Commission staff working document - Social situation report 2007 - Social Cohesion through Equal Opportunities
Date: 2008-04-28
Institutions: European Commission
Subjects: anti-discriminatory measure, application of EU law, economic and social cohesion, equal treatment

COMMISSION OF THE EUROPEAN COMMUNITIES 

Brussels, 28.4.2008 
SEC(2008)561 

COMMISSION STAFF WORKING DOCUMENT 

SOCIAL SITUATION REPORT 2007 

Social Cohesion through Equal Opportunities

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TABLE OF CONTENTS 

Part 1 – Social Cohesion through Equal Opportunities.............................................................. 4 

1. 

1.1. 

1.2. 

1.3. 

Assessing the Case for Equal Opportunities Across the EU: An Overview ................ 4 

EU-SILC: The new tool for monitoring the social situation in the EU ....................... 4 

Income inequality and economic performance ............................................................ 5 

Low incomes — a European perspective..................................................................... 6 

1.4.  Who are the poor: groups most at risk in the Member States ...................................... 8 

1.5. 

1.6. 

1.7. 

1.8. 

2. 

2.1. 

2.2. 

2.3. 

Low incomes and living standards in the EU............................................................. 10 

Intergenerational transmission of disadvantages ....................................................... 11 

Children from a migration background and equal opportunities ............................... 12 

Equal opportunities: the key to economic growth and social cohesion ..................... 13 

Income Distribution and Poverty Risks in the EU ..................................................... 14 

EU-SILC: The new tool for monitoring the social situation in the EU ..................... 14 

Income inequality and economic performance .......................................................... 18 

Low incomes — a European perspective................................................................... 27 

2.4.  Who are the poor: groups most at risk in the Member States .................................... 35 

2.5. 

Low incomes and living standards in the EU............................................................. 47 

3. 

3.1. 

3.2. 

The Scope for More Equal Opportunities .................................................................. 62 

Intergenerational transmission of disadvantages ....................................................... 62 

Children from a migration background and equal opportunities ............................... 75 

Part 2 - Areas of Social Policy Concern: Statistical Portraits ................................................ 100 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

Economic Situation .................................................................................................. 102 

Demography, Households and Families .................................................................. 109 

Ageing of the Population ......................................................................................... 112 

International Migration and Asylum........................................................................ 115 

Education and its Outcomes..................................................................................... 119 

Lifelong Learning .................................................................................................... 123 

Employment ............................................................................................................. 130 

Unemployment......................................................................................................... 136 

Labour Market Policy Expenditure.......................................................................... 140 

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10. 

11. 

12. 

13. 

14. 

15. 

16. 

17. 

18. 

Social Protection Expenditure and Receipts ............................................................ 145 

Social Benefits ......................................................................................................... 150 

Income Distribution ................................................................................................. 156 

Low-income Households ......................................................................................... 161 

Jobless Households and Low wages ........................................................................ 168 

Women and Men in Decision Making ..................................................................... 172 

Earnings of Women and Men .................................................................................. 176 

Life and Health Expectancies................................................................................... 183 

Accidents and Work-related Health Problems......................................................... 190 

Annex 1.1 - Key Indicators per Geopolitical Entity - Latest year available .......................... 197 

Annex 1.2 - Key Indictors per Geopolitical Entity - Time Series.......................................... 201 

Annex 1.3 - Other Statistical Tables per Geopolitical Entity................................................. 222 

Annex 2: Symbols, Country Codes and Country Groupings, other Abbreviations and 
Acronyms ............................................................................................................................... 240 

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PART 1 – SOCIAL COHESION THROUGH EQUAL OPPORTUNITIES 

1. 

ASSESSING  THE  CASE  FOR  EQUAL  OPPORTUNITIES  ACROSS  THE  EU:  AN 
OVERVIEW 

The  2007  Social  Situation  Report  presents  some  key  findings  from  the  EU’s  new  tool  for 
monitoring  the  social  situation  and,  in  the  future,  social  trends,  namely  the  EU-SILC 
(Statistics  on  Income  and  Living  Conditions).  It  looks  at  income  inequality  and  how  this  is 
related to economic performance and at how people on low incomes are distributed across the 
EU  as  a  whole.  Promoting  equal  opportunities  in  the  European  Union  could  make  a  major 
contribution  to  both  greater  social  cohesion  and  economic  performance  by  mobilising  the 
unused  potential  of  disadvantaged  groups.  Two  sections  in  this  report  look  notably  at  the 
transmission  of  social  disadvantages  from  one  generation  to  the  next  and  at  poverty  risks 
among children from a migration background and ethnic minorities.  

The report also tries to identify the largest groups at risk of poverty in the different Member 
States and the extent to which low incomes are linked to access to various essential goods and 
services.  In  view  of  the  theme  of  the  2007  European  Year, the  Social  Situation  Report  also 
has a special focus on equal opportunities. It only scratches the surface of the wealth of data 
produced  by  EU-SILC,  and  the  Commission  invites  the  research  community  to  make 
extensive use of this data source. 

The evidence presented in the Social Situation Report underlines once again the importance of 
investing  in  people,  most  recently  stressed  by  the  Commission  in  its  contribution  to  the 
October Meeting of Heads of State and of Government on the theme Succeeding in the age of 
globalisation1.  How  the  challenges  of  equal  opportunities  are  to  be  tackled  is  also  a  major 
aspect of the public consultation on the ‘social reality’ of Europe2. 

1.1. 

EU-SILC: The new tool for monitoring the social situation in the EU 

The  European  Union  has  a  powerful  new  tool  for  monitoring  the  social  situation  and 
trends  across  all  Member  States  and  thus  for  supporting  the  development  of  better  social 
policies through the Open Method of Coordination. 

Internationally comparable data for monitoring the economic situation and trends have been 
collected  for  about  half  a  century.  By  contrast,  equivalent  tools  for  monitoring  social 
conditions are still in their infancy. Over the past decade, the European Union has made major 
progress  in  producing  internationally  comparable  data  for  social  monitoring.  The  European 
Community  Household  Panel  survey  (ECHP)  was  first  carried  out  in  1994  and  produced 
annual data on social conditions for a decade. It has now been replaced by a new instrument, 
EU-SILC  (Statistics  on  Income  and  Living  Conditions),  with  this  year  data  for  almost  all 
Member States.  

With  EU-SILC  the  European  Union  has  a  much  improved  tool  for  monitoring  the  social 
situation  and  trends.  It  uses  larger  samples,  allowing  more  detailed  analysis  of  the 

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COM(2007) 581 final. 
See http://ec.europa.eu/citizens_agenda/social_reality_stocktaking/index_en.htm.  

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characteristics of the most vulnerable households. The time lag between collection of data and 
publication — three years or more in the case of the ECHP — has been reduced by about one 
year; nevertheless the most recent data used for this report were collected in 2005 and refer to 
incomes in 20043. So the availability of social data will continue to lag considerably behind 
key economic indicators. 

Without internationally comparable data on the social situation as produced by the ECHP and 
EU-SILC, key policy developments in the European Union would not have been possible. A 
major  breakthrough  in  this  regard  has  been  the  establishment  of  an  Open  Method  of 
Coordination,  in  which  Member  States  agreed  on  common  objectives  and  indicators  for 
monitoring  progress  towards  these  objectives  in  the  field  of  social  protection  and  social 
inclusion. Most of these indicators rely on the existence of internationally harmonised surveys 
on incomes and living conditions such as the ECHP and EU-SILC4. 

1.2. 

Income inequality and economic performance 

Incomes are more evenly distributed within the EU than in the US, and in the EU a high 
level of economic performance often goes hand in hand with greater equality.  

According  to  data  published  by  the  OECD  (see  section  2.1  of  the  Social  Situation  Report) 
income  is  much  more  equally  distributed  in  most  Member  States  than  in  the  US.  The  most 
commonly  used  indicator  for  inequality  is  the  Gini  coefficient,5  which  varies  between  0  (if 
everyone gets an equal share of total income) and 100 (if all income goes to one individual 
only). In 2000, the Gini coefficient in the US stood at 35.7. Using EU-SILC and taking the 
population  of  EU-25  as  a  whole,  and  adjusting  for  purchasing  power  differences  across 
Member States, the Gini coefficient for EU-25 can be estimated at around 32.7. This is still 
significantly  less  than  in  the  US,  despite  the  large  differences  in  GDP  per  head  across 
Member  States.  The  results  from  EU-SILC  also  show  that  only  Portugal  surpasses  the  US 
level (41), while Poland, Latvia and Lithuania (at 36) have similar levels of inequality as the 
US. 

The  international  comparison  of  Gini  coefficients  also  suggests  that  there  might  not  be  a 
trade-off  between  equity  and  economic  performance,  as  measured  by  GDP  per  capita,  after 
all. Indeed, plotting the Gini coefficients of EU and applicant countries against their GDP per 
capita shows that the more developed countries also tend to be more egalitarian. While this 
does  not  imply  that  reducing  inequalities  raises  economic  performance  it  does  suggest  that 
low inequality is also consistent with high GDP per capita. 

Taxing the rich to redistribute income to the poor could, according to economic theory, reduce 
aggregate  economic  performance  due  to  deadweight  losses  associated  with  taxation  and 
incentive  effects  of  income-related  transfer  payments.  Economist  Arthur  Okun  used  the 
metaphor of a leaky bucket. However, a relatively equal distribution of incomes need not be 

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The United Kingdom has income reference period 2005 and Ireland a moving income reference period 
2004-05. Household composition etc. reflect the survey period. Note also that the EU-SILC data used in 
the statistical portraits and their annexes was extracted later than for the analysis in this first part of the 
report. Therefore, there might be some inconsistencies between these two parts.   
See  http://ec.europa.eu/employment_social/social_inclusion/indicators_en.htm  for  the  latest  list  of 
indicators. 
The  Gini  coefficient  is  defined  as  the  relationship  of  cumulative  shares  of  the  population  arranged 
according to the level of income, to the cumulative share of the equivalised total net income received by 
them.  

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the result of large-scale redistribution alone. It may be the result of a more narrow distribution 
of  market  incomes  resulting  from  more  equal  opportunities  for  people  to  develop  their  full 
productive potential and contribute to the generation of income. This requires good chances 
for all to access high-quality education, health care and jobs.  

Greater equality resulting from more equal opportunities does not entail the efficiency losses 
potentially  associated  with  redistribution.  On  the  contrary,  promoting  equal  opportunities 
makes  it  possible  to  boost  growth  by  mobilising  resources  that  were  previously  blocked  by 
discrimination and social exclusion. The Social Situation Report’s analysis of social mobility 
suggests  that  a  sizeable  proportion  of  the  European  population  does  not  develop  its  full 
potential. This slows down Europe’s economic development and implies that too many people 
having to live in poor conditions. 

The Report also discusses inequality trends since the 1970s. There is no common trend across 
all countries  under review;  in  each of the sub-periods considered, there  were countries with 
rising  inequality  and  others  with  declining  inequality.  However,  from  the  mid-1980s  to  the 
mid-1990s  a  clear  majority  of  countries  experienced  rising  inequality,  a  trend  which  now 
seems  to  have  subsided  somewhat.  A  recently  completed  study  on  the  social  impact  of 
globalisation in the European Union6 concluded that there is no (or only weak) evidence that 
this  rise  in  income  inequalities  is  attributable  to  globalisation  and  suggested  that  it  is  more 
likely to be intimately associated with the emergence of the knowledge society resulting in an 
increase in the return on human capital and a widening gap between those with a high and a 
merely basic endowment of knowledge and skills.  

1.3. 

Low incomes — a European perspective 

In 2004, around 100 million Europeans (22 % of the total population) had less than 60 % 
of  the  EU  median  income  of  around  €8000  per  year  for  a  single  person  or  €22  a  day 
(amounts  adjusted  for  purchasing  power  and  household  size;  purchasing  power  standard 
PPS7  used  below).  Some  23.5  million  had  to  get  by  on  less  than  €10  a  day.  The 
concentration of people with low incomes relative to the EU median is highest in the poorer 
new Member States, but a large proportion of the low income population can be found in 
the richer EU-15 countries. 

The Open Method of Coordination mainly uses a relative concept of poverty adopted by the 
European  Council  in  1975  which  defined  the  poor  as  “individuals  and  families  whose 
resources  are  so  small  as  to  exclude  them  from  the  minimal  acceptable  way  of  life  in  the 
Member State in which they live”. This relative concept acknowledges that it is not enough to 
ensure access for all to a minimum subsistence level. The aim is also to ensure that all citizens 
can  benefit  from  the  general  level  of  prosperity  of  their  country  and  participate  as  full 
members of society. The main indicator used to reflect this concept is the at-risk-of-poverty 
rate, defined as the percentage of individuals whose equivalised disposable income is below 
60 %  of  the  national  median  income.  The  at-risk-of-poverty  rate  is  published  and  analysed 
jointly  with  the  at-risk-of-poverty  thresholds  in  each  Member  State,  which  range,  in 

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See http://ec.europa.eu/employment_social/social_situation/docs/simglobe_fin_rep.pdf 
One PPS buys the same given volume of goods and services in all countries, whereas different amounts 
of  national  currency  units  are  needed  to  buy  this  same  volume  of  goods  and  services  in  individual 
countries,  depending  on  the  price  level.  PPS  are  obtained  by  dividing  their  original  value  in  national 
currency units by the respective purchasing power parity (PPP), see definition in section 2.3 and table 4. 

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purchasing  power  standards,  from  around  1500-2000  PPS  (Romania,  Bulgaria)  to  around 
10000 PPS (UK, Germany, Denmark, Netherlands) per year. 

The Social Situation Report complements this nationally centred perspective with a European 
perspective (section 2.3). One of the European Union’s main tasks is to raise the standard of 
living and quality of life of all Europeans and to promote economic and social cohesion and 
solidarity  among  Member  States.  Progress  towards  these  objectives  is  mainly  assessed  by 
looking  at  GDP  per  head.  EU-SILC  makes  it  possible  to  assess  the  challenge  of  social 
cohesion  by  looking  also  at  the  number  of  Europeans  whose  incomes  fall  short  of  the 
European  average  in  purchasing  power  terms  or  a  given  absolute  amount.  Monitoring  these 
numbers  over  time  would  make  it  possible  to  assess  whether  all  Europeans  are  benefiting 
from  the  economic  progress  brought  by  European  integration  and  helped  by  the  European 
Union’s structural funds as well as appropriate national social policies. It would accordingly 
complement the monitoring of the process of economic convergence as measured by GDP per 
head  relative  to  the  EU  average,  but  also  the  monitoring  of  social  inclusion  within  a  given 
Member  State  which  focuses  particularly  on  the  number  of  people  with  incomes  below  a 
certain percentage of national median income.8 

Various common thresholds, all expressed in PPS to adjust for differing price levels across the 
EU,  were  selected  before  estimating  the  absolute  numbers  and  proportions  of  people  with 
incomes below this threshold. This was possible only for 24 Member States (EU-27 excluding 
Malta,  Bulgaria  and  Romania).  22 %  of  Europeans  (just  over  100  million)  have  an 
equivalised9  income  below  60 %  of  the  EU  median  income.  16 %  (73.2  million)  are  below 
50 % of the median income and 11 % (48.8 million) below 40 %. These levels of 60 %, 50 % 
and 40 % of the EU median income correspond to an annual disposable income of 8040 PPS, 
6700  PPS  and  5360  PPS  respectively  for  a  single  person,  or  €22,  €18  and  just  under  €15  a 
day. The proportion of people whose income is below 60 % of their national median income 
— this is the at-risk-of-poverty rate as used in the Open Method of Coordination — is 16 %. 
EU-SILC can also be used to estimate what proportion of the European population have to get 
by on extremely low incomes of €10 a day: 5 % (23.5 million people), or even €5 a day: 2 % 
(6.9 million).  

These  figures  are  estimates  and  subject  to  various  caveats  (see  section  2.1  of  the  Social 
Situation  Report).  People  with  low  monetary  incomes  may  be  able  to  consume  goods  and 
services produced informally within the household or local community, which tends to be the 
case in economically less developed and more rural areas. Very low income may also be the 
result of trading losses reported by the self-employed. Monetary incomes thus provide only a 
very partial guide to living standards and the risk of social exclusion. 

The  highest  concentrations  of  people  below  these  various  thresholds  can  obviously  be 
observed in the poorest Member States. More than three quarters of the population in Estonia, 
Latvia,  Lithuania,  Hungary,  Poland  and  Slovakia  live  on  incomes  below  60 %  of  the  EU 
median; half or more of the population in these same countries (except Hungary where it is 

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Data  on  these  indicators  are  published  by  the  Commission  notably  in  the  Joint  Report  on  Social 
Protection and Social Inclusion. http://ec.europa.eu/employment_social/spsi/joint_reports_en.htm 
Household  income  is  equivalised  (adjusted)  in  order  to  reflect  differences  in  household  size  and 
composition.  In  other  words,  the  total  household  income  is  divided  by  the  number  of  household 
members weighted using the so-called "modified OECD" equivalent scale. This equivalence scale gives 
a weight of 1.0 to the first adult, 0.5 to any other household member aged 14 and over and 0.3 to each 
child. The resulting figure is attributed to each member of the household, whether adult or child.  

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40 %) have to get by on less than 40 % of the EU median income. The proportion of people 
who  have  to  live  on  no  more  than  €10  a  day  approaches  40 %  in  Latvia  and  Lithuania  and 
exceeds one quarter in Estonia and Poland. In four Member States, more than five percent of 
the population have no more than €5 a day: Estonia (5 %), Latvia (9 %), Lithuania (10 %) and 
Poland (7 %).  

While these extreme low-income situations are most prevalent in the least developed Member 
States, sizeable numbers of people with very low incomes are also to be found in the richer 
old Member States. 16 % of Europeans with an income below 60 % of the EU median live in 
Poland, 13 % in Germany, 11 % in Spain, 11 % in France, 12 in Italy, but only 8 % in the UK. 
Looking at those with the lowest incomes (below €5 a day), we find that 44 % of them live in 
Poland, but almost 30 % of them live in seven old Member States: Italy (8 % of all Europeans 
with  less  than  €5  a  day),  Spain  (7 %),  Portugal  (4 %),  Germany  (4 %),  UK  (3 %),  Greece 
(2 %) and France (2 %).  

As the new Member States catch up in terms of economic performance, rising incomes, both 
in  absolute  terms  and  relative  to  the  EU  average,  should  result  in a  speedy  reduction  in  the 
number of people with very low incomes. Such progress may, however, not be automatic if 
large  population  groups  (e.g.  pensioners  or  low-skilled  workers)  cannot  benefit  from  better 
earnings  opportunities  and  transfer  incomes  do  not  rise  in  line  with  earnings.  A  major 
preoccupation  of  the  Open  Method  of  Coordination  is  therefore  whether  economic  growth 
translates into reduced social exclusion as measured against the national median income. 

1.4.  Who are the poor: groups most at risk in the Member States 

 In  a  majority  of  Member  States  the  largest  segment  of  the  population  at  risk  of  poverty 
consists of couples with one or two children where one of the partners is not working (at 
least  throughout  the  year)  —  the  ‘male  breadwinner’  family  type.  Single  parents,  while 
being exposed to a high risk of poverty, represent a large share of the population at risk of 
poverty  only  in  countries  where  this  type  of  household  is  widespread.  Policies  to  fight 
poverty and to promote social inclusion need to take into account which groups represent 
the largest share of the population at risk and which groups are most exposed to the risk of 
poverty so that the right mix of horizontal and targeted policies can be developed.  

The  Social  Situation  Report  (section  2.4)  looks  at  the  risk  of  poverty  affecting  different 
sections  of  the  population  and  tries  to  identify  the  largest  subgroups  that  make  up  the  total 
population  at  risk  of  poverty  in  each  Member  State.  For  policy  makers,  it  will  be  useful  to 
look both at group-specific at-risk-of-poverty rates and at the total number of people at risk of 
poverty  in  various  groups.  The  first  gives  an  idea  of  weaknesses  in  poverty  prevention 
policies; the second may be useful to determine where action needs to be taken to achieve the 
biggest reductions in at-risk-of-poverty rates. 

The indicator which is used to measure the risk of poverty is the proportion of the population 
with equivalised disposable income below 60 % of the national median. This measure varies 
from 9 % in Sweden and 10 % in the Czech Republic to 21 % in Lithuania and Poland. The 
risk  of  poverty  within  Member  States  varies  markedly  between  different  sections  of  the 
population. At the same time, those with the highest risk also vary across countries.  

Nevertheless, four groups stand out as having a high risk in nearly all countries. These are:  

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–  people  of  working  age,  both  employed  and  unemployed,  living  alone  with  a 

dependent child, who are, in the vast majority of cases, women; 

–  those  living alone aged 65 and over who are no longer in paid employment and 
who again, in most cases, are women, many of whom may not have been working 
before reaching 65; 

–  those living alone of working age who are not in employment; 

–  families with children where only one of the parents is in employment. 

These groups vary across countries not only in terms of the risk of poverty they face, but also 
in terms of their numbers and the share of total population they represent. In particular, lone 
parents  are  much  more  numerous  in  some  countries  than  others.  In  countries  where  these 
groups  represent  a  relatively  small  proportion  of  the  population,  they  may  also  account  for 
only a small proportion of the total population at risk of poverty, despite their having a high 
risk  of  poverty  as  such.  Similarly,  a  section  of  the  population  with  a  much  lower  risk  of 
poverty may, nevertheless, make up a relatively large share of the total at risk simply because 
there are a substantial number of them.  

In 14 of the 24 Member States for which data were analysed, couples with one or two children 
where  one  of  the  partners  is  not  working  (at  least  throughout  the  year)  made  up  the  largest 
segment of the population at risk of poverty. All of the new Member States apart from Estonia 
and Cyprus are included in this group of 14. In another three countries they were the second 
largest  group.  In  another  two  countries,  Belgium  and  Ireland,  couples  with  three  or  more 
children where one of the partners is not in work represent the largest group. 

In other countries, people living alone represent the largest group among the population with 
income below the at-risk-of-poverty threshold. This is the case in Denmark, Finland, Sweden 
and Estonia, where those of working age living alone feature among the main subgroups of 
the  population  at  risk  of  poverty,  especially  if  they  are  not  employed  throughout  the  year. 
Lone parents also figure prominently among the main groups with income below the at-risk-
of-poverty threshold in these four countries, as they do in Germany and the UK.  

In addition, in Denmark, Estonia, Finland, Sweden, the UK and Cyprus, people of 65 and over 
feature among the main groups at risk of poverty, either as couples or as single women. This 
is also the case in Greece, Italy, Portugal and Slovenia. 

This  diversity  across  the  EU  emphasises  the  differences  between  Member  States  in  how 
policy would need to be focused in order to achieve a large reduction in the number of people 
at risk of poverty. 

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1.5. 

Low incomes and living standards in the EU 

Low incomes result in reduced consumption possibilities and increased financial hardship, 
but not all households with incomes below the at-risk-of-poverty threshold have to forego 
essential goods and services or find it difficult to make ends meet. The high proportion of 
those reporting that they could not afford a decent meal every other day in the new Member 
States (above 15 % of the population in six Member States, which is more than three times 
higher  than  in  EU-15)  illustrates  the  major  disparities  which  remain  across  the  EU  and 
underlines  the  need  to  complement  poverty  measures  based  on  relative  income  with 
material deprivation indicators. However, in some EU-15 countries as well, the proportion 
of people with inadequate nutrition is also worrying, especially in the context of rising food 
prices. Particular attention must be paid to the longer term consequences of low incomes, 
notably  with  regard  to  life  chances  of  children  from  deprived  families  and  the  increased 
risks of poor health and mortality affecting people with a lower socio-economic status. 

