Indicators for early childhood education and care : reconsidering some aspects of the Barcelona target for younger children.
Date: 2022-09-07
Institutions: Joint Research Centre
Subjects: aid to disadvantaged groups, child care, data processing, early childhood, education policy, labour market, participation of women, report, right to health, social indicator, social integration, young person

ISSN 1831-9424 

Indicators for early childhood 
education and care 

Reconsidering some aspects 
of the Barcelona target  
for younger children 

Flisi, Sara 

Blasko, Zsuzsa  

Stepanova, Elena 

2022 

EUR 31184 EN 

This publication is a Science for Policy report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. 
It  aims  to  provide  evidence-based  scientific  support  to  the  European  policymaking  process.  The  contents  of  this  publication  do  not 
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concerning the delimitation of its frontiers or boundaries. 

Contact information  
Sara Flisi 
European Commission – Joint Research Centre 
Via E. Fermi 2749, I-21027 Ispra (VA), Italy 
Sara.FLISI@ec.europa.eu  

EU Science Hub 
https://joint-research-centre.ec.europa.eu 

JRC130350 

EUR 31184 EN 

PDF 

ISBN 978-92-76-55805-7 

ISSN 1831-9424 

doi:10.2760/44338 

KJ-NA-31-184-EN-N 

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© European Union, 2022 

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How to cite this report: Flisi, S., Blasko, Zs. and Stepanova, E., Indicators for early childhood education and care — Reconsidering some 
target  for  younger  children,  Publications  Office  of  the  European  Union,  Luxembourg,  2022, 
aspects  of 
doi:10.2760/44338, JRC130350. 

the  Barcelona 

Contents 

Abstract ................................................................................................................................................................................................................................... 1 

Acknowledgements .......................................................................................................................................................................................................... 2 

Executive summary .......................................................................................................................................................................................................... 3 

1  Introduction ................................................................................................................................................................................................................... 5 

2  An overview of existing ECEC indicators and available data sources at EU level ............................................................ 6 

2.1  Measuring ECEC attendance with EU-SILC .................................................................................................................................... 6 

2.1.1 

The Barcelona target ................................................................................................................................................................... 6 

2.1.2 

Advantages and caveats of EU-SILC in measuring participation in ECEC ................................................. 7 

2.1.3 
The relevance of sample size and confidence intervals in measuring participation in ECEC with 
EU-SILC  ................................................................................................................................................................................................................... 9 

2.2  Measuring ECEC attendance with UOE ......................................................................................................................................... 14 

2.2.1 

The ECEC benchmark ................................................................................................................................................................ 14 

2.2.2 

Advantages and limitations of UOE in measuring participation in ECEC ................................................ 16 

2.3  Moving forward ............................................................................................................................................................................................ 17 

3  Additional considerations to better understand progress in ECEC attendance ............................................................... 18 

3.1  Differentiating by the age of the child ......................................................................................................................................... 18 

3.2  Considering the intensity of care ...................................................................................................................................................... 23 

3.3  Focusing on disadvantaged children .............................................................................................................................................. 26 

4  Conclusions and implications for revising the target ...................................................................................................................... 28 

References .......................................................................................................................................................................................................................... 30 

List of abbreviations and definitions ................................................................................................................................................................. 32 

List of figures ................................................................................................................................................................................................................... 33 

List of tables ..................................................................................................................................................................................................................... 34 

Annex ..................................................................................................................................................................................................................................... 35 

i 

Abstract 

The new European Care Strategy, aimed at ensuring that people in need of care have access to affordable care 
of good quality at all stages of their life, includes a proposal for a Council Recommendation for the revision of 
the  so-called  Barcelona  targets  on  early  childhood  education  and  care  (ECEC).  The  Barcelona  targets  were 
adopted  by  the  European  Council  in  2002  with  the  aim  of  removing  disincentives  to  female  labour  force 
participation by enhancing the provision of ECEC. This JRC report provides evidence in support of the revision of 
the Barcelona target for  children under 3 years  of  age, and  of the development  of  possible complementary 
indicators that can underpin the monitoring of country progress towards the Barcelona objectives. It provides 
an  overview  of  the  existing  indicators  used  in  the  Commission  to  monitor  participation  in  early  childhood 
education and care for children below 3, and of the data sources available for this purpose at EU level. It also 
presents possible options for a more comprehensive monitoring of the progress towards reaching the target: (i) 
by paying special attention to the ECEC attendance of children aged 1 to 2; (ii) by taking intensity of care into 
account;  and  (iii)  by  paying  special  attention  to  children  from  socially  disadvantaged  families.  The  report 
concludes  by  offering  a  number  of  recommendations  for  ensuring  data  quality  and  helping  more  adequate 
monitoring and interpretation of the Barcelona indicator.  

1 

Acknowledgements 

This report was produced by JRC Unit I.1 "Monitoring, Indicators & Impact Evaluation" to support the Directorate-
General for Justice and Consumers (DG JUST) in the preparation of a Council Recommendation for the revision 
of the Barcelona targets under the new European Care Strategy.  

The authors would like to thank Katja Lenzing, Emanuela Tassa and Greet Vermeylen (DG JUST) for their useful 
comments and suggestions to improve earlier versions of this report, as well as Estefania Alaminos Aguilera, 
Emilio Di Meglio, Sigita Geske, and Malgorzata Stadnik (DG ESTAT) for providing supporting information.  

Authors 

Flisi Sara, JRC.I.1, Sara.FLISI@ec.europa.eu   

Blasko Zsuzsa, JRC.I.1, Zsuzsa.BLASKO@ec.europa.eu    

Stepanova Elena, JRC.I.1, Elena.STEPANOVA@ec.europa.eu 

2 

Executive summary 

Policy context 

A proposal for a Council Recommendation for the revision of the so-called Barcelona targets on early childhood 
education and care (ECEC) forms part of a new European Care Strategy, aimed at ensuring that people in need 
of care have access to affordable care of good quality at all stages of their life. The Barcelona targets were 
adopted  by  the  European  Council  in  2002  with  the  aim  of  removing  disincentives  to  female  labour  force 
participation by enhancing the provision of ECEC. This JRC report provides evidence in support of the revision of 
the Barcelona target for children  under 3 years of age,  and of the development  of  possible complementary 
indicators that can underpin the monitoring of country progress towards the Barcelona objectives. It provides 
an overview of the existing indicators used in the Commission to monitor participation in ECEC for children in 
this age group, and of the data sources available for this purpose at EU level. It also presents possible options 
for a more comprehensive monitoring of progress towards reaching the target: (i) by paying special attention 
to the ECEC attendance of children aged 1 to 2; (ii) by taking intensity of care into account; and (iii) by paying 
special attention to children from socially disadvantaged families. The report concludes by offering a number 
of recommendations for ensuring data quality and helping more adequate monitoring and interpretation of the 
Barcelona indicator. The report builds on previous work carried out on the topic by the JRC, in particular in Flisi 
and Blasko (2019) and Flisi et al. (2016). 

Main findings and conclusions 

The main conclusions from the analyses presented in this report are the following: 

-

-

-

For the sake of continuity, and considering its unique features, EU-SILC should remain as the data source
for monitoring progress in ECEC attendance for children aged below 3. Moreover, EU-SILC is  the only data
source that allows the calculation of additional sub-indicators that this report suggests monitoring for a
better  understanding  of  how  the  national  ECEC  systems  support  maternal  employment  and  child
development.

However, special attention needs to be given to data quality issues as the number of children in the national
samples is relatively low and has been sharply decreasing in several countries. To facilitate the assessment
of data quality, reporting of data and metadata should also be improved.

To better understand how the progress in ECEC attendance serves the improvement of mothers’ access to
the  labour  market,  the  report  investigates  the  option  to  monitor  three  particular  aspects  –  with  three
corresponding sub-indicators – of ECEC attendance:

o A sub-indicator that provides ECEC attendance rates for children aged 1-2 would be helpful to focus
on families that are usually not any more supported by the national parental leave systems, and are
therefore most in need of institutional care.

o To better consider the usefulness of the care services provided from the perspective of parental

labour market participation, an additional sub-indicator should only include ECEC participation of at
least medium (20-29 hours per week) or even only high (30+ hours per week) intensity.

o Finally, monitoring ECEC attendance of children from AROPE households would provide a tool to

understand to what extent national ECEC systems care for the most socially disadvantaged children.

Recommendations 

Based on these conclusions, the report makes a number of specific recommendations to ensure data quality 
and a better access to relevant statistics on ECEC participation in Europe. 

Recommendations to ensure data quality and make relevant statistics and accuracy measures accessible for 
users: 

—  Ensuring  adequate  sample  sizes  is  fundamental  to  guarantee  the  good  quality  of  the  indicators;  it  is 
therefore necessary to closely monitor the changes in the number of children aged 0-2 in the national EU-
SILC samples, and take the necessary steps to avoid further decreases to an extent that would harm data 
quality. 

3 

—  Better documentation of non-response rates to the survey in general, as well as to the questions relevant 

for ECEC indicators in particular, with a disaggregation by household type is needed., 

—  Sample sizes  as well  as  confidence intervals around the  estimates for each country should  be reported 

alongside the main indicators. 

Recommendations to better inform policy-makers and interested users about key aspects of ECEC enrolment: 

—  In order to support interpretation and comparison of data (including with national sources), more detailed 
metadata on ECEC indicators should be provided. In particular, the medata should include  a mapping  of 
institutional types considered as an ECEC service in each country over time, both in the original language 
and in English, with information on inclusion criteria for the programmes, theoretical duration and starting 
age. 

—  The  share  of  0-2-year-old  children  enrolled  in  ECEC  institutions  (main  Barcelona  indicator)  should  be 
directly  available  in  the  Eurostat  website,  as  well  as  on  the  Gender  Equality  Strategy  (GES)  Monitoring 
Portal, with no further calculations needed by the user, as is the case now for the ilc_caindformal dataset.  

Additional sub-indicators recommended for a closer monitoring of progress towards the main policy objectives: 

—  - The present report recommends developing and monitoring the following sub-indicators:  

o 

o 

o 

the share of 1-2-year-old children enrolled in ECEC; 

the share of 0-2-year-old children participating in ECEC for at least 20 hours per week, or a level that 
can ensure full labour market participation of the parents; 

the share of children from AROPE and non-AROPE households enrolled in ECEC.  

—  If  adopted  in  the  Recommendation,  the  additional  sub-indicators  analysed  in  this  report  should  also  be 

reported on a yearly basis both in the Eurostat website and as part of the GES Monitoring Portal.  

Related JRC work 

This report builds on previous JRC analytical work on early childhood education and care, such as: 

Flisi,  S.,  and  Zs.  Blasko,  A note on early childhood education and care participation by socio-economic 
background, EUR 29835, Publications Office of the European Union, Luxemburg, 2019, ISBN 978-92-76-09694-
8, doi:10.2760/315380, JRC117663, and 

Flisi,  S.,  Meroni,  E.C.,  and  E.  Vera-Toscano,  Indicators for early childhood education and care,  EUR  28132, 
Publications Office of the European Union, Luxemburg, 2016,. doi:10.2791/550118. 

4 

 
 
 
1 

Introduction 

Early childhood education and care (ECEC) has been at the heart of EU policies for  over two decades. On one 
hand, high-quality early childhood education and care is considered to lay the essential foundations for later 
success  in  life,  in  terms  of  education,  social  integration,  personal  development  and  employability  (2011/C 
175/03). On the other hand, the availability, accessibility and affordability of high quality childcare facilities are 
crucial for enabling women and men with caring responsibilities to participate in the labour market (COM(2018) 
273 final). 

Acknowledging these benefits for the individual as well as for society as large, the European Commission has 
for long been monitoring attendance of ECEC in the EU Member States (MSs). In 2002, the European Council 
set the so-called “Barcelona targets", establishing that Member States should remove disincentives to female 
labour force participation and strive by 2010 to provide childcare to at least 33% of children below 3 years of 
age, and to 90% of children between 3 and the mandatory school age (1). In 2009, a specific “ECEC benchmark” 
was adopted under the strategic framework for European cooperation in education and training (ET2020), with 
the recommendation that at least 95% of children between the age of 4 and the age for compulsory primary 
education  participate  in  early  childhood  education  and  care.  This  goal  was  set  “with  a  view  to  increasing 
participation in high-quality early childhood education as a foundation for later educational success, especially 
in the case of those from disadvantaged backgrounds” (2). Both sets of targets were almost reached by 2019 
at the EU level, but with considerable variations across Member States.  

In 2021, the European Education Area strategic framework for 2021-2030 renewed the commitment for early 
childhood education and care, setting a EU-level target of at least 96% of children between 3 years  and the 
starting age for compulsory primary education participating in ECEC by 2030.  

Both the Gender Equality Strategy (COM(2020) 152 final) and the European Pillar of Social Rights Action Plan 
announced initiatives  on the revision  of the Barcelona targets  on early childhood education  and  care. In her 
State of the Union speech on 15 September 2021, President von der Leyen announced a European Care Strategy 
to  support  men  and  women  in  finding  the  best  care  and  the  best  life  balance  for  them.  The  European  Care 
Strategy aims to ensure that people in need of care have access to affordable care of good quality at all stages 
of  their  life.  A  proposal  for  a  Council  Recommendation  for  the  revision  of  the  Barcelona  targets  on  early 
childhood education and care forms part of this Care Strategy.  

