Innocenti Report Card 15

An Unfair Start
Inequality in Children’s Education in Rich Countries

Innocenti Report Card 15 was written by Yekaterina Chzhen,
Gwyther Rees, Anna Gromada, Jose Cuesta and Zlata Bruckauf
and edited by Madelaine Drohan.
The UNICEF Office of Research – Innocenti would like to acknowledge thegenerous support for Report Card 15 provided by the Government of Italy.
Any part of this Innocenti Report Card may be freely reproduced using
the following reference:
UNICEF Office of Research (2018). ‘An Unfair Start: Inequality in Children’s
Education in Rich Countries’, Innocenti Report Card 15, UNICEF Office of
Research – Innocenti, Florence.
The Innocenti Report Card series is designed to monitor and compare
the performance of economically advanced countries in securing therights of their children.
In 1988 the United Nations Children’s Fund (UNICEF) established a research
centre to support its advocacy for children worldwide and to identify andresearch current and future areas of UNICEF’s work. The prime objectivesof the Office of Research – Innocenti are to improve international
understanding of issues relating to children’s rights, to help facilitate full
implementation of the Convention on the Rights of the Child, supporting
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in both the North and the South, the Office seeks to leverage additional
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The views expressed are those of the authors.
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Innocenti Report Card 15

An Unfair Start
Inequality in Children’s Education in Rich Countries

E X E C U T I V E

S U M M A R Y“By 2030, ensure that all girls and boys
complete free, equitable and quality
primary and secondary education leading torelevant and effective learning outcomes”– Global Goals for Sustainable Development, 2015, Goal 4.1

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EXECUTIVE SUMMARY

In the world’s richest countries,
some children do worse atschool than others because of
circumstances beyond their control,
such as where they were born,
the language they speak or theirparents’ occupations. These children
enter the education system at a
disadvantage and can drop further
behind if educational policies andpractices reinforce, rather than
reduce, the gap between themand their peers. These types ofinequality are unjust. Not all children
have an equal opportunity to reach
their full potential, to pursue theirinterests and to develop their talents
and skills. This has social andeconomic costs.
This report focuses on educational
inequalities in 41 of the world’s
richest countries, all of which are
members of the Organisation for
Economic Co-operation andDevelopment (OECD) and/or theEuropean Union (EU). Using the mostrecent data available, it examines
inequalities across childhood – fromaccess to preschool to expectationsof post-secondary education – andexplores in depth the relationships
between educational inequality andfactors such as parents’ occupations,migration background, the child’s
gender and school characteristics.
The key feature of the report isthe league table, which summarizes
the extent of educational inequalities
at preschool, primary school andsecondary school levels. The
indicator of inequality at thepreschool level is the percentage

of students enrolled in organizedlearning one year before the official
age of primary school entry.
The indicator for both primaryschool (Grade 4, around age 10)
and secondary school (age 15)
is the gap in reading scores
between the lowest- and highestperforming students.

Key findings
At least 9 in 10 children attend
preschool the year before they start
primary school in nearly all the 41
countries. Yet in 16 countries, morethan 5 per cent of children do notattend preschool the year before
they start school. This amounts tomore than 1 million children in total
across these countries.
By Grade 4, around age 10, there
are large gaps in children’s reading
abilities. In almost all countries,
more than 10 per cent of children
do not reach an intermediate levelof reading proficiency expected at
this age.
There are also large inequalities inchildren’s reading scores at age 15.
Latvia, Ireland and Spain are thefirst, second and third most equalcountries respectively. Malta (38th),
Bulgaria (37th) and Israel (36th) are
the three most unequal.
Countries can have different degrees
of educational inequality at different
educational stages. Ireland andSlovenia are in the bottom thirdof countries (high inequality) forpreschool enrolment, but move tothe top third (low inequality) towards
the end of secondary school.

France has one of the highest rates
of preschool enrolment, but thenfalls to the bottom third in secondary
school. The Netherlands goes frombeing the most equal country inprimary school reading scores toranking 26th (of 38 countries) whenchildren are 15 years old.
Tackling educational inequality does
not mean sacrificing high standards.
Countries with higher averageachievement tend to have lower
levels of inequality in children’s
reading scores. Bringing the worstperforming students up does notmean pulling the best-performing
students down.
High national wealth is no guaranteeof high equality. Some of the poorest
countries included in this report,such as Latvia and Lithuania,
have higher preschool enrolment
rates and lower inequality in reading
performance in primary andsecondary school than those with
far greater resources.

What drives educational
inequality among children?
Parental occupation
Large inequalities in children’s
educational progress are linked
to family background. These
inequalities already exist whenchildren enter preschool. In 16 of
the 29 European countries for whichdata are available, children from thepoorest fifth of households have alower preschool attendance rate
than children from the richest fifth.
These patterns persist throughouta child’s educational journey.

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performance between schools
than between children in the sameschool. On the other hand, there
is relatively little variation in
performance between schools in
Finland, Iceland and Norway. An
important factor explaining these
performance variations is the averagefamily background of children in eachschool. Differences caused by family
background are strongest in
countries such as Hungary andLuxembourg, where children fromricher and poorer families tend to
go to different schools.

Differences in parental occupation
explain up to one third of thevariation in children’s reading scoresat the ages of 10 (Grade 4) and 15.
Everything else being equal, children
aged 15 with parents in high-status
jobs are much more likely to expect
to continue into higher education
than those with parents in lowstatus jobs.
Migration backgroundIn 21 of the 25 countries with
substantial levels of immigration,
children who are first-generation
immigrants tend to do less well at
school at age 15 than non-migrantchildren. In 15 countries, secondgeneration immigrant children also
do less well than non-migrantchildren. However, in Australia
and Canada, second-generation
immigrant children do better thannon-migrant children. These
differences reflect varying patternsof migration to different countries.

What can be done to reduce
educational inequalities?

GenderThere are already substantial genderdifferences in children’s reading
abilities by Grade 4. Girls do better
than boys. Yet, in some countries,
the gap can shrink when tests aredone on a computer rather than on
paper. These gaps in reading
performance tend to grow as children
get older. At age 15, they range fromgirls doing 2 per cent better thanboys in Ireland, to girls doing 12 percent better than boys in Bulgaria.
Girls are also much more likely thanboys to expect to continue ineducation beyond secondary school.
Differences between schools
In most countries, there are large
differences in average readingscores between schools. In Bulgaria,
Hungary and the Netherlands,
when children are 15 years old,
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Countries can have very similar
average educational performancebut quite different levels of
educational inequality. This suggeststhat the inequalities can be reduced.
This said, each country’s education
system has developed within adistinct national context. A policy
or practice that works in one country
may not work in another. However,some general principles are relevant
to any country that wishes toreduce inequalities:

 Guarantee high-quality, earlychildhood education and care
for all children – ensuring that all
children have access to highquality preschool learning
opportunities plays an importantrole in reducing socio-economic
inequalities that exist whenchildren start school.

 Ensure that all children achievea good minimum level of coreskills – A key test of any education
system is that it provides all
children with the basic skills
needed to participate fully insociety. This should be a baseline
requirement for an equitableeducation system.

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 Reduce the impact ofsocio-economic inequalities –Through a combination of family
allowances and public services,rich countries can ensure that all
children are able to enjoy learning,develop varied interests andachieve their full potential.
Reducing the segregation ofchildren with different family
backgrounds into different schools
can also help to ensure that all
children have equal opportunities.

 Close the gender gaps inachievement – Policy makers
and educators need to ensure
the equal engagement of boys
and girls in all core subjects,
paying attention to the gendermix of teachers and challenging
gender stereotypes every stepof the way.

Produce better data –Not enough is known about
how inequalities develop andpersist in different contexts.
More high-quality, cross-country,
comparable evidence is needed
to fill these gaps. Longitudinalstudies that follow the samechildren as they grow would beparticularly valuable.

 Focus on equality, not justaverages – Policy and publicdebates should also be more fully
informed by the international
surveys that are already available,
such as the ones used in thisreport. International comparisonsshould consider not just how
countries are faring in average
educational performance, but also
the degree of inequality among
the students in each country.
Greater equality does not come at
the cost of average achievement;
both are necessary to give all
children a fair start.

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SECTION 1
INTRODUCTION“States Parties recognize the right of thechild to education ... with a view to achieving
this right progressively and on the basisof equal opportunity”– United Nations Convention on the Rights of the Child, 1989, Article 28

In the world’s richest countries,
some children do worse atschool than others because of
circumstances beyond their control,
such as where they were born,
the language they speak or theirparents’ occupations. These children
enter the education system at a
disadvantage and can drop further
behind if educational policies andpractices reinforce rather than
reduce the gap between themand their peers. These types ofinequality are unjust. Not all children
have an equal opportunity to reach

their full potential, to pursue theirinterests and to develop their talents
and skills. This has social andeconomic costs.
This Report Card focuses on 41 highand middle-income countries thatare members of the Organisation
for Economic Co-operation andDevelopment (OECD) and/or theEuropean Union (EU).
Our primary concern is inequality
in achievement among children as
they near the end of compulsory
schooling. This is the key measurein the league table. Inequalities
that exist at this stage influenceand limit children’s prospects asadults. They indicate how well an
education system has done inproviding equal opportunities for all.
There are various ways to measure
educational inequalities. In thisreport, we use the best and most
up-to-date data to look at
differences between individual
children and between schools.
We start with disparities in accessto early education. For school-aged
children we look at variations in

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their scores in standardized reading
tests in primary and secondary
school and their expectations ofcontinuing into higher education.
This provides a life-course
perspective on our discussionof educational inequalities.
Our research addresses three setsof questions:
1. How much educational inequality
is there in rich countries? Does itvary between countries?
2. To what extent do children’s
starting points, circumstancesand characteristics explain
educational inequalities?
How does this vary between
countries and across thedifferent stages of education?
3. To what extent do education
systems and schools magnify
or reduce inequalities between
children? What policies andpractices can help to reduce
inequalities?

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We begin tackling these questions
in section 2, which presents aleague table of inequalities acrossdifferent stages of education frompreschool to the age of 15. In somesystems, compulsory educationends at this age. We focus on the
period of compulsory education
because we want to understandeducational inequalities when mostchildren are still at school. We also
have the most complete data forthis stage in children’s lives.
In sections 3, 4 and 5, we painta more detailed picture of thepossible sources of educational
inequalities and how these develop
as children progress throughschool. Section 6 takes a brief lookat education systems and policies.
In section 7, we discuss theimplications of our analysis andprovide our recommendations.
We find substantial variation inaccess to early education for the
youngest children; in children’s

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educational progress; and in their
expectations of continuing in
education beyond the end ofcompulsory schooling. Inequalities
linked to family economic
circumstances start early andpersist. A child’s gender or placeof birth can also be a source of
inequality. We identify the sizeof inequalities between schools
within each country and highlightthe potential role that educational
policies and practices can playin either reducing or reinforcing
inequalities. The international
comparisons show that themagnitude of all these types ofinequality varies substantiallybetween countries. This offers
the potential to learn from different
educational policies and practices.

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Box 1 What are the sources of educational inequality?

Systems and schools can play an equalizing role,

If we are going to reduce educational inequality,
we need a good understanding of its sources.
This report explores these issues using a life-course
perspective (see Figure 1).

narrowing gaps created by children’s different
starting points and early childhood experiences.
They can also accentuate inequalities or create
new ones.

The bottom part of the diagram shows the child’sFamily circumstances, such as wealth and parental

route through the education system and indicatesthat inequalities at one stage in the education
system could feed into later inequalities. It also
notes that some sources of inequality may
originate before birth.

education, and parental actions, such as reading totheir child or funding extra tuition, influence achild’s educational development.

The influence of peers may become increasingly

The overall national context – economic, socialand cultural – has a part to play in influencing
educational inequalities throughout childhood.

important as children move through the education
system.

The policies and practices of the education systemand those of individual schools exert an additional
influence once children enter formal education.

Children’s own actions, such as the interests they
pursue, play some part in widening or narrowing
gaps between them and their peers.

Figure 1: A life-course perspective on educational inequalities

Overall national context (political, economic, social, cultural and institutional)

Educational system, policies and practices

Family circumstances and actions

Peers

Child’s actions

Inheritedabilities andtalents

Pre-birth

Very earlychildhood

Early
childhoodeducation

PrimaryschoolSecondaryschoolCharacteristics

Post-school
education,
employment
and training

Source: Authors’ own design

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SECTION 2
SUMMARY LEAGUE TABLE

Figure 2: League Table
Inequality across three stages of education
Rank

Country

Preschool (rank)

Primary School (rank)

Secondary School (rank)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38

LatviaIrelandSpain
Denmark
Estonia
PolandCroatiaJapan
CanadaSlovenia
Finland
Portugal
Italy
Romania
Lithuania
United Kingdom
Republic of Korea
Switzerland
Hungary
NorwayGreeceIcelandGermany
United States
SwedenNetherlands
Czech Republic
Belgium
Austria
Australia
CyprusSlovakia
New Zealand
Luxembourg
FranceIsraelBulgaria
Malta
Chile
MexicoTurkey

4=
33
22
17=
31
4=
24=
34
27
28
14
8
15
39
1
20
35
4=
32
17=
29
2=
23
40
16
10=
38
10=
10=
36
26
37
30
13
2=
4=
24=
17=
21
9
41

2
16
4
12

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38

15

18
17
3
8
6
13
23

19
7

20
22
11
1
10
9
5
25
21
28
14
27
26
29
24

Note: A light blue background indicates a place in the top third of the ranking, medium blue denotes the middle third, and dark blue the bottom third.
The blank cells indicate there are no data available.
Source: See Box 2.