Income is a means to an end: it is needed to obtain the goods and services needed to survive 
and, beyond that, to lead a life that allows people to feel part of their community. The Social 
Situation Report (section 2.5) examines how income is related to access to those necessities of 
life.  EU-SILC  covers  such  areas  as  housing,  financial  difficulties  (e.g.  with  the  payment  of 
mortgages or rent or utility bills) and the ability to afford a range of goods and services. 

Clearly, people below the at-risk-of-poverty threshold are significantly worse off than people 
above.  Almost  by  definition,  in  all  countries  people  below  the  threshold  are  more  likely  to 
find it difficult to make ends meet, but there are big differences across Member States. While 
in most of the EU-15 countries most of these people in low-income households do not report 
major  difficulties  with  regard,  for  instance,  to  rent  and  mortgage  payments  and  utility  bills 
(possibly  thanks  to  the  availability  of  subsidised  housing  and  energy  in  the  poorer  new 
Member  States,  many  people  even  above  the  at-risk-of-poverty  threshold  report  that  they 
cannot afford things which are taken for granted in the more prosperous Member States.  

The  EU-SILC  data  allow  much  more  thorough  analysis  than  is  presented  in  the  Social 
Situation Report. The fact that a low-income household reports no problem with poor housing 
or that it can afford a particular consumer good does not mean that it is not facing hardship in 
other  areas.  A  more  telling  picture  of  material  deprivation  will  have  to  be  derived  from  an 
analysis of how many people face any one or more types of hardship measured by EU-SILC.  

The time dimension of poverty risks also needs to be taken into consideration. Low-income 
situations may be transitory (e.g. for students, young people starting their professional life, or 
self-employed  people  facing  temporary  difficulties).  EU-SILC  includes  a  panel  dimension 
which,  after  several  survey  waves,  will  allow  an  assessment  of  how  persistent  low-income 
situations are and how likely people are to leave such situations. There is also a longer time 
dimension, spanning generations: children  growing up in households at risk of poverty may 
be more likely to live in such households themselves than are children of better-off families. 
This issue is examined in the report on the basis of a special EU-SILC module (see below). 

Moreover,  income  and  socio-economic  status  are  strongly  linked  to  health  and  life 
expectancy.  There  is  evidence  that  people  with  a  lower  socio-economic  status  and  lower 
incomes  tend  to  die  younger  and  suffer  more  health  problems  than  people  in  higher  socio-
economic  groups.  This  is  linked  to  increased  exposure  to  physical,  psycho-social  and 
behavioural risk factors during all phases of the life cycle. Currently, there are no comparable 

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indicators  available  at  EU  level  to  monitor  such  health  inequalities,  but  they  do  represent  a 
major  challenge  with  regard  to  public  health  and  social  exclusion.  The  development  of 
indicators, notably life expectancy by socio-economic status, should therefore be a priority.  

1.6. 

Intergenerational transmission of disadvantages 

Survey  data  show  that  the  education  and  occupational  background  of  one’s  parents  are 
major determinants of one’s own success, despite improved access to higher education for 
younger people. Such intergenerational transmission of disadvantages suggests that many 
young  people  are  not  able  to  develop  their  full  potential  and  that  Europe’s  economy  is 
being  deprived  of  the  kind  of  highly  skilled  employees  who  will  be  more  and  more  in 
demand  in  the  knowledge  society  and  in  the  context  of  demographic  ageing.  There  are 
important  differences  across  Member  States,  suggesting  that  there  is  major  potential  for 
improvement in education systems and in skills acquisition. 

The Social Situation Report presents a first analysis of results from a special module of the 
EU-SILC  survey  focusing  on  the  intergenerational  transmission  of  disadvantages  (section 
3.1). This module asked questions about the social status of the parents of respondents when 
the  latter  were  aged  12  to  16  years.  The  report  looks  at  correlations  between  educational 
achievements of parents and children as well as the main occupational groups. 

In  the  knowledge  society,  a  high  level  of  economic  performance  and  good  living  standards 
can only be achieved if an increasing share of the population attains a high level of education. 
Social origin should not be an obstacle in this regard. However, the data collected through the 
special  EU-SILC  module  show  that  people  whose  fathers  had  attained  tertiary  level  of 
education are far more likely to do so themselves than people whose fathers had only a low or 
medium level of education: a little more than twice as likely in Germany, Finland and the UK, 
more than nine times as likely in Hungary, Poland and the Czech Republic. High educational 
attainment among female respondents tends to be more influenced by the education level of 
fathers than is the case for male respondents.  

Clearly,  coming  from  a  low-education  background  is  a  major  obstacle  to  achieving  a  high 
level  of  education,  especially  for  girls.  In  a  majority  of  Member  States,  this  disadvantage 
seems  to  have  diminished;  indeed,  for  respondents  aged  25-34  the  education  level  of  their 
fathers remains a strong determinant of their chances of attaining a high education level, but 
less so than for the cohorts aged 35-44 and 45-54. This improvement is less marked in some 
countries  where  a  high  education  level  of  fathers  appears  to  be  a  particularly  strong 
determinant of their children’s educational attainment. 

The  results  from  the  EU-SILC  module  also  suggest  that  access  to  the  highest  occupational 
level (manager, professional or technician) is much easier for the children of fathers in these 
same  professions  than  for  the  children  of  lower  occupational  categories.  The  category  of 
managers, professionals and technicians represents between one quarter (Portugal, Spain) and 
just  over  half  of  the  workforce  (Netherlands,  Germany)  and  can  be  regarded  as  crucial  for 
economic  performance  in  the  knowledge  society.  Yet,  the  data  suggest  that  family 
background can be an important barrier of access to this key occupational category: children 
whose fathers are from a lower level occupation are only half as likely on average across the 
EU  to  accede  to  this  key  occupational  category  as  children  of  managers,  professionals  and 
technicians, and only a third as likely in Portugal. 

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The  EU-SILC  module  on  intergenerational  transmission  of  disadvantages  provides  strong 
evidence  that  inequality  of  opportunities  is  a  serious  problem.  It  prevents  people  from 
disadvantaged  families  from  developing  their  full  potential  and  achieving  a  better  living 
standard for themselves and their own children, and it deprives European labour markets of 
the highly skilled employees that will be more and more in demand in the knowledge society 
and in the context of demographic ageing. 

1.7. 

Children from a migration background and equal opportunities 

Children  from  a  migration  background  are  at  higher  risk  of  poverty  than  children  of 
parents  born  in  the  country.  This  can  be  linked  to  lower  labour  force  participation  of 
foreign-born  parents  and  lower  wages  that  go  with  less  skilled  jobs.  Schools  fail  to  help 
children  with  migrant  background  to  overcome  disadvantages:  the  OECD’s  PISA  study 
shows significantly lower scores in mathematics performance for children of foreign-born 
parents, even though they are highly motivated. Fighting child poverty has become a high 
priority; success will depend on paying special attention to the situation of children with a 
migration or ethnic minority background. 

Children  from  a  migration  background  and  ethnic  minorities  suffer  from  multiple 
disadvantages: a larger proportion of them grow up in less educated, low income households. 
Language and cultural differences constitute additional barriers to accessing the full range of 
opportunities  in  their  host  countries.  Overcoming  these  obstacles  is  becoming  a  major 
challenge  as  the  diversity  of  populations  in  the  Member  States  increases,  due  to  large 
immigration  flows  into  several  Member  States.  According  to  the  2000/2001  Census  round, 
seven  percent  of  the  EU  population  were  born  outside  their  current  country  of  residence,  a 
figure that is likely to have increased significantly since then. The composition of the foreign-
born  population  differs  widely  from  one  Member  State  to  another,  and  in  many  Member 
States half or more of foreign-born residents come from just three or four countries. 

The Social Situation Report takes a close look at children at risk of poverty (section 3.2) in 
migrant households, defined as households where both parents were born outside the EU. An 
estimated  5.5 %  of  children  aged  under  16  in  the  European  Union,  or  over  4  million 
altogether,  live  in  such  households.  40 %  of  children  from  a  non-EU  migration  background 
live  in  a  household  at  risk  of  poverty  (equivalised  income  below  60 %  of  the  median), 
compared to 18 % of children of parents born in the country of residence. The proportion of 
children  in  households  with  income  below  the  at-risk-of-poverty  threshold  exceeds  50 %  in 
Belgium,  Spain,  Luxembourg  and  the  Netherlands.  This  increased  poverty  risk  is  linked  to 
employment: parents in migration households are less likely to be fully employed than parents 
born in the country of residence. Moreover, it is likely that a higher proportion of parents born 
outside the EU will be doing less qualified and less well-paid jobs. 

The disadvantages of migrant children at home are also reflected in student performance. The 
OECD’s  PISA  study  compared  mathematics  performance  of  native  students  (those  with  at 
least  one  parent  born  in  the  country)  and  first  and  second  generation  immigrant  students 
(students  born  outside  the  country,  and  students  born  in  the  country  with  foreign-born 
parents)10. Although students from an immigrant background show high levels of motivation, 
their scores in most of the OECD countries participating in the survey are significantly lower 
than those of native students.  

10 

See Education at a Glance 2007, OECD. 

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1.8. 

Equal opportunities: the key to economic growth and social cohesion 

The analysis presented in the 2007 Social Situation Report, albeit very preliminary, suggests 
that promoting equal opportunities in the European Union could make a major contribution to 
both greater social cohesion and economic performance. As long as a significant proportion of 
the population cannot develop their full potential, there is no trade-off between equality and 
efficiency. This report illustrates this by showing that educational outcomes are still strongly 
determined by the level of education of parents and by showing that particularly children from 
a  migration  background  are  growing  up  in  difficult  social  circumstances.  The  Report  only 
presents  a  very  cursory  analysis  based  on  the  new  set  of  EU-SILC  survey  data  that  has 
become  available,  but  it  demonstrates  that  the  European  Union  and  its  Member  States  now 
have powerful analytical tools at their disposal for identifying and monitoring major obstacles 
to achieving more equality of opportunity and hence better prospects for social cohesion and 
growth. 

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2. 

INCOME DISTRIBUTION AND POVERTY RISKS IN THE EU 

This chapter presents  some  key findings from the EU’s new tool for monitoring the social 
situation  and,  in  the  future,  social  trends,  namely  the  EU-SILC  (Statistics  on  Income  and 
Living  Conditions).  It  looks  at  income  inequality  and  how  this  is  related  to  economic 
performance and at the distribution of people on low incomes across the EU as a whole. It 
also tries to identify the largest groups at risk of poverty in the different Member States and 
the extent to which low incomes are linked to access to various essential goods and services. 
The  results  presented  here  only  scratch  the  surface  of  the  wealth  of  data  produced  by  EU-
SILC, and the research community will be able to make extensive use of this data source. 

2.1. 

EU-SILC: The new tool for monitoring the social situation in the EU 

Internationally comparable data for monitoring the economic situation and trends have been 
collected  for  about  half  a  century.  By  contrast,  equivalent  tools  for  monitoring  social 
conditions are still in their infancy. Over the past decade, the European Union has achieved 
major progress in terms of producing internationally comparable data for social monitoring. 
The European Community Household Panel survey (ECHP) was first carried out in 1994 and 
produced annual data on social conditions for a decade. The ECHP has now been replaced 
by  a  new  instrument,  EU-SILC  (Statistics  on  Income  and  Living  Conditions),  from  which 
this year data for almost all Member States have become available.  

With  EU-SILC,  the  European  Union  has  a  much  improved  tool  for  monitoring  the  social 
situation  and  trends.  It  uses  larger  samples,  allowing  more  detailed  analysis  of  the  most 
vulnerable households. The time lag between the collection of data and their publication — 
three  years  or  more  in  the  case  of  the  ECHP  —  has  been  reduced  by  about  one  year; 
nevertheless  the  most  recent  data  used  for  this  report  were  collected  in  2005  and  refer  to 
incomes in 2004. So the availability of social data will continue to lag considerably behind 
that of key economic indicators. 

Without  internationally  comparable  data  on  the  social  situation  as  produced  by  the  ECHP 
and  EU-SILC,  key  policy  developments  in  the  European  Union  would  not  have  been 
possible. A major breakthrough in this regard has been the Open Method of Coordination, in 
which Member States agreed on common objectives and indicators for monitoring progress 
towards these objectives in the field of social protection and social inclusion. Most of these 
indicators rely on the existence of internationally harmonised surveys on incomes and living 
conditions such as the ECHP and EU-SILC11. 

EU-SILC  was  introduced  in  2003  to  replace  the  European  Community  Household  Panel 
(ECHP)  and  now  covers  all  EU  Member  States12,  with  the  exception  of  Bulgaria  and 
Romania (where it was implemented in 2006). As its name implies, it is the primary source 
of  data  across  the  EU  on  household  income  and  living  conditions.  It  was  designed  to 
overcome the limitations of the ECHP (See Box 2 for details) and to cover the new Member 
States. It was also intended to conform to internationally agreed definitions of income. At the 

11 

12 

See  http://ec.europa.eu/employment_social/social_inclusion/indicators_en.htm  for  the  latest  list  of 
indicators. 
In practice Malta is not covered either because of missing values. 

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same  time,  the  general  approach  of  surveying  a  representative  sample  of  households  each 
year and asking all members of the household aged 16 and over relatively detailed questions 
remained the same. However, because of some simplification in the questionnaire and in the 
procedures, the delay in the results of the survey becoming available has been reduced to less 
than two years. 

To  ensure  compatibility  between  countries,  the  survey  is  based  on  a  common  framework 
with  a  common  set  of  sampling  variables,  guidelines  and  procedures  —  as  regards 
imputation  in  particular  —  as  well  as  common  concepts  and  definitions.  In  six  Member 
States  (the  three  Nordic  countries  plus  Ireland,  the  Netherlands  and  Slovenia),  data  from 
administrative registers are used to supplement, or to replace, survey data for items, income 
especially, for which they are considered to be more reliable. 

The EU-SILC provides both cross-sectional and longitudinal data from the same sample; a 
proportion  of  those  surveyed  remains  the  same  for  two,  three  or  four  consecutives  waves. 
More specifically, a quarter of the households surveyed in 2004 are, therefore, followed up 
for four years (up to 2007), a quarter for three years and a quarter for two years, while the 
remaining  quarter  is  surveyed  only  once.  Those  who  drop  out  are  replaced  by  others  on  a 
rotational basis. The fact that three-quarters of the sample are the same from one year to the 
next  should  ensure  a  relatively  high  degree  of  consistency  over  time  in  the  data  collected, 
while respondents dropping out will tend to be less of a problem. 

The countries covered and data collected 

The  EU-SILC  was  launched  on  a  trial  basis  in  2003  in  six  Member  States  (Belgium, 
Denmark,  Ireland,  Greece  Luxembourg,  and  Austria)  as  well  as  Norway.  In  2004,  it  was 
extended to seven more Member States (Estonia, Spain, France, Italy, Portugal, Finland and 
Sweden) and, in 2005, to the rest of the EU-25 countries as well as Iceland. In 2006, surveys 
were conducted in Bulgaria and Romania as well as Turkey. 

The  data  included  in  the  EU-SILC  are  much  the  same  as  in  the  ECHP,  though  with  some 
streamlining. In particular, there is less of an overlap with the EU Labour Force Survey than 
was  the  case  with  the  ECHP.  While  much  of  the  focus  is  on  household  income,  other 
household,  personal  and  non-monetary  information  is  collected  as  well,  reflecting  the 
multidimensional nature of social exclusion. The areas covered include: 

•  housing conditions, the state of accommodation as well as the size and composition of the 

household, tenure status and the cost of rent or mortgage payments; 

•  material deprivation, in terms of ability to afford certain goods and services and to avoid 

financial strain; 

•  employment  characteristics,  in  particular  whether  or  not  in  work,  the  nature  of  the  job 
held, hours of work and employment status each month over the past year, as well as the 
work intensity of the household (i.e. how many people are in work relative to the potential 
number); 

•  health status, the presence of any long-term diseases, and access to health care; 

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•  education,  in  terms  of  the  highest  level  of  education  attained  and  summary  details  of 
current participation in education (but no details of participation in continuing training, or 
lifelong learning) 

•  the  use  of  childcare,  in  terms  of  the  hours  of  care  in  particular  facilities  or  in  informal 
arrangements  (this  is  the  first  time  such  questions  have  been  included  in  a  regular 
household survey). 

The  definition  of  income  used  in  the  survey  follows  recommended  international  standards 
(specifically  those  recommended  by  the  Canberra  Group  of  experts13),  which  makes  it 
somewhat  different  from  that  adopted  in  the  ECHP,  but  not  radically  so.  The  main 
differences are that it includes in income the imputed rent of owner-occupied housing, goods 
produced for own consumption, employer’s social insurance contributions and non-monetary 
benefits  received  by  employees  (see  Box  1).  In  addition,  mortgage  interest  payments  are 
deducted  from  gross  income  (as  a  corollary  of  including  imputed  rent).  The  inclusion  of 
these items, apart from non-monetary benefits received by employees, is being deferred until 
2007, though. 

Box 1: Definition of household income in the EU-SILC 

The gross income of households is defined as the sum of:  

cash or near-cash income of employees 

- 
-  non-cash income of employees (such as a company car or luncheon vouchers) 
- 
- 
-  value of goods produced for own consumption (from 2007)  
- 

employer’s social insurance contributions (from 2007) 
income or losses from self-employment 

social  benefits  of  various  kinds,  including  family  or  child  allowances  and  housing 
benefits 
imputed rent (from 2007) 
income from rents 
cash transfers received from other households 
interest and dividends received, plus profits from unincorporated businesses 

- 
- 
- 
- 

less  

- 

interest paid on mortgages (from 2007) 

Household disposable income is defined as gross income minus: 

- 
- 
- 
- 

employer’s social insurance contributions 
regular taxes on wealth 
regular cash transfers paid to other households 
taxes on income and social insurance contributions 

13 

The “Canberra Group” was organised following an initiative of the Australian Bureau of Statistics and 
owes  its  name  to  the  first  meeting  held  in  Canberra  in  1996.  This  International  Expert  Group  on 
Household  Income  Statistics  works  on  developing  statistics  on  household  economic  well-being  and 
particularly  on  household  income.  Its  primary  objective  was  to  enhance  national  household  income 
statistics  by  developing  standards  on  conceptual  and  practical  issues  related  to  the  production  of 
income distribution statistics. http://www.lisproject.org/links/canberra/canberragroup.htm 

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The sample size 

A major advantage of the EU-SILC over the ECHP is the large sample of households — and 
individuals covered — which should enable more detailed analysis to be carried out. In most 
countries the sample is 2-3 times larger than for the ECHP. On the other hand, there are still 
major differences between countries in the number of households and individuals surveyed 
relative  to  total  population  (See  Table  1).  This  does  not  just  reflect  the  fact  that  the 
population  surveyed  in  smaller  countries  needs  to  represent  a  larger  share  of  the  total 
population  to  guarantee  sufficient  sample  sizes.  The  sample  in  the  Czech  Republic,  for 
instance, is only just over half that in Hungary, which has a similar population; the sample 
for  the  UK  is  only  a  third  the  size  of  that  in  Italy.  The  reliability  of  some  results  may 
therefore differ somewhat across countries. 

Table 1: EU-SILC sample size 

Households 
surveyed (No.) 

5.137 
4.351 
5.957 
13.106 
4.169 
6.085 
5.568 
12.996 
9.754 
22.032 
3.746 
3.843 
4.441 
3.622 
6.927 
3.459 
9.356 
5.148 
16.263 
4.620 
8.287 
5.147 
11.229 
6.133 
9.820 

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

Individuals 
surveyed (No.) 
9.974 
8.628 
11.901 
24.982 
9.643 
12.032 
12.381 
30.375 
18.769 
47.311 
8.997 
7.913 
9.929 
7.535 
14.791 
8.246 
17.852 
10.419 
37.671 
10.715 
23.862 
12.879 
22.961 
12.191 
16.675 

Population 
in 2005 (000) 
10478,6 
10235,8 
5419,4 
82469,4 
1346,1 
4159,1 
11104,0 
43398,1 
60873,5 
58607,0 
757,8 
2300,5 
3414,3 
457,3 
10087,1 
403,5 
16319,9 
8236,2 
38165,4 
10549,4 
2000,5 
5387,0 
5246,1 
9029,6 
60226,5 

Individuals as % 
of population 
0,10 
0,08 
0,22 
0,03 
0,72 
0,29 
0,11 
0,07 
0,03 
0,08 
1,19 
0,34 
0,29 
1,65 
0,15 
2,04 
0,11 
0,13 
0,10 
0,10 
1,19 
0,24 
0,44 
0,14 
0,03 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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BOX 2: The European Community Household Panel  

The European Community Household Panel (ECHP) was a harmonised longitudinal survey 
introduced  in  the  early  1990s  by  Eurostat  in  response  to  the  strong  demand  for 
internationally comparable information on household and individual income in the EU. The 
ECHP enabled comparable social statistics and indicators to be developed in Member States 
on  living  conditions,  social  transfers,  poverty  and  social  exclusion,  housing,  health  and  so 
on.  

The  questionnaire  was  designed  by  Eurostat  in  close  consultation  with  the  Member  States 
and  was  common  to  all  countries,  though  the  precise  questions  were  adapted  to  a  certain 
extent  to  national  circumstances.  By  surveying  the  same  panel  of  households  (and 
individuals) each year, the ECHP produced longitudinal data covering the eight years from 
1994 to 2001 for most of the EU-15 countries (Austria from 1995, Finland from 1996 and 
Sweden from 1997).  

The ECHP suffered from a number of limitations, the main ones being: 

•  the  sample  size  was  relatively  small,  partly  because  of  its  panel  nature  and  the  detailed 
questions asked, thus limiting the degree of detail of the analysis which could reliably be 
carried out; 

•  the lengthy lag between the data being collected and becoming available, of around three 

years or more, reduced its usefulness for monitoring developments; 

•  the panel element, which was one of its main strengths, was compromised by the high rate 
of attrition among the households surveyed in many countries. Although those dropping 
out  were  replaced  by  other  households,  the  longitudinal  element  of  the  data  was 
significantly diminished, again reducing the possibilities of carrying out detailed analysis. 

2.2. 

Income inequality and economic performance 

There is an ongoing debate among economists about the nature of the relationship between 
inequality  in  income  distribution  and  economic  performance.  While  some  point  to  the 
likelihood  of  a  trade-off  between  economic  growth  and  the  pursuit  of  a  more  egalitarian 
society, largely because of the adverse effect on incentives of the taxes, benefits and other 
measures  required  to  achieve  a  more  equitable  distribution  of  income,  others  highlight  the 
potential gains for economic performance that a more cohesive society might bring.  

The idea of a trade-off stems from the fact that taxing the rich to redistribute income to the 
poor  could,  according  to  economic  theory,  reduce  aggregate  economic  performance  due  to 
deadweight  losses  associated  with  the  taxation  and  incentive  effects  of  income-related 
transfer payments. Economist Arthur Okun used the metaphor of a leaky bucket.  

However,  a  relatively  equal  distribution  of  incomes  need  not  be  the  result  of  large-scale 
redistribution  alone.  It  may  result  from  a  more  narrow  distribution  of  market  incomes  as 
people  have  more  equal  opportunities  to  develop  their  full  productive  potential  and 
contribute  to  the  generation  of  income.  This  requires  good  chances  for  all  to  access  high-
quality  education,  health  care  and  jobs.  Greater  equality  resulting  from  more  equal 

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opportunities  does  not  necessarily  entail  the  efficiency  losses  potentially  associated  with 
redistribution if the corresponding policy is well-targeted and the associated financial burden 
is  limited.  On  the  contrary,  promoting  equal  opportunities  can  make  it  possible  to  boost 
growth by mobilising resources that could not be deployed previously due to discrimination 
and social exclusion. 

