UNICEF
Innocenti Report Card 13
Children in the Developed World

Fairness for Children
A league table of inequality in childwell-being in rich countries

Innocenti Report Card 13 was written by John Hudson and Stefan Kühner.
The UNICEF Office of Research – Innocenti would like to acknowledge
the generous support for Innocenti Report Card 13 provided by theGovernment of Italy.
Any part of this Innocenti Report Card may be freely reproduced using
the following reference:
UNICEF Office of Research (2016). ‘Fairness for Children: A league
table of inequality in child well-being in rich countries’, Innocenti
Report Card 13, 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 aresearch centre to support its advocacy for children worldwide and to
identify and research current and future areas of UNICEF’s work. The
prime objectives of the Office of Research – Innocenti are to improve
international understanding of issues relating to children’s rights, tohelp facilitate full implementation of the Convention on the Rights of
the Child, supporting advocacy worldwide. The Office aims to set out
a comprehensive framework for research and knowledge within theorganization, in support of its global programmes and policies. Throughstrengthening research partnerships with leading academic institutions
and development networks in both the North and the South, the Officeseeks to leverage additional resources and influence in support ofefforts towards policy reform in favour of children.
Publications produced by the Office are contributions to a global
debate on children and child rights issues and include a wide range of
opinions. For that reason, some publications may not necessarily reflect
UNICEF policies or approaches on some topics. The views expressed
are those of the authors and/or editors and are published in order tostimulate further dialogue on issues affecting children.

Cover photo © Blend Images / Alamy Stock Photo©United Nations Children’s Fund (UNICEF), April 2016
ISBN: 978 88 6522 045 0
eISBN: 978-92-1-057893-6

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Innocenti Report Card 13
Children in the Developed World

Fairness for Children
A league table of inequality in childwell-being in rich countries

S E C T I O N

1I N T R O D U C T I O N

SECTION 1
INTRODUCTION“In all actions concerning children, whether
undertaken by public or private social welfare
institutions, courts of law, administrative
authorities or legislative bodies, the best interestsof the child shall be a primary consideration.”– United Nations Convention on the Rights of the Child, 1989 (article 3)This Report Card presents an
overview of inequalities in childwell-being in 41 countries of theEuropean Union (EU) and theOrganisation for Economic
Co-operation and Development(OECD). It focuses on ‘bottom-end
inequality’ – the gap between
children at the bottom and thosein the middle – and addresses thequestion ‘how far behind arechildren being allowed to fall?’in income, education, health andlife satisfaction.

Why inequality?
With the gap between rich and poorat its highest level for some three
decades in most OECD countries,
there is now a renewed focus onquestions surrounding inequality.
While much political debate has
centred on the growing income of
the top 1 per cent, in many richcountries incomes below themedian have grown less quickly
than have those above the median.1

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Across the OECD, the risks ofpoverty have been shifting from theelderly towards youth since the1980s. These developments
accentuate the need to monitor
the well-being of the mostdisadvantaged children, but income
inequality also has far-reachingconsequences for society, harming
educational attainment, key healthoutcomes and even economic growth.2
A concern with fairness and social
justice requires us to consider
whether some members of society
are being left so far behind that it
unfairly affects their lives both now
and in the future.This Report Card
asks the same underlying question
as Report Card 9,3 which focused oninequality in child well-being, butuses the most recent data available
and includes more countries.

Inequality, fairness and children
Questions of fairness and social
justice have a special resonancewhen inequalities among children,

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rather than adults, are the focus
of attention.
Social inequalities among adults
may be justifiable if they havearisen through fair competition andunder conditions of equality ofopportunity. But when it comes tochildren, the social and economic
circumstances they face are beyond
their control, and so differences inmerit cannot reasonably be
advanced as justification forinequalities among them.
In addition, few dispute thatchildhood experiences have a
profound effect not only onchildren’s current lives, but also
on their future opportunities andprospects. Likewise, social andeconomic disadvantages in earlylife increase the risk of having lower
earnings, lower standards of healthand lower skills in adulthood. Thisin turn can perpetuate disadvantage
across generations.4 None of this is
the fault of the child.

S E C T I O NComparing bottom-end
inequality across rich countries
The league tables in this Report
Card rank countries according to
how far children at the bottom areallowed to fall behind their peers inincome, education, health and life
satisfaction. We also provide an
overall league table of inequality inchild well-being that summarizes
performance across all four ofthese dimensions.
The measures of inequality in theleague tables are put into context
through the use of indicators that
capture how many children in eachcountry have low income, low
educational achievement, poor
health or low levels of life
satisfaction. This offers a wider
picture of how far children’s rights
are being upheld in rich countries.
The league tables presented in
Section 2 compare countries on thebasis of how far children are being
allowed to fall behind. Sections 3,
4, 5 and 6 offer a more detailed
exploration of trends in inequality
affecting income, education, healthand life satisfaction, respectively.
Each of these sections also
considers the impacts of inequality
on child well-being. Section 7
returns to the general question of
fairness and inequality, considering
the extent to which child well-being
in rich countries is shaped bydeeply rooted social and economic
inequalities over which children
have no control. Section 8 presents
conclusions and recommendations.

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Box 1 Social justiceand fairness
The findings of Report Card 9 were presented as a “first attempt tomeasure nations by the standards of a ‘just society’ as defined by theAmerican political philosopher John Rawls”.i Though subject to muchdebate since its publication, Rawls’ ground-breaking analysis of justiceas fairness provides a lens through which our exploration of bottomend inequality over time can be viewed.
Rawls asked us to imagine an “original position” in which the overall
shape of society is debated before its creation. He then asked us toimagine that a “veil of ignorance” would prevent individuals fromknowing their position in the society being created. Through thisthought experiment, he effectively reframed the question ‘what doesa fair society look like?’ to become ‘what kind of society would
reasonable citizens consent to living in?’Rawls argued that a key principle to emerge from such a bargaining
process would be that people would agree that social and economic
inequalities could exist in a fair society, but only so far as they(i) emerged from fair conditions of equality of opportunity and (ii) wereto the greatest benefit of the least-advantaged members of society –which he termed the “difference principle”.ii In other words, in Rawls’
model inequalities in material living conditions are permissible if they
benefit all (e.g. by creating higher standards of living for everyone) andarise from a position of equality of opportunity that allows all a fairchance of succeeding.
In this Report Card the themes that Rawls identified are explored, butwith an exclusive focus on the position of children. Inequalities inchildren’s lives are examined in detail, as is the extent to which
inequality itself shapes outcomes for children. These issues are
considered alongside a concern with how far inequalities in child wellbeing are connected to social and economic inequalities over whichchildren have no control.
i
UNICEF (2010). ‘The Children Left Behind: A league table of inequality in childwell-being in the world’s rich countries’, Innocenti Report Card 9, UNICEF
Innocenti Research Centre, Florence (Box 3).
ii

Rawls, J. (1971). Theory of Justice, Harvard University Press, Cambridge, MA.

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SECTION 2
LEAGUE TABLES
League Table 1 Inequality in income
Rank

Relativeincome gap

CountryChild poverty rate (50% of the median)

1

Norway

37.00

4.5

2

Iceland

37.76

6.4

3

Finland

38.34

3.7

4

Denmark

39.54

4.8
6.3

5

Czech Republic

39.62

6

Switzerland

39.64

7

7

United Kingdom

39.94

9.3
5.7

8

Netherlands

40.64

9

Luxembourg

41.21

13

10

Ireland

41.49

6.9

11

Austria

41.87

9.6

12

Germany

43.11

7.2

13

France

43.95

9

14

Australia

44.75

9.3

15

Republic of Korea

45.74

8

16

Sweden

46.23

9.1

17

New Zealand

46.52

11

18

Cyprus

47.19

9.1

19

Slovenia

47.29

8.3

20

Malta

48.21

14.5

21

Hungary

48.34

15

22

Belgium

48.41

10.1

23

Poland

51.76

14.5

24

Canada

53.19

16.9

25

Slovakia

54.21

13.7

26

Croatia

54.59

14.8

27

Lithuania

54.81

17.8

28

Estonia

55.55

12.4

29

Turkey

57.07

22.8

30

United States

58.85

20

31

Chile

59.03

26.3

32

Latvia

59.66

16.3

33

Portugal

60.17

17.4

34

Japan

60.21

15.8

35

Italy

60.64

17.7

36

Spain

62.62

20.2

37

Israel

64.58

27.5

38

Greece

64.69

22.3

39

Mexico

65.00

24.6

40

Bulgaria

67.01

23.1

41

Romania

67.08

24.3

See data sources and notes on page 44.

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The four main league tables
presented in this Report Card rankrich countries on the basis ofbottom-end inequality in children’s
income, education, health and life
satisfaction. Each league tableprovides a snapshot of how far richcountries allow their mostdisadvantaged children to fallbehind the ‘average’ child. The
league tables are supplemented by
a fifth league table, which provides
a summary of the overall record
across these four areas. Each of
the main league tables puts its
measure of inequality into context,
using an indicator that captures
how many children fall in the verybottom of the distribution ofincome, educational achievement,
health and life satisfaction.
League Table 1 ranks countries on
the size of their relative income
gap. This measure of bottom-end
inequality captures how far thepoorest children are being allowed
to fall behind the ‘average’ child ineach country.
To provide context for the inequality
measure, League Table 1 also
displays the child poverty rate(measured as 50 per cent of thenational median) for each country.
More detail about these measures
is provided in the box ‘Interpretingthe data: League Table 1 – Income’.

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Key findings:

Figure 1 Relative income gap versus levels of poverty
Lower poverty»» The Scandinavian countries, withthe exception of (mid-ranking)Sweden, have the smallest
relative income gaps. In thesecountries, the disposable
household income of the child at
the 10th percentile is around 38
per cent lower than that of thechild at the middle of the income
distribution.

Child poverty rate

FI
DK NO
NL
CZ
DE
IE CH IS
KR
SI
FR
CY
UK
SE AU AT
BE
NZ
EE
JP
TT
ES

Higher poverty

2

RO

BG

SK
HR PL
LV
PT

LT

MT
HU

LU

CA

US

GR

»» In 19 of 41 rich countries the

TR

MX
IL

CL

Higher income gap

Lower income gap
Relative income gap

relative income gap exceeds 50
per cent: the child at the 10th
percentile has less than half thedisposable household income of
the child at the median.

»» In Bulgaria and Romania, theSources: see page 44 – League Table 1.

Interpreting the data: League Table 1 – Income

relative income gap is 67 per
cent, i.e. household income ofchildren at the 10th percentile
is 67 per cent lower than at
the median.

»» Income gaps in excess of 60 per
Calculations of bottom-end income inequality for children, also
referred to as the relative income gap, are based on the disposable
incomes of households with children aged 0 to 17 (after adding
benefits, deducting taxes, and making an adjustment for the different
sizes and compositions of households).
To measure inequality at the bottom end of the distribution, thehousehold income of the child at the 50th percentile (the median)is compared with the household income of the child at the 10th
percentile (i.e. poorer than 90 per cent of children); the gap between
the two, reported as a percentage of the median, provides us with ameasure of how far behind the poorest children are being allowed
to fall.
For example, in Norway, the household income of the child at the 10th
percentile is 37 per cent lower than that of the child in the middle ofthe income distribution – the median.

cent are also found in the larger
southern European countries(Greece, Italy, Portugal andSpain), as well as in Israel, Japanand Mexico.

»» Relative income gaps and levelsof poverty are closely related(Figure 1): higher levels ofpoverty tend to be found incountries with higher income
gaps (bottom-left quadrant of
Figure 1) and lower levels ofpoverty in countries with lower
income gaps.

Child poverty is measured as the percentage of children inhouseholds with incomes below 50 per cent of national medianincome (after taking taxes and benefits into account and adjusting forfamily size and composition).
The league table uses survey data for 2013 (or the most recent year available).
See data sources on page 44.

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Key findings:

League Table 2 Inequality in education»» The two countries with the lowest

Rank

Country

Achievement
gap

Share of children below proficiency
level 2 in all three subjects

1

Chile

1.92

24.6

2

Romania

1.77

24.0

3

Estonia

1.59

3.2

4

Latvia

1.19

8.3

5

Croatia

0.88

11.7

6

Poland

0.79

5.7

7

Lithuania

0.67

12.1

8

Denmark

0.66

9.3

9

Ireland

0.62

6.8

10

United States

0.54

12.2

11

Slovenia

0.46

9.9

12

Spain

0.36

10.4

13

Czech Republic

0.30

8.9

14

Canada

0.28

6.2

15

Republic of Korea

0.22

4.4

16

Finland

0.18

5.3

17

Hungary

0.15

13.1

18

Greece

0.08

15.7

19

Portugal

-0.10

12.6

20

Switzerland

-0.12

7.5

21

Austria

-0.17

10.7

22

Italy

-0.26

11.9

23

Norway

-0.28

11.0

24

Australia

-0.29

9.1

25

United Kingdom

-0.40

11.2

26

Iceland

-0.46

13.6

27

Japan

-0.48

5.5

28

Germany

-0.56

8.8

29

Sweden

-0.61

15.0

30

Netherlands

-0.70

8.6

31

New Zealand

-0.94

11.1

32

Bulgaria

-0.97

28.6

33

Luxembourg

-0.98

14.4

34

Slovakia

-1.03

18.8

35

France

-1.36

12.7

36

Belgium

-1.39

11.5

37

Israel

-1.96

18.5

Mexico2.19

31.0

Turkey1.76

15.6

See data sources and notes on page 44.

League Table 2 ranks countries
according to their achievement gap in
the OECD’s Programme for International
Student Assessment (PISA) tests. Thismeasure captures how far low‑achieving
students are allowed to fall behind the‘average’ child in reading, maths andscience literacy at the age of 15.

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League Table 2 also displays the
proportion of students performing
at below PISA’s proficiency level 2
in all three subjects.
More detail about these measures isprovided in the box ‘Interpreting thedata: League Table 2 – Education’.

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achievement gap, Chile andRomania, have a very highproportion of students falling
below proficiency level 2 in all
three subjects. This means that,
although fewer children are left
behind the ‘average’ child inthese countries, a higher
proportion of children lack basic
skills and competencies.

»» Two high-income countries,
Belgium and France, are found at
the bottom of the league table,with very large achievement gaps.

»» Across rich countries, theproportion of 15-year-olds falling
below proficiency level 2 in all
three subjects is as low as 3–5 percent in Estonia, Finland and Korea,
and as high as 24–28 per cent in
Bulgaria, Chile and Romania.

»» Figure 2 depicts the relationshipbetween the achievement gap andthe proportion of children below
proficiency level 2 in all threesubjects. Countries in the upperright quadrant are the best
performers, as they combine low
achievement gaps with a low
proportion of children falling
below proficiency level 2 in all
three subjects; countries in thebottom-left corner are the worst
performers, displaying both highachievement gaps and a highabsolute proportion of children
below proficiency. It highlights
the fact that minimizing theachievement gap does not require
countries to ‘trade off’ equality
against standards. In Estonia,
Ireland, Latvia and Poland, lowbottom-end inequality in
educational achievement iscombined with a low proportionof children scoring below

S E C T I O N»» Estonia is the best-performing
country in terms of combining
good outcomes on bothmeasures. Yet even here, theachievement gap in reading
equates to 2.5 years of schoolinglost for the child at the 10th
percentile, compared with the‘average’ child.

Fewer low performers

achievement gap can exist
alongside a comparatively large
proportion of students achieving
below proficiency level 2 in all
three subjects. This is the case in
Bulgaria, Israel, Luxembourg,
Slovakia and Sweden (bottom-leftquadrant).