This  report  provides  evidence  in  support  of  the  revision  of  the  Barcelona  targets  and  the  development  of 
complementary indicators for children  below 3 years  of age. It first provides  an  overview  (Section 2)  of the 
existing indicators used in the Commission to monitor participation in early childhood education and care for 
children under 3 years of age, and of the data sources available for this purpose at EU level.  Section 3 then 
looks into possible options for developing additional indicators to better support the interpretation of the main 
Barcelona  indicators.  Specifically,  Section  3.1  considers  the  possibility  of  calculating  the  same  indicator  but 
restricting  the  target  age  group  from  0-2  to  1-2-year-old  children.  Section  3.2  discusses  the  importance  of 
ECEC intensity, and considers the possibility to take this aspect into account to better understand how ECEC 
services support maternal employment in the various countries.  Section 3.3 then looks into the possibility of 
monitoring  ECEC  participation  among  children  from  a  disadvantaged  background.  Section  4  concludes,  and 
offers recommendations for data provision and interpretation. 

The present report builds on previous work carried out on the topic by the JRC, in particular in Flisi and Blasko 
(2019) and Flisi et al. (2016). 

European Council (2002). Presidency conclusions. Barcelona European Council 15-16 March 2002. 

(1) 
(2)   OJ of the EU, 2009/C 119/02. 

5 

 
                                         
2  An overview of existing ECEC indicators and available data sources at EU level 

The two ECEC indicators presented in Section 1 are based on the two main sources of data currently available 
to monitor ECEC enrolments across EU Member States, i.e. the EU Survey on income and living conditions (EU-
SILC), and the UNESCO-UIS/OECD/Eurostat (UOE) data collection. The next sections provide more information 
on the features and definitions of these data sources.  

2.1  Measuring ECEC attendance with EU-SILC 

2.1.1  The Barcelona target 

One of the Barcelona targets set in 2002 by the European Council established that the Member States should 
remove disincentives to female labour force participation and strive by 2010 to provide childcare to at least 
33% of children below 3 years of age. The indicators for monitoring the Barcelona childcare targets were agreed 
in 2004 by the Employment Committee, and the EU Survey on income and living conditions was chosen as the 
European statistical source for measuring them.  

EU-SILC is the EU reference source for comparative statistics on income distribution and social inclusion at the 
European level. The survey provides annual data for the 27 European Union countries, as well as for Iceland, 
Norway, Switzerland, United Kingdom and Turkey. 

The reference population in EU-SILC includes all private households and their current members residing in the 
territory of the countries at the time of data collection. Persons living in collective households and institutions 
are generally excluded from the target population. All household members are surveyed, but only those aged 
16 and more are interviewed. 

The Barcelona target based on SILC data is practically defined as “children cared for by formal arrangements 
other than by the family up to 30 hours a usual week / 30 hours or more a usual week as a proportion of all 
children in the same age group”. Formal arrangements include all kinds of care organised and/or controlled by 
a structure (whether public or private) (3), i.e.: 

—  pre-school or equivalent,  

—  compulsory education,  

—  centre-based services outside school hours, 

—  collective  crèche  or  another  day-care  centre,  including  family  day-care,  and  professional  certified  child-

minders. 

Data  for  these  indicators  are  consistently  reported  by  Eurostat  under  the  ilc_caindformal  (or  tps00185) 
dataset (4). 

As shown in Figure 1, the 33% target for children below 3 years of age was reached in the EU as a whole in 
2019 (5).  In  that  year,  35%  of  children  in  this  age  group  were  cared  for  by  formal  arrangements,  but  with 
significant differences between Member States. 15 MSs were below the target, and 12 MSs were above, from 
which in 8 countries the attendance rate was above 50%. 

(3) Care provided by child-minders without any structure between the carer and the parents (direct arrangements) has been excluded from

the definition of “formal care” in order to take into account only childcare recognised as fulfilling certain quality criteria.

(4) See https://ec.europa.eu/eurostat/databrowser/product/view/ILC_CAINDFORMAL and https://ec.europa.eu/eurostat/web/products-

datasets/-/tps00185. 

(5) While data are already available for 2020, this year saw a disruption both in the provision of ECEC services due to the widespread
lockdowns in the first months the COVID-19 pandemic, and in the way the EU-SILC survey was implemented, with a limited use of 
face-to-face interviews. This report therefore considers as reference the last available year before the outbreak of the pandemic, i.e.
2019.

6 

Figure 1. ECEC enrolment rate for children aged 0-2, EU-SILC (2019)  

e
t
a
r

t
n
e
m
o
r
n
E

l

65 66

60

57

56

53 53

51

47

41

38 38

Barcelona target for age group 0-2 (33%)

35

31 31 32 32

28

26 27

23

20

14 16 17

10

6

7

70

60

50

40

30

20

10

0

CZ SK PL RO HR HU BG AT

IT

LT LV CY DE EE EL EU-
27

FI MT IE

SI FR PT SE BE ES LU NL DK

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019.  
Notes: Countries are ordered by increasing rates of ECEC participation.  

2.1.2  Advantages and caveats of EU-SILC in measuring participation in ECEC 

Flisi and Blasko (2019), Flisi et al. (2016), Keck & Saraceno (2011) and Harrison Villalba et al. (2012) provide 
detailed overviews of the advantages and limitations of using EU-SILC to measure participation in ECEC (6).  

Based on these sources, the main advantages of this data source are the following: 

—  EU-SILC collects timely and comparable cross-sectional data in each EU MS on a yearly basis. Information 
is  mainly  collected  at  the  household  level,  and  gives  sufficient  details  about  young  children  in  the 
households to establish their enrolment status in ECEC services. 

—  Moreover, EU-SILC allows to distinguish between different types of formal (and informal) arrangements. 
Such differentiation – that is normally not available in other official statistics, such as UOE administrative 
data – can contribute to a better understanding of the ECEC structure and the implications for policy.  

—  The survey provides information on the intensity of care in a “normal week”, i.e. on the time spent in each 
of the different types of arrangements. This is an important aspect, as it allows to understand how different 
arrangements are combined.  

—  EU-SILC provides the unique opportunity to carry out more complex analyses, and in particular to relate 
ECEC attendance to family and household characteristics; this can give important insights into what factors 
affect access to and participation in ECEC. 

The two latter points are particularly important as they make EU-SILC the only data source that allows a better 
understanding  of  how  the  ECEC  system  serves  those  children  and  families  that  are  in  the  biggest  need  of 
institutional care and / or are likely to benefit the most from it. As Section 2.3 will explain, it would be particularly 
important to regularly monitor ECEC participation by the age of the child as well as by parental socioeconomic 
status, while intensity of care should also be taken into account. These aspects can only be monitored by using 
EU-SILC data, as will be discussed in detail in Section 3. 

While  all  these  are  very  strong  reasons  to  rely  on  EU-SILC  for  monitoring  purposes,  several  conceptual  and 
methodological  problems  related  to  this  data  source  have  also  been  raised.  While  some  of  these  are 
unavoidable as they follow from the nature of the data, others should be addressed and improved as pointed 
out below. A first issue relates to the types of programmes covered by ECEC variables in EU-SILC.  

(6)   This section and the next one draw from and further expand the discussion presented in Flisi and Blasko (2019). 

7 

  
 
 
                                         
 
The  EU-SILC  documentation  (see  e.g.  Eurostat,  2020)  provides  guidelines  and  definitions  for  EU-SILC  target 
variables.  For  ECEC,  this  documentation  describes  the  services  that  should  be  considered  under  each  of  the 
types of formal arrangements mentioned in Section 2.1.1. However, no overview of which national programmes 
are included in each of them is currently provided. National  questionnaires  – in the national language  – can 
sometimes help, but this is far from providing a comprehensive overview of the features of the programmes 
covered or excluded.  

Harrison Villalba et al. (2012) highlight that there is a risk of limited cross-country comparability, since it is not 
clear  whether  the  types  of  formal  childcare  arrangements  captured  by  each  EU-SILC  variable  in  different 
educational systems are comparable, despite the homogenising effort implemented in the survey through the 
documentation mentioned above. The authors show different patterns of response across countries in terms of 
type  of formal care arrangement, and explain that while this  may  be  driven  by the features  of the national 
systems, it can become an issue for the use of the survey to create common indicators for monitoring purposes. 
Differences between the national systems, therefore, call for careful interpretations of the data.  

Moreover, the inclusion of certain national ECEC programmes under the EU-SILC variables might also change 
over  time.  Plantenga  and  Remery  (2009)  report  that  “In  France,  for  example,  the  SILC  data  on  formal 
arrangements  do  not  include  childminders,  (‘assistantes  maternelles’),  who  are  paid  directly  by  parents. 
However, in France, the great majority of childminders must be registered and are therefore considered as a 
form of formal care in the national statistics. This is, in fact, the main form of childcare for very young children.” 
Indeed, as mentioned in the previous section, the general guidelines for EU-SILC explain that care provided by 
child-minders  without  any  structure  between  the  carer  and  the  parents  are  excluded  from  the  definition  of 
formal care considered in the indicator; however, Eurostat metadata for the ilc_cainformal dataset (7) explains 
that for France, “care provided by 'assistantes maternelles' directly paid by the parents, without any organised 
structure between them, is not included in 2005, 2006 and 2007. In order to give a better view of the total 
number of children covered by formal childcare structures it was decided to include them from 2008 onwards”. 
This is also confirmed in Plantenga and Remery (2015).   

The provision of more detailed metadata for the relevant data collection would surely help clarify these aspects, 
and  support interpretation and comparison  of  data, including with national  sources. In particular, data users 
would greatly benefit from a mapping of institutional types considered as an ECEC service in each country over 
time, both in the original language and in English, with information on inclusion criteria for the programmes, 
theoretical duration and starting age (8). A similar mapping exercise would also provide insight into qualitative 
aspects  of  ECEC  provisions  –  such  as  parental  involvement,  monitoring  structure,  quality  assurance 
mechanisms,  general  links  to  national  or  local  regulations,  leadership  and  management  within  the 
arrangements – which as pointed out by Harrison Villalba et al. (2012), are not directly provided in the EU-SILC 
data collection.  

A second possible issue is highlighted by Keck and Saraceno (2011), who warn that EU-SILC makes no distinction 
between  public  and  private-market  childcare  provision,  and  therefore  between  services  financed  publicly  or 
privately. The inclusion of private childcare – especially when not subsidized – may hide inequalities in access 
to  and  quality  of  services,  as  the  lack  of  subsidised  provision  is  likely  to  leave  low-income  parents  without 
accessible and high-quality services. Social inequalities in access to ECEC services can be analysed in EU-SILC 
e.g. by considering the socioeconomic status of the households – as will be discussed in the next section.  

From a statistical perspective, another remark concerns the representativeness of the population of children in 
SILC  (Flisi  et  al.,  2016).  As  a  matter  of  fact,  the  survey  is  meant  to  sample  private  households,  but  not  the 
population of children; this can create some problems regarding representativeness. To take this into account, 
the  Barcelona  target  is  calculated  using  ad-hoc  weights  that  are  supposed  to  adjust  for  the  distribution  of 
children for each year of age and ensure a correct distribution of children by age. These weights should make 
the age distribution of the children covered in the sample similar  to the same information from some more 
reliable external sources (age distribution of children aged 0 to 12 in private households).  Though the use of 
these weights should ensure full comparability of the distribution of children for each year of age, there have 
been cases where problems of over- and under-representation of certain subgroups of individuals have arisen, 
as it seems to be the case in Germany. As shown by Hauser (2008), there is an indication of misrepresentation 
of children by age groups in the German EU-SILC sample: “[...] small children up to the age of four are clearly 

(7)   See https://ec.europa.eu/eurostat/cache/metadata/en/ilc_ca_esms.htm.  
(8)   Eurostat (2021) also highlights that in recent EU-SILC guidelines, “the description of variables has not been updated in line with the 
revised ISCED 2011 classification – which includes definitions of ISCED 01 educational programmes for children under the age of three 
– and the description still refers to ISCED level 0 ‘pre-school’ only (not ISCED 01 and 02) and to children under the age of three as ‘too 
young to be at pre-school’”.  

8 

                                         
under-represented in EU-SILC compared with the microcensus. As age is one of the variables used to calculate 
the weighting of persons in EU-SILC these deviations are particularly in need of explanation. And they can also 
clearly distort the indicators calculated”. In addition, it should also be noted that ensuring representativeness of 
the  distribution  of  children  for  each  year  of  age  does  not  necessarily  guarantee  representativeness  of  the 
distribution of children in ECEC. 

A  last  point  that  is  important  to  raise  relates  to  sample  sizes  and  confidence  intervals;  the  next  section  is 
devoted to this discussion.  

2.1.3  The relevance of sample size and confidence intervals in measuring participation in ECEC with 

EU-SILC 

As EU-SILC is a sample survey, a relevant factor to consider when measuring ECEC participation based on these 
data is the sample size underlying the attendance rates.  

Eurostat  guidelines for publication identify two cell size thresholds for EU-SILC cross-sectional results; when 
the  unweighted  sample is  below  20  observations (or if  non-response for the item concerned  exceeds 50%), 
results cannot be published; with a sample between 20 and 49 observations (or if non-response for the item 
exceeds 20% and is lower than or equal to 50%), results may be published but are to be individually flagged. 
Any sample above 49 is therefore considered to be reliable (9).  

Figure 2 shows the unweighted sample size for children aged 0-2 in EU-SILC surveys across countries and over 
time (see also Table A.1 in the Annex). All sample sizes indicated exceed the described thresholds for reliability; 
however, given the high importance of the Barcelona indicator as a tool to monitor European Member States’ 
progress in providing for young children, it can be argued that even bigger sample sizes can give reasons for 
concern, especially when they form part of a consistently and notably decreasing tendency. 