The nature of the relationship between inequality and economic performance in practice is of 
importance for policy across the EU, given that achieving a high level of social protection 
and securing greater social cohesion are major objectives of the European Union, along with 
attaining  sustained  economic  growth  by  maintaining  and  strengthening  competitiveness.  If 
indeed there is trade-off between equity and efficiency, then the implication is that choices 
have to be made regarding the weight attached to each. If, on the other hand, a more equal 
distribution of income is not only compatible with improvements in economic performance 
but might even help to achieve them, then the pursuit of social objectives can play a dual role 
in both reducing inequalities and strengthening competitiveness.  

The concern in this section is threefold. It is, first, to examine the distribution of income in 
EU  Member  States  using  data  from  the  new  EU-SILC  (which  for  the  first  time  enable  a 
comparison to be made across all 25 countries on a consistent basis), and at the same time, to 
compare  this  with  the  distribution  in  the  US.  Secondly,  it  is  to  relate  the  distribution  of 
income  in  Member  States  to  GDP  per  head,  which  is  commonly  used  as  a  measure  of 
economic performance. Thirdly, it is to examine trends in income distribution over the long 
term, to see whether the distribution has tended to become more or less equal over time. 

Income inequality in EU Member States in 2004 

Data  from  the  EU-SILC  allow  the  distribution  of  income  in  all,  or  almost  all,  of  the  EU 
Member States to be assessed on a comparable basis for the first time14. The data, collected 
in 2005, relate to the income of households in 2004 and cover all the present EU Member 
States apart from Bulgaria and Romania.  

14 

For the 1990s, the European Community Household Panel provided a reasonably comparable basis for 
assessing  differences  in  income  distribution  across  the  EU,  but  this  was  confined  to  the  EU-15 
countries. 

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BOX 3 Technical issues 

The measurement of equivalised income 

Income is defined to exclude taxes and social contributions and to include social transfers, so 
as to measure disposable purchasing power, and is adjusted for differences in household size 
and composition. More specifically, to take account of economies in collective expenditure, 
a  weight  of  one  is  assigned  to  the  first  adult  in  a  household,  0.5  to  the  second  and  each 
subsequent adult and 0.3 to each child under 16, which corresponds to what is known as the 
modified OECD equivalence scale. The income thus adjusted or equivalised is then assumed 
to  be  divided  equally  between  household  members  in  order  to  measure  the  distribution  of 
income between individuals in each country rather than between households.  

Non-positive  income  values  —  which  result  from  the  way  that  the  income  of  the  self-
employed is defined, i.e. essentially in terms of net trading profits — are excluded from the 
analysis.  To  adjust  for  the  problem  of  ‘outliers’,  or  extreme  levels  of  income  reported  at 
either  end  of  the  distribution,  which  involve  a  high  degree  of  uncertainty  but  which  can 
unduly affect the results of the analysis, income values at the bottom of the ranking of less 
than the 0.1 percentile were replaced by the value of the 0.1 percentile, while at the top of 
the ranking, values greater than the 99.95 percentile were replaced by the value of the latter.  

Standard errors of estimates 

To  compare  income  distribution  across  countries  on  a  meaningful  basis,  it  is  important  to 
take  account  of  the  margin  of  error  arising  from  data  being  compared  on  a  sample  of 
households rather than the whole population. This is done by calculating the standard error 
of the estimates and estimating confidence intervals around this in order to identify the range 
within  which  the  value  of  the  inequality  indicator  is  likely  to  lie15.  In  other  words,  any 
comparison of income inequality between countries needs to be carried out in terms of these 
ranges  instead  of  ‘point’  estimates.  If  the  ranges  for  two  countries  overlap,  then  it  is  not 
possible  to  conclude  with  sufficient  confidence  that  one  country  has  a  more  unequal 
distribution of income than the other. 

Three commonly employed indicators are used below to measure inequality. The first is the 
Gini coefficient or index (as used in Figure 1 below), which measures the extent to which the 
distribution  of  income  diverges  from  a  situation  where  everyone  has  the  same  level  of 
income — the higher the value of the index, the more unequally is income distributed16.  

The second is the S80/S20 index, which is the ratio of the share in total income of the 20 % 
of people with the highest incomes (the top quintile) to the share of the 20 % with the lowest 
incomes  (the  bottom  quintile).  Whereas  the  Gini  index  summarises  the  distribution  of 
income  across  the  whole  range,  the  S80/S20  index  focuses  on  the  top  and  bottom  of  the 
ranges. A third indicator, the P90/P10 index, the ratio of the 90th percentile of the income 
distribution to the 10th, is similar in that it measures the median income of the top 20 % (i.e. 

15 
16 

The ‘bootstrap’ simulation method is used here to estimate the standard error. 
Formally,  the  Gini  index  is  measured  as  (1/2n((n  —  1))Σi=1,…,nΣj=1,…,n|yi – yj|,  where  yi  are  individual 
incomes, n is sample size. The index varies between a value of zero, when everyone has the same level 
of income, and 1 when a single individual has all the income. 

EN 

20 

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the income of the person ranked at the midpoint of this group, with 10 % of the population 
having income higher than this and 90 % lower). The S80/S20 index will tend to be higher 
than the P90/P10 index, the larger the share of income going to the top 10 %, i.e. the richest 
people in the country, and the smaller the share going to the bottom 10 %. 

According  to  the  Gini  index,  Portugal  has  the  highest  degree  of  inequality  of  income 
distribution, with a value of 41 % (Figure 1, which also shows the 95 % confidence intervals 
around the estimate, implying that there is a 95 % probability that the true value of the index 
lies within this range — see Box 3). The new Member States of Lithuania, Latvia and Poland 
form  a  second  group  of  countries  with  Gini  coefficients  of  around  35-36 %,  while  a  third 
group,  with  indices  of  between  30 %  and  35 %,  is  composed  of  the  other  three  Southern 
European  countries  of  Spain,  Greece  and  Italy,  the  UK  and  Ireland,  and  Estonia.  These 
countries  have  Gini  indices  above  30 %  but  below  35 %.  The  four  Southern  European 
countries,  the  three  Baltic  States,  Poland,  Ireland  and  the  UK,  therefore,  have  the  highest 
levels of inequality in the EU. 

Figure 1 Gini indices and confidence intervals, 2004 

44%
43%
42%
41%
40%
39%
38%
37%
36%
35%
34%
33%
32%
31%
30%
29%
28%
27%
26%
25%
24%
23%
22%
21%
20%

SE DK SI

IS FI NL NO SK CZ LU AT BE DE HU FR CY ES IE IT GR UK EE PL LV LT PT

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

At  the  other  extreme,  countries  with  the  lowest  degree  of  inequality  by  this  measure  are 
Sweden, Denmark and Slovenia, with Gini indices of below 25 %.  

Between  the  low  and  high  inequality  countries  there  are  a  large  number  of  countries  with 
Gini indices of above 25 % but below 30 %. Differences in the indices between countries in 
this  group  are  in  many  cases  very  small,  so  that  the  confidence  intervals  of  the  estimates 
overlap. Finland, the other Nordic Member State, is at the lower end of the group together 
with the Netherlands, while Hungary, France and Cyprus are at the upper end. 

The  ranking  of  countries  in  terms  of  the  S80/S20  index  is  very  similar  to  that  described 
above in relation to the Gini index. There are only a few changes to the ranking of individual 
countries,  mostly  of  only  one  or  two  places.  In  particular,  Slovakia  is  ranked  two  places 

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21 

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higher according to the S80/S20 index than according to the Gini coefficient, which implies 
that there is a wider dispersion between the top and bottom of the income range than within 
these  two  parts  of  the  distribution  or  in  the  middle  of  the  range.  By  contrast,  the  UK  is 
ranked two places  lower and  Ireland and Latvia one place lower, suggesting the reverse is 
the case in these countries. This narrower dispersion between incomes at the top and bottom 
of the distribution is confirmed by the P90/P10 index. 

Table 2 Values of different inequality indices in 2004 

SE 
DK 
SI 
FI 
NL 
CZ 
SK 
AT 
LU 
BE 
DE 
HU 
FR 
CY 
ES 
IE 
IT 
EL 
UK 
EE 
PL 
LV 
LT 
PT 
EU 
US 

Gini 

22,5 
22,7 
23,7 
24,9 
25,1 
25,8 
25,8 
26,0 
26,0 
26,6 
26,7 
27,3 
27,6 
28,4 
31,4 
31,8 
32,4 
32,6 
33,1 
33,4 
35,2 
35,5 
35,9 
41,2 
32,7 
35,7 

S80/S20 
3,2 
3,2 
3,4 
3,5 
3,6 
3,6 
3,8 
3,7 
3,8 
3,9 
3,9 
4,0 
4,0 
4,3 
5,2 
4,9 
5,4 
5,5 
5,3 
5,5 
6,4 
6,2 
6,6 
8,0 
6,7 
na 

P90/P10 
2,6 
2,7 
3,0 
2,9 
2,9 
3,0 
3,1 
3,1 
3,2 
3,2 
3,2 
3,3 
3,2 
3,6 
4,4 
3,9 
4,1 
4,4 
4,2 
4,5 
5,1 
4,7 
5,3 
6,0 
5,2 
5,4 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Estimates for the EU are based on the sum of disposable income in each country measured in purchasing power parity terms. 
Estimates for US relate to 2000 and are taken from Michael Förster and Marco Mira d’Ercole, Income distribution and poverty 
in OECD countries in the second half of the 1990s, OECD, 2005 

The main feature of the ranking based on the Gini index, however, is largely confirmed, in 
that there is a group of countries with the lowest ranking which have a significantly lower 
level  of  income  inequality  than  other  Member  States  and  a  group  at  the  top  which  have  a 
significantly higher level. At the same time, the countries included in these two groups are 
somewhat different.  

In particular, according to both the S80/S20 and P90/P10 measures, Sweden and Denmark 
have a significantly lower level of inequality than other Member States, while Slovenia has a 
level which is similar to Finland and the Netherlands. 

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At the other end of the scale, the distinct difference in income inequality between the group 
of  10  countries  with  the  highest  value  of  the  Gini  index  (i.e.  those  listed  above  where  the 
index is over 30) and those with a lower value (i.e. of below 30) is confirmed by the S80/S20 
index, though to a lesser extent by the P90/P10 index (which shows only a small difference 
between Ireland in the top group and Cyprus in the lower group). 

Within the top group of countries, Poland, Latvia, Lithuania and Portugal stand out as having 
the most unequal distributions of income according to both the Gini and the S80/S20 indices, 
though  again  the  difference  is  less  marked  according  to  the  P90/P10  index  (in  this  case 
between Latvia in the top group of four, and Estonia and Greece in the lower group of six). 
This implies that focusing on the very top and bottom of the income distribution (i.e. the top 
and  bottom  10 %  of  income  earners)  can  give  a  slightly  different  picture  of  income 
inequality than taking account of income dispersion over a wider range. 

It is also possible to compare income distribution in the EU and in the US. The Gini index 
estimated for the US amounts to 35.7 (Table 2), which is markedly higher than in any EU 
country apart from Lithuania, Portugal, Poland and Latvia, signifying that income is slightly 
more unevenly distributed in the US than in EU Member States. The value of the P90/P10 
index is higher than in all EU countries except Portugal, thus confirming the high degree of 
inequality in the US as compared with the EU17.  

Moreover,  estimates  of  the  Gini  index  for  the  EU  as  a  whole  (aggregating  household 
disposable income measured in purchasing power terms across Member States) put the value 
at  around  32.7,  below  the  value  in  the  US  despite  the  wide  disparities  in  income  levels 
between EU countries. In addition, the P90/P10 is also estimated to be less in the EU than in 
the US (5.25 as against 5.4), though in this case the difference is small, suggesting that the 
gap in incomes between the highest and lowest income earners is much the same in the EU 
as in the US. 

Differences between 2000 and 2004 

The  ranking  of  countries  according  to  the  Gini  index  in  2004  shows  only  relatively  minor 
differences from the ranking for 200018 (Figure 2).  

17 

18 

Estimates  of  the  degree  of  inequality  in  income  distribution  in  the  US  are  not  adjusted  for  extreme 
values in the same way as for EU Member States, as explained in the Box. This in itself will tend to 
reduce  the  estimates  for  these  countries  relative  to  those  for  the  US  even  if  relatively  slightly.  The 
estimates for the EU as a whole, however, are not adjusted in the same way and so ought to be more 
comparable with those for the US. 
Data for 2000 are from the Eurostat online database:   
http://epp.eurostat.ec.europa.eu/portal/page?_pageid=1996 45323734&_dad=portal&_schema=PORT
AL&screen=welcomeref&open=/livcon/ilc/ilc_ip/ilc_di&language=en&product=EU_MASTER_livin
g_conditions_welfare&root=EU_MASTER_living_conditions_welfare&scrollto=164 
Data for EU-15 countries come from the ECHP, data for other countries from national sources.Note 
that the data are referred to in the database as relating to 2001, which is the year of the survey rather 
than the year to which the income relates. 

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23 

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Figure 2 Gini indices in 2000 and 2004  

45%

40%

35%

30%

25%

20%

15%

10%

5%

0%

SE DK SI FI NL CZ LU AT BE DE HU FR ES IE IT GR UK EE PL IT PT

2000

2004

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Portugal was the most unequal country in both 2000 and 2004, but Poland and Lithuania had 
index  values  below  Spain,  Greece  and  Estonia.  The  countries  with  the  most  equal  income 
distributions were the same in 2000 as in 2004, though Sweden appears to have moved from 
being  the  fourth  least  unequal  country  to  being  the  least  unequal.  Among  countries  in 
between the least and most unequal groups, there were also some changes in ranking, with 
Austria,  Germany  and  Hungary  moving  up  the  ranking  —  i.e.  income  becoming  more 
unequally distributed — and Luxembourg and Belgium moving down. 

Taking account of the likely margins of error surrounding the estimates, however, there were 
relatively few countries in which the value of the Gini index differs enough between the two 
years  to  denote  a  significant  change.  The  countries  concerned  —  Hungary,  Ireland,  Italy, 
Poland, Lithuania and Portugal — generally showed an increase in inequality. Nevertheless, 
there  is  a  need  for  a  great  deal  of  caution  in  interpreting  these  differences  since  they  are 
based  on  two  different  surveys  (the  ECHP  or  national  surveys  for  2000,  the  EU-SILC  for 
2004). Since there is no way of assessing as yet the effect of the different data sources on the 
results,  it  would  be  rash  to  conclude  that  incomes  became  more  unequally  distributed  in 
these six countries over these four years19. 

Income inequality and GDP per head 

While  it  is  not  possible  from  the  data  available  to  say  with  any  confidence  how  the 
distribution of income in EU Member States has changed over recent years, some light can 
be  shed  on  the  relationship  between  economic  performance  and  income  distribution  by 
examining  the  relationship  between  the  latter  and  GDP  per  head  across  countries.  This, 

19 

The fact that the two estimates of the Gini index for the two years come from different surveys makes 
it  difficult  to  specify  margins  of  error  in  comparing  the  two.  Although  it  is  possible  to  calculate 
confidence intervals for the estimates for 2000 from the ECHP at least, these intervals cannot be used 
in conjunction with the intervals for 2004 to give an indication of the margin or error surrounding the 
change over the four years. 

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24 

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therefore,  indicates  the  extent  to  which  countries  with  a  relatively  high  level  of  GDP  per 
head (which, as noted above, is commonly taken as an indicator of economic strength) tend 
to have more or less unequal distribution of income than those with lower levels.  

The  relationship  between  the  two  in  2004  indicates  that  there  is  a  general  tendency  for 
countries with relatively high levels of GDP per head to have a more equal distribution of 
income  (as  measured  by  the  Gini  index)  (Figure  3).  The  relationship,  however,  is  by  no 
means systematic. In particular, there are a number of countries with very different degrees 
of income inequality which have similar levels of GDP per head, such as the UK, Belgium 
and  Denmark  or  Portugal,  Greece  and  the  Czech  Republic.  This  suggests  that  reducing 
income  inequality  —  or  achieving  a  more  even  distribution  of  income  —  need  not 
necessarily  in  itself  lead  to  a  higher  level  of  GDP  per  head,  which  is  perhaps  only  to  be 
expected given the many other factors which are likely to play a role, including the way in 
which a more even distribution comes about.  

Figure 3 Distribution of EU Member States by GDP per capita (in PPS and Gini index, 2004) 

Gini Index

PT

LV

LT
PL

EE

EL

IT
ES

UK

IE

CY

HU

SK

CZ

SI

FR

BE

DE
FI

AT
NL

DK

SE

45

40

35

30

25

20

45

40

35

30

25

20

LU

0

50

100

150

200

250

300

GDP (in PPS), EU25 average=100

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Long-term trends in the distribution of income 

The  evidence  on  whether  and  how  far  the  distribution  of  income  has  become  more  or  less 
unequal in EU Member States over time is unclear, in no small measure because of the lack 
of  a  consistent  set  of  data  with  which  to  assess  long-term  developments  in  different 
countries.  Moreover,  a  priori  considerations  point  in  conflicting  directions.  The  ICT 
revolution and the growth of the knowledge-based economy suggest that there should be a 
premium  on  high  levels  of  education  and  know-how  and,  accordingly,  a  widening  gap 
between  the  earnings  of  those  with  university  degrees  or  equivalent  high  skills  and  those 
with  lower  education  levels,  especially  manual  workers  whose  jobs  can  be  replaced  by 
automation.  On  the  other  hand,  any  tendency  of  this  kind  is  likely  to  be  dissipated  by  the 

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increased  participation  in  education  and  the  growing  number  of  people  with  high-level 
qualifications. Moreover, the growth in the number of women in employment might in itself 
be expected to lead to a more equal distribution of income across households, allied with the 
continued development of the social welfare system to support incomes at the bottom end of 
the scale. 

Against  this,  the  transition  of  the  Central  and  Eastern  European  countries  from  centrally 
planned  to  market  economies  might  be  expected  to  result  in  a  widening  of  income 
differentials,  at  least  so  far  as  the  earnings  component  of  income  is  concerned,  as  the 
influence of market forces on wages and salaries has increased.  

The  evidence  which  does  exist  from  household  surveys  for  most  European  countries  dates 
back only 20 years or so, and for a number of EU Member States data are available only for 
the recent past. For the six European countries for which data do exist for the years before 
the 1980s, they indicate a mixed picture for the period from the mid-1970s to the mid-1980s, 
with  the  distribution  of  income  (as  measured  by  the  Gini  coefficient)  becoming  more 
unequal in the UK and to a lesser extent in the Netherlands, but becoming less unequal in 
Finland, Sweden and Greece, especially the latter (Table 3). 

Table 3 Overall trends in income inequality in countries for which data available, mid-1970s to 
2000  

Strong 
decline 

Moderate 
decline 

Small 
decline 

No change  Small increase

Moderate 
increase 

Strong 
increase 

Greece 

Finland, 
Sweden 

Canada 

Netherlands  United States 

United 
Kingdom

Spain 

Australia, 
Denmark

Austria, 
Canada, 
France, 
Greece, 
Ireland 

Belgium, 
Germany, 
Luxembourg, 
Japan, Sweden

Mid-
1990s  
to 2000 

Mexico, 
Turkey 

France, 
Ireland, 
Poland 

Australia, 
Czech Rep., 
Germany, 
Hungary, Italy, 
Luxembourg, 
Netherlands, 
New Zealand, 
Portugal, 
United States

Austria, 
Canada, 
Denmark, 
Greece, Japan, 
Norway, United 
Kingdom 

Czech Rep., 
Finland, 
Hungary, 
Netherlands, 
Norway, 
Portugal, 
United 
Kingdom, 
United States 

Italy, 
Mexico, 
New 
Zealand, 
Turkey 

Finland, 
Sweden 

Mid-
1970s  
to mid-
1980s 

Mid-
1980s  
to mid 
1990s 

Source: Förster and D’Ercole, OECD, 2005 

Note: The table presents summary results for the total population, as expressed by the Gini coefficient applied to the income of 
individuals  as  derived  from  equivalised  net  household  income.  “Strong  decline/increase”  denotes  a  change  in  income 
inequality  above  +/-  12 %;  “moderate  decline/increase”  a  change  between  7  and  12 %;  “small  decline/increase”  a  change 
between  2  and  7 %;  “No  change”  changes  between  +/-  2 %.  Results  are  based  on  the  values  of  the  Gini  coefficient  in  four 

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26 

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reference years which may vary among countries. The last reference period is shorter than the previous ones: this should be 
borne in mind for comparisons. 

Between the mid-1980s and the mid-1990s, when there are many more countries for which 
data are available, the data suggest that there was a marked increase in income inequality in 
most cases. Of the 17 current EU Member States for which there are data, the distribution of 
income narrowed moderately in Spain and to a lesser extent in Denmark, while it remained 
broadly unchanged in Austria, France, Greece and Ireland. In the other eleven countries, the 
distribution  widened,  only  to  a  relatively  small  in  Belgium,  Germany,  Luxembourg  and 
Sweden but substantially in Italy.  

In  the  subsequent  five  years  up  to  2000,  there  was  less  of  a  widespread  increase  in 
inequality. Nevertheless, the distribution of income seems to have narrowed only in three of 
the 16 Member States for which data exist — France, Ireland and Poland — and then only to 
a small extent. It remained much the same in another six — the Czech Republic, Germany, 
Hungary,  Italy,  Luxembourg  and  the  Netherlands  —  and  widened  in  the  other  seven,  to  a 
small extent in Austria, Denmark, Greece and the UK but more substantially in Finland and 
Sweden.  

The only countries in which any overall trend can be observed over the long term from these 
data  are,  on  the  one  hand,  Finland  and  Sweden,  where  a  decline  in  the  first  decade  was 
followed by a small to moderate increase in the next and a strong increase in the last period, 
and, on the other, the UK, in which there was a gradual reduction in the rate of increase in 
inequality  over  the  25  years  —  though  the  degree  of  income  inequality  still  rose  over  this 
period. 

2.3. 

Low incomes — a European perspective 

The  share  of  people  on  low  incomes  in  the  EU  is  conventionally  measured  in  relation  to 
household income in the country in question. Specifically, the measure, which is the focus of 
the Open Method of Coordination in the field of social protection and social inclusion in this 
respect  and  one  of  the  main  indicators  used  in  this  context,  is  the  proportion  of  the 
population with equivalised income of less than 60 % of the national median20, as analysed 
in the Joint Report on Social Protection and Social Inclusion21.  

This measure is meaningful from a national perspective in that it identifies the people with 
the  lowest  levels  of  income  in  each  Member  State  who  are  most  likely  to  be  deprived  of 
access to the resources which other people in the community take for granted. The people so 
identified, however, can have very different levels of income in different Member States. To 
take  the  extreme  case,  people  living  in  Luxembourg  have  a  median  level  of  equivalised 
income  which  is  six  times  higher  than  in  Lithuania  even  when  income  is  measured  in 
purchasing  power  parity  terms  to  allow  for  differences  in  price  levels  between  the  two 
countries.  

20 

21  

Equivalised income is the income of households adjusted for their size and composition. The income 
thus adjusted and measured in disposable terms — i.e. net of taxes and social contributions paid by 
household members and gross of social transfers received — is assumed to be divided equally between 
household members.  
http://ec.europa.eu/employment_social/spsi/joint_reports_en.htm 

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27 

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Such differences across countries are of obvious relevance for one of the main objectives of 
the EU, which is to raise the standard of living and quality of life for all its citizens and to 
promote economic and social cohesion throughout the Union. Progress towards reducing the 
differences is primarily assessed and monitored by reference to GDP per head, measured in 
purchasing power parity terms. This, however, is an indicator of the economic strength of the 
countries, or regions, concerned and of the output produced, rather than of income levels as 
such,  and  still  less  of  the  income  received  by  households  and  the  distribution  of  income 
between households.  

