European Sociological Review
VOLUME 25
NUMBER 1
2009
123–138
123
DOI:10.1093/esr/jcn031, available online at www.esr.oxfordjournals.org
Online publication 18 July 2008
Persistent Inequalities? Expansion
of Education and Class Inequality
in Italy and Spain
The paper analyses inequalities in educational outcomes (IEO) by class of family of origin
in Italy and Spain for five 10-year cohorts born from 1920 to 1969, using the cumulative
logit (ordinal regression) model. In both countries the question is whether, as education
expanded, the class IEO’s remained stable or diminished. The dominant view in the 1990s
was that, with the exception of a few countries, inequalities persisted. In the current
decade the consensus on this is changing, and decreasing class IEO is now more often
found. Italy has been given as an example of educational expansion while maintaining
class IEO. Spain was not included in previous analyses. The results show clearly that class
IEO diminished in Spain as well as in Italy; differences in the timing of expansion and
change in IEO can be accounted for through the different institutional settings of the two
countries. A more contained reduction of IEO is found in Spain than in Italy.
Introduction
The paper analyses the relation between class of origin
and educational attainment over time in Italy and
Spain and investigates whether the educational expansion that occurred in both countries has also brought
about a lessening in the inequality of educational
opportunities (IEO) in education by social class of
origin. The main conclusion of the comparative study
on IEO directed by Shavit and Blossfeld (1993)
suggested persisting class inequalities in education,
despite schooling expansion, in the majority of the
countries analysed, but in recent years this conclusion
has been questioned for an increasing number of
countries and, lastly, by the first results of new
comparative studies, which show decreasing IEO in
most of the countries under observation (Breen and
Jonsson, 2005; Breen et al., 2005).
The paper contributes to this ongoing debate in two
ways. First, it tries to ‘establish the phenomenon’
(Merton, 1987), namely, whether class IEO has been
stable or decreasing in the two countries under study.
The evidence for both is, in fact, inconclusive. In Italy
most of the studies have found persistent inequality
(Schadee and Schizzerotto, 1987; Cobalti, 1990; Cobalti
and Schizzerotto, 1994; Pisati, 2002), but there are
some noteworthy exceptions (Shavit and Westerbeek,
1998; Recchi, 2003). The same goes for Spain, for
which there are few (and almost none in English)
systematic studies on these issues; while Martinez
(2002) finds persistent IEO, Carabaña (1999) finds a
non-linear pattern, where IEO increases and declines
thereafter. Second, the paper models IEO differently
from most of the studies in the field, using cumulative
logits (McCullagh, 1980). This type of statistical model
allows us to investigate how differences among countries in educational expansion and the distribution of
educational titles are related to IEO as it includes,
differently from the usual log-linear or logit analysis,
direct parameters for the expansion of education.
ß The Author 2008. Published by Oxford University Press. All rights reserved.
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Gabriele Ballarino, Fabrizio Bernardi, Miguel Requena and
Hans Schadee
124
BALLARINO et al.
Substantively, the question becomes: which class has
managed to benefit more from the educational
expansion?
The paper is divided into 6 sections. After this
introduction, section 2 presents the main results of
previous research on class IEO over time, and the main
theoretical arguments put forward to explain them.
Section 3 describes the historical and institutional
context of educational expansion in Italy and Spain,
while in section 4 data, variables, and the statistical
model are presented. Section 5 gives the empirical
results, and section 6 contains the conclusions.
The expansion of education, at all its levels, is one of
the main features of contemporary societies (Meyer
et al., 1992; Walters, 2000; Shavit et al., 2007).
Obviously, it has increased the chances for the lower
classes to reach secondary and higher educational
levels, previously reserved for the offspring of the
upper classes. Still, whether educational expansion is
also associated with diminishing IEO (i.e. whether
relative chances to reach higher education are becoming more equal among classes) is a much more debated
issue in the literature, and many hypotheses and
explanations have been put forward on the topic.
Why Inequalities Should Persist
The first major international comparative project on IEO
found it quite stable over time and across countries,
albeit with the notable exception of Sweden and,
partially, the Netherlands (Blossfeld and Shavit, 1993).
This finding has been generalized in the so-called
maximally maintained inequality (MMI) hypothesis
(Raftery and Hout, 1991), which states that the new
opportunities created by educational expansion are
exploited first by the offspring of the higher classes,
because their familiar financial, cultural, social, and
motivational resources are appropriate for taking
advantage of the new opportunities. IEO inertia,
according to this hypothesis, is produced by a kind of
‘red queen in Alice in Wonderland’ action, where you
have to run to stay in the same place. According to
Walters (2000) school expansion has purposively been
supported by the élite classes, in order to overcome the
potentially equalizing effects of school reforms: the
expansion of education has given elites a major means
for maintaining their relative educational advantage.
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Educational expansion and
inequality of educational
opportunities
Higher classes not only take advantage of new openings,
but can also create new barriers and social closures, for
instance, by creating less prestigious and ‘dead-end’
tracks in secondary and higher education to accommodate the demand coming from the lower classes without
changing the pattern of social stratification (Lieberson,
1980). This kind of collective action can be more
effective in authoritarian right-wing regimes, where it
is not counterbalanced by the working classes’ participation in policy-making via democratic representation.
This happened in Italy during the Fascist regime,
when a school reform designed by Idealist philosopher
and minister of education Giovanni Gentile increased
the stratification of secondary school and higher
education, in order to have a sharper separation
between élite and popular tracks (Schizzerotto and
Barone, 2006).
More detailed micro-level rational action models of
educational decisions have also been proposed to
explain the persistence of IEO (Eriksson and Jonsson,
1996a; Breen and Goldthorpe, 1997; Breen and Yaish,
2006). Following Becker’s (2003) exposition, the key
parameters that drive educational decisions on whether
to continue to achieve the next educational level
(En þ 1) or to exit the educational system at the
educational level En are: the educational returns (B)
in the labour market associated with En þ 1; the amount
of status decline (SD) implied by the decision of
stopping at En; the costs (C) of En þ 1 and the
probability of failing (Pf) in completing it. The greater
the benefits of En þ 1 and the status decline implied by
En, the higher the motivation to pursue En þ 1.