Figure 2 indeed shows that there is a decreasing trend for the national SILC subsamples of children in the age 
group  of  interest  in  several  countries,  at  least  for  some  parts  of  the  past  10-year  period.  Beside  Malta  and 
Romania,  the  countries  with  the  highest  percentage  drop  (above  40%)  between  2010  and  2019  are  Italy, 
Hungary, Luxembourg, and the Netherlands. 16 countries out of 27 had a decrease above 20%, as shown in 
Table A.1. By the end of the period considered, particularly small sample sizes are available in Malta (falling 
from 277 in 2014 to only 120 in 2019) as well as in Romania (from 153 in 2011 to 102 in 2019, but with 
numbers  below 100 in 2016 and 2017). The tendencies look worrying in  other countries as well; in Italy for 
example, in 2019 only 380 children were included in the subsample in contrast to 1138 in 2011. Undoubtedly, 
the situation requires close monitoring in several countries, while in Malta and Romania one can argue that the 
reliability of the Barcelona indicator can already be questioned.   

These negative tendencies in the number of 0-2-year-old children included in the national SILC samples do not 
seem to be mirrored in the changes observed in the total national sample sizes in the previous years (Table 
A.2) (10), nor appear to reflect comparable trends in the demographic processes of the various countries (11). 

A  final  remark,  also  related  to  the  sample  sizes  underlying  the  attendance  rates,  concerns  the  possibility  to 
compute confidence intervals for these rates.  As also  explained  by  Osier et  al. (2013), as the indicators  are 
based on EU-SILC sample estimates, it would be more appropriate to report them along with standard errors 
and  confidence  intervals,  particularly  if  they  are  used  for  policy  purposes.  Barcelona  indicators  are  used  to 
evaluate the performance of a country,  but also to compare different countries or evaluate changes in rates 
over  time  in  a  country.  To  make  proper  interpretations,  one  needs  to  consider  accuracy  measures  of  the 
published indicators, that is standard errors and confidence intervals. This is the only way to understand whether 
the observed differences are sufficiently big to  be considered as statistically significant, i.e. very likely to be 
linked to real differences though their practical relevance must be assessed. 

(9)   ECEC rates are computed as the share of children in ECEC over the total number of children in a certain age group. The (unweighted) 
sample size considered for the threshold is the denominator in the calculation – that is the number of children in the subgroup – and 
not the numerator – i.e. the number of children in the group that are in ECEC. 

(10)  In several cases, the number of children in the samples appears to decline even when the overall sample size is either stable or declining 
to a much smaller extent. In Italy for example, the 42% decline in the number of 0-2-year-olds in the sample between 2018 and 2019 
was coupled with only a 4% decline in the overall sample size, while in Greece the respective figures were 40 vs 29% in the same year. 
This raises the possibility that families with young children get underrepresented in the samples – possibly due to their disproportionally 
high non-response rates. 

(11)  See Eurostat dataset Population on 1 January by age and sex [DEMO_PJAN__custom_3070064]. 

9 

 
                                         
Figure 2. Number of 0-2-years-old children in the EU-SILC national subsamples (2010-2019) 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2010-2019.  
Notes: The threshold defined by Eurostat for a sample to be reliable is above 49 observations. 

10 

 
 
Sample sizes play a key role when computing standard errors, which are in turn used to calculate confidence 
intervals;  larger  sample  sizes  tend  to  provide  a  more  accurate  reflection  of  the  population  mean.  For  these 
reasons, estimates calculated from low sample sizes must be handled with caution (12). 

Figure 3 presents the Barcelona indicator for 2019 already shown in Figure 1, adding also confidence intervals, 
i.e. an indication of the level of uncertainty in the estimates of the indicators. For example, for the EU-27, there
is a 95% chance that the estimated confidence interval between 33.5 and 36.9% (i.e. the 1.7 percentage points
confidence interval around the estimate of 35.2% participation) contains the real participation rate in the EU.

The confidence intervals calculated for the individual MSs are wider than those calculated for the combined EU 
sample, and therefore call for more caution. At the country level, one can see for example that for a country 
that is considered to be above the 33% target – i.e. Malta – it is not possible to rule out the possibility that the 
target has not been attained, as the confidence interval covers values below this threshold. On the other hand, 
one can also note that there are six Member States – i.e. Lithuania, Latvia, Cyprus, Germany, Estonia and Greece 
– that are considered to be still below the target, but they might have reached the 33% already. Finally, even
though a direct comparison between countries would require the estimation of specific confidence intervals, the
chart clearly shows how differences between countries might often be non-significant, and one should therefore
be careful in e.g. ranking countries in terms of ECEC participation.

Figure 3. ECEC enrolment rate for children aged 0-2 with confidence intervals, EU-SILC (2019)  

80

70

60

50

40

30

20

10

0

e
t
a
r

t
n
e
m
o
r
n
E

l

Barcelona target for age group 0-2 (33 %) 

31 31 32 32

26 27 28

23

20

16 17

14

10

6

7

65 66

60

57

56

53 53

51

47

38

35

CZ SK PL RO HR HU BG AT

IT

LT

LV CY DE EE

EL EU-27MT SI

FR PT SE BE ES LU NL DK

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019. 
Notes: Countries are ordered by increasing rates of ECEC participation. Finland and Ireland are not reported since figures provided in the 
special extraction for these countries were not in line with the standard Barcelona indicator due to differences in the procedure used by 
Eurostat to compute the confidence intervals (CIs). For the interpretation of confidence intervals: non-overlapping CIs between two countries 
suggest  a  95% significant  difference;  overlapping  CIs  show no  clear  evidence  of  a  difference,  but  a  further  significance test would  be 
needed. 

What clearly emerges from Figure 3 is also that confidence intervals vary greatly across countries, and that in 
several cases the countries with relatively low sample sizes, such as Malta, Lithuania or Romania, also show 
the  largest  confidence  intervals.  This  evidence  is  further  reinforced  looking  at  the  evolution  over  time  of 
participation rates and confidence intervals in the period 2010-2019, presented in Figure 4; this shows that in 

(12)  Di  Meglio  et  al.  (2013)  explain  that  “the increased complexity of EU-SILC, the widening of the user community and the increased 
reliance on EU-SILC for policy targeting and evaluation, particularly since the launch of the "Europe 2020" Strategy for smart, 
sustainable and inclusive growth, have enhanced the need for comparable, accurate as well as workable solutions for the estimation 
of standard errors and confidence intervals”.  Until  now,  Eurostat  has  refrained  from  consistently  publishing  standard  errors  and
confidence intervals alongside the official childcare indicators. However, over the last years Eurostat as well as European researchers
have been dedicating increasing attention to the issue of a correct computation of SEs in SILC (see Goedemé, 2013; Di Meglio  et al.,
2013; Osier et al., 2013). EU-SILC is a complex survey involving different sampling designs in different countries, but unfortunately, 
relevant sample design variables are missing in the EU-SILC User Database (Flisi and Blasko, 2019).

11 

 
some countries, ECEC participation rates are measured with increasing uncertainty. In Malta for example, the 
size of the confidence interval was +/- 4 percentage points (p.p.) in the beginning of the period and went up to 
as much as +/- 10 p.p.  by 2019.  Similarly, in Romania the size of the confidence interval was +/- 3.7 p.p. in 
2010 and grew to +/- 7.7 p.p. by 2019. 

Figure 4 also suggests that even when a slightly positive trend is found in ECEC participation in a country, year-
to-year changes in country performance are likely to be often non-significant. More relevant evolutions would 
therefore be longer-term, positive trends, as can be observed for example in Belgium or Spain.  

All these examples reinforce two main arguments: 

—  the use of confidence intervals would greatly contribute to a more accurate interpretation of the Barcelona 

indicator; 

—  ensuring adequate sample sizes is fundamental to guarantee good quality of the indicators; it is therefore 
necessary  to  closely  monitor  the  changes  in  the  number  of  children  aged  0-2  in  the  national  EU-SILC 
samples, and consider the consequences of them further decreasing, especially in countries with already 
low numbers such as Malta and Romania. 

12 

 
 
 
Figure 4. ECEC enrolment rate for children aged 0-2 with confidence intervals, EU-SILC (2010-2019) 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2010-2019. 
Notes: Countries are ordered by decreasing rates of ECEC participation in 2019. FI and IE are not reported since figures provided in the 
special extraction for these countries were not in line with the standard Barcelona indicator due to differences in the procedure used by 
Eurostat to compute the confidence intervals. For the same reason, confidence intervals for NL for 2016/2017 are not reported. For the 
interpretation of confidence intervals: non-overlapping CIs between two years suggest a 95% significant difference; overlapping CIs show 
no clear evidence of a difference, but a further significance test would be needed. 

13 

2.2  Measuring ECEC attendance with UOE 

2.2.1  The ECEC benchmark  

The  official  data  source  for  monitoring  the  ECEC  benchmark  adopted  in  2009  within  the  ET  2020  strategic 
framework, targeting children between the age of 4 and the age for starting compulsory primary education, is 
the UOE database on education statistics. UOE is a joint data collection of international statistics on education 
and  training  systems  administrated  by  the  United  Nations  Educational,  Scientific,  and  Cultural  Organisation 
Institute for Statistics (UNESCO-UIS), OECD and Eurostat. It is compiled on the basis of national administrative 
sources, reported by Ministries of Education or National Statistical offices according to international standards, 
definitions and classifications. While the ECEC benchmark was aimed at children aged 4 and above, the same 
data source can also be used to monitor participation of younger children. 

The participation rate provided in UOE data captures the “ECE” (Early Childhood Education) component of ECEC. 
As  explained  by  Eurostat  (2021),  “Early  Childhood  Education  (ECE)  refers  to  ECEC  programmes  which  are 
considered by the International Standard Classification of Education (ISCED) to be ‘educational’ and therefore 
constitute the first level of education in education and training systems – ISCED level 0. The word ‘care’ is not 
included  in  the  term  ECE/early  childhood  education  even  though  programmes  may  and  do  include  childcare 
components, which may be greater than the educational components.” 

According to UOE (2020), “early childhood education (ISCED level 0) provides learning and educational activities 
with a holistic approach to support children’s early cognitive, physical, social and emotional development and 
introduce young children to organized instruction outside of the family context to develop some of the skills 
needed for academic readiness and to prepare them for entry into primary education”. As also explained in Flisi 
et al. (2016), the boundary between education and childcare can be hard to establish, and countries differ in 
the way they define early childhood education. As a consequence, the inclusion of a programme under ISCED 0 
is  not  straightforward.  In  order  to  ensure  international  comparability  of  data,  ISCED  stipulates  a  number  of 
internationally  agreed  criteria  to  determine  whether  a  programme  should  be  recognised  as  early  childhood 
education (ISCED level 0) or not; these criteria are to be met for the programmes to be reported in the UOE 
data collection. 

According to UOE (2015), “along with an intentional child-development and educational focus, a key defining 
factor of ISCED level 0 programmes is the sustained intensity and duration of delivery of intentional educational 
activities. These are what differentiate ISCED level 0 from other programmes, such as childcare and occasional, 
after hours or vacation care”.  

More precisely, a set of “Main” and “Subsidiary Criteria” are used to determine whether  or not a programme 
should be classified as ISCED level 0 and included in reporting. According to the Main Criteria, for a programme 
to be reported as ISCED level 0 it must:  

—  have adequate intentional educational properties;  

—  be institutionalised;  

—  be targeted at children within the age range starting from age 0 up to the age of commencement in ISCED 

level 1 education;  

—  meet the minimum intensity/duration (education programmes must account for at least the equivalent of 

2 hours per day and 100 days a year of educational activities in order to be classified in ISCED).  

According to the Subsidiary Criteria, programmes should wherever possible also have a regulatory framework 
recognised  by  the  relevant  national  authorities;  and  have  trained  or  accredited  staff  as  per  the  appropriate 
regulatory framework. Details for each of the criteria are provided in UOE (2015). 

Figure 5 shows participation in ECE for children aged 0-2 based on UOE data. The EU average enrolment rate 
in 2019 was 19%, with eleven countries showing rates below 10%, and only one above 50%.  

14 

 
Figure 5. ECEC enrolment rate for children aged 0-2, UOE (2019) 

56

46 47

44

39 40 40

35

30 31

60

50

40

30

20

10

0

e
t
a
r

t
n
e
m
o
r
n
E

l

Barcelona target for age group 0-2 based on EU-SILC data (33%)

25 25 26

22

19 20

4 4 5 5 5 6 7

10

9

0 1 3

NL LU PL FR BG SK HU IT CZ MT RO EL EU-
27

AT HR CY IE EE LT LV FI DE ES PT SI BE SE DK

Source: authors’ calculations based on Eurostat UOE data, 2019 [educ_uoe_enra25]. 
Notes: PT refers to 2018. EU-27 does not cover PT. For EL: under-coverage, pupils at ISCED11_01 in Independent private institutions are 
not included. For MT: under-coverage, ISCED 0 does not include ISCED 01. Countries are ordered by increasing rates of ECEC participation. 

As clearly emerges from Figure 6, enrolment rates from UOE data are, with very few exceptions, considerably 
lower than those computed based on EU-SILC. In some cases, exceptionally high attendance rates calculated 
from EU-SILC data are coupled with very low levels measured by UOE (see the Netherlands and Luxembourg), 
but the discrepancies are also notable for other countries, leading to an overall low correlation between the two 
measures. This is because as mentioned above, the definition of ECEC used in UOE is more restrictive than the 
one of EU-SILC, which covers also services that might be relatively more oriented to “care” than to education. 
In several of the countries with very low participation, some national programmes fail to meet one or several 
of the ISCED criteria to qualify as ISCED 0, despite being considered by the countries as an integral part of their 
ECEC systems (13). 