More low performers»» On the other hand, a high

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Figure 2 Achievement gap and educational disadvantage
Share of low performers in all three subjects

proficiency level 2 in all threesubjects.

2

FI

JP
NL
BE
FR

NZ
LU

IL

CH

EE

KR
CA

DE
CZ
AU
SI
NO
ES
AT
UK
OECD
IT
US
PT
HU
IS
SE
GR

IE

PL
LV

DK
HR

LT

SK

RO

CL

BG

Higher achievement gap

Lower achievement gap
Achievement gap

Source: PISA 2012. See page 44 – League Table 2.
Note: Mexico and Turkey are excluded.

Interpreting the data: League Table 2 – Education

The OECD’s PISA measures the competence ofstudents aged 15 in maths, reading and science
literacy. Data from the most recent survey, conducted
in 2012, are used in League Table 2.
The educational achievement gap is measured as the
PISA test-score point difference between students at
the median and the 10th percentile.
In order to allow achievement gaps for the threesubjects to be combined in a single measure, in
League Table 2 the score-point differences between
the median and the 10th percentile in each subject
are converted into z-scores, which are then averaged
across subjects to provide an overall achievement gap
for each country. Z-scores measure the standardized
distance of any given value from the group average.
Positive figures above 0.5 represent a score that is
above the OECD average; negative figures below -0.5
indicate a score that is below average; and figures
between -0.5 and 0.5 are considered close enough to
be indistinguishable from the average.

For example, in Chile the average z-score across thethree subjects is 1.92 standard deviations above theOECD average.
PISA also maps test scores against six levels ofachievement that capture milestones related to key‘aspects’ of each subject that are definedindependently by experts in the field.
PISA defines low academic performance as a scorethat is below the threshold of proficiency level 2 ineach subject.
League Table 2 provides information on the proportionof students in each country who fall below proficiency
level 2 for all three subjects. Low performance at age
15 in all three subjects is a proxy for profoundeducational disadvantage.
In Section 4 we analyse the raw PISA test scores(rather than the z-scores) for reading. A difference of
41 points corresponds to the equivalent ofapproximately one year of formal schooling.

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League Table 3 Inequality in health
Rank

Country

Relative
health gap

One or more health complaints
every day

1

Austria

23.64

17.7

2

Germany

24.76

19.6

3

Switzerland

24.95

16.3

4

Norway

25.15

14.9

5

Denmark

25.50

17.6

6

Finland

25.89

15.0

7

Portugal

26.39

17.7

8

Netherlands

26.74

19.9

9

Czech Republic

26.84

25.3

10

Spain

27.31

23.9

11

Greece

27.37

27.9

12

Croatia

27.59

25.7

13

Estonia

27.65

23.8

14

United States

27.98

28.2

15

Belgium

28.14

23.8

16

Slovenia

28.29

18.7

17

Latvia

28.61

23.3

18

Hungary

28.79

22.2

19

United Kingdom

28.87

21.4

20

Ireland

28.90

21.0

21

Slovakia

28.96

23.8

22

Sweden

29.08

19.1

23

France

29.18

30.7

24

Canada

29.27

22.6

25

Lithuania

29.31

23.0

26

Bulgaria

29.39

30.6

27

Australia

29.86

21.8

28

Italy

30.11

30.5

29

Luxembourg

30.27

24.1

30

Malta

30.56

30.7

31

Iceland

31.08

22.6

32

Romania

33.95

31.2

33

Poland

34.05

27.4

34

Turkey

34.54

53.3

35

Israel

38.88

29.7

League Table 3 ranks countries interms of the size of the relative gap
in children’s self-reported healthsymptoms. For each country, therelative gap compares a child withfrequent reporting of healthsymptoms and an ‘average’ child at
the median of the health scale, withthe gap measured as the difference
between the two calculated as ashare of the median. This captures
the extent to which children at thebottom are allowed to fall behindthe ‘average’ child in health.
League Table 3 also displays the
proportion of children who report
one or more health symptoms
every day. This indicates the
proportion of children with poor
self-reported health in each country.
More detail about these measures
is provided in the box ‘Interpretingthe data: League Table 3 – Health’.
Key findings:»» The average relative gap inchildren’s self-reported healthsymptoms is 29 per cent acrossthe 35 countries examined.

»» The smallest relative health gaps
are found in Austria (23.6 percent), Germany (24.8 per cent)and Switzerland (25 per cent).
Denmark, Finland and Norway
also have comparatively small
gaps in self-reported health.

»» The largest relative health gaps

See data sources and notes on page 44.

are found in Israel (38.9 per cent),
Turkey (34.5 per cent) and
Poland (34.1 per cent).

»» More than half of children in
Turkey and around a third ofchildren in Bulgaria, France,
Israel, Italy, Malta and Romania
report one or more healthsymptoms a day.

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Fewer complaints

Figure 3 Relative health gap and daily health complaints

One or more health complaints every day

terms of their performance onbottom-end inequality andabsolute frequency of healthcomplaints. Countries in the topright quadrant perform better
than average on both counts,
while countries in the bottom-leftquadrant perform worse than
average on both measures. Only
Turkey shows both high bottomend inequality and highfrequency of reported healthcomplaints (bottom-leftquadrant).

PL

IL

RO

More complaints»» Figure 3 positions countries in

2

FI NO
CH
PT DK
SE IE SIDENL
AU CA UK
HUBE ESIS
LV
LTLU
SK EE HR CZ
GR
BG US
MT
FR
IT

AT

TR

Higher health gap

Lower health gap
Relative health gap

Source: HBSC 2014. See page 44 – League Table 3.
Note: data for 2010 used for Israel, Turkey and the United States.

Interpreting the data: League Table 3 – Health

Data from the 2013/2014 wave of the HealthBehaviour in School-aged Children (HBSC) study arereported in League Table 3.
This table ranks countries on the basis of bottomend inequality in self-reported health symptoms.
Students aged 11, 13 and 15 were asked how often
in the previous six months they had experienced thefollowing psychosomatic symptoms: headache;
stomach ache; backache; feeling low; irritability or
bad temper; feeling nervous; difficulties in getting tosleep; and feeling dizzy. The response options were“about every day”, “more than once a week”, “about
every week”, “about every month”, “rarely or never”.
These responses are summed to produce acomposite scale that captures the frequency of selfreported health complaints. It ranges from 0 to 32,
where 0 corresponds to frequent occurrence of alleight symptoms and 32 refers to no healthcomplaints at all.
Using this scale, for each country the relative healthgap is computed by comparing a child with relatively

frequent health complaints (represented by themean of values below the median) to the frequency
of complaints recorded by the ‘average’ child(represented by the median itself), with the gap
measured as the difference between the two
calculated as a share of the median. This indicatorshows how far children at the bottom are allowed tofall behind the ‘average’ child in each country.
For example, in Austria the health score for children
at the bottom of the distribution is 23.6 per centlower than that of the child at the middle.
The relative health gap is supplemented by the
proportion of children in each country who report
one or more health complaints every day – anindication of absolute severity in health symptoms.
The HBSC survey includes a wide range of healthrelated indicators. In Section 5 we not only explore
self-reported health symptoms data in more detail,but also examine data on key health behaviours,
such as diet and exercise.

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League Table 4 Inequality in life satisfaction
Rank

Country

Relative life
satisfaction gap

Life satisfaction at 4 or lower out of 10

1

Netherlands

24.03

4.4

2

Australia

24.34

4.5

3

Denmark

25.12

5.7

4

Greece

25.72

4.5

5

Romania

26.06

4.8

6

Latvia

26.09

6.4

7

Switzerland

26.32

5.4

8

Norway

26.35

4.5

9

Austria

26.90

5.2

10

Estonia

26.95

5.3

11

Finland

27.01

5.7

12

Slovenia

27.21

5.6

13

Ireland

27.38

6.9

14

Malta

27.61

5.7

15

Hungary

27.86

6.3

16

Bulgaria

27.90

5.0

17

Sweden

27.98

8.2

18

Portugal

28.03

6.0

19

Iceland

28.38

6.7

20

United Kingdom

28.42

7.4

21

United States

28.67

7.3

22

Italy

28.80

8.0

23

Croatia

29.13

5.0

24

Spain

29.23

5.6

25

Canada

29.37

8.6

26

Slovakia

29.41

7.0

27

Lithuania

29.44

5.4

28

France

29.56

8.5

29

Germany

29.58

8.4

30

Belgium

29.96

9.6

31

Israel

30.01

7.7

32

Luxembourg

30.04

8.2

33

Poland

31.11

10.0

34

Czech Republic

31.50

8.6

35

Turkey

35.95

15.3

See data sources and notes on page 44.

League Table 4 ranks countries on
the size of the relative life
satisfaction gap for children. Thismeasure indicates how far thosewith the lowest levels of life
satisfaction fall behind their peers.
League Table 4 also displays the
proportion of children with very low
overall levels of life satisfaction ineach country – i.e. those reporting
4 or less on a scale from 0 to 10.
More detail about these measures isprovided in the box ‘Interpreting thedata: League Table 4 – Life satisfaction’.
Key findings:»» The ‘average’ child reports life
satisfaction of 8 out of 10 in almost
all countries, but children at thelower end of the life satisfaction
distribution fall far behind theirpeers – typically between 2.5 and3 points out of 10 lower thanthe median.

»» Children at the bottom fall furthest
behind in Turkey, where the relative
life satisfaction gap is 36 per cent.
Gaps in excess of 30 per cent arealso found in Poland and theCzech Republic.

»» The smallest relative life
satisfaction gap (24 per cent) isfound in the Netherlands, while
Australia and Denmark also havecomparatively low relative gapsof around 25 per cent. In otherwords, in Denmark the mean life
satisfaction score of children in thebottom half of the distribution is
75 per cent of the score of a childat the median.

»» There are important cross-national
differences in the proportion ofchildren who rate their life
satisfaction at the very low level of
4 out of 10 or below. The size of
this group ranges from 4.4 per centin the Netherlands to 15.3 per centin Turkey.
1 0

I N N O C E N T I

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C A R D

1 3

S E C T I O N

L E A G U E

T A B L E S

Higher life satisfaction

Figure 4 Relative life satisfaction gap and low life satisfaction

CZ
PL

Lower life satisfactionof four quadrants where, as
before, those in the top-rightquadrant perform better than
average both in bottom-end
inequality and in the proportionof children reporting very low life
satisfaction. For life satisfaction,
the relationship between the twois quite strong, as most countries
are either in the top-right or thebottom-left quadrants. Countries
with lower bottom-end inequality
also tend to have a lower shareof children who rate their life
satisfaction at 4 out of 10 or
below, and vice versa – a larger
proportion of those in countries
with higher bottom-end
inequality assign life satisfaction
a low score.

Life satisfaction at 4 or less out of 10»» Figure 4 places countries in one

2

AU
NO
GR
NL
HR
AT
BG
RO
LT
MT SI EE CH
ES
DK
FI
PT
LV
IS HU
IE
SK US
UK
IL
DE IT
LU
SE
FR CA
BE

TR

Higher life satisfaction gap

Lower life satisfaction gap
Relative life satisfaction gap

Source: HBSC 2014. See page 44 – League Table 4.
Note: data for 2010 used for Israel, Turkey and the United States.

Interpreting the data: League Table 4 – Life satisfaction

Data from the 2013/2014 [see page 44] wave of the
Health Behaviour in School-aged Children (HBSC)
study are reported in League Table 4.
The life satisfaction scores are based on children’s
own ratings of their life satisfaction on a scale of 0(“the worst possible life for you”) to 10 (“the best
possible life for you”).
For each country, the relative life satisfaction gap isthe difference between mean life satisfaction of achild with relatively low life satisfaction (represented
by the mean of values below the median) and thelife satisfaction of the ‘average’ child (represented by
the median itself), with the gap measured as thedifference between the two calculated as a share of
the median. This indicates how far those withrelatively low levels of life satisfaction have fallen
behind their peers.
For example, in the Netherlands the life satisfaction
score for children at the bottom is 24 per cent lower
than that for children in the middle.
League Table 4 also reports the proportion ofchildren in each country rating their life satisfaction
at 4 out of 10 or below. This allows us to assess theprevalence of very low levels of life satisfaction ineach country.

I N N O C E N T I

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1 3

1 1

S E C T I O N

2L E A G U E

T A B L E S

League Table 5 Average rank across all dimensions of inequality
Rank

Country

IncomeEducation

HealthLife satisfaction

Missing indicators

1

Denmark

4

8

5

3

0

2=

Finland

3

16

6

11

0

2=

Norway

1

23

4

8

0

2=

Switzerland

6

20

3

7

0

5

Austria

11

21

1

9

0

6

Netherlands

8

30

8

1

0

7

Ireland

10

9

20

13

0

8

Estonia

28

3

13

10

0

9

Slovenia

19

11

16

12

0

10

Latvia

32

4

17

6

0

11

Czech Republic

5

13

9

34

0

12

Croatia

26

5

12

23

0

13

Australia

14

24

27

2

0

14=

Germany

12

28

2

29

0

14=

Greece

38

18

11

4

0

14=

Hungary

21

17

18

15

0

14=

United Kingdom

7

25

19

20

0

18

United States

30

10

14

21

0

19

Portugal

33

19

7

18

0

20

Iceland

2

26

31

19

0

21

Romania

41

2

32

5

0

22

Spain

36

12

10

24

0

23

Sweden

16

29

22

17

0

24

Malta

20

30

14

1

25

Lithuania

27

7

25

27

0

26

Canada

24

14

24

25

0

27

Poland

23

6

33

33

0

28

France

13

35

23

28

0

29=

Belgium

22

36

15

30

0

29=

Luxembourg

9

33

29

32

0

31

Slovakia

25

34

21

26

0

32

Italy

35

22

28

22

0

33

Bulgaria

40

32

26

16

0

34

Turkey

29

34

35

1

35

Israel

37

37

35

31

-

Republic of Korea

15

15

2

-

Chile

31

1

2

-

New Zealand

17

31

2

-

Japan

34

27

2

-

Cyprus18

3-

Mexico39

3

n.a

top third

middle third

See data sources and notes on page 44.

1 2

I N N O C E N T I

R E P O R T

C A R D

1 3

bottom third

two or more indicators missing0S E C T I O N

League Table 5 summarizes eachcountry’s overall record for bottomend inequality in child well-being. It
displays each country’s rank in theincome, education, health and life
satisfaction league tables, andprovides an overall rank based onthat country’s average position
across each of the four previous
league tables.
Countries lacking indicators for two
or more domains of child well-being
are excluded from the overall
ranking, but are displayed at the endof the league table for reference.
Key findings:»» Denmark is at the top of theoverall league table. It hascomparatively low bottom-end
inequality in each of the fourdomains of child well-being.
Indeed it is the only country torank in the top third in all four
league tables. Denmark’s lowest
ranking is eighth in education.

»» Finland, Norway and Switzerland
share second place in the overall
league table. They rank in the top
third in each domain, except
education.

»» Israel and Turkey rank lowest in
the overall league table. They2

L E A G U E

T A B L E S

have comparatively high bottomend inequality in each of the fourdomains of child well-being forwhich they have valid data.

»» Some of the richest countries in
the world are placed in thebottom third of the overall league
table, including three of theGroup of Seven countries:
Canada (26th), France (28th) and
Italy (32nd). The country in theEuropean Union with the highest
income per person, Luxembourg,ranks 29th.