Conversely, the greater the costs of En þ 1 and the
risk of failing in achieving it, the lower the motivation
in continuing to En þ 1. This model assumes that the
benefits B and costs C are equal for all social classes,
while the amount of SD and risk of failure, Pf, vary
among social classes. This is because the amount of
status decline is relative to one’s social position
of origin. In general, one might argue that the
amount of SD associated with a given En is lower for
lower social classes. With regard to Pf, the argument is
that it depends on previous educational achievement
and performance. Children from privileged families are
advantaged in this respect because their parents are
more likely to transmit cognitive and other skills that
are positively associated with learning and success in
the educational system. Moreover, higher classes are
better able to compensate unexpected failures of their
children in the educational system thanks to their social,
economic, and cultural resources (Becker, 2003, p. 5).
All in all, for a given level of education En þ 1, Pf is
assumed to be higher for lower class children.
EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
Why Inequalities can Diminish
In sum, from both MMI and the rational action
model, one might derive a hypothesis of non-declining
class IEO over time. In the case of MMI, persistent
class inequalities are the result of an active attempt by
higher classes to take advantage of the new opportunities opened up by educational reforms, and possibly
of the creation of new closures in the educational area.
In the case of the rational action model the key
assumption is that the assessment of the status decline
associated with a given level of education and of the
risk of failure in purchasing it differs for each of the
social classes. If these class-specific differences remain
constant over time, class IEO will also persist.
Almost at the same time that the MMI hypothesis
and the rational action model were put forward, the
interpretation and explanation of Shavit and Blossfeld’s
findings of persistent class IEO has been contested
(see Treiman and Ganzeboom, 1998, p. 8), and further
research has found evidence of decreasing IEO in
Germany and France (Jonsson et al., 1996; Thélot and
Vallet, 2000). The most recent comparative study on
IEO patterns over time in Europe (Breen et al., 2005)
casts considerable doubts on the ‘persistent inequality’
claim: in six of the eight studied countries class IEO
actually decreased during the second half of the last
century.1 The authors can thus conclude calling for a reorientation in theoretical work, which should now focus
on clarifying ‘why declining inequality is more common than so far assumed’ (Breen et al., 2005, p. 25).
Some work in this direction has already been done,
in particular for the case of Sweden, the most evident
outlier from Shavit and Blossfeld’s study. The Swedish
case suggests that political intervention has been
able to lower IEO, neither with explicitly
equalization-oriented school reforms nor with just
the general equalization in living conditions that
followed the development of the welfare state, but
with interventions aimed at increasing employment
security for the lower classes (Eriksson, 1996; Eriksson
and Jonsson, 1996b). Eriksson (1996, p. 107) argues
that in Sweden higher employment security changed
the lower classes’ perception of the risk associated with
the probability of educational failure (Pf), as it
strengthened their reliance on future incomes, increasing their overall propensity for risk-taking. But in this
way class-specific differences with respect to Pf do
indeed change, making a reduction in IEO possible.
Eriksson and Jonsson (1996a) highlight two further
mechanisms by which class-specific differences in Pf
could change.2 The first one is the diminishing school
selection that is typically associated with school
expansion: if chances of dropping out decrease, the
overall level of Pf should correspondingly decrease, but
this decrease will be higher for the lower classes, who
start from a higher level of perceived failure chances.
The second one involves school reforms, which can
reduce the stratification of the school system, and thus
the complexity of school choice, for instance, by
introducing comprehensive secondary education. This
should diminish the importance of correct information
in the structure of the system itself for an efficient
choice, one that can correctly estimate Pf. As information on the schooling system is typically better in
families from higher classes, where parents have, on
average, a higher level of education, a destratification
of the school system would thus diminish class-specific
differences in Pf.
Educational Expansion and
the School System in Italy
and Spain
It is thus possible to develop hypotheses for both
persisting and decreasing IEO. Before turning to the
empirical analysis, it can be useful to highlight some
institutional differences in educational reforms and
the structure of the educational system in the two
countries, for the period under analysis.
In the Italian case, a gradual destratification of the
school system can be observed from the 1940s onwards.
Fascism, in power from the 1920s, had strengthened
the élitist features of the school system with the already
mentioned Gentile reform, whose aim was to
clearly differentiate school tracks in order to adapt
education to a segmented and corporatist society.
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An implication of this model is that if the costs of
En þ 1 decline over time and the benefits associated
with it increase, more individuals will pursue En þ 1. In
other words, if the costs of schooling decline and
educational credentials become increasingly important
at entry in the labour market, more people will engage
in higher education. This model, thus, explains
educational expansion over time in terms of declining
costs, C, and increasing educational returns, B.
Although some empirical evidence shows that the
latter growth has stopped (Jackson et al., 2005), the
argument still holds if the decrease in costs is stronger
than the one for benefits. From the point of view of
class IEO, this model predicts that it will persist in
spite of educational expansion, if the class-specific
differences with respect to SD and Pf do not change.
125
126
BALLARINO et al.
secondary education. For instance in 1960, 80 per cent
of those attending secondary education were doing so
in private schools (Fernández, 2001).
In addition one has to consider that the economic
and living conditions of the majority of the Spanish
population had worsened dramatically in the
aftermath of the Civil war. This was a consequence
of the destruction of the production system and of the
international isolation of Franco’s regime after the
end of the Second World War. The average income per
capita in 1945 was 66 per cent of that in 1935, and it
caught up with the previous Civil War levels only in
the 1950s (Alonso and Conde, 1994). The combination
of a highly stratified and private educational system
with the dramatic economic hardships makes up a
scenario for strong class-based educational inequalities
in the post-Civil war years.
The main structural reform of the Spanish educational system that aimed at increasing public education
and educational attainment at higher levels was passed
in 1970, only a few years before Franco’s death. With
this reform the track system was abolished, and a
comprehensive system of compulsory education until
the age of 14 was introduced. One should note,
however, that some timid steps towards an opening of
the educational system and greater investments in
public schooling had already been taken since the
beginning of the 1960s. For instance, the age of
compulsory education was formally raised from 12 to
14 years in 1964.