(13)  As explained in European Commission (2019), “this is the case for example in Ireland, which offers integrated programmes that include
education and childcare services; although some ECEC services for children under the age of 3 have an explicit educational aim, they
do not adhere to all criteria and therefore are considered to be outside the scope of ISCED 0. In France, publicly subsidized and regulated
home-based childcare (Assistant(e)s maternel(le)s agréé(e)s) is available and widely used for children below 3, as well as community
day-care  services  (Crèches collectives)  and  discovery  gardens  (Jardin d’eveil);  despite  representing  a  relevant  component  of  the
education  expenditure  for  the  French  government,  these  programmes  are  all  outside  the  scope  of  the  ISCED  classification.  In
Luxemburg, the well-developed system of regulated home-based care delivered by child-minders (assistants parentaux), as well as the
day-care centers (Crèches), are not reported under ISCED 0. Similar situations apply to other countries (e.g. to Amas in Portugal)”.

15 

 
Figure 6. Comparison of enrolment rates for children aged 0-2 based on EU-SILC and UOE data (2019) 

NL

60

LU

50

FR

DK

ES

PT

BE
SE

SI

40

30

C
L
I
S
-
U
E

20

10

0

0

IE

EE

CY

LV
LT

FI

DE

MT

EU-27

EL

IT

BG
HU

RO

PL

CZ

SK

AT

HR

10

20

30

UOE

40

50

60

Source: authors’ calculations based on Eurostat special extraction from EU-SILC and UOE data, 2019.  
Notes: in UOE data, PT refers to 2018; EU-27 does not cover PT; and there is under-coverage for EL (pupils at ISCED 01 in Independent 
private institutions are not included).  

2.2.2  Advantages and limitations of UOE in measuring participation in ECEC 

As mentioned above, the UOE data collection is based on national administrative sources, reported by Ministries 
of Education or National Statistical offices according to international standards, definitions and classifications. 
The administrative nature of the data makes UOE indicators in principle more reliable than information based 
on survey data, which might be exposed to risks related to representativeness, sample size and precision, as 
explained in Sections 2.1.2 and 2.1.3. However, a number of possible limitations of UOE data should also be 
acknowledged. 

First of all, UOE by definition does not cover “ECEC” as a whole – i.e. the scope of the current Barcelona target 
– but only programmes that qualify as “ECE” (ISCED 0). When compared to the information captured in EU-SILC,
the UOE indicator is therefore rather restrictive, as the focus is clearly more on education than on care.

To complement the picture provided by ECE participation, over the last few years, the OECD has been collecting 
data on “other registered ECEC services” outside the scope of ISCED 0 for a few countries, in particular those 
which do not have educational programmes for children under 3 (OECD, 2017).  

Figure A.1 in the Annex shows the results from this ad-hoc data collection for 2016. It is clear that for some 
countries, this additional coverage of ECEC services drastically changes the enrolment rates. However, this ad-
hoc data collection is not carried out for all countries in all years (see for example data for 2019 in Figure A.2, 
where coverage is clearly much more limited); Figure A.3 shows a comparison between indicators including and 
excluding this additional component (14).  

In  the  last  UOE  data  collection, Eurostat  and  the  OECD  asked  countries  to  report  information  on  both  ECEC 
programmes that meet ISCED 0 criteria and other ECEC services considered an integral part of countries’ ECEC 
provision (e.g. registered settings), but not covered by the ISCED 2011 classification. While this transmission of 
mapping information is still done by MSs on a voluntary basis, this new metadata can support the interpretation 

(14)  It should be pointed out that for some countries, the reported source for “other registered ECEC services” is actually EU-SILC.

16 

of statistics on early childhood education collected in UOE. The same type of mapping is currently not available 
for EU-SILC, as already mentioned. 

A second issue worth mentioning is that the computation of indicators from UOE data is not as flexible as for 
EU-SILC. The data collection does not make any distinction based on intensity of use of the ECE service (apart 
from the minimum threshold required to qualify for ISCED 0 mentioned in Section 2.2.1), and the age groups 
for which the information is collected is relatively fixed. UOE data do not allow an analysis by socio-economic 
background  of  the  family  either.  These  represent  a  notable  drawback  when  exploring  options  to  create 
complementary indicators for the main Barcelona targets. 

2.3  Moving forward 

With the current Barcelona target for younger children set for 2010 reached in the EU on average, a new and 
more ambitious target for children aged 0-2 will be set in the Proposal for a Council Recommendation on the 
Revision of the Barcelona Targets on early childhood education and care. Besides this revised target, a number 
of  additional  dimensions  could  be  taken  into  account  when  monitoring  progress  towards  the  Barcelona 
objectives.  In  order  to  do  so,  relevant  indicators  should  be  set  up.  The  rest  of  the  report  assesses  different 
options for developing accompanying indicators to the Barcelona target that would help to better understand 
to what extent ECEC services can serve maternal employment, in particular: 

- 

- 

by  serving  those  age  groups  that  are  the  least  likely  to  be  supported  by  other  national  institutional 
arrangements; 

by offering long enough service hours to effectively help maternal employment; and  

-  measuring ECEC enrolment rates of children from socioeconomically disadvantaged backgrounds. 

The three main options for additional indicators that will be explored in the next sections are the following. The 
first one, presented in Section 3.1, will focus on narrowing the age group considered for the indicator to children 
aged between 1 and 2, therefore excluding those below 1. The second option, investigated in Section 3.2, takes 
into account the level of intensity of the ECEC service, to focus on children enrolled in ECEC for enough hours 
to allow parental participation in the labour market. Finally, Section 3.3 looks into the possibility of measuring 
ECEC participation rates of children in households that are at risk of poverty and social exclusion (AROPE). 

Despite the limitations discussed in the previous sections, EU-SILC is the only available data source for these 
three new possible indicators; the UOE data collection does not allow to calculate a participation rate separately 
for the age group 1-2 (15), nor a distinction of ECE participation by intensity beyond the minimum required (at 
least the equivalent of 2 hours per day), nor linking participation to any indicator of socioeconomic background. 
Moreover,  using  EU-SILC  data  also  allows  continuity  and  comparability  between  the  main  Barcelona  target 
indicator for children aged 0-2, and the proposed accompanying ones.  

(15)  In the current data collection, information for children under the age of 3 enrolled in ECE is gathered for children aged 0-1 and 2, so 

the calculation of an indicator for age 1-2 is not feasible for the time being. 

17 

 
 
                                         
3  Additional considerations to better understand progress in ECEC attendance  

3.1  Differentiating by the age of the child 

The Barcelona target considers all children below age 3, however ECEC participation varies greatly depending 
on  age.  A  first  option  for  a  complementary  indicator  therefore  specifically  looks  only  at  1-  and  2-years-old 
children. This section provides some arguments, together with supporting evidence, for the implementation of 
such focus and to develop a sub-indicator for this sub-group. Then, it presents the ECEC enrolment rate of 1- 
and  2-years-old  children  to  show  how  looking  at  a  more  restricted  age  group  would  affect  the  overall 
performance of countries. Finally, it provides some comments on the technical feasibility of the calculation of 
such a sub-indicator. 

Across the European MSs, ECEC attendance of children below age 1 is generally low and remains far below the 
participation rates of older children. As shown in Figure 7, no children from the youngest group are enrolled in 
an ECEC institution in 10 out of the 27 countries, and only very few in another one. From these 11 countries, 
no ECEC service is provided for children below 1 in Czechia, Estonia, and Sweden (16). At the same time, despite 
the formal availability of the service, actual ECEC attendance is still close to 0% in Slovakia, Poland, Romania, 
Croatia, Hungary, Austria, Lithuania and Slovenia, according to EU-SILC 2019 data. 

In contrast, the attendance rates of 35, 36 and 48% in Belgium, Portugal and the Netherlands can be considered 
as exceptionally high, as in the rest of the Member States, comparable figures vary between 1-2% (Germany, 
Latvia, Bulgaria, Greece) and 27% (Denmark). With the only exception of France, in all the countries, enrolment 
rates  gradually increase with age, with notable differences  both between years 0 and 1 as well as  between 
years 1 and 2. The EU-27 average enrolment rate is 10%  among  0-year-olds, 37% among 1-year-olds and 
54% between for 2-year-olds. 

Figure 7. ECEC enrolment rate by age group, EU-SILC (2019) 

100

90

80

70

60

50

40

30

20

10

0

e
t
a
r

t
n
e
m
o
r
n
E

l

39 39

33

25

21

16 16

9

10

13 11 12

48

43

25

9

19

96

62

79

66

48

92

82

27

74

57

35

87

84

71

66

21

17

81

55

64

53

36

62

57

19

80

59

55

56

53

60

54

67

64

68

41

37

36 36

31

22

13

22

10

14

16

12

14

10

CZ SK PL RO HR HU BG AT

IT

LT LV CY DE EE EL EU-
27

FI MT IE

SI

FR PT SE BE ES LU NL DK

Age 0-2

Age 0

Age 1

Age 2

Barcelona target for age group 0-2 (33%)

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019. 
Notes: Countries are ordered by increasing rates of ECEC participation in the 0-2 age group. 

The  remarkably  lower  ECEC  attendance  of  children  below  age 1  as  opposed  to  older  ones  is  due  to  many 
differences in the provision of care for the two age groups, as well as to the expected developmental effects 
of care on children. Research on the child development consequences of a very early ECEC enrolment age – i.e. 
age 0 – is still scarce. Even for the broader age group of 0-2, empirical findings on developmental consequences 
are mixed, even pointing at potential adverse effects, especially when institutional care is either of low quality 

(16)  According to Eurydice (2019), young children had also no access to ECEC in Latvia, but in this case small attendance was still found in 

EU-SILC survey data. 

18 

 
 
 
                                         
 
or used for too long hours, making scholars conclude that “…earlier may not always be better” (van Huizen and 
Plantenga, 2018, pp 208). According to Adamson (2008), the risks involved in spending long hours in childcare 
are particularly high before the first birthday. A not too early start of ECEC attendance is also in line with the 
recommendation by the World Health Organization regarding the advantages of exclusive breastfeeding in the 
first six months of life (17).  

The considerations calling for a special treatment of the youngest age group is well reflected in the Member 
States’  institutional  settings.  Across  the  EU-27  countries,  the  first  year  of  life  is  often  covered  by  a  mix  of 
parental  leave  schemes  and  ECEC  support,  though  with  notable  cross-country  differences  in  the  weights  of 
these two elements. Moreover, besides these two main options, in many cases various alternative solutions are 
used (e.g. childminder and home-care options) that do not count as ECEC in all categorisations. The actual mix 
of these different solutions offered and used varies significantly across MSs, mirroring historical traditions, as 
well as cultural norms.  

Generally  speaking,  institutional  care  is  not  considered  to  be  the  main  solution  for  care  in  the  case  of  the 
youngest children. Albeit to a varying extent, the institutional systems of MSs prioritise parental – most often 
maternal – care at least in the first months of life. Across the EU-27 countries, paid leave is provided to the 
mothers for a minimum of 16 weeks of a child’s life, as happens in the Netherlands and Spain. However, usually 
paid leaves last for much longer, and are further extended by paternal leaves in several countries. OECD data 
presented in  

Table A.3 shows that in most EU countries, paid maternal leave is offered for (almost) a full year after childbirth 
(Italy,  Denmark,  Poland,  Slovenia),  or  even  beyond  (slightly  more  than  a  year  in  Sweden,  Croatia,  Germany, 
Austria, Lithuania; around 1.5 years in Czechia and Estonia; around 2 years in Latvia, Romania and Bulgaria; up 
to around 3 years in Hungary, Finland and Slovakia).  

Whether or not maternal (parental) caregiving is a viable option to substitute institutional care depends also on 
the size of monetary compensation offered during the leave period. This again varies substantially across  EU 
countries,  with  Finland  and  Ireland  respectively  offering  on  average  only  25  and  27%  of  the  previous 
payments (18), while Estonia, the Netherlands, Slovenia and Spain provide full coverage.  

The two pieces of information combined – i.e. the length of paid leave together with the payment offered during 
this  period  –  help  to  understand  at  least  some  part  of  the  cross-country  variations  in  the  level  of  ECEC 
attendance among young children. Figure 8 plots the length of full-rate equivalent of total paid leave available 
to mothers (in weeks, provided in the fourth column of Table A.3) on the Y-axis, and the ECEC enrolment rates 
by single year of age in 2019 (as shown in Figure 7) on the X-axis.   

The left-hand side panel in Figure 8 presents data for children below 1 year of age. In this age group, ECEC 
attendance is strongly and negatively correlated with the length of full-rate payment equivalent maternal leave 
among countries that offer such a leave for less than a year (with a correlation of -0.66). In countries where 
full-rate payment equivalent maternal leave exceeds a year (i.e. Slovenia, Czechia, Hungary, Bulgaria, Slovakia, 
Estonia,  Romania),  children  below  1  hardly  ever  attend  an  ECEC  institution.  The  parental  leave  system  still 
influences a lot children’s ECEC participation rates also in their second year of life, as shown in the right hand 
side  of  Figure  8.  For  this  age  group,  ECEC  enrolment  still  correlates  strongly  with  the  length  of  full-rate 
equivalent  maternal  leave  (corr.=-0.56),  and  countries  offering  well-paid  leave  beyond  a  year’s  time  have 
enrolment rates below 15% among 1-year-old children. 