»» Report Card 9 examined bottomend inequality before theeconomic crisis. A comparison of
the overall league tables in the
two Report Cards suggests that
France, Iceland and Sweden haveseen their comparative positions
decline in recent years: France,
previously towards the middle ofthe overall table, now ranks inthe bottom third; while Icelandand Sweden, previously towards
the top of the overall league
table, now sit marginally above
the bottom third. However, adirect comparison between the
two Report Cards cannot bemade as somewhat different
measures are used.

I N N O C E N T I

R E P O R T

C A R D

1 3

1 3

S E C T I O N

3I N C O M E

SECTION 3
INCOME

Income gaps have widened in
the majority of rich countries
How has income inequality evolved
over the past few years? Different
pathways can explain changes in
the relative income gap over time.
For example, if incomes at thebottom of the distribution growfaster than in the middle, the result
is a doubly positive scenario ofoverall improvements coupled withdeclines in bottom-end inequality.
Conversely, if the 10th percentile
decreases faster than the median,inequality widens and the poorest
children are left even further behind.

four – the Czech Republic,
Finland, Korea and Switzerland –was that because of a ‘positive’closing of the gap: the incomesof both the 10th percentile andthe median grew, but those of the10th percentile increased faster.

»» In the second group of countries,
the relative gap shrank because
the median income declined,
while the 10th percentile either
decreased more slowly (Ireland,
Lithuania and Luxembourg),
remained unchanged (the United
Kingdom and the United States)
or even increased (Mexico).

Countries are placed into fivegroups in Figure 5 to clarify thereasons for changes in inequality
between 2008 and 2013. Thesepathways are based on ‘real’changes in incomes over time,i.e. adjusting for inflation, although
this does not affect the relative
gap itself.

»» In Canada, France, Israel,

Bottom-end income inequality has
increased in over half of the richcountries analysed: 19 of 37 saw anincrease in the relative child income
gap of at least 1 percentage point
between 2008 and 2013. Two-thirdsof these countries saw a substantial
increase in inequality, exceeding
2 percentage points.

»» The largest increases in inequality

Figure 5 shows that:»» Of the 10 countries where therelative income gap narrowed byat least 2 percentage points
between 2008 and 2013, in only

1 4

I N N O C E N T I

R E P O R T

Slovakia and Sweden, the relative
income gap increased, as themedian income grew or at least
remained unchanged, while the10th percentile income improved
more slowly or even decreased,thus widening the gap between
the bottom and the middle.
– of at least 5 percentage points– occurred in four southern
European countries (Greece, Italy,
Portugal and Spain) and threeeastern European countries(Hungary, Slovakia and Slovenia).
In all these countries, except
Slovakia, children’s medianhousehold incomes fell, but the10th percentile income
decreased even faster, leaving
the poorest children increasingly
lagging behind.

C A R D

1 3

Social transfers matterLabour markets play a significant
role in shaping the income ofhouseholds with children –particularly following an economiccrisis, when rates of unemployment
and underemployment rise. Children
living in jobless households areoverrepresented in the bottom
income decile in all European
countries. In Bulgaria, over 75 percent of children in the poorest
decile live in a jobless household,while that is the case for over 60
per cent in Belgium, Greece,
Hungary, Ireland and Slovakia.
The comparison of pre- and posttransfer incomes for European
countries shown in Figure 6
underlines the fact that socialtransfers also play a role in
reducing relative income gaps
among children in rich countries.
Indeed, in all these countries
income inequality is higher before
social transfers than after, but thedegree to which social transfers
reduce the relative income gap
varies considerably across Europe.
In Ireland and the United Kingdom,social transfers nearly halve therelative income gap. Indeed,without significant social transfers,
the income gaps in these twocountries would be among thehighest in Europe. In othercountries, particularly Bulgaria,
Greece, Italy and Portugal, the preand post-transfer income gaps arevery similar. These are countries

S E C T I O N

3I N C O M E

Figure 5 Change in income inequality
Country

Relativeincomegap 2008

Relativeincomegap 2013

Change(2008–2013)

Countries in which the 10th percentile increased faster than the medianwith some of the highest levelsof bottom-end inequality inthe comparison.

Higher income gaps, higher
levels of poverty anddeprivation
An examination of inequality inchildren’s income alongsidemonetary child poverty and material
deprivation rates provides a fuller
picture of changes in children’s
living standards. As noted in
Section 2, the relative income gap
and child poverty are closely
associated: countries with higher
bottom-end income inequality tend
to have higher child poverty (andvice versa, lower bottom-end
income inequality tends to equate
to lower child poverty). However,relative income statistics do notnecessarily convey what it means
to live on a low income in a richcountry. Analysis of material
deprivation can help us better
understand the situation ofchildren at the bottom end of theincome distribution.
Children are considered materiallydeprived when their household
cannot afford three or more out ofnine items considered necessary
for an adequate life: 1) to face
unexpected expenses; 2) to afforda one-week annual holiday awayfrom home; 3) to avoid arrears in
rent, mortgage and utility bills; 4) tohave a meal with meat or proteins
every second day; 5) to keep thehome adequately heated; 6) tohave a washing machine; 7) to havea colour TV; 8) to have a telephone;

Republic of Korea

51.1

45.7

-5.4

Switzerland

42.4

39.6

-2.8

Czech Republic

42.1

39.6

-2.5

Finland

40.5

38.3

-2.2

Countries in which the 10th percentile decreased more slowly than the median
United Kingdom

48.1

39.9

-8.2

Ireland

46.7

41.5

-5.2

Luxembourg

45.5

41.2

-4.3

Mexico

68.4

65.0

-3.4

United States

61.1

58.9

-2.2

Lithuania

56.9

54.8

-2.1

Countries in which the relative gap remained stable (+/-2pp)
Australia

46.5

44.7

-1.8

Iceland

39.2

37.8

-1.4

Latvia

60.9

59.7

-1.2

New Zealand

47.6

46.5

-1.1

Austria

42.7

41.9

-0.8

Norway

36.6

37.0

0.4

Belgium

47.9

48.4

0.5

Germany

42.6

43.1

0.5

Denmark

38.5

39.5

1.0

Poland

50.7

51.8

1.1

Netherlands

39.4

40.6

1.2

Bulgaria

65.7

67.0

1.3

Romania

65.6

67.1

1.5

Malta

46.5

48.2

1.7

Countries in which the 10th percentile increased more slowly than the medianFrance

41.4

43.9

2.5

Canada

50.3

53.2

2.9

Israel

61.6

64.6

3.0

Sweden

41.4

46.2

4.8

Slovakia

46.2

54.2

8.0

Countries in which the 10th percentile decreased faster than the median
Estonia

52.7

55.5

2.8

Cyprus

42.4

47.2

4.8

Portugal

54.8

60.2

5.4

Hungary

42.6

48.3

5.7

Slovenia

40.7

47.3

6.6

Spain

55.9

62.6

6.7

Italy

52.6

60.6

8.0

Greece

55.6

64.7

9.1

Source: EU-SILC 2008–2013.
Notes: Canada and the United States, 2007–2013; Israel, 2007–2012; Mexico, 2008–2012.
There was a break in time series in Canada, Spain and the United Kingdom.
No trend data available for Croatia, Turkey, Chile and Japan.

I N N O C E N T I

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1 5

S E C T I O N

3I N C O M E

Figure 6 Income inequality and social transfers
Country

Relativeincome gap
pre-transfers

Relativeincome gap
post-transfers

Percentage of gap reduced bysocial transfers

United Kingdom

77.4

39.9

48.4

Ireland

76.3

41.5

45.6

Belgium

82.2

48.4

41.1

Iceland

63.6

37.8

40.6

Austria

68.9

41.9

39.2

Norway

60.5

37.0

38.8

Hungary

76.1

48.3

36.5

France

68.5

43.9

35.9

Denmark

61.4

39.5

35.6

Finland

58.2

38.3

34.1

Luxembourg

61.3

41.2

32.8

Sweden

67.7

46.2

31.7

Germany

62.9

43.1

31.5

Malta

68.1

48.2

29.2

Netherlands

56.3

40.6

27.8

Lithuania

75.2

54.8

27.1

Slovenia

63.0

47.3

25.0

Croatia

68.8

54.6

20.6

Switzerland

48.9

39.6

19.0

Estonia

67.9

55.5

18.2

Spain

75.2

62.6

16.7

Poland

61.7

51.8

16.2

Bulgaria

78.3

67.0

14.5

Czech Republic

46.3

39.6

14.4

Latvia

69.0

59.7

13.5

Cyprus

54.5

47.2

13.4

Slovakia

62.3

54.2

13.0

Romania

75.9

67.1

11.6

Italy

64.5

60.6

6.0

Portugal

62.5

60.2

3.6

Greece

66.3

64.7

2.4

9) to have a personal car. Althoughnational income plays a role inshaping the levels of material
deprivation, across Europe there is astrong association between relative
income gaps and material deprivation
in households with children:countries with higher bottom-end
income inequality tend also to havehigher material deprivation.5

Figure 7 shows that in all European
countries children in the bottom
income decile are more likely to bematerially deprived than the childpopulation as a whole. In Bulgaria,
Hungary and Romania, over 90 per
cent of children in the bottom
income decile live in materiallydeprived households.

Source: EU-SILC 2013.

1 6

I N N O C E N T I

R E P O R T

C A R D

1 3

Lower income inequality,
higher child well-being
How is bottom-end income
inequality related to overall childwell-being? Figure 8 plots a revised
version of the multi-dimensionalchild well-being index presented inReport Card 11 (2013) against
relative income gaps.6 Countries
with higher income gaps tend tohave lower levels of overall childwell-being.
The evidence presented here
shows that large relative income
gaps are not inevitable, that policy
makers have tools at their disposalthat are effective in reducing
income inequality, and that smaller
income gaps are better for all
children, insofar as they areassociated with higher levels of
overall child well-being. While
policy makers face undoubted
challenges in balancing budgets
in the aftermath of the economiccrisis, the arguments in favour ofprioritizing policies that prevent theincomes of the poorest householdswith children from falling behind
are compelling.

S E C T I O N

3I N C O M E

Figure 7 Percentage of children living in deprived households
100
90
80

Per cent

70
60
50
40
30
20
10

Children in the poorest income decile

Bulgaria

Hungary

GreeceRomania

LatviaSlovakia

CyprusPortugal

Croatia

Lithuania

Italy

Malta

Spain

Belgium

PolandCzech Republic

FranceEstonia

Ireland

Slovenia

Denmark

United Kingdom

FinlandGermany

SwedenNetherlands

Austria

NorwayIceland

Luxembourg

Switzerland0

All children

Source: EU-SILC 2013.

Figure 8 Relative child income gap and overall child well-being (2009)
2
NL

1

IS

NO

Child well-being

DK

SE

FI
SI

CY
CZ

0

HU

DE
CH
IE FR
NZ
MT

AT

JP

AU
LU BE
ES

PT

UK
CA
EE
SK PL TT

-1

GR
US

LT

-2

LV

RO

BG

-3
30

40

50

60

70

Relative income gap
R-squared=0.60
Source: Bradshaw, J. (2015). ‘Child poverty and child well-being in international perspective’, in
E. Fernandez, A. Zeira, T. Vecchiato and C. Canali (eds), Theoretical and Empirical Insights into
Child and Family Poverty, Springer International, Cham, Switzerland, pp.59–70; EU-SILC 2009.

I N N O C E N T I

R E P O R T

C A R D

1 3

1 7

S E C T I O N

4E D U C A T I O N

SECTION 4
EDUCATION

Inequality in educational
achievement narrowed in the
majority of the countries

The main pathways distinguished in
Figure 9 are:

Whether or not inequality has
declined in recent years is an
important question. But
understanding how theachievement gaps have alteredindicates how far educational
disadvantage and low achievement
have been addressed. For example,
a closing of the achievement gap
can result from children at thelower end being ‘lifted up’, so that
their achievement level is closer tothe average standard. However, it
may also be the result of falling
average achievement, alongsideconstant (or even declining)achievement among the children at
the bottom end of the distribution.

inequality while improving
median test scores. The positive
news is that 20 out of the 38
countries fell into this category,with the largest improvements inChile, the Czech Republic,
Germany and Mexico, although
the median test scores in the
Czech Republic and Mexico
remain low compared with othercountries. Belgium and Germany
show large improvements, butwith higher median test scores.

Figure 9 details changes ininequality in PISA test scores forreading between 2006 and 2012.7
It shows that the majority ofcountries display a positive trend interms of reducing the achievement
gap in reading. Countries areplaced into five groups, depending
on how their inequality haschanged. We are particularlyinterested in cases where both themedian improved and theachievement gap narrowed, as thisis a ‘win-win’ scenario of overall
improvement coupled with adecline in inequality at thelower end.

1 8

I N N O C E N T I

R E P O R T»» Countries that narrowed»» Countries that saw a decrease
in inequality but with a fall in
median test scores. This typeof trajectory is only seen in
Canada, where a notable decline
in lower-end inequality occurs inpart because of a decline inoverall achievement.

»» Countries that saw an increase ininequality alongside increased
median test scores. Only Bulgaria
displays this trend; low achievers
have been allowed to fall evenfurther behind.

»» Countries where bottom-end
inequality increased alongside afall in median test scores. This
type of downward trajectory is
the most worrying – and not very
common in reading. Two highincome countries fall into thisgroup: Finland and Sweden.

C A R D

1 3

Many countries reduced
absolute educational
disadvantage
In League Table 2, measures of therelative achievement gap were
supplemented by an indicator of
absolute educational disadvantage,
measured as all children who fallunder the PISA threshold ofproficiency level 2 in all threesubjects. Across the OECD
countries in 2012, 28 per cent of
15-year-olds fell below proficiency
level 2 in at least one of the threesubjects, and 11.6 per cent scoredbelow level 2 in all three subjects(Figure 10). Children who
underachieve in all three subjects
are likely to have been in thelowest-achieving group forsome time.

S E C T I O N

4E D U C A T I O N

Figure 9 Change in inequality in reading achievement
Country

Achievementgap 2006

Achievementgap 2012

Change (2006–2012)

Countries in which the 10th percentile increased more than the medianCzech Republic

153

117

-36.0

Chile

133

104

-28.5

Germany

158

131

-27.6

Mexico

130

106

-24.0

Belgium

167

144

-23.6

Poland

139

118

-20.6

Austria

151

131

-20.5

Italy

153

138

-15.2

Lithuania

131

118

-13.0

Turkey

120

109

-11.0

Norway

146

135

-10.7

Ireland

126

116

-10.5

United Kingdom

142

132

-10.4

Romania

125

115

-10.0

Estonia

116

106

-9.8

Portugal

140

131

-9.3

Japan

145

136

-8.7

Greece

148

140

-8.1

Switzerland

132

126

-6.1

Croatia

123

118

-5.0

Countries in which the 10th percentile decreased less than the median
Canada

132

125

-7.5

Countries in which the achievement gap remained within +/- 5 score points
Denmark

120

116

-4.9

New Zealand

147

143

-4.6

Republic of Korea

123

119

-3.8

Netherlands

136

133

-3.1

Latvia

122

120

-1.8

Slovenia

124

123

-1.4

Hungary

131

131

-0.3

Australia

130

130

0.0

Israel

165

167

2.0

Spain

125

127

2.1

Iceland

136

138

2.4

Luxembourg

143

145

2.4

France

153

157

4.2

Slovakia

146

151

4.7

Figure 10 Percentage below
proficiency level 2 in mathematics,
reading and science
72% are at level 2
or above
Reading
2.6%

2.5%Countries in which the 10th percentile increased less than the median
Bulgaria

153

167

11.6%
14.2
5.5%

Countries in which the 10th percentile decreased more than the median
Sweden

134

147

13.0

Finland

109

131

21.7

Source: PISA 2006 and 2012.
Note: no trend data available for the United States.

