CUMULATIVE INEQUALITIES IN ITALIAN HIGHER EDUCATION An analysis of data from the Italian Household Longitudinal Survey1

Moris Triventi* and Paolo Trivellato** University of Milano Bicocca - Italy

Working paper – Draft version. Please do not quote

14th -17th August 2007 Montreal

Research Committee 28 Summer Meeting

* Ph.D. candidate, Department of Sociology and Social Research. ** Professor of Sociology, Department of Sociology and Social Research.

1 The authors would like to thank Maurizio Pisati and Antonio Schizzerotto for their useful comments and suggestions. The research has been co-funded by the University of Milano-Bicocca and by the Ministero dell’Istruzione, dell’Università e della Ricerca, contract n° 2004149592.

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Abstract

Using data from the five waves of ILFI, the Italian Household Longitudinal Survey, this paper deals with the dynamics of higher education in the 20th century investigating how and how far cohort of birth and social class are associated with enrolment rate, drop-out rate, graduation behind schedule. Enrolment growth has not been followed by a proportional increase in graduation rates along the whole century. The drop-out rate has been high for decades, the amount of delayed graduations and the duration of the delay have been high too and have been increasing over time. As a consequence Italy is nowadays quite far from the other European countries in terms of tertiary education attainment. Moreover, in spite of the «1969 reform», there are still nowadays relevant inequalities in the rates of enrolment and graduation among different social categories. In particular, absolute social class inequalities tend not to diminish across cohorts. Upper classes not only have more opportunities than working classes to enter university and obtain a degree, they also have less chances of dropping-out, and graduating behind schedule. Results show cumulative advantages for higher classes, and cumulative disadvantages for lower classes.

1. Introduction

Studies of university systems traditionally follow two main approaches: the first one is

the «institutional approach» and the second one is the «inequality approach». The

former looks at universities using organizational concepts, trying to evaluate the

efficiency and the efficacy of the institutional functioning. The latter focuses on

inequalities in the field of tertiary education and how they change over time. In other

words, the focus of the first approach is the university functioning, whereas the object

of interest of the second perspective is the degree of inequality in the field of education

in contemporary societies. The «institutional approach» is adopted by organizations like

OECD (at the international level) or ISTAT, Almalaurea and MIUR (in Italy), which

collect data on the educational attainments of the adult population, university enrolment

and graduation rates, drop-outs and job opportunities for graduates (Almalaurea 2006a,

2006b; Istat 2000, 2004; Oecd 2003, 2006). The «inequality approach» is adopted by

academic scholars who investigate whether access to higher education and the

opportunity of graduating are equally distributed among different social categories,

according to gender, social origin and cultural capital (for example, Blossfeld e Shavit

1993; Schizzerotto et. al 2002; Breen et. al 2005).

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Usually, these two perspectives have been kept separate; in this paper we build a bridge

between the two research traditions. In the past some research has followed a similar

approach, trying to analyse the performance of university students according to their

social origins (Martinotti 1969; de Francesco and Trivellato 1983, 1985). Nevertheless,

the data which were analysed had many limits. Those surveys were carried out in

particular universities and therefore produced local results. Moreover, they analysed

short time series, based on cross-section data from administrative sources. Those

analyses were pretty good at describing change in university attendance year by year,

but did not enable the monitoring of the careers of students belonging to different

cohorts. The dataset we use for our analysis (Italian Household Longitudinal Survey,

see details below), on the other hand, allows us to study these phenomena. Our

perspective is broader in comparison with past research, for several reasons. First of all,

the members of the panel who have been interviewed have enrolled and graduated in

many Italian institutions, representatives of the whole Italian university system;

therefore our results can be generalised at the national level. Second, we can count on

data which are not related to specific academic years, but to the different academic

experiences of the members of different cohorts of birth. Third, information is collected

in a longitudinal and retrospective frame; hence we can study changes at the individual

or «micro» level and study in detail the diachronic characteristics of the social

phenomena under scrutiny (Blossfeld and Rowher 1995).

The paper is organized as follows. In the next section we present a brief history of

Italian Higher Education and in the third section we outline the broad theoretical

structure on which the hypotheses are built. After this, data, variables and statistic

methods employed in the analysis are described. In the fourth and fifth section we

present the main results of the analysis; in the sixth part we discuss the most important

results of the analysis and, finally, we outline some considerations on higher education

policy in the concluding remarks.

2. A brief history of Italian Higher Education

This paragraph is meant to provide an overall picture of the university system during the

second half of the 20th century. We focus on this time span because reliable data on

higher education are available since the mid-forties and because it is during those five

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decades that the cohorts under scrutiny experience their university education. Before

commenting graph 1 and 2, we underline two peculiar elements which are to be kept in

mind in order to better understand the dynamics of Italian higher education. First, in this

country degrees have legal validity, i.e. graduates are considered to have the same

amount of knowledge and competence in their field irrespective of the university where

they have gained their degrees. This validity rests on the still centralised system of

control (the ministry which states national regulatory frames) and is in the meantime the

main hindrance to devolving autonomy to Universities. While this validity has

straightforward effects in the domain of public employment (two thirds of graduate

posts in Italy), in the private sector recruiters tend more and more to screen graduates

according to actual competences and personality traits. To hold the laurea, the

certificate that entitles the holder to be named dottore has been for long time and partly

still is one of the most important pillars of the Italian culture. As a consequence

meritocracy has probably always been considered with mixed feelings. The key point is

to get a degree; then friends, relatives, patrons and the like will help in finding a

reasonably rated and paid post. If one considers that, as far as the starting salary is

concerned, graduates and high schools diploma holders are nearly on the same foot and

that career mobility of Italian graduates is nearly non-existent (Pisati e Schizzerotto

2002), one can better interpret what might be the mood of many university students and

the ensuing phenomena on which we have drawn attention at the very beginning,

namely high dropout rates, low graduation rates and long duration of studies.

The cost charged for tuition and fees has been, and still is, pretty low in Italian state

universities; if the legal validity is the same and the cost is lower, why spend more?

