The long-term consequences of parental divorce for children’s educational attainment

DEMOGRAPHIC RESEARCH

VOLUME 30, ARTICLE 61, PAGES 1653

−

1680

PUBLISHED 27 MAY 2014

http://www.demographic-research.org/Volumes/Vol30/61/

DOI: 10.4054/DemRes.2014.30.61

Research Article

The long-term consequences of parental divorce

for children’s educational attainment

Fabrizio Bernardi

Jonas Radl

2014 Fabrizio Bernardi & Jonas Radl.

This open-access work is published under the terms of the Creative Commons

Attribution NonCommercial License 2.0 Germany, which permits use,

reproduction & distribution in any medium for non-commercial purposes,

provided the original author(s) and source are given credit.

See http:// creativecommons.org/licenses/by-nc/2.0/de/

Table of Contents

Introduction

1654

1.1

Theory and hypotheses

1655

Data and methods

1659

Results

1661

3.1

Sensitivity checks

1669

Conclusions

1670

Acknowledgments

1672

References

1673

Appendix

1678

Demographic Research: Volume 30, Article 61

Research Article

http://www.demographic-research.org 1653

The long-term consequences of parental divorce for

children’s educational attainment

Fabrizio Bernardi

Jonas Radl

Abstract

BACKGROUND

In this paper we study the long-term consequences of parental divorce in a comparative

perspective. Special attention is paid to the heterogeneity of the consequences of

divorce for children’s educational attainment by parental education.

OBJECTIVE

The study attempts to establish whether the parental breakup penalty for tertiary

education attainment varies by socioeconomic background, and whether it depends on

the societal context.

METHODS

Data are drawn from the first wave of the Generations and Gender Survey, covering 14

countries. We estimate multi-level random-slope models for the completion of tertiary

education.

RESULTS

The results show that parental divorce is negatively associated with children’s tertiary

education attainment. Across the 14 countries considered in this study, children of

separated parents have a probability of achieving a university degree that is on average

seven percentage points lower than that of children from intact families. The breakup

penalty is stronger for children of highly educated parents, and is independent of the

degree of diffusion of divorce. In countries with early selection into educational tracks,

divorce appears to have more negative consequences for the children of poorly educated

mothers.

CONCLUSIONS

For children in most countries, parental divorce is associated with a lower probability of

attaining a university degree. The divorce penalty is larger for children with highly

European University Institute, Italy. E-Mail: Fabrizio.Bernardi@eui.eu.

Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain.

Bernardi & Radl: The long-term consequences of parental divorce for children’s educational attainment

1654 http://www.demographic-research.org

educated parents. This equalizing pattern is accentuated in countries with a

comprehensive educational system.

COMMENTS

Future research on the heterogeneous consequences of parental divorce should address

the issue of self-selection into divorce, which might lead to an overestimation of the

negative effect of divorce on students with highly educated parents. It should also

further investigate the micro mechanisms underlying the divorce penalty.

1. Introduction

Studies of the implications of parental separation for children’s well-being have

consistently shown that children of divorced parents fare worse on different measures of

well-being than children living in intact families (Amato 2001; Amato and Keith

1991)

. While there is ample evidence that divorce has negative implications for

children in the short term, there is less research examining the effect on long-term

socioeconomic outcomes (Liu 2007). The consequences of divorce for educational

attainment may be of special importance as having a poor education may lead to other

socioeconomic and health-related disadvantages, and may therefore persistently

undermine an individual’s life chances (Ross and Wu 1995; Shavit and Müller 1998).

Until relatively recently, research linking family structure and children’s well-being has

not paid much attention to the moderating effects of socioeconomic background (Demo

and Acock 1988). Although newer studies of the consequences of divorce have

increasingly controlled for social origin, questions of whether and how the long-term

parental breakup penalty for children’s educational achievement is related to their

socioeconomic background are still largely unanswered (McLanahan, Tach, and

Schneider 2013). As Amato (2010: 661) put it, “focusing on the average effects of

divorce masks the substantial degree of variability that exists in people’s adjustment.”

Finally, possibly due to a lack of adequate data, comparative analyses of cross-country

differences in the effects of divorce on children are still rare (but see Dronkers and

Härkönen 2008; Engelhardt, Trappe, and Dronkers 2002; Lange, Dronkers, and

Wolbers 2009; Pryor and Rodgers 2001).

In this paper, we aim to fill these gaps in the literature by focusing on the penalty

associated with a parental breakup for tertiary education achievement in a comparative

perspective. We do so by bringing together insights from two strands of research:

studies on the consequences of divorce and family forms on the one hand, and studies

In this article we use the terms divorce, parental separation, and parental breakup as synonyms.

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on educational attainment and social mobility on the other. We examine whether the

diffusion of divorce and the configuration of the educational system affect the impact of

parental separation on children’s educational achievement, and whether these two

factors also moderate the relationship between social background and the breakup

penalty.

More precisely, we address the two following research questions. First, to what

extent do the long-term consequences of parental separation on tertiary education

attainment vary by level of parental education? In other words, we ask whether the

negative consequences of parental separation for educational attainment are the same

for children from highly educated families and from poorly educated families. Second,

does the parental breakup penalty for children’s educational attainment vary depending

on the type of educational system and the level of diffusion of divorce?

We use data from the first wave of the Generations and Gender Survey covering

14 countries. We analyze educational attainment in different country-cohort clusters,

and employ multi-level models to investigate the effects of divorce on tertiary

educational achievement across institutional contexts.

1.1 Theory and hypotheses

The divorce literature has focused on four mechanisms that might explain the observed

negative association between parental breakup and children’s educational attainment.

(Amato 2000; Conger, Conger, and Martin 2010; Magnuson and Berger 2009):

reduction in economic resources following a breakup (McKeever and Wolfinger 2001);

changes in parental time and in parenting practices (Beck et al. 2010; Gershoff et al.

2007); an increase in parenting stress (Beck et al. 2010; Cooper et al. 2009; Nomaguchi

and Brown 2010); and a child’s emotional crisis linked to parental separation (Jekielek

1998). Our key interest in this paper is to investigate how parental education might

moderate these different mechanisms.