Figure A.4 in the Annex provides similar information  but this time  on the X-axis an indicator considering the 
income level paid one / two years after childbirth is shown. ECEC enrolment rates again are given by age group 
on the Y-axis: left panels consider family income when  the child reaches the age of 1, right panels consider 
family income when the child reaches the age of 2. While in countries without any paid parental leave by this 
time varying levels of ECEC enrolment are found for children aged both 0 and 1 (these countries are placed 

(17)  See Infant and young child feeding (who.int).  
(18)  OECD refers the "average payment rate" as the proportion of previous earnings replaced by the benefit over the length of the paid 
leave entitlement for a person earning 100% of average national full-time earnings. If this covers more than one period of leave at 
two different payment rates then a weighted average is calculated based on the length of each period. In most countries benefits are 
calculated on the basis of gross earnings, with the "payment rates" shown reflecting the proportion of gross earnings replaced by the 
benefit.  In  Austria  and Germany,  Lithuania  and  Romania  (parental  leave  only),  benefits  are  calculated  based  on  previous  net  (post 
income tax and social security contribution) earnings, while in France benefits are calculated based on post-social-security-contribution 
earnings. Payment rates for these countries reflect the proportion of the appropriate net earnings replaced by the benefit. Additionally, 
in  some  countries  maternity  and  parental  benefits  may  be subject  to  taxation  and  may  count  towards  the  income  base for  social 
security contributions. As a result, the actual amounts received by the individual on leave may differ from those shown in the table. 

19 

                                         
right on the Y-axis on Figure A.4), there is a clear association between the level of enrolment and net equalised 
income paid in countries, where payments are still provided one / two years after childbirth.  

To summarize, the fact that long parental leave periods account for a large part of the unequal uptake of ECEC 
in the first year of life in the European countries, points to a certain limitation of the current Barcelona target 
and the main indicator that handles the 0-2 age category as one homogenous group of children.  

Figure 8. Enrolment rates (2019) and length of paid maternity/paternity/parental leaves (2020) 

(a)  Age 0 

(b)  Age 1 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, and OECD Family Database. 

Another important argument for differentiating the youngest children from the focus of the Barcelona target is 
the  particularly  high  costs  attached  to  high  quality  institutional  care  for  this  age  group.  In  countries  where 
formal ECEC is offered for children under year 1, regulations for this age group are often markedly different 
from those applied for older children. This involves in particular the rules concerning the maximum number of 
children per staff member, which is a crucial component of quality of childcare, as well as a determinant of the 
overall costs. According to Eurydice (2019), this is regulated differently for children below age 1 compared to 
older children in 10 out of the 23 European countries where ECEC for young children is provided. As shown in 
Table A.4, in Poland for example, the maximum number of children per staff member is set at 5 for children 
aged 0, and at 8 for both children aged 1 and 2. In Austria, the respective thresholds are set from 4 to 5 for 
the youngest ones and from 4 to 8 for the older children. Similar increases in the number of children per staff 
member from age 0 to 1, but also from 1 to 2 exist in other countries (Ireland, Spain, Croatia, Lithuania, Malta, 
the  Netherlands,  Portugal,  Romania). In contrast, the increase  only  between age  groups 1 and 2  occurs  in  a 
small number of countries (Cyprus, France, and Luxembourg). 

As shown in this section, there are a number of reasons for separately monitoring ECEC participation of relatively 
older  children.  Complementing  the  overall  Barcelona  target  for  children  aged  0-2  with  a  sub-indicator  for 
children aged 1-2, would allow to better understand how service provision develops for children that are most 
in need of institutional arrangements – both because they better fit their age-specific needs, and because their 
parents are typically not supported any more by alternative care options, such as parental leave.  

Figure 9 presents the ECEC enrolment rate for each MS based on the age category used in the Barcelona target 
(0-2, light blue bars) together with the respective rate for the proposed sub-indicator for age group 1-2 (dark 
blue  square). As children below 1 are far less likely to  be enrolled in ECEC than  older children, changing  the 
reference age group increases the ECEC enrolment rate in each and every country in the EU. Across the EU-27, 
the average participation rate of 1-2-year-old children reaches 46%, as opposed to 35% for the broader age 
group. A comparable – and sometimes much bigger – difference can be observed in the individual countries as 
well. Figure 10, showing the evolution of both rates over time, confirms the same pattern. 

20 

 
 
 
 
Figure 9. ECEC enrolment rate for the 0-2 and the 1-2 age groups, EU-SILC (2019) 

100

90

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10

0

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23 25 26

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15

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9

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79

76

72

77

66

69

59 59

54

52

50

49

44

46

43

CZ SK PL RO HR HU BG AT IT

LT LV CY DE EE EL EU-
27

FI MT IE

SI FR PT SE BE ES LU NL DK

Age 0-2

Age 1-2

Barcelona target for age group 0-2 (33%)

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019. 
Notes: Countries are ordered by increasing rates of ECEC participation in the 0-2 age group. 

As mentioned in Section 2.1.2, sample size is an issue that needs to be carefully considered when dealing with 
ECEC indicators based on EU-SILC. Calculating a sub-indicator for children aged 1-2 implies a further reduction 
in the sample sizes underlying the indicator, which reinforces the concerns already described above.   

As discussed in Section 2.1.3, the sample size has important implications for the quality of indicators calculated 
from it. In particular, the smaller the sample size used to estimate the proportion of children enrolled in ECEC, 
the bigger the confidence interval, i.e. the range of values around the estimated value that is likely to contain 
the true proportion of children in ECEC.  

Table A.5 provides the unweighted sample sizes used to estimate ECEC participation rates for the 1-2 age group 
between 2010 and 2019. Despite the obvious decrease in the overall sample sizes considered when narrowing 
down the target age group, in the vast majority of instances, it is still possible to rely on a sample of 200 or 
more children to estimate the ECEC participation rates, well above the reliability thresholds mentioned in Section 
2.1.3. In many countries in fact a sample size between 300 and 500 remains available in each year to calculate 
the statistics of interest. Countries with samples consistently below 200 include Bulgaria, Cyprus and Denmark, 
while a sample size below 150 was repeatedly observed during the past years in Lithuania. The lowest numbers 
however are again found in Malta and especially in Romania where since 2013 there were less than 100 children 
in the 1-2 age group. Samples below 150 and 100 are highlighted in Table A.5. 

From a data reliability point of view, it is important to notice that the trends for age group 1-2 run almost fully 
in parallel with those for age group 0-2. In other words, as can be seen in Figure 10, the reduced sample size 
does not seem to lead to any more irregular yearly variations in the sub-indicator’s value than what has been 
observed  with  the  Barcelona  target  indicator.  Still,  particular  caution  is  needed,  due  to  the  further  reduced 
sample sizes when dealing with a limited age group of young children based on EU-SILC data.   

21 

 
 
 
 
 
 
 
Figure 10. ECEC enrolment rates for age groups 0-2 and 1-2, by country, EU-SILC (2010-2019) 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2010-2019. 
Notes. Countries are ordered by decreasing rates of ECEC participation in the 0-2 age group. The red line is the current value of the target.  

22 

 
3.2  Considering the intensity of care  

The current Barcelona indicator takes into account enrolment in any ECEC service, irrespective of the number 
of hours that children spend in it. However, from a gender equality perspective, i.e. considering the promotion 
of  maternal  employment  as  an  important  aim  of  ECEC  provision,  it  is  clear  that  below  a  certain  minimum 
number of hours, institutional care is not a sufficient support towards this aim.  

It is of course not straightforward to identify the minimum number of weekly institutional ECEC hours that is 
needed to achieve this goal. From the service provider’s point of view, Eurydice distinguishes two main goals 
that  each  require  different  (minimum)  number  of  hours  for  a  child  to  spend  in  ECEC.  According  to  this 
categorisation, a service provided for less than 30 hours per week serves mainly educational purposes. It is only 
from a minimum  of 30  hours  of care  provision  that  one  can consider  childcare as  an intervention  targeting 
“family work-life balance challenges faced by working parents” (Eurydice, 2019, pp49).  

Using a somewhat more flexible criterion, in the following it is assumed for illustrative purposes that low (time) 
intensity of care (defined as an attendance  of 1-19 hours per week) does not permit mother’s employment; 
medium level intensity (that is 20-29 hours attendance) permits part-time employment; and high intensity of 
care attendance (30+ hours) permits full-time employment. 

Figure 11(a) presents children’s ECEC participation in the age group 0-2 split by number of weekly hours spent 
in ECEC in 2019. Three intensity categories are distinguished: 1 to 19 hours, 20 to 29 hours and 30+ hours. On 
average in the EU-27, only 22% of children aged 0-2 spend 30 hours or more per week in institutional care, 
while an additional 8% stay there for 20 to 29 hours. 6% of the age group only receives ECEC for 1 to 19 hours 
per week (see Table A.6 in the Annex). Cross-country differences are notable, with Romania, the Netherlands, 
Austria, Ireland, Greece, Czechia and Spain providing high-intensity care for less than half of the children in their 
ECEC institutions (7, 10, 35, 37, 43, 46 and 47% respectively) and with Croatia, Slovenia, Bulgaria, Portugal and 
Latvia for over 90%.  

What clearly emerges from Figure 11 is that high overall ECEC rates do not always go hand in hand with high-
intensity participation. This suggests that an accompanying indicator to the present Barcelona target that only 
considered  high-intensity  (30+  hours)  services  would  significantly  change  the  picture  of  where  European 
countries  stand  in  supporting  maternal  employment.  The  share  of  children  that  receive  high-intensity  care 
across the EU-27 remains far below the 33% target, and five countries that are above this threshold  on the 
main  indicator  (Finland,  Malta,  Ireland,  Spain  and  the  Netherlands)  also  show  much  lower  performance.  If 
instead also medium-level intensity – i.e. care of 20 to 29 hours – was considered as sufficient service, then 
one would only observe a notable change in the position of the Netherlands and Ireland, and not so much in 
the  relative  achievements  of  the  other  Member  States.  Even  in  this  case,  however,  the  EU-27  average 
achievement would remain somewhat below the current target of 33%.  

Moving one step further, and applying the proposed intensity criteria on the 1-2 age group (i.e. combining the 
two suggested complementary indicators for the Barcelona target simultaneously), a somewhat more positive 
picture would emerge. This is because children in the excluded age group – children below age 1 – are most 
likely to spend only few hours in ECEC. Figure 11(b) breaks down ECEC enrolment rates of 1- and 2-year-old 
children by hours they attend care facilities. Taking only high-intensity care into account, the current Barcelona 
target of 33% in this age group would still not be met at the EU-27 level, as across the EU only 28% of this 
age group is receiving care for 30+ hours per week. The Netherlands and Ireland would again drop from the 
group of high-performing countries.  

When also taking into account ECEC provided for 20-29 hours (medium intensity) for the 1-2 age group, once 
again the 33% target would be met at the EU-27 level (39%). The Netherlands and Ireland would still remain 
below the threshold and thus be excluded from the group of high-performing countries, because of the high 
incidence of low intensity ECEC. In Ireland, 59% of the enrolled 1-2-year-old children spend a minimum of 20 
hours in ECEC – representing 31% of the age group. Even lower is the care intensity in the Netherlands, where 
only 39% of the enrolled 1-2-year-old children are provided a minimum of 20 hours of service per week, which 
accounts for only 28% of all the children in this age group in the country.  

Figure 12 shows that after many years of stagnation, enrolment in high-intensity ECEC started to increase after 
2017.  In  that  year,  only  17%  of  0-2-year-old  children  in  the  EU  received  high-intensity  care  in  an  ECEC 
institution, but this figure increased to 19% by 2018 and further to 22% by 2019. This pattern seems to suggest 
that ECEC services for this age group are becoming increasingly supportive to maternal employment in Europe. 

23 

 
Figure 11. ECEC enrolment rates by time-intensity of care (number of hours per week), EU-SILC (2019) 

(a) Children aged 0-2  

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15 14

19

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8

5

3

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27 25 23 24

23

28 25

22

14

15

50

44

34

37 36

27

58

47

6

CZ SK PL RO HR HU BG AT

IT

LT LV CY DE EE EL EU-
27

FI MT IE

SI

FR PT SE BE ES LU NL DK

30+ hours

20-29 hours

1-19 hours

Barcelona target for age group 0-2 (33%)

(b) Children aged 1-2  

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21 20

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4

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34 30 29

33

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37 34

18

19

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35

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CZ SK PL RO HR HU BG AT IT LV LT CY EL DE EU-
27

EE MT IE

FI PT FR BE SI NL ES SE LU DK

30+ hours

20-29 hours

1-19 hours

Barcelona target for age group 0-2 (33%)

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019. 
Notes: Countries are ordered by increasing rates of overall ECEC participation. The number reported in the chart corresponds to participation 
for 30+ hours.  

24 

 
 
 
 
 
 
Figure 12. ECEC enrolment rates for children aged 0-2 by time-intensity of care (number of hours per week),  
EU-27, EU-SILC (2010-2019)   

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22

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

30+ hours

20-29 hours

1-19 hours

Barcelona target for age group 0-2 (33%)

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2010-2019.  