Besides this stylized description of the Italian and
Spanish educational systems, in Table 1 we present two
indicators of the parameters of the educational
decision model discussed in the previous section. We
focus on changes over time of the risk of educational
failure (Pf) and of employment security within the
family of origin, to the extent that it might increase the
propensity of risk-taking (Eriksson, 1996). The risk of
educational failure is operationalized as the percentage
of those who have started higher secondary education
and have dropped out before completing it. The level
of employment security refers to the employment
relation of the head of the family, when the respondent
was at school-age: we distinguish employees and
employers with employees from those who are selfemployed with no employees and family helpers.3
Although this is a somewhat rough distinction, one
might argue that the second group faces higher
insecurity than the first one.
Table 1 shows that in both countries the risk of
dropping out at non-compulsory secondary education
has grown less over time. In Spain, this reduction first
takes place for the cohort born after the Civil war and
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However, in 1940, a first reform partially corrected
this orientation, reducing the number of tracks in lower
secondary schooling. After the war and the overthrow of
the Fascist regime, policies oriented towards educational
expansion and the destratification of the educational
system were pursued by the new democratic governments, under the influence of the Socialist and the
Communist parties.
A socio-economic context including fast industrialization, urbanization, and steady increase in income
and consumption (referred to as the Miracolo economico) helped school reform policies to gain consensus,
and a major school reform was introduced in 1962:
education was made compulsory until age 14, up from
age 10, and lower secondary school tracking was
abolished (Martinelli et al., 1999; Schizzerotto and
Barone, 2006). During the 1960s, the destratification
process was extended to higher secondary schools:
although fully comprehensive schools were not introduced, the differentiation between vocational and
academic tracks diminished, and, most importantly,
in 1969 access to university was opened to all students
holding a 5-year higher secondary diploma (maturità),
while earlier students coming from vocational and
technical schools were excluded from most of the
university subjects.
In the 1970s Italy went into a period of political
instability, and further school reforms oriented towards
inclusion and against selection were designed but only
partially enacted. Only in the late 1980s discussions
about school and university reforms started again, but
destratification ceased to be the main issue, in favour
of decentralization (Schizzerotto and Barone, 2006).
During the 1990s some significant steps in this
direction were made, but our data do not give us the
possibility of studying their association with IEO. For
the period we observe, the main orientation of the
Italian school policy was one favouring destratification
and educational inclusion, although the efficiency of
the policies is still under discussion.
In the case of Spain, after the Civil War (1936–1939)
and for most of the period observed here, two aspects
of the educational system stand out. First, it was an
extremely highly stratified system. Students had to pass
a selective exam at the age of 10 and were accordingly
sorted into two separate tracks, one of which led to
secondary education while the other one was a deadend track, with no possibility of pursuing further
education. Second, under Franco’s authoritarian
regime, the State had mainly a subsidiary role in
education. Schooling was, by large, dominated by
the private sector and by religious institutions
within it. This was particularly true at the level of
EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
127
Table 1 Parameters for educational choices, by cohort
Spain
Cohort
1910–1919
1920–1929
1930–1939
1940–1949
1950–1959
1960–1969
Italy
Failures higher
secondary (%)
Parents with
secure
employment (%)
Failures higher
secondary (%)
Parents with
secure
employment (%)
31.0
31.8
31.6
14.7
14.6
17.8
34.0
41.8
46.3
53.1
60.3
64.9
45.5
51.5
35.8
38.0
37.1
41.9
44.7
53.0
56.6
61.2
66.9
69.5
who finished compulsory education between 1952 and
1961, while in Italy it starts one cohort earlier, for the
cohort born in the 1930s, who finished compulsory
education in the 1940s. Moreover, there are hints that
the level of employment security experienced by the
family of origin when the subject was 14-years old has
steadily increased over time in both countries. If one
refers to the model of educational decisions discussed
in the previous section, the results of Table 1 seem to
pave the way for a hypothesis of declining IOE over
time, both in Italy and Spain.
Data, Variables, and Methods
Data
The data used for Italy merge the Indagine nazionale
sulla mobilità sociale (INMS, 1985) and the first wave
of the Indagine longitudinale sulle famiglie italiane
(ILFI, 1997) after checking for their consistency
(Ballarino and Schadee, 2005). Data from INMS for
cohorts born from 1920 to 1959 and from ILFI for
cohorts born from 1920 to 1969 have been merged in a
single file, with 11,036 respondents.4 For Spain, we
used data from the Socio-demographic Survey (SD). A
retrospective survey was conducted by the Spanish
National Statistical Institute in 1991 on a sample of
157,100 respondents. We used cohorts from 1920 to
1966 only (102,763 cases) because individuals from the
more recent ones may not have finished their studies
as they were interviewed in 1991.
individual’s father and mother at age 14 (age 16 for
Spain). When parents were employed in different
occupational classes, the higher-ranking of the two
parental classes was attributed to the individual (‘dominance approach’). Classes are coded following a
variation of the Goldthorpe classification (as presented
in Breen, 2004, tab. 1.1) adapted to Southern European
societies to deal more adequately with the persistence
of the agricultural classes, which were relevant until
the 1960s. The scheme distinguishes six classes:
Bourgeoisie (classes I þ II of the Goldthorpe scheme);
White Collars (IIIa and IIIb, except for unskilled nonmanual workers included in the urban working
class (Uwc) here); Urban Petty Bourgeoisie (IVab);
Agricultural Petty Bourgeoisie (IVc); Urban Working
Class (V, VI and VIIa); and Agricultural Working Class
(VIIb).
Education is defined as the highest educational title
achieved by an individual, coded as a four-classes
ordered variable: (i) elementary (up to 5 years of
schooling, including people with no schooling and
with some schooling); (ii) lower secondary (corresponding to completed compulsory schooling up to 14
years of age, and including up to 2 years of further
vocational training not leading to university); (iii) higher
secondary (a full higher secondary degree); (iv) university (corresponding to a full 3–6 years university
degree). Translated into the Casmin educational
classification (Breen, 2004, tab. 1.2) these four levels
are: Elem ¼ 1a þ 1b; Low Sec ¼ 1c; Hi Sec ¼ 2a þ 2b
þ 2c_gen þ 2c_voc; Uni ¼ 3a þ 3b.5 Appendix Table 1
shows education by social class by cohort tables which
are used in the analysis.