A fifth important theme that is omitted here refers to self-selection into divorce (Kim 2011). Since divorce is

not a random event but is more likely to occur in troubled families, the negative association between parental

divorce and children’s educational outcomes may be (co)determined by some unobserved characteristics that

influence both divorce and children’s educational outcomes. It has also been suggested that the well-being of

children from high-conflict families might actually be higher following parental breakup than if their parents

had stayed together (Amato, Loomis, and Booth 1995; Jekielek 1998). The present study is of a largely

descriptive nature and does not offer any counter-factual estimates on the causal effects of divorce. The use of

“causal” terminology (“effect,” “consequences,” etc.) is purely for stylistic purposes, as our data only allow

for naïve estimates of the “divorce penalty.” It is worth noting in this context that quasi-experimental

approaches for analyzing divorce effects are not without problems either, as it becomes difficult to derive

substantial meaning from causal estimates that have been purged of all types of selection effects (cf. Sigle-

Rushton et al. 2014).

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To the extent that the impact of divorce on children’s educational attainment is due

to a loss of economic resources, we can expect it to vary across different socioeconomic

backgrounds. Since highly educated parents are more likely than their less educated

counterparts to have a high income and substantial savings, we might expect to find that

parental breakup has less harmful consequences for the educational trajectories of their

children. Moreover, we might expect to find that having a high level of education helps

parents in coping with the stress of parenting and in reducing the emotional turmoil

experienced by their children following a breakup (Cooper et al. 2009). Thus, it is often

assumed that highly educated parents may be able to minimize the likelihood that their

children, like many children of divorced parents, will have worse school results

following the separation of their parents. In addition, even if the school results of the

children worsen, studies on educational inequalities have shown that students from

advantaged social backgrounds are more likely to have a “second chance,” and are more

likely to progress to the next educational level despite having below-par educational

performance (Boudon 1998; Gambetta 1987). This phenomenon has been labelled the

“social origin compensatory effect” (Bernardi 2012, 2014).

Based on these considerations, we might therefore expect to find that highly

educated parents, who are assumed to have superior economic resources and skills for

coping with their own and their children’s feelings of stress, would manage to mitigate

the negative long-term consequences associated with divorce for their children’s

educational outcomes. To recapitulate, the “compensation hypothesis” states that:

H1: Parental separation has less harmful consequences for the educational

achievement of children of highly educated parents than of children with less

educated parents.

However, we might also argue that children of parents with low levels of education

suffer less from divorce because their expected levels of educational attainment are

already very low to begin with. In societies with marked inequalities in educational

opportunity, only the most talented children from poorly educated families will manage

to progress through the various educational transitions and eventually achieve a high

level of education (Mare 1993). In other words, for a child from a disadvantaged

socioeconomic background, the road to university is already so steeply uphill that the

additional disadvantage of family breakup does not make the climb significantly more

difficult. Only exceptionally talented students from poorly educated families will

eventually make it to the top. They already have to overcome so many obstacles on

their way through the school system that a parental breakup does not prove to be a

decisive hurdle.

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Evidence supporting this argument has been found in previous studies on racial

differences. Studies of the United States have shown that the consequences of divorce

for children are less pronounced among black families than among white families

(Brown 2010; McLanahan and Bumpass 1988). Another study found that children of

Caribbean origin in the Netherlands are less strongly affected by parental separation

than whites (Kalmijn 2010). Kalmijn also offered an insightful and slightly different

explanation for why the relative income loss associated with divorce is smaller among

ethnic minorities. Specifically, he noted that poverty levels among people of Caribbean

origin tend to be high regardless of family background, partly because the men are often

unemployed. The essence of Kalmijn’s argument is that if the dual-parent families of a

given minority group are already very poor, there is not much room to sink further, and

thus the children do not have much to lose from a parental breakup.

A parallel argument can also be made about the consequences of parental breakup

for parenting styles and behavior. Parents with high and low levels of education differ

in their parenting styles. Compared to their less educated counterparts, highly educated

parents participate more in the organization of their children's after-school activities,

and spend more time with their children engaging in activities that foster cognitive

development and learning (Laureu 1998). A parental breakup might, however, reduce

the amount of time parents have to engage in these types of activities. For instance,

highly educated mothers have been found to be more likely to reduce literacy-

promoting activities after experiencing a change in marital status (Beck et al. 2010).

The core of the argument in this case is that children with highly educated parents can

lose more learning opportunities if their parents separate. Meanwhile, the amount of

time poorly educated parents spend engaging in activities that enhance the school

results of their children is likely to have been low both before and after separation.

To sum up, only the most talented and motivated children from poorly educated

families manage to progress to the higher levels of the educational system. On the one

hand, they are a positively selected group, and this should minimize the repercussions

of divorce. On the other hand, they have a lower risk of educational and occupational

downward mobility because they start from a low level. Similarly, these children have

less to lose from changes in parental practices following divorce. These mechanisms

suggest that the negative implications of divorce should be less pronounced for children

of lower socioeconomic backgrounds. The “floor effect hypothesis” thus leads us to

formulate a prediction in direct opposition to that of the compensation hypothesis:

H2: Parental separation has less harmful consequences for the educational

achievement of children of poorly educated parents.

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With regard to cross-country differences, it has long been recognized that the

structure of the educational system affects the reproduction of social inequality (Van de

Werfhorst and Mijs 2010). In particular, the degree of stratification of a given

educational system, defined by the system of tracking into higher and lower tier

secondary schools, appears to affect social mobility. There is robust evidence that the

degree of stratification of educational systems, conventionally measured by the age of

first selection into different educational tracks, is positively associated with the level of

inequality of educational opportunities (Horn 2009). The earlier children are assigned to

diverging educational tracks according to their performance, the stronger the

background effects on children’s final educational attainment are (Brunello and Checchi

2006).

Linking these insights to the divorce literature, we might ask whether the

consequences of a parental breakup are more negative for a student enrolled in a

stratified educational system than for a student enrolled in a comprehensive system. In

this context, it is worth noting that a large proportion of parental separations occur

when the children are still in primary education or younger (Andersson and Dimitrov

2002). Previous research has shown that a parental break-up is associated with an

immediate deterioration in school performance (Kim 2011). If the educational system is

more selective based on demonstrated performance, any source of disadvantage that

affects short-term academic achievement, including parental divorce, could have a

magnified influence on final educational attainment. The “educational system

hypothesis” thus stipulates that a drop in school performance has more long lasting

consequences for the final educational attainment in stratified educational systems than

it does in comprehensive systems:

H3: The divorce penalty for achievement of tertiary education is larger in stratified

educational systems.