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Box 2 Interpreting the data

Some rich countries do better
than others in ensuring equality
across the three stages ofchildren’s education: preschool,
primary and secondary. The league
table displays where a country
ranks in each of the three stages
and highlights whether it is in thetop, middle or bottom third. A
country’s overall place in the league
table is based on its position interms of inequalities at age 15.
The inequalities that exist at thisage influence and limit children’s
prospects as adults.
The indicators provide a snapshotof inequality at each of the threestages (see Box 2):

 The measure for preschool is

the percentage of students
enrolled in organized learning forat least one hour per week one
year before the official age ofprimary school entry. It denotes
equality of access to preschool
education and is a measure ofequality of opportunity.

The indicator for primary schoolis the gap in reading scores
between the lowest- and highestscoring students at Grade 4.
We focus on reading, rather
than mathematics or science,
because reading is a gateway
to other learning.

The indicator for secondary

school is the gap in readingscores between the lowestand highest-scoring students
at age 15.

Preschool – The indicator used is the percentage of students enrolled
in organized learning one year before the official age of primaryschool entry for at least one hour per week. The official age varies bycountry. An average rank is reported for the countries that have thesame preschool participation rate.
Source: Sustainable Development Goals Indicators Global Database (UNESCO, OECDand Eurostat Surveys of Formal Education) (see <https://unstats.un.org/sdgs/indicators/
database/>), except for Austria, the Czech Republic, Germany and Slovakia (Age 5
enrolment in formal childcare, EU Statistics on Income and Living Conditions 2016 user
database) and Canada (Indicator 4.2.2, 2015–16, Government of Canada Sustainable
Development Goal Data Hub, <www144.statcan.gc.ca/sdg-odd/goal-objectif04-eng.htm>).

Primary School – The indicator is the gap in reading scores between
those Grade 4 students (around 10 years of age) who have done
worse than 90 per cent of their peers (10th percentile) and those whohave done better than 90 per cent of their peers (90th percentile).
The rank for the UK is based on England and Northern Ireland only.
The reading scores were standardized in 2001 so that they had
an international mean of 500 and a standard deviation of 100.
Most children tend to score between 300 and 700 points.
Source: Progress in International Reading Literacy Study (PIRLS) 2016, the International
Association for the Evaluation of Educational Achievement. See <https://timssandpirls.bc.
edu/pirls2016/index.html>.

Secondary School – The indicator is the gap in reading scores
between the 15-year-old students (Grade 7 or higher) who havedone worse than 90 per cent of their peers (10th percentile) andthose who have done better than 90 per cent of their peers(90th percentile). The reading scores were standardized in 2000 sothat they had an international mean of 500 and a standard deviationof 100. Most children tend to score between 300 and 700 points.
Source: OECD Programme for International Student Assessment (PISA) 2015.
See <www.oecd.org/pisa/>.

Chile, Mexico and Turkey are omitted from the summary league
table because the proportion of 15-year-olds who are either excluded
from PISA 2015 or are not at school exceeds 20 per cent. This meansthat the figures for these countries are not a reliable measure of
educational inequality for that age group. Their positions on thepreschool indicator appear below the league table, for reference.
Source: PISA 2015.

For more detail on the data and methods, see Gromada, A. et al.,‘Measuring Inequality in Children’s Education in Rich Countries’,
Innocenti Working Paper 2018-18, UNICEF Office of Research –Innocenti, Florence, 2018.

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The results suggest that there
is no systematic relationshipbetween country income and anyof the indicators of equality in
education. It is notable that someof the poorest countries in thecomparison, such as Latvia and
Lithuania, achieve near-universal
access to preschool learningand curb inequality in reading
performance among both primaryand secondary school students
more successfully than countries
that have far greater resources.
Finland, Latvia and Portugal havethe most equal education systems
across all three indicators ofequality in education in the league
table. Australia, New Zealand andSlovakia are in the bottom thirdfor each of the three indicatorsof equality in education.

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Some countries have very different
degrees of inequality at different
stages in the school system.
Ireland and Slovenia are the only
two countries that move up fromthe bottom third in preschool
access to the middle third inequality at primary school and the
top third in equality at secondary
school. Estonia and Japan also
do much better at the secondary
school level than their rank forpreschool would predict.
It is also possible to have arelatively equitable system tobegin with, and then see wide
inequalities by the end of
secondary school. Austria, Belgium
and the Netherlands score in the
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school ranking. Between the
primary and secondary school
indicators, Austria’s standing drops
from 5th to 29th, Belgium’s from
9th to 28th, and the Netherlands
plummets from 1st to 26th.
It is tempting to think that thecountries that do worse in the
ranking can successfully copy
the education system of thosecountries that do well. There areundoubtedly lessons that can belearned from the countries at the
top of the league table. Yet thesemust be replicated with care.
As we noted at the start of thisreport, there are many sources ofinequality in education. Political,
economic, social, cultural andinstitutional contexts vary widely
among countries. What works in one
country may not work elsewhere.

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SECTION 3
PRESCHOOL EDUCATION

A child’s journey through education
often begins in a childcare centre,
where children learn to interact
with each other and theircaregivers. Public provision ofhigh-quality childcare is increasingly
being seen as a policy that helps
working parents and counteracts
the unequal starting conditions ofchildren by providing a stimulatingsocial and learning environment
for all types of family.1
We use the terms ‘preschool’ and‘childcare provision’ interchangeably
to refer to all forms of centrebased, early childhood educationand care. The divide between careprovision and preschool educationis blurred in many countries, but it
is still common to think of services
for children under the age of 3,
as childcare and those for children
aged 3 and over as preschool.
The benefits of preschool education
can be long-lasting. According to
the OECD, 15-year-olds who reporthaving had more than one yearof pre-primary education do
substantially better at reading thanthose with no pre-primaryeducation, even after accounting
for the child’s economic and social
position.2 Studies that follow thesame children over a period oftime point to an array of long-term
benefits. Children who attend
preschool are more likely tocomplete other levels of school andgraduate from university. Overall,they tend to have more years ofeducation.3 Those who benefit
most are children whose mothers
did not go far in school and thosefrom poorer families.4 Providing
universal access to early childhood
learning and care is a potential
means of reducing inequality.

Most children start primaryschool with some experienceof organized learning
One of the targets contained in
the Sustainable Development Goals(SDGs) is that all children shouldhave access to quality preschool
education. Figure 3 shows thatat least 9 in 10 children attend
preschool the year before they start
primary school in nearly all the

41 OECD and EU countries. In manyof these countries, the enrolment
rate is virtually 100 per cent, often
reflecting a statutory requirement
to enrol a child in preschool thatyear. Although this snapshot does
not account for the international
differences in the organization ofearly childhood education – such as
the quality of education or the hours
of attendance – it does indicatethat almost all children start primaryschool with at least someexperience of learning with
their peers.
In a handful of countries this is not
the case. Only two in three children(69 per cent) in Turkey attend
preschool the year before starting
compulsory education. In another15 countries, including Australia,
Canada, the Republic of Korea andthe United States, the enrolment
rate is between 85 per cent and95 per cent. This still leaves morethan a million children across thesecountries entering primary schoolwith no recent experience ofgroup-based learning.

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Figure 3: How many children attend preschool?
Percentage of children participating in preschool education in 2015 (for at least
one hour per week, one year before the official age of primary school entry)
Lithuania

99.9

Iceland

99.8

France99.8

Switzerland

99.7

Latvia99.7

Poland99.7

Israel99.7

Portugal

99.5

Mexico99.4

Austria

99.2

Belgium

99.2

Netherlands

99.2

Luxembourg

99.0

Finland

98.6

Italy

98.5

Sweden98.1

Norway

97.8

Malta

97.8

Denmark

97.8

United Kingdom

97.7

Chile

97.5

Spain

96.0

Germany

95.5

Bulgaria

95.4

Croatia

95.4

Cyprus94.6

Canada94.5

Slovenia

94.0

Greece93.8

New Zealand

93.3

Estonia

93.0

Hungary

91.5

Ireland

91.4

Japan

91.1

Republic of Korea

90.8

Australia

90.6

Slovakia

89.2

Czech Republic

88.6

Romania88.0

United States

86.8

Turkey68.6

Most children start school withsome experience of group-basedlearning. Yet an international
comparison indicates that
attendance rates vary dependingon the age of preschoolers.
Figure 4 shows the percentagesof preschool children under 3 yearsof age and those aged 3 and older,
who attend centre-based care forat least one hour a week in the
31 (European) countries for which
comparable statistics are available.
More than half of children aged 3
and over attend preschool in every
country. In two thirds of thecountries, at least four in fivechildren do so, with near-universal
enrolment in Belgium, Denmark,Iceland, Spain and Sweden.
In Cyprus, Lithuania and Slovakia,
fewer than four in five children inthis age range attend preschool.
In Bulgaria, Switzerland and theUnited Kingdom fewer than three
in four do. The rate falls to below
two in three in Croatia, Greece,
Poland and Romania.

0

20

40

60
per cent

Enrolled

1 2

Not enrolled

I N N O C E N T I

Childcare provision foryounger preschoolers is
far from universal

R E P O R T

C A R D

1 5

80

100

Note: Most recent data are from 2013 for Icelandand Japan, and from 2014 for Greece,
Luxembourg, Poland, Portugal, Mexico, Slovenia,
Switzerland and the United Kingdom.
Source: SDG Indicators Global Database,
Indicator 4.2.2 (UNESCO, OECD and Eurostat
Surveys of Formal Education), except Austria, theCzech Republic, Germany and Slovakia (Age 5
enrolment in centre-based services, EU-SILC
2015) and Canada (Indicator 4.2.2, 2015–16,
Government of Canada Sustainable Development
Goal Data Hub, <www144.statcan.gc.ca/sdg-odd/goal-objectif04-eng.htm>). Data last accessed 2
July 2018.

S E C T I O N

primary education did not start until
the age of 7 at the time the survey
was conducted. Average enrolment
rates also hide sub-nationalvariations (see Box 3).

The age at which a child starts
school varies across the EU
countries, and so the period
between 3 years of age and thecompulsory school age is longer
in some countries than in others.5
In Hungary, pre-primary education
starts as early as age 3 (and primaryat age 6). Yet only 87 per cent ofchildren aged 3 and over attend
preschool. More than 90 per centof children do so in Estonia andSweden, the only two EU countries
where compulsory pre-primary or

3

P R E S C H O O L

E D U C A T I O N

does so in Bulgaria, Croatia,
Hungary, Lithuania and Romania.
Enrolment rates are below 50 per
cent in nearly all the countries. The
exceptions are France, Luxembourg,
the Netherlands, Norway, Portugal
and Sweden, where around one
child in two under the age of 3
attends centre-based care, andDenmark, which stands out as thecountry with the highest childcare
enrolment rate for children under 3(70 per cent).

In every country, children under theage of 3 are less likely to attend
centre-based childcare than theircounterparts aged 3 and older.
Less than 1 in 10 children under
the age of 3 does so in the Czech
Republic, Greece, Poland andSlovakia, and less than one in five

Figure 4: Who is providing children with the best start?
Percentage of children below the minimum compulsory school age attending centre-based education or care forat least one hour per week in 2016100

per cent

80

60

40

20

Childcare enrolment rate (between 3 and compulsory school age)

Denmark

Netherlands

NorwaySwedenLuxembourg

FrancePortugal

Iceland

Belgium

Spain

Slovenia

Italy

FinlandGermany

Malta

Estonia

Ireland

Switzerland

United Kingdom

LatviaCyprusAustria

Romania

Croatia

Hungary

Bulgaria

Lithuania

GreecePolandCzech Republic

Slovakia

0Childcare enrolment rate (under 3)

Note: The most recent data are for 2014 for Switzerland and 2015 for Iceland. The minimum compulsory school age varies between 4 and 7 across these31 countries. Centre-based education and care services include education or care at preschool, compulsory school, centre-based services or day-care centres
Source: Eurostat (last update 1 March 2018).

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3P R E S C H O O L

E D U C A T I O N

Box 3 Childcare in Canada

Being able to access affordable childcare is an
issue for many Canadian families. Just over half
(54 per cent) of children between the ages of 2 and4 attend some type of regulated, early childhood
education or care programme in Canada.
This national figure obscures substantial variation
across Canada’s 13 provinces and territories. In
Quebec, which has the highest enrolment, nearly
three in four children (73 per cent) attend childcare,compared with just one child in three (34 per cent)in Newfoundland and Labrador.6of children in this age group. Figure 5 indicatesthat those governments that spend a greater
proportion of their budget on early childhood
education and care tend to have higher enrolment.
We have information on average childcare fees for
major Canadian cities,7 but not for each province
and territory. Fees are lowest in cities in Quebec.
Families in these cities on average incomes and withat least one child under 5 pay around 3 per centof their after-tax income for a full-time place inregulated childcare. Toronto, Ontario, is the mostexpensive of the 20 cities surveyed.8 The average
cost of a childcare space for children under 5 inCanada’s largest city amounts to 22 per cent of
average net household income for families withpreschool children.