This is likely to be the rationale of most students, many of them entering the higher

education system for the first time in the history of their family. And most of them

commuting to the nearest university, as they cannot afford the cost of living out of

home. Attending the university in a town far from home is not a popular attitude in

Italy. Halls of residence are few and renting a flat can be very expensive in many

university towns. Student loans were virtually unknown till the mid nineties and are still

not popular today (a few thousands granted, mainly to engineering students).

Figures 1 and 2 depict five long time series concerning Italian Universities and are

meant to provide the reader with the vary basic knowledge, namely a rough idea of

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sheer numbers and an awareness of the most important changes-cum-reform which did

occur during the century. We look at the main trends starting that year and ending 1995-

96, i.e. when respondents born in 1970 should in principle have completed their

university study, allowing a three year period delay for graduating in case of 4 year

programmes and two year delay for graduating in case of 5 year programmes.

Let us look at total enrolments. During second world war and in the ensuing decade

numbers stay even around 220 thousand. Rules of access had been established by the

law enacted by the fascist minister G. Gentile which was inspired by what we would

call today ‘sponsored mobility’. Admission to tertiary education was allowed only to

students who had graduated from licei. No numerus clausus was implemented in any

faculty. The university was strictly under the ministerial central control. During the

second part of the fifties enrolments start to grow, helped by economic development

which was gaining momentum. But it is in 1965-66, when the baby-boomers were ready

for higher education, that numbers jump over 400 thousand. Growth constantly

continues till 1977-78. The sixties and the seventies are key years for Italian higher

education: in fact the “natural” increase of the first decade receives a boost in 1969

when a law is enacted which allows everyone who has successfully completed a five

year high school programme (licei, technical school, vocational education, any diploma

holder) to enrol in whatever university programme2. Numbers rose over 800 thousand,

for the Italian academic world it was some sort of revolution. As Recchi (2003) puts it,

«the door was open, but the house remained the same. The result was overcrowding,

physically and symbolically: physically because universities had to face expansion

without adequate facilities and re-arrangement of teaching roles; symbolically because

all students had to contend for the same degree». Interestingly enough, the reform did

not trigger expansion, which had started earlier, but provided a boost bound to last till

the end of the seventies. As a matter of fact new teaching resources were pretty fast

conferred, see the graph showing the boost in the number of professors which started in

2 After the pressures of students’ contestation in the second half of the ‘60s, the decree n.1239 of 31st

October 1969 instituted the first great reform of university system after the Second World War. Its main function was to liberalize the access to university by abolishing the rule imposed by Gentile’s law of 1923, which didn’t allow the access to tertiary education to students who had not attended the licei (classical or scientific studies). After the 1969 reform all students that have successfully concluded 5-year programmes at upper secondary school can enter university, without any restriction on the choice of the faculty or course.

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1971-72. But they were from the traditional breed, and neither immediately nor in later

years they understood that their role should have been revised, in order to cope with the

new profile of the audience. In principle, the quality of teaching should have improved,

as the student/teacher ratio, after a steady growth during the sixties, went down very

quickly (Figure 2). But the distance between the new students and the old university

was too simply too large. Also in Figure 2 one can see that in the academic year 1971-

72 the percentage of students behind schedule (fuori-corso) resumes its rise, a rise

which was bound to continue till the end of the nineties, when it was again as high as in

1950. The count of people who were admitted and soon gave up sounds as a memorable

defeat: two thirds of students who enrolled between 1970 and 1985 (de Francesco,

1988). Between 1977-78 and 1986-87 enrolments remained stable, around one million.

Public debate was continuing around the issues of how to cope with the unexpected

consequences which where under everybody’s eyes, but no overall solution was agreed

upon. So, when the trend resumed to rise in 1987-88 (see upper graph in figure1) the

Italian university system was still unprepared to deal with the second, robust wave of

growth.

It was only in 1999 that a full-fledged reform was enacted, defining three levels of post-

secondary education, a structure complying with the agreements signed in Bologna and

envisaging a European higher education space, namely first level or bachelor degree

(three years), second level laurea magistrale (two years) and doctoral studies (three

years). Therefore the reader should keep in mind that the work presented in this paper is

based on data which refer to the “old rule” (only one type of degree, 4 years). As the

first academic year of implementation of the new organization has been 2001-02, we

cannot say at present if the goals are going to be achieved3. Data from the first two

cohorts of new entrants seem to follow the usual pattern (one year delay in graduation,

25% dropout rate from first to second year).

One could be tempted to say that the legislative reaction aimed at redressing the

functioning of Italian higher education institutions has arrived too late in 1999. But one

3 The university reform - decree n° 509 - was enacted in 1999, but started to be implemented with the beginning of academic year 2001-02. The rationale was as follows: 1) to re-design the degree structure according to the Bologna model, 2) to allow university autonomy in curriculum design, 3) to stress a student-centered approach in teaching and learning, 4) to focus on employability of graduates, 5) to introduce opportunities for internationalisation.

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could wonder if a decree can effectively influence teaching and learning practices which

– we shall see in the following sections – have been in place for decades. Or if it is the

case that practices start changing and then the law follows, as in 1969. The issue is open

ended, in six or nine years time we will be able to draw a balance. By now, in 2007, no

relevant departure from the old practices can be seen, so the idea according to which

continuity and tradition will outbalance change and innovation cannot be dismissed, yet.

3. Theory and hypotheses

Our perspective is mainly descriptive in character: we share the persuasion that social

scientists very often devote themselves to the elaboration of complex explanatory

theories or sophisticated statistical models without paying enough attention to the

description of the empirical evidence they have under their eyes (Goldthorpe 2006).

True, descriptive analysis is often driven by contingent interests (Boudon 2002) and for

this reason it is usually based on short-term data. But in our opinion an attempt at

depicting an illustrative overview of the long-term trends of an important institutional

field such as higher education of contemporary Italy is worth doing.