Another possible macro-level determinant of parental separation penalties is the

degree of diffusion of divorce. Several authors have defended a socio-structural

argument that links the level of diffusion of a given living arrangement to its normative

acceptance and institutionalization, and in turn to its impact on individual well-being

and life chances (Cherlin 2004; Kalmijn 2010; Soons and Kalmijn 2009). According to

this so-called “institutionalization hypothesis” (Lacey et al. 2012), the negative effects

of parental separation on children are expected to be stronger in contexts in which the

divorce rate is low because of the widespread normative disapproval of divorce.

According to this view, single parenthood and divorce tend to be more institutionalized

in those countries and cohorts in which divorce is more common. A higher incidence of

divorce may translate into less stigmatization of single parents and greater acceptance

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of the children of divorced parents. Moreover, there might be selection effects at work

here as well: if the conditions necessary to bring about separation are more serious in

nature, the parents who do get divorced might have had very serious problems in their

marriage. The level of discord in the marriage might in turn have grave implications for

the well-being of their children. Hence, the institutionalization hypothesis states that:

H4: The adverse effect of a parental breakup on a child’s educational attainment is

smaller in those social contexts in which the experience of divorce is more

common.

Finally, we are also interested in examining whether the social background

differences in the consequences of divorce for children’s educational attainment vary

depending on the type of educational system and the level of diffusion of divorce.

Although we do not develop hypotheses for these issues, in the empirical analyses we

will examine the three-way interactions of social background, divorce, and,

respectively, the characteristics of the educational system and the diffusion of divorce.

2. Data and methods

To examine the long-term effects of parental separation the study draws on the first

wave of the Generations and Gender Survey

covering 14 countries: Australia, Austria,

France, Italy, Lithuania, Norway, the Netherlands, Belgium, Hungary, Estonia,

Bulgaria, Romania, Georgia, and Russia.

Depending on the country, the data collection

took place between 2003 and 2008. We selected all respondents aged 25 years and

older, yielding a total sample size of 83,048. Since the incidence of divorce varies

greatly not only across countries but also over time, we decided to use a hierarchical

design to account for contextual circumstances that may alter the consequences of

parental separation. Specifically, we constructed 55 country-cohort clusters with four

birth cohorts in each country: 1945−1954, 1955−1964, 1965−1974, and 1975−1984.

The dependent variable is whether or not subjects obtained a tertiary education

degree. The advantage of focusing on tertiary education attainment (ISCED 5 or more)

as an outcome measure is that the dependent variable is highly comparable across

countries. We present estimations of multi-level linear probability models with robust

standard errors, where the upper-level units are formed by country-cohort clusters, and

For details see http://www.ggp-i.org/.

The data for Germany had to be disregarded because of faulty information on parental breakup.

There are no observations for the oldest cohort in Austria, which sampled a smaller age range than the rest

of the countries.

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where the dependent variable is whether the respondent has achieved a university

degree (ISCED level 5 or 6). The model features a random slope for the breakup

penalty. The choice to use multi-level linear probability models (LPM) instead of multi-

level logit models was made for both practical and theoretical reasons. In our practical

considerations, we took into account the fact that the coefficients of the LPM are very

close to the marginal effects of the equivalent logit model if the proportion of out-of-

range predictions (between zero and one) is low, as in our case (about 1%). On the other

hand, it appears that when using an LPM instead a logit model, the estimation is less

grueling, the interpretation of interactions is more straightforward, and it is possible to

compare coefficients across models (Mood 2010). In our theoretical considerations, we

observed that both the floor and the institutionalization hypotheses discussed in the

previous sections are framed in terms of absolute variations in the divorce penalty,

rather than relative variations. The floor and institutionalization hypotheses are

therefore more directly addressed when we focus on the coefficients of an LPM rather

than on the log-odds or the odds ratios of a logit model.

Our independent variables of interest at the individual level are parental divorce

and parental education. Divorce is measured using the survey question: “Did your

biological parents ever break up?” This means that – like in most other studies – our

definition of divorce includes union dissolutions that did not result in divorce (because

the parents were either never married or remained married after splitting up). Subjects

who responded affirmatively were then also asked about the year in which the parental

separation happened. We only consider parental separations that occurred before

respondents turned 18 years of age.

We use parents’ level of education as an indicator for social background. We

consider the highest level of educational attainment among both parents if the

respondent spent their childhood with both biological parents. If the respondent lived

with only one parent, the educational information refers to the parent with whom the

respondent spent most of his or her childhood (until age 15). In other words, we apply

either the dominance model for intact families or the respective education of the

primary caring parent (who in 83% of cases is the mother). Unfortunately the GGS data

provide educational information for both parents of divorced and separated families in

only three of the 14 countries included in this study. This is an important limitation, and

we will come back to it when discussing the sensitivity checks that have been

performed. We distinguish between four levels: primary education or less (ISCED 0−1),

A possible floor effect in the divorce penalty should not be perceived as a statistical artifact based on the fact

that a probability is bound to be greater than zero. If an event is relatively rare (such as, for instance, tertiary

education attainment among the children of poorly educated families) and its probability is close to zero, the

occurrence of other events (such as parental separation) is structurally less likely to yield large absolute

effects.

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lower secondary education (ISCED 2), upper or post-secondary education (ISCED

3−4), and tertiary education (ISCED 5−6).

At the macro level we include three covariates. First, the incidence of divorce is

measured in terms of crude divorce rates per 1000 inhabitants. Except for a few data

points that were collected from miscellaneous sources, these data come from Eurostat

(2012). It would have been preferable to use cohort-adjusted divorce rates, but

unfortunately these rates were not available for all countries and time points. Second,

we control for enrollment rates in tertiary education using data from the Cross-National

Time-Series (CNTS) Data Archive. Enrollment rates refer to the percentage of the

population participating in tertiary education at any given moment. Both the divorce

rates and the enrollment rates have been mean-centered. Finally, the first age of

selection in the educational system is compiled from various sources (Brunello and

Checchi 2006; OECD 2005), and was completed through expert consultations. It

captures the age at which pupils are placed into different school tracks or educational

career paths. We distinguish between the educational systems in which tracking takes

place at early (at ages 10 through 12), late (at age 15 or 16), and average ages (at age 13

or 14)

. All of the macro-level variables are linked with individual subjects based on

their year of birth, and respectively refer to the situation in a given country when the

respondents were between six and 15 years old.