The enrolment rate among children aged 2–4 years
is higher in the provinces and territories withgreater availability of spaces for children under 6.
Availability is measured as the percentage of
regulated childcare places to the population

Figure 5: Childcare enrolment rates, availability of spaces and spending on childcare acrossCanadian provinces and territories (2016)
80

5.0

70

4.5
4.0
3.5

50

3.0

40

2.5

30

2.0

per cent

per cent

60

1.5

20

1.0

Childcare enrolment rate (left-hand axis)

QuebecOntarioPrince Edward
IslandNorthwest
Territories

Nova Scotia

New Brunswick

British Columbia

Yukon

Manitoba

Alberta

Nunavut

0.0

Saskatchewan

0.5

0Newfoundlandand Labrador

10

Availability of spaces (left-hand axis)

Proportion of budget spent on early childhood education and care (right-hand axis)
Note: The childcare enrolment rate refers to the percentage of children between the ages of 2 and 4 who regularly attend an early childhood
education programme. The provinces and territories are ordered by increasing enrolment rate. No data on availability of spaces for Yukon.
Source: Akbari, E. and K. McCuaig, Early Childhood Education Report 2017, Atkinson Centre/University of Toronto, Toronto, 2018.

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2040

per cent

Iceland
Belgium
Hungary
Estonia
Spain
FranceDenmark

80

E D U C A T I O N

100Children aged 3 and older are lesslikely to attend preschool if they livein the lowest-income households.
Figure 6 plots the childcare
enrolment rates separately forchildren in the poorest fifth and in therichest fifth of households in the 29
countries for which data are available.
In 16 countries, children from thepoorest fifth of households havea lower preschool attendance rate
than children from the richest fifth.
Croatia has the largest gap in bothabsolute and relative terms. The
attendance rate of children frombetter-off households is three times
that of their poorer peers. While twoin three children (70 per cent) fromhouseholds in the richest fifth of theincome distribution attend preschool,
the rate for the poorest fifth is lessthan one child in four (22 per cent).

Germany
Slovenia
Italy
Netherlands
Lithuania
SwedenNorwayBulgaria has the second-largest gap
in absolute terms: 42 per cent ofchildren from the poorest fifthof households attend preschool,
compared with 89 per cent of theirpeers from the richest fifth. Thismeans that children from richer
families are more than twice as likely
to attend preschool. The enrolment
rate for children from the richest fifth

Luxembourg
Portugal
Austria
Ireland
GreeceRomania
Slovakia
Czech Republic
LatviaFinland
PolandUnited Kingdom
CyprusBulgaria
Croatia

Poorest fifth (see notes)

60

P R E S C H O O L

Children from lower-income
households are less likely toattend preschool

Figure 6: Poor children are more likely to miss out on preschool
Preschool attendance for children in the bottom and top fifth ofhousehold income distribution (2016)
03

Richest fifth (see notes)

Note: Countries are sorted by magnitude of
the absolute percentage point gap.
2015 data used for Iceland. No data for Malta
or Switzerland.
No area data for Germany, the Netherlands
or Slovenia.
Personal cross-sectional weights used.
Countries with statistically significant differences
between the top and bottom income quintiles(at p<0.05) are noted with darker shading. A
difference is considered statistically significant
when it is larger than might be expected to occur
by chance.
The child’s age and the area of residence bydegree of urbanization are controlled for. Income
quintiles are constructed using the distribution ofequivalent disposable household income (after
transfers and taxes) among all children between
the ages of 3 and the minimum compulsory
school age.
Source: EU-SILC 2016 (version 14 March 2018).

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of households in Bulgaria is on a parwith the average rate in Norway.
A further factor in preschool
attendance is the availability oraccessibility of services in rural
areas, compared with urban ones.
In two countries, Croatia and
Poland, there is a significant
urban–rural divide. While four infive children aged 3 and older
attend preschool in urban Croatia,
just one child in three does so inrural areas. In Poland, three in fourchildren in urban areas are enrolled
in preschool, compared to lessthan one in two in rural areas.
Countries with greater income
inequality in preschool attendance
tend to have lower average rates
of attendance (see Figure 7).
This suggests that the affordabilityof childcare services for preschool
children may be a crucial barrier
to access and a source of
educational inequality.

Figure 7: Where income inequality is high, preschool attendance isgenerally low
Preschool attendance and the income gap (2016)
100
IS

95
90

Childcare enrolment rate (age 3 or older)S E C T I O N

BE
SE
ES DK
FR NL
EE
IT PT
DE
SI
NO
LU

HU

85

IE
AT
FI
LV

CZ

80

LT

CY

SK

75

BG

GB

70
65
RO

60

GR

55
50

-10

PL

HR

0

10

20

30

40

50

Percentage difference in preschool attendance rates between
top 20% and bottom 20% income groups.
Pearson correlation = - 0.73, p<0.001
Note: Countries with statistically significant differences between the top and bottom income groupquintiles (at p<0.05) are noted in blue.
Source: See Figure 4 and Figure 6.

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4P R I M A R Y

S C H O O LSECTION 4
PRIMARY SCHOOL

There are already large differences inchildren’s skills when they start primaryschool.9 Schools have a role to play in
reducing these differences by bringing
all children up to a good competency
level in core subjects. Reading
achievement at the end of primaryschool is particularly important,because it also affects a child’s ability
to do well in other subjects.
We used data from the Progress inInternational Reading Literacy Study(PIRLS 2016) to assess the extent ofinequalities in reading comprehension.
This international study tests
nationally representative samples ofapproximately 4,000 Grade 4 students
from 150 to 200 schools per country
or territory. The average student doing
the test is 10 years old. At this age,children have typically learned toread and are now reading to learn.
The PIRLS reading scale has fourbenchmarks for reading
comprehension that can be used tocompare the performance of students
across diverse school systems: low(400), intermediate (475), high (550)
and advanced (625). Children are
expected to demonstrate certain
abilities at each benchmark. At thelowest level, a child can read a simple
text and locate information that is
explicitly stated within the text.
At the advanced level, a child canread a relatively complex text andinterpret a character’s motivations
and feelings, even though these
are not explicitly stated.
Figure 8 ranks 31 school systems in
29 countries, based on the gap inreading scores between students who

Figure 8: Where are the widest gaps in reading comprehension?
Performance gap in reading achievement at Grade 4 (2016)
0

50

100

150

200

Netherlands

153

Flanders (Belgium)

155

Latvia161

Finland

165

Spain

166

Austria

166

Italy

166

Norway166

Portugal

168

Czech Republic

169

Sweden170

Denmark

171

Lithuania

174

France175

Wallonia (Belgium)

176

Poland182

Ireland183

Slovenia

185

Canada190

Hungary

194

Germany

194

250

Slovakia

196

United States

199

England (UK)200

Northern Ireland (UK)

202

Chile

204

Australia

212

Bulgaria

213
228

IsraelNew Zealand

230

Malta

232

Note: Flanders (Belgium) or BE-VLG refers to the Flemish-speaking region in Belgium. Wallonia(Belgium) or BE-WAL refers to the French-speaking Wallonia-Brussels Federation in Belgium.
The reading achievement scale has a mean of 500, corresponding to mean reading achievementin 2001, and a standard deviation of 100. The performance gap is measured as the absolutedifference between the 90th and the 10th percentile of the reading score.
Source: PIRLS 2016.

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have done worse than most of theirpeers (10th percentile) and those
who have done better than most
(90th percentile).
The Netherlands has the smallest
performance gap, 153 points, in thecomparison. This is still a very large
difference in the context of thisinternational assessment, where
the lowest and most advanced
benchmarks are separated by only
225 points. A gap of 153 points
means that students with thelowest scores are two benchmarks
or proficiency levels below thosewith the highest scores in thesecountries. The divide is even wider
in Israel, Malta and New Zealand,
which have the largest gaps (228,
232 and 230 points, respectively)
in reading comprehension
scores – equivalent to threebenchmark levels.

Figure 9: Where performance inequality is higher, reading proficiency
is generally lower
Percentage of students achieving the Intermediate International
Benchmark at Grade 4 is higher where the performance gap inreading achievement is lower (2016)
100

90% achieving Intermediate Proficiency

S E C T I O N

LV
NL IT
AT

80

ES
BE-VLG

FI

SE PL
LT
DK
CZ

IE

GB-NIRHU GB-ENG
SI CA
US
BG
SK
DE
AU

PT
NO

70

IL

NZ

FR
BE-WAL
CL

60

50
MT

40
150

160

170

180

190

200

210

220

230

Performance gap in reading achievement
Pearson correlation = -0.48, p<0.01240
Note: See Figure 8.
Source: PIRLS 2016.

Box 4 What is the PIRLS Intermediate
International Benchmark?
When reading a mix of simpler and relatively complex
literary texts, students can:When reading a mix of simpler and relatively complex
informational texts, students can:Independently locate, recognize and reproduceLocate and reproduce two or three pieces ofMake straightforward inferences about

Make straightforward inferences to provide

explicitly stated actions, events and feelings;
the attributes, feelings and motivations ofmain characters;

Interpret obvious reasons and causes, recognize
evidence and give examples; andinformation from the text;
factual explanations; andBegin to interpret and integrate information
to order events.

Begin to recognize language choices.
Source: Mullis, I.V.S., M.O. Martin, P. Foy and M. Hooper, PIRLS 2016 International
Results in Reading, Boston College, TIMSS & PIRLS International Study Center, 2017.

1 8

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S E C T I O N

The performance gap does notindicate absolute levels of reading
comprehension. It shows the
distance between the best and theworst readers. When we look atboth the performance gap and theabsolute level of reading proficiency,
we find that children in countries
with greater inequality in readingscores are less likely to achieve agood level of reading proficiency,
as measured by the Intermediate
International Benchmark (see Box 4).
Israel, Malta and New Zealand havethe largest performance gaps andsome of the largest shares ofstudents not reaching even thismodest international benchmark.
Figure 9 illustrates that this is nota straightforward relationship.
Far fewer children achieve theintermediate benchmark in Chile,
France, Malta and Wallonia(Belgium) than would be expected,
given their performance gaps.
Nevertheless, the overall trend
suggests that countries with large
gaps between their best and worst
performers have lower levels of
reading proficiency.

Differences in parental
occupation explain up to
one third of the variation inchildren’s reading scores
The circumstances in whichchildren grow up influence
how well they do at school.
Figure 10 compares readingscores of children with at least one
parent working in a professional
occupation with those of childrenof non-professionals. This is done
for a subset of countries that havesufficiently high parental response
rates for inclusion in this analysis.
Professionals include corporate
managers, senior officials,
teachers, nurses, engineersand doctors.

4

P R I M A R Y

S C H O O L

Figure 10: Children of professionals score higher in reading tests
Children’s average reading scores at Grade 4, by parental occupation
460

480

500

520

540

560

580

600

620

Finland

LatviaSpain

Portugal

NorwayCzech Republic

Italy

IrelandDenmark

Austria

PolandSlovenia

Slovakia

Hungary

Bulgaria

Non-professionals

Professionals

Note: Countries are sorted by the magnitude of the absolute parental occupation gap in reading scores.
We exclude countries missing more than 15 per cent of the information on parental occupation.
Professionals include corporate managers, senior officials, doctors, lawyers and engineers, as well as
technicians or associate professionals (such as nurses or paralegals).
Non-professionals include small business owners, clerical workers, skilled workers, general labourers,
service or sales workers, craft or trade workers, plant or machine operators, and those who have neverworked for pay.
Source: PIRLS 2016.

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4P R I M A R Y

S C H O O L

In all countries analysed, children
who have at least one professional
parent have significantly higher
reading scores than the children of
non-professionals. The gap inscores between the children of
professionals and non-professionals
ranges from around 28 points in
Finland to 66 points in Bulgaria.

Other characteristics of children or
their parents affect a child’s reading
achievement. These include thechild’s gender, the language thechild speaks at home, the locationof the school, the child's country ofbirth, the parents' education, andwhether the child comes to school
hungry or tired. This set ofcircumstances (including parental
occupation), explains over 30 per
cent of the variation in children’s
reading scores in Bulgaria(36 per cent), Hungary (32 per cent)and Slovakia (41 per cent) (seeFigure 11); but only 13 per cent in
Portugal and 15 per cent in Ireland.

Figure 11: What affects reading scores?
Percentage of variation in children’s reading achievement at Grade 4 explained by personal and family circumstances
45
40
35

per cent

30
25
20
15
10
5

All circumstances

Parental occupation only

Note: Personal and family circumstances include the child’s gender, whether the child speaks the language of testing at home, the location of the school,
whether a child is born abroad, parental occupation and education, and whether the child comes to school hungry or tired.
See notes to Figure 10.
Source: PIRLS 2016.

2 0

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Slovakia

Bulgaria

Hungary

Austria

Slovenia

Spain

Italy

PolandCzech Republic

LatviaNorwayDenmark

Finland

Ireland

Portugal0S E C T I O N

4P R I M A R Y

S C H O O L

Box 5 Educational inequalities between richand poor in the United States of America

divided into five equally sized groups, based on
average household income over the survey period.