Variables
Cohort is coded by decades of birth, starting from 1920–
1929 up to 1960–1969 (1966 for Spain). Class of origin is
coded, as usual, according to the occupation of the
The Statistical Model
The model proposed here has been developed
originally by psychologists in other contexts
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Sources: Spain, Socio-demographic survey (INE 1991) for failures, Social classes and social structure survey (CIS 2006) for employment;
Italy, ILFI (1997; 1997þ1999 for failures).
128
BALLARINO et al.
1990; Long and Freese, 2003). Using T for a cohort
effect, this gives
P
k¼1...e CðkÞ
P
ln
¼ C þ T þ E
ð1Þ
k¼eþ1...K CðkÞ
¼ Ct þ E
in the parametrization given before with the constraint
Ct – C0 t ¼ constant for all values of t and all pairs of
classes C, C0 . Put differently, the distances among classes
remain the same. This specification, thus, assumes that
the educational expansion is homogeneous for all social
classes. We test the validity of this by means of a more
complex model with interactions between class, cohort,
and educational separators:
P
CðkÞ
ln P k¼1...e
¼ C þ T þ E þ C T
k¼eþ1...K CðkÞ
ð2Þ
þ C E þ T E
¼ Ct þ Etc
in the parameterization given before with the constraint that
Etc ¼ 0Et þ 00Ec
In this more general specification the parameters C T
express how the class IEO might change differentially
under educational expansion, while the parameters T E
express how the educational expansion varies over time
for each single separator (threshold). In this way, the
model includes both class inequality and educational
expansion. One should note that in the usual log-linear
and logistic analyses educational expansion is not
explicitly modelled since it is a marginal effect, while
interest centres on the interaction effects. In this
difference lies, in our opinion, the main substantive
interest and usefulness of the cumulative model.
Standard logit and log-linear analyses of IEO took their
inspiration from the log-linear models of class mobility,
where the variation of the margins is not constrained, but
the interactions in the table are modelled. Substantively,
this meant estimating relative mobility; the relative
chances of mobility for the different classes were
modelled conditional on the change of the occupational
structure. While this makes substantive sense for a class
of arrival by class of origin table, in the case of an
education by class of origin table there is far less
substantive reason to leave the variation of the educational levels without constraints.
Empirical Results
The Expansion of Education
First, models were estimated of an education by cohort
cumulative table, in a reduced version of model (2)
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(Edwards and Thurstone, 1952). In the generalized
linear model tradition, it has been presented as
ordinal regression by McCullagh (1980; see Nelder
and McCullagh, 1983), and is known as generalized
ordinal logit model (Long and Freese, 2003).6 The
main difference between this approach and the more
usual (conditional) logit and log-linear models is that
the model fits a cumulative logistic curve for education
by class of origin or any other independent variable
defining a social group: gender, cohort, etc. From this
it follows that class and other non-educational
parameters do not just fit certain sums of frequencies
for the variable mentioned, as in log-linear and
logistic analyses, but also involve the total quantity
of education of the class of origin (put differently,
a parameter for a class represents an interaction,
in log-linear terms, between class and education).
To the best of our knowledge, this model has never
been applied before to the study of the IEO. However,
it has some advantages over the (conditional) logit
models ordinarily used in the field (Mare, 1980), as it
provides a synthetic measure of final educational
attainment by class and includes explicit parameters
for educational expansion.
Formally, let the size of a class (of origin) be C, and
let the frequency in a given class of origin for
obtaining an educational title e be C(e): then C(e)/
C ¼ p(c, e) is the fraction of the class that has a certain
title. In its simplest form, the model proposes that ln
P
P
½ k¼1...e CðkÞ= k¼eþ1...k CðkÞ ¼ C þ E , where C is a
(set of) parameter(s) giving the class location (location
of the curve representing the class) and E is a (set of)
parameter(s) which determine the location of the
separators between educational titles. In principle the parameters can vary for each class (Ec) and and parameters can vary over time ( Ct, Et). If each class
at each point in time is allowed to have its ‘own’
parameters for the separator values (Etc) the model
would fit perfectly. The constraints on the parameters are that they (should) apply to more than one
class and that variation over time should show some
sort of regularity for the and parameters.
Substantively, we interpret the C parameters as a
measure of class position in the ranking of (resources
useful for) educational attainment, and the E parameters as a measure of the resources needed to pass
one educational threshold or separator (educational
transition). Moreover, the models we consider include
change over time. The base line presentation of this
model is an ordered logit model where class and
cohort parameters determine the location of a given
class at a certain point in time (Peterson and Harrell,
EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
129
Table 2 Model selection for education over time
Model
Terms
AþE
A þ E þ T E
A þ E þ Tm E
Spain
1
2
3
4
AþE
A þ E þ T E
A þ E þ T E
þ A5 E
A þ E þ T (el) þ A5 E þ A3 E
DF
P
356.6
64.5
6.2
8
6
6
0.000
0.000
0.40
4157.8
1480.4
29.5
6.4
8
6
4
3
0.000
0.000
0.000
0.094
A ¼ Cohort (age) qualitative; A3, A5 ¼ cohorts 3, 5 qualitatively different from the others;
T ¼ Time, cohorts parameterized: cohort 1:20–29 2:30–39 3:40–49 4:50–59 5:60–69 (Spain 66)
T¼
0
1
2
3
4
(Italy) Tm ¼
0
1
2
4
8
E¼ separators Education levels;
e-l ¼ separator elementary–lower secondary; l-h ¼ separator lower secondary–higher secondary
þ adds term; interaction between variables (Wilkinson and Rogers, 1973).
without the class parameters ( C). Table 2 shows these
models and their fit measures. Model 1 for both
countries specifies the effect of cohort (A) and the
separators for the four educational levels (E). Model 2
adds an interaction term for time and the separators
(T E). The Time (T) variable is a linear parameterization of the cohorts, which are given values from 0 to 4.
This interaction term means that the quantity of
education in the population changes linearly (in logits)
across cohorts (less resources are needed in order to
pass a separator7). But the fit is not satisfactory: in
neither country has educational expansion been linear
over time. Therefore, model 3 substitutes linear time by
education interaction terms with a different time by
education term for each country. In Italy, we get a good
fit with a multiplicative parameterization of time,8
while the case for Spain is less regular, and has to be
modelled by means of a time by education term for
the transition from elementary to lower secondary
and two cohorts by education terms for cohorts 3 and 5.