In order to test our hypotheses, we focus on the interactions between parental

separation with socioeconomic background on the one hand, and the (cross-level)

interactions of parental separation with divorce rates and the comprehensiveness of the

educational system on the other.

3. Results

Table 1 shows basic descriptive statistics for the analysis sample. Country-specific

samples range from 3,217 subjects in Austria to 9,687 in Norway. There is substantial

cross-country variation on all variables. As for the dependent variable, the average rate

of tertiary education attainment is 29%, but ranges from 12% in Romania to 45% in

Russia. While the incidence of parental breakup (before age 18) is 9% on average, the

lowest level is found in Italy (only 1.5%) and the highest level is found in Australia

(18.6%). The distribution of parental education also varies greatly across contexts.

These large country disparities underline the need for a multi-level design that allows

We have also estimated models with age of first selection specified as a continuous variable. The pattern of

results is the same. In the end we present the results based on the categorical specification because it allows

for a clear-cut distinction between early and late selection countries.

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the relationship between parental breakup and educational attainment to vary across

contexts.

Table 1: Descriptive statistics by country

Country

Tertiary

education

attainment

Parental

Breakup

Parental Education (highest level)

Primary or

less

Lower

secondary

Upper

secondary

Tertiary

Australia

37.6% 18.6% 9.0% 48.0% 6.0% 37.0%

3,293

Austria

21.7% 12.3% 0.2% 24.2% 66.6% 9.0%

3,217

Belgium

41.7% 9.1% 33.0% 18.6% 24.7% 23.6%

4,122

Bulgaria

24.1% 6.0% 15.9% 33.8% 37.3% 13.1%

8,171

Estonia

33.0% 18.0% 9.2% 28.6% 45.8% 16.4% 3,934

France

33.4% 10.2% 1.6% 57.9% 27.5% 12.9%

5,256

Georgia

33.3% 3.2% 10.2% 15.6% 52.4% 21.8%

6,321

Hungary

18.6% 10.6% 15.6% 26.4% 40.2% 17.8%

8,898

Italy

13.2% 1.5% 63.4% 17.7% 14.4% 4.5%

6,914

Lithuania

27.2% 9.0% 27.5% 23.9% 35.5% 13.9%

5,314

Netherlands

38.7% 5.2% 20.0% 39.6% 20.9% 19.5%

4,857

Norway

39.7% 10.4% 26.9% – 50.0% 23.1% 9,687

Romania

12.0% 5.3% 51.6% 31.1% 15.1% 2.2%

7,688

Russia

45.4% 14.2% 16.3% 29.7% 29.2% 24.8%

5,376

Total

28.7% 8.8% 23.7% 26.2% 33.7% 16.3%

83,048

Source: GGS wave 1 version 4

Table 2 shows the divorce rates and the first age of selection in the 14 countries in

our sample. Depending on when the divorce regulations were liberalized, in most

countries we see a rising trend in divorce at some point between 1960 and 1990.

Additionally, there is substantial cross-country variation, with divorce rates ranging

from close to zero in Italy to around four per thousand in Russia and Estonia in 1990.

The lowest age of selection, or age 10, is found in Austria; while the highest age of

selection, or age 16, is found in Norway and Australia. The other countries have ages of

Only Romania has taken a different road, as it experienced a backlash because of restrictions in legislation

that took place with the 1966 reform.

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selection that are somewhere in between. In France, Hungary, and the Netherlands there

have been educational reforms that changed the first age of selection.

Table 2: Divorce rates and tracking ages by country and cohort

Divorce rate

(per 1,000 inhabitants)

Age of first selection in the

educational system

1960 1970 1980 1990 1960 1970 1980 1990

Australia

0.6 1.0 2.7 2.5

16 16 16 16

Austria

1.1 1.4 1.8 2.1

10 10 10 10

Belgium

0.5 0.7 1.5 2.0

12 12 12 12

Bulgaria

0.9 1.2 1.5 2.0

Estonia

2.1 3.2 4.1 3.7

France

0.7 0.8 1.5 1.9

13 13 16 15

Georgia

1.3 1.3 1.3 1.4

15 15 15 15

Hungary

1.7 2.2 2.6 2.4

15 15 15 11

Italy

0.3 0.3 0.2 0.5

11 14 14 14

Lithuania

0.9 2.2 3.2 3.4

14 14 14 14

Netherlands

0.5 0.8 1.8 1.9

Norway

0.7 0.9 1.6 2.4

Romania

2.0 0.4 1.5 1.4

15 15 15 15

Russia

1.5 3.0 4.2 3.8

15 15 15 15

Note: Various sources, authors' compilation.

Table 3 and Table 4 show the results of the multivariate random-slopes models.

The first model shows that parental separation is associated with a decrease in

university education attainment rates. On average, children whose parents divorced

have a deficit of almost seven points in the probability of achieving a university degree

when compared with children from intact families. Considering that the average

attainment of tertiary education is 29%, a difference of seven percentage points is not

large, but neither is it small. Table 3 and Table 4 also document an advantage for girls

in achieving a university degree of about five percentage points. This divorce penalty is

therefore about the same size as the college gender gap that has recently received a lot

of academic and media attention (Becker, Hubbard, and Murphy 2010; DiPrete and

Bernardi & Radl: The long-term consequences of parental divorce for children’s educational attainment

1664 http://www.demographic-research.org

Buchman 2013),

and is consistent with previous research. The probability that

subjects whose parents have a tertiary education will obtain a university degree is 53

percentage points higher than that of subjects whose parents’ highest level of education

is primary or less.

Table 3: Multi level random-slopes model of tertiary education attainment

Model 1 Model 2 Model 3

b se b se b se

Female

.052***

(.003)

.052***

(.003)

.052***

(.003)

Parents' education (reference: primary or less)

Lower secondary

.076***

(.004)

.076***

(.005)

.076***

(.005)

Upper secondary

.224***

(.004)

.227***

(.004)

.226***

(.004)

Tertiary

.530***

(.005)

.538***

(.005)

.538***

(.005)

Parental breakup

-.066***

(.008)

-.033* (.014)

-.034* (.014)

Group-specific Breakup effect (ref.: div X par.prim.)