The research has four main goals: the first aim is to update and give an overview of

changes in the participation of Italians in the higher education system during the 20th

century. The second aim is to analyse how some indicators of the ‘quality’ of university

students’ careers (called in the paper ‘performance’ or ‘efficacy’ indicators) have

changed over time. The third goal is to identify trends in absolute inequalities in

university participation between upper and lower classes. Finally, the fourth objective is

to evaluate whether social origin affects the ways in which students conduct their

studies and, eventually, whether the differences between classes are changed over time.

Specifically, we are in a position to analyse drop-outs and delayed graduations in a

long-term perspective and follow these trends according to the social class of the

students: this is probably the distinctive feature of our work.

Although the main purpose of the paper is descriptive, this does not mean that we don’t

have any theory of reference or hypotheses. In particular, we can formulate several

hypotheses on the trends of interest by looking at different sources: the influence that

society exerts on the educational system, Stinchcombe’s typology of sociological

explanation, and previous research results on the Italian educational system. We think

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that these contributions – although very heterogeneous – can help us to formulate some

hypotheses on the trends of interest, positioning them into a more comprehensive and

explicative frame. Thus, let us briefly spend some words to illustrate them.

The first reference has to do with the relation that links the educational system, or part

of it as the university, to the society in which it is nested. The authors who have stressed

this sort of relation are for example Durkheim (1938), Levin (1976), Brint (1999),

Cobalti (2006). According to these interpretative models, educational operations reflect

the prevailing institutional culture and social consciousness; therefore one cannot

change such a deep rooted sub-system as the university by decree only, without the

support of the prevailing culture, let alone against it. So the continuation of inefficient

practices that Italian universities have witnessed may be understood if we reckon that

during the last century in Italian society sensitivity regarding meritocracy and fair

competition has been poor (Altan 1995; Galli della Loggia 1998). In a sense, the legal

validity of the degree4 is a revealing sign; in this country patronage and friends are still

very important in many domains: if you want to succeed – so goes the popular tale –

personal excellence can help, but the point is to get a degree, then somebody will help.

As long as what really still counts in Italian society is to be dottore, characterizing Italy

as a paradigmatic example of credential society, we can expect that universities do not

change gear and carry on in delivering few graduates, with sloppy skills, with

embarrassing delays. This is true in particular for the public sector of employment,

companies know that universities are not on equal foot, but the culture has a long

tradition.

A second theoretical hint that can help in explaining some steady patterns of the Italian

university system can be traced in an early work of A. Stinchcombe (1968). When

confronted with complex causal structures it is possible to distinguish between

demographic, functional and historicist explanations. University education seems a case

in which all three can be applied. In fact the dynamics of enrolments depend on the

number of age cohorts multiplied by the enrolment rate (demographic explanation).

Moreover, the structure of the higher education system is partly caused by its

consequences, namely the production of certain numbers of lawyers, geologists,

4 It means that the degree holder is supposed to have a lifelong command of the knowledge s/he has acquired at university; and that s/he has to be employed at a proper level, with proper salary consistent with her/his degree.

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psychologists (functional explanation). But it is the historicist explanation which is of

special interest for us: if we register those inefficacy patterns also a long time ago, then

we could say that present-day inefficacy patterns are the descendants of old ones which,

once established, have been able to reproduce themselves (historicist explanation5). Of

course there are social mechanisms at work (power dynamics, for instance) in the

reproduction process and this adds interest for Stinchcombe’s theory in the field of

Italian higher education.

Finally, previous empirical results are compatible with the predictions deducible from

the above described interpretative models. The works by Barbagli (1972), de Francesco

and Trivellato (1985), Checchi (1997), Schizzerotto et al. (2002), Pisati (2002) show in

fact that several features and results of the Italian education system are anything but a

recent product; far from common sense they can be retrievable also at the beginning of

the 20th century.

Here comes our general hypothesis. Expressing it in an intuitive way, we expect more

continuity than discontinuity in university functioning during the 20th century and in

particular we expect to observe long-term trends of inefficacy and low productivity of

the tertiary education system. In principle the worsening of system performance does

not come as a surprise: when numbers are skyrocketing the organization has difficulties

to cope. But we think that bad results continue also after the enrolment peaks and after

new resources have been added. In particular, we know that along the ‘900 a huge

increase in enrolment rates and a substantial increase in the percentage of people

obtaining a degree have occurred. At the same time, some changes in the structures and

resources of universities have occurred: for example, the number of professors and

faculties increased and the average expenditure per student has risen as well (see section

2 and figures 1 and 2). So the question arises: which might be the causes of the

supposed enduring patterns of malfunctioning?

We suspect that there has been and there still is a substantial inertia in the most diffused

social representations of Italian tertiary education functions, both inside and outside

university institutions. Expectations, values, beliefs expressed by professors, students

5 For example, Stinchcombe (1968:59-60) stated that «… many social phenomena regenerate themselves from year to year. [...] Such infinite self-replicating causal loops tend to preserve on into the future the historical causes which got them started. […] They are the kinds of causal structures which make ‘tradition’ a powerful source of explanations of social phenomena». Needless to say, a functional element is in order to ensure reproduction.

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and their families and – eventually – the labour market have stayed invariant. Teaching

practices of the formers may have gone hand in hand with habits that students adopt in

their academic life. If daily functioning of the university system is affected by the

expectations, values and practices of its actors, well, not only continuity of pattern

behaviour can be expected but a slight worsening in the performance of Italian higher

education institution along the 20th century would be expected as well. In other terms,

while great changes in the students’ population, in the demands of education, and in the

whole society took place, universities have progressively adapted their resources to the

new conditions, but in the meantime no structural mending action or real re-routing in

the way to conceive higher education has been taken.

Second, we expect that social origin affects not only the probability of entering

university or taking the degree, but also the ways in which the students conduct their

studies and, in particular, the timing they use to reach the laurea. We expect that

members of upper classes exhibit a less proportion of drop-outs and delayed graduations

than students from lower classes. Third, we expect that there has not been a decrease of

absolute inequalities in participation and university performances between classes. At

the beginning of the last century in fact the grade of selection at inferior lever of

education was more severe and only the talented and motivated members of the working

classes could attend higher education, and so their performances would not have been

significantly different from those of upper classes. During the 20th century an increase

of students from lower classes has occurred and this has probably increased their

heterogeneity and, consequently, the proportion of less motivated and talented students.