Substantively, this means that in Italy there are two
big and consecutive leaps in education: one for the
cohort born immediately after World War 2, and one,
twice as large, for the cohort born in the 1960s, during
and after the Miracolo economico that, in little more
than a decade, transformed Italy from a mostly
agricultural country to an industrial one. In Spain,
there is a regular linear increase in education, but two
cohorts stand out from this pattern, namely the one
born after the Civil War and, as in Italy, the one born
in the 1960s. Thus, the expansion of education
followed different paths in Italy and Spain: while in
Italy it started from the cohort born in the 1930s and
increased its pace with the following ones, in Spain it
has been less regular. The parameter estimates for the
A3 E and A5 E effects9 tell us that with the cohort
born in the 1940s the expansion relented, only to
resume with the following one, while with the fifth
there has been a great jump forward. We would
explain this difference between the two countries by
referring to the different timings of their transition
from Fascism to democracy and of the socio-economic
modernization associated with it: while in Italy Fascism
fell after the second World War, in Spain the
authoritarian regime resisted until the 1970s and,
especially in the two decades after the Civil War,
managed to reduce educational expansion and, more
generally, societal modernization.
Class IEO Over Time
We turn now to the results of the analysis of the
variation of class IEO over time, addressing the two key
questions motivating this paper. Table 3 describes the
analysis for the two countries. Model 1 for Italy specifies
the effect of class (C), cohort (A) and the separators for
the four educational levels (E). This is a proportional
model equivalent to a standard ordered logit since there
is no interaction between the separators and the other
independent variables. The next models explore some
interactions. Model 2 suggests that the educational
separators work differently for the petty bourgeoisie,
since the interaction term between a dummy (P) that
identifies the petty bourgeoisie and the separators (E)
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Italy
1
2
3
chi2
130
BALLARINO et al.
Table 3 Model selection for education by class over time
Model
Terms
AþC
AþC
AþC
A þ C þ T C
A þ C þ T C3
A þ C þ T C3
Spain
7
8
9
10
11
12
13
14
AþC
þE
AþC
þ E þ Apb E
AþC
þ E þ Apb E þ Uwc E
AþC
þ E þ Apb E þ Uwc E þ T E
AþC
þ A5 E
þ E þ Apb E þ Uwc E þ T E
A þ C þ T C þ A5 E
þ E þ Apb E þ Uwc E þ T E
A þ C þ A C þ A5 E
þ E þ Apb E þ Uwc E þ T E
A þ C þ A C þ A5 E þ A3 E þ E þ Apb E þ Uwc E þ T E
þE
þ E þ P E
þ E þ P E þ T E
þ E þ P E þ T E
þ E þ P E þ T E
þ E þ P E þ Tm E
DF
P
531.7
490.1
185.2
111.1
113.3
62.4
78
76
74
69
72
72
0.000
0.000
0.000
0.000
0.000
0.780
5660.1
5440.6
5358.0
2319.0
705.2
181.2
100.3
75.1
78
76
74
72
70
65
50
48
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.007
A ¼ Cohort (age) qualitative; A3, A5 ¼ cohorts 3, 5 qualitatively different from the others;
T ¼ Time, cohorts parameterized: cohort 1:20–9 2:30–9 3:40–49 4:50–59 5:60–69 (Spain 66)
T¼
0
1
2
3
4
(Italy) Tm ¼
0
1
2
4
8
E ¼ separators Education levels: e-l ¼ separator elementary–lower sec.; l-h ¼ separator lower sec. –higher sec.
C ¼ Class; C3 ¼ class coded in 3: (Pba eq Awc) (WhC eq Pbu eq Uwc) (Bor); Upb ¼ Urban petty bourgeoisie; Apb ¼ Farmers; Uwc ¼ Urban
working class; P ¼ UpbþApb;
þ ¼ addsterm; ¼ interaction between variables (Wilkinson and Rogers, 1973).
significantly improves the fit of the model. Model 3 adds
an interaction term between time and the separators,
while model 4 looks at the linear changes of the class
effects over time (T C interaction). In both cases these
interactions significantly improve the fit of the model.
Substantively, this means that the pace of educational
expansion has differentially affected the various educational levels and that the effects of class have changed
(also relatively) over time. The next two models 5 and 6
elaborate on model 4 by adding a constraint on the class
over time effects and specifying that the pace of the
educational expansion is not linear,10 but the main
conclusion on IEO over time does not change.
For Spain, the specification of the models starts with
an ordered logit model with proportional odds
(model 7) assuming that class and cohort have a
proportional effect for all educational levels (separators).
The next models add interactions to test whether this
proportionality assumption holds. Model 12 is equivalent to model 4 for Italy, as it includes an interaction
between time and class (T C) meaning that the effects of
class on education change in Spain as well. However,
some discrepancies between the two countries can be
highlighted. First, while in Italy the effects of the educational separators for the urban and agricultural petty
bourgeoisie are different from the ones for the other
classes (the P E term in model 4), in Spain one finds
specific interactions for the agricultural petty bourgeoisie (Apb E in model 8) and for the urban working class
(Uwc E in model 9). Substantively, this means that the
educational separators are not the same for all social
classes, i.e. the difficulty of passing through the various
educational levels is not the same for all social classes.
While in Italy both agricultural and urban petty
bourgeoisies show the same pattern, in Spain the Uwc
and the agricultural petty bourgeoisie diverge differently
from the general pattern. Second, in Spain the change
over time of the class effect is less regular than in Italy;
thus, model 11 includes a specific interaction between
education and the last cohort (A5 E), when educational
expansion increased its speed. Models 13 and 14 are
refined versions of model 12, which allow improvement
to the fit of the model with a categorical specification of
the class effect on education over time (A C) and the
other interactions already seen in Table 2 between
education and a specific cohort, namely the third.