Breakup X parents: lower secondary

-.012

(.017)

-.012

(.017)

Breakup X parents: upper secondary

-.034* (.016)

-.033* (.016)

Breakup X parents: tertiary

-.084***

(.018)

-.084***

(.018)

Level-2 covariates

Age at tracking (ref: late, 15–16)

early (10–12)

.010 (.031)

average (13–14)

-.045

(.029)

Enrolment rate

.002 (.002)

Divorce rate

-.017 (.014)

Constant

.091***

(.012)

.089***

(.012)

.104***

(.017)

N of observ.

83,048 83,048 83,048

Source: GGP Wave 1

+ p<0.1, * p<0.05, ** p<0.01, *** p<0.001

Model 2 tests hypotheses 1 and 2, according to which the consequences of divorce

vary depending on parents’ education. The estimated interaction effects show that the

negative effect on educational attainment associated with divorce becomes larger as the

level of parental education increases. The divorce penalty is about 12 percentage points

among those children whose parents have a university degree (-.033-.084), compared to

With regard to the media, see, for example, the following articles on the college gender gap in The

Guardian and Fortune: http://www.theguardian.com/education/datablog/2013/jan/29/how-many-men-and-

women-are-studying-at-my-university; http://management.fortune.cnn.com/2013/03/27/college-graduation-

gender-salaries/.

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three percentage points among those children whose parents have only a primary

education or less. Model 2 thus shows that the negative consequences of divorce for

university degree attainment are more pronounced among children with highly educated

parents. A recent paper on Finland reported a similar finding (Erola and Jalovaara

2012). This result is at odds with the hypothesis of a compensation effect (H1),

according to which children from a privileged background should be less affected by

parental separation. It is, however, in line with the floor effect hypothesis (H2). The

underlying explanation for this finding is that a divorce cannot substantially worsen the

already limited educational opportunities of children who come from poorly educated

families. A similar pattern has also been documented for disadvantaged ethnic

minorities (Kaljmin 2010).

To illustrate these group differences, Figure 1 shows the predicted probabilities of

tertiary education attainment by parental level of education with either divorced or

intact families. We can see that the gap between children from divorced and intact

families is larger for those whose parents have a university education than for those

whose parents have only a primary education. If we look at Figure 1 from another

perspective, we can see that the degree of social background inequality is greater among

intact families than among divorced families.

Returning to Table 3, in the third model we add mean-centered enrollment and

divorce rates as contextual covariates at level 2. We also include dummies in order to

distinguish between educational systems with early, average, and late ages of selection

into tracks. Country-specific enrollment rates in tertiary education in the respective

decade are used here to control for educational expansion. We do not find any clear-cut

associations between university degree attainment and these three contextual variables.

The coefficients are small and not precise (the standard errors are large). Robustness

checks involving the stepwise inclusion of the various macro-level covariates separately

confirmed these results.

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1666 http://www.demographic-research.org

Figure 1: Predicted probability of tertiary education attainment by parental

divorce and parental education

Source: GGP Wave 1

To test hypotheses 3 and 4, the next specification (Model 4 in Table 4) adds a set

of cross-level interaction effects between parental divorce and the two contextual

variables. The coefficient for the cross-level interaction between early age of selection

and parental breakup is negative (minus three percentage points). This result gives some

support to hypothesis 3, and suggests that the negative consequences of a parental

breakup on educational attainment are slightly more pronounced in cases in which the

educational system assigns students to tracks at an early age. But as the standard error

associated with the coefficient is large, we must be cautious in interpreting the point

estimate.

The results of model 4 also show a small negative interaction effect in terms

of the degree of diffusion of divorce. This finding is surprising because it so clearly

refutes the claims of the institutionalization hypothesis (H4). According to our

estimates, divorce penalties for attaining a university degree seem to actually increase

as divorce becomes more common.

Significance tests have no meaning in terms of classic statistical inference with a non-random convenience

sample of cohort by country clusters (Freedman, Pisani, and Purves 1978). It might be proposed that we use

some sort of “supra-population” of cohort-by-country constellations, including possible future cases, of which

the data under analysis are a specific sample. This kind of argument is, however, hardly convincing (Berk

2004). In this paper we report the standard error and the conventional symbols to highlight statistical

significance, because this is still standard practice in multi-level modeling.

The estimated interactive effect of divorce rates on the break-up penalty is unaffected by different model

specifications. Moreover, additional analyses showed that the three-way interaction effects estimated in

Model 6 do not change when models are fitted without controlling for divorce rates.

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Table 4: Multi level random-slopes model of tertiary education attainment

Model 4

Model 5

Model 6

Female

.052***

(.003)

.052***

(.003)

.051***

(.003)

Parents' education (reference: primary or less)

Lower secondary

.076***

(.005)

.069***

(.006)

.070***

(.006)

Upper secondary

.226***

(.004)

.202***

(.006)

.204***

(.006)

Tertiary

.538***

(.005)

.512***

(.007)

.513***

(.007)

Parental breakup

-.028+

(.015)

-.032*

(.016)

-.018

(.018)

Group-specific Breakup effect (ref.: div X par.prim.)

Breakup X parents: lower secondary

-.010

(.017)

-.009

(.017)

-.021

(.021)

Breakup X parents: upper secondary

-.029+

(.016)

-.022

(.016)

-.044*

(.020)

Breakup X parents: tertiary

-.079***

(.018)

-.071***

(.018)

-.084***

(.021)

Level-2 covariates

Age at tracking (ref: late, 15–16)

early (10–12)

.021

(.032)

-.024

(.034)

-.020

(.034)

average (13–14)

-.041

(.029)

-.070*

(.031)

-.069*

(.031)

Enrolment rate

.002

(.002)

.002

(.002)

.002

(.002)

Divorce rate

-.012

(.014)

-.013

(.014)

-.013

(.014)

Cross-level interactions

Breakup X divorce rate

-.014+

(.008)

-.014+

(.008)

-.014+

(.007)

Breakup X early tracking

-.031

(.021)

-.033

(.021)

-.105*

(.041)

Breakup X average tracking

-.008

(.018)

-.010

(.018)

-.029

(.037)

Early tracking X parents: tertiary

.031*

(.014)

.025+

(.014)

Early tracking X parents: upper secondary

.063***

(.012)

.055***

(.013)

Early tracking X parents: lower secondary

.066***

(.012)

.065***

(.013)

Average tracking X parents: tertiary

.089***

(.013)

.091***

(.013)

Average tracking X parents: upper secondary

.053***

(.010)

.050***

(.010)

Average tracking X parents: lower secondary

-.007

(.010)

-.009

(.010)

Three-way interactions

Breakup X par.tert X average tracking

-.021

(.049)

Breakup X par.upp.sec. X average tracking

.031

(.041)

Breakup X par.low.sec. X average tracking

.035

(.044)

Breakup X par.tert X early tracking

.100+

(.053)

Breakup X par.upp.sec. X early tracking

.116*

(.047)

Breakup X par.low.sec. X early tracking

.039

(.049)

Constant

.101***

(.017)

.118***

(.018)

.117***

(.018)

N of observ.

