0.00
0.23
0.01
0.23
0.01
0.07
0.06
0.01
0.46
0.01
0.25
0.07
0.15
0.18
0.07
0.02
0.14
0.06
0.00
0.12
0.01
0.11
0.00
0.00
0.17
0.02
0.00
0.05
0.02
0.00
0.00
0.00
0.14
0.00
0.04
0.00
0.10
0.12
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.08
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.07
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Table A.5 reports the direct effects of all variables on one another and these serve as the basis for calculating the contribution of all 15 possible paths from
divorce to turnout in Table A.6.
Divorce
Current
Events
Discussion
Number of
moves
1988–1992
Parent–Child
Communication
1992
Family Income
1991
Enrollment in
2 Year College
Enrollment in
4 Year College
Parental Turnout
Electoral
Participation
Family Parent–Child
Current
Parent–Child Family 2 Year 4 Year
Income Communication Parental
Events
Numer of Communication income College College Parent
Female 1987
1988
Education Divorce Discussion Moves
1992
1991 Enroll. Enroll. Turnout
TABLE A.5. Standardized Direct Effects
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
157
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SANDELL AND PLUTZER
TABLE A.6. Indirect Paths of Divorce on Voter Turnout
Indirect Effect Through
FAMINC
F2SCOMM
NUMMOVES
F2S99H
VOTEPROB
SOPH2
SOPH4
FAMINC*SOPH2
F2SCOMM
NUMMOVES
F2S99H
FAMINC
F2SCOMM
NUMMOVES
F2S99H
= .174*.018
= .046*.080
= .140*.097
= .044*.124
= .107*.117
= .024*.107
= .011*.109
= .174*.015*.107
*SOPH2 = .046*.001*.107
*SOPH2 = .140*.064*.107
*SOPH2 = .044*.015*.107
*SOPH4 = .174*.071*.109
*SOPH4 = .046*.121*.109
*SOPH4 = .140*.116*.109
*SOPH4 = .044*.062*.109
Total Indirect Effect
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
.003
.004
.014
.005
.013
.003
.001
.000
.000
.001
.000
.001
.001
.002
.000
.036
classes in either 2 or 4 year colleges for September, October, and November of 1993 and for February, March, and April of 1994 (the academic
school year). Full time attendance = 1, part time attendance = .5, and less
than part time attendance = .25. Likewise, variables were divided into 2 and
4 year colleges and coded on a percentage scale ranging from 0% to 100%.
A student who reported full-time attendance at a 4 year college or university during all 6 months received a score of 100%. A student who reported
half time attendance during all 6 months, or full time attendance for
3 months, would receive a score of 50%. Students attending less than half
time are scored as 25% for that particular month.
APPENDIX B: STRUCTURAL EQUATION ESTIMATION
To estimate a structural equation model, we assumed that parental education, family income in 1987, respondent sex, and base-year child–parent
communication were exogenous. All other variables were considered endogenous. The model was estimated by Amos. Base year income and communication were assumed to influence turnout through their lagged counterparts
or indirectly through other variables, though relaxing these assumptions had
no impact on any estimates or substantive conclusions. In addition, we have
no basis for hypothesizing an effect of gender on likelihood of residential
mobility and 1991 family income so these effects are constrained to zero.
In addition, we compared models with all independent residuals with models that permitted correlated errors among identical questions asked at both
FAMILIES, DIVORCE AND VOTER TURNOUT IN THE US
159
waves (parent–child communication) and the two college enrollment measures,
which are partially constrained to be complements of one another (someone
enrolled in a 2-year college is unlikely to be enrolled in a 4 year college).
Allowing these correlations improved the fit of the model (Goodness of Fit Index increased from .961 to .987). Since we discovered no direct effect of
divorce in our OLS models, we then constrained the direct effect of divorce to
be zero. The GFI increased modestly (to .989) and the fit was not significantly
worse (chi square = .189, p=.664) so by conventional standards our ‘‘best’’
model constrains the direct effect of divorce on turnout to zero.
The standardized coefficients are reported in Appendix Table A.2 and the
direct effects on turnout (near the bottom of the table) conform quite closely to reported effects in model 5.4.
NOTES
1. We ran the model for the white sample with parental education and income represented by
categorical dummy variables, to account for any nonlinear effects that might spuriously get
absorbed by divorce. The divorce impact showed little change (B=9.83) and still achieved
statistical significance. Hence, the divorce impact is not an artifact of nonlinear independent
variables being treated as intervals. In addition, we investigated whether the impact of divorce varied by income, as suggested by a reader of an earlier version of the paper; the
interaction was essentially zero and did not approach statistical significance.
2. The divorce effect decreases from 9.93 to 6.00 and is still significant at the 95% level
with the addition of the parental voter turnout variable. The divorce effect decreases from
9.93 to 4.83 with a p-value of .061 with the addition of the current events variable.
3. The divorce effect decreases from 9.93 to 9.82 and is still significant at the 99% level
with the addition of the 1991 family income variable. The divorce effect decreases from
9.93 to 9.26 with a p-value of .000 with the inclusion of the 1992 family communication
scale. The divorce effect decreases to 4.02 and is no longer significant at the 95% confidence level with the inclusion of the residential mobility variable. These results are available
from the authors upon request.
4. We ran Model 5.4 with a variable that measured the completion of a college degree by the
1996 Presidential election (4.5 years after completing high school). The results were essentially unchanged and this variable was not statistically significant. The divorce coefficient was
nearly identical (B=8.28 compared with 8.37). This is consistent with Plutzer’s (2002)
conclusion that enrollment, but not degree attainment, was a crucial predictor of young voters’ turnout.
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