The Direction of Change in IEO
With our research question in mind, the next step is
to establish the direction of the change of IEO over
time and its relation to the process of educational
Downloaded from http://esr.oxfordjournals.org/ at Pennsylvania State University on February 18, 2016
Italy
1
2
3
4
5
6
chi2
EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
131
Table 4 Fitted parameters for education by class over time, Italy and Spain
1920–1929
1930–1939
Cohort
1940–1949
1950–1959
1960–1969
Italy
Model 6: chi2 62.4; 72 df
0.99
1.79
3.05
4.04
4.76
5.95
0.95
1.57
2.85
3.84
4.31
5.50
0.60
1.07
2.33
3.32
3.54
4.73
0.32
0.64
1.90
2.80
2.84
3.02
0.65
0.81
2.07
2.97
2.76
2.95
–3.05
–1.79
0
–3.35
–1.88
0
–3.65
–1.98
0
–4.24
–2.17
0
–5.43
–2.55
0
–2.60
–1.45
0
–2.90
–1.53
0
–3.20
–1.65
0
–3.79
–1.84
0
–4.98
–2.22
0
1.20
2.10
3.18
3.71
4.03
5.29
0.93
1.82
2.91
3.44
3.64
5.00
0.44
1.41
2.47
2.77
2.89
3.91
0.08
0.90
1.85
2.33
2.12
3.45
0.29
1.05
1.85
2.26
2.10
3.13
Separators
Bourg., WhCo, Upb, Awc
Elementary–higher sec.
Lower sec.–higher sec.
Higher sec.–university
1.32
0.87
0
1.47
0.90
0
1.51
0.73
0
1.76
0.96
0
3.45
1.49
0
Urban working class
Elementary–higher sec.
Lower sec.–higher sec.
Higher sec.–university
1.48
1.06
0
1.62
1.09
0
1.67
0.91
0
1.92
1.15
0
3.60
1.67
0
Agricultural petty bourgeoisie
Elementary–higher sec.
Lower sec.–higher sec.
Higher sec.–university
1.02
0.66
0
1.16
0.70
0
1.20
0.52
0
1.43
0.76
0
3.14
1.29
0
Separators
Bourg., WhCo, Uwc, Awc
Elementary–higher sec.
Lower sec.–higher sec.
Higher sec.–university
Urban petty bourg., Agr. petty b.
Elementary–higher sec.
Lower sec.–higher sec.
Higher sec.–university
Spain
Model 14: chi2 75.1; 48 df
Class
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
expansion. This requires an examination of the
parameters estimated in model 6 for the class and
time interaction (T C) and the class and separators
interaction (P E). Table 4 gives the necessary parameter estimates. The upper panel of the table shows
the parameters for Italy, the lower panel those for
Spain, estimated, respectively, by models 6 and 14 of
Table 3. The parameters for class in each cohort
are the Ct ðC þ T þ C T Þ parameters that give
the class location in the ordering of resources
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Class
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
132
BALLARINO et al.
cohort and exploding with the last cohort, and, second,
the class-by-education interaction effects for the urban
working class and for the agricultural petty bourgeoisie
have opposite directions, with the children of the
former getting, in proportion, more education than
the children of the other classes, and the children of
the latter getting less.
The parameters of Table 4 also offer some hints on
whether the educational expansion has benefited some
classes more than others. It has been shown that in
Italy educational expansion came about with two large
and consecutive increases for the cohorts born between
1950–1959 and 1960–1969. The parameters show that
in these cohorts the agricultural classes benefited most
from educational expansion, as can be seen in the
larger reduction of the class effects for the agricultural
classes born between 1950–1959 and 1960–1969 with
respect to the other classes. In Spain, the picture of the
change of class effect along educational expansion is
somewhat complicated by the fact that the urban
working class and the agricultural petty bourgeoisie
started out, respectively, more and less favourably in
the educational attainment of their offspring, in
proportion, than did the other classes. However, the
classes which appear to have benefited more from the
expansion of education that took place with the cohort
born in the 1960s are the agricultural working class,
and, to a lesser extent, the urban working class, and
the agricultural petty bourgeoisie.
Conclusions
This paper studied class IEO over time in Italy and
Spain by means of a relatively innovative statistical
model for this topic, the cumulative logit. This model
allows taking explicitly into account educational
expansion when modelling class IEO, differently from
the log-linear and (conditional) logit models which are
normally used in sociological research for this
phenomenon. Moreover, because of its cumulative
structure, the model gives a parsimonious view of IEO
and its change over time, as it does not separate the
outcomes of the educational process into separate
transitions, as conditional logits do. The price for this
is some loss of detail, but in our opinion this is a fair
price.
Substantively, we can now answer the two questions
put forward in the introduction, namely whether class
IEO remained stable over time in Italy and Spain, in
spite of the remarkable educational expansion, and
if not, which class benefited most from this educational expansion? With regard to the first question,
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relevant for education. The separators by class are the
Ec parameters that are a measure of the resources
needed to pass one educational threshold that might
vary across time (educational expansion) or classes.11
The decreasing parameters mean that education, at
all levels, is increasing in both countries, as the percentage of people not passing the separators decreases.12
The estimates show also that in both countries there is
a decreases in class inequalities.13 For Italy, considering
the differences between bourgeois and farmhands in
the first (5.950.99 ¼ 4.95) and in the last cohort
(2.950.65 ¼ 2.3) this is clear. This change was already
known and discussed in the literature and the usual
argument is that farmers and farmhands have nearly
disappeared in Italy, so it is not all that relevant that
their relative position becomes less unequal. However, if
one compares Uwc with the bourgeoisie in the first and
last cohort the difference at the beginning is 3.05 and in
the last cohort it is 2.32. This is not a large decrease in
the difference, but it is a decrease. This conclusion has to
be interpreted keeping in mind that the model is based
on a logistic distribution: in the flat part at the beginning
and end of a logistic curve, a change in X translates into
a relatively smaller change in Y when compared with the
central part of the curve. If one considers the tables
presented in the Appendix, instead of the fitted
parameters, between cohorts 20–29 and 60–69 the
percentage of university degree holders increases from
23.5 to 32.5 among the bourgeoisie and from 1.0 to 4.9
among the working class in Italy. Thus, the inequality in
access to university education between the two classes
actually increases if it is measured in terms of differences
(from 23.51.0 ¼ 22.5% to 32.54.9 ¼ 27.5%) and
decreases if it is measured with odds (from 23.5/1 ¼
23.5 to 32.5/4.9 ¼ 6.6). This story is not really influenced
by the fact that there is a slight difference in the position
of the separators for the petty bourgeoisie which makes
them have slightly higher fractions of children with only
elementary or lower secondary education than they
would have had if the separators of the other classes
applied to them.