83,048

Source: GGP Wave 1

+ p<0.1, * p<0.05, ** p<0.01, *** p<0.001

In Model 5 we include a set of interaction terms between parental education and

the structure of the educational system, measured by the age of first selection. As

expected, almost all the coefficients here are positive. In accordance with previous

social mobility research (Brunello and Checchi 2006; Van de Werfhorst and Mijs

2010), the model shows that the association between parental education and children’s

educational achievement is stronger when the educational system has an early or an

average tracking age than when it has an older tracking age.

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1668 http://www.demographic-research.org

Finally, in model 6 we introduce a set of three-way interaction effects of parental

divorce, social origin, and the age of first selection in the educational system. In this

specification, we find positive effects for the interaction terms of early age of first

selection, parental education, and parental breakup. Accordingly, in countries where

tracking takes place at a young age, the tertiary education attainment of children whose

parents have upper secondary or tertiary education is relatively less affected by parental

divorce.

To get a clearer look at these group specificities across societal contexts, Figure 2

shows the estimated divorce penalty for children with high and low levels of parental

education, respectively; with early, average, and late selection into diverging tracks.

The bars in Figure 2 express the differences in the predicted probability of obtaining

tertiary education between children of divorced parents and children from intact

families in each origin group. The differences in Figure 2 are all negative, which means

that in cases with divorce the probability of achieving a university degree is smaller

throughout.

In comprehensive educational systems with a late age of first selection (age 15 or

16) there are virtually no adverse effects for children whose parents only have a primary

education, whereas the divorce penalty for children from highly educated families is

much larger, at 10 percentage points. Strikingly, the pattern is almost reversed in

countries with very early selection. The probability of obtaining a college degree among

children from poorly educated families is reduced by 12 percentage points in

educational systems with an early age of selection (ages 10 to 12), while the

corresponding reduction in attainment rates among children from advantaged social

backgrounds is slightly smaller. Overall, Figure 2 suggests that the relative

disadvantage stemming from divorce grows larger for children from lower social

backgrounds the earlier the educational system places children into qualitatively

different tracks. The pattern is less clear for children from higher social backgrounds,

for whom the differences in the divorce penalty across societal contexts are less

pronounced, and do not follow a linear pattern in terms of the age of selection.

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Figure 2: Difference in the predicted probability of attainment of tertiary

degree for respondents from divorced families when compared to

intact families by level of parental education and tracking age

3.1 Sensitivity checks

All of the analyses have been replicated with multi-level (random slopes) logit models

rather than with a multi-level (random slopes) linear probability model (see Table A.1

in appendix). The main conclusions are the same when the divorce penalty in the

educational attainment is measured in terms of log-odds. A second sensitivity analysis

consisted of considering educational attainment in general instead of focusing only on

university degree attainment. With this aim in mind, we have recoded the respondents’

educational level into the average number of years required to achieve that educational

level. The results of the analysis with this different specification of the dependent

variable have an overall pattern similar to that of the findings for the attainment of a

university degree (Table A.2). Most importantly, we again find a larger divorce penalty

among children with highly educated parents, which provides further support for

hypothesis 2.

Finally, unlike the rest of the sample, three countries participating in the

Generations and Gender Survey – Estonia, Hungary, and Italy – provide information on

the educational levels of both parents for divorced families. In Table A.3 of the

appendix we have replicated the analyses for these three countries, while also taking

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1670 http://www.demographic-research.org

into account the education of the absent parent. The first model specification enables us

to validate the robustness of our previous findings when using the dominance principle

to measure the highest level of parental education with full information on both parents.

The estimated coefficients for the origin-specific breakup penalty turn out to be

markedly similar to those obtained for the full set of countries with only partial

information on the education of divorced parents (Table 3, model 2).

When we consider the educational level of the mother and father separately

(models 2 and 3), we also find that the divorce penalty is larger for children of highly

educated parents, regardless of whether it is measured with reference to the level of

education of the mother or the father. The same result is confirmed overall when we

jointly consider the mother’s and the father’s levels of education (model 5), although in

this latter case the estimates are not statistically significant due to multicollinearity and

large standard errors.

4. Conclusions

In this paper we were interested in gaining a better understanding of to what extent the

negative consequences for children associated with parental divorce depend on the

social origins of the families, and on the societal context. First, we found that parental

breakup is associated with negative long-term consequences for children's educational

attainment. On average across countries and cohorts, we found a parental breakup

penalty of about seven percentage points for the chances of attaining a university

degree. Second, this penalty is not uniform, but varies by socioeconomic background

and across countries and cohorts. More precisely, our findings suggest that parental

divorce tends to be more detrimental for children of highly educated parents: for them,

a divorce is associated with a 12-percentage-point drop in the probability of attaining a

university degree. Interestingly, a recent study by Erola and Jalovaara (2012) found a

similar result for Finland. Moreover, we showed that the socioeconomic background

penalty associated with parental breakup varies depending on the level of stratification

of the educational system. On average, we found that the divorce penalty is larger

(about three additional percentage points) if selection takes place early. It should be

emphasized, however, that this estimate was not precise enough to allow us to draw

firm conclusions on this point. After further scrutinizing the interaction between

parental breakup, social background, and age of selection, we found that if selection

into different educational tracks takes place early, a larger divorce penalty is observed

for children from poorly educated families. As a result, in stratified educational

systems, the divorce penalty barely changes according to parental level of education.