By the time children start school, there aresubstantial differences in their cognitive abilities
linked to their family backgrounds. Researchsuggests that these differences can persist as
children go through primary school. Figure 12
shows scores in reading tests in a large andnationally representative sample of children
entering kindergarten in the US in 2011.
These children are then followed until Grade 4.
Because children’s reading generally improvesas they get older, the scores have been put on
a common scale with an average of 50 points toaid comparisons over time. Children have been

There are already significant differences in readingscores between all five income groups whenchildren enter kindergarten. These differences
then persist up to Grade 4. There is no evidenceof the gaps closing, but nor do they widen. So it ispossible that schools might be counteracting thewidening that might otherwise occur due tothe cumulative advantages of children in higherincome households.

Figure 12: Mean scores in reading by income group, US
70
65

Mean reading score

60
55
50
45
40
35
30

Kindergarten
AutumnKindergarten
SpringGrade 1

Grade 2

Grade 3

Grade 4

Grade
Highest 20%

2nd highest 20%

Mid 20%

2nd lowest 20%

Lowest 20%

Note: The chart shows mean reading scores, standardized to have a mean of 50 and a standard deviation of 10 at each time point.
The tests were conducted in the Autumn and Spring terms of the kindergarten year and the Spring terms of Grades 1 to 4.
The scores are controlled for children’s age and are weighted to be representative of the US population of schoolchildren in this cohort.
Source: Early Childhood Longitudinal Study: K-2011, US.

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4P R I M A R Y

S C H O O L

Differences between schools
explain one fifth of the variationin children’s reading scores
Inequalities between children arise
not only from differences in theirfamily background, but also fromdifferences between the schools
they attend. A child could flourish
in one school but languish inanother. Schools differ, even within
the same education system. These
differences can be caused by theway a school selects students.
For example, some select on thebasis of academic ability or
religious affiliation, some charge
fees. The location of a school
and the characteristics of thesurrounding community can also
create differences.
We looked at the total amount ofvariation in children’s readingscores in each country and broke
it down into two parts: the partdue to differences between schools
and the part due to differences
between children attending thesame school.
Figure 13 shows the share of thetotal variation in children’s readingscores due to differences between
schools. These differences accountfor 19 per cent of the total variationin children’s reading achievement
on average, across 31 school
systems. This ranges from just
4 per cent in Slovenia to 39 per centin Bulgaria. In another sevencountries, schools account for atleast 25 per cent of the variationin reading achievement: Chile,
Germany, Hungary, Israel, Lithuania,
New Zealand and Slovakia.

Figure 13: Schools influence reading scores
Share of variation in reading scores at Grade 4 explained byschool differences (2016)
per cent
0

5

10

15

20

25

30

35

40

45

Slovenia
Finland
NorwayNetherlands
PolandNorthern Ireland (UK)
Malta
England (UK)
Denmark
IrelandItaly
LatviaPortugal
Flanders (Belgium)
Czech Republic
Spain
FranceSwedenAustria
Australia
Wallonia (Belgium)
CanadaUnited States
Lithuania
Germany
Hungary
Chile
Slovakia
New ZealandIsraelBulgaria
Note: The length of each bar denotes the share of school-level variance obtained from a multilevel model.
Source: PIRLS 2016.

2 2

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Box 6 Online tests and the gender gap

Online reading is not simply a transposition of
traditional reading to the screen. It involves skills thatare qualitatively different from those used offline:
the use of search engines, hyperlinks, interactive ads
or more evaluation of information reliability. These
differences present both risks and opportunities forstudent achievement and well-being. The interactive
nature of the digital environment means that children
are exposed to more distractions. On a positive note,
online tests are believed to lead to increased student
engagement,10 lower anxiety11 and more focus on
applied knowledge. Students enjoy them.12 Since
students learn more when they are engaged,13 these
positive characteristics might present an opportunity
to improve the achievement of groups that havetraditionally fallen behind in reading, such as boys.
The TIMSS & PIRLS International Study Center
prepared ePIRLS, an online reading test withassignments in science and social studies, to see
how students perform in an interactive environment.
The test presents pupils with lessons on webpages
with animations, graphics, tabs, ads, a guiding
avatar and pop-up windows that imitate the Internet
environment. It assesses pupils’ understanding of
the lessons. In 10 EU or OECD countries, the same
Grade 4 students sat the paper test one day andtook the computer-based test the next day. The two
tests are designed to be directly comparable, andso we can see how the testing method affected
the scores.

Girls perform better than boys in reading in every
country, regardless of the testing method. However,
the average gender gap shrank from 13 to 9 points
in ePIRLS, while the average score increased.
Figure 14 presents the difference between online
and paper reading.
In Denmark, Israel, Norway, Sweden and theUS, both boys and girls do better in online tests
than paper tests. In Ireland, boys perform better
online, while girls’ performance does not differ
between tests.
No country has both worse performance andwider gender gaps when using online testing.
In most countries, there is no trade-off between
performance and gender equality. Three countries
do better in both dimensions, while another three dobetter in least one of the dimensions and no worsein the other.
Gender gaps in Denmark and Italy are notstatistically significant in online tests, which means
we cannot say that in these countries girls performbetter than boys in online reading. This suggeststhat not only the size but the very existence ofgender gaps might be influenced by the testing
method. It is unclear whether greater engagement
by boys leads to better results in the online tests.
The influence of interactive environments onreading scores requires further research.

Figure 14: The gender gap in reading scores was smaller in online tests

Average gender gap in
PIRLS and ePIRLS

25
20
15
10
5
0

PortugalePIRLS gender gap

Italy United States Canada

IrelandDenmark

IsraelSwedenSlovenia

NorwayPIRLS gender gap

Note: The darker shading within pairs indicates statistically significant differences in gender gaps between the online and paper tests.
Source: ePIRLS and PIRLS 2016.

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Box 7 Bullying at school

Figure 15: Percentage of Grade 4 children reporting bullying
per cent
020

About monthly

Almost never

40

60

80

100

Finland
NorwayIrelandSwedenDenmark
PolandFranceHungary
Czech RepublicNetherlands
Lithuania
Austria
Germany
Northern Ireland (UK)Portugal
Chile
Flanders (Belgium)
Slovakia
Italy
Bulgaria
United States
Slovenia
Spain
England (UK)
CanadaMalta
Australia
Wallonia (Belgium)
LatviaNew Zealand
About weekly

Note: No data for Israel.
Based on the question “During this year, how often have other students from your school done any of the following things to you (including
through texting or the Internet): ‘made fun of me or called me names’, ‘left me out of their games or activities’, ‘spread lies about me’, ‘stole
something from me’, ‘hit or hurt me’, ‘made me do things I didn’t want to do’, ‘shared embarrassing information about me’, ‘threatened me’?”Source: PIRLS 2016.

2 4

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A school environment that allows bullying to thrive
harms everyone, not just the victims. Grade 4
children who are bullied tend to score worse inreading literacy. Their schoolmates are also affected.
The school-level prevalence of frequent bullying is
associated with significantly lower individual reading
achievement in all but 6 of the 30 school systems
in the comparison (see Figure 16). This is after
controlling for a range of other important individual
and school-level characteristics influencing reading
achievement. The association between school-levelbullying and student reading scores is strongest in
Chile and weakest in Wallonia (Belgium).

Bullying is one of the most common forms ofviolence experienced by children. It can cause
long-lasting harm to victims, bystanders and thebullies themselves. It takes different forms, both
physical and psychological, and happens face toface, through text messaging and over the Internet.
Figure 15 shows that about one child in four inFinland, Ireland and Norway say they experiencebullying at least once a month. That ratio rises to
one child in two in Australia, Latvia, New Zealandand Wallonia (Belgium). The survey covers Grade 4
children across the 30 school systems for which
comparable data are available.

Figure 16: The relationship between school-level bullying and reading scores
0.0

Effect of bullying on reading scores

-0.2
-0.4
-0.6
-0.8
-1.0
-1.2
-1.4
-1.6

Chile

IrelandSwedenUnited States

FrancePolandHungary

Germany

Northern Ireland (UK)Portugal

New Zealand

Lithuania

Flanders (Belgium)

Netherlands

Malta

NorwayCanadaFinland

Australia

Slovakia

Denmark

Czech Republic

Spain

England (UK)

Bulgaria

Slovenia

Italy

Austria

LatviaWallonia (Belgium)-1.8

Note: The bars represent the statistical effect on reading achievement of a 1 percentage point higher school-level share of students reporting
being bullied weekly, controlling for the child’s gender, the language of testing and the language the child speaks at home, the location of theschool, whether the child comes to school hungry or tired, or has breakfast on school days, the child’s age, and principal-reported school
composition by student socio-economic status.
School systems with statistically significant effects (at p<0.05) are shown with darker shading.
Source: PIRLS 2016.

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Figure 17 shows that the countries
with higher inequality between
schools tend to have larger gaps
between the lowest- and highestscoring students.

Figure 17: Unequal school systems produce unequal reading outcomes
Performance gap in children’s reading scores at Grade 4 is larger where
the share of school-level variance is greater
240
MT

Performance gap in reading scores (P90-P10)

230

NZ

220
BG

AU

210
200

CL

GB-NIR

GB-ENG

US
DE

190

SK

IE

PL

180

BE-WAL

FR
DK

170
FI

150

HU

CA
SI

NO

IT

LT

CZ SE
ES
AT

PT
LV

160
NL

0

BE-VLG

5
10
15
20
25
30
35
40
per cent variation in reading scores explained by school differences
Pearson Correlation = 0.54, p<0.01

Note: Between-school inequality is obtained from an empty multilevel model.
Source: PIRLS 2016.

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IL

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45

More than one factor accounts forthe significant differences in thereading skills of children in Grade 4.
Up to one third of those differences
can be explained by parental
occupation, with the children of
non-professionals doing muchworse than children with at least
one parent in a professional job.
A child’s family background matters,
both because of what happens
within the family and because
children from similar families often
attend the same school. We findlarge inequalities between schools
in average student performance.
When there are smaller differences
between schools in an education
system, there tend to be smallerdifferences between the readingscores of children in that system.

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S C H O O LSECTION 5
SECONDARY SCHOOL

The end of compulsory schoolingis an important stage in a child’s
journey through the education
system. By the age of 15, which iswhen this stage of education ends
in some countries, children shouldhave acquired essential knowledge
and the skills that will help themmake their way in the world.
We address the same issues at thesecondary school level as we did at
the primary school level. We lookat overall levels of inequality inreading performance. We consider
inequalities in performance
between individual children related
to their characteristics and family
backgrounds. Finally, we discuss
inequalities between schools.
The data come from the 2015
Programme for International
Student Assessment (PISA),a study done by the OECD thattests large and nationally
representative samples of 15-yearolds in all OECD and EU countries.

All countries have large gaps
between their best- andworst-performing students
Figure 18 shows the gap in eachcountry between the best andworst performers. This approach
is similar to that used in Figure 8
for children in primary school.
The gap for older children ranges
from 221 points in Latvia to 311
points in Malta. Even the smallest
gaps show substantial inequality,with the lowest-scoring students
falling far behind their peers.

Figure 18: Where are the largest gaps in reading?
Performance gap in reading at age 15 (2015)
0

50

100

150

LatviaIrelandSpain
Denmark
Estonia
PolandCroatiaJapan
CanadaSlovenia
Finland
Portugal
Italy
Romania
Lithuania
United Kingdom
Republic of Korea
Switzerland
Hungary
NorwayGreeceIcelandGermany
United States
SwedenNetherlands
Czech Republic
Belgium
Austria
Australia
CyprusSlovakia
New Zealand
Luxembourg
FranceIsraelBulgaria
Malta

200

250
300
350
221
222
224
225
226
231
237
238
238
239
239
240
244
245
246
249
251
254
255
255
256
256
258
259
262
262
262
263
265
265
269
271
274
279
293
295
300
311

Note: The reading achievement scale has a mean of 500 and a standard deviation of 100 based on areference group of countries. The performance gap is measured as the absolute difference between
the 90th and the 10th percentiles of the reading score. Chile, Mexico and Turkey are not included in the
rankings due to low coverage rates (below 80 per cent) in PISA, which means that their results may not
be representative (OECD, PISA 2015 Results, Vol. II: Policies and Practices for Successful Schools,OECD Publishing, Paris, 2016, Table A2.1, Coverage Index 3).
Source: PISA 2015.

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Box 8 How do inequalities differ
for reading and maths?

Countries that are below the dotted line,

This report focuses on children’s reading scoresbecause proficiency in reading is a necessary skill
for studying many other subjects at school. Wouldthe picture have been any different if we had
focused on mathematics? The PISA study we used
for reading also tests children in mathematics andscience. If we compare the results for reading andfor mathematics we see that they tell much thesame story in most countries (see Figure 19).
But in some countries, there are differences.

such as Finland, Latvia and Norway – havehigher inequality in reading than mathematics.

There are also gender differences in inequalities
in maths and reading. Girls do better than boys atreading in all countries (see Figure 22). However,in maths there is a much more mixed picture.
Boys do significantly better in some countries.
In others, there is no clear difference.
The relationship between parental occupationand maths is similar to the relationship between
parental occupation and reading.

Countries that are above the dotted line in

the chart, such as Korea and Portugal, haverelatively higher inequality in mathematics
than reading.