For Spain, the story is more complex as has
already been seen. In terms of the differences between
the bourgeoisie and the farmhands, they also diminish
from the first to the last cohort, going from
4.09 (5.291.20) to 2.84 (3.130.29). For the urban
working class the difference in the first cohort is 2.51
(3.711.20) and in the last cohort 1.97 (2.260.29). In
comparison with Italy the reduction in IEO has been
somewhat lower, especially for the agricultural classes.
Looking at the separators, two things should be noted:
first, the cohort pattern already seen above, with
educational expansion slowing down for the 1940s
EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
authoritarian regime which kept the country out of the
war but retarded its educational development.
In order to make this picture clearer, more research
is needed. More detailed hypotheses drawn from
historical and institutional circumstances have to be
developed and empirically tested. This work should
incorporate gender as a not-negligible dimension of
IEO. This is quite important for Southern European
countries, where structures of social reproduction are
more gender-based than in Northern Europe16:
hypotheses about the impact of Fascism and its antimodernist view of gender roles on gender IEO could
be developed and empirically tested. Another limitation of our study is that data are not that recent,
especially for Spain: more recent data could allow us to
incorporate the cohort born in the 1970s into the
analysis, to check whether the trends observed here
persist. We hope that our paper might stimulate
further research along these lines.
Notes
1.
2.
3.
4.
5.
6.
7.
Italy and Ireland are exception to this pattern
with little or no decrease in IEO, or with very
mixed evidence.
The model that Eriksson and Jonsson (1996a)
developed to analyze the Swedish case does not
directly include the probability of status decline
(SD). But they treat it with reference to the
‘Social Position Theory’. However, we think that
this is a mechanism quite stable over time, and
do not think class-specific differences in SD
change.
In Italy we only distinguish employee from selfemployed, since the data aggregate the latter.
On the basis of our check of two datasets, and
like previous studies that merged them (Pisati
and Schizzerotto, 2004; Breen et al., 2005), we
will ignore design effects.
Detailed coding of educational titles into our
four categories is available from the authors.
The estimation presented here was done by a
macro written in GLIM by one of the authors.
The command to run this model is GOLOGIT2
in Stata, but some parameters estimated here
cannot currently be estimated with it.
Actually, a significant estimate of an interaction
term just means that education changes: we can
say it increases because we already know this
from other evidence. But it is important to notice
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results show that the class IEO has decreased in both
countries, as expected: we think this depends on the
reduction in the risks families associate with the choice
to further their offspring’s schooling after compulsory
education (Pf in the notation used above). This
reduction, in turn, depends on decreasing school
selectivity and on increased parental employment
security. Our result differs from what previous research
found using conditional logit and log-linear models for
Italy and conditional logit and ordinary least squares
(OLS) for Spain. In our opinion, this difference does not
depend much on the models, but on the typical
interpretation scholars give of the results obtained
modelling educational transitions with conditional
logits: what is typically found is a decrease in IEO at
the lower transitions, and stability at the higher levels,
and intepretation typically centres on the latter, downplaying the former.14 However, more work has to be
done on the topic, analytically comparing different
models for the study of IEO across time.
The answer to the second question is less straightforward. In Italy, it is the agricultural classes that
benefited from the educational expansion, and this
process had an acceleration for the cohorts born in the
1950s and the 1960s. We would explain this change,
already noted in the literature but not really interpreted, as a result of improvement in transport, which
has made it possible for girls and boys from marginal,
difficult-to-reach rural villages to go on to further
education.15 In Spain the expansion of education
accelerated one cohort later than in Italy, possibly
because of the delay in modernization caused by the
long-lasting Franco’s authoritarian regime. The Civil
War from the 1930s, from which this regime was born,
could also explain a (relative) contraction in the access
to higher secondary education found for the cohort
born after the war. However, when the great schooling
expansion arrived, the class which benefited more was
the agricultural working class, and to a lesser extent the
Uwc and the agricultural petty bourgeoisie.
Thus, what we observe is a similar process (educational expansion with a decrease in IEO, strong for the
agricultural classes but significant also for the Uwc)
which takes place with some differences in the two
countries under study. Differences in educational
expansion are to be explained by the different histories
and institutional developments of the two countries:
Italy had a relatively short-lasting Fascist regime which
got Italy involved in the Second World War and fell
because of the defeat, and was followed by a
democratic regime which favoured modernization
and educational expansion. Spain had a very hard
Civil War in the 1930s, followed by the Franquist
133
134
8.
9.
11.
12.
13.
14.
that in order to check the direction of change
one has to look at the parameters.
We model time as Tm, Time Multiplicative, for
the sake of numerical elegance, but it is clear that
this Tm parameterization cannot be considered
to be a prediction: we would not say that cohort
1970–1979 would have the value of 16 on this
parameter!
Parameters are not reported for lack of space, but
are available from the authors. However, by
looking at the values for the separators in Table
5, the slowing down of educational expansion
can be seen, as the values of the separators ceases
decreasing for the 1940s cohort (i.e. the percentage of people not making the transition ceases
decreasing).
The class scheme is collapsed in a threefold
version (bourgeoisie, agricultural classes, and all
the other classes), while the effect of time is
specified multiplicatively, as in the analysis
reported above.
One should note that the parameterization of the
educational separators sets the separator between
higher secondary and university as the reference
category and expresses the other separators as
left-side shift with respect to the reference
category. In this way, the class parameter ends
up expressing the effect of a given class on the
higher secondary–university separator.
Looking at university education it can be seen that
there is an actual increase in the parameters
between the fourth and the fifth cohort. This can
be explained by the fact that many young
individuals who were interviewed are still in the
university: samples include people aged 28 years in
Italy and 25 years in Spain, while in both countries
it is not uncommon to conclude university after the
age of 30. But a part of the phenomenon could
come from some real slowing down of the pace of
university expansion: more recent data are needed
to control both explanations.
This result can be seen also in the parameter
estimates of models 4 and 11 of Table 6
(available from the authors).
We estimated logit models for educational
transitions for the Italian case, both on the
observed frequencies and on frequencies fitted by
the cumulative logit, and in both cases the results
15.