It’s possible that an analogous process has occurred also among upper classes’ students,

but their resources could have cushioned the effect of the diminishing motivation and

talent. Moreover, students of the lower classes have more probability to engage in a

part-time job during their tertiary studies than upper classes’ students and this

differential behaviour can affect the timing they devote to study and to attend the

lessons; therefore, this can influence in a not negligible way the risk of dropping-out

and postponing the graduation.

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4. Data, variables and method

Data

The data analysed in this paper is sourced from the five waves of Indagine

Longitudinale sulle Famiglie Italiane ILFI (Italian Household Longitudinal Survey), a

prospective panel conducted in 1997, 1999, 2001, 2003 and 2005 by a research team

coordinated by Prof. A. Schizzerotto. The 1997 wave asked retrospective information to

respondents, whereas the other waves contributed to update information on the same

respondents and collect retrospective data on first-time interviewed entered in the

sample after the first wave. ILFI was carried out on a representative sample of Italian

men and women aged 18 or older and residing in Italy at the moment of the interview.

The sample design was a stratified two-stage one. The 8,104 Italian municipalities were

taken as the PSUs and divided into 42 strata defined by two variables: region and

municipalities type (metropolitan, suburbs, other). The 12 metropolitan municipalities

were included in the sample with certainty as self-representing PSUs. Within each of

the remaining 30 strata, a random sample of municipalities was extracted with

probabilities proportional to the number of residents; on the whole 248 municipalities

were selected. After this, within each selected municipality a simple random sample of

households was extracted, using the registry list as a sampling frame; on the whole

4,637 households were selected. Within each household, all individuals aged 18 or older

were defined eligible for interview6. The overall sample of the five surveys is

constituted by 11,221 cases; since we consider in the analysis persons born between

1920 and 1970, the overall sample is 7,684 cases: 1,002 are members of upper classes

and 6,682 are members of lower classes. Since ILFI is based on a complex sample design

the calculation of uncertainty around estimates may be distorted. However, some

previous tests (Bernardi and Pisati 2002; Pisati and Schizzerotto 2002) have shown that

the design effect tends to be fairly small (ranging in most cases from 0.8 to 1.2);

therefore we decided not to incorporate sample design in the analysis.

6 More detailed information on the sample design are available in Bernardi and Pisati (2002).

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Variables

There are six dependent variables in our analysis. Enrolments is the percentage of

people who enrolled at university and Graduates represents the percentage of people

who obtained laurea at university; both indicators are calculated on the whole

population. Transition rate is the percentage of students that engage in university after

obtained the Diploma (the degree obtained after having completed a 5-year programme

at high school). Drop-outs is the percentage of students who don’t complete their

studies and leave university without obtaining the laurea. Late graduates represents the

percentage of graduates who have obtained the degree after the formal end of the

attained program. We adopt a definition of ‘delay’ less constraining than the

administrative one. Defined fd the formal duration of the programme (in years) and ad

the years employed to obtain the degree, we consider the student x of faculty y as a

«late graduate» if adx>fdy+1. Index of delayed graduation is the ratio between the actual

duration of the studies and the formal duration of the attained programme (expressed in

a log-natural scale7), calculated on graduated students. In other words, late graduates

indicator is a measure of diffusion of the postponed graduation experience, whereas the

index of delayed graduation is a measure of the duration of the delay.

The independent variable is year of birth of respondents. We consider people who were

born between 1920 and 1970; by establishing the rough average age of enrolment at

university at 20 years old, our analysis covers people who attained tertiary education

between about 1940 and 1995.

Social origin corresponds to the father’s occupational class when the respondent was 14

years old. If the father was not present in the family at that time, social origin is

obtained by the mother’s or other major breadwinner’s occupational class. Social origin

is used to compare trends among different social categories; we use a simplified

dichotomic variable, dividing population in «upper classes» and «lower classes». The

first category includes bourgeoisie and white collar class, whereas the second category

embraces (agrarian and urban) working class and (agrarian and urban) petit bourgeoisie.

The dichotomization of social class is a problematic operation requiring further

explanations. The rationale of this choice is double. The first reason is pragmatic: we 7 The distribution of actual duration/programme duration ratio was very skewed, with a long tail on the right. The transformation in a log-natural scale modifies such distribution in a curve very similar to a Gaussian curve. Therefore we can use a linear regression model to predict the transformed index’s values.

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need to estimate models on a sufficient amount of cases and a more articulated

definition of social class would not allows us to obtain reliable estimates, given the

small amount of Italians who have attained tertiary education during the 20th century.

The second motivation is that previous analyses on the same dataset (Triventi e

Trivellato 2007) have shown that the main differences in the participation in the

university system are between «intellectual workers», usually well educated

(bourgeoisie and white collar class), and manual workers, often less educated (petit

bourgeoisie and working class).

Statistical methods

The main objective of the paper is to analyse changes in university functioning along

the 20th century. To address this purpose we model the variation of some «university

performance indicators» according to the year of birth of respondents. As our aim is to

find appropriate functional forms that can approximate the relation between such

indicators and time, we have applied the fractional polynomials method8 (Royston and

Altman 1994). Fractional polynomials (FP) are a useful parametric method that models

the relation between a continuous predictor and a dependent variable without requiring a

specification of a pre-defined functional form. FP are able to model curvilinear relations

using a small number of parameters and providing a relative simple equation that

describes the fitted curve. It has been showed that FP usually give a better fit than

polynomials of the same degree and even of those of higher degree (Royston and

Altman 1997).