25 

 
 
 
 
 
 
3.3  Focusing on disadvantaged children 

The benefits of participation in high quality ECEC services are widely recognised, both in terms of improvement 
of children’s cognitive, social and educational development, and of promotion of parental employment. However, 
enrolment in ECEC is considered to be particularly beneficial for children from disadvantaged backgrounds. As 
reported  in  the  European  Commission  Recommendation  on  “Investing  in  children:  breaking  the  cycle  of 
disadvantage” (2013/112/EU), children are more at risk of poverty or social exclusion than the overall population 
in most EU countries, and those growing up in such situations are less likely to perform well in school, be healthy 
and realise their full potential throughout their lives. The Recommendation highlights the key role of ECEC in 
developing children’s potential  and fostering  social inclusion, thereby reducing inequality already at a young 
age.  In  parallel,  it  acknowledges  the  strong  link  between  parents’  labour  market  participation  and  the  living 
condition of children, recommending MSs to support parents’ labour market participation, including by ensuring 
access to affordable, high quality ECEC. The importance of ECEC participation for children is therefore twofold. 

Against  this  background,  complementing  the  official  Barcelona  indicator  with  a  more  targeted  additional 
indicator focusing on the sub-group of children from disadvantaged households would allow to better monitor 
the progress towards reaching the social equalising aim of ECEC provision. 

The literature often considers socio-economic background as a combination of parental education, occupation, 
income and wealth. While different categorisations can be used to identify disadvantaged children, this section 
focuses  on  those  living  in  households  at  risk  of  poverty  or  social  exclusion  (AROPE) (19).  To  identify  AROPE 
households, this report adopts the definitions from EU official statistics, which can be found here. This category 
includes households that: 

—  Have an equivalised disposable income (after social transfer) below the at-risk-of-poverty threshold, which 

is set at 60 % of the national median; 

—  Are severely materially and socially deprived, i.e. lack necessary and desirable items to lead an adequate 

life (20); 

—  Have a very low work intensity. 

Figure 13 shows ECEC enrolment for children aged 0-2 from households at risk of poverty and social exclusion 
and  for  children  from  non-AROPE  households for  year  2016 (21).  The  chart  shows  that  the  EU  average  gap 
between the two groups is as big as 15 p.p., albeit with notable variations across Member States. Overall, the 
attainment of the 33% Barcelona target for this age group was in fact driven by children not at risk of poverty 
and social exclusion, with an average participation rate of 37%. Children from AROPE households, on the other 
hand, were lagging severely behind, with an enrolment rate of only 22%. 

Except  for  Austria,  in  all  EU  countries  ECEC  enrolment  rates  are  lower  among  children  from  disadvantaged 
backgrounds. The biggest gap – above 40 p.p. – is found in the Netherlands, followed by France with 31 p.p. 
and  Spain  (19 p.p.). In six  of the nine countries that  have already attained the 33% Barcelona target at the 
national  level,  the  good  performance  is  driven  by  non-AROPE  children,  while  those  from  disadvantaged 
households are still below this threshold (Italy, Spain, Slovenia, Belgium, France, the Netherlands). Smaller gaps 
are found in other countries; however, even when limited in terms of percentage points, these differences can 
be quite relevant as a percentage of the participation rate of non-AROPE children.  

It is important to notice, however, that not all gaps by socio-economic background are statistically significant; 
this is the case only for 12 out of the 26 countries for which it was possible to carry out the analysis. Statistically 
non-significant  differences  between  children  from  AROPE  and  non-AROPE  households  were  found  both  in 
overall good performing countries (such as Luxembourg and Sweden), and in traditionally low enrolment ones 
(e.g. Slovakia, Czechia, Poland, Greece and Bulgaria). 

(19)  Alternative classifications can be based for example on equivalised disposable income of the household (considering tertiles or quintiles 

of income), or mother’s education level. An overview is provided in Flisi and Blasko (2019). 

(20)  Until 2020, this AROPE component captured “severe material deprivation”, i.e. a situation where one cannot  afford (rather than the 
choice not to do so) at least 4 out of 9 predefined material items considered by most people to be desirable or even necessary to lead 
an  adequate  life.  In  2021,  this  has  been  modified  according  to  the  new  EU  2030  target,  to  capture  “severe  material  and  social 
deprivation”, i.e. a situation where one experiences an enforced lack of at least 7 out of 13 deprivation items (6 related to the individual 
– such as having internet connection – and 7 related to the household – e.g. the capacity to face unexpected expenses). The list of 
items can be found here.  

(21)  This section presents indicators computed in Flisi and Blasko (2019), using EU-SILC microdata from 2016. Starting from the microdata, 
the analysis reproduced official statistics from Eurostat, with only marginal differences from the official indicators, except for Germany, 
for which small discrepancies remained. Malta was excluded from the analysis because no age variable was available in the microdata. 
The EU average therefore refers to the average of the other EU countries. 

26 

                                         
Figure 13. ECEC enrolment rates by socio-economic background, EU-SILC (2016) 

60

56

53 52 53

47

44

42

37 38

35 34

31

31

29

46 45

38

28

24

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SK CZ PL EL BG LT* HR HU* RO AT CY LV* IE EE FI* DE EU* IT* ES* SI* BE* FR* PT* LU SE NL*

Overall ECEC enrolment

AROPE

Not AROPE

Barcelona target for age group 0-2 (33%)

Source: authors’ calculations based on EU-SILC microdata, 2016.  
Notes: * = difference between AROPE and not AROPE statistically significant (p < 0.05). MT is missing because no age variable is available 
in the microdata. DK not reported because of low sample size for the AROPE sub-group. The rate for AROPE in RO is unreliable. See Flisi 
and Blasko (2019) for more information.  

As for the sub-indicator differentiating participation by age group presented in Section 3.1, the issue related to 
sample size should be carefully considered for the sub-indicator by socio-economic background as well. In this 
case, the overall sample size for the 0-2 age group is split in two subsamples, one for children from households 
at  risk  of  poverty  and  social  exclusion,  and  one  for  children  from  households  not  at  risk.  This  implies  a 
substantial  reduction  in  the  samples  underlying  the  enrolment  rates  presented  above,  in  particular  for  the 
AROPE group, which is by definition smaller than the other one. In 2016, around 23% of children aged below 6 
were at risk of poverty of social exclusion in the EU-27, with country shares ranging from 12% in Denmark to 
46% in Romania (22). Table A.7 shows in more detail the level of reliability of the figures presented in Figure 
13, together with the relative sample sizes. As already reported in the notes to Figure 13, in two EU countries – 
Denmark  and  Romania  –  EU-SILC  does  not  offer  a  sufficient  sample  size  of  children  in  the  subgroup  of 
disadvantaged children, with the number  of AROPE children being as low as 17 and 34 respectively (23). The 
table in the Annex, however, shows that in particular for AROPE children, many more countries have sample 
sizes below 150 (21 MSs) and even 100 (14 MSs) (24). In some cases, this might contribute to explaining why 
difference in enrolment rates between the two sub-groups are not significant.  

Summing  up,  this  section  presented  evidence  that  enrolment  in  ECEC  varies  greatly  by  socio-economic 
background of the children, with those from disadvantaged households showing  considerably lower levels of 
participation.  This  reinforces  the  argument  for  the  adoption  of  a  sub-indicator  to  complement  the  official 
Barcelona indicator, to encourage MSs to strive towards closing the participation gap in ECEC. This is especially 
true since so far, there has been no systematic and regular reporting of ECEC attendance by socio-economic 
status of the parents in a comparative manner across EU Member States.  

The  section  also  highlights  once  more  how  relevant  sample  size  can  be  in  the  calculation.  When  particular 
subgroups in a country’s sample are too small to produce reliable ECEC enrolment rates, as it can be the case 
for children in AROPE households, then it would be hard to draw conclusions on the gaps in participation among 
children  from  disadvantaged  background.  This  suggests  that  further  attention  should  be  devoted  to 
guaranteeing  appropriate  sample  sizes  in  EU-SILC,  should  a  sub-indicator  by  socio-economic  background  be 
adopted to monitor progress towards reaching the Barcelona target. 

(22)  See Persons at risk of poverty or social exclusion by age and sex - EU 2020 strategy [ILC_PEPS01__custom_3113212]. 
(23)  The issue is likely to affect Malta as well, but as mentioned above, it was not possible to produce the indicators for this country using 

microdata because the age variable was not available. 

(24)  Indeed, similar analysis presented in European Commission (2022) shows results only for 22 EU countries in 2019, while the remaining 
ones had less than 50 observations for AROPE children. This reinforces the concern about the overall trend of reduction in SILC national 
sample sizes, which poses particular challenges for the computation of the ECEC indicator by socio-economic background. 

27 

 
 
 
                                         
 
4  Conclusions and implications for revising the target 

This report provides evidence in support of the proposal for a Council Recommendation for the revision of the 
Barcelona targets on early childhood education and care for children below 3 years of age, which forms part of 
the new European Care Strategy. 

In view of the revision of the Barcelona targets, and of the development of possible complementary indicators 
that can support the monitoring of country progress towards the Barcelona objectives, this report: (i) provides 
a comprehensive overview of the existing indicators used in the Commission to monitor participation in early 
childhood education and care for children under 3 years of age,  and of the two main European data sources 
offering information on ECEC attendance in the European Members States, i.e. EU-SILC and UOE; (ii) investigates 
options for developing accompanying indicators to the main Barcelona target, looking into the main dimension 
that should be considered when evaluating country performance in ECEC.  The report focuses on the younger 
age group considered by the Barcelona targets, i.e. children aged 0-2. 

After  carefully  considering  the  main  advantages  and  disadvantages  of  the  two  available  data  sources,  the 
report concludes that EU-SILC should remain as the data source for monitoring ECEC attendance in Europe for 
young children aged 0-2. The reason is twofold: 

—  first, relying  on EU-SILC would allow continuity and comparability  between the present Barcelona target 

indicators and the future ones; 

—  second, EU-SILC is also the only data source that currently allows investigating further options for a closer 
monitoring of ECEC’s role in supporting maternal employment in Europe. The current UOE data collection 
does not allow for any of the distinctions considered in this report. 

Despite its many  qualities, EU-SILC currently has its limitations as well.  Sample  sizes in some countries  are 
already  relatively  low,  and  a  worrying  trend  of  decreasing  samples  is  found  in  many  EU  countries.  This  is 
especially  relevant  because  indicators  computed  from  this  data  source  are  sample  estimates,  and  as  such, 
should be reported along with accuracy measures such as standard errors and confidence intervals, especially 
when their interpretation is highly important for policy purposes. Since larger sample sizes tend to provide a 
more accurate reflection of the population mean, estimates calculated from low sample sizes must be handled 
with caution. For this reason, attention should be paid to monitor data quality for EU-SILC for the computation 
of Barcelona and accompanying indicators.  

This report considered three main options for accompanying indicators to the Barcelona target that would allow 
to  better  monitor  progress  towards  a  childcare  system  that  supports  maternal  employment.  The  first  sub-
indicator proposed focuses on children aged between 1 and 2, i.e. children that are  often not supported any 
more by other family policy arrangements in the various Member States such as parental leave. The second 
option considers the level of intensity of the ECEC service, to focus on children enrolled in ECEC for a sufficient 
number of hours to allow parental participation in the labour market. Finally, the third option focuses on children 
from disadvantaged background, in particular those living in households at risk of poverty and exclusion. 

Looking specifically at children aged 1-2 would allow to understand the progress regarding a more homogenous 
age  group of children, where parents are usually not any more supported  by additional policy arrangements 
(though not all MS offer these arrangements and/or adequate monetary compensation for the full first year of 
the child), and have the highest need for ECEC services. ECEC participation in the 1-2 age group is higher than 
for the overall 0-2 age group in each and every MS; the EU-27 average enrolment in 2019 increases from 35 
to 46% when narrowing down the age group considered. 

Considering a sub-indicator that covers only ECEC of either medium (20-29 hours per week) or high (30+ hours 
per week) intensity, the EU-27 average achievement falls to 30%, slightly below the current target of 33%. This 
sub-indicator  highlights  the  specificities  of  some  countries,  in  particular  the  Netherlands  and  Ireland,  which 
despite having high levels of overall ECEC enrolment, are characterised by very low levels of intensity. A recent 
increase observed in the proportion of young children who receive high-intensity ECEC in the EU is reassuring 
that maternal employment is increasingly supported by ECEC provision in Europe. 

Finally, this report showed that enrolment in ECEC varies greatly by socio-economic background of the children, 
with those from disadvantaged households showing  considerably lower levels of participation. While the gap 
between children from AROPE and non-AROPE background in the EU on average stands at 15 p.p., in some MSs 
the difference is as high as 31 (France) or even 41 (the Netherlands) p.p.. 

28 

The  analyses  presented  in  this  report  for  the  sub-indicators  on  the  age  group  1-2  and  for  the  indicators  by 
AROPE status of the household, also highlighted once again the issue related to low sample sizes, which  can 
affect reliability and accuracy of indicators calculated on EU-SILC data. 

Recommendations 

Based on these conclusions, the report makes a number of specific recommendations to ensure data quality 
and a better access to relevant statistics on ECEC attendance in Europe. 

Recommendations to ensure data quality and make relevant statistics and accuracy measures accessible for 
users: 

—  Ensuring  adequate  sample  sizes  is  fundamental  to  guarantee  the  good  quality  of  the  indicators;  it  is 
therefore necessary to closely monitor the changes in the number of children aged 0-2 in the national EU-
SILC samples, and take the necessary steps to avoid further decreases to an extent that would harm data 
quality. 

—  Better documentation of non-response rates to the survey in general, as well as to the questions relevant 

for ECEC indicators in particular, with a disaggregation by household type is needed. 

—  Sample sizes  as well  as  confidence intervals around the  estimates for each country should  be reported 

alongside the main indicators. 