1.2%

Mathematics

1.5%
3.4%

Science

Source: PISA 2012.
Note: unweighted average for 34 OECD countries.

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S E C T I O N

4E D U C A T I O N

Box 2 A ‘sticky floor’ in poor
children’s cognitive development:
evidence from the UK’sMillennium Cohort Study

From as early as the age of 3, children from more affluent backgrounds
tend to do better in cognitive tests.i The Millennium Cohort Study (MCS)
has tracked around 19,000 children born at the turn of the century
across the United Kingdom from the age of 9 months. They were
followed up at ages 3, 5, 7 and 11 and will be surveyed into adulthood.
Although at each sweep of the MCS, one child in 10 falls into thebottom decile of the cognitive ability distribution, each child’s chancesof ending up in the bottom depend on their family background. At age
5, children from income-poor families are around three times more
likely to be in the bottom 10 per cent than are their peers from nonpoor households.
Figure 11 shows the shares of MCS children who scored in the bottom
decile of the cognitive ability distribution in a given year (i.e. at ages 3, 5or 7) and who remained in the bottom decile or moved up the
distribution the next time they were tested. Children from poor
households (43 per cent) are substantially more likely to get stuck in thebottom of the distribution than are their counterparts from non-poorhouseholds (28 per cent), but the differences are smaller among those
who do make the transition from the bottom decile. Most of both poorand non-poor children who exit the bottom decile move up only one or
two deciles. Thus, there is a ‘sticky floor’ for all children with low
cognitive scores; but it is far stickier for those from income-poor families.

Figure 12 displays trends inabsolute educational disadvantage
between 2006 and 2012 for the 38
countries included in the PISA
study. It shows:»» The largest reductions in crosssubject low performance were
found in Bulgaria, Israel, Romania
and Turkey. However, despite
positive developments, thesefour countries remained among
those with the highest overalllevels of absolute educational
disadvantage in 2012.

»» Reductions in the share ofchildren performing at below
proficiency level 2 in all threesubjects occurred in the Czech
Republic, Germany, Latvia and
Poland; this improvement
resulted in them joining the top
third of countries (those that
performed best) in terms ofabsolute educational
disadvantage in 2012.

»» Absolute educational
disadvantage remained broadly
static between 2006 and 2012 ina number of other countries.
Some countries with the highest
proportions of children falling
below proficiency level 2 in all
three subjects, such as Chile,
Greece and Luxembourg,
struggled to reduce theproportion of low performers.

Figure 11 Transitions from the bottom decile ofcognitive ability distribution
50

Per cent

40
30
20»» Finland and Sweden saw a

100

Bottomdecile

2

3

4
Poor

5

6

7

8

9

Top
decileNon-poor

Source: UK Millennium Cohort Study; Bruckauf, Z. and Y. Chzhen (2016). 'Poverty andChildren's Cognitive Trajectories: Evidence from the UK Millennium Cohort Study'.

iHansen, K. and H. Joshi (2007). Millennium Cohort Study Second Survey:
A user’s guide to initial findings, Centre for Longitudinal Studies, London.

2 0

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1 3

notable increase in the
proportion of 15-year-olds who
failed to achieve proficiency level
2 in all three subjects between
2006 and 2012, suggesting that
there is a growing group of very
disadvantaged children in thesetwo countries.

S E C T I O NReducing inequality iscompatible with academic
progress for all
While some countries are moving‘upward’ (by raising academic
standards and reducing absolutelevels of educational disadvantage),others demonstrate a worrying
regressive trend in terms of theirsupport for children at the ‘bottom’.
The evidence presented here
shows that large relativeeducational achievement gaps are
not inevitable. The strong all-roundperformance seen in countries suchas Estonia, Denmark and Poland
shows that there is no need tosacrifice a rise in overall educational
achievement in order to reduce
relative achievement gaps orabsolute educational disadvantage.
The primary focus of this Report
Card is to compare the overalllevels of bottom-end inequality
across countries; but analysis ofwithin-country differences
underlines significant ways inwhich social inequalities shapeeducational disadvantage. Boxes 2
and 3 and Section 7 examinesome of the key issues here in
more detail.

4

E D U C A T I O N

Figure 12 Change in educational disadvantage
Country

Below level 2
in all threesubjects 2006

Below level 2
in all threesubjects 2012

Romania

36

24

-11.9

Turkey

25

16

-9.8

Israel

26

19

-7.4

Bulgaria

35

29

-6.5

Mexico

35

31

-4.2

Portugal

16

13

-3.8

Poland

9

6

-3.7

Italy

15

12

-3.3

Spain

13

10

-2.7

Germany

11

9

-2.2

Japan

8

6

-2.2

Latvia

10

8

-2.0

Estonia

5

3

-1.7

Czech Republic

11

9

-1.7

Switzerland

9

7

-1.5

Lithuania

13

12

-1.4

Norway

12

11

-1.2

Ireland

8

7

-0.8

Chile

25

25

-0.7

Croatia

12

12

-0.5

France

13

13

-0.4

Austria

11

11

0.0

Luxembourg

14

14

0.0

Greece

15

16

0.3

United Kingdom

11

11

0.3

Republic of Korea

4

4

0.5

Belgium

11

12

0.7

Canada5

6

1.0

Denmark

8

9

1.1

Netherlands

7

9

1.3

Australia

7

9

2.0

Slovenia

8

10

2.0

Hungary

11

13

2.5

Iceland

10

14

3.1

New Zealand

8

11

3.3

Finland2

5

3.5

Slovakia

13

19

5.7

Sweden9

15

6.1

OECD average

12

12

0

Change (2006–2012)

Source: PISA 2006 and 2012.
Note: no trend data available for the United States.

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2 1

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Box 3 Educational disadvantage
through a gendered lensSince the first PISA study in 2000, 15-year-old boys
have consistently done worse than girls in maths,
reading and science. The gaps in favour of girls arelargest in reading: in 2012, girls outperformed boys inreading by a good margin (38 score points, or nearly
one year of schooling) on average across OECD
countries. In 37 of the 39 countries studied, boys
were significantly more likely to be in the bottom
decile of reading achievement than girls.
Boys are also more likely to be in the group of crosssubject low performers in 35 of the 39 countries(Figure 13). Although the scale of gender disparity (infavour of girls) for those who fall below proficiency

level 2 in all three subjects is lower than in reading,for example, it nevertheless overwhelmingly points
to boys’ educational disadvantage. On average
across the OECD countries, the probability of boys
being in this group is around 4 percentage points
higher than it is for girls. But in Bulgaria, Greece,
Israel and Turkey, the difference is 10–14 percentage
points. The gap is statistically significant in all but
four countries (Austria, Luxembourg, the Netherlands
and the United Kingdom). This gender gap is also
highly persistent over time. In a few countries where
the change is significant between 2006 and 2012
(for example, the Czech Republic, Finland, Lithuania
and Sweden), the disparity increased.

Figure 13 Gender gap in low educational achievement: boys vs girls
40
35

Percentage points

30
25
20
15
10
5

Luxembourg
United Kingdom
Netherlands
Austria
Switzerland
EstoniaJapan
Korea
CanadaDenmark
IrelandSpain
Germany
Australia
Belgium
Czech Republic
PolandFinlandChile
Slovakia
MexicoNew Zealand
Italy
Hungary
Slovenia
FrancePortugal
NorwayUnited States
LatviaRomania
IcelandSwedenLithuania
Croatia
GreeceTurkeyIsraelBulgaria
OECD average

0

Boys

Girls

R E P O R T

C A R D

Gender Gap

Source: PISA 2012.

2 2

I N N O C E N T I

1 3Gender Gap – significant differences

S E C T I O N

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B E H A V I O U R S

SECTION 5
HEALTH SYMPTOMS AND BEHAVIOURS

League Table 3 highlighted bottomend inequality in self-reported
health symptoms in 2014. Thissection considers three additionalvariables – physical activity, healthyeating and unhealthy eating – topresent a fuller picture of change inadolescent health and healthrelated behaviours. Bottom-end
inequality is measured in the sameway for all four indicators. For eachcountry, the relative gap iscomputed by comparing a child
who reports relatively low scores(represented by the mean of values
below the median) and the‘average’ child (represented by the
median itself). The gap is measured
as the difference between the two,
calculated as a share of themedian. It captures the extent towhich children at the bottom fallbehind the ‘average’ child in theirown country.

Figure 14 Change in health inequality

Figures 14–17 show the changes inbottom-end inequality for each of
the four indicators between 2002
and 2014. Countries are grouped inorder to clarify the reasons behindthese changes. The first group
includes countries where therelative gap decreased because
both the bottom and the middle
improved over time, but the bottom
advanced faster; this positive
scenario represents not only overall
progress but also declines inbottom-end inequality. Countries inthe second group also saw adecrease in the relative gap, but
the middle regressed while thebottom improved. The third group
includes countries where theCountry

Relative gap
2002

Relativegap 2014

Change (2002–2014)

Countries in which the relative gap remained stable (-/+ 2 ppt)
United States

29.2

28.0

-1.2

Estonia

28.8

27.7

-1.1

Spain

27.8

27.3

-0.5

Lithuania

29.2

29.3

0.1

Austria

23.2

23.6

0.4

Greece

26.2

27.4

1.2

Hungary

27.3

28.8

1.5

United Kingdom

27.3

28.9

1.6

Finland

24.0

25.9

1.9

Countries in which the middle improved more than the bottom
Romania

31.6

34.0

2.3

Sweden

26.2

29.1

2.8

Slovakia

25.5

29.0

3.5

Portugal

22.5

26.4

3.9

Israel

31.2

38.9

7.7

Countries in which the bottom declined more than the middle
Norway

23.1

25.2

2.0

Luxembourg

28.2

30.3

2.1

Bulgaria

27.2

29.4

2.2

Croatia

25.3

27.6

2.3

Belgium

25.7

28.1

2.5

Switzerland

22.4

25.0

2.5

Canada

26.6

29.3

2.7

Latvia

25.4

28.6

3.3

Iceland

27.7

31.1

3.4

Italy

26.4

30.1

3.7

Denmark

21.8

25.5

3.8

Czech Republic

22.8

26.8

4.0

Germany

20.5

24.8

4.3

Netherlands

22.2

26.7

4.6

France

24.4

29.2

4.8

Turkey

29.7

34.5

4.9

Slovenia

22.2

28.3

6.1

Ireland

22.5

28.9

6.4

Malta

24.0

30.6

6.6

Poland

26.3

34.1

7.8

Source: HBSC 2002–2014.
Note: Israel and the United States, 2002–2010; Bulgaria, Iceland, Luxembourg,
Romania and Slovakia, 2006–2014; Turkey, 2006–2010.

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relative gap increased because
either the middle improved fasterthan the bottom, or the middle
improved while the bottom lost
ground. In the fourth group, healthin both the bottom and the middle
worsened, but the decline wasgreater at the bottom. This trend
deserves the most attention.
Changes in the relative gap of
within 2 percentage points are
deemed too small to be indicativeof a real trend, and so only changes
above or below this benchmark areconsidered here.

Inequality in health increased in
the majority of the countries
No country saw a decline inbottom-end inequality in adolescenthealth over the decade underconsideration. The relative gap in
self-reported symptoms widenedby 2 percentage points or more in
25 of the 34 countries, remaining
stable elsewhere (Figure 14). The
largest increases (of at least 6
percentage points) are found in
Ireland, Malta, Poland and Slovenia,
where the bottom regressed morethan the middle, and in Israel,
where the middle gained ground
while the bottom lost out. Poland
and Israel lie at the bottom of the
Health League Table (see Section 2,
page 8).
The chances of falling behind in
health are not the same for all
children. In the majority of thecountries studied, those from lessaffluent households have thepoorest health outcomes.8
However, the difference between
girls and boys is even larger, morewidespread and persistent (seeBox 4).

2 4

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Figure 15 Change in inequality in physical activity
Country

Relative gap
2002

Relative gap
2014

Change (2002–2014)

Countries in which the bottom improved more than the middle
Malta

64.6

55.6

-9.0

Finland

51.0

42.5

-8.5

Norway

55.7

47.6

-8.1

France

58.3

50.3

-8.0

Spain

51.4

45.1

-6.3

Bulgaria

56.9

51.1

-5.8

Estonia

52.8

47.8

-5.0

Portugal

51.0

46.9

-4.1

Ireland

49.8

46.1

-3.7

Switzerland

48.7

45.3

-3.4

Croatia

50.1

46.8

-3.3

Czech Republic

49.3

46.2

-3.1

Latvia

49.6

46.5

-3.1

Iceland

50.3

47.7

-2.6

Belgium

51.5

49.2

-2.3

United States

54.3

52.1

-2.2

Hungary

54.4

52.3

-2.1

Netherlands

49.4

47.5

-2.0

Countries in which the relative gap remained stable (-/+ 2 ppt)
Slovakia

49.6

47.7

-1.9

Denmark

51.8

50.3

-1.5

Luxembourg

49.4

48.2

-1.2

Canada

47.9

46.9

-1.0

United Kingdom

47.7

47.3

-0.4

Austria

47.3

47.0

-0.4

Lithuania

48.1

47.9

-0.2

Slovenia

47.7

48.2

0.5

Sweden

47.9

48.6

0.7

Greece

50.3

51.2

0.9

Germany

46.8

47.7

0.9

Israel

61.8

62.9

1.1

Countries in which the middle improved more than the bottom
Poland

45.6

48.5

2.9

Romania

55.9

58.8

2.9

Countries in which the bottom declined more than the middle
Italy

54.2

56.8

2.6

Turkey

55.5

60.9

5.3

Source: HBSC 2002–2014.
Note: Israel and the United States, 2002–2010; Belgium, Bulgaria, Iceland,
Luxembourg, Romania and Slovakia, 2006–2014; Turkey, 2006–2010.

C A R D

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S E C T I O N

5H E A L T H

S Y M P T O M S

A N DInequality in physical activity
decreased in the majority of
the countries

Figure 16 Change in inequality in healthy eating

Regular exercise is key toadolescent well-being. Children in
the HBSC survey report the numberof days in the preceding week onwhich they engaged in physicalactivity for a total of at least 60
minutes a day, as recommended by
the World Health Organization. The
HBSC questionnaire defines
physical activity as “any activity that
increases your heart rate andmakes you get out of breath someof the time”.9 Children’s responses
are on a scale from 0 to 7 daysa week.

Countries in which the bottom improved more than the middle

Bottom-end inequality in physicalactivity narrowed in 18 of the 34
countries over the previous decade,with pronounced reductions of 6
percentage points or more in
Finland, France, Malta, Norway andSpain (Figure 15). In all thecountries where the relative gap
decreased, gains at the bottom
outpaced those in the middle.
In 12 of the 34 countries, therelative gap remained within 2
percentage points in 2002 and2014. But there were notable
increases in bottom-end inequality
in the remaining four countries.
These changes occurred for two
different reasons: in Poland andRomania the relative gap increased
because children were more
physically active in 2014 than in
2002, but improvements in the
middle outstripped gains at thebottom; meanwhile, in Italy andTurkey the gap increased because
children at the bottom lost out
disproportionately more than thosein the middle.