Figure 19: Overall inequalities in reading and maths (at age 15)
320

300
MT

Performance gap in maths scores

280
IL

260

KR
PT

CH

IT

240

GB
GR
DE

HR
PL

220

ES
EE

200

180
200

IE

DK

JP

SI
CA

LT

BE
HU
IS

US

NL
CZ

AT
AU

FR

SK
CY

BG

LU
NZ

SE

NO

RO
FI

LV

220

240

260

280

300

320

Performance gap in reading scores
Pearson correlation = 0.81, p<0.001
Note: The chart shows the gaps between children at the 10th and the 90th percentiles in mathematics and reading.
Source: PISA 2015.

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National averages can hide large
differences between sub-national
regions. PISA data are available forsub-national regions in four countries.
In Belgium, there is not muchdifference between the gap observed
within the Flemish-speaking
community (a gap of 266 scorepoints) and the gap within the Frenchspeaking community (255 points).
There are more substantial variations
between the four constituent partsof the UK. Inequality is lowest in
Wales (219) and Northern Ireland(220), higher in Scotland (235) andhighest in England (254). In Spain,
17 different regions are identified in
the PISA survey. The smallest gaps
within regions are in Castile and León
(212), Navarre (217) and the Valencian
Community (218). The largest arein the Canary Islands (238) and
Andalusia (239). In the 10 provincesin Canada, the lowest level ofinequality within a province is in

Prince Edward Island (218) followed
by Saskatchewan (222). The highest
is in Ontario (244).

S E C O N D A R Y

S C H O O L

will enable them to participate
effectively and productively in life”.
Figure 20 shows the percentage ofchildren in each country who reachthis level of proficiency and theperformance gap in reading scores
discussed above. Latvia performs
best on equality, while Ireland
performs best on proficiency inreading at age 15. Bulgaria andMalta are at or near the bottom of
the rankings for both. Most othercountries range close to a line
between these two extremes, withsimilar patterns for both measures.
Romania stands out for having amuch lower percentage of children
reaching basic proficiency thanwould be expected, given its levels
of inequality.

Countries with greater equalityof achievement tend to havebetter basic reading proficiency
Countries with wide gaps between
their best- and worst-performing
students tend to have fewer children
reaching basic proficiency. We foundthe same relationship between overall
inequality and reading proficiency forchildren in primary school. The PISA
study for 15-year-olds has a different
definition of reading proficiency than
the PIRLS study for Grade 4 students(see previous section). PISA sets thebaseline for proficiency at Level 2.
Students at this level “begin todemonstrate the reading skills that

Figure 20: More equal systems tend to have higher standards
Percentage of students achieving basic reading proficiency at age 15 ishigher where the performance gap in reading achievement is lower (2015)100
per cent of children reaching level 2 reading proficiency

A country’s rank for educational
inequalities can change between the
primary school and the secondary
school surveys. Some countries have
similar rankings in both. Finland, Italy,
Latvia, Portugal and Spain are in the
top third (most equal) systems inboth surveys. Australia, Bulgaria,
Israel, Malta, New Zealand andSlovakia are in the bottom third(most unequal) in both. Canada,
Denmark, Ireland, Poland andSlovenia move from the middle thirdat primary school level to the top
third at secondary school level. Somecountries fall considerably from one
ranking to the next. The Netherlands
is ranked the most equal country
for students in Grade 4, where theaverage age is 10 years, but is in
the bottom third when children are
15 years old. Austria, Belgium andthe Czech Republic also move fromthe top third to the bottom third(see Figure 2).

5

95
90
85

IE

ES
LV

80

FI
JP
SI

EE CA
DKPL

PT

DE
GB

HR

75

KR

CH
IT
IS
LT
HU

NO

NL
US

NZ

AU
SE BE
CZ

FR

AT
LU

GR

IL

70
SK

65

MT

CY
RO

60

BG

55
50
200

220

240
260
280
Performance gap in reading achievement
Pearson correlation = -0.64, p<0.001

300

320

Note: Chile, Mexico and Turkey are not shown in this analysis (see Figure 18).
Source: PISA 2015.

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Box 9 The impact of a parent’s vocabulary
on a child in the UK

A good command of language is a prerequisite forreading. Children from wealthier families tend toscore higher in assessments of verbal ability from anearly age.14 Evidence from the UK Millennium Cohort
Study (MCS) suggests that differences in parental
vocabulary account for some of this variation.
Children and their resident parents completed astandardized vocabulary test measuring theirunderstanding of 20 different words. The word lists
were different for the 14-year-olds and their parents.
One of the more difficult words on the children’s listwas ‘indifferent’. Only 10 per cent of children
selected the right answer (i.e. ‘uninterested’).
Nearly half of those who got it wrong thought itmeant ‘similar’.
Figure 21 plots the average number of words out of
20 that children identified correctly (vertical axis)
against the number of correct words answered by
the parent who acted as the main respondent in thesurvey (horizontal axis). These were predominantly
mothers. The results are presented separately forchildren whose parents work in different occupations.

Children got seven words correct, on average.
The children of managers and professionals chose
1.3 more words correctly on average than children
whose parents work in routine and semi-routine
occupations, such as cleaners or labourers.
Parental occupation makes no difference to children’sscores if their parents scored below average in theirown vocabulary test. However, social class makes
progressively more of a difference for children whoseparents score above average, with the social-class
gap reaching 1.8 words.
Having a parent with a poor vocabulary puts children
at a disadvantage, regardless of the family’s overallsocial background. Children from poorer social
backgrounds would need their parents to have aprogressively richer vocabulary to bridge the socialclass gap. This only works up to a point because
children whose parents work in professional andmanagerial occupations and have a very richvocabulary (scoring at least 17 words out of 20)
have the highest scores of all.

Figure 21: Adolescent word gap and parental vocabulary
10Child’s average score

9

8

7

6

5

0

1

2

3

Managers and Professionals

4

5

6

7

8

9
10 11
Parent’s score

Routine and Semi-Routine occupations

Note: The analysis accounted for the weights and survey design.
Parental occupation is based on the highest occupational category of the parent(s).
Average children’s score: 7 out of 20; parental score: 11 out of 20. N = 10,014.
Bars represent 95 per cent confidence intervals.
Source: UK Millennium Cohort Study 2015 (6th sweep).

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12

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13

14

15

16

17

18

19

20

S E C T I O N

Greater equality of achievement
is linked to having more children
achieve a basic level of reading
proficiency. There is no evidence
that greater equality undermines
educational standards. This is an
important message for policy
makers who fear that efforts tocreate a more equal system will
push the top students down, rather
than pull the bottom students up.

5

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Figure 22: Girls outperform boys in reading
The percentage by which girls score higher than boys in reading at Grade 4
and at age 15
Country

Grade 4 (PIRLS)

15 years old (PISA)

Portugal

ns

3.40%

Austria

1.10%

4.30%

Italy

1.40%

3.40%

United States

1.50%

4.10%

France

1.50%

6.00%

Spain

1.60%

4.20%

Slovakia

1.70%

8.20%

Educational researchers have long
been interested in the differencesin performance between girls andboys. There is evidence in somecountries that gender gaps emerge
in the early years15 and persist
across different stages in
education.16 These genderdisparities can be in opposite
directions for different subjects,
for example, girls may do betterat reading and boys atmathematics. Various reasons
have been proposed for thesegaps, including the internalizationof gender roles and norms bychildren as they grow up, attitudes
to gender, and the balance offemale and male teachers.17

Czech Republic

1.90%

5.50%

Netherlands

1.90%

4.80%

Belgium

2.10%

3.30%

Ireland

2.10%

2.30%

Germany

2.10%

4.20%

Canada

2.20%

5.10%

Hungary

2.30%

5.40%

Denmark

2.40%

4.50%

Israel

2.50%

4.90%

United Kingdom

2.70%

4.50%

Sweden

2.80%

8.20%

Bulgaria

2.90%

11.50%

Latvia

3.10%

9.00%

Figure 22 shows the extent towhich girls did better than boys
in reading tests in the 28 countries
that took part in both PIRLS 2016
and PISA 2015. The gap isexpressed as a percentage basedon the difference between thetwo scores divided by the boys’score. For example, if the meanscore for girls was 550 and themean score for boys was 500,
then girls would be doing
10 per cent better than boys.

Poland

3.20%

6.00%

Slovenia

3.50%

8.90%

Lithuania

3.80%

8.60%

Norway

3.90%

8.10%

Finland

3.90%

9.20%

Australia

4.00%

6.50%

New Zealand

4.20%

6.50%

Malta

4.70%

9.90%

Inequalities in reading
between girls and boys arehigher in secondary school

Note: The figure shows the percentage by which girls score higher than boys in reading in each country
and stage, calculated as 100*(Girls’ mean - Boys’ mean) / Boys’ mean. All differences were statisticallysignificant (p<0.05) except in Portugal at Grade 4. The shading shows the countries in the lowest (lightblue), middle (medium blue) and highest (dark blue) third of the rankings among the 28 countries thattook part in both surveys.
Source: PIRLS 2016 and PISA 2015.

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 In all countries in both surveys,

is only a small gender gap of a few
score points in favour of boys.

girls had higher mean readingscores than boys. In every case
except Portugal, at Grade 4 (whenthe average age is 10) the gender
gap was statistically significant.
Girls also had significantly higherscores than boys in the other11 countries that took part in PISA
but not in PIRLS.

Gender differences vary acrosscountries and subjects. However,the persistent gender gaps in reading
at both educational stages areimportant because reading is afundamental gateway skill forachievement in many other academic
subjects. Furthermore, as discussed
in Box 11, in most rich countries
covered in this report girls tend tohave higher expectations than boysof gaining a university degree.
Educational statistics show a greater
participation in higher education
among girls than boys in most OECD
countries.19 The data suggest thatboys are entering post-secondary
education on an unequal footing withgirls when it comes to reading.

 The gender gap in reading waslarger at age 15 than at Grade 4 inall countries. The two surveys test
different reading skills, and so are
not directly comparable; but it
appears that the gap tends towiden as children get older.

 The shading shows the rankingsof countries in three groups – low,
medium and high gender gaps.
Many countries are in the samegroup in both surveys. Eight of
the ten most unequal countries
at Grade 4 were also among themost unequal at age 15. There
were, however, substantialchanges in rankings in a few
countries. Bulgaria, Slovakia
and Sweden are all ranked asmuch more unequal at age 15
than at Grade 4.

Gaps in reading scores insecondary school are still linked
to parental occupation
The PISA study asks children what
their parents do for a living andplaces their answers on a scale.
Lower scores on this scale represent
jobs like manual work. Higher scores
relate to jobs like managerial work.
In Figure 23 we have divided children
in each country into two halves,
based on whether their parents had
high-status or low-status occupations.

To what extent are these genderdifferences unique to reading? PISA
has also published findings on recent
gender gaps in mathematics andscience at age 15.18

In all countries, children whoseparents had high-status occupations
tended to have significantly higher
reading scores. The differences weremuch larger in some countries thanin others. The average gap was lessthan 30 points in Iceland and Japan,
but over 70 points in Bulgaria,
Hungary and Luxembourg.

 For mathematics, boys in mostcountries tended to score higher
than girls. However, thesedifferences were significant in
only just over half of the countries
covered in this report.

 For science, there is a more mixed

picture. In some countries, boys
do better than girls; in othercountries, girls do better than boys.
On average across countries there

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These patterns match the findings
in previous sections. They reflectongoing educational inequalities
linked to family background as
children near the end of compulsory
schooling. Box 9 shows that socio-

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economic status and parents’own skills reinforce each other in
influencing children’s verbal scores.

There are large inequalities inachievement between schools
Children’s educational opportunities
can be substantially influenced bywhich school they attend. There areoften large differences in averageachievement between schools within
the same country. Analysing thesedifferences helps us understand thenature of educational inequalities andwhat might be done to reduce them.
We looked first at how much of thetotal variation in children’s readingscores at the age of 15 in eachcountry was between schools,
rather than between children within
schools. This is similar to theapproach we used in the section on
primary schools. The length of the barin Figure 25 shows the total variation
between schools.
In Iceland, about 95 per cent of
the inequality in reading scores is
between children within schools,
and only a small amount is between
schools. In Bulgaria, Hungary and
the Netherlands, there is moreinequality between schools than
within schools. In most othercountries, at least one fifth of thevariation is between schools.
Bulgaria and Hungary already had
relatively high variation between
schools at the primary level (seeFigure 13). However, the Netherlands
had relatively low variation of thiskind at primary school, but has themost variation when children are
15 years old. Italy also has muchgreater variation between schools
at the secondary level than at the
primary level. New Zealand andthe US had less between-school
variation at secondary school thanat primary school.

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Figure 23: Children of parents with high-status jobs have higher reading scoresChildren’s reading scores at age 15, by parental occupation (2015)
Mean reading score
0

100

200

300

400

500

600

IcelandJapan
NorwayRepublic of Korea
Romania
CanadaUnited States
Estonia
FinlandDenmark
LatviaIreland
Australia
United Kingdom
CyprusPolandSpain
Germany
SwedenMalta
New Zealand
Lithuania
Netherlands
Slovenia
Italy
Croatia
IsraelAustria
Portugal
Switzerland
Slovakia
GreeceCzech Republic
Belgium
FranceHungary
Luxembourg
Bulgaria
Low-status jobs

High-status jobs

Note: The chart shows the mean scores for children whose parents were in the top and bottom half of the occupation classification in each country.
The differences in means were statistically significant in all countries. The chart is ranked in order of the size of the gap, from smallest to largest.
Source: PISA 2015.