Put it briefly, the procedure works as follows: some terms of the form Xp are fitted

(equally to the selected polynomial’s degree), where the powers p are chosen from a

small predefined set P of integer or not integer values. By this way, the different

possible combinations of polynomial’s degrees and values of power provide a rich class

of possible functional forms, leading to a satisfactory fit to the data in many situations 8 In an exploratory phase of the analysis we have applied the lowess smoothing method to represent graphically trends of interest. Lowess smoothing is a nonparametric ‘local’ regression procedure which applies weighted least squares regression to fit a curve approximating the observed data, without requiring a previous specification of a global function. The calculated lowess smoothed curves (not reported in this paper) showed that trends under scrutiny are not linear; this means that a simple linear regression model cannot approximate adequately the relationships. Although lowess smoothing provides a good representation of the data, it does not produce a regression function that is easily represented with a mathematical equation. In order to overcome this limit we have applied fractional polynomials.

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(Sauerbrei 2006). Following the standard procedure, we decided to estimate FP of

second degree, choosing values of p from the set { }3,2,1,5.0,0,5.0,1,2 −−−=P .

We elaborate six major models: each of them includes the year of birth as continuous

predictor, whereas the dependent variables are: 1) the probability of enrolment at

university in the whole population, 2) the probability of graduation in the whole

population, 3) the probability of enrolment at university among high school leavers, 4)

the probability of dropping-out among university students, 5) the probability of having a

delayed graduation among graduates, 6) the values of index of delayed graduation

among graduates.

We estimate logistic regression (1-5 models) and linear regression models (the sixth

model) to predict values of interest and 95% confidence interval generated from the best

fitting fractional polynomial. We represent these values on a line graphic, wherein the

x-axis contains the years of birth and y-axis contains the predicted values of dependent

variables. After this, we estimate the same models in two major social groups: people

coming from upper classes and those coming from lower classes.

5. Results

Participation and performances in Italian Higher Education

To give a summary overview of the trends of interest we present the results of the

analysis in a graphic form. As we said in the previous section, the predicted values

reported in these graphics are estimated by applying logistic and linear regression

models in which the functional form of the relation between the independent variable

(year of birth) and the dependent variables has been determined by the fractional

polynomials method9.

Our first goal is to describe the variation in the participation of Italians in higher

education during the 20th century. As we expected, Figure 3 shows that before the

Second World War there was a very low rate of participation in tertiary education in

Italy: among people born in 1920 less than 5% has enrolled at university and about 3%

has obtained the laurea. This was mainly a consequence of the process of

alphabetization which started in Italy later than in most European countries. The first

9 Table 3 in the Appendix presents in a synthetic form the equations describing the functional form of the curves in the figures 3 to 12.

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curve presents an overall form fairly similar to a logistic curve, with a not pronounced

slope for the early years, a rapid increase in correspondence of the central values of the

predictor and, finally, a less pronounced slope. In substantial terms, this means that

people born between 1940 and 1960 have experienced a leap in the access to tertiary

education, while people born in the following period don’t show an analogous growth in

the enrolments. The second curve presents a shape similar to the previous one but a

different slope. Both curves show a growth but the graduates’ slope is less intense, and

therefore the absolute difference in graduation rates between people born in 1950 and

people born in 1970 is not very high (about five percentage points). As a consequence

of these trends, at the beginning of 90s about 30% of the population in ‘academic age’

enters university and about 15% graduates; as we can see these values are very low,

especially compared with other European countries’ results (see tab. 1), and this

represents a signal of a sort of empass of the Italian university system.

Figure 3 shows further interesting information: the difference between the proportion of

enrolments and graduates increased during the century, in fact the distance between the

two lines becomes larger and larger. Looking at Figure 5, it is possible to find a piece of

evidence which is consistent with the trend shown in Figure 3: even though the

uncertainty around the estimate is not small, it seems that the percentage of drop-outs

increased during the ‘900. It must be noted that our starting hypothesis seems to be

confirmed: in fact, the problem of the high diffusion of drop-outs is far from being a

recent problem or an issue emerging after the 1969 reform. Among people born before

1950, in fact, the percentage of students who didn’t conclude with success their

academic course is between 30% and 40%. However, the worsening trend of drop-outs

seems to have been stopped among students born after 1960.

Turning back to Figure 4, we can look at the transition rate, a measure of the probability

of enrolling in higher education after concluding successfully high school studies. In

line with our hypothesis, there is only a small increase in transition rate during the 20th

century. It must be noted that this trend changed in more recent days: in fact, at the end

of the 90s a rough measure of transition rate indicate a percentage near to 70% (Istat

2000).

Figure 6 and 7 show the change in the proportion of late graduations and in the length of

delays. Both graphs indicate that the efficacy of the university system has been

16

worsening during the 20th century. Nevertheless, the experience of having a postponed

graduation was very diffuse also before the easing of the access conditions to higher

education which took place in 1969: more than 40% of graduates born in the 30s

obtained their degree after the formal end of their program. This proportion continued to

increase during the following period, in particular among people born in the 50s. As a

consequence, graduates born at the end of the 60s, who entered university in the 90s, are

very likely to conclude their studies behind schedule. These days the diffusion of

delayed graduation has reached dramatic values: out of 10 graduates, about 8 obtained

laurea after the formal end of the course. This bad performance is amplified if we look

at Figure 7: not only the percentage of late graduates grew, but also the length of the

delay increased over time. The duration of the delay has been quite constant for students

born in the period 1920-1950, whereas it began to rise quickly for those born after 1950.

This means that the reform of 1969 seems to have had a negative impact on the length

of tertiary studies.

Participation and performances by SES

The next step of the analysis is to examine the same trends in different social categories.

As anticipated above, in order to obtain reliable estimates without excessive uncertainty

we decided to consider two major groups: upper classes and lower classes. The

questions we try to answer are as follows. How strong are inequalities in attendance

within the Italian university system? Has the level of inequalities diminished over time?

Is it possible to recognize an inequality pattern also in the probability of dropping-out or

having an irregular academic career? And how have the differences in academic

performances between classes changed in the last century?

Figure 8 shows three important pieces of information: first of all, there is a strong effect

of social class of origin on the probability of university attendance; as we expected,

upper classes have many more opportunities of enrolling in tertiary studies than

members of working classes and petit bourgeoisie. Second, there are persistent and

rising absolute inequalities in the percentage of enrolments between the two broad

social categories: among students born in the 20s the class difference was about 30

percentage points, while among students born in the 60s is about 45 percentage points.