Country

Malta

Relative gap
2002
52.9

Relative gap
2014

B E H A V I O U R S

Change (2002–2014)

40.3

-12.6

Hungary

58.8

50.5

-8.3

Denmark

49.8

42.2

-7.6
-7.2

Norway

51.2

44.0

Spain

53.8

47.4

-6.3

Sweden

51.2

45.5

-5.7

Greece

49.8

45.0

-4.8

Italy

51.8

48.0

-3.8

Estonia

49.9

46.4

-3.5

Bulgaria

47.6

44.6

-3.0

United States

52.1

49.6

-2.5

Lithuania

47.4

45.4

-2.1

Countries in which the relative gap remained stable (-/+ 2 ppt)
Iceland

49.6

47.9

-1.8

Germany

50.3

48.6

-1.7
-1.6

Latvia47.6

46.0

Ireland

48.2

46.7

-1.5

Switzerland

45.7

44.6

-1.0

Slovenia

45.4

44.4

-1.0

United Kingdom

50.1

49.6

-0.5

Turkey

43.9

43.4

-0.5

Austria

47.4

47.2

-0.2

Canada

42.8

43.0

0.2

Romania

45.2

45.5

0.3

Netherlands

35.0

35.4

0.3

Slovakia

45.6

46.3

0.7

Israel

49.2

50.3

1.1

Belgium

40.7

41.9

1.2

Luxembourg

47.1

48.7

1.5

Countries in which the middle improved more than the bottom
Finland

42.7

48.6

6.0

Countries in which the bottom declined more than the middle
Czech Republic

43.8

45.9

2.1

France

44.4

47.2

2.8

Poland

43.2

46.4

3.2

Croatia

43.9

48.4

4.4

Portugal

41.6

48.2

6.6

Source: HBSC 2002–2014.
Note: Israel and the United States, 2002–2010; Bulgaria, Iceland,
Luxembourg, Romania and Slovakia, 2006–2014; Turkey, 2006–2010.

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S Y M P T O M S

There are mixed trends ininequality in healthy eating
Fruit and vegetables are essential
components of a healthy andbalanced diet. HBSC respondents
indicate how many times a week
they usually eat fruit andvegetables. Their answers to thesetwo questions are combined tocreate an indicator of healthy eating(on a scale from 0 to 14).
Bottom-end inequality in healthyeating narrowed in 12 of the 34
countries (Figure 16). All 12
countries saw improvements at thebottom that outpaced any gains in
the middle. The largest decreases
in the relative gap – of at least 6
percentage points – were in Malta,
Hungary, Denmark, Norway andSpain, suggesting that thesecountries made notable progressover the previous decade in
improving children’s access tohealthy food.
The relative gap remained stable in
16 countries and increased in theother six. The largest increases
were in Portugal (where the bottom
lost out, while the middle remained
the same) and in Finland (where themiddle improved more than thebottom, against a backdrop of an
overall rise in healthy eating among
adolescents).

A N D

B E H A V I O U R S

Figure 17 Change in inequality in unhealthy eating
Country

Relative gap
2002

Relative gap
2014

Change (2002–2014)

Countries in which the bottom improved more than the middle
Netherlands

89.1

69.4

-19.7

Slovenia

73.2

53.8

-19.4

Iceland

61.9

44.5

-17.4

Norway

71.1

57.8

-13.3

Greece

66.0

52.7

-13.3

Bulgaria

89.5

77.8

-11.7

Israel

90.3

79.8

-10.4

Spain

75.0

64.6

-10.4

Italy

77.1

66.7

-10.4

Canada

68.1

57.8

-10.4

Ireland

76.0

66.5

-9.5

Germany

77.0

67.8

-9.2

Luxembourg

74.7

66.4

-8.3

Malta

77.7

69.7

-8.0

Portugal

73.5

66.1

-7.4

Finland

61.8

55.9

-5.9

Czech Republic

70.6

66.2

-4.4

Denmark

64.3

60.0

-4.3

United States

76.9

72.6

-4.3

United Kingdom

72.5

68.2

-4.3

Latvia

67.7

63.7

-4.1

Croatia

74.2

70.5

-3.6

Austria

69.2

65.7

-3.5

Sweden

60.9

58.5

-2.5

France

74.9

72.5

-2.3

Countries in which the relative gap remained stable (-/+ 2 ppt)
Hungary

80.8

79.1

-1.7

Switzerland

75.0

73.6

-1.4

Poland

74.0

73.0

-1.0

Inequality in unhealthy eating
decreased in most countries

Estonia

63.9

63.3

-0.6

Lithuania

63.5

65.4

1.9

In contrast to fruit and vegetables,
excess consumption of addedsugar in food and beverages isoften linked to poor healthoutcomes – especially in dental
health. HBSC respondents indicate
how often during the past week
they have consumed “sweets(candy or chocolate)” and “CokeCountries in which the middle improved more than the bottom

2 6

I N N O C E N T I

R E P O R T

Romania

75.2

78.4

3.2

Slovakia

70.9

75.2

4.3

Belgium

71.2

76.3

5.1

Countries in which the bottom declined more than the middle
Turkey68.7

76.9

Source: HBSC 2002–2014.
Note: Israel and the United States, 2002–2010; Bulgaria, Iceland,
Luxembourg, Romania and Slovakia, 2006–2014; Turkey, 2006–2010.

C A R D

1 3

8.2

S E C T I O N

5H E A L T H

S Y M P T O M S

A N D

B E H A V I O U R S

Box 4 Adolescent girls persistently
more likely to fall behind in health

Figure 18 shows the gender gap in poor healthamong adolescents in the 2014 HBSC survey. The
bars display the percentage-point difference
between girls and boys in terms of the chances offalling furthest behind the ‘average’ (i.e. children withhealth scores below the mean in the lower half ofthe distribution in their country). Differences in age
and family affluence are held constant. In all 34
countries under review, girls are significantly more
likely to fall behind in health. Since adolescence is aformative stage for adult health, these differences
are likely to endure into adulthood.
Notably there is no correlation across countries
between bottom-end inequality in health and thegender differential in the chances of falling furthest
behind. Indeed, the countries with the largest

differences between girls and boys (15 percentage
points or more) are Denmark, Sweden and Italy.
They place in the top, middle and bottom,
respectively, of League Table 3 in Section 2. The
gender differential is lowest in Israel, the country
with the largest level of bottom-end inequality inadolescent health in the comparison.
Gender gaps in adolescent health are not only
widespread, but persistent; and in some cases, theywiden over time. In all 34 countries, girls are
significantly more likely to fall behind in health in all
four HBSC cycles between 2002 and 2014. In 10 ofthese countries, the gender gap has increased since
2002: Belgium, Canada, the Czech Republic, Estonia,
Ireland, Italy, Slovenia, Sweden, the United Kingdom
and the United States.

Figure 18 Gender gap in poor health: girls vs boys
20
18

Percentage points

16
14
12
10
8
6
4
2
IsraelTurkeySlovakia
Belgium
Malta
Austria
Iceland
PolandFinlandUnited States
Hungary
Bulgaria
Spain
Portugal
Lithuania
FranceNorwayGermany
LatviaRomania
Estonia
Croatia
Czech Republic
Switzerland
United Kingdom
IrelandNetherlands
CanadaSlovenia
Luxembourg
GreeceDenmark
SwedenItaly0

Source: HBSC 2013/2014; Chzhen, Y., et al. (2016). ‘Family Affluence and Inequality in Adolescent Health and Life Satisfaction’.
Note: data for 2010 used for Israel, Turkey and the United States.

I N N O C E N T I

R E P O R T

C A R D

1 3

2 7

S E C T I O N

5H E A L T H

S Y M P T O M S

or other soft drinks that containsugar”. Their responses areconverted into an indicator of
unhealthy eating (on a scale from 0
to 14), with higher values
corresponding to less-frequentconsumption of added sugar.
The vast majority of countries, 25
out of 34, had reduced bottom-end
inequality in unhealthy eating by atleast 2 percentage points over theprevious decade (Figure 17). In allcases, this came about because thebottom improved faster than the
middle – a veritable ‘win-win’
scenario. The Netherlands, Slovenia
and Iceland saw considerable
reductions in the relative gap of over
17 percentage points. A sizeable
improvement of 19 percentage
points places Slovenia alongside
Greece and Iceland as one of thebest-performing countries in bottomend inequality in terms of(abstinence from) unhealthy eating.
The relative gap in unhealthy eating
decreased in more countries – andby a greater margin – than in any
other health-related indicator in thissection, albeit from a higher base.
This indicates that today’s
adolescents consume less sugar
than their counterparts did at theturn of the century, while even those
who eat less healthily than theirpeers no longer fall so far behind.
Nevertheless, bottom-end inequality
in unhealthy eating tended to
exceed that in the other three
indicators in 2014, and there werefour countries – Belgium, Romania,
Slovakia and Turkey – where the

2 8

I N N O C E N T I

R E P O R T

A N D

B E H A V I O U R S

relative gap in unhealthy eating had
increased by 2 percentage points
or more since 2002. The sizeable
increase of 8 percentage points in
the relative gap in Turkey is due toworsening outcomes overall, andespecially at the bottom. By
contrast, inequality widened in theother three countries because, inspite of an overall reduction in theprevalence of unhealthy diets,
outcomes at the bottom improved
more slowly than in the middle.
Reductions in inequality in healthy
and unhealthy eating can go handin hand. Ten out of the 12 countries
that showed progress in reducing
bottom-end inequality in the
consumption of fruit andvegetables also reduced bottomend inequality in the consumptionof added sugars. The relative gap in
unhealthy eating remained stable in
the other two countries, Hungary
and Lithuania. Norway and Spainstand out in particular, achieving
large reductions in bottom-end
inequality of 6 percentage points ormore in both diet-related indicators.

Explaining trends in bottomend inequality
Growing up in unequal, harsh social
environments may pose a barrier
for children to a healthy, happy andproductive life.10 Although there are
no clear relationships between
income inequality and the healthrelated indicators in this section,
income inequality can have alagged effect on health and wellbeing in adolescence.11 Cultural
factors may also be important, but

C A R D

1 3

the influence of such factors isquite difficult to detect in crossnational analyses.
The complexity of the processes
driving bottom-end inequality inhealth is underlined by the fact thatthe vast majority of countries
examined here have seen inequality
in health-related outcomes widen insome of the four areas considered
here, yet narrow in others. Indeed,
Spain and the United States are theonly countries that have reduced
inequality among adolescents
across all four measures. A similar
picture exists in terms of country
rankings in 2014, with mostcountries placing in the top half forsome measures and in the bottom
half for others. This is true even forsome of the best overall
performers: the Netherlands shows
relatively large bottom-end
inequality in unhealthy eating,Finland in healthy eating, andDenmark in physical activity.12
What we do know is that, based ondata from the HBSC survey for
2013/2014, average levels of selfreported health, physical activity,
healthy and unhealthy eating varywith the relative health inequality
gaps for each of these outcomes.
The country-level averages for allthese measures are highly
correlated with the respective
relative gaps in health-related
outcomes studied here.13
More precisely: children are more
likely to report more frequent healthsymptoms and to have lower
average physical activity, lower

S E C T I O N

Lower sugar consumption

It is difficult to draw general
lessons on why exactly countries
end up at the top or the bottom of
rankings in these four indicators.
The consistent findings of a close
relationship between generalprogress and bottom-end inequality
in children’s health and healthbehaviours suggest that overall
improvement in health outcomes isvery difficult to achieve without
closing the gap at the bottom of
the distribution.

H E A L T H

S Y M P T O M S

A N D

B E H A V I O U R S

Figure 19 Relative inequailty and average level of unhealthy eating

Higher sugar consumption

average healthy eating and higher
average unhealthy eating incountries where children at thebottom are allowed to fall further
behind the middle. The relationshipbetween relative inequality andaverage levels of unhealthy eating
is particularly strong (Figure 19).

5

7

IS

SI
GR

6

CA

DK

FI
NO

5

SE
EE

4

ES
LT
PT
LV
IE
TR
CZ
IT
DE
LU

HR

UK

MT
NL

3

TR

US
FR

CH

PL
SK

BE

RO
HU
BG
IL

2
40

50

60

70

80

Relative gap in unhealthy eating
R-squared=0.79

Source: HBSC 2014.
Note: data for 2010 used for Israel, Turkey and the United States.

I N N O C E N T I

R E P O R T

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S E C T I O N

6L I F ES A T I S F A C T I O N

SECTION 6
LIFE SATISFACTION

Inequality in life satisfaction
remains stable in most countries

Figure 20 Change in inequality in life satisfaction

Figure 20 supplements the findingspresented in League Table 4, detailingchanges in bottom-end inequality inchildren’s life satisfaction between
2002 and 2014. The relative gap inlife satisfaction has narrowed in six
out of the 32 countries under review;
increased in another seven; and has
remained stable (i.e. within 2
percentage points) in over half ofthe countries.

Country

Among the six countries that haveseen reductions in inequality are fourthat experienced economic transitionin the 1990s – Estonia, Latvia,
Lithuania and Slovakia – as well as
two Nordic countries – Denmark and
Norway. In the three Baltic countries(Estonia, Latvia and Lithuania), boththe median life satisfaction (i.e. themiddle) and the mean score forchildren below the median (i.e. thebottom) increased between 2002 and2014, suggesting a notable
improvement in children’s life
satisfaction levels across the
distribution. In Denmark, Norway and
Slovakia, the median remained thesame in both years, but scores at thebottom improved.
By contrast, life satisfaction scores
increased both in the middle and at
the bottom of the distribution in
Israel, but the median advanced
faster, leading to an increase inbottom-end inequality in life
satisfaction. Meanwhile, increases in
the relative life satisfaction gap in
Belgium, Germany, Luxembourg,
Spain and Turkey occurred because
3 0

I N N O C E N T I

R E P O R T

Relative gap
2002

Relative gap
2014

Change (2002–2014)

Countries in which the bottom improved more than the middle
Norway

29.2

26.4

-2.9

Latvia

28.9

26.1

-2.8

Estonia

29.6

27.0

-2.6

Slovakia

31.9

29.4

-2.5

Lithuania

31.9

29.4

-2.5

Denmark

27.6

25.1

-2.5

Countries in which the relative gap remained stable (-/+ 2 ppt)
United States

30.5

28.7

-1.9

Greece

27.1

25.7

-1.3

Bulgaria

29.1

27.9

-1.2

Austria

27.7

26.9

-0.8

Portugal

28.7

28.0

-0.7

Slovenia

27.7

27.2

-0.5

Croatia

29.6

29.1

-0.5

Switzerland

26.8

26.3

-0.4

Sweden

28.1

28.0

-0.1

Ireland

27.4

27.4

0.0

Poland

31.1

31.1

0.1

Iceland

28.3

28.4

0.1

Hungary

27.6

27.9

0.3

Canada

28.8

29.4

0.6

Italy

28.1

28.8

0.7

United Kingdom

27.5

28.4

0.9

Finland

25.5

27.0

1.5

Netherlands

22.5

24.0

1.5

France

27.7

29.6

1.9

Countries in which the middle improved more than the bottom
Israel

28.0

30.0

2.0

Countries in which the bottom declined more than the middle
Luxembourg

27.8

30.0

2.2

Turkey

33.4

36.0

2.5

Germany

26.9

29.6

2.7

Spain

26.3

29.2

3.0

Czech Republic

28.0

31.5

3.6

Belgium

26.3

30.0

3.7

Source: HBSC 2002–2014.
Note: Israel and the United States, 2002–2010; Bulgaria, Greece, Iceland, Luxembourg,and Slovakia, 2006–2014; Turkey, 2006–2010. No trend data for Malta or Romania.