16.
were quite close to those of the existing studies
(Cobalti, 1990; Pisati, 2002). We also estimated a
linear regression model, and its results matched
those of Cobalti and Schizzerotto (1993). Results
are not reported for lack of space but they are
available from the authors.
Some comments suggested that the mechanization of agriculture played a role, stimulating
farmers to get more education in order to be able
to operate the new agricultural machines. This is
a possible alternative hypothesis.
It is worth noting that the result of persisting
inequalities for Italy found by Breen et al. (2005)
refers only to men.
Acknowledgements
Previous versions of this paper and of the work leading
to it have been presented on various occasions,
particularly at the RC28 meetings in Los Angeles
(2005) and Nijmegen (2006), and in the Reunión
Intercongresos del Comité de Investigación Sobre
Estratificación Social, Madrid (2005). We would like
to thank all those who made comments and suggestions, particularly Vida Maralani, Robert Mare,
Reinhart Pollack, Luis Garrido, Julio Carabaña, John
Goldthorpe and Jaap Dronkers, as well as the three
anonymous reviewers of the ESR. Fabrizio Bernardi
and Miguel Requena acknowledge the financial support
of the Fundación de las Cajas de Ahorros (FUNCAS).
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Authors’ Addresses
Gabriele Ballarino (To whom correspondence should
be addressed), Dipartimento di Studi del Lavoro e
del Welfare, Università di Milano, Via
Conservatorio 7, 20122 Milano, Italy.
Email: [email protected]
Fabrizio Bernardi, CEACS, Juan March Institute, Calle
Castelló, 77, 28006 Madrid, Spain.
Email: [email protected]
Miguel Requena, Sociology Department II, UNED, C./
Obispo Trejo s/n, 28040 Madrid, Spain.
Email: [email protected]
Hans Schadee, Dipartimento di Psicologia, Università
di Milano-Bicocca, edificio U6, p.zza dell’Ateneo
Nuovo, 1, 20126 Milano, Italy.
Email: [email protected]
Manuscript received: January 2007
Downloaded from http://esr.oxfordjournals.org/ at Pennsylvania State University on February 18, 2016
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EDUCATION AND CLASS INEQUALITY IN ITALY AND SPAIN
137
Appendix
Table A1 Tables used for the analyses
Elem.
Italy
Low sec.
High sec.
Cohort 1920–1929
University
N
7.3
21.5
60.1
91.4
70.4
95.2
73.7
26.5
25.3
24.8
4.4
20.6
4.1
14.5
42.6
39.2
10.8
2.6
8.0
0.4
8.6
23.5
13.9
4.3
1.6
1.0
0.4
3.2
68
79
323
498
476
271
1,715
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
6.8
11.8
47.4
80.7
62.2
87.5
62.1
17.6
28.3
31.7
12.8
27.0
11.3
22.3
Cohort 1930–1939
44.6
40.9
15.7
4.7
9.6
0.7
11.6
31.1
18.9
5.1
1.7
1.2
0.4
4.0
74
127
432
530
749
265
2,177
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
5.0
8.4
30.5
59.7
43.2
73.1
41.8
21.0
23.0
32.7
26.3
36.5
21.2
30.6
Cohort 1940–1949
39.5
39.9
28.0
11.0
16.2
5.7
19.7
34.4
28.6
8.7
3.0
4.1
0.0
7.9
119
213
514
464
1,023
245
2,578
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
2.3
2.4
12.1
28.4
21.7
45.4
19.7
10.0
16.9
38.5
46.4
44.4
38.3
38.5
Cohort 1950–1959
43.5
51.4
38.1
18.8
28.1
14.3
30.7
44.1
29.3
11.3
6.4
5.7
1.9
11.1
170
249
512
377
1,234
209
2,751
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
0.0
0.9
4.3
6.8
8.4
20.2
6.4
12.5
11.5
45.3
59.8
53.6
62.8
44.3
Cohort 1960–1969
55.1
56.6
39.3
25.8
33.1
16.0
37.7
32.3
31.0
11.0
7.6
4.9
1.1
11.6
136
226
417
132
810
94
1,815
(continued)
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Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
138
BALLARINO et al.
Table A1 Continued
Elem.
Spain
Low sec.
High sec.
Cohort 1920–1929
University
N
48.2
68.5
86.7
95.3
89.8
98.1
89.5
8.0
9.3
3.8
1.4
3.6
0.8
2.8
21.0
10.9
5.6
1.3
4.7
0.4
4.1
22.8
11.3
3.9
1.9
1.9
0.6
3.5
1,360
911
3,179
6,721
5,272
4,949
22,392
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
38.7
57.5
81.2
92.1
85.8
97.0
85.3
12.3
13.8
6.8
2.8
5.8
1.6
4.9
Cohort 1930–1939
18.8
16.1
6.5
2.6
5.1
0.8
5.0
30.2
12.6
5.4
2.5
3.3
0.6
4.8
1,219
787
2,775
5,215
5,112
4,349
19,457
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
24.3
47.1
72.6
84.8
75.4
91.4
73.9
20.4
19.0
12.4
6.3
10.9
4.8
10.3
Cohort 1940–1949
15.6
15.1
7.0
3.6
7.9
1.9
6.8
39.6
28.1
15.2
10.6
8.7
3.1
14.3
1,396
975
2,598
3,698
5,283
2,899
16,849
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
14.2
28.9
53.5
66.5
59.9
84.4
56.4
15.3
19.8
17.5
12.3
16.6
7.7
15.1
Cohort 1950–1959
24.0
23.1
13.9
10.6
14.8
4.8
14.2
46.7
28.1
15.2
10.6
8.7
3.1
14.3
2,246
1,843
3,576
3,616
9,644
3,039
23,965
Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total
3.6
8.0
16.7
24.8
21.1
42.7
19.9
17.8
29.9
43.5
45.7
42.8
41.0
39.0
Cohort 1960–1966
38.0
37.7
25.1
18.8
26.2
11.5
26.1
40.6
24.5
14.7
10.7
9.8
4.8
15.0
2,339
1,778
3,067
2,119
8,718
2,080
20,101
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Bourgeoisie
White collars
Urban petty bourg.
Agr. petty bourg.
Urban working class
Agr. working class
Total