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Box 10 How migration affects reading abilityChildren who move to a new country face challenges
that directly or indirectly affect their educational
progress. These can include getting used to adifferent way of life, making new friends, learninga new language and adapting to a new education
system. Their family’s economic circumstances may
have been affected by the move. They could haveexperienced trauma before or during their journey.
They could have faced prejudice and negative
reactions on arrival in their new country. The childrenof immigrants also face some of these challenges.
So how do child immigrants or the children of
immigrants fare educationally in rich countries?
We answer this question using the PISA data for
15-year-olds in 25 countries where at least 5 per centof children are immigrant students. We use the three
OECD categories to define immigration status:20
1. Non-immigrant students are children who haveat least one parent who was born in the country,irrespective of whether the child was born there.
2. First-generation immigrant students are foreignborn children whose parents are also bothforeign born.
3. Second-generation immigrant students are children
who were born in the country and whose parents
are both foreign born.

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In most countries, first-generation immigrant children
have significantly lower reading scores than
non-immigrant children. That said, the difference
between these groups is statistically significant inAustralia, Canada, Estonia and New Zealand.
Second-generation immigrant children had
significantly lower reading scores than non-immigrantchildren in 15 countries. However, in Australia andCanada, they did better than their non-immigrantpeers. Figure 24 shows the percentage of children
in each country who had not reached a basic level ofreading proficiency in the test language at age 15.
These results may reflect different historical patternsof migration. For example, the OECD identifies
Australia, Canada and New Zealand as ‘settlement
countries’, where immigration is part of the heritageof the country, immigrants are often highly educatedand may share English as a first language. Austria,
Belgium, France and Germany are ‘long-standing
destination countries with many settled, loweducated migrants’. Greece, Italy and Spain haveexperienced substantial levels of immigration inrecent years. This type of educational inequality
cannot be tackled without a thorough understandingof these historical migration patterns.

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Figure 24: Percentage of 15-year-olds by migrant status, who have not reached Level 2 proficiency
in reading
per cent
0

10

20

30

40

50

60

CanadaNew ZealandIreland
Australia
Portugal
Croatia
CyprusEstonia
United Kingdom
United States
Spain
Luxembourg
Switzerland
NorwayIsraelDenmark
Belgium
Italy
Netherlands
Slovenia
GreeceFranceSwedenGermany
Austria
Non-immigrant

Second-generation

First-generation

Note: The chart shows percentages for each group in all countries where at least 5 per cent of children were not born in the country. Countries
are ranked on absolute gaps between non-immigrant and first-generation immigrants. Differences between non-migrant children and first-generation
migrant children were statistically significant in all countries except Australia, Canada, Estonia and New Zealand.
Source: PISA 2015.

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Variations between schools
are linked to the backgroundsof children in the school

Figure 25: Most countries have significant differences between schools
Share of variation in reading scores at age 15 explained by school
differences (2015)

There are many possible
explanations for the existenceof these substantial variations inaverage reading scores between
schools. They include the school’s
location: Is the area urban or rural?
Are residents mostly rich or poor?
They also include the type of school:
Is it public or private? Does it selectstudents? Schools also vary in the
resources available to them. There isevidence in the PISA survey of links
between all these factors andaverage reading scores.21
Another important part of the pictureis the family background of students
within each school. This explains asubstantial proportion of the variationin achievement between schools,
which is shown by the darker partof the bar in Figure 25.

per cent variation in reading scores explained by school differences
0

10

20

30

40

50

60

IcelandFinland
NorwayIreland
PolandSpain
SwedenDenmark
LatviaCanadaNew ZealandEstonia
United States
United Kingdom
Australia
Portugal
CyprusRepublic of Korea
Luxembourg
Malta
Lithuania
Switzerland
GreeceRomania
Croatia
IsraelItaly
Japan
Czech Republic

Note: The total length of each bar represents thepercentage of total variance in test scores
occurring between schools obtained from anempty multi-level model. As noted in the initialreport on the PISA 2015 survey “In somecountries, sub-units within schools were sampled
instead of schools, and this may affect theestimation of the between-school variancecomponents” (OECD, PISA 2015 Results, Vol. I:
Excellence and Equity in Education, OECD
Publishing, Paris, 2016, p. 294).
In France, the PISA test happens around the time
when children move between two stages ofschooling. This makes it difficult to interpret
variations between schools, and so France is
not included in this chart.
Source: PISA 2015.

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Germany
Belgium
Austria
Slovakia
Slovenia
Bulgaria
Hungary
Netherlands
Explained by parents' occupationC A R D

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Not explained by parents' occupation

70

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occupation are considered, otherfactors – such as school location,
type and resources – are much lessstrongly linked to performance
inequalities between schools. Just as
in primary school, the composition of
the secondary school population interms of family background is an
important aspect of understanding
educational inequalities.

Social and economic differencesamong students are a feature of
education systems in all countries.
But they are much stronger in somecountries than others. When children
with the same social and economic
position are clustered together inschools it is called socio-economic
segregation.22 Scandinavian countries
tend to have low levels of this typeof segregation, as do some East

Figure 26: Socio-economic inequalities in children’s test scores are higher
where there is more socio-economic segregation between schools

Inequality in performance linked to parental occupation

25

LU

20

PT
HR

CH GR

10

NZ
SE

IE

IT

LT

LV PL
DK
EE
GB MT
CA
AU
US

FI

HU

IL

CZ
SI
RO
ES

CY

KR

NO

5

NL

SK
AT

DE

JP
IS

0

0

5
10
15
20
25
30
Extent of socio-economic segregation between schools
Pearson correlation = 0.84, p<0.001

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Asian and English-speaking
countries. The highest levels of thistype of segregation are in Hungary
and Luxembourg. Countries withgreater socio-economic segregation
between schools tend also to be
ones that have greater inequality ofachievement based on a parent’s job(see Figure 26).
Socio-economic segregation has
been recognized for some time as
an important part of the picture of
how educational inequalities due tofamily background develop andpersist. A recent analysis suggeststhat levels of segregation within richcountries have changed little inrecent decades.23 The authors of thatanalysis point out that this type ofsegregation has persisted despite
policy initiatives to reduce it. They
conclude that policy makers need to
be much more radical if they want
to foster greater levels of integration
between the rich and the poor.
This is a complex issue to tackle.
There are many different factorsthat lead to socio-economic
segregation of children between
schools. Not all of them are directly
related to the education system.
In countries where there are largesocial and economic differences
between geographic areas,
residential segregation will occur
naturally if children are assigned
to their local school. Segregation
can also be a consequence of
education policy, which we discussin the next section.

BG
BE

15

5

35

Note: The vertical axis shows the R-squared from a regression of reading scores onto highest parental
occupation. The horizontal axis shows the intra-class correlation coefficient from an empty multilevel
model with parental occupation as the dependent variable. In France, the PISA test happens aroundthe time when children move between two stages of schooling. This makes it difficult to interpret
variations between schools, and so France is not included in this chart.
Source: PISA 2015.

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Box 11 Inequality and future
expectations

To what extent might the inequalities we have highlighted in thisreport be reflected in young people’s participation in education as
they move into adulthood?

Students in the rich countries of theworld are on an unequal footing as
they near the end of compulsory
schooling. Parental occupation still
predicts how well a child will read insecondary school. The segregationof students along social andeconomic lines contributes to thepersistence of inequalities due tofamily background. Children whoseparents work in lower-status
occupations are less likely to saythat they expect to complete tertiary
education, even if they score as
highly as their peers with high-status
occupation parents (see Box 11).

The PISA study asked 15-year-olds what level of education they
expected to complete. At 15, many children will have ideas not
only about what they hope to do in the future, but also what theymight realistically expect to do, given their circumstances andeducational progress.
We focus here on children who expect to complete some form of
tertiary education. This includes academically oriented education,such as a university degree, and practically oriented, post-secondary
education. The percentage of children who said they expected tocomplete tertiary education ranged from less than 20 per cent inGermany and the Netherlands to just under 90 per cent in Korea.
These variations in expectations between countries are rooted ina range of historical, cultural and economic differences. They may
also reflect the structure of the different educational, vocationaland occupational pathways open to young people in each country.

The PISA study from which we drew
our data has been compared to an
X-ray of a country’s education
system: it does not give the full
picture, but it highlights where
things are going wrong. Fixing these
problems is the job of education
systems and policies, which we turnto next.

Socio-economic background affects expectations,regardless of achievement
Children’s expectations about completing some form of tertiary
education are linked to their family circumstances. In every country,
children whose parents work in high-status occupations weresignificantly more likely to expect to complete some form of
tertiary education. To some extent this can be anticipated, because
children from more privileged families tend to be doing better atschool. But that is not the whole story. In all countries, there weresignificant differences by parental occupational status amongchildren who were doing equally well at school. Figure 27 shows
the gap in expectations between those whose parents work in lowand in high-status occupations, adjusting for differences in readingscores between the two groups. This gap ranged from only around
4 per cent in the Republic of Korea to 20 per cent in Poland.

Girls and boys have unequal expectations in mostcountries
In addition to differing expectations based on family background,
expectations also differed by gender (not shown). In 29 of the
35 countries included in this analysis, females were significantly
more likely than males to expect to complete tertiary education.
The gender gap in expectations was largest (19 percentage points)
in Bulgaria and Norway. There were six countries (Austria, France,
Germany, Japan, the Netherlands and Switzerland) where the rates
were similar for both genders.

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Figure 27: Expectation gap between children with the same reading scoresby occupation status of their parents
Difference in expectations of completing tertiary education between children
with parents in low- and high-status jobs, taking account of reading scores
0

20

40

60

80

100

Republic of Korea
IsraelIrelandUnited States
Netherlands
GreeceJapan
Germany
CanadaCyprusAustralia
NorwaySwitzerland
IcelandFranceNew Zealand
Denmark
Lithuania
Spain
United Kingdom
Finland
Bulgaria
Austria
Croatia
Czech Republic
Luxembourg
Belgium
Estonia
Slovenia
SwedenHungary
Portugal
Latvia
Italy
PolandLow-status occupation

High-status occupation

Note: The bars show the marginal
expectations of completing tertiary
education by the status of parental
occupation (low vs. high) in eachcountry, from a regression model
controlling for reading scores.
Countries are ranked in ascendingorder of the size of the difference
between the two groups.
The differences are significant inall countries. No valid data for Malta,
Slovakia and Romania.
Source: PISA 2015.

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SECTION 6
EDUCATION SYSTEMS AND POLICIES

Education policies and practices
can reduce or reinforce educational
inequalities stemming fromchildren’s starting points andongoing family circumstances.
There is no one-size-fits-all policy
guaranteed to produce the best
results. Countries and regions
differ in their social, cultural,
economic and political make-up.
What works for those at the top of
our league table will not necessarily
help those at the bottom toreduce educational inequalities.
Figure 28 provides an overview
of key characteristics of the school
systems and illustrates the great
diversity of educational experiencesthat children may have in
different countries.

Educational participation rates

are generally high. However, insome countries the percentages
indicate that a substantial
number of 15-year-olds are nolonger in school. Chile, Mexicoand Turkey were not included insome of our rankings because
the PISA study captured lessthan 80 per cent of 15-year-olds
in these countries. There canbe many reasons for this,including that these children
had left school.

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The age at which children are

first divided into different typesof schools or programmes(sometimes called selection or
tracking) varies from 10 years inAustria and Germany to 16 years
in many others, including
Australia, Estonia and the UK.

Some countries have multiple

types of schools or programmes,
while some only have one. The
Czech Republic has six. The
Netherlands has seven. Thesemay include pathways that are
more vocationally oriented andothers that are more academic.
At some point a decision is made(by teachers and/or parents and/or children themselves) about
which path a child will initiallytake. Often it is possible toswitch tracks later.

Some countries make extensive

use of grouping children byability within schools. This cantake the form of putting children
into different classes or into
different groups within classes.
This practice may apply to all
subjects or to selected subjects.
Over 90 per cent of schools in
Ireland, Israel and the UK use
these practices.

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 In some countries, it is common

for children to repeat at least one
grade during their school career.
This happens to over 30 per cent ofchildren in Belgium, Luxembourg,
Portugal and Spain. In othercountries, such as Japan and
Norway, this practice is very rareor does not happen at all.

The balance of schools managed

by public bodies and privatebodies also varies widely. Latvia
and Ireland are at the top of theleague table of educational
inequalities (see Figure 2) but arehugely different in this respect.
In Ireland, 57 per cent of schools
are managed privately, comparedwith 2 per cent in Latvia.