Since we consider percentage of enrolments on the whole population, it must be kept in

17

mind that this result can be caused by processes or events situated at different levels of

the educational system; anyway, we are confronted with the fact that also nowadays

sheer inequalities in the opportunity of entering university are still with us. Moreover, in

spite of the great increase in the number of students, the reform which opened university

entry in late 60s and the changes in the labor market, these disparities seem not to have

diminished in the 20th century. Third, changes in enrolments can be described by

different functional forms: in particular, the line for students born in the 20s is quite

similar in the two social groups (even if on different absolute levels, of course), whereas

the slope became stronger in the upper classes from 1930 till 1960. This means that the

reform of 1969 seems more useful for the bourgeoisie and the white collars than for the

working classes and the petite bourgeoisie. Furthermore, results are consistent with

previous considerations (Moscati 1983a, 1983b) which indicate that the increase in

university participation anticipated the reform instead of following it. In other words,

the law which formally opened the university system to all has merely sanctioned a

trend which was already settled, more than opening up brand-new opportunities for

enrolment. Figure 9 shows that there are persistent inequalities between upper classes

and lower classes as to the probability of getting a degree. Even if the estimate

regarding the upper classes is rounded by a consistent uncertainty, the pattern is

substantially clear: the difference in the diffusion of graduates between upper and lower

classes was high at the beginning of the century; after 1925 the percentage of

graduations started to grow in both groups, but at a quicker pace among the bourgeoisie

and the white collar classes than among the petite bourgeoisie and the working class.

The level of absolute inequality in the distribution of academic degrees reached its peak

with people born in the late 50s; in the following years the proportion of graduates in

lower classes continued to increase, whereas it diminished among upper classes.

However, looking at the extremes of the curve it cannot be safely said that during the

20th century there has been a decrease in the level of absolute inequality: in fact, the

difference in the proportion of graduates between the two social categories is pretty high

also for students born in the late 60s.

Not surprisingly, social origin affects the transition from high school to university. In

Figure 10 we can see that this effect has been reinforced during the last century: among

students born in the mid-20s the difference between upper and lower classes is 15

18

percentage points, but it increases to 25 percentage points among the cohorts born in the

second half of the 60s. The overall trend of the transition rate is fairly similar in the two

social categories: in fact, both lines present a small increase up to students born in 1940,

a relative growth between 1940 and 1960 and, finally, a small decrease in recent times.

The main difference is in the intensity of the slope that is more intense among

bourgeoisie and white collars.

Trends in student wastage are more puzzling to comment. As we might expect and

partially contrary to common sense, at the beginning of the century the percentage of

drop-outs was lower among the petite bourgeoisie and the working class than among the

bourgeoisie and the white collars (the absolute difference between estimates was about

15 points). As already stated, this fact may be the result of the sorting process which at

the time was very severe. Very few students from the lower classes were able to engage

in tertiary studies: it sounds sensible to assume that they were on average well

motivated and talented. Figure 11 displays also an interesting and partially unexpected

pattern of change in the form of the drop-out trend in the two social categories: the

second curve seems the mirror image of the first one. The upper classes line presents a

slightly downwards bend and a slight upgrade starting from students born in the mid-

50s; opposite, the lower classes line shows an evident upwards bend and a faint decline

from the students born in the late 50s. In sum, people born in the late 60s show a quite

similar drop-out rate, irrespective of social origin.

Figure 12 and 13 present respectively the percentage of delayed graduation and the

index of the duration of delayed graduation according to social origin. Among people

born in the 20s there was a strong difference in the proportion of late graduates; as

expected, upper classes show systematically lower level of delayed graduation than

members of the working class and the petite bourgeoisie. Even if the confidence interval

at the beginning of the century is not negligible, the absolute difference in the diffusion

of graduation behind schedule between the two groups is around 25 percentage points.

For example, one third of upper classes students born in 1927 obtained their degree

behind schedule, whereas this proportion is six out of ten among lower classes students.

Furthermore, the two social groups show a different pattern (Fig 12); namely, in both

groups we can see a steady increase in the proportion of postponed graduations during

the 20th century; but among the upper classes there was a constant growth, whereas

19

among the lower classes there was stability until 1950, then in the 50s the percentage of

late graduates started to rise and continued in the following period. The reform of 1969

seems not to have affected student wastage proliferation among the bourgeoisie and the

middle class, but it could have had a negative impact among working classes. Finally, as

we can see in Figure 13, not only the percentage of behind schedule graduates became

larger during the last century, but at the same time the average length of the delay has

also increased in both groups. The shape of the line is similar to previous figures’ ones:

a fairly constant growth for the upper classes and a stability until middle 50s followed

by a sudden increase for the lower classes. An overall view of the graph suggests that

there were no major changes in the level of inequality, as far as the graduation on time

pattern is concerned, between upper and lower classes during the ‘900; in particular the

latter exhibit a remarkable higher risk of concluding academic studies with one or more

years of delay.

6. Discussion

Data shown so far confirm our hypotheses. Italian universities have been moving along

the whole 20th century on tracks of continuity and tradition rather than those of change

and innovation. The overall results in terms of inefficacy, irregularity of students’

careers and level of class inequality tell us that the university system has reproduced

habits, procedures, rituals and results decade after decade10. These trends are not

amenable to recent reforms or laws or bills. We have seen they have a long history and

probably fit nicely with the society’s needs and values, or at least of the majority of

such a society.

Important changes have actually occurred, namely the number of students has grown,

the number of universities, faculties and courses rose as well, together with the decrease

of the number of students per teacher. But an overall worsening of the relative efficacy

of the university system took place. The main cause can be traced in the fact that the

quantitative expansion of tertiary education, the diversification of the courses and the

growth of students’ heterogeneity have not been followed by a process of adequacy and

change of habits and social representation of university functioning. As a result the

Italian university system appears under many respects stagnant in the 20th century. 10 This conclusion, based on macro data is consistent with good practices and good results at micro level in some institutions or in part of them.