C A R D

1 3

tia

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Slo

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Polan

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ve

nia

35

Finland

ai

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Sp

d

ed
Sw

Portugal

30

Franc
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25

aria

Ca
na
da

Estonia

Belgiu
m

5

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Bul
g

Romania

k

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Den

Austria

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rlan

15

S A T I S F A C T I O N

lic

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Sw

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L I F E

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S E C T I O N

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15 likely to be in Dthe
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movements
in the relativeRolife
remained the same, while the meandsbottom end
ec
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lan
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Estonia5
ersatisfaction gap were trivial: inia19hscores for children at the bottomteNThe three radar charts in Figure
Finla21ndlPortugaof the 32 countries surveyed,thedecreased. In the Czech Republic,
break down the risks of falling intolife satisfaction gap remained nd
the relative gap widened becauseFrancethe bottom group for life
Pola
within 2 percentage points. In partboth the bottom and the middle
Geysatisfaction(children
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life
r
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ma
rw
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because of this broad stability
worsened, with a relatively greater
No over
Gr of thesatisfaction below the meansedetime in its life satisfaction gap, thecedecline at the bottom, suggesting alr anelower half of the distribution) forth
Netherlands recorded the lowest
widespread and inequitable fall inNeeach country, by age and gender.
gap not only in 2014 but also inchildren’s life satisfaction levels.
Differences between the darker and
2002, 2006 and 2010.
lighter-shaded areas show the gap
Against these examples of change,
between girls and boys.
it should be noted that in the

Slov

urg

Lithu

Latviaania

boLatvia

m

Ca

na

da

gar

ia

BelgiuBulAustria

a

Lithu

Lu
xem

Latvia

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BelgiuAustria

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Estonia5

Finland

Franc
e

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Polan

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ay

rm

rw

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R E P O R T

C A R D

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ee

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rla O C E N T I

atvia

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urg

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da
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da
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Bul
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Lu
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Romania

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any

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BelgiumAustria

ia

da

gar

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urg
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LatviaAustria

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Latvia

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25

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nia

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m
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a
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Hu

lan
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nd

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35

n

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Finland

ai

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nd

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y
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lan

nd

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itze

e
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Estoniadomd King

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k

mar

Den

lan

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lan
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Italy

xem

ng

Hu

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Irela

d

lic

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any

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ub

p
Re
ch

Cz

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ee

dom

tia

oa

Cr

Sp

Italy

rm

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any

ee

d
rlan

5

Ge

d Kingsnd

Sw

Romania

Hu

la

rm

Gr

10

ay

er

y

15

s
nd

Ge

20

akia

rw

th

d

30

nia

d
Polan
No

Finland

rla

25

Franc
e

Estonia

5

ar

lan

10

Portugal

Ne

nd

5

m

Romania

d

15

o
Kingd

20

akia

en

ed

25

Slov

35

a
c
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bli
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pu
Cr
Re
h
c
d
Polan Czeark
ay Denm
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No
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nia
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30

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Source: eHBSC

lan

r
itze
Sw

35

10

ay

he

Sw

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o
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ai

Slov

k

mar

Den

Franc
e

t
Ne

n

ve

n

de

Sp

d
rlan

itze

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Sw

boys

Irela

nd

Slo

d
Unite
Sw

girls

ai

ec

15

any

lic

ub

ep
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Cz

20

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d
Unite

Irela

Italy

Sp

25

rw

No

ce

At age 15

tia

oa

Cr

d
Polan

any

ee

y
ar
ng
Hu
d
lan
Ice

rla

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Ice

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Portugal

rm

Gr

Ge

rm

akia

Finland

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Romania

Ge

ay

rw

No

en

Slov

Franc
e

d
Polan

nia

enm

Italy

Portugal

rlan

ark

30

Franc
e

ng

th

n

ve

ec

35

Finland

ai

Slo

D
ds
lan Estonia
r
e

Ne

itze

5

10

ed

Romania

ep
hR

rw

No

Sw

15

Sp

c

li
ub

Cz
ay

Estonia

Hu

akia

ia

t
oa

k

mar

Den

At age 13

10

Cr
d
Polan

20

ec

Sw

5

25

nia

Slov

Romania

Italy

dom

d

ve

15

lic

ub

ep
hR

Cz

20

akia

Portugal

tia

oa

Cr

25

nia

Slov

30

n

d

dom

en

ai

Slo

35

30

in

ve

d King

rlan

itze

ed

Sw
Sp

en

Slo

Unite
Sw

At age 11

pa

Lithu

Lithu

Latvia

ania

ou

rg

M
alt
a

em
b

y
ar

nd

d

lan

Irela

Lu
x

ng

Hu

Ice

Italy

d King
Unite

rlan

itze
Sw

ed
Sw

35

Figure 21 Gender gap in life satisfaction:S girls vs boys

any
3 1

S E C T I O N

6L I F ES A T I S F A C T I O N

While the picture is mixed acrosscountries at 11 years, at ages 13
and 15 girls are more likely thanboys in all countries to have fallen
behind in life satisfaction, with thegap being larger at 15 than at 13
nearly everywhere. At age 15, thelargest gender gaps are in France
and Poland. At age 13, the largest
gaps are in Malta and Sweden.
Across all countries, older children
are generally more likely to be in
the bottom group than are younger
children, illustrated by the overall
size of the shaded areas.

arguably dissipated in recent years,
as policy makers in many countries
have begun to engage more openly
and directly with such measures.
However, understanding why, and inwhat ways, policy makers might
address low life satisfaction remains
an issue.
Adolescence can be a time of big
transitions, new experiences andrisk taking. Analysis of how low life
satisfaction may overlap withadolescents’ risk or problem
behaviours provides compelling
reasons for addressing inequality.
Analysis of HBSC data14 shows thatchildren with low life satisfaction(i.e. those with scores below themean of the lower half of the
distribution in their country) are, on
average, twice as likely to report
three or more different types of risk
behaviours as are their peers. This
association holds even after
controlling for children’s age, genderand family socio-economic status.
Across more than 20 of thecountries studied, children in thebottom group for life satisfaction are
up to three times more likely thantheir peers to experience regular

While the primary focus of thisReport Card is to compare overalllevels of life satisfaction crossnationally, it is clear that there issignificant social patterning of life
satisfaction within rich countries
that must be considered if bottomend inequality in life satisfaction
is to be reduced.

Why inequality in life
satisfaction matters
Debates about the validity ofsubjective well-being measures
such as self-reported life
satisfaction or happiness havefighting, to be victims of bullying
and to smoke regularly. In 19 of
those countries, this group is also
more likely to report bullying others;
and in 11 they are more likely toexperience a higher level of injuries.
Figure 22 shows that there is a clear
relationship between low life
satisfaction and cumulative risk
behaviours. The direction of
causality – i.e. whether low life
satisfaction leads to greater
exposure to health risks or whether
greater exposure to health risks
leads to lower life satisfaction – isopen to debate.
In short, while tackling bottom-end
inequality in children’s life
satisfaction may seem a more
abstract policy goal than addressing
the inequalities examined in theincome, education and healthsections of this Report Card, life
satisfaction cannot be disregarded
as irrelevant to policy agendas
concerned with child well-being.
Indeed, the HBSC data suggest thattaking low life satisfaction seriously
may help us understand how betterto address inequalities in health andrisk behaviours.

25
20
15
10
5

High life satisfaction

Low life satisfaction

I N N O C E N T I

R E P O R T

C A R D

1 3

Malta

Denmark

Czech Republic

Finland

Luxembourg

Croatia

Slovenia

LatviaDifference (percentage points)

Source: HBSC 2013/2014.
Note: Multiple risk behaviours include smoking, drinking and binge drinking, fighting, frequent injuries, and bullying.

3 2

Bulgaria

Belgium

Romania

Estonia

Netherlands

Germany

Lithuania

CanadaAustria

Spain

Ireland

Iceland

PolandFranceSlovakia

Hungary

Italy

United Kingdom

GreecePortugal0

SwedenPer cent reporting 3 or morerisk behaviours

Figure 22 Risk behaviours and life satisfaction

S E C T I O N

6L I F ES A T I S F A C T I O N

Box 5 Immigration and adolescent life satisfaction

Migration is high on the agenda in Europe andbeyond, but little is known about the needs of
migrant children. In many countries they areafforded opportunities and resources that differ fromthose of children from non-immigrant families.
Several countries in the HBSC network collect dataon children’s country of birth. Eleven countries did
so in 2009/2010: Denmark, Germany, Greece,
Iceland, Ireland, Israel, Italy, the Netherlands, Spain,
the United Kingdom (Wales) and the United States.

Italy, Spain and the United States, either first- or
second-generation (or both) migrant children
reported lower life satisfaction than non-immigrantchildren (Figure 23).i
HBSC data found that schools with a higher
proportion of immigrant children also had higher
levels of fighting and bullying, but that classmate
support played an important role. When classmate
support was high, regardless of the proportion of
immigrant children in the school, levels of violent
behaviour were lower.ii

Analysis of HBSC 2010 study for 10 of thesecountries shows that in Germany, Iceland, Ireland,

Figure 23 Life satisfaction and migrant background
8.4

Mean life satisfaction (0–10)

8.2
8.0
7.8
7.6
7.4
7.2
7.0
6.8
6.6

Non-immigrantFirst generation

Italy

Wales

Germany

IrelandUnited States

Iceland

GreeceDenmark

Spain

Netherlands

6.4

Second generation

Source: HBSC 2009/2010; Stevens, G.W., S.D. Walsh, T. Huijts, M. Maes, K. Rich Madsen, F. Cavallo and M. Molcho (2015). 'An
Internationally Comparative Study of Immigration and Adolescent Emotional and Behavioral Problems: Effects of generation andgender', Journal of Adolescent Health, vol. 57, no. 6, pp. 587–594.

i
Stevens, G.W., S.D. Walsh, T. Huijts, M. Maes, K. Rich Madsen, F. Cavallo and M. Molcho (2015). ‘An Internationally
Comparative Study of Immigration and Adolescent Emotional and Behavioral Problems: Effects of generation and gender’,Journal of Adolescent Health, vol. 57, no. 6, pp. 587–594.
ii
Walsh, S.D., B. De Clercq, M. Molcho, Y. Harel-Fisch, C.M. Davison, K. Rich Madsen and G.W. Stevens (2015). ‘The
Relationship between Immigrant School Composition, Classmate Support and Involvement in Physical Fighting and Bullying
among Adolescent Immigrants and Non-Immigrants in 11 Countries’, Journal of Youth and Adolescence (published online 26
October 2015).

I N N O C E N T I

R E P O R T

C A R D

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S E C T I O N

7F A I R N E S S

F O R

C H I L D R E N

SECTION 7
FAIRNESS FOR CHILDRENIn this section, we investigate theextent to which the socio-economic
status (SES) of a child’s family
predicts his or her outcomes in
education, health and life
satisfaction – what social scientists
refer to as the ‘social gradient’. With
income inequality rising in most richcountries,15 analysts have asked
whether this will affect equality ofopportunity in the future.16 Indeed,
the OECD recently warned thatrising income inequality can “stifle
upward social mobility”.17
An examination of how strongly
factors such as family backgroundshape inequalities in health,education and life satisfaction canhelp us to understand some of theways in which economic inequality
affects children’s lives now and in
the future – particularly the lives ofthe most disadvantaged children.
If income or family backgroundstrongly predict children’s life
chances, and if income inequality
is widening in most rich countries,that will exacerbate inequality inchildren’s outcomes, raising
important questions about fairness
for children.

Life satisfaction
The HBSC study includes anindicator of family SES – the family
affluence scale – allowing
examination of the degree to which
the SES of the household in which achild grows up predicts their life
satisfaction and health outcomes.
For each of the outcomes, we show
the likelihood that a child from thelowest SES category is at the very

3 4

I N N O C E N T I

R E P O R T

bottom of the distribution of life
satisfaction and health, comparedwith a child from the highest
SES category.18
Figure 24 shows the influence of
SES on children’s lowest reported
life satisfaction in 2014. In all 34
countries the bars are above 0,
indicating that children with thelowest SES are more likely to be at
the bottom of the life satisfaction
scale, though there is aconsiderable range across thecountries. The largest effects of
SES are found in Hungary, Israel,
Luxembourg, Poland and Portugal,
where children in the lowest SES
group are between 18 and 27
percentage points more likely toreport extremely low life
satisfaction.
Crucially, this effect can be seen
just as clearly in 2002, 2006 and2010 as in 2014.19 These fourcycles of the HBSC survey capture
the voices of some 700,000
children in countries of the EU
and OECD. In short, there is clear
evidence that over the course of
the twenty-first century, children
from the lowest SES households
are consistently more likely tofall behind their peers in terms oflife satisfaction.

HealthThe relationship between SES andpoor health is most pronounced forphysical activity and healthy eating.
The interpretation of these figures
is the same as before – thelikelihood that a child from theC A R D

1 3

lowest SES category will be at thevery bottom of the scale for theoutcome being measured,compared with a child in the top
SES category. The figures show
that, for 2014:»» SES influences inequalities inphysical activity across richcountries (Figure 25). In all 34
countries in the analysis, children
from the lowest SES group are
significantly more likely to fallbehind in physical activity. The
largest social gradients are in
Belgium, Latvia and Luxembourg,
where children in the lowest SES
group are over 20 percentage
points more likely to be at thebottom than are children fromthe highest SES group. The
social gradient in physical activity
has widened over time in six
countries: Belgium, Italy, Latvia,
the Netherlands, Sweden andthe United Kingdom.

»» SES influences inequalities inhealthy eating across richcountries (Figure 26), withchildren from the lowest SES
households significantly more
likely to fall behind in
consumption of fruit andvegetables. Only in three
countries, Israel, Malta andRomania, is there no significant
correlation between SES andfalling behind in healthy eating.
The largest social gradients (of20 percentage points or more)
can be seen in Canada and theUnited Kingdom, where they
have widened over the past

20

15

10

5

0
Austria

SwedenSpain

Germany

Switzerland

IcelandDenmark

Italy

Belgium

Malta

Croatia

Slovenia

GreeceFinlandCzech Republic

I N N O C E N T I

R E P O R T

Hungary
IsraelLatviaLuxembourg

United Kingdom

Estonia

Luxembourg

Lithuania

PolandLuxembourg

Netherlands

Hungary

Portugal

TurkeyUnited Kingdom

Denmark

Belgium

Estonia
United States

EstoniaF O R

CanadaCanadaSlovakia

United States

F A I R N E S S

SwedenLithuania

Lithuania

IrelandUnited States

Latvia

Italy

Italy

Slovakia

IsraelLatviaDifference between low SES andhigh SES (percentage points)

7

Netherlands

Ireland
NorwayBulgaria
Germany

TurkeyPolandFinlandRomania

Denmark

Bulgaria

25
France30

Bulgaria

Figure 26 Socio-economic status and healthy eating
France0
United Kingdom

5

Iceland

10

France15
Netherlands

20

Canada25

Norway30

Belgium

Romania

Czech RepublicTurkeyHungary

Slovenia

PolandAustria

Switzerland

Ireland

Croatia

Spain

Malta

GreeceFinland

Portugal

Difference between low SES andhigh SES (percentage points)

Figure 25 Socio-economic status and physical activity

Czech Republic

Slovakia

IcelandSpain

GreecePortugal

Austria

SwedenGermany

Croatia

NorwaySwitzerland

Slovenia

IsraelMalta

Romania

Difference between low SES andhigh SES (percentage points)

S E C T I O N
C H I L D R E N

Figure 24 Socio-economic status and life satisfaction
30

25

20

15

10

5

0

Source for Figures 24–26: HBSC 2013/2014.
Note: data for 2010 used for Israel, Turkey and the United States.