Recommendations to better inform policy-makers and interested users about key aspects of ECEC enrolment: 

—  In order to support interpretation and comparison of data (including with national sources), more detailed 
metadata on ECEC indicators should be provided. In particular, the medata should include  a mapping  of 
institutional types considered as an ECEC service in each country over time, both in the original language 
and in English, with information on inclusion criteria for the programmes, theoretical duration and starting 
age. 

—  The  share  of  0-2-year-old  children  enrolled  in  ECEC  institutions  (main  Barcelona  indicator)  should  be 
directly  available  in  the  Eurostat  website,  as  well  as  on  the  Gender  Equality  Strategy  (GES)  Monitoring 
Portal, with no further calculations needed by the user, as is the case now for the ilc_caindformal dataset.  

Additional sub-indicators recommended for a closer monitoring of progress towards the main policy objectives: 

—  - The present report recommends developing and monitoring the following sub-indicators:  

o 

o 

o 

the share of 1-2-year-old children enrolled in ECEC; 

the share of 0-2-year-old children participating in ECEC for at least 20 hours per week, or a level that 
can ensure full labour market participation of the parents; 

the share of children from AROPE and non-AROPE households enrolled in ECEC.  

—  If  adopted  in  the  Recommendation,  the  additional  sub-indicators  analysed  in  this  report  should  also  be 

reported on a yearly basis both in the Eurostat website and as part of the GES Monitoring Portal.  

29 

 
 
 
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https://circabc.europa.eu/sd/a/f8853fb3-58b3-43ce-b4c6-
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(2021). 

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programmes. 

30 

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31 

 
 
 
List of abbreviations and definitions 

Country codes 

Country 

Austria 

Belgium 

Bulgaria 

Croatia 

Cyprus 

Czechia 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Code 

AT 

BE 

BG 

HR 

CY 

CZ 

DK 

EE 

FI 

FR 

DE 

EL 

HU 

IE 

Country 

Italy 

Latvia 

Lithuania 

Luxembourg 

Malta 

Netherlands 

Poland 

Portugal 

Romania 

Slovak 

Slovenia 

Spain 

Sweden 

Code 

IT 

LV 

LT 

LU 

MT 

NL 

PL 

PT 

RO 

SK 

SI 

ES 

SE 

Abbreviations 

CI 

ECE 

ECEC 

Confidence Interval 

Early childhood education 

Early childhood education and care 

ET 2020  

Education and Training 2020 

EU 

European Union 

EU-SILC   

EU Survey on income and living conditions  

ISCED 

OECD 

UOE 

SE 

International Standard Classification of Education 

Organisation for Economic Co-operation and Development 

UIS (UNESCO Institute of Statistics)/OECD/Eurostat data collection 

Standard Error 

32 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
List of figures 

Figure 1. ECEC enrolment rate for children aged 0-2, EU-SILC (2019) ............................................................................................7 

Figure 2. Number of 0-2-years-old children in the EU-SILC national subsamples (2010-2019) ................................ 10 

Figure 3. ECEC enrolment rate for children aged 0-2 with confidence intervals, EU-SILC (2019).............................. 11 

Figure 4. ECEC enrolment rate for children aged 0-2 with confidence intervals, EU-SILC (2010-2019) ............... 13 

Figure 5. ECEC enrolment rate for children aged 0-2, UOE (2019) ................................................................................................ 15 

Figure 6. Comparison of enrolment rates for children aged 0-2 based on EU-SILC and UOE data (2019).......... 16 

Figure 7. ECEC enrolment rate by age group, EU-SILC (2019) ........................................................................................................... 18 

Figure 8. Enrolment rates (2019) and length of paid maternity/paternity/parental leaves (2020) ........................... 20 

Figure 9. ECEC enrolment rate for the 0-2 and the 1-2 age groups, EU-SILC (2019) ........................................................ 21 

Figure 10. ECEC enrolment rates for age groups 0-2 and 1-2, by country, EU-SILC (2010-2019) ........................... 22 

Figure 11. ECEC enrolment rates by time-intensity of care (number of hours per week), EU-SILC (2019) .......... 24 

Figure 12. ECEC enrolment rates for children aged 0-2 by time-intensity of care (number of hours per week),
 .................................................................................................................................................................................................................................................... 25 

Figure 13. ECEC enrolment rates by socio-economic background, EU-SILC (2016) ............................................................. 27 

Figure A.1. Enrolment rate for children aged 0-2 in ISCED 0 and other registered ECEC services, UOE and OECD 
(2016) ..................................................................................................................................................................................................................................... 38 

Figure A.2. Enrolment rate for children aged 0-2 in ISCED 0 and other registered ECEC services, UOE and OECD 
(2019) ..................................................................................................................................................................................................................................... 38 

Figure A.3. Comparison of enrolment rates based on EU-SILC and UOE (top panel) vs UOE+ad-hoc OECD data 
collection (bottom panel) (2016-2019) ............................................................................................................................................................ 39 

Figure A.4. Enrolment rates and affluence of maternity/paternity/parental leaves, in terms of net equivalised 
income (2014) ................................................................................................................................................................................................................... 41 

33 

 
 
List of tables 

Table A.1. EU-SILC sample sizes for age group 0-2 by country (2010-2019) ........................................................................ 36 

Table A.2. EU-SILC overall sample size, by country (2016-2019) ................................................................................................... 37 

Table A.3 Summary of available paid leave entitlements. ................................................................................................................... 40 

Table A.4. Maximum number of children per staff member at ages 0, 1 and 2. ................................................................... 42 

Table A.5. EU-SILC sample sizes for age group 1-2, by country (2010-2019) ....................................................................... 43 

Table A.6. ECEC enrolment rates by intensity of care (number of hours per week), EU-SILC (2019) ....................... 44 

Table A.7. ECEC enrolment rates for age group 0-2 by socio-economic background, EU-SILC (2016) ................... 45 

34 

 
 
 
 
Annex 

35 

Table A.1. EU-SILC sample sizes for age group 0-2 by country (2010-2019)  

Country 

2010 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019 

2019/2011 
% change 

AT 
BE 
BG 
CY 
CZ 
DE 
DK 
EE 
EL 
ES 
FI 
FR 
HR 
HU 
IE 
IT 
LT 
LU 
LV 
MT 
NL 
PL 
PT 
RO 
SE 
SI 
SK 

401 
564 
240 
189 
612 
607 
364 
414 
458 
965 
910 
869 

596 
601 
1138 
216 
625 
376 
205 
837 

175 
147 
593 
850 
295 

372 
543 
254 
214 
594 
573 
341 
408 
322 
826 
797 
878 

381 
516 
215 
320 
510 
537 
327 
449 
310 
733 
828 
894 

641 
530 
1084 
191 
610 
370 
235 
836 

616 
715 
965 
183 
565 
328 
246 
799 
1084  1072 
269 
132 
534 
755 
227 

215 
153 
568 
811 
229 

356 
504 
168 
312 
469 
482 
274 
456 
352 
748 
950 
758 
217 
456 
685 
915 
144 
349 
270 
248 
698 
988 
313 
120 
464 
701 
314 

351 
511 
171 
317 
402 
452 
293 
447 
400 
743 
925 
791 
229 
427 
663 
959 
164 
343 
308 
277 
646 
949 
303 
107 
419 
697 
332 

374 
508 
170 
287 
393 
425 
251 
447 
617 
748 
909 
754 
322 
410 
611 
758 
135 
264 
353 
249 
596 
872 
365 
107 
434 
632 
319 

390 
414 
276 
258 
475 
507 
292 
462 
781 
802 
853 
726 
342 
409 
548 
872 
166 
328 
358 
210 
683 
877 
436 
99 
448 
622 
292 

372 
419 
279 
299 
533 
499 
274 
413 
883 
751 
729 
683 
341 
378 
470 
799 
194 
348 
334 
168 
643 
960 
472 
95 
474 
672 
303 

391 
430 
255 
245 
507 
493 
237 
397 
823 
646 
660 
600 
351 
334 
422 
650 
198 
358 
288 
147 
572 
1128 
525 
101 
465 
667 
317 

354 
446 
250 
196 
489 
453 
241 
395 
490 
762 
614 
656 
264 
268 
401 
380 
188 
322 
303 
120 
545 
1520 
536 
102 
404 
603 
295 

-11.7 
-20.9 
4.2 
3.7 
-20.1 
-25.4 
-33.8 
-4.6 
7.0 
-21.0 
-32.5 
-24.5 
21.7 
-55.0 
-33.3 
-66.6 
-13.0 
-48.5 
-19.4 
-41.5 
-34.9 
40.2 
206.3 
-30.6 
-31.9 
-29.1 
0.0 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC (2010-2019). 

Notes: sample sizes below 100 are marked in red, sample sizes between 100 and 149 are highlighted in bold. 

36 

  
  
  
  
 
 
Table A.2. EU-SILC overall sample size, by country (2016-2019) 

Country 

2016 

2017 

2018 

2019 

2016/2019 % 
change 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

10,848 

11,054 

15,515 

9,388 

16,157 

23,144 

11,721 

12,499 

37,850 

30,688 

20,742 

21,325 

16,957 

15,826 

10,178 

41,547 

9,614 

8,228 

11,637 

9,209 

24,123 

27,131 

22,693 

15,795 

11,227 

21,930 

14,101 

10,778 

11,352 

15,382 

9,623 

16,286 

23,081 

10,826 

12,640 

46,478 

29,294 

19,939 

20,469 

17,376 

15,729 

9,804 

42,392 

9,798 

8,766 

11,304 

8,755 

24,608 

29,098 

25,848 

15,688 

11,572 

22,400 

13,824 

10,633 

11,082 

14,939 

9,317 

16,054 

21,917 

9,949 

12,290 

48,903 

28,372 

19,224 

19,952 

18,372 

14,365 

8,580 

39,969 

9,755 

8,526 

10,785 

8,542 

23,113 

33,380 

29,360 

15,537 

11,404 

21,924 

13,588 

10,351 

12,590 

14,980 

9,295 

16,127 

20,854 

10,291 

12,424 

34,836 

33,376 

18,720 

21,421 

17,121 

12,980 

8,217 

38,327 

9,906 

8,505 

9,578 

8,351 

25,378 

42,377 

28,783 

15,314 

10,660 

21,370 

12,719 

-4.6 

13.9 

-3.4 

-1.0 

-0.2 

-9.9 

-12.2 

-0.6 

-8.0 

8.8 

-9.7 

0.5 

1.0 

-18.0 

-19.3 

-7.8 

3.0 

3.4 

-17.7 

-9.3 

5.2 

56.2 

26.8 

-3.0 

-5.1 

-2.6 

-9.8 

Source: authors’ calculations based on EU-SILC microdata, 2016-2019. 

37 

 
Figure A.1. Enrolment rate for children aged 0-2 in ISCED 0 and other registered ECEC services, UOE and OECD (2016) 

e
t
a
r

t
n
e
m
o
r
n
E

l

70

60

50

40

30

20

10

0

5

42

53 56

57

1

45

3

35

30

27 25

32

36

37 39

4

1

18

CY AT HR LT LV EE FI ES FR PT DE SI SE LU NL BE DK

2

12

18 20 18 20 23

9 17

2
5

2
5

5

5

6

6

3
BG EL IT MT RO CZ SK PL IE HU EU-
27

3

5

ECE (ISCED0)

Other registered
ECEC services

Barcelona target for age group 0-2
based on EU-SILC data (33%)

Source: authors’ calculations based on Eurostat and OECD data. Data on early childhood education (ISCED 0) come from Eurostat UOE data, 
2016 [educ_uoe_enra25]. Data on other registered ECEC services outside the scope of ISCED 0 come from an INES ad-hoc survey in OECD 
Education at a Glance 2018 [Table B2.1a] for all countries covered in the OECD data collection.  
Notes: Early childhood education (ISCED 0) covers programmes classified as ISCED 0; other registered ECEC services (Non-ISCED 0) cover 
other ECEC services that lie outside the scope of ISCED 0 because they do not comply with all ISCED criteria (and are therefore excluded 
from UOE data). Countries are ordered by increasing shares of ECEC participation (including programmes both within and outside the scope 
of ISCED 0).  

Figure A.2. Enrolment rate for children aged 0-2 in ISCED 0 and other registered ECEC services, UOE and OECD (2019) 

70

60

50

40

30

20

10

0

e
t
a
r

t
n
e
m
o
r
n
E

l

1

4

4

5

5

5

6

7

9 10

10
3

LU FR BG SK HU IT CZ MT RO EL PL EU-
27

5

62

56

3

19 22 20

25 25

30 31

26

35 39 40 40

44 46 47

0
HR AT CY IE LT LV EE FI DE ES PT SI BE SE DK NL

ECE (ISCED0)

Other registered
ECEC services

Barcelona target for age group 0-2
based on EU-SILC data (33%)

Source: authors’ calculations based on Eurostat and OECD data. Data on early childhood education (ISCED 0) come from Eurostat UOE data, 
2019 [educ_uoe_enra25]. Data on other registered ECEC services outside the scope of ISCED 0 come from  OECD Education at a Glance 
2021 [Table B2.1] for all countries covered in the OECD data collection.  
Notes: Early childhood education (ISCED 0) covers programmes classified as ISCED 0; other registered ECEC services (Non-ISCED 0) cover 
other ECEC services that lie outside the scope of ISCED 0 because they do not comply with all ISCED criteria (and are therefore excluded 
from UOE data). Countries are ordered by increasing shares of ECEC participation (including programmes both within and outside the scope 
of ISCED 0).  