20

Continuity has overweighted change: the already low standards of ‘productivity’ of the

first part of the century have gone lower during the second part, confirming our

hypothesis.

Data show that enrolments in tertiary education increased, but we have to acknowledge

that the Italian university system has reached the third stage of Trow’s typology, «mass

entry», very late, between the end of the 80s and the beginning of the 90s. Such a late

growth has not been sufficiently rapid to bridge the gap with other Europeans countries.

Furthermore, during the past century only a small increase in the transition rate from

high school leavers to university took place. A large increase of the graduates output

would have been necessary, but only a small growth has occurred and there are signals

of a slowdown at the end of the century. As a result Italy is nowadays still lagging

behind her European counterparts as to the diffusion of degree holders. One can easily

understand the consequences for the functioning of the whole society, from the culture

domain to the economic sphere.

The unsatisfactory final results, we have seen, have their roots in a decline in the

efficacy of the university system; in particular an increase of drop-outs, behind schedule

graduations and a lengthening of average timing to gain the laurea. Data show that slow

academic careers and delayed graduations were present in the university system also

before the reform of 1969. The bill which allowed every high school diploma holder to

enter into higher education did not create these dysfunctions, at most it has aggravated

them, unwillingly. Again, long-term trends confirm our hypothesis of generalized

resilience to change inside the universities allowing room for persistence of career

patterns among university students. Much like in economic development, where if there

is no growth decline follows, overall results did not stay the same, they got worse.

Finally, the inequality issue. Higher education in Italy has been characterized by

persistent and in some cases rising absolute inequality in tertiary education attendance

and graduation. In particular, there was a great increase as to inequalities between upper

and lower social classes in the opportunity of enrolling, a slight increase in disparities in

the distribution of degrees and stability in the relative probability of entering tertiary

studies after leaving high school. Data confirm in large part the hypothesis of

cumulative inequalities in higher education. We can talk of cumulative inequalities in

two ways: on the one hand, in a diachronic fashion, social class inequalities come from

21

distant days and are reproducing themselves year after year. With a sort of slogan, we

can state that heavy inheritance of the past inevitably conditions the present. On the

other hand, there are not only inequalities in enrolments and graduations as traditional

research has shown, but also disparities in the way students conduct their studies. In

particular, the resources of the family of origin affect the risk of dropping-out, having a

postponed graduation and the duration of the delay in gaining the degree when this goal

is reached. If we consider that people entering higher education do not bear any

resemblance, as far as social class of origin is concerned, with the whole population and

got successfully through school selection processes, the persistence of differences at

university level appears still more relevant and difficult to accept on equity ground. The

explanation here could lie in the fact that students from lower classes take on full-time

jobs or part-time jobs more frequently than students from upper lasses and consequently

the formers devote piecemeal time to study activity compared wih the latter ones.

To sum up, in most cases inequalities haven’t declined during the last century, and this

is not a good piece of news, in spite of the fact that it sounds a confirmation of our

hypothesis: striking inequalities are surviving in spite of the rhetoric about equality of

opportunities and the shortage of graduates. It seems safe to assume that all this would

not be possible without a strong, although not conscious, backing from different strata

of the Italian society. Those who are better off do not disdain the advantage; those who

are worse off strive as much as they can, hoping that the legal validity of the degree they

will eventually gain will pay, with the little help of their friends, at least in the long run.

Well, the persistence of different sorts of inequality was predictable. What was not

expected and worries a little bit is the fact that where we spot a sign of a reduction of

absolute distance between social classes (as with late graduates’ indicator) this outcome

is the consequence not of an upgrade of lower classes students, but of bad performance

among upper classes students. This is only a clue of a more general process which

might have worked as follows. During the second part of the century, universities have

adopted less strict yardsticks, got looser in their operations in order to cope with huge

numbers and heterogeneous audiences. It was the easiest and cheapest way to react,

keeping “business as usual” would have cost a lot. But this solution might prove wrong

because it has not helped students from lower classes to catch up, and has encouraged a

bulk of children from upper classes to relax, avail themselves of this unexpected bonus

22

and pick up such a bizarre habit of graduating with a two or three years delay. Again,

one can see that the structure has its own responsibility, but also the families acceptance

of these outcomes makes us think that between the working of the university and the

dominant values in society there is some sort of correspondence and mutual

understanding.

7. Concluding remarks

Before closing, we deal very briefly with the policy issue, trying to envisage which

educational or welfare policy – if any – could be implemented in order to reduce the

inefficacy trends we have witnessed and possibly help Italian universities make a

turnaround. There are two main fields where intervention could be possible and useful:

the area of micro-policies and the area of macro-policies. As to the first, we have reason

to believe that huge improvements could be attained as to teaching techniques in

delivering classes, careers’monitoring, and quality of teaching resources. Distance

programmes are now present in the catalogue of some Italian universities, although the

quality is uneven. But also traditional face-to-face mathods can be hugely improved.

Micro-policies, both of educational and welfare types, should focus on students who

enter higher education for the first time in their family history and are therefore ill

equipped in coping with the new environment. The intervention in the field of the

quality of dydactics is more urgent, as the age distribution of teachers shows that the

majority is well over 50, not an age bracket where teaching capacity is at its peak. And

because the amount of tuition and fees is not as high as to prevent a boy or a girl to

enter the university by means of a summer or week-end job.

More important would be to launch programmes of sponsored mobility, aimed at

securing proper entry and regular careers in the best universities to most promising

students coming from lower classes. The point is not which policy to enact and

implement. It is rather whether the Italian society and her polity really want to enact and

implement innovative policies in the domain of higher education. Looking at what

happened in th 20th century, we would say that we cannot be too optimistic. Many

traditions, academic customs, vested interests would be at stake. Frankly, at present we

do not see in Italy a representative enough coalition of social strata that would be able to

23

initiate change aimed at reversing the trends we have presented in this paper. Let alone

to implement it.

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Figures

29

Students

00.

51.

01.

52.