C A R D

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3 5

S E C T I O N

7F A I R N E S S

F O R

decade, and in Luxembourg,
where the gradient has remained
stable. On the other hand,progress was made in Latvia,
Lithuania and Romania, where
the effect of SES was reduced
significantly between 2002
and 2014.

Educational achievement
The PISA data set constructs anindex of economic, social andcultural status which acts as a
useful proxy for the broad SES ofthe household and is the indicator
we use to estimate the influence offamily background on children’s
educational outcomes.
In a similar way to life satisfaction
and health, we estimate theprobability that a child from thelowest SES category will not reachproficiency in all three subjects,
relative to a child from the highest
SES group. In every single country
under review, the likelihood that theleast privileged students fall into
the bottom achievement group is

C H I L D R E N

higher than for the most privileged
students (Figure 27).
Across OECD countries, students
from the most disadvantaged
backgrounds were on average 18
percentage points more likely to fall
into the bottom achievement groupthan were children from the highest
SES group. However, the strength of
this social patterning varies acrosscountries. In a third of the countries,
the SES achievement gap is 20
percentage points or higher. In only
four countries is this difference 10
points or less – Canada, Estonia,
Japan and Korea – showing that thepowerful effects of family
background can be overcome.
Although the PISA measure of SES
is a useful proxy for economic
disadvantage, it does not have thegranularity that would be gained byactual household income data. In
Section 3 of the Report Card, datafrom the EU-SILC were used to
explore bottom-end inequalities inincome. The 2009 wave of thesurvey also collected information
on children’s access to several
education-related items.
Differences in household income
affect children’s access to
educational resources. Figure 28
and Figure 29 show that a child’s
access to books that are suitablefor his/her age group and a child’s
participation in school trips,
respectively, depend on the incomeof the household. In countries withhigh bottom-end income inequality,
these differences can be very large:
in Romania, a 1 per cent increase inhousehold disposable income isassociated with nearly a 25
percentage point rise in theprobability of a school-age childparticipating in school trips; andthere is a similarly large income
gradient when it comes to having
suitable books at home. In
countries with lower relative
income gaps among children,
access to these educational
opportunities depends less onhousehold income.

Figure 27 Socio-economic status and educational achievement

Difference between low SES andhigh SES (percentage points)

50
45
40
35
30
25
20
15
10
5
Estonia
Korea
Japan
CanadaLatviaFinland
PolandPortugal
United Kingdom
Croatia
Spain
TurkeyIrelandGermany
Slovenia
United States
Italy
Lithuania
Switzerland
Netherlands
Czech Republic
Australia
New ZealandSwedenIsraelDenmark
Luxembourg
Hungary
GreeceBelgium
MexicoFranceNorwayIceland
Austria
Chile
Romania
Bulgaria
Slovakia
OECD average0

Source: PISA 2012.

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S E C T I O N

Nonetheless, the data examined
here show that, across richcountries, those children who areallowed to fall furthest behind do
so in part because of general socialand economic inequalities in thesocieties in which they live. The
fact that SES continues to be an
important predictor of a child’s
success in health, schooling andlife satisfaction indicates that not all
children are given an equal
opportunity to develop. These
inequalities are unfair to children,
disadvantaging them in the earlystages of life and weakening their
futures. The fact that social
inequalities are smaller and have
weaker impacts on health,education and life satisfaction insome countries than in othersshows, at the very least, that the
lives of children can be made fairer
by policies that directly address theinequalities examined here.

F O R

C H I L D R E N

30
HUIncome gradient (percentage points)

Limits in the available crossnational data mean that the analysis
presented here cannot do justice tothe depth of disadvantage thatmany children face, particularly
some of the most disadvantaged
children, whose voices are often
marginalized in the surveys drawn
on for this Report Card (Box 6).
Moreover, while the league tables
presented in this Report Cardexamine inequalities in income,education, health and life
satisfaction separately, in reality
they are interrelated aspects ofchildren’s lives, and disadvantage in
one area may lead to, or reinforce,disadvantage in another.

F A I R N E S S

Figure 28 Income inequality and income gradient in possession of books

RO

20

PT

SK

PL

EL

LV

IT

10
CY

BE

CZ

NO
IS

30

EE

FR

IE
DK FI
NL

LT

LU

DE

SI

0

AT

CH

ES

UK

MT

40

50

60

70

Relative income gap
R-squared=0.29
Source: EU-SILC 2009.

Figure 29 Income inequality and income gradient in going on school trips
40
Income gradient (percentage points)

Fairer policies for children

7

HU

30

RO
LV

PL
SK

20

PT
EL

LU

10

IE
CZ
SI
IS

0
30

CY
NO FI
DK

40

EE

FR

MT
DE
CH
NL

LT
AT

UK

BE

ES

IT

50

60

70

Relative income gap
R-squared=0.32
Source: EU-SILC 2009.

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Box 6 Who is missing from the surveys?

The analysis in this Report Card has drawn,
wherever possible, on the best available childsurveys, in order to reflect the voices of children
themselves. However, while they represent thebest sources available, all surveys have their limits,and so we need to ask: Do these surveys cover thelife experiences of all children adequately? If not,which children are missing? Does this vary bycountry? And what does this mean for the analysis
presented here?

Why are some children’s voices missing?
School-based surveys, such as the OECD PISA
survey and the HBSC study, have many advantages,
but they are not able to collect information that istruly representative of the life experiences of allchildren. While acknowledging that some children
will be left out of these surveys, it is important toknow which ones are most often in the missing,or hidden, groups.
Children taught in schools that provide special
educational support and children out of school
altogether (e.g. in institutions, home taught, or who
have severe health problems or physical disabilities)
are missing from the studies.i
Children missing from the collection processinclude those who did not attend school on thesurvey day because they had health problems,
had played truant, or had been excluded fordisciplinary reasons.
Children who do not fully complete the survey often
miss out questions they find complex or on too
sensitive a topic, and sometimes a child does not
answer all the questions because of time constraints
or ability.ii
The Report Card’s analysis of income gaps draws on
household income surveys. Here, too, children canbe missing if, for instance, families are homeless orin temporary accommodation; if the children live in
undocumented or unregistered families orhouseholds; or if the parents are institutionalized.

Do the missing or hidden groups vary bycountry?
The missing or hidden child populations do vary bycountry. For example, the level of school enrolment
at age 15 varies across the OECD countries. In 2012,
drop-out rates in Mexico (around one in three) andTurkey (around one in five) were much higher than in

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the other OECD countries – so much so that theirPISA results are not included in the Report Card’s
League Table 2. In other OECD countries, enrolment
rates are around 100 per cent, though somecountries had drop-out rates of 4 per cent or more.
There are also wide variations in the proportion ofchildren in special schools across rich countries.
Different legislative frameworks and differingdefinitions of special educational needs are factors
in this variation. Indeed, the proportion of children
with special educational needs is 1 per cent in
Korea, compared with 10 per cent in the UnitedStates and almost 25 per cent in Iceland, where avery wide definition operates.iii
Hidden groups can also vary by country due todifferences in the types and rates of ‘at risk’populations in rich countries. For example, analysisof the Roma population in many European countries,
and of indigenous populations in countries such as
Canada and Australia, is central to understanding
inequality in child well-being in those countries.
These same groups are often underrepresented indata collections;iv however, improved survey design
can address these issues.

What does this mean for the analysis of childwell-being?
Many of these missing or hidden children are at a
disadvantage across all the measures of child wellbeing examined in this Report Card. Truants, children
who need tailored educational support, children who
are ill, or children who are unwilling or unhappy
about addressing questions they find sensitive, areamong the most likely to be left behind. Therefore,
we can be fairly sure that all estimates of inequality
between those on the bottom rung of the ladder andtheir better-off peers are an underrepresentation of
the reality, and that there are more children being
left behind in education, health and income in richcountries than our data can show.
iRichardson, D. and N. Ali (2014). ‘An Evaluation ofInternational Surveys of Children’, OECD Social,
Employment and Migration Working Papers, No. 146,
OECD Publishing, Paris.
ii
OECD Social Policy Division (2012). CX3.1 Special
Educational Needs (SEN), OECD Social Policy Division, Paris.
iii
iv

ibid.

Richardson, D. and N. Ali (2014). ‘An Evaluation ofInternational Surveys of Children’, OECD Social,
Employment and Migration Working Papers, No. 146,
OECD Publishing, Paris.

S E C T I O N

8C O N C L U S I O N

SECTION 8
CONCLUSION

Questions about when inequalities
become so large as to become
unfair defy easy answers; but thefigures presented in this Report
Card set out some stark facts about
the degree to which children at thebottom are being allowed to fallbehind their peers.

Smaller gaps are associatedwith improved outcomes
The evidence suggests that
reducing bottom-end inequality isan effective way of improving childwell-being outcomes for all.
In Section 2, in addition to showing
how far children at the bottom areallowed to fall behind their peers intheir own country, we provide
context for each of the league
tables, by using an indicator that
captures how many children fall
below a basic minimum threshold inincome, educational achievement,

Figure 30 brings this evidence
together, plotting the average rankof each country for the bottom-end
inequality measures against its
average rank on the four contextualindicators. The two are closely
related: countries that rank higher
on equality also rank higher onminimum standards. In otherwords, countries with lower
bottom-end inequality in child wellbeing have fewer children living inpoverty, fewer children with very
low educational achievement, fewer
children reporting frequent healthThe persistence of gaps
Sections 3–6 showed that, in all
countries, bottom-end inequality
has persisted over time, andprogress in reducing gaps has often
been limited. Ten years might seemtoo short a time frame in which to
expect gaps to be significantly
reduced, but for the individual childthis covers most of their childhood.
Not only does this mean that they
are being denied the best possible
start in life, but that theiropportunities to flourish in adult life
are often being harmed, too.

Figure 30 Bottom-end inequality and child well-being outcomes
Higher child well-being

The scale of the gaps between
children at the bottom and in the
middle can be very large. For
example, the income of a child at
the bottom end in Bulgaria, Mexicoand Romania is only a third of thatof an average child in the same
country. In Sweden and Finland, thegap in reading between a 15-yearold student at the bottom end
and the average student is theequivalent of more than three yearsof schooling.

complaints, and fewer children
reporting very low life satisfaction.
None of the countries with low
gaps has traded equality off against
minimum standards.

FI
NO
CH

NL
AU

SI

IE
EE

DK

AT

DE

Lower child well-being

This Report Card has documented
the extent to which children at thebottom are allowed to fall behind
their peers in rich countries.

health or life satisfaction. Figures
1–4 showed that, for each domainof child well-being, outcomes are
better in countries with lower levels
of inequality.

Child well-being outcomes

When are gaps too big?

SK
BG

IT

BE
LU
FR

UK
IS
LV
CZ
CA SE PT
HR
ES
HU
PL LT
GR
MT
US
RO

IL
TR

Higher inequality

Lower inequality

Inequality in child well-being
R-squared=0.80
Source: see page 44.

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C O N C L U S I O N

None of this is to underestimate
the challenges that can be faced inaddressing the issues explored inthis Report Card. However, the factthat children fall less far behind insome countries than in others
demonstrates that large gaps are
not inevitable.

How inequality affects childwell-being
Inequalities in the ‘adult world’
often impact on the ‘children’s
world’. Section 7 documents thestrong association between family
background and children’s
outcomes. This strong andpersistent social gradient is linked
to overall societal inequality, which
affects the extent to which children
are left behind.
It may, therefore, be the case that,for some countries, further
progress in reducing inequalities inchild well-being will require broadsocial and economic inequalities tobe addressed. Figure 31 shows therelationship between the mean
proportion of children at the very

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Figure 31 Income inequality and child well-being outcomes
Higher child well-being

Governments, of course, face many
competing demands on resources.
Yet it is precisely because
childhood is such a formative but
short stage in the life course thattaking children’s rights seriouslymeans acting with urgency toaddress the disadvantages facedby those children who are falling
furthest behind.

FI
CH
EE
LV

UK
ES

AU

AT

PT
LT

HR
CA

GR
IT

US

Lower child well-being

8

Child well-being outcomes (z-scores)

S E C T I O N

IL

FR

DK
IE
DE

SI

MT
CZ

HU
PL

NO

NL

BE
SK

LU

IS
SE

RO

BG

TR

Higher inequality

Lower inequality
Gini coefficient

R-squared=0.33
Source: see page 44. Solt, F. (2014). 'The Standardized World Income Inequality
Database (SWIID) Version 5.0'.

bottom of our four domains andoverall income inequality, as
measured by the Gini coefficient.
Indeed, as Figure 31 shows, in themain those societies with moreequal income distributions also
tend to be those that do better at
minimizing poor child well-being
outcomes (top-right quadrant).

Addressing the gaps
The complex and varied policy
frameworks found in rich countries
mean that many different pathways
for reducing bottom-end inequality
exist. But analysis in this Report CardC A R D

1 3

suggests the following principles
and recommendations forgovernments to consider instrengthening child well-being:»» Protect the incomes ofhouseholds with the poorest
children. Boosting employment
opportunities for parents,
implementing progressive
taxation and effective service
provision all have a role to play.
However, it is evident that large
income gaps tend to go hand inhand with less-extensive socialtransfer systems.

S E C T I O N»» Focus on improving the
educational achievements ofdisadvantaged learners. The
Convention on the Rights of theChild requires recognition not justof the right to education, but also“achieving this right progressively
and on the basis of equal
opportunity”. This means
preventing children from falling
far behind in their educational
achievement. Evidence from the
PISA surveys shows that there isno inevitable trade-off between
reducing achievement gaps andoverall outcomes, and so thisagenda can be both fair andeffective.

»» Promote and support healthy
lifestyles for all children. Promoting
healthy lifestyles at an early age islikely to pay short- and long-term
dividends, but the fact that suchlarge relative child health gaps
exist in many countries is a cause
for concern. This is particularly sofor inequalities in physical activity,
given that these seem more tightly
bound to inequalities in income.
This would suggest that there isparticular scope for governments
to do more to open up
opportunities for less-affluent
children to participate in physicalactivity in and out of school.
Evidence from the EU-SILC showsthat low income is a barrier toparticipation in extra-curricular
activities in European schools.

»» Take subjective well-being
seriously. Data gathered over a
period of more than 10 years for
the HBSC survey show stable
patterns of inequality inchildren’s life satisfaction. While
this stability confirms that
subjective well-being data reveal
meaningful information aboutchildren’s lives in rich countries,
the fact that some countries
have had persistently large gaps
is a cause for concern. Moreover,the findings that children withlow life satisfaction are more
likely to be exposed to risky
health behaviours and outcomesunderlines the fact that
subjective well-being also
matters for health and education.

»» Place equity at the heart of childwell-being agendas. The leaveno-one-behind principle should
form the foundation of futuresocial strategies. The evidence
presented in this Report Cardsuggests that to improve overall
child well-being the mostdisadvantaged must not beignored.

Better monitoring andmeasurement of child wellbeing
Producing better data for informed
public debate and a morecomprehensive picture of childwell-being is essential. To this end
we recommend:

8

C O N C L U S I O N»» The availability, timeliness andusefulness of information about
the well-being of children in richcountries should be improved. Aspart of this process, governments
and national statistical agencies
should continue to work together
more closely to harmonize
surveys, wherever possible, inorder to allow for fruitful crossnational comparison of child wellbeing outcomes and to foster
cross-national policy learning.