38 

 
 
 
 
 
 
Figure A.3.  Comparison of enrolment rates  based on  EU-SILC and UOE (top  panel) vs UOE+ad-hoc  OECD data collection 
(bottom panel) (2016-2019) 

2016 

2019 

2016 

2019 

Source: authors’ calculations based on Eurostat (EU-SILC and UOE) and OECD data. See previous figures for more information.  
Notes: Countries reported in light blue in the bottom panel are those for which information on “Other registered ECEC services” is included 
from OECD data.  

39 

 
 
 
 
 
 
Table A.3 Summary of available paid leave entitlements. 

Total paid leave available to mothers, 2020  Net equivalised income over the period of parental and home care 

Country 

Length 
(weeks) 

Average 
payment 
rate (%) 

Full-rate 
equivalent 
(weeks) 

leave, 2014 

First month 
after birth 

Six months 
after 
childbirth 

One year 
after 
childbirth 

Two years after 
childbirth 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

60.0 

32.3 

110.4 

18.0 

75.1 

58.0 

50.0 

82.0 

43.0 

16.0 

161.0 

42.0 

56.0 

160.0 

28.0 

47.7 

62.0 

46.0 

94.0 

18.0 

16.0 

52.0 

30.1 

108.7 

55.7 

52.1 

164.0 

80.3 

41.7 

61.1 

72.0 

73.8 

73.4 

52.4 

100.0 

61.8 

100.0 

25.0 

45.2 

83.5 

41.1 

27.3 

52.7 

77.6 

85.2 

53.9 

85.6 

99.2 

80.0 

67.7 

85.0 

61.9 

100.0 

42.2 

48.2 

13.5 

67.5 

13.0 

55.4 

42.6 

26.2 

82.0 

26.6 

16.0 

40.2 

19.0 

46.8 

65.8 

7.6 

25.2 

48.1 

39.2 

50.6 

15.4 

15.9 

41.6 

20.4 

92.4 

34.5 

52.1 

69.2 

91.1 

85.4 

100.2 

89.6 

92.9 

59.8 

91.9 

76.5 

85.2 

59.5 

77.3 

90.1 

86.7 

83.5 

90.0 

92.4 

102.4 

85.9 

87.5 

89.4 

116.3 

96.6 

73.6 

90.8 

87.4 

82.7 

60.3 

93.0 

75.4 

72.5 

67.7 

91.8 

45.0 

45.7 

66.0 

43.3 

90.2 

84.7 

63.4 

88.0 

71.2 

93.0 

47.0 

70.0 

74.3 

69.9 

81.7 

76.5 

88.0 

86.6 

82.7 

49.5 

93.0 

71.7 

75.4 

72.5 

75.4 

42.1 

91.8 

51.6 

45.7 

49.0 

41.6 

84.7 

46.5 

70.0 

45.7 

50.3 

43.3 

68.7 

84.7 

46.4 

88.0 

71.2 

93.0 

70.0 

79.2 

81.7 

53.3 

65.8 

65.8 

Source: OECD Family Database, extraction from Tables PF 2.4 and PF 2.1 
Notes: OECD refers to net equivalised household income in the first month after the birth, six months after the birth, one year after the 
birth, and two years after the birth, as a percentage of net equivalised household income one year before the birth, by level of earnings. 
Situation for a two-child two-earner family with both parents on the mentioned percentage of average earnings. The elder child is assumed 
to be two years older than the child just born. Parents are assumed to be in full-time work except during the leave periods. Parents are 
assumed to take all available maternity and paternity leave (including unpaid maternity and paternity leave) in one spell and at the earliest 
possible  opportunity,  regardless  of  the  payment  level,  and  all  available  paid  parental  leave  in  one  spell  and  at  the  earliest  possible 
opportunity, except where there are individual mother- and father-specific paid parental leave entitlements, in which case parents take paid 
parental leave sequentially with the mother using her entitlement first and the father second. Parents do not take additional (secondary) 
unpaid  parental  leave  if  they  have  already  taken  paid  parental  leave,  but  do  use  any  unpaid  weeks  of  a  partially-paid  parental  leave 
entitlement, and do take unpaid parental leave if no paid parental leave is available. Data shown only if at least one parent is on leave at 
the given point in time. 

40 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure A.4. Enrolment rates and affluence of maternity/paternity/parental leaves, in terms of net equivalised income 
(2014) 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, and OECD Family Database. 

41 

 
 
 
 
 
 
Table A.4. Maximum number of children per staff member at ages 0, 1 and 2. 

AT 
BE (de) 
BE (fr) 
BE (nl) 
BG 
CY 
CZ 
DE 
DK 
EE 
EL 
ES 
FI 
FR 
HR 
HU 
IE 
IT 
LT 
LU 
LV 
MT 
NL 
PL 
PT 
RO 
SE 
SI 
SK 

Age 0 
4 to 5 
6 
7 
9 
9 
6 
X 
4 to 8 
nr 
X 
4 
8 
4 
5 
5 
4 
3 
nr 
6 
6 
X 
3 
3 
5 
5 
4 
X 
6 
5 

Age 1 
4 to 8 
6 
7 
9 
9 
6 
8 
4 to 8 
nr 
8 
4 
13 
4 
5 
8 
4 
5 
nr 
10 
6 
nr 
5 
5 
8 
7 
5 
nr 
6 
5 

Age 2 
4 to 8 
6 
7 
9 
9 
16 
12 
4 to 8 
nr 
8 
4 
18 
4 
8 
14 
4 
6 
nr 
15 
8 
nr 
6 
8 
8 
9 
6 
nr 
6 
5 

X: no service provided; nr: no regulation applied.  
Source: Eurydice 2019: Key data on early childhood education and care in Europe - Publications Office of the EU (europa.eu), table on page 
154.  

42 

  
 
 
Table A.5. EU-SILC sample sizes for age group 1-2, by country (2010-2019) 

Country 

2010 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019 

AT 
BE 
BG 
CY 
CZ 
DE 
DK 
EE 
EL 
ES 
FI 
FR 
HR 
HU 
IE 
IT 
LT 
LU 
LV 
MT 
NL 
PL 
PT 
RO 
SE 
SI 
SK 

267 
382 
177 
143 
447 
436 
286 
291 
314 
656 
628 
586 

455 
368 
838 
165 
433 
303 
147 
591 

142 
117 
400 
570 
229 

248 
372 
189 
153 
424 
402 
266 
287 
246 
603 
552 
638 

496 
381 
829 
144 
438 
303 
158 
604 
767 
169 
127 
381 
567 
196 

269 
353 
162 
267 
380 
373 
231 
306 
221 
538 
576 
606 

479 
429 
706 
133 
411 
266 
170 
552 
782 
223 
112 
366 
554 
160 

244 
355 
131 
254 
338 
348 
180 
313 
250 
525 
657 
517 
149 
372 
427 
650 
114 
238 
208 
176 
508 
689 
246 
96 
316 
489 
237 

224 
339 
122 
243 
290 
327 
199 
306 
299 
536 
631 
560 
166 
300 
409 
685 
132 
236 
246 
183 
466 
671 
230 
93 
303 
489 
264 

253 
366 
127 
213 
256 
294 
187 
313 
455 
542 
624 
517 
224 
284 
379 
559 
94 
174 
276 
171 
413 
620 
283 
86 
300 
439 
253 

270 
292 
205 
179 
339 
355 
189 
323 
573 
571 
621 
511 
244 
309 
330 
703 
127 
220 
296 
148 
463 
616 
318 
76 
311 
426 
220 

253 
294 
198 
236 
381 
338 
203 
305 
670 
534 
518 
474 
248 
279 
284 
640 
149 
231 
260 
121 
449 
651 
366 
78 
345 
442 
238 

282 
314 
187 
191 
382 
363 
153 
287 
604 
480 
458 
416 
229 
259 
255 
518 
151 
243 
224 
110 
406 
774 
394 
81 
311 
485 
250 

252 
325 
187 
159 
350 
333 
164 
264 
365 
551 
411 
454 
197 
206 
245 
306 
148 
217 
245 
82 
379 
1066 
396 
81 
277 
430 
240 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC (2010-2019). 
Notes: sample sizes below 100 are marked in red, sample sizes between 100 and 149 are highlighted in bold. 

43 

Table A.6. ECEC enrolment rates by intensity of care (number of hours per week), EU-SILC (2019) 

Country 

EU-27 

1-19 Hrs 
6 

Age 0-2 

20 -29 Hrs 
7.9 

30+ Hrs 
21.6 

1-19 Hrs 
7.3 

Age 1-2 

20 -29 Hrs 
10.2 

30+ Hrs 
28.4 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

MT 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

5.9 

5.2 

1 

0.7 

1.4 

3.4 

4.3 

2.9 

1.9 

7.4 

1.5 

10.1 

0.4 

0 

16.4 

1.4 

0 

5.9 

0.3 

2.2 

41 

0.9 

0 

4.5 

6 

1 

0.8 

8.8 

14.3 

0 

5.4 

2 

4.8 

3.7 

5.1 

16.5 

23.1 

9.1 

7 

0.7 

3.3 

9.4 

6.2 

3.7 

6.9 

0.8 

11.4 

17.7 

0.9 

2.6 

8.6 

10.1 

1.5 

0.8 

8 

36 

18.7 

25 

2.9 

23.2 

58.1 

23.8 

14 

26.9 

27.6 

33.6 

14.6 

13.6 

15 

18.7 

22.9 

47.2 

27.2 

24.7 

6.2 

8.3 

50.3 

1 

37.1 

44.4 

5 

8.7 

7.7 

0.7 

1 

2 

4.8 

5.5 

4.5 

2.5 

9 

1.9 

12.2 

0.6 

0 

21.6 

1.4 

0 

8.3 

0 

3 

44.3 

1.4 

0 

5.9 

8.6 

1.5 

1.1 

13 

15.6 

0 

6.9 

2.8 

6.4 

4.3 

7.8 

22.3 

31.8 

12.7 

7.5 

1 

4.9 

11.6 

8.4 

5 

10 

1 

12.9 

21.1 

1.4 

2.2 

11.3 

14.6 

2.2 

1.1 

11.7 

42.3 

25.6 

28.5 

4.1 

32.9 

76.5 

36.5 

18.1 

34.8 

39.8 

39.7 

21.3 

20.3 

18.9 

24.6 

30.3 

61 

33.6 

34.4 

7.1 

12 

56.4 

1.3 

53.6 

65.6 

6.7 

Source: authors’ calculations based on a Eurostat special extraction from EU-SILC, 2019 

44 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table A.7. ECEC enrolment rates for age group 0-2 by socio-economic background, EU-SILC (2016) 

ECEC enrolment rate 

Sample size 

Country 

Overall  

AROPE 

Not AROPE 

Sign.  
Diff. 

Overall  

AROPE 

Not AROPE 

EU 

AT 

BE 

BG 

CY 

CZ 

DE 

DK 

EE 

EL 

ES 

FI 

FR 

HR 

HU 

IE 

IT 

LT 

LU 

LV 

NL 

PL 

PT 

RO 

SE 

SI 

SK 

33.8 

20.5 

43.8 

12.5 

24.9 

4.7 

32.9 

70 

30.2 

8.9 

39.3 

32.6 

48.9 

15.6 

15.6 

28.6 

34.4 

15.2 

50.9 

28.3 

53 

7.8 

49.9 

17.4 

51 

39.5 

0.5 

22.4 

23.6 

30.9 

10.9 

17 

2.2 

28.6 

26.6 

7.2 

25.5 

22.4 

24.2 

12.9 

6.6 

26.8 

25.2 

6.6 

45.9 

19.2 

19.1 

6.3 

38.1 

16.2 

u 

44.8 

26.2 

0 

37.2 

19.6 

46.6 

14 

27.9 

5.2 

34 

c 

71.1 

31 

9.6 

44 

35.3 

55.6 

16.5 

18.5 

29.1 

37.5 

19.6 

52.2 

31.3 

60.1 

8.2 

52.6 

18.1 

52.7 

42.2 

0.7 

*** 

n.s 

* 

n.s 

n.s 

n.s 

n.s 

n.s 

n.s 

*** 

** 

*** 

n.s 

** 

n.s 

** 

* 

n.s 

* 

*** 

n.s 

* 

n.s 

n.s 

** 

n.s 

12710 

2870 

9840 

390 

414 

276 

258 

475 

500 

292 

462 

781 

802 

853 

726 

342 

409 

549 

872 

166 

328 

358 

683 

877 

436 

99 

448 

622 

292 

78 

88 

137 

67 

73 

105 

17 

100 

252 

218 

134 

151 

86 

130 

138 

204 

59 

68 

90 

70 

201 

120 

34 

72 

98 

80 

312 

326 

139 

191 

402 

395 

275 

362 

529 

584 

719 

575 

256 

279 

411 

668 

107 

260 

268 

613 

676 

316 

65 

376 

524 

212 

Source: authors’ calculations based on EU-SILC microdata, 2016. 

Notes: c = confidential (sample of less than 20 observations); u = unreliable (between 20 and 49 observations). The column “Sign. diff.” 
reports the level of significance of the difference between the AROPE and non-AROPE subgroups. * p < 0.05, ** p < 0.01, *** p < 0.001; 
“n.s.”, difference is not significant. Sample sizes below 100 are marked in red, sample sizes between 100 and 149 are highlighted in bold. 
MT is missing because no age variable is available in the dataset. See Flisi and Blasko (2019) for more information.   

45 

  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
  
 
  
 
  
  
 
  
 
  
  
  
 
  
 
 
 
 
 
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