To  supplement  GDP  per  head,  there  is  therefore  a  case  for  examining  household  incomes 
from  a  European  perspective  and,  accordingly,  focusing  on  social  as  well  as  economic 
cohesion  across  all  Member  States  of  the  EU.  The  need  for  an  analysis  of  differences  in 
living  standards  across  the  EU  to  complement  nationally  focused  measures  has  been 
recognised almost ever since the latter were first developed in 200122. This section therefore 
looks at the relative number of people with disposable income below a particular level either 
in  relation  to  median  income  across  the  EU  as  a  whole  —  i.e.  the  income  received  by  the 
average  person,  defined  as  the  person  at  the  mid-point  of  the  income  distribution,  which 
amounted  to  around  1100  PPS  a  month  in  2004  —  or  in  absolute  terms,  income  being 
measured,  as  in  the  case  of  GDP  per  head,  in  purchasing  power  parity  terms  to  ensure 
comparability across countries (see below).  

Such a measure is not new but has been suggested on a number of occasions in the recent 
past23.  The  EU-SILC  makes  this  calculation  possible  and  more  meaningful  than  before  by 
providing data on household income for all Member States on a reasonably consistent basis 
— with the exception, for the moment, of Bulgaria and Romania. It, accordingly, allows us 
to identify people whose income falls below a certain level and show in which countries they 
live,  as  well  as  their  characteristics.  It  allows  the  relative  income  of  such  people  to  be 
monitored over time and how this is affected by economic growth as the countries concerned 
develop.  

Measuring disposable income across the EU on a comparable basis, however, is not without 
problems. Applying purchasing power parity (PPP) estimates to data on equivalised income 
from the EU-SILC, in principle, makes it possible to compare disposable income in terms of 
what it  is capable  of purchasing. Such estimates  suggest that the average level of prices is 
around  twice  as  high  in  EU-15  countries  than  in  the  new  Member  States.  Accordingly,  in 
2004, the year to which the income data used in the analysis below  relate, a given sum of 
money expressed in euros was capable of buying almost three times as much in Poland than 
in Denmark (Table 4). 

22 

23 

See the discussion and references in Atkinson, A.B., Cantillon, B., Marlier, E. and Nolan, B. Taking 
forward the EU Social Inclusion Process, Aan independent report commissioned by the Luxembourg 
Presidency of the Council of the European Union, 2005. 
Atkinson et al, op. cit. 

EN 

28 

   EN 

 
                                                 
Table 4 Purchasing power parity rates, 2004 

PPP exchange rate1 

Value of  
€102 

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

1 322 
1 178 
1 178 
1 125 
1 104 
1 090 
1 089 
1 070 
1 065 
1 043 
1 031 
0 996 
0 898 
0 887 
0 829 
0 819 
0 730 
0 679 
0 589 
0 574 
0 534 
0 523 
0 497 
0 485 
0 482 

7,56 
8,49 
8,49 
8,89 
9,06 
9,17 
9,19 
9,35 
9,39 
9,59 
9,70 
10,04 
11,14 
11,28 
12,06 
12,21 
13,70 
14,72 
16,99 
17,41 
18,74 
19,10 
20,14 
20,60 
20,75 

1 EUR or national currency/purchasing power parity  
2 Equivalent value of €10 in terms of goods and services which it can purchase 
Source: Eurostat 

Of  course,  the  estimates  are  by  no  means  perfect.  In  particular,  it  is  difficult  to  identify 
equivalent  packages  of  goods  and  services  for  different  parts  of  the  EU  on  which  price 
comparisons  can  be  based.  They  also  take  no  account  of  regional  variations  in  purchasing 
power,  which  can  be  pronounced.  Moreover,  the  income  being  measured  does  not  include 
income in kind, such as food grown for a household’s own consumption, which is important 
in a number of places, especially in the more rural parts of some of the new Member States. 
These  considerations  need  to  be  kept  in  mind  when  interpreting  the  estimates  presented 
below. 

The population with income below various low income thresholds in the EU 

As indicated above, estimates of the relative number of people with income below a certain 
level in the EU can be made from the data collected by the EU-SILC in 2005 for income in 
2004.  These  data,  however,  do  not  include  Bulgaria  and  Romania.  Moreover,  no  detailed 
data  are  available  for  Malta.  Accordingly,  the  estimates  presented  below  relate  to  24 
Member States. A range of measures of the low income threshold are taken, both because it 
is  not  clear  what  the  most  appropriate  level  should  be  and  in  order  to  examine  how  the 
relative number of people living below the threshold changes as the level is varied.  

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29 

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As  Figure  4  below  shows,  around  100  million  Europeans  in  2004  (22.5 %  of  the  total 
population) had less than 60 % of the EU median income of around 670 PPS per month for a 
single person or €22 a day measured on an equivalised basis24. Some 23.5 million had to get 
by on less than €10 a day, and nearly 7 million even less than €5 a day.  

Figure 4: EU Population below 60 percent of EU median income (2004) 

EU-27 Population Below 60% of EU Median Income

above € 22; 356,5 m

€18-€22; 28,1

€15-€18; 24,4

€10-€15; 25,3

below €5; 6,9

€5-€10; 16,6

* except Bulgaria, Malta and Romania.

 Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

These  figures  need  to  be  interpreted  with  caution.  In  particular,  the  limitations  of  the  EU-
SILC data on income need to be recognised. They inevitably involve a degree of uncertainty, 
which is especially large for incomes at the two extremes of the distribution. At the bottom 
end  of  the  scale,  there  are  a  number  of  negative  incomes.  These  relate  to  self-employed 
people  who  reported  losses  in  2004,  since  the  disposable  income  of  the  self-employed  is 
measured by their business earnings. In these cases, income defined in this way is unlikely to 
reflect their actual consumption possibilities. Moreover, wealth is not included at all in the 
EU-SILC. The group with the lowest incomes may, therefore, include people who can afford 
a reasonably high level of consumption as a result of running down their savings and wealth. 
Finally, many people with low monetary incomes, particularly in rural areas, may be able to 
increase their consumption possibilities by producing their own food or bartering goods and 
services  within  their  local  communities.  The  numbers  presented  here  may  therefore  give  a 
false impression of the number of people on very low incomes.  

24 

Income in the EU is the sum of equivalised household disposable income, measured in PPP terms in 
the 24 Member States covered.  

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30 

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Relative thresholds: 60 %, 50 % and 40 % of EU median 

The  22.5 %  of  the  population  below  60 %  of  the  EU  median  level  of  disposable  income 
compares with a figure of 16 % with income below 60 % of the national median level in the 
country  in  which  they  live,  which  is  the  weighted  average  of  the  figures  for  the  risk  of 
poverty  at  national  level  across  the  EU  (i.e.  the  indicator  used  in  the  Open  Method  of 
Coordination in the field of social protection and social inclusion). 

Figure 5 Proportion of people with income below 60 %, 50 % and 40 % of the EU median level 
of disposable income (in PPS), 2004 

% of population in each country

< 60% < 50% < 40%

90

80

70

60

50

40

30

20

10

0

90

80

70

60

50

40

30

20

10

0

T
L

K
S

V
L

U
H

L
P

E
E

Z
C

T
P

L
E

S
E

I

5 S
2
-
U
E

T

I

Y
C

E

I

K
U

R
F

E
B

E
D

E
S

I

L F
N

K
D

T
A

U
L

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

The  proportion  of  people  in  each  Member  State  with  income  below  this  threshold  is 
obviously much larger in the countries with relatively low levels of income per head than in 
those with higher levels. In Latvia, Lithuania and Slovakia 83-84 % of the population in each 
case  have  an  income  below  60 %  of  the  EU  median  (i.e.  only  16-17 %  of  people  have  an 
income above this), in Estonia, Hungary and Poland 76-78 % and in the Czech Republic just 
over 51 %. On the other hand, in Slovenia, the figure is only just over 16 % and in Cyprus 
12-13 %, which in both cases is below the EU average. It is also well below the proportion in 
Portugal (45 %), which in turn is well above the proportion in Greece and Spain (25-26 %).  

These  three  countries  apart,  the  only  other  Member  States  where  the  relative  number  of 
people with income below 60 % of the EU median is above 10 % are Italy (just under 16 %) 
and  Ireland  (just  under  12 %)25.  In  Denmark  and  Austria,  the  figure  is  under  5 %  and  in 
Luxembourg only around 1 %.  

Lowering  the  threshold  from  60 %  to  50 %  of  EU  median  income,  of  course,  reduces  the 
number of people below the threshold but at varying rates in different countries because of 
national differences in the distribution of income. In the EU as a whole, the proportion with 

25 

Although  GDP  per  head  in  Ireland  is  the  second  highest  in  the  EU,  behind  Luxembourg,  average 
household income is much lower than this because of the substantial scale of net income going abroad 
(in practice to foreign-owned enterprises in the country). 

EN 

31 

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income below this level is reduced to just over 16 % of the total population, or to some 73.2 
million. In Latvia and Lithuania, the proportion is reduced but it is still around 75 % of the 
population. In Slovakia it remains at 70 %, slightly above the figures in Estonia and Poland, 
at  around  66-67 %.  These,  in  turn,  are  now  higher  than  in  Hungary  (63 %),  reflecting  the 
greater  concentration  of  incomes  in  Hungary  at  just  below  60 %  of  the  EU  median  (and 
accordingly the more equal distribution of income). In the Czech Republic, the proportion is 
reduced to below that of Portugal and in Slovenia, to the same level as in Italy (10 %). 

A further reduction of the threshold to 40 % of the EU median (or to just under 450 PPS a 
month) lowers the share of the population with income below this level to 11 %, or to some 
48.8 million. The proportion in Latvia and Lithuania is still well over 60 %. In Estonia and 
Poland it is reduced by more but remains at 51-52 %, which is now above the proportion in 
Slovakia, and some 10 percentage points more than in Hungary. In the Czech Republic, the 
proportion  is  reduced  to  well  below  that  in  Portugal  (to  just  over  15 %  as  compared  with 
22 % in Portugal) and in Slovenia to below that in Italy. In the EU-15 Member States except 
for the four southern countries, less than 3 % of people have income below 40 % of the EU 
median.  

Despite  the  relatively  small  proportions  of  people  with  income  below  these  thresholds  in 
most of the EU-15 countries, it is still the case that, because of their population size, a large 
share of all the people in the EU with incomes of these levels live in these countries. Almost 
half (just under 48 %) of people with income below 60 % of the EU median, therefore, live 
in  the  EU-15,  some  11 %  of  them  in  Spain,  another  9 %  in  Italy  and  just  under  7 %  in 
Germany. At the same time, 29 % live in Poland (Figure 6). 

Figure  6  Persons  with  income  below  60 %,  50 %  and  40 %  of  the  EU  median  level  of 
disposable income (in PPS), 2004 

% of EU population below 60% of EU median level of disposable income

< 60%

< 50%

< 40%

PL: 29%, 35%, 40%

12

11

10

9

8

7

6

5

4

3

2

1

0

12

11

10

9

8

7

6

5

4

3

2

1

0

0

L
P

S
E

T

I

U
H

E
D

Z
C

R
F

T
P

K
U

K
S

T
L

R
G

V
L

L
N

E
E

E
B

E
S

E

I

I

T S
A

I

F

K
D

Y
C

U
L

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

With the low income threshold at 50 % of EU median income, some 60 % of the people with 
income  below  this  level  live  in  the  new  Member  States  –  around  35 %  in  Poland  alone. 
Nevertheless, 40 % still live in the EU-15 countries, 18 % of these in Spain and Italy taken 
together. With the threshold reduced to 40 % of the EU median, the proportion with income 
below  this  level  living  in  the  new  Member  States  goes  up  to  around  65 %,  with  40 %  in 
Poland. Nevertheless, some 16 % live in Spain and Italy. 

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32 

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Income below €10 per day 

The thresholds used to measure the relative number of people with low incomes can also be 
expressed in  absolute rather than relative  terms,  which  may  clarify  what  income  levels  are 
being looked at. An income of 40 % of the EU median in 2004 represents an average of just 
under €15 a day (measured in terms of what this amount can purchase on average in different 
countries rather than in actual euros — see Table 4 above). A significant number of people 
across  the  EU,  and  in  the  new  Member  States  in  particular,  however,  have  equivalised 
disposable incomes below this.  

Just over 5 % of the total population in the EU had a daily income in 2004 of less than €10 a 
day, measured in PPS terms, which means some 23.5 million people overall. In Latvia and 
Lithuania, this was the case for 37-40 % of the population (over 2 million people in total), 
and in Estonia and Poland, for over a quarter (26-27 %). The proportion was also significant 
in  Hungary  (15 %)  and  Slovakia  (18 %).  In  Portugal,  it  was  9 %,  which  represents  almost 
960 000 people — twice the total number and the proportion in the Czech Republic (Table 
5). 

Table 5 People with income below €10 and €5 a day, in PPP terms, 2004  

Less than €10 a 
day (000) 

Less than €5 
a day (000) 

BE 
CZ 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
IT 
CY 
LV 
LT 
LU 
HU 
NL 
AT 
PL 
PT 
SI 
SK 
FI 
SE 
UK 
EU-25 

70 
417 
62 
841 
354 
28 
469 
1 718 
425 
1 787 
5 
828 
1 348 
1 
1 512 
287 
84 
10 400 
957 
31 
977 
24 
141.9 
743 
23 500 

27.9 
32.5 
47.5 
412.8 
69.1 
8.8 
168.7 
696.7 
152.3 
848.4 
1.2 
193.4 
351 
0.4 
120 
177 
22.6 
2 642.6 
230.8 
6.9 
164.9 
6.4 
81.5 
410.5 
6 873.6 

Less than €10 
a day 
(% in each 
country) 
0.7 
4.1 
1.2 
1.0 
26.6 
0.7 
4.4 
4.0 
0.7 
3.1 
0.7 
37.2 
39.6 
0.3 
15.2 
1.8 
1.0 
27.5 
9.1 
1.6 
18.1 
0.5 
1.5 
1.5 
5.3 

Less than €5 
a day  
(% in each 
country) 

0.3 
0.3 
0.9 
0.5 
5.2 
0.2 
1.6 
1.6 
0.3 
1.5 
0.2 
8.7 
10.3 
0.1 
1.2 
1.1 
0.3 
7.0 
2.2 
0.4 
3.1 
0.1 
0.9 
0.8 
1.5 

Note: Household income equivalised for differences in household size and composition and shared equally between members, 
expressed in PPS terms in each country. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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33 

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In all the other EU-15 countries, the proportion with this level of income was less than 5 %. 
It is still the case, however, that almost a third of people with this level of income — over 
7.5  million  altogether  —  lived  in  the  EU-15  countries,  and  around  15 %  of  the  total  (3.5 
million)  in  Spain  and  Italy.  Nevertheless,  the  main  concentration  is,  of  course,  in  the  new 
Member States, where almost 16 million people are estimated to have an income this low. 
Almost 10.5 million of these lived in Poland.  

A significant proportion of these people on extremely low incomes have actually reported a 
negative  income.  They  number  almost  200 000  each  in  Germany,  Spain  and  the  UK  and 
more than 300 000 in Italy. Although the people concerned account for only around 0.5 % or 
less of the total population in each country — and would accordingly reduce the proportion 
with  an  income  of  less  than  €10  a  day  by  this  amount  —  they  represent  a  significant 
proportion  of  those  with  very  low  incomes  in  many  EU-15  countries  in  particular.  In 
Denmark, they account for over half of people with an income of below €10 a day and over a 
quarter  in  the  Netherlands  and  the  UK  (Table  6).  It  is  still  the  case,  however,  that  1.2-1.3 
million people in each of Spain and Italy had an income of less than €10 a day in 2004.  

Table 6 People with income below or equal to zero, 2004 

Number 
(000) 

6.9 
- 
33.8 
191.2 
7.9 
4.9 
72.6 
180.1 
27.0 
304.9 
0.4 
16.8 
17.2 
0.1 
10.5 
89.7 
1.9 
110.0 
38.9 
0.8 
10.0 
1.4 
32.1 
193.6 
1 352.8 

BE 
CZ 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
IT 
CY 
LV 
LT 
LU 
HU 
NL 
AT 
PL 
PT 
SI 
SK 
FI 
SE 
UK 
EU-25 

Low income thresholds relative to EU 
median income: 
<50 % 
(% of people in each category) 

<40 % 

<60 % 

0.8 
- 
12.9 
2.8 
0.8 
1.0 
2.6 
1.7 
0.5 
3.3 
0.4 
0.9 
0.6 
2.8 
0.1 
8.5 
0.5 
0.4 
0.8 
0.3 
0.2 
0.5 
5.2 
4.2 
1.4 

1.6 
- 
18.6 
5.5 
0.9 
2.1 
3.7 
2.5 
1.0 
5.3 
0.7 
1.0 
0.7 
5.3 
0.2 
13.4 
0.8 
0.4 
1.1 
0.4 
0.3 
1.0 
8.9 
8.1 
1.8 

4.0 
- 
27.4 
10.9 
1.1 
5.5 
6.7 
4.2 
2.5 
8.5 
1.6 
1.2 
0.8 
7.0 
0.3 
19.3 
1.3 
0.6 
1.7 
1.0 
0.4 
2.1 
13.5 
14.0 
2.8 

<€10 a 
day 

<€5  
a day 

9.8 
- 
54.2 
22.7 
2.2 
17.4 
15.5 
10.5 
6.3 
17.1 
7.1 
2.0 
1.3 
11.7 
0.7 
31.2 
2.3 
1.1 
4.1 
2.7 
1.0 
5.8 
22.6 
26.1 
5.8 

24.8 
- 
71.2 
46.3 
11.4 
56.5 
43.0 
25.9 
17.7 
35.9 
29.6 
8.7 
4.9 
34.6 
8.7 
50.7 
8.4 
4.2 
16.9 
12.1 
6.1 
22.2 
39.4 
47.2 
19.7 

Note: Household income equivalised for differences in household size and composition and shared equally between members, 
expressed in PPP terms in each country. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007.  

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34 

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Income below €5 a day 

A  significant  number  of  people  in  the  EU  have  an  income  of  even  less  than  €10  a  day. 
According to the EU-SILC, around 1.5 % of the EU population26 had a disposable income of 
just €5 a day (again measured in PPP terms) in 2004. Although this is a small percentage, it 
still represents almost 7 million people. In Latvia and Lithuania, this accounted for around 9-
10 % of the population, while in Poland some 7 % of the population, or around 2.6 million 
people, had an income this low. 

Although the majority of people with an income of €5 a day live in the new Member States 
—  39 %  in  Poland  —  almost  half  live  in  the  EU-15  countries.  Many  of  these  are  self-
employed with a negative trading income, but even if these are excluded, there are still just 
over  2  million  people  with  this  level  of  income  in  the  EU-15  Member  States  and  over  1 
million in Spain and Italy taken together. 

Concluding remarks 

The  above  analysis  suggests  that  examining  low  incomes  across  the  EU,  in  the  sense  of 
estimating  the  relative  number  of  people  whose  disposable  income,  duly  adjusted  for 
purchasing  power  differences,  falls  below  a  particular  level  calculated  either  in  relation  to 
the EU median or as an absolute amount provides a useful complement to nationally-based 
indicators  of  poverty  risk.  In  particular,  it  could  become  a  useful  additional  tool  for 
monitoring how quickly the poorer parts of the EU are catching up. As such, it provides an 
indication of how disparities in income distribution across the EU as a whole are tending to 
change  and  of  how  to  assess  progress  towards  convergence  of  income  levels  and  living 
standards, in the same way as GDP per head is used to assess economic convergence. 

The measure highlights the fact that, although the problem of low incomes is most serious in 
many of the new Member States, there are nevertheless significant numbers of people in the 
richer parts of the Union whose income is well below the median in the EU and who seem to 
have relatively little to live on. Further investigation is required to assess how far the income 
data  in  the  EU-SILC  accurately  reflect  their  living  conditions  and  the  kinds  of  policy  best 
suited to alleviating their situation. 

There is a parallel need in the EU-15 countries, in particular, to examine in more detail the 
living  standards  of  the  self-employed  and  to  see  how  the  problem  of  negative  or  zero 
incomes arising from the way their income is currently measured can best be overcome. 

2.4.  Who are the poor: groups most at risk in the Member States 

The  indicator  which  is  used  to  measure  the  risk  of  poverty  in  EU  Member  States  is  the 
proportion of the population with equivalised disposable income below 60 % of the national 
median.  This  varies  from  9 %  in  Sweden  and  10 %  in  the  Czech  Republic  to  21 %  in 
Lithuania and Poland. The risk of poverty within Member States, however, varies markedly 
between different sections of the population. At the same time, those at the highest risk also 
vary across countries.  

Nevertheless, four groups stand out as having a high risk in nearly all countries. These are:  

26 

Not including Bulgaria, Malta and Romania.  

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35 

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–  people of working age living alone with a dependent child, who are, in the vast 

majority of cases, women; 

–  people living alone aged 65 and over who are no longer in paid employment – 
and  who  again,  in  most  cases,  are  women,  many  of  whom  may  not  have  been 
working before reaching 65; 

–  people living alone of working age who are not in employment; 

–  families with children where only one of the parents is in employment. 

These groups vary across countries not only in terms of the risk of poverty they face but also 
in terms of their numbers and the share of total population they represent. In particular, lone 
parents are much more numerous in some countries than others, as are those of working age 
living  alone  generally.  In  countries  where  these  groups  represent  a  relatively  small 
proportion  of  the  population,  they  may  also  account  for  only  a  small  proportion  of  people 
with income below the at-risk-of-poverty threshold, despite having a high risk of poverty as 
such.  Similarly,  a  section  of  the  population  with  a  much  lower  risk  of  poverty  may, 
nevertheless, make up a relatively large share of the total at risk simply because there are a 
substantial number of them.  

The  risk  of  poverty  within  different  groups,  therefore,  gives  policymakers  only  partial 
guidance as to where measures to alleviate poverty should be targeted. A high risk of poverty 
among a particular group may signify gaps in policy or in its effectiveness, but it does not 
necessarily indicate the groups which policy needs to target if the concern is to reduce the 
overall risk. To achieve the latter objective, measures could be targeted at people who make 
up the largest number of those with income below the at-risk-of-poverty threshold, who may 
not necessarily be those with the highest risk.  

The concern here is with the composition of the population with income below the threshold, 
with the groups who make up the largest shares, and with the extent to which these groups 
differ across Member States.  

The risk of poverty 

The analysis is based on data from the EU-SILC for 2005, which relate to income in 2004 
and cover 24 EU Member States, the countries excluded being Bulgaria, Romania and Malta. 
Being at risk of poverty is defined as having equivalised annual disposable income of less 
than 60 % of the national median income level27. The focus is on people, including children, 
having  income  below  this  level  and  specifically  on  their  age,  sex  and  household 
circumstances in terms of the type of household in which they live and its work intensity — 
i.e.  the  number  of  people  in  the  household  in  work  relative  to  the  total  living  there  of 
working age, adjusted for months during the year when not in employment28.  

27 
28 

Equivalised to adjust for differences in the size and composition of households. 
Work intensity is 1 if all people of working age in the household are employment throughout the year. 
It is less than 1 if this is not the case. In practice, in most cases where it is less than 1 either only one 
of a couple is employed throughout the year or no-one in the household is working. 