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In other words, our findings indicated that when the level of stratification in an

educational system is low, parental divorce tends to reduce inequality of educational

opportunities. It therefore seems that the characteristics of the educational system, and

particularly the extent of early tracking, play key roles in mediating the consequences of

parental breakup. On the other hand, our empirical evidence did not confirm the

institutionalization hypothesis, which states that the adverse consequences of divorce

are smaller in societies in which divorce rates are high. While this idea may be intuitive,

our results did not support the assumption that a high degree of diffusion of divorce

would, via diminished social stigma, lead to lower penalties for divorce. Our models

yielded the opposite finding, suggesting that the divorce penalty might be larger in

countries and cohorts in which divorce is more diffused (although the respective

coefficient is only marginally significant). This finding may reflect the fact that in the

initial period after divorce is legalized in a given context, it is mostly used by social

elites who may well be capable of protecting their offspring from any negative

repercussions.

In order to compare various countries in this study, we had to forego the option of

directly testing the micro mechanism driving the heterogeneity in divorce penalty by

social background. Thus, the main limitation of this study is that we were only able to

consider the educational level of the parent (the mother in the large majority of the

cases) co-residing with the child after divorce. We therefore have not been able to

investigate directly the mechanisms of economic and occupational downward mobility

that may contribute to the large divorce penalty observed for the children of highly

educated single parents.

Similarly, we did not have sufficient data to control for further differences between

children of divorced parents and children from intact families, which may induce

selection effects (Bhrolcháin 2001; Kim 2011; Steele, Sigle-Rushton, and Kravdal

2009). Of major relevance for our conclusions is the fact that, in recent years, a negative

educational gradient in the risk of divorce has been documented in the majority of

countries (Amato and James 2010; Lyngstad and Jalovaara 2010). Divorcing parents

with high and low levels of education might therefore differ in terms of unobserved

factors that could affect the children's educational attainment. If, for instance, highly

educated parents are less likely to divorce and do so only when there is a very high

degree of conflict in the relationship, then their children might be selected on negative

unobserved characteristics that might also explain their larger penalty in educational

attainment. To complicate matters further, the educational gradient has changed over

time from positive to negative, making it difficult to predict the implications for the

potential biases due to selection into divorce in a cross-cohort study like this one

(Bernardi and Martínez Pastor 2011; Härkönen and Dronkers 2006; Matysiak, Styrc,

and Vignoli 2011).

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1672 http://www.demographic-research.org

These concluding observations suggest the need for additional research on the

social background gradient in the divorce penalty which draws on more information

about the social background of both parents, and which is based on research designs

that permit the analysis of the endogenous nature of divorce when studying its

consequences.

5. Acknowledgements

The authors wish to thank Héctor Cebolla-Boado, Feinan Chen, Jaap Dronkers, Jani

Erola, Alexi Gugushvili, Juho Härkönen, Daniel Horn, and the two anonymous

reviewers for their helpful comments and suggestions.

The research leading to these results has received funding from the European

Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no.

320116 for the research project FamiliesAndSocieties.

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Bernardi & Radl: The long-term consequences of parental divorce for children’s educational attainment

1678 http://www.demographic-research.org

Appendix

Table A1: Multi-level random-slopes logit model of tertiary education

attainment

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Female

.317***

(.017)

.317***

(.017)

.317***

(.017)

.317***

(.017)

.317***

(.017)

.317***

(.017)

Parents' education (reference: primary or less)

Lower secondary

.610***

(.032)

.615***

(.033)

.615***

(.033)

.614***

(.033)

.541***

(.044)

.551***

(.045)

Upper secondary

1.448***

(.030)

1.454***

(.031)

1.453***

(.031)

1.451***

(.031)

1.280***

(.040)

1.301***

(.041)

Tertiary

2.771***

(.033)

2.796***

(.034)

2.795***

(.034)

2.793***

(.034)

2.626***

(.044)

2.641***

(.045)

Parental breakup

-.378***

(.043)

-.217+

(.112)

-.226*

(.112)

-.184

(.116)

-.236*

(.116)

-.047

(.125)

Group-specific Breakup effect (ref.: div X par.prim.)

Breakup X parents: low. sec.

-.111

(.129)

-.109

(.129)

-.100

(.129)

-.070

(.130)

-.222

(.150)

Breakup X parents: upp. sec.

-.126

(.118)

-.118

(.119)

-.096

(.119)

-.026

(.120)

-.275*

(.135)

Breakup X parents: tertiary

-.302*

(.124)

-.294*

(.125)

-.276*

(.125)

-.204

(.126)

-.394**

(.141)

Level-2 covariates

Age at tracking (ref: late, 15-16)

early (10-12)

.120

(.178)

.150

(.176)

.0140

(.185)

.051

(.185)

average (13-14)

-.227

(.160)

-.214

(.161)

-.632***

(.173)

-.607***

(.173)

Enrolment rate

.016+

(.009)

.015+

(.009)

.016+

(.009)

.017+

(.009)

Divorce rate

-.078

(.078)

-.063

(.079)

-.075

(.079)

-.077

(.079)

Cross-level interactions

Breakup X divorce rate

-.077+

(.041)

-.080+

(.041)

-.078+

(.040)

Breakup X early tracking

-.182

(.115)

-.176

(.114)

-1.088**

(.362)

Breakup X average tracking

-.056

(.103)

-.092

(.105)

-.776+

(.413)

Early tracking X parents: tertiary

-.019

(.084)

-.066

(.087)

Early tracking X parents: upp. sec.

.143+

(.076)

.081

(.078)

Early tracking X parents: low. sec.

.247**

(.079)

.226**

(.081)

Aver. tracking X parents: tertiary

.713***

(.085)

.695***

(.087)

Aver. tracking X parents: upp. sec.

.580***

(.075)

.543***

(.076)

Aver. tracking X parents: low. sec.

.160*

(.080)

.134+

(.081)

Three-way interactions

Breakup X par.tert X aver. tracking

.583

(.445)

Breakup X par.upp.sec. X aver. tracking

.802+

(.428)

Breakup X par.low.sec. X aver. tracking

.735

(.452)

Breakup X par.tert X early tracking

1.005*

(.400)

Breakup X par.upp.sec. X early tracking

1.177**

(.383)

Breakup X par.low.sec. X early tracking

.631

(.409)

Constant

-2.294***

(.072)

-2.303***

(.072)

-2.231***

(.097)

-2.239***

(.098)

-2.105***

(.101)

-2.118***

(.101)

N of observ.

83,048

Source: GGP Wave 1.