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Figure 28: Key characteristics of school systems that influence education equality
Coveragerate (a)First
selectionin theeducationsystemNumberof school
types orprogrammes
available to15-year-olds

Withinschool
abilitygrouping(b)

Graderepetition(c)

Privateschoolenrolment(d)Country%

Student’s
age

N

% of
15-yearolds%%

Australia

90.6

16

1

88.1

7.1

43.7

Austria

83.4

10

4

16.4

15.2

12.6

Belgium

92.9

12

4

28.4

34.0

N/A

Bulgaria

80.6

15 (e)

3

26.3

4.8

1.2

Canada

83.5

16

1

86.8

5.7

9.7

Chile

79.8

16

3

27.1

24.6

63.1

Croatia

90.8

14

1

22.9

1.6

2.3

Cyprus

94.9

15

2

27.0

4.7

16.0

Czech Republic

93.5

11

6

28.9

4.8

8.2

Denmark

89.0

16

1

25.2

3.4

23.2

Estonia

92.8

16

1

38.1

4.0

4.2

Finland

97.3

16

1

53.2

3.0

4.5

France

91.0

15

3

24.3

22.1

21.0

Germany

96.1

10

4

30.0

18.1

7.3

Greece

91.1

15

2

11.6

5.0

4.9

Hungary

89.6

11

3

35.1

9.5

18.0

Iceland

93.3

16

1

22.6

1.1

0.6

Ireland

96.5

15

4

95.9

7.2

57.3

Israel

93.7

15

2

97.8

9.0

N/A

Italy

80.3

14

4

13.1

15.1

4.1

Japan

94.7

15

2

53.6

0.0

31.8

Latvia

88.8

16

5

18.7

5.0

2.0

Lithuania

90.2

m

5

51.0

2.5

2.3

Luxembourg

87.6

13

4

71.8

30.9

15.6

Malta

97.7

15

3

75.5

7.0

41.8

Mexico

61.7

15

3

46.9

15.8

12.5

Netherlands

95.1

12

7

70.8

20.1

60.1

New Zealand

90.2

16

1

89.9

4.9

6.6

Norway

91.3

16

1

15.7

0.0

1.9

Poland

90.9

16

1

38.0

5.3

3.5

Portugal

87.6

15

3

11.6

31.2

5.5

Republic of Korea

91.7

15

3

57.8

4.7

34.7

Romania

N/A

16

2

46.2

5.9

1.1

Slovak Republic

89.2

11

5

34.6

6.5

11.6

Slovenia

92.8

14

3

34.7

1.9

2.6

Spain

90.9

16

1

40.3

31.3

31.3

Sweden

93.6

16

1

21.4

4.0

17.9

Switzerland

96.2

12

4

62.3

20.0

6.1

Turkey

69.9

11

3

30.5

10.9

4.8

United Kingdom

84.0

16

1

99.8

2.8

55.8

United States

83.5

16

1

82.6

11.0

7.7

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Note: (a) These figures are the coveragerate for participation in the PISA survey at
15 years old.
(b) Percentage of 15-year-olds enrolled inschools that practise ability grouping forsome or all subjects.
(c) Percentage of students (self-reported)
who repeated a grade at least once inprimary or secondary school.
(d) Based on the OECD definition of private
schools, “Schools that are directly or indirectly
managed by a non-government organisation,such as a church, trade union, business,or other private institution”.
(e) Starting age at some vocational schools
is 14.
Source: Private school enrolment: OECD,PISA 2015 Results, Vol. II: Policies andPractices for Successful Schools OECD
Publishing, Paris, 2016.
Enrolment of 15-year-olds and grade
repetition: OECD, PISA 2015 Results, Vol. I:
Excellence and Equity in Education, OECD
Publishing, Paris, 2016.
Ability grouping: Results based on reports
by school principals in PISA 2015 datacollection (OECD).
First age at selection in the education system
and number of education programmes:
OECD, PISA 2012 Results: What makes
schools successful? OECD Publishing,Paris, 2013, Table IV.2.5.

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Box 12 Sorting and inequality
in Germany

Several key policies and practices
have a bearing on inequalities bothwithin and between schools in
specific countries or contexts.24
These include features highlighted
in the table, such as grade
repetition, streaming and tracking.
Other policies relating to school
choice and to school transfers andexpulsions may reduce the diversityof children within schools,
potentially increasing educational
inequalities. Where children are
sorted into different streams within
schools or go to different schools
based on their academic
performance, children from lessprivileged families tend to be overrepresented in the lower tracks,
with fewer opportunities in the
future. This is especially the case
if sorting takes place at a very earlyage, when children have not yet
managed to develop their potential(see Box 12).

Austria and Germany start earlier than other rich countries to sort or track
their students into different schools or programmes. This has an impact
on what opportunities are available to students in the future. In Germany,
after four years of primary school (Grundschule), most 10-year-olds are
sorted by ability into one of three main tracks: academic, which leads touniversity-entry examination (Abitur), general and basic. The last two are
more likely to lead to vocational training and, subsequently, to blue-collar
jobs (see Figure 29). Some students are allowed to switch tracks.

Figure 29: Educational pathways in Germany

University
Academic
Track

31%
12%

It is tempting to use the above
figure to try to identify featuresthat are associated with greater
educational equality. However,the fact that societies with suchdifferent approaches to school
management as Latvia and Ireland
can appear side by side at the topof the league table suggests thatthings are not simple (see Figure 2).
Education policies within any
country are drawn up anddeveloped within that country’s
own economic, social and politicalcontext. It may be that individual
policies and practices do not
successfully transfer from one
context to another. More analysis
is needed at the country level,
and more evidence is needed ofwhat works and why before
seemingly successful policies
can be safely copied.

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23%Primary
SchoolGeneral
Track

100%

35%
17%
Basic
Track

12%
Vocation

73%(=22% fromthe basic track+ 29% fromthe general +22% from
academic)

34%
Note: All numbers on the graph refer to a proportion of the original cohort (100 per cent from theprimary school). A number alongside an arrow indicates the percentage of the original cohort ofprimary students that switches track. For example, 17 per cent of all students went from thebasic to the general track at some point. Downgrading is so rare that it is left out of the model.
Percentages might not add up to 100 per cent because of the drop-outs from the system. Overthe whole secondary cycle, 2 per cent of the cohort dropped out of the basic track, 2 per centdropped out of the general track and 1 per cent dropped out of the academic track.
Source: Own presentation based on numbers calculated by Biewen and Tapalaga from the
National Educational Panel Study (NEPS, starting cohort adults, SC6) based on a representative
sample of people born between 1950 and 1979.25

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Figure 30: Percentage of children on different tracks by parental occupation
80

70

60

per cent

50

40

30

20

10

0

Low-status jobs

Basic general

Extensive general

Academic

High-status jobs

Note: Families are split into two groups (low- and high-status jobs) on the median of the occupation ranking provided by PISA 2015 for Germany.
Source: Own calculation based on PISA 2015.

Supporters of tracking believe it fosters specialization
and allows schools to design a better course ofstudies for students in each track. Opponents say
tracking increases inequalities without increasing
average performance.26 They say it gives parental
status disproportionate influence and takes placeat an age when many pupils are too young to show
their potential.27
Sorting is based on the primary school’s
recommendation. In most regions, therecommendation can be challenged by parents,
a process that requires effort, knowledge andresources. Differences in parental status may affect
tracking allocations. Among children who end up on
the basic track, 76 per cent come from families withlow-status occupations (see Figure 30). Four out of fivechildren whose fathers have the Abitur go on to theacademic track. The children of migrants to Germany
can be affected by their parents’ lack ofa high-status occupation or knowledge of how tochallenge a school’s recommendation. Most of thesechildren end up on the basic track, with only
20 per cent making it onto the academic track.28

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SECTION 7
CONCLUSION AND RECOMMENDATIONS“All of us do not have equal talent,but all of us should have an equal
opportunity to develop thosetalents.” That observation, made in
1963 by US President John F.
Kennedy to a group of university
graduates, is at the heart of thisReport Card. All children deserve thesame chance to learn and develop
the crucial skills needed for life. In
the richest countries of the world,
some children are being denied
that opportunity.
We asked three sets of questions at
the outset:
1. How much educational inequality
is there in rich countries? Does itvary between countries?
2. To what extent do children’s
starting points, circumstancesand characteristics explain
educational inequalities?
How does this vary between
countries and across the different
stages of education?
3. To what extent do education
systems and schools magnify
or reduce inequalities between
children? What policies andpractices can help to reduce
inequalities?
In our search for answers, we
looked at milestones on the paththat children take from pre-primaryeducation to the end of compulsory
schooling, and we looked at their
future educational expectations.
Our survey covered 41 countries inthe EU and OECD. We used threemeasures of inequality in children’s
reading performance: the dispersion

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in the scores between the lowestand highest-scoring students (i.e.
the performance gap); differences inchildren’s reading scores due tocircumstances outside their control(e.g. parental occupation; the child’s
gender; country of birth); anddifferences between schools.
We found that educational inequality
is pervasive, but that some affluent
societies do better than others inmaking sure that the lowestperforming students do not lag
too far behind their highest-scoring
peers. This offers hope and thepotential to learn from different
education policies and practices.
Societies as diverse as Latvia andSpain have low performance gaps
in reading achievement among bothprimary and secondary school
students. Contrary to the view thathigher standards require greater
inequality between children,
there is no trade-off between lower
performance gaps and higher
average achievement. Making an
education system more equal does
not mean that standards must sinkto the lowest common denominator.
Both primary and secondary school
students are more likely to achievea good minimum level of reading
proficiency in countries withsmaller gaps.
The answers to the second question
deliver a less optimistic story.
Boys tend to do worse in reading
than girls. Gender gaps are wider
in secondary school. Children born
outside the country of the test
perform worse than their native-born

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peers in most of the countries
where there are sufficient numbersof foreign-born children to measure
the difference.
Almost universally, children fromless-privileged families do worse.
Some of these inequalities emerge
before primary school. In half ofthe European countries, preschool
children aged 3 and older fromlower-income households are lesslikely to attend centre-based
education services. Grade 4
students whose parents work in
professional occupations do betterin reading in all the countries forwhich data are available. Parental
occupation explains up to one thirdof the variation in reading scores at
Grade 4. Toward the end ofcompulsory schooling at the age of15, children whose parents work inlower-ranked occupations do worse
in reading and are less likely to saythat they expect to complete postsecondary education across all
35 countries in the comparison.
There is much more inequality withincountries than there is between
countries. Among 15-year-olds thelargest gap in mean reading scoresis 95 points – between Canada andBulgaria. In comparison, the gap
between children at the 10th
and 90th percentiles in Canada is
238 points and in Bulgaria is
300 points (see Figure 18).
There is a lot of variation in inequality
between schools in this assessment.

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Box 13 Who is left out of this report?

This Report Card has drawn on the best available
data for international comparisons. Yet it does notpaint a completely accurate picture of all children,
because some are not captured in national orinternational surveys. Those left out include children
who are not in school, perhaps because they are in
institutions, are home schooled, or have severe
health problems or disabilities. Children who are in
special education are not well captured in the data.
Nor are children who are not in standard housing
because they are homeless, are in temporary
accommodation or are part of an unregisteredfamily. Then there are those less likely to attend
school on the date of the survey due to health,truancy or other issues. The children we are unable
to capture through statistics may face multiple,
overlapping forms of disadvantage. The followingcase study of Roma children shows how
disadvantages can build on each other.
Roma children: Less likely to enrol, more likely todrop out
Roma are Europe’s largest ethnic minority and oneof the most disadvantaged groups on the continent.
A recent survey indicated that 90 per cent of Romalive in households below national poverty lines and40 per cent live in households where someone
experienced hunger in the month preceding thesurvey.29 They are more likely to live in sub-standard
housing in segregated areas. Urban segregation anddeprived housing exacerbate economic hardship.
Some administrative practices are ill-adapted to thesecircumstances. For example, families without aresidence certificate find it harder to register children
for school. Low education is both the outcome ofprevious and a driver of future exclusions.

Roma are often missing from national statistics
where data collection is organized around regularhousing. Roma children are less visible in education
statistics because they have a lower enrolment rate
than non-Roma, they have a higher drop-out rate
after the end of compulsory education, and they are
more likely to be placed in special schools.
Around half of Roma children between the age of 4
and the start of compulsory education (which varies
by country) do not attend preschool. On reaching theage of compulsory schooling, 14 per cent of Romachildren are not in education, compared to 3 per centof their non-Roma peers, in the 11 EU countries witha significant Roma presence.30 Roma non-enrolment
ranges from 5 per cent in Hungary to 43 per cent in
Greece and is driven by poor housing conditions,among other factors. Among Roma children frominformal settlements in France, 3 in 10 have neverbeen registered for school, while two out of three
do not go to school on a regular basis.31
Roma children are likely to drop out of school. Acrossthe EU, 88 per cent of Roma aged 18–24 had notcompleted any sort of upper-secondary education.
They are also more likely to be placed in special
schools, a practice believed by some human rights
organizations to amount to ethnic segregation.32
Non-enrolment, irregular attendance, high drop-out
rates and special school segregation are only someof the factors that lead to the under-representation ofchildren in international surveys. In every country,
there are disadvantaged groups whose plight is notclearly captured by the official figures. This suggeststhat the educational inequalities presented in thisreport are likely to be much greater than the available
data show.

Figure 31: Why are children missing from national statistics?