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36 

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These characteristics can be combined into a limited number of broad groups to assess the 
risk of poverty as follows: 

–  lone parents with dependent children living at home 

–  lone women of 65 and over 

–  lone men of 65 and over 

–  people  living  alone  of  less  than  65  who  are  unemployed  or  were  employed  for 

only part of the year 

–  people of less than 65 living alone and who were employed throughout the year 

–  couples aged 65 and over  

–  households  with  two  people  of  working  age  and  with  one  or  two  dependent 

children, with a work intensity of less than 1 

–  households  with  two  people  of  working  age  and  with  one  or  two  dependent 

children, with a work intensity of 1 

–  households  with  two  people  of  working  age  and  with  three  or  more  children, 

with a work intensity of less than 1 

–  households  with  two  people  of  working  age  and  with  three  or  more  children, 

with a work intensity of 1 

–  households  with  two  people  of  working  age  without  children,  with  a  work 

intensity of less than 1 

These  groups  are  mutually  exclusive  but  do  not  cover  all  households.  In  practice,  most  of 
them  feature  among  the  five  groups  who  account  for  the  largest  shares  of  those  at  risk  of 
poverty in at least one Member State and, as noted above, several feature in most countries. 
They do not include, it should be noted, households with two people working throughout the 
year  and  households  with  more  than  two  adults  both  with  and  without  children  and  with 
varying levels of work intensity. In all of these cases, the households concerned tend to have 
a relatively low risk of poverty and do not feature among the ‘top’ five groups with income 
below the at-risk-of-poverty threshold in any of the countries. 

The risk of poverty among these groups in each of the 24 Member States is shown in Table 
7, which indicates the wide differences across the EU in the risk faced by particular groups. 
For  women  living  alone  aged  65  and  over,  for  example,  the  risk  is  over  50 %  in  Cyprus, 
Spain  and  Ireland  but  under  8 %  in  Luxembourg,  the  Netherlands  and  Poland.  For  lone 
parents, on the other hand, the risk does not exceed 50 % in any country, but is over 20 % in 
all Member States except Sweden.  

The  effect  on  income  of  unemployment,  or  only  partial  employment,  among  those  of 
working age is very apparent. The risk of poverty is particularly high in nearly all countries 
for people of working age living alone who are not employed or employed for less than half 
the year. Nevertheless, it still ranges from 23 % in the Netherlands to over 70 % in Estonia, 
Latvia and Slovenia. The risk is particularly high in households with three or more children 
where  not  everyone  —  typically  only  one  of  a  couple  —  or  no-one  is  working.  This  risk 
exceeds 50 % in Spain, Latvia, Lithuania, Poland and Portugal, and is below 20 % only in 
Germany and Finland.  

EN 

37 

   EN 

 
Table 7 At-risk-of-poverty rates in selected social groups by household type and work intensity, 2004  

Lone 
women 
of 65+ 

Lone  
men  
of 65+ 

Single 
people <65 
with work 
intensity  
of <1 

Single 
people <65 
with work 
intensity=1 

Couples 
without 
children 65+ 

Households 
with 1-2 
children with 
work 
intensity of 
<1 

2 adults with 
1-2 children 
with work 
intensity of 1 

Households 
with 3+ 
children with 
work 
intensity of 
<1 

Households 
with 3+ 
children with 
work 
intensity of 1 

Households 
<65 without 
children with 
work 
intensity of < 
1 

Lone 
parents 

AT 

BE 

CY 

CZ 

DE 

DK 

EE 

ES 

FI 

FR 

EL 

HU 

IE 

IT 

LT 

LU 

LV 

NL 

PL 

PT 

SE 

SI 

SK 

UK 

27 

27 

74 

16 

27 

20 

44 

51 

39 

22 

36 

12 

65 

38 

36 

5 

46 

7 

8 

40 

21 

49 

13 

33 

11 

27 

60 

5 

18 

24 

29 

32 

27 

20 

31 

6 

56 

25 

18 

13 

37 

5 

6 

45 

12 

26 

3 

23 

33 

33 

52 

41 

50 

40 

71 

46 

41 

31 

39 

37 

65 

47 

58 

31 

73 

23 

36 

53 

28 

72 

32 

49 

7 

5 

12 

4 

10 

10 

10 

8 

5 

7 

6 

18 

8 

9 

9 

10 

13 

6 

12 

18 

10 

11 

10 

9 

11 

16 

47 

2 

12 

13 

11 

29 

8 

13 

27 

4 

20 

20 

9 

7 

11 

4 

6 

28 

4 

12 

4 

23 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007.

28 

43 

26 

43 

17 

27 

37 

51 

18 

32 

43 

50 

34 

48 

55 

23 

55 

32 

55 

51 

21 

36 

38 

48 

8 

3 

2 

2 

1 

8 

8 

13 

5 

5 

16 

15 

10 

7 

33 

16 

11 

11 

31 

30 

4 

5 

16 

18 

15 

12 

19 

14 

15 

8 

25 

19 

8 

12 

17 

14 

24 

14 

25 

12 

28 

11 

16 

22 

10 

15 

12 

24 

27 

36 

35 

41 

30 

21 

40 

37 

20 

26 

43 

27 

45 

35 

48 

32 

31 

26 

40 

34 

18 

22 

32 

36 

3 

1 

2 

2 

3 

3 

4 

8 

2 

3 

7 

8 

2 

3 

5 

8 

6 

5 

9 

12 

3 

2 

10 

8 

18 

25 

19 

22 

13 

8 

24 

29 

10 

19 

25 

35 

24 

28 

37 

23 

28 

18 

30 

38 

7 

27 

27 

27 

38 

EN 

EN 

 
  
 
The composition of the population at risk of poverty 

•  Age breakdown 

As noted above, the social groups who are at most risk of poverty are not necessarily those 
who make up most of the population with income below the at-risk-of-poverty threshold. The 
ratio of the groups in question to the total population is an equally important factor. Since the 
broad  age  composition  of  the  population  at  large  is  relatively  similar  across  countries,  the 
differences  in  the  at-risk-of-poverty  rates  described  above  are  indicative  of  the  variations 
between  Member  States  in  the  age  breakdown  of  people  with  at-risk-of-poverty  levels  of 
income.  

Thus,  in  Cyprus,  where  the  risk  of  poverty  among  people  of  65  and  over  is  higher  than 
anywhere else in the EU, such people account for some 37 % of all those with income below 
the at-risk-of-poverty threshold, much higher than in other parts of the EU. On the other hand, 
in a number of the other new Member States, where the risk of poverty for those in this age 
group is relatively low — in particular in the Czech Republic, Hungary, Poland and Slovakia 
— people aged 65 and over make up less than 10 % of the total with at-risk-of-poverty levels 
of  income  (Table  8).  This  is  also  the  case  in  Luxembourg  and  the  Netherlands.  In  these 
countries, children make up a much larger share of those at risk of poverty than in most other 
parts of the EU, accounting for well over 20 % of the total and around 30 % in Luxembourg 
and the Netherlands.  

At the same time, in the new Member States concerned, people of working age also account 
for a relatively large share of the population at risk (65 % or more in each case and over 70 % 
in  Poland  and  Slovakia).  As  indicated  below,  the  age  composition  of  people  with  income 
below  the  at-risk-of-poverty  threshold  in  these  countries  reflects  the  relatively  high  level  of 
retirement pensions relative to wages and unemployment benefit. 

EN 

39 

   EN 

 
Table 8 Distribution of the population at risk of poverty by age group  
(% of total population at risk of poverty in the country) 

Children, 0-15  Working age, 16-64 

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

23 
27 
17 
15 
19 
25 
15 
18 
20 
18 
16 
17 
24 
30 
25 
29 
21 
24 
19 
15 
22 
16 
18 
23 

54 
65 
61 
63 
63 
56 
58 
57 
58 
58 
47 
65 
64 
63 
68 
64 
61 
71 
57 
60 
72 
59 
63 
54 

Elderly, 65+ 
22 
7 
22 
22 
18 
19 
26 
25 
21 
23 
37 
19 
13 
8 
8 
7 
19 
5 
24 
25 
7 
25 
19 
22 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

•  Breakdown by age, household type and work intensity 

These  age  groups  can  be  broken  down  into  the  same  sub-groups  as  for  the  risk  of  poverty 
examination above in order to identify the characteristics of those who account for significant 
shares  of  the  population  with  income  below  the  at-risk-of-poverty  threshold  in  different 
countries. Such a breakdown shows that there are not only large variations across the EU in 
the  risk  of  poverty  faced  by  the  different  groups,  but  equally  marked  differences  in  the 
relative  size  of  the  groups  —  i.e.  in  the  shares  of  total  population  which  they  represent. 
Accordingly, the shares of the population with income below the threshold in each country are 
not completely in line with the risk of poverty as such.  

Nevertheless,  the  characteristics  of  the  main  groups  which  make  up  the  total  with  income 
below  the  threshold  vary  just  as  much  between  Member  States  as  do  the  at-risk-of-poverty 
rates  examined  above.  The  main  groups  concerned  differ  considerably  across  the  EU,  as 
shown  in  the  pie  charts  below,  which  indicate  the  groups  which  account  for  the  largest 
proportions  of  the  total  with  income  below  the  threshold  in  each  Member  State.  There  are, 
however, common features of the groups in question in many cases. 

Women  aged  65  and  over  living  alone  account  for  a  relatively  large  proportion  of  the 
population  at  risk  of  poverty  in  many  countries,  reflecting  both  the  tendency  for  women  to 
live longer than men and for them to have lower pension levels. In Finland and Slovenia they 
account for 15-16 % of all those with income below the threshold, and in Estonia and Sweden 
for 12 %. At the other extreme, in Luxembourg, the Netherlands and Poland, they account for 

EN 

40 

   EN 

 
 
only around 1-2 % of the total and in the Czech Republic, Hungary and Slovakia for 4-5 %, 
reflecting the relatively low risk of poverty of older people, even those who live alone. 

Whereas  men  aged  65  and  over  living  alone  make  up  only  a  small  proportion  of  the 
population with income below the at-risk-of-poverty threshold in all countries, couples where 
both partners are 65 and over account for a relatively large share in many countries. This is 
particularly the case in Cyprus, where they account for 25 % of the total, much more than in 
other  Member  States.  They  also  account  for  a  relatively  large  share  in  the  other  southern 
countries, Greece (16 %), Spain, Portugal (14 % in each) and Italy (12 %), as well as in the 
UK (14 %) and Germany (12 %). In these countries, therefore, the pensions paid to couples 
are in many cases not sufficient to give them an income above the threshold. 

As  indicated  above,  lone  parents  bringing  up  a  dependent  child,  almost  all  of  whom  are 
women, also face a relatively high risk of poverty in most countries. Indeed, in five Member 
States — the Czech Republic, Ireland, Lithuania, Greece and Poland — the at-risk-of-poverty 
rate  is  over  40 %  (see  Table  7  above).  In  the  first  three  of  these  countries,  lone  parents 
account for a significant proportion of the population with income  below the threshold (15-
17 %  in  each  case).  In  the  last  two,  Greece  and  Poland,  however,  they  make  up  a  smaller 
proportion  than  in  most  other  countries  (only  4-5 %)  because  of  the  small  number  of  lone 
parents  in  the  two  countries  (perhaps  partly  due  to  the  high  poverty  risk  they  face,  which 
makes it difficult to bring up a child alone). 

Lone parents account for a similarly large share of the total with income below the threshold 
in  Belgium,  Estonia  and  Sweden,  and  in  Germany  (20 %)  and  the  UK  (18 %).  In  all  these 
countries, the risk of poverty is less than in the five countries listed above. 

Even if they do not have a dependent child, people below the retirement age living alone are 
also  vulnerable  to  the  risk  of  poverty  if  they  are  not  working.  Such  people  make  up  a 
particularly large share of those with income below the threshold in Finland (19 %), Denmark 
(16 %),  Germany  and  Sweden  (12 %  in  each),  not  so  much  because  of  their  high  risk  of 
poverty — indeed in Sweden, it is lower than anywhere else in the EU — but because of their 
relatively large numbers. The large number of people of working age living alone in Denmark 
and Sweden means that even those in employment throughout the year make up 7-8 % of the 
total below the threshold in these two countries. 

Joblessness is also responsible for the fact that a large number of people sharing a household 
with  their  spouse  or  partner  or  others  of  working  age  have  an  income  below  the  threshold. 
This is especially the case for those with children, who make up a substantial proportion of 
those at risk of poverty in most countries. In both the Czech Republic and Italy, persons living 
in households with 1-2 dependent children (excluding lone parents) and with a work intensity 
of  less  than  one  (i.e.  not  everyone  of  working  age  is  in  employment  throughout  the  year) 
account for just under 30 % of all those with an income below the threshold — typically only 
one adult is working in these households. In the other three southern EU countries — Greece, 
Spain and Portugal — such people make up 21-25 % of the total, while they also account for 
over 20 % in Luxembourg, Lithuania and Slovenia.  

In  Luxembourg,  as  well  as  in  Belgium  and  the  Netherlands,  families  with  three  or  more 
children where not everyone is working (i.e. with a work intensity of less than 1) also account 
for a relatively large share of the total number of people at risk of poverty (15-16 % in each 
case), as they do in Ireland (17 %). 

EN 

41 

   EN 

 
Working-age  adults  living  together  without  children,  but  where  not  everyone  is  working, 
account for a relatively small proportion of the total with income below the threshold in most 
countries, though in the Czech Republic and the Netherlands the figure is close to 10 %. 

Joblessness,  however,  is  not  the  only  reason  for  people  of  working  age  being  at  risk  of 
poverty. Low wages also seem to play a role in a number of Member States. This is especially 
the case in Slovakia, Hungary and Portugal, where those living in households with one or two 
children and where everyone of working age is in employment make up 12-14 % of the total 
with  income  below  the  threshold,  while  in  the  Netherlands,  Luxembourg  and  the  UK,  the 
equivalent  figure  is  9-10 %.  The  figure  in  Hungary  and  Slovakia  is  increased  to  18-20 %  if 
households with three or more children are included, and in the Netherlands and the UK, to 
15-16 %.  

In  both  the  Netherlands  and  the  UK,  this  relatively  large  proportion  can  be  attributed  to  a 
large  extent  to  at  least  one  of  the  people  in  employment  working  only  part-time,  women  in 
particular. This is not the case in Hungary and Slovakia, or indeed Portugal, where relatively 
few  people  work  part-time.  In  these  countries,  therefore,  it  is  predominantly  a  result  of  low 
wage rates. 

EN 

42 

   EN 

 
Figures 7 Individuals at risk of poverty by main household types, 2004 

Austria 
Total poor population: 1,001,000 
(Children: 21%, Working age: 61%, Elderly: 19%)

Other
51%

Lone women of 65+
9%

Single people <65 
with work intensity 
of <1 
8%
Couples <65 
without children 
with work intensity 
of <1
8%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
9%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
15%

Belgium 
Total poor population: 1,538,000 
(Children: 24%, Working age: 54%, Elderly: 22%)

Other
46%

Couples with 1-2 
children with work 
intensity of <0.5
8%

Single people <65 
with work intensity 
of <1 
9%

Couples without 
children 65+

12%

Couples with 3+ 
children with work 
intensity of <0.5
10%

Lone parents
15%

Cyprus
Total poor population: 120,000 
(Children: 16%, Working age: 47%, Elderly: 37%) 

Czech Republic 
Total poor population: 1,049,000 
(Children: 27%, Working age: 65%, Elderly: 7%) 

Other
37%

Couples with 1-2 
children with 
work intensity of 
0.5<=WI<1 
17%

Lone parents
16%

Single people <65 
with work 
intensity of <1 
7%

Couples <65 
without children 
with work 
intensity of <1
10%

Couples with 1-2 
children with 
work intensity of 
<0.5
13%

Single people <65 
with work intensity 
of <1 
7%

Couples <65 
without children 
with work intensity 
of <1
10%

Other
37%

Lone parents
16%

Couples with 1-2 
children with work 
intensity of <0.5
13%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
17%

Germany 
Total poor population: 10,632,000 
(Children: 15%, Working age: 63%, Elderly: 22%) 

Denmark 
Total poor population: 632,000 
(Children: 17%, Working age: 61%, Elderly: 22%)

Couples <65 
without children 
with work intensity 
of <1
9%

Couples with 1-2 
children with work 
intensity of <0.5
9%

Single people <65 
with work intensity 
of <1 
12%

Other
38%

Couples without 
children 65+
12%

Lone parents
20%

Single people <65 
with work 
intensity=1
7%

Lone women of 65+
8%

Other
47%

Couples without 
children 65+
10%

Lone parents
12%

Single people <65 
with work intensity 
of <1 
16%

EN 

43 

   EN 

 
 
Figures 7 Individuals at risk of poverty by main household types, 2004 (continued) 

Estonia 
Total poor population: 243,000 
(Children: 19%, Working age: 63%, Elderly: 19%)

Other
46%

Lone women of 65+
12%

Lone parents
16%

Couples <65 
without children 
with work intensity 
of <1
7%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
9%

Single people <65 
with work intensity 
of <1 
10%

Spain 
Total poor population: 8,369,000 
(Children: 18%, Working age: 56%, Elderly: 25%)

Other
51%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
18%

Couples with 1-2 
children with work 
intensity of <0.5
5%

Lone women of 65+
6%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
6%

Couples without 
children 65+

14%

Finland 
Total poor population: 604,000 
(Children: 16%, Working age: 59%, Elderly: 25%)

Greece 
Total poor population: 2,088,000 
(Children: 15%, Working age: 58%, Elderly: 26%)

Other
41%

Lone parents
9%

Lone women of 65+
16%

Single people <65 
with work intensity 
of <1 
19%

France 
Total poor population: 7,641,000 
(Children: 20%, Working age: 58%, Elderly: 21%)

Other
50%

Lone parents
11%

Couples without 
children 65+
11%

Couples with 1-2 
children with work 
intensity of <0.5
7%

Couples <65 
without children 
with work intensity 
of <1
8%

Lone parents
4%

Other
45%

Couples without 
children 65+
16%

Households with 1-
2 children with 
work intensity of 1
6%

Lone women of 65+
6%

Households with 1-
2 children with 
work intensity of <1 
23%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
8%

Couples <65 
without children 
with work intensity 
of <1
8%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
12%

44 

Hungary 
Total poor population: 1,333,000 
(Children: 25%, Working age: 68%, Elderly: 8%) 

Other
51%

Lone parents
10%

Couples with 1-2 
children with work 
intensity of 1
12%

Couples <65 
without children 
with work intensity 
of <1
7%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
7%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
13%

   EN 

EN 

 
Figures 7 Individuals at risk of poverty by main household types, 2004 (continued) 

Ireland 
Total poor population: 817,000 
(Children: 25%, Working age: 56%, Elderly: 19%) 

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
8%

Other
49%

Lone women of 65+
8%

Couples with 1-2 
children with work 
intensity of <0.5
8%

Lone parents
17%

Lithuania 
Total poor population: 699,000 
(Children: 24%, Working age: 63%, Elderly: 13%) 

Other
49%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
14%

Lone parents
15%

Couples with 3+ 
children with work 
intensity of <0.5
10%

Couples with 1-2 
children with work 
intensity of <0.5
7%

Single people <65 
with work intensity 
of <1 
7%

Lone women of 65+
8%

Italy 
Total poor population: 11,084,000 
(Children: 18%, Working age: 58%, Elderly: 23%) 

Other
44%

Households with 
1-2 children with 
work intensity of 
<1 
23%

Lone women of 
65+
9%

Luxembourg 
Total poor population: 58,000 
(Children: 30%, Working age: 63%, Elderly: 8%) 

Other
43%

Lone parents
5%

Households with 
3+ children with 
work intensity of 
<1
7%

Couples without 
children 65+
12%

Couples with 1-2 
children with work 
intensity of <0.5
8%

Lone parents
8%

Couples with 1-2 
children with work 
intensity of 1
10%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
19%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
12%

Latvia 
Total poor population: 424,000 
(Children: 17%, Working age: 64%, Elderly: 19%)

Netherlands 
Total poor population: 1,750,000 
(Children: 29%, Working age: 64%, Elderly: 7%) 

Other
55%

Lone women of 65+
9%

Lone parents
9%

Single people <65 
with work intensity 
of <1 
8%

Couples <65 
without children 
with work intensity 
of <1
9%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
10%

Other
50%

Lone parents
9%

Couples with 1-2 
children with work 
intensity of 1
9%

Couples <65 
without children 
with work intensity 
of <1
9%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
11%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
12%

EN 

45 

   EN 

 
 
Figures 7 Individuals at risk of poverty by main household types, 2004 (continued) 

Poland 
Total poor population: 7,595,000 
(Children: 25%, Working age: 70%, Elderly: 5%) 

Other
63%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
11%

Slovenia 
Total poor population: 238,000 
(Children: 15%, Working age: 60%, Elderly: 25%) 

Other
46%

Lone women of 65+
15%

Sweden 
Total poor population: 846,000 
(Children: 18%, Working age: 63%, Elderly: 19%) 

Other
44%

Couples with 1-2 
children with work 
intensity of 1
5%

Couples with 3+ 
children with work 
intensity of <0.5
5%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
7%

Couples with 1-2 
children with work 
intensity of <0.5
9%

Couples with 1-2 
children with work 
intensity of <0.5
8%

Couples without 
children 65+
8%

Single people <65 
with work intensity 
of <1 
9%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
14%

Couples <65 
without children 
with work intensity 
of <1
8%

Single people <65 
with work 
intensity=1
8%

Lone women of 65+
12%

Single people <65 
with work intensity 
of <1 
12%

Lone parents
16%

Portugal 
Total poor population: 2,135,000 
(Children: 19%, Working age: 57%, Elderly: 24%) 

Couples <65 
without children 
with work intensity 
of <1
6%

Lone women of 65+
6%

Other
44%

Couples without 
children 65+
14%

Couples with 1-2 
children with work 
intensity of 1
12%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
18%

Slovakia 
Total poor population: 718,000 
(Children: 22%, Working age: 72%, Elderly: 7%) 

Other
53%

Couples with 1-2 
children with work 
intensity of 1
14%

United Kingdom 
Total poor population: 9,353,000 
(Children: 23%, Working age: 52%, Elderly: 24%)

Other
43%

Couples without 
children 65+

14%

Lone parents
18%

Couples with 3+ 
children with work 
intensity of 1
6%

Couples with 1-2 
children with work 
intensity of <0.5
7%

Couples with 3+ 
children with work 
intensity of 
0.5<=WI<1
8%

Couples with 1-2 
children with work 
intensity of 
0.5<=WI<1 
12%

Households with 
3+ children with 
work intensity of 1
7%

Households with 1-
2 children with 
work intensity of 1
9%

Lone women of 65
9%

EN 

46 

   EN 

 
 
 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Concluding remarks 

The above analysis indicates that there are differences between the social groups which have 
the highest risk of poverty, in the sense that the proportion of them with income below 60 % 
of the median in the country where they live is relatively large. These differences reflect the 
differing composition of households across the EU — and, in particular, the extent to which 
people live alone instead of sharing a house with a spouse, partner or other people — as well 
as  differences  in  the  level  of  pensions  and  social  transfers,  especially  transfers  to  the 
unemployed.  They  also  reflect,  however,  the  level  of  wages  in  different  countries  and  the 
ability  of  households  to  secure  a  level  of  income  above  the  at-risk-of-poverty  threshold 
without more than one person being in employment. This is especially the case for households 
where  there  are  dependent  children,  which  may  point  to  a  lack  of  affordable  childcare 
preventing both partners from working. 

In 14 of the 24 Member States, therefore, couples with one or two children where one of the 
partners is not working (at least throughout the year) are the largest group among those at risk 
of poverty, while in another three countries they are the second largest group. All of the new 
Member States apart from Estonia and Cyprus are included in this group of 14 countries. In 
another two countries, Belgium and Ireland, couples with three or more children where one of 
the partners is not in work represent the largest group, and these are the second or third largest 
group  among  those  at  risk  of  poverty  in  nine  of  the  countries  where  those  with  one  or  two 
children are the largest. 