+ p<0.1, * p<0.05, ** p<0.01, *** p<0.001

Demographic Research: Volume 30, Article 61

http://www.demographic-research.org 1679

Table A2: Multi-level random-slope model of years of education

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Female

.181***

(-.021)

.181***

(-.021)

.181***

(-.021)

.181***

(-.021)

.181***

(-.021)

.181***

(.021)

Parents' education (reference: primary or less)

Lower secondary

1.388***

(-.033)

1.395***

(-.034)

1.393***

(-.034)

1.393***

(-.034)

1.133***

(-.046)

1.145***

(-.047)

Upper secondary

2.766***

(-.032)

2.773***

(-.033)

2.770***

(-.033)

2.768***

(-.033)

2.294***

(-.044)

2.314***

(-.044)

Tertiary

4.604***

(-.038)

4.637***

(-.039)

4.633***

(-.039)

4.631***

(-.039)

4.122***

(-.051)

4.133***

(-.052)

Parental breakup

-.620***

(-.061)

-.474***

(-.111)

-.483***

(-.111)

-.447***

(-.121)

-.530***

(-.121)

-.374**

(-.137)

Group-specific Breakup effect (ref.: div X par.prim.)

Breakup X parents: lower secondary

-.117

(-.128)

-.116

(-.128)

-.109

(-.129)

-.046

(-.129)

-.205

(-.160)

Breakup X parents: upper secondary

-.121

(-.119)

-.120

(-.119)

-.105

(-.121)

.018

(-.121)

-.208

(-.147)

Breakup X parents: tertiary

-.352**

(-.132)

-.352**

(-.133)

-.338*

(-.134)

-.193

(-.134)

-.340*

(-.160)

Level-2 covariates

Age at tracking (ref: late, 15-16)

early (10-12)

-.282

(-.261)

-.252

(-.262)

-1.110***

(-.267)

-1.081***

(-.267)

average (13-14)

-.361

(-.240)

-.364

(-.240)

-1.035***

(-.244)

-1.016***

(-.244)

Enrolment rate

.018

(-.013)

.019

(-.013)

.021

(-.013)

.022+

(-.013)

Divorce rate

.125

(-.116)

.128

(-.117)

.102

(-.115)

.097

(-.115)

Cross-level interactions

Breakup X divorce rate

-.048

(-.063)

-.054

(-.063)

-.051

(-.062)

Breakup X early tracking

-.274

(-.173)

-.286+

(-.172)

-.821**

(-.316)

Breakup X average tracking

.017

(-.153)

-.010

(-.152)

-.436

(-.282)

Early tracking X parents: tertiary

1.123***

(-.103)

1.084***

(-.106)

Early tracking X parents: upper secondary

1.160***

(-.092)

1.102***

(-.095)

Early tracking X parents: lower secondary

.920***

(-.091)

.901***

(-.094)

Average tracking X parents: tertiary

1.242***

(-.094)

1.235***

(-.097)

Average tracking X parents: upper secondary

.580***

(.075)

.543***

(.076)

Average tracking X parents: lower secondary

.160*

(.080)

.134+

(.081)

Three-way interactions

Breakup X par.tert X average tracking

.235

(-.366)

Breakup X par.upp.sec. X average tracking

.595+

(-.308)

Breakup X par.low.sec. X average tracking

.535

(-.327)

Breakup X par.tert X early tracking

.631

(-.393)

Breakup X par.upp.sec. X early tracking

.815*

(-.351)

Breakup X par.low.sec. X early tracking

.407

(-.368)

Constant

1.108***

(-.002)

1.108***

(-.002)

1.108***

(-.002)

1.108***

(-.002)

1.106***

(-.002)

1.106***

(-.002)

N of observ.

83,448

Source: GGP Wave 1.

+ p<.1, * p<.05, ** p<.01, *** p<.001

Bernardi & Radl: The long-term consequences of parental divorce for children’s educational attainment

1680 http://www.demographic-research.org

Table A3: Linear probability models of tertiary education attainment in

Estonia, Hungary, and Italy

Model 1

Model 2

Model 3

Model 4

Female

.060***

(.005)

.062***

(-.005)

.061***

(-.005)

.062***

(-.005)

Parental breakup

-.015

(.017)

-.019

(-.017)

-.015

(-.021)

-.012

(-.021)

Parents' education (reference: primary or less)

Lower secondary

.082***

(-.007)

Upper secondary

.205***

(-.008)

Tertiary

.515***

(-.012)

Group-specific Breakup effect (ref.: div X par.prim.)

Breakup X parents: lower secondary

-.041+

(-.023)

Breakup X parents: upper secondary

-.043+

(-.022)

Breakup X parents: tertiary

-.100**

(-.033)

Mother's education (ref.: primary or less)

Lower secondary

.091***

(-.007)

.038***

(-.009)

Upper secondary

.248***

(-.009)

.146***

(-.012)

Tertiary

.505***

(-.014)

.324***

(-.017)

Interation of Breakup and Mother's education (ref.: breakup X mother prim.)

Breakup X mother: lower secondary

-.028

(-.022)

-.002

(-.033)

Breakup X mother: upper secondary

-.067**

(-.024)

-.036

(-.037)

Breakup X mother: tertiary

-.084*

(-.038)

-.027

(-.05)

Father's education (ref.: primary or less)

Lower secondary

.081***

(-.007)

.054***

(-.009)

Upper secondary

.210***

(-.008)

.119***

(-.011)

Tertiary

.541***

(-.014)

.325***

(-.018)

Interation of Breakup and Father's education (ref.: breakup X father prim.)

Breakup X father: lower secondary

-.041

(-.026)

-.041

(-.036)

Breakup X father: upper secondary

-.047+

(-.026)

-.036

(-.039)

Breakup X father: tertiary

-.085+

(-.046)

-.050

(-.057)

Country (ref. Hungary)

Italy

.065***

(-.006)

.063***

(-.007)

.049***

(-.007)

.052***

(-.007)

Estonia

.141***

(-.008)

.137***

(-.008)

.147***

(-.008)

.142***

(-.008)

Constant

-.008

(-.007)

.016*

(-.007)

.007

(-.007)

-.010

(-.007)

adj. R-squared

.166

.147

.152

.172

N of observ.

19,746

19,503

19,498

19,255

Source: GGP Wave 1.

+ p<0.1, * p<0.05, ** p<0.01, *** p<0.001

Note: Models control for birth cohort.