»» Data sets should track children
through different stages of theirlife. Such analysis is particularly
powerful for an exploration of thetemporality of child well-being
and the factors that shape childwell-being. Governments should
increase their support for theselongitudinal data sources.

»» Children’s voices should be built
into data-collection processes.
While children’s voices are heard
more clearly than ever before in
the key data sets used in thisReport Card, further efforts canstill be made to capture childderived measures of well-being
more systematically and tounderstand better the particular
contexts in which child well-being
improves and worsens. Children
need to be able to shape thequestions asked in surveys of
their own lives and well-being.

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INTERNATIONAL ABBREVIATIONSInternational abbreviations (ISO) for
countries covered in the Report Card
AT

Austria

AU

Australia

BE

Belgium

BG

Bulgaria

CA

CanadaCH

Switzerland

CL

Chile

CY

CyprusCZ

Czech Republic

DE

Germany

DK

Denmark

EE

Estonia

ES

Spain

FI

Finland

FR

FranceGR

GreeceHR

Croatia

HU

Hungary

IE

IrelandIL

IsraelIS

Iceland

IT

Italy

JP

Japan

KR

Republic of Korea

LT

Lithuania

LU

Luxembourg

LV

Latvia

MT

Malta

MX

MexicoNL

Netherlands

NO

NorwayNZNew Zealand

PL

PolandPT

PortugalRO

RomaniaSE

SwedenSI

SloveniaSK

Slovakia

TR

TurkeyUK

United Kingdom

US

United States

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DATA SOURCES – THE LEAGUE TABLES»» Republic of Korea: Household andLeague Table 1 – Income

Income Expenditure Survey and FarmHousehold Economy Survey 2013;

Data refer to children aged 0 to 17.
Sources: The calculations for League
Table 1 are based on micro-data from theEuropean Union Statistics on Income andLiving Conditions (EU-SILC) 2013 forEuropean Union countries and Iceland,
Norway and Switzerland.

»» Turkey: Income and Living Conditions
Survey 2013;»» United States: Current Population
Survey 2013, Annual Social andEconomic Supplement (from
Luxembourg Income Study).

For the remaining countries:»» Australia: Household, Income andLabour Dynamics in Australia 2013;»» Canada: Canadian Income Survey(CIS) 2013. The 2007 estimates (Figure5) are based on the Survey of Incomeand Labour Dynamics (SLID) 2007
(from Luxembourg Income Study).
The CIS and the SLID use different
methodologies, and so the results are
not directly comparable;»» Chile: La Encuesta de Caracterización
Socioeconómica Nacional (CASEN)
2011;»» Israel: Household Expenditure Survey
2012 (from Luxembourg Income
Study);»» Japan: Ministry of Health, Labour andWelfare’s Comprehensive Survey of
Living Conditions 2013;

League Table 2 – Education
Data refer to children aged 15 (between
15 years 3 months and 16 years 2 months).
Source: The calculations for League
Table 2 are based on micro-data from theOECD Programme for International
Student Assessment (PISA) 2012.
Mexico and Turkey are excluded from themain ranking because of low school
enrolment rates of 15–19-year-olds in2011 (56 per cent in Mexico and 64 percent in Turkey).*More detailed information on the OECDPISA survey can be found at:www.oecd.org/pisa and in OECD (2014).
PISA 2012 Technical Report, OECD
Publishing, Paris.

»» Mexico: Household Income andExpenditure Survey 2012 (from
Luxembourg Income Study);»» New Zealand: Household Economic
Survey 2013/2014 (estimates takenfrom B. Perry, Household Incomes in
New Zealand: Trends in indicators ofinequality and hardship, 1982 to 2014,
New Zealand Ministry of Social
Development, Auckland, 2015);*

http://www.oecd.org/edu/educationataglance2013-countrynotesandkeyfacttables.htm

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League Table 3 – Health andLeague Table 4 – Life satisfaction
Data refer to children aged 11, 13 and 15,
except in Australia (age 13–14).
Source: The calculations for
League Table 3 and for League Table 4
are based on micro-data from the
Health Behaviour in School-aged Children(HBSC) 2013/2014.
Data from the 2009/2010 cycle of the
HBSC are used for Israel, Turkey and theUnited States.
Detailed information on HBSC can befound at: www.hbsc.org
Identical survey questions from the 2014
Australian Child Wellbeing Project (ACWP)
are used for Australia.
For more information about ACWP see:www.australianchildwellbeing.com.au

League Table 5
League Table 5 summarizes League
Tables 1– 4 and thus uses all the above
sources.

DATA SOURCES – THE BACKGROUND PAPERS

The original research for this report,
including further methodologicalexplanations, can be found in the
Innocenti Working Papers detailed below
and available at www.unicef-irc.org
Aleman-Diaz, A., E. Toczydlowska, J.
Mazur, D. Frasquilho, M. Melkumova andG. Holmqvist (2016). ‘Why Do Inequalities
Matter? A look at the evidence’, Innocenti
Working Paper 2016-06, UNICEF Office of
Research – Innocenti, Florence.
Bruckauf, Z. (2016). ‘Falling Behind:Socio-demographic profiles of
educationally disadvantaged youth.
Evidence from PISA 2006–2012’, Innocenti
Working Paper 2016-11, UNICEF Office of
Research – Innocenti, Florence.
Bruckauf, Z. and Y. Chzhen (2016).
‘Education for All? Measuring inequality ofeducational outcomes among 15-yearolds across 39 industrialized nations’,
Innocenti Working Paper 2016-08, UNICEF
Office of Research – Innocenti, Florence.
Bruckauf, Z. and Y. Chzhen (2016).
‘Poverty and Children’s Cognitive
Trajectories: Evidence from the UK
Millennium Cohort Study’, Innocenti
Working Paper 2016-14, UNICEF Office of
Research – Innocenti, Florence.
Chzhen, Y., E. Toczydlowska and S. Handa(2016). ‘Child Poverty Dynamics andIncome Mobility in Europe, 2010–2013’,
Innocenti Working Paper 2016-16, UNICEF
Office of Research – Innocenti, Florence.

Chzhen, Y., Z. Bruckauf, K. Ng, D. Pavlova,
T. Torsheim and M. Gaspar de Matos(2016). ‘Inequalities in Adolescent Healthand Life Satisfaction: Evidence from the
Health Behaviour in School-aged Children
study’, Innocenti Working Paper 2016-09,
UNICEF Office of Research – Innocenti,
Florence.
Elgar, F.J. and C. Currie (2016). ‘Early-life
Exposure to Income Inequality andAdolescent Health’, Innocenti Working
Paper 2016-07, UNICEF Office of Research– Innocenti, Florence.
Toczydlowska, E. (2016). ’Children in the
Bottom of Income Distribution in Europe:
Risks and composition’, Innocenti Working
Paper 2016-12, UNICEF Office of Research– Innocenti, Florence.
Toczydlowska, E., Y. Chzhen, Z. Bruckauf
and S. Handa (2016). ‘Income Inequality
among Children in Europe 2008–2013’,
Innocenti Working Paper 2016-15, UNICEF
Office of Research – Innocenti, Florence.
Walsh, S.D., Z. Bruckauf and T. Gaspar(2016). ‘Adolescents at Risk:
Psychosomatic health complaints, low life
satisfaction, excessive sugar consumption
and their relationship with cumulative risk
behaviours’, Innocenti Working Paper
2016-13, UNICEF Office of Research –Innocenti, Florence.

Chzhen, Y., I. Moor, W. Pickett, G. Stevens
and E. Toczydlowska (2016). ‘Family
Affluence and Inequality in Adolescent
Health and Life Satisfaction: Evidence
from the HBSC study 2002–2014’,
Innocenti Working Paper 2016-10, UNICEF
Office of Research – Innocenti, Florence.

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REFERENCES

1. OECD (2015). In it Together: Why lessinequality benefits all, OECD Publishing,Paris.
2. Cingano, F. (2014). ‘Trends in Income
Inequality and its Impact on Economic
Growth’, OECD Social, Employment andMigration Working Papers, No. 163, OECD
Publishing, Paris; OECD (2014). ‘Does
Income Inequality Hurt Economic
Growth?’, OECD Focus on Inequality and
Growth, December 2014; Wilkinson, R.
and K. Pickett (2009). The Spirit Level,
Penguin Books, London.
3. UNICEF (2010). ‘The Children Left
Behind: A league table of inequality inchild well-being in the world’s richcountries’, Innocenti Report Card 9,
UNICEF Office of Research, Florence;
Stewart, F. (2013). ‘Approaches towards
Inequality and Inequity: Concepts,
measures and policies’, UNICEF Office of
Research Discussion Paper 2013-01,
UNICEF Office of Research, Florence.
4. UNICEF (2010). ‘The Children Left
Behind: A league table of inequality inchild well-being in the world’s richcountries’, Innocenti Report Card 9,
UNICEF Office of Research, Florence, p. 3.
5. Toczydlowska, E., Y. Chzhen, Z.
Bruckauf and S. Handa (2016). ‘Income
Inequality among Children in Europe
2008–2013’, Innocenti Working Paper
2016-15, UNICEF Office of Research –Innocenti, Florence.
6. UNICEF (2013). ‘Child Well-being in RichCountries: A comparative overview’,
Innocenti Report Card 11, UNICEF Officeof Research, Florence; see also Table 4.1
in Bradshaw, J. (2015). ‘Child Poverty andChild Well-being in International
Perspective’, in E. Fernandez, A. Zeira, T.
Vecchiato and C. Canali (eds), Theoreticaland Empirical Insights into Child andFamily Poverty, Springer International
Publishing, Cham, Switzerland, pp. 59–70.

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7. Bruckauf, Z. and Y. Chzhen (2016).
‘Education for All? Measuring inequality ofeducational outcomes among 15-yearolds across 39 industrialized nations’,
Innocenti Working Paper 2016-08, UNICEF
Office of Research – Innocenti, Florence.
8. Chzhen, Y., I. Moor, W. Pickett, G.
Stevens and E. Toczydlowska (2016).
‘Family Affluence and Inequality in
Adolescent Health and Life Satisfaction:
Evidence from the HBSC study 2002–
2014’, Innocenti Working Paper 2016-10,
UNICEF Office of Research – Innocenti,
Florence.
9. Currie, C., J. Inchley, M. Molcho, M.
Lenzi, Z. Veselska and F. Wild (eds) (2014).
Health Behaviour in School-aged Children(HBSC) Study Protocol: Background,methodology and mandatory items for the
2013/14 survey, Child and Adolescent
Health Research Unit, University of
St Andrews.
10. Aleman-Diaz, A., E. Toczydlowska, J.
Mazur, D. Frasquilho, M. Melkumova andG. Holmqvist (2016). ‘Why Do Inequalities
Matter? A look at the evidence’, Innocenti
Working Paper 2016-06, UNICEF Office of
Research – Innocenti, Florence.
11. Elgar, F.J. and C. Currie (2016).
‘Early-life Exposure to Income Inequality
and Adolescent Health’, Innocenti Working
Paper 2016-11, UNICEF Office of Research– Innocenti, Florence.
12. Chzhen, Y., Z. Bruckauf, K. Ng, D.
Pavlova, T. Torsheim and M. Gaspar deMatos (2016). ‘Inequalities in Adolescent
Health and Life Satisfaction: Evidence
from the Health Behaviour in School-agedChildren study’, Innocenti Working Paper
2016-09, UNICEF Office of Research –Innocenti, Florence.
13. ibid.

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14. Walsh, S.D., Z. Bruckauf, Y. Chzhen
and T. Gaspar (2016). ‘Adolescents at Risk:
Psychosomatic health complaints, low life
satisfaction, excessive sugar consumption
and their relationship with cumulative risk
behaviours’, Innocenti Working Paper
2016-13, UNICEF Office of Research –Innocenti, Florence.
15. OECD (2015). In it Together: Why lessinequality benefits all, OECD Publishing,Paris.
16. OECD (2011). Divided We Stand: Why
inequality keeps rising, OECD Publishing,Paris; Corak, M. (2013). ‘Income Inequality,
Equality of Opportunity, andIntergenerational Mobility’, Journal of
Economic Perspectives, vol. 27, no. 3,
pp. 79–102.
17. ibid., p. 40.
18. The very bottom of the distribution isdefined as having a score that is below
the mean of the bottom half of the
distribution.
19. Chzhen, Y., I. Moor, W. Pickett, G.
Stevens and E. Toczydlowska (2016).
‘Family Affluence and Inequality in
Adolescent Health and Life Satisfaction:
Evidence from the HBSC study 2002–
2014’, Innocenti Working Paper 2016-10,
UNICEF Office of Research – Innocenti,
Florence.

ACKNOWLEDGEMENTS

The Innocenti Report Card 13 project wascoordinated by the UNICEF Office of
Research – Innocenti and assisted by apanel of advisors and reviewers.
Research was completed at the end of
November 2015.

Heather Joshi (Institute of Education,
University College London)

The full text and the background papers
to this report can be downloaded fromthe UNICEF Office of Research website:www.unicef-irc.org

Denisa Sologon (Luxembourg Institute ofSocio-Economic Research (LISER))

Research and data analysis
Zlata Bruckauf (Consultant, UNICEF Officeof Research)
Yekaterina Chzhen (Social and Economic
Policy Specialist, UNICEF Office of
Research)
Sudhanshu Handa (Chief, Social andEconomic Policy Unit, UNICEF Office of
Research)
John Hudson (Independent Consultant,
University of York)
Stefan Kühner (Independent Consultant,
University of York)
Emilia Toczydlowska (Consultant, UNICEF
Office of Research)

Advisory board
Mario Biggeri (University of Florence)Francesca Borgonovi (Organisation for
Economic Co-operation and Development)
Jonathan Bradshaw (University of York)

Eric Marlier (Luxembourg Institute ofSocio-Economic Research (LISER))
Kate Pickett (University of York)

Russell Viner (University College London)

Health Behaviour in School-agedChildren (HBSC) Technical Committee
Aixa Aleman-Diaz (University of
St Andrews)
Michal Molcho (National University of
Ireland, Galway)
Torbjorn Torsheim (University of Bergen)

UNICEF advisors
Marta Arias Robles (Specialist, Advocacy
and Child Rights Education, UNICEF
Private Fundraising and Partnerships)
Prerna Banati (Chief, Programme andPlanning, UNICEF Office of Research)
Sarah Cook (Director, UNICEF Officeof Research)
Goran Holmqvist (Associate Director,
UNICEF Office of Research)
Dominic Richardson (Senior Education
Specialist, UNICEF Office of Research)
Dale Rutstein (Chief, Communication Unit,
UNICEF Office of Research)

Candace Currie (University of St Andrews)
Frank Elgar (McGill University)
David Gordon (University of Bristol)Anne-Catherine Guio (Luxembourg
Institute of Socio-Economic Research(LISER))

Administrative support at the UNICEF
Office of Research was provided by Cinzia
Iusco Bruschi and Laura Meucci.
Production was overseen by Eve Leckey.

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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

Graphics: MCC Design, UK (mccdesign.com)
Printed by:

Innocenti Report Card 13, 2016
Fairness for Children:
A league table of inequality inchild well-being in rich countries

UNICEF Office of Research – Innocenti
Piazza SS. Annunziata, 1250122 Florence, Italy
Tel: +39 055 20 330
Fax: +39 055 2033 220
florence@unicef.org
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ISBN: 978 88 6522 045 0© The United Nations Children’s Fund (UNICEF)
April 2016

ISBN: 978-88-6522-045-0
eISBN: 978-92-1-057893-6

Sales no.: E.16.XX.1