In other countries, people living alone represent the largest group among the population with 
income below the threshold. This is the case in Denmark, Finland and Sweden as well as in 
Estonia, where people of working age living alone feature among the main subgroups of the 
population  at  risk  of  poverty,  especially  if  they  are  not  employed  throughout  the  year, 
(though,  in  Denmark  and  Sweden,  even  if  they  are).  Lone  parents  also  figure  prominently 
among the main groups with income below the threshold in these four countries — though to 
a lesser extent in Finland than in the other three — as they do in Germany and the UK.  

In addition, in Denmark, Estonia, Finland, Sweden and the UK, as well as Cyprus, people of 
65 and over feature among the main groups at risk of poverty, either as couples or women of 
this age living alone, or both. This is also the case in Greece, Italy, Portugal and Slovenia. 

This  diversity  among  the  social  groups  which  make  up  the  bulk  of  those  at  risk  of  poverty 
across  the  EU  emphasises  the  differences  between  Member  States  in  the  way  that  policy 
would need to be focused in order to achieve a major reduction in the number of people at risk 
of poverty.  

2.5. 

Low incomes and living standards in the EU 

The  main  indicator  of  the  risk  of  poverty  across  the  EU  is  the  proportion  of  people  with 
disposable  income  below  60 %  of  the  national  median.  However,  this  measure  of  relative 
income can only be regarded as a proxy for the ability of households to maintain a standard of 
living which enables the people concerned to feel part of their community. As this indicator is 
calculated  relative  to  national  median  income,  it  also  leaves  open  the  question  of  how  far 
people  in  different  Member  States  have  difficulty  in  affording  consumer  goods  and  other 
items which are taken for granted elsewhere in the Union. 

EN 

47 

   EN 

 
The EU-SILC contains information which throws light on both these issues. In particular, it 
indicates  whether  or  not  people  with  different  income  levels  are  able  to  afford  a  range  of 
consumer durables and an annual holiday as well  as  basic  necessities,  like  a  square  meal  at 
least  once  every  other  day  or  paying  their  utility  bills.  It  also  indicates  their  housing 
conditions  and  whether  or  not  they  have  difficulty  in  making  ends  meet  or  in  facing 
unexpected expenses. 

It, accordingly, allows estimates to be made of the relative number of people in each Member 
State  who  cannot  afford  at  least  one  of  a  range  of  items,  thus  possibly  causing  a  sense  of 
deprivation.  It  also  makes  it  possible  to  assess  the  proportion  of  people  who  suffer  from 
multiple deprivation in that they are unable to afford more than one of the items in question.  

The  analysis  below  examines,  first,  the  various  indicators  of  material  deprivation  and 
financial  hardship  and  the  proportion  of  the  population  in  each  EU  country  who  report 
experiencing one or the other or both, distinguishing those with income above and below the 
at-risk-of-poverty threshold. Secondly, it considers  people's housing conditions,  focusing on 
problems  like  a  leaking  roof,  damp  walls,  rotten  floors  or  window-frames,  and  the  link 
between having these kinds of problem and having both low income and financial difficulties. 
In  each  case,  it  also  examines  the  link  between  the  overall  prevalence  of  deprivation  and 
median  disposable  income  per  head  (measured  in  equivalised  and  purchasing  power  parity 
terms) across countries. 

As  such,  the  results  of  the  analysis  are  intended  to  complement  the  estimates  of  the  risk  of 
poverty, measured by the relative number of people with (equivalised) income below 60 % of 
the  national  median,  which  is  one  the  main  indicators  for  monitoring  the  social  situation 
across the EU, and to provide an additional insight into the extent of deprivation in different 
Member States. 

Ability to afford key consumer durables 

Analysis of the information contained in the EU-SILC shows that in nearly all EU countries, 
very few people report being unable to afford either a telephone, a colour TV or a washing 
machine — or, more accurately, live in households which cannot afford at least one of these 
items  (see  Figure  8  —  note  that  countries  are  ranked  in  terms  of  median  income  per  head 
measured in purchasing power parity terms to pinpoint the relationship between the inability 
to afford any of these items and the level of income, or more accurately, purchasing power). 
Around half of those reporting such difficulties for their household have income above the at-
risk-of-poverty  threshold  (60 %  of  the  national  median),  although  in  all  countries  there  is  a 
much  greater  probability  of  those  with  income  below  the  at-risk-of-poverty  threshold  not 
being able to afford at least one of these items than those with income above. Only in Poland 
and the three Baltic States does the proportion of people who are unable to afford the above-
mentioned consumer goods exceed 5 %, reaching a particularly high level of around 16 % in 
Latvia and Lithuania. 

EN 

48 

   EN 

 
Figure  8  Proportion  of  population  not  able  to  afford  either  a  telephone,  a  colour  TV  or  a 
washing machine, 2005 

% of total population

above poverty threshold*

below poverty threshold*

18

16

14

12

10

8

6

4

2

0

18

16

14

12

10

8

6

4

2

0

LU AT UK DK NL BE

IE

DE

FI

FR SE CY

IT

SI

ES GR PT CZ HU SK

PL EE

LV

LT

* at-risk-of-poverty threshold: 60 % of the national median equivalised income. Countries are ranked by average disposable 
income per (equivalised) head measured in PPP terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

In  all  parts  of  the  EU,  more  people  live  in  households  which  are  unable  to  afford  a  car; 
nevertheless,  in  most  countries  the  number  is  relatively  small,  especially  among  the  EU-15 
Member States. Only in Ireland, Greece and Portugal, among the EU-15 countries, did 10 % 
or more of the population report not being able to afford a car (Figure 9). 

Figure 9 Proportion of population not able to afford a car, 2005 

% of total population

30

25

20

15

10

5

0

above poverty threshold*

below poverty threshold*

38

30

25

20

15

10

5

0

LU AT UK DK NL BE

IE

DE

FI

FR SE CY

IT

SI

ES GR PT CZ HU SK

PL EE

LV

LT

* at-risk-of-poverty threshold: 60 % of the national median equivalised income. Countries are ranked by average disposable 
income per (equivalised) head measured in PPP terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Among the new Member States, the percentage is higher in all countries apart from Slovenia 
and  Cyprus.  In  the  Czech  Republic,  the  figure  is  around  15 %,  in  Hungary  22 %,  and  in 
Poland,  Lithuania,  Slovakia  and  Estonia  25-30 %,  while  in  Latvia,  it  is  as  high  as  38 %.  In 

EN 

49 

   EN 

 
 
 
each  case,  substantially  more  people  who  say  they  are  unable  to  afford  a  car  have  income 
above the threshold than below (though again the probability of not being able to afford a car 
is  much  greater  among  those  below  —  around  50 %  or  more  in  each  of  the  three  Baltic 
States).  

Whether  not  being  able  to  afford  a  car  represents  a  strong  form  of  deprivation  or  social 
exclusion is likely to depend, amongst other things, on how widespread car ownership is in 
the  community  in  which  a  person  lives.  While  almost  all households can afford telephones, 
colour TVs and washing machines, the proportion of households with a car is around 80 % in 
the EU-15 countries (slightly less in Greece, Portugal and Denmark), and less than 60 % of 
people have cars in Hungary, Slovakia, Poland and the three Baltic States, and less than 50 % 
in Latvia. 

Ability to afford a decent meal every other day 

More  worryingly  perhaps,  a  large  number  of  people  in  all  the  new  Member  States,  except 
Estonia, report not being able to afford a meal with meat or fish or the vegetarian equivalent 
at least every other day — something which is defined as a basic need by the World Health 
Organisation. The proportion often exceeds that of people who report being unable to afford a 
car.  In  Hungary,  Slovakia,  Poland,  Latvia  and  Lithuania,  around  30 %  or  more  of  the 
population  (slightly  below  this  in  Lithuania)  and  around  40 %  in  Slovakia  state  that  they 
cannot  afford  a  decent  meal  every  other  day.  Most  of  the  people  concerned  have  income 
above the threshold (Figure 10). What this underlines is that income-based indicators are not 
sufficient  for  assessing  the  intensity  of  deprivation  across  the  Member  States.  They  also 
suggest that more attention needs to be given to access to affordable basic nutrition.  

Figure  10  Proportion  of  population  not  able  to  afford  a  meal  with  meat,  chicken,  fish  (or 
vegetarian equivalent) every second day, 2005 

% of total population

40

35

30

25

20

15

10

5

0

above poverty threshold*

below poverty threshold*

41

40

35

30

25

20

15

10

5

0

AT UK DK NL

BE

IE

DE

FI

FR SE CY

IT

SI

ES GR PT CZ HU SK

PL

EE

LV

LT

* at-risk-of-poverty threshold: 60 % of the national median equivalised income. Countries are ranked by average disposable 
income per (equivalised) head measured in PPP terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

In many of the EU-15 countries, including Spain, Greece and Portugal, between two and six 
percent of the population reported that they could not afford such a decent meal every other 
day. However, in both Austria and Germany, the proportion of the population was larger — 

EN 

50 

   EN 

 
 
8 %  and  10 %  respectively  with,  in  each  case,  many  more  people  with  income  above  the 
threshold  than  below,  although  this  might  reflect  a  slightly  different  interpretation  of  the 
question in these two countries rather than more widespread deprivation as such. 

Arrears on utility bills 

Indicators of financial hardship contained in the EU-SILC include being in arrears on utility 
bills29. Here there is less of a difference between the EU-15 countries and the new Member 
States in the relative numbers. Again, the number concerned is relatively small in most EU-15 
countries — 5 % or less in the majority of cases and over 8 % only in Italy (11 %) and, most 
strikingly, Greece where, at 27 %, it is higher than anywhere else in the EU; two-thirds of the 
people concerned in Greece have income above the at-risk-of-poverty threshold (Figure 11). 
In the new Member States, it is less than 10 % in Cyprus, the Czech Republic and Slovakia, 
but  over  20 %  in  Lithuania  and  Poland,  with  again  most  of  those  concerned  having  income 
above the threshold. 

Figure 11 Proportion of population in arrears on utility bills, 2005 

% of total population

above poverty threshold*

below poverty threshold*

30

25

20

15

10

5

0

n a

30

25

20

15

10

5

0

AT UK DK NL

BE

IE

DE

FI

FR SE CY

IT

SI

ES GR PT CZ HU SK

PL

EE

LV

LT

* at-risk-of-poverty threshold: 60 % of the national median equivalised income. Countries are ranked by average disposable 
income per (equivalised) head measured in PPP terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Capacity to face unexpected expenses 

The  EU-SILC  also  contains  a  question  on  the  capacity  of  households  to  pay  an  unexpected 
cost from their own resources. To make this more objective the amount of the unexpected cost 
was specified in the question and related to the level of income in each country (specifically 
to  the  at-risk-of-poverty  threshold)  so  as  to  adjust  for  this  and  make  the  answers  more 

29 

It  also  includes  being  in  arrears  on  rent  and  mortgage  payments.  This,  however,  does  not  apply  to  a 
large proportion of people  in  most  EU  countries because they  own  their  own  homes  and  seem  not  to 
have  outstanding  loans  to  pay  off.  This  is  particularly  the  case  in  the  new  Member  States  in  most  of 
which the great majority of people own the homes they live in and report having no housing costs. 

EN 

51 

   EN 

 
 
                                                 
comparable between Member States30. The number of people who reported not being able to 
meet the expense was relatively large in all Member States. It was also considerably larger in 
most  of  the  new  Member  States  than  in  other  parts of the EU,  despite the fact  that the cost 
represented a similar share of income to other parts of the EU. This suggests that the ability to 
meet such costs is not proportionate to income but is less in low-income countries, reflecting 
the smaller amount of money left over after essential items have been purchased. 

Even  in  EU-15  countries,  however,  with  the  sole  exception  of  Sweden  and,  perhaps 
surprisingly,  Portugal,  over  20 %  of  the  population  reported  difficulties  in  meeting  a 
significant  unexpected  cost.  In  the  UK,  Finland,  France  and  Spain,  the  proportion  was  over 
30 % and in Greece close to 40 % (Figure 12). 

In  all  the  new  Member  States,  with  the  sole  exception  of  Estonia,  where  the  question  was 
somewhat different, over 40 % of the population reported that they would have difficulties. In 
Hungary and Slovakia, the proportion was 55-60 % and in Poland, Latvia and Lithuania, 60-
70 %. In all cases, over 70 % of those who said they could not meet an unexpected cost had 
income above the at-risk-of-poverty threshold. 

Figure 12 Proportion of population unable to face unexpected financial expenses, 2005 

% of total population

above poverty threshold*

below poverty threshold*

80

70

60

50

40

30

20

10

0

80

70

60

50

40

30

20

10

0

AT UK DK NL

BE

IE

DE

FI

FR SE CY

IT

SI

ES GR PT CZ HU SK

PL

EE

LV

LT

* at-risk-of-poverty threshold: 60 % of the national median equivalised income. Countries are ranked by average disposable 
income per (equivalised) head measured in PPP terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

People experiencing at least one form of deprivation 

There  is  a  good  deal  of  overlap  between  the  people  reporting  difficulties  in  relation  to  the 
items examined above, in the sense that many of the same people appear under the different 
items.  The  difficulties,  however,  are  not  confined  to  a  small  group  in  many  cases.  In  most 
countries, a significant proportion of the total population report having problems as regards at 
least one of the items considered above. Accordingly, there are a great many people across the 

30 

Specifically,  respondents  were  asked  whether  their  household  could  afford  an  unexpected  required 
expense  of  an  amount  equal  to  the  poverty  threshold,  expressed  as  a  monthly  sum,  from  its  own 
resources. 

EN 

52 

   EN 

 
 
                                                 
EU who can be regarded as materially deprived on the strength of at least one indicator. The 
number,  as  might  be  expected,  varies  in  fairly  close  correlation  with  the  median  level  of 
income per head of countries, with a few significant exceptions. 

Leaving  the  capacity  to  face  unexpected  expenses  aside,  the  proportion  of  people  who  say 
they cannot afford any one of a telephone, TV, washing machine, a car or a decent meal at 
least once every other day or who were in arrears on their utility bills amounted to just 6 % in 
Luxembourg,  the  country  with  by  far  the  highest  median  income  per  head,  and  10-12 %  in 
Austria, the UK, Denmark and the Netherlands, the four countries with the next highest levels 
(Table 9). The proportion, however, was equally small in Sweden and Spain, where income 
per head was lower, especially in the latter. Similarly in Portugal, only 17 % of people lived 
in households not able to afford at least one of the items in question or in arrears on utility 
bills, which is the same as in Germany or Finland, where income per head is much higher. 

In the new Member States, the proportion was around 40 % or more in all the countries apart 
from Cyprus and Slovenia, where median income per head is higher than in Spain, Greece or 
Portugal,  and  in  the  Czech  Republic,  where  median  income  was  lower  but  where  the 
proportion (at 29 %) was also well below 40 %. In Slovakia, Poland, Latvia and Lithuania, it 
was 50 % or more. In most countries, and in all of the new Member States, around two-thirds 
or more of those concerned had income above the at-risk-of-poverty threshold. 

With  a  few  exceptions,  therefore,  there  is  a  close  inverse  association  across  EU  Member 
States  between  indicators  of  financial  hardship  and  the  median  level  of  income  per  head 
(Figure 13). 

Figure 13 Distribution of EU Member States by equivalised median household income (in PPS) 
and proportion of population deprived*, 2004 

60

50

40

30

20

10

0

0

% of total population deprived

SK

LV

PL

LT

HU

EE

CZ

EL

PT

SI

ES

IT FR

FI

CY

DE

IE
BE

DK

AT

SE

NL

UK

5.000

10.000

15.000

20.000

25.000

Equivalised median income

60

50

40

30

20

10

LU

0
30.000

* Unable to afford phone / TV / washing machine / car / decent meal and/or in arrears on utility bills 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

If  the  range  of  indicators  of  financial  hardship  is  extended  to  include  a  lack  of  capacity  to 
meet  unexpected  expenses,  the  proportion  of  people  reporting  negatively  in  relation  to  any 
one of the indicators is increased significantly in all countries, reflecting the limited overlap 
between  this  indicator  and  the  others  in  many  cases.  The  proportion  of  people  concerned 
increases to 25 % or more in all Member States, except Luxembourg, where it is just below, 

EN 

53 

   EN 

 
 
and Sweden, where it is only 19 %, reflecting the smaller scale of financial difficulties here 
compared to other parts of the EU. In Greece it is increased to almost half, while in all of the 
new Member States, except for Cyprus and Slovenia, where it is just below, it is up to 50 % or 
more. In Slovakia, Poland, Latvia and Lithuania the proportion exceeds 70 %. 

Table 9 Population deprived according to at least one indicator, 2005 

 % of total population 

Total 

Phone, TV, washing 
machine, car, meal, utility 
bills 
Income 
above 
60 % 
median 
3 
9 
6 
8 
7 
7 
9 
11 
12 
10 
8 
10 
9 
16 
6 
21 
11 
23 
37 
47 
40 
27 
43 
35 
13 

Income 
below 
60 % 
median 
3 
4 
4 
4 
3 
6 
7 
6 
5 
5 
2 
5 
7 
5 
4 
11 
6 
7 
10 
9 
16 
12 
16 
16 
6 

6 
12 
10 
12 
10 
13 
16 
17 
17 
14 
11 
15 
16 
21 
10 
31 
17 
29 
46 
56 
55 
38 
58 
50 
20 

Phone, TV, washing 
machine, car, meal, utility 
bills+unexpected cost 

Income 
above 
60 % 
median 
15
22
22
22
22
17
17
21
28
29
15
34
21
38
25
35
18
41
55
62
54
35
59
53
28

Income 
below 
60 % 
median 
8
7
10
7
6
10
11
9
8
9
4
13
12
9
11
14
9
9
12
11
18
15
18
19
11

Total 

23
29
33
28
28
26
28
29
37
38
19
46
33
47
36
49
27
50
66
72
73
50
78
72
38

Total 

 % unable to meet unexpected 
costs 
Extent of overlap of capacity 
to meet unexpected costs 
with items in first columns 
Income 
above 
60 % 
median 
14 
28 
23 
27 
26 
34 
39 
38 
34 
28 
36 
24 
31 
35 
17 
47 
39 
46 
62 
71 
68 
62 
68 
60 
39 

Income 
below 
60 % 
median 
32
46
40
55
44
60
57
64
57
48
47
39
52
52
30
70
58
73
82
80
84
74
86
83
57

21 
33 
28 
33 
30 
44 
47 
46 
39 
33 
38 
28 
39 
38 
21 
54 
46 
52 
65 
72 
72 
66 
73 
67 
44 

LU 
AT 
UK 
DK 
NL 
BE 
IE 
DE 
FI 
FR 
SE 
CY 
IT 
SI 
ES 
EL 
PT 
CZ 
HU 
SK 
PL 
EE 
LV 
LT 
EU-25 

Note: Countries are ranked by median disposable income per head on an equivalised basis and measured in purchasing power 
terms. 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

In the new Member States, again with the exception of Cyprus and Slovenia, there is a higher 
degree of overlap between being unable to meet unexpected expenses and the other indicators 
of deprivation or financial hardship than in all the EU-15 countries apart from Greece. In the 
Czech Republic over 50 % of those without the resources to cover an unexpected expense also 
report being unable to afford one or more of the items taken as indicators of deprivation; in 
the  other  transition  countries  this  proportion  rises  to  over  65 %.  The  extent  of  overlap  is 
particularly  large  among  those  with  income  below  the  at-risk-of-poverty  threshold.  In 
Hungary, Slovakia, Poland, Latvia and Lithuania 80 % or more of those with income below 

EN 

54 

   EN 

 
 
 
 
the  threshold  and  reporting  an  inability  to  meet  unexpected  expenses  also  report  financial 
difficulties in relation to the other indicators. 

Housing conditions 

A significant number of people in all Member States, with the exception of the three Nordic 
countries  and  Slovakia,  report  problems  with  leaking  roofs,  damp  walls,  rotten  floors  and 
window frames or similar. The percentage of the population concerned ranges in the EU-15 
countries from 10 % in Austria to around 20-21 % in Greece and Portugal and 23 % in Italy 
(Table 10). In the latter three countries, however, it is perhaps not so much of a problem as in 
the north of Europe given the warmer climate. In all the countries well over two-thirds of the 
people affected have income above the at-risk-of-poverty threshold, though it is still the case 
that a much larger share of those with income below this report this kind of problem (20-30 % 
of them in all the countries apart from Austria and the three Nordic countries).  

EN 

55 

   EN 

 
Table 10 Population reporting various problems with housing, 2004, % of total population 

Leaking roof, 
damp walls, 
floors… 
12 

No indoor 
bath or 
shower 
0 

No indoor 
toilet for 
sole use 
0 

Leaking 
roof, etc + 
no bath 
0 

3 
8 

2 
11 

4 
7 

1 
15 

3 
11 

4 
8 

4 
11 

3 
4 

1 
10 

3 
5 

1 
29 

7 
17 

6 
15 

4 
13 

5 
15 

6 
14 

6 
17 

3 
27 

6 
5 

2 
32 

12 
18 

7 
29 

11 
23 

9 

0 
0 

0 
0 

0 
0 

0 
0 

0 
1 

1 
0 

0 
0 

0 
1 

1 
1 

0 
0 

0 
1 

1 
0 

0 
1 

1 
0 

0 
1 

1 
2 

2 
1 

1 
5 

3 
1 

1 
5 

4 
14 

6 
14 

9 
13 

10 

0 
1 

1 
1 

0 
0 

0 
0 

0 
1 

0 
0 

0 
1 

0 
1 

0 
1 

0 
0 

0 
1 

1 
0 

0 
1 

1 
0 

0 
2 

2 
2 

1 
1 

1 
5 

3 
2 

1 
4 

3 
12 

5 
14 

9 
15 

10 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

1 
0 

0 
1 

1 
0 

0 
0 

1 
1 

1 
0 

1 
3 

2 
0 

0 
4 

3 
5 

3 
9 

6 
6 

5 

Leaking 
roof, etc + 
no toilet 

All 3 
problems 

0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

1 
0 

0 
1 

1 
1 

1 
1 

1 
3 

2 
1 

0 
3 

3 
4 

2 
8 

6 
6 

5 

0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
0 

0 
1 

1 
0 

1 
3 

2 
0 

0 
3 

3 
4 

2 
8 

6 
5 

5 

At least 1 
of 3 
problems 
12 

3 
9 

2 
11 

4 
7 

2 
15 

3 
12 

4 
8 

4 
11 

3 
5 

1 
10 

3 
5 

1 
30 

7 
17 

6 
16 

4 
13 

5 
16 

7 
15 

6 
18 

3 
29 

7 
7 

2 
33 

13 
28 

10 
36 

13 
32 

15 

LU  >60 % median 

<60 % median 
AT  >60 % median 

<60 % median 
UK  >60 % median 

<60 % median 
DK  >60 % median 

<60 % median 
NL  >60 % median 

<60 % median 
BE  >60 % median 

<60 % median 
>60 % median 

IE 

<60 % median 
DE  >60 % median 

<60 % median 
>60 % median 

FI 

<60 % median 
FR  >60 % median 

<60 % median 
SE  >60 % median 

<60 % median 
CY  >60 % median 

<60 % median 
>60 % median 

<60 % median 
>60 % median 

IT 

SI 

<60 % median 
ES  >60 % median 

<60 % median 
EL  >60 % median 

<60 % median 
PT  >60 % median 

<60 % median 
CZ  >60 % median 

<60 % median 
HU  >60 % median 

<60 % median 
SK  >60 % median 

<60 % median 
PL  >60 % median 

<60 % median 
EE  >60 % median 

<60 % median 
LV  >60 % median 

<60 % median 
LT  >60 % median 

<60 % median 

Note: Countries ranked by median equivalised income of people 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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56 

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In the new Member States, apart from Slovakia (where there are few reported problems with 
housing), the number of people with housing problems of this kind range from 19-20 % of the 
total  population  in  Slovenia  and  the  Czech  Republic  and  25 %  in  Estonia  to  32-33 %  in 
Hungary and Lithuania and 40-44 % in Latvia and Poland. Again, as in the EU-15 countries, 
the large majority of the people concerned by such housing problems — over three-quarters 
—  have  income  above  the  threshold.  However,  the  share  of  people  experiencing  such 
problems is much higher among those with income below the threshold: 30-33 % in Slovenia 
and the Czech Republic, 37 % in Estonia and over 40 % in all the other countries. The people 
concerned, therefore, experience both a low income and poor housing conditions. 