0M

illio

ns

1940 1950 1960 1970 1980 1990 2000

Professors

010

2030

40Th

ousa

nds

1940 1950 1960 1970 1980 1990 2000

Faculties

01

23

45

Hun

dred

s

1940 1950 1960 1970 1980 1990 2000Academic Year

Fig. 1 – Long term trends in Italian Universities: number of students, professors, and faculties per academic year. 1943-1995. Source: ISTAT (1986, 1998)

Students/Professors

010

2030

4050

6070

80U

nits

1940 1950 1960 1970 1980 1990 2000

Fuori corso

010

2030

40%

1940 1950 1960 1970 1980 1990 2000Academic Year

Fig. 2 – Two key indicators: average number of students per professor and percentage of fuori-corso on the total amount of students per academic year. Italy, 1943-1995. Note: Fuori-corso are students who are still enrolled beyond the programme duration. Source: authors’ calculation on ISTAT data (1986, 1998).

30

Enrolments

Graduates

0

10

20

30

40%

1920 1930 1940 1950 1960 1970Year of birth

Fig. 3 – Enrolment rate and graduation rate per year of birth (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

Transition rate

0

10

20

30

40

50

60

70

%

1920 1930 1940 1950 1960 1970Year of birth

Fig. 4 – Percentage of university enrolments on high-school leavers per year of birth (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

31

Drop-outs

0

10

20

30

40

50

60%

1920 1930 1940 1950 1960 1970Year of birth

Fig. 5 – Drop-out rate per year of birth (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

Late graduates

0

10

20

30

40

50

60

70

80

90

%

1920 1930 1940 1950 1960 1970Year of birth

Fig. 6 – Delayed graduation rate per year of birth (predicted values and 95% confidence interval). Italy, 1922-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

32

Index of delayed graduation

0

1Ln

(Act

ual d

urat

ion/

Pro

gram

me

dura

tion)

1920 1930 1940 1950 1960 1970Year of birth

Fig. 7 – Index of delayed graduation per year of birth (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

Upper classes

Lower classes0

10

20

30

40

50

60

70

80

% E

nrol

men

ts

1920 1930 1940 1950 1960 1970Year of birth

Fig. 8 – Enrolment rate per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

33

Upper classes

Lower classes0

10

20

30

40

50%

Gra

duat

es

1920 1930 1940 1950 1960 1970Year of birth

Fig. 9 – Graduation rate per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

Upper classes

0

10

20

30

40

50

60

70

80

Tran

sitio

n ra

te

1920 1930 1940 1950 1960 1970

Lower classes

0

10

20

30

40

50

60

70

80

Tran

sitio

n ra

te

1920 1930 1940 1950 1960 1970Year of birth

Fig. 10 – Transition rate per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1920-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

34

Upper classes

0

10

20

30

40

50

60%

Dro

p-ou

t

1920 1930 1940 1950 1960 1970

Lower classes

0

10

20

30

40

50

60

% D

rop-

out

1920 1930 1940 1950 1960 1970Year of birth

Fig. 11 – Drop-out rate per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1923-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

Upper classes

0102030405060708090

% L

ate

grad

uate

s

1920 1930 1940 1950 1960 1970

Lower classes

0102030405060708090

% L

ate

grad

uate

s

1920 1930 1940 1950 1960 1970Year of birth

Fig. 12 – Delayed graduation rate per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1923-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

35

Upper classes

0

1Ln

(Act

ual d

urat

ion/

Pro

gram

me

dura

tion)

1920 1930 1940 1950 1960 1970

Lower classes

0

1

Ln(A

ctua

l dur

atio

n/P

rogr

amm

e du

ratio

n)

1920 1930 1940 1950 1960 1970Year of birth

Fig. 13 – Index of delayed graduation per year of birth and social origins (predicted values and 95% confidence interval). Italy, 1923-1970. Source: authors’ calculation on ILFI data (1997, 1999, 2001, 2003, 2005).

36

Tables Tab. 1 – Highest level of education attained in the whole population and in the youngest cohort in some European countries (%). 2004

Upper secondary education Tertiary education 25-64 25-34 25-64 25-34

France 65 80 24 38 Germany 84 85 25 23 Great Britain 65 70 26 31 Italy 48 64 11 15 Spain 45 61 26 38 Sweden 83 91 35 42 Oecd average 67 77 25 31 Eu19 average 67 78 23 28 Source: Oecd, 2006. Tab. 2 – A summary of the trends of efficacy/inefficacy and inequality in Italian Higher Education system during the 20th century Efficacy Inequality Indicators of participation Enrolments ↑↑ ↑↑ Graduates ↑ ↑ Transition rate ↑ ↔ Inefficacy Inequality Indicators of performance Drop-outs ↑ ↔ Late graduates ↑↑ ↓ Duration of delay ↑↑↑ ↑↑ Note: ↑ = small increase, ↑↑ = consistent increase, ↑↑↑ = great increase; ↓= decrease, ↔ = stability. Appendix Tab.3 – Equations for the estimated curves reported in the graphs. Powers of Xs are calculated with fractional polynomials method.

Note: X is year of birth.

Dependent variable Total Population Upper classes Lower classes

Y=Pr(Enrolment=Yes) Y = β0 + β1X2 + β2X2 Y = β0 + β1X3 + β2X3 Y = β0 + β1X2 + β2X2

Y=Pr(Graduation=Yes) Y = β0 + β1X2 + β2X2 Y = β0 + β1X2 + β2X3 Y = β0 + β1X-2 + β2X1

Y= Pr(Transition=Yes) Y = β0 + β1X2 + β2X3 Y = β0 + β1X2 + β2X3 Y = β0 + β1X3 + β2X3

Y= (Drop-out=Yes) Y = β0 + β1X2 + β2X3 Y = β0 + β1X2 + β2X2 Y = β0 + β1X2 + β2X2 Y= Pr(Late graduation=Yes) Y = β0 + β1X-2 + β2X3 Y = β0 + β1X-2 + β2X2 Y = β0 + β1X3 + β2X3

Y= Ln(Actual duration/ Formal duration) Y = β0 + β1X 3 + β2X3 Y = β0 + β1X-1 + β2X2 Y = β0 + β1X3 + β2X3