Childrencoveredin surveys

Neverregistered

Registered
but not
enrolled

Enrolled in
types ofeducation thatare not covered

Were
enrolled but
droppedout

Are enrolled
but attend
irregularly

Took thetest but
did not
hand it in

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In Finland, less than 10 per centof overall variation in reading
performance is due to differencesin average scores between schools(rather than among children within
schools) at both primary andsecondary levels. In Hungary,differences between schools
account for nearly one third of thevariation in reading scores at the
primary level and for more thanhalf of the variation at the secondary
level. Similarities in children’s family
background within schools accountfor a substantial share of the
between-school differences inmost countries.
While the sources of theseinequalities are complex, there is
ample potential for policies andpractices to mitigate them. We
cannot prescribe solutions forindividual countries. Still, there
are general principles andrecommendations that emerge fromthis comparison that apply to all thecountries we analysed. They alsooffer guidance to other countries
in working towards the SDGs.

1. Guarantee high-quality, earlychildhood education and care
to all children
All children should be able to accesshigh-quality, age-appropriate, formal,
early childhood education and care,including those with disabilities
and special needs, and irrespectiveof their parents’ employment,
migration status or income.
Accessible and affordable centrebased childcare benefits children,
their families and societies.
It teaches children to play and learn
with their peers and allows parents
to achieve a better balance of workand family life. Early group learning
reduces educational inequalities by
preparing all children for primary

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education, regardless of their family
background.
Yet access to formal childcare
varies between and withincountries, even for the children
closest to starting primary school.
Household income and location
often act as barriers to access inthe EU. Comparable data for nonEuropean OECD countries arelacking, but national studies painta similar picture. When only somechildren are in high-quality centrebased childcare, existing inequality
due to family circumstances isentrenched rather than redressed.

2. Ensure that all children
achieve a good minimum levelof core skills
A substantial proportion of students
in primary and secondary school
fail to achieve a minimum level ofreading proficiency appropriate totheir grade and age. The true
figures are probably far greater thanshown in large-scale international
assessments, because some of themost vulnerable children in society
are missing from these schoolbased assessments.
Policy makers need to ensure thatno students fall so far behindthat they lack the skills toparticipate fully in society. Thereis no inevitable trade-off between
higher overall standards in reading
achievement and narrower gaps
between the lowest- and highestperforming students. Bringing thelowest achievers up does notnecessarily mean bringing thehighest achievers down.
To achieve competency in core
subjects, children need smoothtransitions between different stagesof their education. This allows themto build on their skills progressively.
Primary schools should be ready for

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all children, including those whohave missed out on preschool
learning. Secondary schools need
to offer an inclusive environment tochildren coming from diverse
primary schools.
There also needs to be a more
holistic emphasis on child wellbeing at school. We focus on
student achievement in thisReport Card but are aware that
other experiences at school, suchas bullying, can have a detrimental
effect on a child’s performance.

3. Reduce the impact ofsocio-economic inequalities
Children from disadvantaged
backgrounds often startcompulsory education with fewerskills. Schools can help close thesegaps. Yet certain features of school
systems may inadvertently widen
inequalities instead. Where children
are sorted into different streams
within schools, or go to different
schools altogether based on theiracademic performance, children
from less-privileged families tend
to be over-represented in the lower
tracks, with fewer opportunities in
the future. Grouping children by
their abilities is a long-standing
feature of many school systems.
There needs to be greaterawareness of its role in reinforcing
inequalities between children.
We found large inequalities
between schools. In many
countries, they are related to thesocio-economic composition ofchildren within schools. The
countries where children with asimilar family background are more
likely to study together tend tobe those where parental
background plays a greater role inchildren’s reading achievement.
This reinforces inequality. MoreS E C T I O N

children would have an opportunity
to do well in school if this type ofsegregation were reduced. One of
the aims of the UN Convention on
the Rights of the Child and theSDGs is that all children shouldhave an equal opportunity forhigh-quality education.
The degree to which socioeconomic background matters tostudent achievement is, admittedly,
an outcome of wider social andeconomic forces. Yet it is also amatter of political priorities anddecisions. Through a combinationof family allowances and public
services, rich countries can ensurethat all children have access to adecent breakfast, suitableequipment, and school events andenriching extra-curricular activities,
so that they are able to enjoy
learning, develop varied interests
and achieve their full potential.
This goes beyond education policy
into the realm of social policy.

4. Close the gender gaps
in achievement
International assessments showthat boys tend to score higher inmathematics than girls in mostcountries and do better in sciencein some countries. But everywhere
they do worse in reading. Policy
makers and educators need toensure equal engagement of boys
and girls in all core subjects, paying
attention to the gender mix ofteachers and challenging genderstereotypes every step of the way.
We need a better understanding of
how girls and boys respond todifferent types of assessment.

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countries. To study international
differences in the development ofeducational inequalities acrossdifferent stages of education,
we need more high-quality, crosscountry, comparable evidence.
Longitudinal studies that follow thesame children as they grow older
would be particularly valuable. To
understand the depth of educational
disadvantage, we need informationon all children, including those whoare missing from standard surveys.

6. Focus on equality, not justaverages
Policy and public debates should
also be more fully informed by theinternational surveys that are alreadyavailable, such as those used in thisreport. International comparisonsshould consider not just how
countries are faring in average
educational performance, but also
the amount of inequality among thestudents in each country. Greater
equality does not come at a cost to
average achievement. Both arenecessary to give all children afair start.

5. Produce better data
There is an old saying that whatgets measured gets done. We havefound numerous gaps in data
coverage and quality across rich

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ABBREVIATIONSInternational abbreviations (ISO)for countries and regions covered inReport Card 15

Abbreviations and acronyms used inReport Card 15

IrelandEU

IL

IsraelEurostatIS

Iceland

Statistical Office of
the European Union

Flanders (Belgium)

IT

Italy

ePIRLSElectronic (online) versionof the Progress in International
Reading Literacy Study

EU-SILCEU Statistics on Incomeand Living Conditions

ISO

International Standards
Organization

MCS

Millennium Cohort StudyNEPS

National Educational
Panel StudyOECD

Organisation for Economic
Co-operation and Development

PIRLS

Progress in the International
Reading Literacy StudyPISA

Programme for International
Student Assessment

SDG

Sustainable Development Goal

TIMSS

Trends in International
Mathematics and Science StudyAT

Austria

IE

AU

Australia

BE

Belgium

BE-VLG
BE-WAL

Wallonia (Belgium)

JP

Japan

BG

Bulgaria

KR

Republic of Korea

CA

CanadaLT

Lithuania

CH

Switzerland

LU

Luxembourg

CL

Chile

LV

LatviaCY

Cyprus

MT

Malta

CZ

Czech RepublicMX

MexicoDE

Germany

NL

Netherlands

DK

DenmarkNO

NorwayEE

EstoniaNZ

New Zealand

ES

Spain

PL

PolandFI

FinlandPT

Portugal

FR

FranceRO

Romania

GB

United Kingdom

SE

SwedenGB-ENGEngland (UK)SI

Slovenia

GB-NIR

Northern Ireland (UK)SK

Slovakia

GR

GreeceTR

TurkeyHR

Croatia

US

United States of America

HU

Hungary

European Union

UNESCO

United Nations Educational,
Scientific and Cultural
Organization

UNICEF

United Nations Children’s FundI N N O C E N T I

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5. European Commission/EACEA/Eurydice(2016). Compulsory Education in Europe –2016/17, Eurydice Facts and Figures,
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15. Mensah, F. and Kiernan, K. (2010).
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6. Akbari, E. and McCuaig, K. (2018).
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16. Bradbury, B., Corak, M., Waldfogel, J.
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7. MacDonald, D. and Friendly, M. (2017).
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17. Hadjar, A., Krolak-Schwerdt, S.,
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ACKNOWLEDGEMENTS

The Innocenti Report Card 15 was written
by a UNICEF Office of Research – Innocentiteam, composed of Zlata Bruckauf,
Yekaterina Chzhen, Jose Cuesta,
Anna Gromada and Gwyther Rees, under
the overall supervision of Sarah Cook,
Director. A panel of advisers and UNICEF
reviewers provided quality assurance.
Madelaine Drohan edited the Report Card.
Administrative support at the UNICEF Officeof Research – Innocenti was provided by
Amparo Barrera, Cinzia Iusco Bruschi,
Lisa Gastaldin, Laura Meucci andFlora Zecchi. Production was managed
by Sarah Marchant.
The full text and related materials canbe downloaded from the UNICEF Officeof Research – Innocenti website:www.unicef-irc.org

Authors
Zlata Bruckauf is Research and Evaluation
Specialist at UNICEF Mozambique. Prior tothis she led the work on inequality ofeducational outcomes for the Innocenti
Report Card 13 and the analysis ofchild-focused SDG indicators in educationand health for the Innocenti Report Card
14, at the UNICEF Office of Research –Innocenti. She holds a PhD in Comparative
Social Policy from Oxford University.
Yekaterina Chzhen is a Social andEconomic Policy Specialist at the UNICEF
Office of Research – Innocenti. She holds
a PhD from the University of York andpublishes on poverty, inequality and childwell-being in higher-income countries.
She co-edited Children of Austerity:
Impact of the Great Recession on Child
Poverty in Rich Countries (Oxford
University Press, 2017).
Jose Cuesta is Chief of Social andEconomic Policy at UNICEF Office of
Research – Innocenti. He has a PhD in
Economics from Oxford University andis an Affiliated Professor at Georgetown
University. He has published extensively
on poverty and inequality issues,
including the Poverty and Shared
Prosperity 2016 report.

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Anna Gromada is a Social and Economic
Policy consultant at UNICEF Office of
Research – Innocenti, a researcher at thePolish Academy of Sciences and a
co-founder of the Kalecki Foundation thinktank. Prior to this she collaborated with the
Chancellery of the President of Poland,Thomson Reuters and the Organisation
for Economic Co-operation andDevelopment (OECD).
Gwyther Rees is a Social and Economic
Policy consultant at UNICEF Office of
Research – Innocenti. He is also an
Associate Research Fellow at the
University of York, where he is Research
Director of Children’s Worlds, theInternational Survey of Children’s
Well-being. He has a PhD from Cardiff
University and a research backgroundin child protection and children’s
subjective well-being.

Dominic Richardson (Senior Education
Specialist, UNICEF Office of Research –Innocenti)
Jan Vandemoortele (Independent Adviser)
Jane Waldfogel (Professor of Social Work,
Columbia University)

UNICEF advisers
Prerna Banati (Chief, Programme andPlanning, UNICEF Office of Research –Innocenti)
Victor Cebotari (Consultant, UNICEF Officeof Research – Innocenti)
Laurence Chandy (Director of Data,
Research and Policy, UNICEF New York
Headquarters)
Sarah Crowe (Senior Communication
Specialist, UNICEF)

Advisory board

Despina Karamperidou (Consultant,
UNICEF Office of Research – Innocenti)

Fabrizio Bernardi (Professor of Sociology,
European University Institute)

Dale Rutstein (Chief, Communication Unit,
UNICEF Office of Research – Innocenti)

Francesca Borgonovi (Senior Analyst,
OECD Directorate of Education and Skills)

Juliana Zapata (Consultant, UNICEF Officeof Research – Innocenti)

Matt Brossard (Senior Adviser Education,
UNICEF New York Headquarters)
John Jerrim (Professor of Educationand Social Statistics, University College
London)Bergsteinn Jonsson (Executive Director,
UNICEF Iceland)
Jan Jonsson (Official Fellow, Nuffield
College)
Daniel Kelly (Education Specialist, UNICEF
New York Headquarters)
Ides Nicaise (Professor, Faculty ofPsychology and Education Sciences,
KU Leuven)
Kate Pickett (Professor of Epidemiology,
University of York)
Ilze Plavgo (PhD student, European
University Institute)

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Previous issues in this series:
Innocenti Report Card 1
A league table of child poverty in rich nations
Innocenti Report Card 2
A league table of child deaths by injury in rich nations
Innocenti Report Card 3
A league table of teenage births in rich nations
Innocenti Report Card 4
A league table of educational disadvantage in rich nations
Innocenti Report Card 5
A league table of child maltreatment deaths in rich nations
Innocenti Report Card 6
Child poverty in rich countries 2005
Innocenti Report Card 7
Child poverty in perspective: An overview of childwell-being in rich countries
Innocenti Report Card 8
The child care transition: A league table of early childhood
education and care in economically advanced countries
Innocenti Report Card 9
The children left behind: A league table of inequality inchild well-being in the world’s rich countries
Innocenti Report Card 10
Measuring child poverty: New league tables of childpoverty in the world’s rich countries
Innocenti Report Card 11
Child well-being in rich countries: A comparative overview
Innocenti Report Card 12Children of the recession: The impact of the economiccrisis on child well-being in rich countries
Innocenti Report Card 13
Fairness for children: A league table of inequality in childwell-being in rich countries
Innocenti Report Card 14
Building the Future: Children and the Sustainable
Development Goals in Rich Countries

Graphics: MCC, UK (mccdesign.com)
Printed by: Idea Web (ideawebsrl.it)

Innocenti Report Card 15, 2018
An Unfair Start:
Inequality in Children’s Educationin Rich Countries#UnfairStart

UNICEF Office of Research – Innocenti
Piazza SS. Annunziata, 1250122 Florence, Italy
Tel: +39 055 2033 0
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Print ISSN: 1605-7317
Online ISSN: 2519-108X© United Nations Children’s Fund (UNICEF)
October 2018

ISBN: 978-92-1-103303-8
eISBN: 978-92-1-047424-5

Sales no.: E.18.XX.2