In the new Member States, a leaking roof, damp walls or similar problem also goes together 
in some cases with the lack of a bath, shower or indoor flushing toilet for the sole use of the 
household,  whereas  very  few  people  in  the  EU-15  countries  lack  these  amenities.  This  is 
particular the case in the lowest-income countries. In Hungary 5 % of the population had both 
leaking  roof,  damp  walls  or  similar  problems  and  had  no  indoor  bath,  shower  or  toilet.  In 
Poland and Estonia the proportion was 6 %, in Lithuania 10 % and in Latvia as much as 14 %.  

Poor housing conditions and financial hardship 

In a number of cases, those living in poor housing conditions also face financial hardship — 
indeed the latter tends to exacerbate the former. This is the case in Poland, in particular, where 
21 % of the population in 2005 reported that they both lived in poor housing conditions and 
could not afford a meal of meat or fish, or the vegetarian equivalent, at least every other day 
(Table 11). Over 60 % of these had income above the at-risk-of-poverty threshold, but 8 % of 
the total population could not afford such a meal, lived in poor housing and had low income. 
In Latvia, the proportion facing all three problems was only slightly smaller at 7 %.  

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Table 11 People living in poor housing conditions who also have financial problems, 2004 

Those with leaking roof, damp walls or similar problems who also: 

Cannot afford a meal of meat or 
fish every other day 

Are in arrears  
on utility bills 

 % total 
population

Total 
0,6 
1,7 
1,3 
0,2 
0,6 
1,2 
1,0 
2,4 
0,4 
1,5 
0,2 
3,1 
2,7 
3,3 
0,8 
2,6 
2,1 
5,9 
14,3 
4,1 
20,6 
5,3 
18,1 
11,4 

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

>60 % 
median 
0,3 
1,2 
0,7 
0,1 
0,4 
0,5 
0,4 
1,4 
0,3 
0,9 
0,1 
1,7 
1,4 
2,2 
0,3 
1,2 
0,7 
4,2 
10,3 
2,8 
12,6 
2,8 
11,0 
6,2 

<60 % 
median 
0,3 
0,5 
0,6 
0,1 
0,2 
0,7 
0,7 
1,0 
0,1 
0,6 
0,1 
1,4 
1,3 
1,0 
0,6 
1,4 
1,3 
1,7 
4,0 
1,3 
7,9 
2,5 
7,1 
5,2 

Total 
1,0 
0,5 
n a 
0,4 
1,0 
2,1 
2,3 
0,9 
0,9 
1,9 
0,7 
5,5 
4,2 
4,2 
1,1 
8,1 
1,5 
2,9 
8,7 
1,1 
14,8 
4,9 
9,8 
9,8 

>60 % 
median 
0,5 
0,3 
n a 
0,3 
0,8 
1,0 
1,1 
0,6 
0,6 
1,2 
0,5 
4,1 
2,1 
2,9 
0,7 
4,8 
0,8 
1,9 
5,7 
0,5 
8,8 
3,1 
6,9 
6,3 

<60 % 
median 
0,5 
0,2 
n a 
0,1 
0,3 
1,1 
1,3 
0,3 
0,2 
0,7 
0,2 
1,4 
2,0 
1,3 
0,4 
3,3 
0,8 
1,0 
2,9 
0,6 
6,1 
1,8 
2,9 
3,4 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Elsewhere  the  proportion  living  in  poor  housing  conditions  and  at  the  same  time  not  being 
able  to  afford  a  square  meal  every  other  day  was  also  over  10 %  in  Hungary  (14 %)  and 
Lithuania (11 %). In other Member States, however, especially in the EU-15, the link between 
poor  housing  and  financial  hardship  was  less  close:  under  4 %  of  the  population  in  all 
countries  apart  from  the  Czech  Republic,  Slovakia  and  Estonia  experienced  this  particular 
combination of problems. 

The same is broadly true if being in arrears on utility bills is taken as an indicator of financial 
hardship.  The  proportion  of  the  population  reporting  both  kinds  of  problem  was  again 
relatively large in Poland (15 %) as well as Latvia and Lithuania (10 %); in Greece, too, this 
combination of problems was relatively common (8 %). 

Socio-economic inequalities in mortality and morbidity 

Low  incomes  may  not  only  result  in  poor  living  conditions,  but  may  even  be  reflected  in 
poorer health and increased mortality. Several studies focus on this connection and reveal that 
income,  occupational  status,  education  and  psychosocial  factors  affect  the  distribution  of 
morbidity, particularly cardiovascular diseases and mental illness, within countries and tend to 

EN 

58 

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reduce life expectancy substantially (four to six years among men, two to four years among 
women). As a consequence, people with a low  socio-economic status not only die younger, 
but also tend to be ill for more years during their lifetime31.  

The relation between health conditions and social economic status operates indirectly through 
several  specific  health  determinants.  Material  factors,  such  as  low  income  and  increased 
exposure to health risks, are certainly partly responsible for this outcome. Socio-economically 
disadvantaged  people  are  also  more  likely  to  suffer  from  psycho-social  stress.  Work 
organisation, for instance, has proved to be an important factor in explaining socio-economic 
inequalities in cardiovascular health. Unhealthy behavioural traits (smoking, inadequate diet, 
excessive alcohol consumption, lack of physical exercise etc) tend to be more prevalent in the 
lower socio-economic groups in many European countries32.  

Differences  in  access  to  health  services  across  socio-economic  groups  have  also  been 
observed  and  may  contribute  to  health  inequalities.  In  some  EU-15  and  almost  all  new 
Member States, people with higher income report easier access to hospitals. The accessibility 
gap  in  the  EU-15  between  the  highest  and  lowest  income  quartile  is  more  than  20 %  in 
Belgium, France, Italy, Portugal and the UK; in the new Member States the difference is less 
than 20 % only in the Czech Republic, Slovenia, Estonia, Lithuania, and Latvia; in Hungary 
and Slovakia it is larger than 30 %. The differences are, however, less marked with reference 
to general practitioner’s services (Figure 14). Unemployed and retired people have on average 
greater  difficulty  than  the  employed  in  getting  to  hospital.  This  is  the  case  in  all  European 
countries, both in terms of geographical barriers and the likelihood of being admitted, but the 
difference is more marked in the new Member States33. 

31 
32 
33 

J.P. Mackenbach Health Inequalities: Europe in Profile, February 2006. 
Ibidem 
Alber, J. and Kohler, U., “Health and care in an enlarged Europe”, Dublin, European Foundation for the 
improvement of working and living conditions, 2004) 

EN 

59 

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Figure 14 Proximity to hospitals and general practitioner’s services: difference between lowest 
and highest income quintile 

s
t
n
o
p

i

e
g
a
t
n
e
c
r
e
P

40

30

20

10

0

-10

-20

-30

AT BE BG CY CZ DE DK EE EL ES FI

FR HU IE IT LT LU LV MT NL PL PT RO SE SI

SK UK

EU27

General practictioner Hospital

Note: proximity is measured by access to a hospital and general practitioners’ services in less than 20 minutes. 
Source:  Alber  and  Köhler,  2004  based  on  Eurobarometer  52.1,  Q17/D29;  Candidate  Countries  Eurobarometer  2002.1, 
Q25/D29:  if  you  had  to  go  to  each  of  the  following  places  from  home,  how  long  would  it  take  you?  —  The  nearest  hospital.’ 
‘Your general doctor/health centre.’ 

There  are  wide  inequalities  in  self  perceived  health  between  groups  based  on  level  of 
education,  with  the  worst  educated  reporting  2-3  times  the  level  of  fair/poor  health.  These 
differences  have  persisted  throughout  the  1980s  and  1990s.  Health  inequalities  by  socio-
economic status and by education in particular have been observed34 in self-assessed health in 
Austria,  Denmark,  England,  Italy,  Finland,  the  Netherlands,  Norway,  West  Germany,  and 
Spain (see Table 12). Between the 1980s and the 1990s, socio-economic inequalities in self-
assessed  health  remained,  on  average,  stable  for  men  but  increased  slightly  for  women. 
Increasing  inequalities  were  observed  in  Italy,  the  Netherlands  and  Spain,  but  this  was  not 
seen in Northern countries. 

34 

Kunst et al, “Trends in socio-economic inequalities in self-assessed health in 10 European countries”, 
International Journal of epidemiology 34(2): 295-306, 2005). 

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Table  12  Magnitude  of  educational  differences  in  fair/poor  self-assessed  health:  men  and 
women aged 25-69 years; odds ratios (95 % confidence intervals) 

Country 

Men 

1980s 

1990s 

Women 

1980s 

1990s 

AT 

DK 

UK 

FI 

IT 

NL 

NO 

ES 

3.39 (2.92-3.93) 

3.22(2.79-3.71) 

2.75 (2.37-3.19) 

2.67 (2.31-3.07) 

2.93 (2.16-3.9) 

2.30 (1.73-3.04) 

3.10 (2.13-4.50) 

2.84 (2.10-3.82) 

3.11 (2.27-4.25) 

3.08 (2.57-3.68) 

2.08 (1.59-2.71) 

2.66 (2.21-3.19) 

3.15 (2.55-3.88) 

2.99 (2.44-3.66) 

2.86 (2.28-3.58) 

3.29 (2.60-4.18) 

2.05(1.79-2.34) 

2.94 (2.54-3.40) 

1.86 (1.62-2.15) 

2.55 (2.20-2.95) 

2.95 (2.46-3.52) 

2.81 (2.39-3.30) 

1.95 (1.63-2.35) 

2.12 (1.81-2.49) 

2.37 (1.71-3.29) 

2.37 (1.70-3.30) 

3.32 (2.37-4.66) 

3.06 (2.22-4.23) 

1.86 (1.56-2.17) 

2.58 (1.81-3.67) 

1.97 (1.63-2.37) 

3.10 (2.18-4.41) 

DE (W) 

1.50 (1.20-1.88) 

1.76 (1.44-2.14) 

1.89 (1.43-2.50) 

1.91 (1.50-2.44) 

The reference category in all countries is higher educational level 
Source: Kunst et al, 2005. 

Concluding remarks 

The  above  analysis  suggests  that  material  deprivation  and  financial  hardship  does  not  only 
affect  people  with  income  below  the  at-risk-of-poverty  threshold.  It  is  particularly  wide-
spread in the poorer new Member States, where a significant proportion of the population live 
in  households  which  report  not  being  able  to  afford  particular  consumer  goods  or  a  decent 
meal at least once every other day. Most of the people concerned have income above the at-
risk-of-poverty threshold. The same is true for other indicators of financial hardship, namely 
being in arrears on utility bills and not having the resources to meet unexpected expenses.  

Equally, a significant number of people in many parts of the EU report living in poor housing, 
once again in the new Member States in particular, in some cases in accommodation which 
lacks  an  indoor  bath  or  shower  and/or  an  indoor  flushing  toilet  for  the  sole  use  of  the 
household.  In  the  lowest-income  countries,  in  particular,  a  sizeable  proportion  of  the 
population both live in poor housing and face financial hardship. Again many of these have 
income above the threshold. 

However, it is people at the lower end of the income distribution who are most likely to face 
material deprivation and financial hardship. In addition, the lower socio-economic groups are 
disadvantaged  in  terms  of  health,  resulting  in  poorer  access  to  health  care,  a  worse  self-
assessed health status and, ultimately, lower life expectancy. 

It is evident from the analysis, therefore, that the indicators on material deprivation, financial 
hardship, housing conditions and health provide an important additional insight into the extent 
of poverty and social exclusion over and above what can be gleaned from the indicator of the 
risk of poverty based on income levels relative to the median in each country. In particular, 
material  deprivation  indicators  highlight  disparities  across  the  Member  States  that  do  not 
show up in the same way when looking at income-based indicators. Efforts to reduce relative 
poverty in each Member States must go hand in hand with determined efforts to raise living 
standards across all socio-economic groups, particularly in the poorer Member States. 

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3. 

THE SCOPE FOR MORE EQUAL OPPORTUNITIES 

This part of the Social Situation Report examines the extent to which European societies fail 
to offer equal opportunities and hence to make full use of their human potential. It is based on 
a first analysis of the EU-SILC module on the intergenerational transmission of disadvantages 
(3.1)  and  on  an  analysis  of  the  risk  of  poverty  among  children  with  migrant  family 
background. 

3.1. 

Intergenerational transmission of disadvantages 

The extent to which a person’s life chances are affected by their family background and how 
far it is possible for someone to escape from a less advantaged background provide a measure 
of social mobility across the EU.  

The  EU-SILC  for  2005  included  a  special  ad  hoc  module  which  addressed  this  issue. 
Specifically, each respondent aged 25-65 was asked a set of questions about the situation of 
their parents when the respondent was aged between 12 and 16. The analysis here examines 
the responses to these questions and what they reveal, first, about the educational attainment 
level  of  parents  and  their  children  and  the  closeness  of  the  links  between  the  two,  and, 
secondly, about the same kind of links as regards the jobs held by parents and their children. 
The strength of these links are indicated below in terms of the ‘odds ratio’, which measures 
the increased probability of, for example, someone whose father or  mother had a university 
degree  or  the  equivalent  (i.e.  a  tertiary  level  of  education)  him/herself  having  this  level  of 
qualification as compared with someone whose parents had a lower education level.  

The results of the analysis are not only interesting in themselves but are important for the light 
they  throw  on  the  scale  of  obstacles  to  achieving  true  equality  of  opportunity  for  people 
throughout the EU, irrespective of their social origin, and ensuring that everyone is given the 
chance to realise their potential and contribute to the full to economic advancement and rising 
living  standards.  Such  obstacles  could  be  a  major  constraint  to  the  pursuit  of  the  Lisbon 
agenda and to securing its central aim of making the EU the most competitive and dynamic 
knowledge-based economy in the world, capable of sustainable economic growth with more 
and better jobs and greater social cohesion, as was stated in the Conclusions of the Lisbon 
European Council of March 2000. 

The link between the education level of fathers and their children 

Differences in education systems across the EU and in the relative number of people attaining 
different  levels  of  education  complicate  any  comparison  of  the  influence  of  parents  on  the 
education level attained by their children. In particular, taking two extremes, the proportion of 
people  aged  25-64  with  no  education  beyond  compulsory  schooling  (lower  secondary 
education or below) varies from 74 % in Portugal to 10 % in the Czech Republic, while the 
proportion with upper secondary education, but not tertiary level, varies from under 14 % in 
the former to 77 % in the latter.  

The  probability  of  someone  attaining  an  upper  level  of  secondary  education  is,  therefore, 
much lower in Portugal than in the Czech Republic, irrespective of the level of education of 
the father or mother. By the same token, in the Czech Republic, only around 12 % of people 
aged  25-64  have  tertiary  education  as  compared  with  35 %  in  Finland,  which  implies  that 
there is a much smaller chance of attaining this level of education in the former than the latter, 
again irrespective of the father’s or mother’s education. 

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62 

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These large differences should be kept in mind when interpreting the results presented below. 
The analysis focuses on the relative chances of men and women attaining tertiary education in 
relation  to  the  education  level  of  their  parents,  because  there  is  more  similarity  in  the 
proportion of those with tertiary education across the EU and, accordingly, the results are less 
subject to distortion, but also because tertiary education is becoming increasingly important to 
economic performance. 

The probability of men and women aged 25-64 having tertiary level education is significantly 
higher in all EU Member States if their father had the same level of education than if he had a 
lower level.  

Table 13 Probability of attaining High education, of women and men, aged 25-65, by education 
level of father 

Highest education attained 
by father 

Odds 
ratio 

Low  Medium

High 

High/Low

Country 

Father 
not 
present 

CZ 
PL 
HU 
SI 
IT 
SK 
LU 
PT 
LV 
CY 
EL 
LT 
EU-25 
AT 
IE 
FR 
ES 
DK 
BE 
NL 
SE 
EE 
UK 
FI 
DE 

0,10 
0,08 
0,14 
0,07 
0,08 
0,15 
0,21 
0,09 
0,14 
0,18 
0,18 
0,18 
0,18 
0,15 
- 
0,12 
0,20 
- 
0,18 
0,25 
0,21 
0,21 
- 
0,27 
0,31 

0,05
0,07
0,07
0,05
0,08
0,08
0,12
0,11
0,12
0,20
0,16
0,17
0,18
0,14
0,23
0,22
0,22
0,18
0,25
0,25
0,24
0,22
0,29
0,29
0,28

0,12
0,24
0,19
0,20
0,36
0,20
0,32
0,58
0,26
0,55
0,46
0,36
0,33
0,26
0,56
0,53
0,51
0,28
0,54
0,43
0,52
0,36
0,43
0,45
0,35

0,52
0,69
0,60
0,42
0,64
0,52
0,80
0,65
0,58
0,81
0,65
0,65
0,63
0,51
0,82
0,72
0,72
0,57
0,79
0,69
0,63
0,58
0,69
0,62
0,58

11,0
9,7
9,1
8,0
7,7
6,7
6,5
6,0
4,7
4,1
4,1
3,8
3,6
3,6
3,5
3,3
3,3
3,2
3,2
2,8
2,6
2,6
2,4
2,2
2,1

Odds 
ratio 
High/ 
Father 
not 
present 
5,1 
9,1 
4,2 
6,0 
7,7 
3,5 
3,8 
6,9 
4,1 
4,6 
3,7 
3,7 
3,4 
3,3 
- 
6,0 
3,7 
- 
4,3 
2,8 
3,1 
2,8 
- 
2,3 
1,9 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

In all the EU Member States for which data are available (i.e. the 27 less Bulgaria, Malta and 
Romania), with the sole exception of Slovenia, the probability of someone having completed 
tertiary education is over 50 % if their father had tertiary education (Table 13). Moreover, in 
all countries, the chances of people having this level of education if their father had the same 
level  are  over  twice  as  high  as  for  people  whose  fathers  had  only  basic  schooling  (‘low’ 
education in the table). In the Czech Republic, Poland and Hungary, the chances are over nine 
times greater (i.e. the odds ratio thus calculated is over nine) and in Slovenia and Italy around 

EN 

63 

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eight  times  greater.  Indeed,  in  all  the  new  Member  States  covered,  apart  from  Estonia,  the 
odds ratio is around four or higher.  

At the other extreme, in the Netherlands, Sweden, the UK, Finland and Germany, as well as 
Estonia, the odds ratio is under three — though still of course over two — implying that there 
is  less  of  an  obstacle  in  these  countries  than  elsewhere  to  someone  whose  father  had  only 
basic schooling attaining tertiary education, but that the obstacle is, nevertheless, significant. 

Having no father living at home during a person’s early teenage years — i.e. being brought up 
by a lone mother — seems to have a similar influence on the child’s education level as having 
a father with only a basic level of education (which could have more to do with the education 
level of the mothers than the fact of having no father at home). 

The link between education levels of fathers and that of sons and daughters 

The  influence  of  the  father’s  education  level  is  similar  for  sons  and  daughters  considered 
separately,  in  the  sense  that  for  both  the  chances  of  having  tertiary  education  if  their  father 
had also completed tertiary education are much greater than if their father had a lower level of 
education. In both cases, the odds ratio, comparing fathers with tertiary education with fathers 
with only basic schooling, is around two or over in all countries (Table 14a and 14b).  

There are a number of countries, however, where the odds ratio is higher for daughters than 
sons, implying that it is more difficult for women to attain tertiary education if their father had 
only basic schooling than it is for men. This is the case, in particular, in the Czech Republic, 
Hungary,  Germany,  Austria  and  the  Netherlands.  However,  the  reverse  is  true  in  Denmark, 
Sweden and Portugal, suggesting that the obstacles are less for daughters. 

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Tables 14a and 14b Probability of attaining High education of men and women aged 25-65, by 
education level of father 

14a Men 

Highest education attained 
by father 

Odds 
ratio 

Low  Medium

High 

High/Low

Country 

Father 
not 
present 

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

0,07 
0,09 
0,14 
0,07 
0,06 
0,04 
0,16 
0,22 
0,11 
0,17 
0,17 
0,18 
- 
0,16 
- 
0,07 
0,21 
0,24 
0,19 
0,22 
- 
0,24 
0,21 
0,37 

0,06
0,07
0,07
0,08
0,08
0,05
0,09
0,15
0,09
0,14
0,16
0,22
0,15
0,14
0,25
0,21
0,18
0,22
0,25
0,18
0,29
0,31
0,24
0,33

0,20
0,13
0,17
0,36
0,52
0,17
0,19
0,35
0,15
0,26
0,47
0,55
0,25
0,27
0,59
0,50
0,48
0,49
0,53
0,29
0,44
0,47
0,39
0,43

0,65
0,57
0,58
0,67
0,62
0,36
0,49
0,81
0,51
0,60
0,67
0,84
0,53
0,51
0,88
0,72
0,61
0,72
0,77
0,48
0,69
0,72
0,54
0,63

10,5
8,4
8,2
8,0
7,6
6,6
5,5
5,5
5,4
4,4
4,1
3,9
3,7
3,6
3,6
3,4
3,3
3,3
3,1
2,6
2,4
2,4
2,2
1,9

Odds 
ratio 
High/ 
Father 
not 
present 
9,4 
6,2 
4,2 
9,1 
9,9 
8,4 
3,1 
3,8 
4,8 
3,5 
4,0 
4,8 
- 
3,3 
- 
9,6 
2,9 
3,1 
4,1 
2,1 
- 
3,0 
2,5 
1,7 

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14b Women 

Highest education attained 
by father 

Odds 
ratio 

Low  Medium

High 

High/Low

Country 

Father 
not 
present 

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

0,11 
0,15 
0,10 
0,08 
0,20 
0,13 
0,09 
0,10 
0,12 
0,17 
0,18 
0,18 
0,19 
- 
0,26 
0,18 
0,16 
0,16 
- 
0,26 
- 
0,20 
0,25 
0,33 

0,03
0,06
0,05
0,08
0,10
0,07
0,08
0,10
0,14
0,15
0,18
0,16
0,20
0,23
0,19
0,25
0,22
0,23
0,21
0,22
0,30
0,30
0,29
0,33

0,11
0,21
0,23
0,28
0,30
0,20
0,36
0,23
0,64
0,36
0,55
0,45
0,45
0,54
0,40
0,55
0,53
0,55
0,31
0,28
0,43
0,56
0,43
0,50

0,46
0,63
0,48
0,72
0,79
0,54
0,61
0,54
0,67
0,65
0,78
0,63
0,71
0,76
0,65
0,81
0,73
0,73
0,61
0,54
0,69
0,66
0,64
0,70

16,8
10,0
9,7
9,1
8,1
8,0
7,5
5,4
4,9
4,4
4,3
4,1
3,5
3,4
3,4
3,3
3,3
3,2
2,9
2,5
2,4
2,2
2,2
2,1

Odds 
ratio 
High/ 
Father 
not 
present 
4,2 
4,2 
4,9 
8,9 
3,9 
4,0 
6,6 
5,5 
5,4 
3,8 
4,4 
3,4 
3,8 
- 
2,6 
4,6 
4,6 
4,6 
- 
2,0 
- 
3,3 
2,6 
2,1 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

The link between education levels of fathers and children by age 

The EU-SILC module can also be used to examine the relationship between education levels 
of  fathers  and  their  children  by  the  age  of  respondents  (i.e.  of  the  children  concerned). 
Dividing the respondents into successive ten-year age groups — 25-34, 35-44 and 45-54 — 
gives an indication of how the closeness of the link between the education level of fathers and 
their children has tended to change over time. Assuming that the average age of fathers at the 
birth of their children has not changed much over the years, the fathers of children aged 25-34 
will have gone through the education system on average 10 years after the fathers of 35-44-
year-olds, who will in turn have completed their education 10 years after those aged 45-54. 

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Table 15 Probability of attaining High education of men and women by age and by education 
level of father 

Country  Age 

Father not 
present 

Low 

Medium 

High 

High/ Low 

Highest education attained by father 

Odds ratio 

BE 

CZ 

DK 

* 
DE 

EE 

IE 

EL 

ES 

FR 

IT 

CY 

LV 

LT 

LU 

HU 

NL 

AT 

PL 

25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
35-44 
45-54 
55-64 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 

0,25
0,20
0,15
0,11
0,13
0,08
-
-
-
0,24
0,41

0,13
0,23
0,24
-
-
-
0,26
0,25
0,13
0,27
0,26
0,14
0,18
0,14
0,12
0,11
0,08
0,07
0,26
0,17
0,17
0,16
0,14
0,11
0,32
0,12
0,15
0,33
0,21
0,19
0,13
0,17
0,16
0,27
0,23
0,22
0,30
0,17
0,17
0,07
0,10

0,33
0,27
0,23
0,04
0,02
0,07
0,22
0,21
0,19
0,28
0,33
0,28
0,16
0,22
0,23
0,41
0,24
0,18
0,19
0,20
0,14
0,33
0,23
0,16
0,35
0,24
0,17
0,10
0,09
0,08
0,28
0,20
0,18
0,13
0,11
0,12
0,16
0,13
0,20
0,18
0,13
0,08
0,04
0,06
0,06
0,34
0,28
0,24
0,15
0,16
0,13
0,10
0,07

0,57
0,56
0,48
0,11
0,15
0,13
0,33
0,29
0,30
0,36
0,40
0,35
0,30
0,38
0,36
0,60
0,50
0,59
0,44
0,51
0,49
0,57
0,50
0,46
0,62
0,50
0,46
0,32
0,34
0,49
0,55
0,56
0,62
0,22
0,25
0,32
0,34
0,32
0,46
0,41
0,30
0,28
0,19
0,22
0,17
0,46
0,40
0,43
0,29
0,26
0,25
0,28
0,21

0,84 
0,76 
0,77 
0,50 
0,55 
0,49 
0,58 
0,50 
0,61 
0,61 
0,68 
0,58 
0,55 
0,56 
0,65 
0,84 
0,85 
0,81 
0,63 
0,71 
0,55 
0,75 
0,74 
0,69 
0,80 
0,66 
0,73 
0,63 
0,66 
0,61 
0,81 
0,81 
0,81 
0,54 
0,59 
0,60 
0,69 
0,60 
0,67 
0,83 
0,81 
0,74 
0,59 
0,66 
0,58 
0,68 
0,69 
0,70 
0,46 
0,51 
0,62 
0,77 
0,62 

2,5
2,8
3,4
11,9
27,0
7,1
2,4
3,1
3,1
2,2
2,1
2,1
3,5
2,6
2,8
2,1
3,6
4,6
3,3
3,6
4,0
2,3
3,2
4,3
2,3
2,7
4,2
6,3
7,4
7,3
2,9
4,1
4,4
4,2
5,2
5,1
4,2
4,6
3,3
4,6
6,3
8,8
14,1
10,3
9,6
2,0
2,4
3,0
3,1
3,1
4,8
7,5
9,1

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Country  Age 

Father not 
present 

Low 

Medium 

High 

High/ Low 

Highest education attained by father 

Odds ratio 

PT 

SI 

SK 

FI 

SE 

UK 

45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 
25-34 
35-44 
45-54 

0,04
0,14
0,07
0,10
0,11
0,09
0,06
0,14
0,16
0,15
0,28
0,34
0,23
0,21
0,22
0,28
-
-
-

0,06
0,17
0,09
0,09
0,09
0,05
0,04
0,05
0,06
0,08
0,34
0,32
0,29
0,31
0,22
0,24
0,42
0,33
0,27

0,19
0,55
0,54
0,62
0,25
0,20
0,16
0,18
0,17
0,24
0,43
0,40
0,50
0,49
0,59
0,52
0,51
0,43
0,46

0,62 
0,62 
0,63 
0,79 
0,32 
0,58 
0,50 
0,45 
0,50 
0,63 
0,52 
0,71 
0,62 
0,64 
0,64 
0,55 
0,76 
0,65 
0,72 

10,4
3,6
7,0
8,9
3,7
10,8
12,8
9,5
7,9
7,9
1,5
2,2
2,1
2,1
2,9
2,3
1,8
2,0
2,6

* DE Older age groups compared because of later graduation 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Table 1535 shows that: 

•  The probability of someone whose father had low education attaining a university degree 
or  the  equivalent  has  tended  to  increase  over  time  in  most  Member  States,  but  this  also 
reflects the general rise in participation in tertiary education.  

•  More relevantly, the chance of a person whose father had only basic schooling completing 
tertiary  education  relative  to  someone  whose  father  had  tertiary  education  has  risen  over 
the long term in 17 of the 24 EU Member States for which data are available. 

•  In three Member States — Estonia, Hungary and Slovakia — however, it has fallen, in the 
sense that the odds ratio of a person whose father was a university graduate attaining such 
a qualification relative to someone whose father had only basic schooling has increased. 

In  Germany  and  Sweden,  the  odds  ratio  has  remained  much  the  same,  while  in  the  Czech 
Republic  and  Lithuania  it  is  difficult  to  determine  the  direction  of  change  since  the  figures 
fluctuate between the three age groups.  

The link between the education level of mothers and their children 

Partly because there is a relatively close correlation between the education attainment level of 
fathers and mothers, the education level of men and women is also closely linked to that of 
their mother as well as of their father. 

35 

Because young people in Germany tend to graduate from university at a later age than in other countries 
and  a  significant  number  of  those  aged  25-34  are,  therefore,  still  in  the  process  of  completing  their 
tertiary level programme, the age groups compared in this case are, therefore, 35-44, 45-54 and 55-64. 

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The odds ratio of someone having tertiary education if their mother had this level of education 
as compared with only basic schooling is highest in the same countries where the odds ratio in 
respect  of  their  father’s  education  is  highest  —  i.e.  the  Czech  Republic,  Hungary,  Poland, 
Slovenia, Slovakia, Italy and Portugal. Equally, the countries where the odds ratio is lowest in 
terms  of  the  education  of  fathers  is  also  lowest  where  the  criterion  is  the  mother  —  i.e. 
Germany, Finland, the UK, Estonia, Sweden and the Netherlands. Moreover, the influence of 
the  education  level  of  mothers  on  that  of  their  children  seems  to  be  much  the  same  for 
daughters as for sons (Table 16). 

Table  16  Probability  of  attaining  High  education  of  men  and women  aged  25-65  by  education 
level of mother 

Highest education attained 
by mother 

Odds 
ratio 

Low  Medium

High 

High/ 
Low 

Country 

Mother 
not 
present 

CZ 
PL 
SI 
HU 
IT 
SK 
PT 
LV 
LU 
AT 
EL 
LT 
CY 
IE 
EU-25 
FR 
ES 
BE 
EE 
NL 
SE 
DK 
UK 
FI 
DE 

0,06 
0,08 
0,07 
0,13 
0,07 
0,13 
0,08 
0,11 
0,13 
0,16 
0,15 
0,10 
0,15 
- 
0,14 
0,06 
0,18 
0,20 
0,15 
0,23 
0,22 
- 
- 
0,20 
0,22 

0,06
0,08
0,06
0,08
0,10
0,10
0,12
0,11
0,17
0,14
0,17
0,17
0,22
0,23
0,20
0,22
0,25
0,27
0,21
0,28
0,26
0,23
0,31
0,29
0,34

0,17
0,28
0,25
0,27
0,42
0,24
0,48
0,27
0,45
0,34
0,50
0,34
0,61
0,63
0,39
0,56
0,61
0,61
0,34
0,54
0,51
0,35
0,59
0,44
0,42

0,57
0,73
0,48
0,63
0,63
0,59
0,67
0,56
0,86
0,68
0,71
0,64
0,83
0,77
0,68
0,74
0,76
0,83
0,58
0,72
0,62
0,55
0,71
0,61
0,62

9,9
9,7
7,9
7,8
6,4
5,9
5,7
5,3
5,2
4,9
4,1
3,9
3,8
3,4
3,4
3,3
3,1
3,1
2,8
2,6
2,4
2,4
2,3
2,1
1,8

Odds 
ratio 
High/ 
Mother 
not 
present 
10,0 
8,7 
6,5 
4,9 
9,0 
4,6 
8,4 
5,2 
6,4 
4,1 
4,7 
6,1 
5,5 
- 
4,7 
12,0 
4,2 
4,2 
3,8 
3,2 
2,7 
- 
- 
3,0 
2,9 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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BOX 4 Educational attainment — comparison of results from EU-SILC data with LFS 
data 

A  special  module  of  the  EU  Labour  Force  Survey  in  2000  —  on  the  transition  of  young 
people from education to work — also investigated the links between the education level of 
parents and their children. The results for most countries were similar:  

Comparison of evidence from EU-SILC module, 2005 and LFS module, 2000 

Odds ratio: Those with tertiary 
education with father with same 
level relative to those with father 
with low education

HU
SI
IT
SK
EL
AT
FR
ES
BE
SE
FI

EU-SILC
9,1
8,0
7,7
6,7
4,1
3,6
3,3
3,3
3,2
2,6
2,2

LFS
16,6
2,3
6,9
7,6
2,4
2,9
2,4
2,0
3,0
1,9
1,1

Note: The results reported for the LFS module in the Eurostat database state only that the calculation is based on the parent’s 
education level without specifying whether this refers to the father or mother or both. The EU-SILC results shown relate to the 
father’s education level but they would be much the same if the mother’s education level was taken instead. 

The main exception is Slovenia, which is reported by the LFS module to have a relatively low 
odds  ratio  but  by  the  EU-SILC  to  have  a  relatively  high  one.  Greece  is  also  recorded  as 
having  a  lower  odds  ratio  by  the  LFS  than  by  the  EU-SILC,  as  is  Finland  (where  the  LFS 
indicated  an  odds  ratio  of  close  to  1  rather  than  2).  On  the  other  hand,  the  odds  ratio  in 
Hungary was reported by the LFS to be substantially higher than calculated  from  EU-SILC 
data, though since the relative number with low education is small, a minor difference in this 
can lead to a big difference in the odds ratio. 

Occupational links 

The  same  kind  of  analysis  can  be  made  for  occupations.  The  EU-SILC  module  makes  it 
possible to examine the closeness of the link between the occupations of men and women and 
those of their parents. This is as relevant as the link between education levels since the kind of 
job  which  a  person  has  tends  to  determine  both  their  status  in  society  and  their  level  of 
income and living standards.  

There  tends  to  be  a  relatively  close  correlation  between  education  levels  and  occupations, 
implying that the conclusions reached above as regards the link between education levels of 
children  and  their  parents  should  also  apply  to  occupations.  However,  the  correlation  is  not 
perfect. It is therefore of interest to examine the occupation link separately, not least because 
it gives a guide to the relative earnings of the parents and, accordingly, to the income of the 
household when the people surveyed were young. The focus is on the influence of the father’s 
occupation  rather  than  the  mother’s  since  in  many  countries  a  substantial  proportion  of  the 

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70 

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mothers  were  not  in  paid  employment  during  the  period  when  the  people  surveyed  were 
young teenagers (which is up to some 50 years ago).  

The  focus  is  also  on  the  highest  level  of  occupation  in  the  ISCO  classification,  that  of 
managers, professionals and technicians, which are considered together as one group, both to 
allow for differences in the classification of particular jobs between countries and for the fact 
that  earnings  levels  in  many  cases  do  not  differ  markedly  between  the  various  sub-groups. 
The link between the probability of someone being employed in these jobs and the occupation 
of  their  fathers  is  examined,  first,  for  men  and  women  aged  25-64  taken  together  and 
secondly, for men and women considered separately. 

The occupations of men and women and those of their fathers 

The  proportion  of  those  aged  25-64  who  are  employed  as  managers,  professionals  and 
technicians  varied  markedly  across  the  EU,  from  25 %  in  Portugal  to  51-52 %  in  Germany 
and the Netherlands. The proportion in this occupational group whose father was also in such 
a  job,  however,  varies  much  less  widely.  In  all  Member  States  without  exception,  the 
proportion is over 50 %, and in 15 of the 24 countries for which data are available over 60 % 
(Table 17). There is, moreover, in all Member States a much greater chance of someone being 
employed  in  such  jobs  if  their  father  had  the  same  kind  of  job  than  if  he  had  a  lower-level 
occupation, though the scale of this chance differs significantly between countries. 

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Table 17 Probability of having jobs as manager, professional or technician for women and men 
aged 25-65 by education level of father 

Country 

PT 
PL 
ES 
CY 
HU 
CZ 
SI 
LT 
LU 
EL 
LV 
IT 
FR 
AT 
EU-25 
SK 
BE 
EE 
SE 
DK 
FI 
IE 
UK 
NL 
DE 

Father 
not 
present 
0,22 
0,21 
0,22 
0,18 
0,28 
0,29 
0,29 
0,23 
0,35 
0,26 
0,23 
0,29 
0,25 
0,27 
0,31 
0,32 
0,21 
0,30 
0,34 
- 
0,38 
- 
- 
0,44 
0,41 

Main occupation of father 

Man+Prof+Tech Clerks

Sales 
+Serv

Skilled 
manual 

Unskilled 
manual 

Total 

Odds 
ratio 

0,61
0,63
0,54
0,61
0,63
0,62
0,63
0,60
0,67
0,54
0,55
0,61
0,62
0,51
0,62
0,60
0,57
0,58
0,60
0,62
0,65
0,52
0,61
0,65
0,65

0,43
0,39
0,41
0,50
0,43
0,36
0,38
0,40
0,56
0,47
0,39
0,46
0,49
0,41
0,50
0,50
0,43
0,38
0,47
0,50
0,53
0,52
0,54
0,56
0,56

0,38
0,31
0,29
0,36
0,35
0,30
0,40
0,39
0,35
0,32
0,34
0,37
0,37
0,27
0,38
0,36
0,39
0,32
0,54
0,45
0,59
0,43
0,38
0,48
0,50

0,19
0,28
0,23
0,25
0,28
0,28
0,31
0,29
0,30
0,29
0,29
0,31
0,32
0,26
0,33
0,32
0,28
0,34
0,28
0,37
0,41
0,34
0,30
0,42
0,44

0,14 
0,16 
0,15 
0,19 
0,18 
0,23 
0,18 
0,26 
0,26 
0,20 
0,24 
0,24 
0,23 
0,19 
0,23 
0,26 
0,24 
0,27 
0,32 
0,31 
0,30 
0,19 
0,27 
0,40 
0,40 

0,25 
0,29 
0,26 
0,29 
0,32 
0,35 
0,33 
0,32 
0,42 
0,30 
0,31 
0,36 
0,39 
0,30 
0,38 
0,37 
0,38 
0,37 
0,39 
0,44 
0,44 
0,40 
0,42 
0,52 
0,51 

3,07
2,71
2,57
2,46
2,41
2,25
2,24
2,22
2,12
2,12
2,07
2,06
2,05
2,05
1,99
1,93
1,93
1,84
1,84
1,73
1,70
1,66
1,62
1,48
1,46

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

The odds ratio, therefore, is around two in the EU as a whole, signifying that someone whose 
father had a job in this occupational group was over twice as likely as other people to have 
such a job themselves.  

The countries in which the odds ratio is highest include many of the new Member States — 
Poland,  Cyprus,  Hungary,  the  Czech  Republic,  Slovenia  and  Latvia.  They  also  include 
Portugal, Spain, Luxembourg and Greece. Most of the countries — the exception is Spain — 
are  also  those  where  the  odds  ratio  for  education  levels  was  high.  Similarly,  the  countries 
where  the  odds  ratio  is  lowest  —  Germany,  the  Netherlands,  the  UK,  Ireland,  Finland  and 
Denmark — and where there is a greater chance than elsewhere in the EU of securing a high-
level job without having a father with such a job, are also the countries where the odds ratio 
for education levels was lowest. Nevertheless, even in these countries having a father with a 
high-level job significantly increases the chances of also having this kind of job (i.e. they are 
around 50 % higher or more).  

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The occupations of fathers, sons and daughters 

The father’s occupation has a significant influence on the kind of job that both the sons and 
daughters do, though there is some tendency for the influence to be greater in respect of sons 
than daughters (Tables 18 and 19).  

Table 18 Probability of having jobs as manager, professional or technician for men aged 25-65 
by education level of father 

Country 

PL 
PT 
ES 
LV 
HU 
CZ 
LT 
SI 
CY 
EL 
IT 
AT 
SK 
EU-25 
EE 
LU 
FR 
BE 
SE 
DK 
FI 
IE 
NL 
UK 
DE 

Father 
not 
present 
0,15 
0,24 
0,26 
0,17 
0,27 
0,22 
0,18 
0,25 
0,25 
0,21 
0,28 
0,30 
0,27 
0,30 
0,26 
0,34 
0,29 
0,23 
0,34 
- 
0,39 
- 
0,44 
- 
0,39 

Main occupation of father 

Man+Prof+Tech Clerks 

Sales 
+Serv 

Skilled 
manual

Unskilled 
manual 

Total 

Odds 
ratio 

0,58
0,66
0,59
0,50
0,58
0,61
0,53
0,61
0,68
0,55
0,62
0,61
0,53
0,64
0,51
0,74
0,66
0,60
0,61
0,62
0,64
0,60
0,71
0,62
0,67

0,35
0,42
0,46
0,28
0,37
0,33
0,37
0,40
0,58
0,48
0,43
0,50
0,46
0,52
0,21
0,65
0,52
0,49
0,60
0,54
0,62
0,63
0,58
0,59
0,60

0,29
0,41
0,30
0,22
0,35
0,22
0,31
0,34
0,36
0,30
0,37
0,30
0,26
0,40
0,21
0,47
0,46
0,35
0,65
0,46
0,66
0,50
0,51
0,43
0,59

0,21
0,20
0,23
0,20
0,23
0,24
0,22
0,27
0,29
0,26
0,29
0,32
0,25
0,31
0,26
0,36
0,35
0,30
0,29
0,36
0,40
0,39
0,44
0,28
0,44

0,12 
0,15 
0,15 
0,18 
0,14 
0,22 
0,18 
0,17 
0,23 
0,20 
0,24 
0,21 
0,21 
0,22 
0,18 
0,25 
0,25 
0,24 
0,38 
0,30 
0,31 
0,23 
0,43 
0,30 
0,38 

0,23 
0,27 
0,28 
0,24 
0,28 
0,32 
0,25 
0,30 
0,32 
0,29 
0,34 
0,35 
0,31 
0,38 
0,30 
0,47 
0,42 
0,39 
0,41 
0,44 
0,44 
0,47 
0,56 
0,45 
0,52 

3,25
3,20
2,76
2,65
2,63
2,56
2,55
2,44
2,43
2,28
2,21
2,13
2,10
2,08
2,07
2,06
1,95
1,95
1,76
1,74
1,69
1,65
1,57
1,52
1,50

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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Table  19  Probability  of  having  jobs  as  manager,  professional  or  technician  for  women  aged  
25-65 by education level of father 

Country 

PL 
PT 
ES 
LV 
HU 
CZ 
LT 
SI 
CY 
EL 
IT 
AT 
SK 
EU-25 
EE 
LU 
FR 
BE 
SE 
DK 
FI 
IE 
NL 
UK 
DE 

Father 
not 
present 
0,26 
0,21 
0,17 
0,28 
0,30 
0,35 
0,28 
0,33 
0,11 
0,31 
0,29 
0,23 
0,35 
0,33 
0,33 
0,35 
0,21 
0,19 
0,33 
- 
0,38 

- 

- 

0,45 

0,44 

Main occupation of father 

Man+Prof+Tech Clerks

Sales 
+Serv

Skilled 
manual 

Unskilled 
manual 

Total 

Odds 
ratio 

0,67
0,56
0,48
0,59
0,68
0,63
0,67
0,64
0,54
0,53
0,60
0,37
0,66
0,60
0,63
0,60
0,59
0,54
0,59
0,63
0,66
0,45
0,58
0,60
0,64

0,43
0,43
0,35
0,52
0,49
0,40
0,43
0,36
0,44
0,46
0,50
0,30
0,54
0,47
0,53
0,47
0,46
0,37
0,38
0,46
0,45
0,46
0,55
0,49
0,52

0,34
0,35
0,27
0,46
0,35
0,39
0,47
0,46
0,35
0,35
0,36
0,23
0,43
0,35
0,41
0,18
0,28
0,44
0,42
0,44
0,53
0,36
0,43
0,34
0,41

0,34
0,19
0,22
0,37
0,34
0,31
0,35
0,35
0,21
0,33
0,34
0,18
0,38
0,34
0,40
0,24
0,29
0,27
0,27
0,37
0,43
0,30
0,40
0,31
0,44

0,21 
0,13 
0,16 
0,29 
0,21 
0,24 
0,32 
0,19 
0,15 
0,20 
0,26 
0,17 
0,30 
0,24 
0,34 
0,26 
0,20 
0,23 
0,26 
0,33 
0,30 
0,16 
0,38 
0,24 
0,43 

0,34 
0,24 
0,25 
0,37 
0,36 
0,38 
0,38 
0,36 
0,25 
0,32 
0,37 
0,23 
0,42 
0,38 
0,43 
0,37 
0,35 
0,36 
0,37 
0,45 
0,44 
0,34 
0,49 
0,40 
0,51 

2,37
2,91
2,35
1,78
2,26
2,03
2,03
2,06
2,57
1,95
1,90
1,90
1,83
1,90
1,70
2,24
2,18
1,92
1,96
1,72
1,72
1,63
1,36
1,74
1,44

Note: countries are ranked in the same order as in Table 18 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

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This  is  the  case  both  across  the  EU  as  a  whole  and  in  most  countries.  The  exceptions  are 
Cyprus,  Luxembourg,  France,  Sweden  and  the  UK,  where  the  influence  on  daughters  is 
greater than the influence on sons — though in each case the difference is relatively small — 
and Belgium, Denmark, Finland, Ireland and Germany, where the influence is much the same. 
The influence on sons as compared with daughters is particularly large in Poland, Latvia, the 
Czech Republic and Lithuania. Indeed, although there are a few exceptions, the influence of 
the  father’s  occupation  on  the  jobs  held  by  men  in  particular  tends  to  be  larger  in  the  new 
Member States and in the southern countries than in the rest of the EU. 

Concluding remarks 

It is evident that the education level attained by both men and women is very much influenced 
by that of the father in all EU Member States. At the same time, the influence of the mother’s 
education  level  is  no  less  significant,  which  partly  reflects  the  relatively  close  correlation 
between  the  education  levels  of  mothers  and  fathers,  making  it  difficult  to  disentangle  the 
relative importance of one as opposed to the other.  

There  are,  however,  marked  differences  in  the  scale  of  the  influence  between  countries 
whichever parent is considered. It seems particularly large in a number of the new Member 
States — the Czech Republic, Hungary, Poland, Slovenia, Slovakia and Cyprus — and also 
relatively  significant  in  Greece,  Italy  and  Portugal.  On  the  other  hand,  the  influence  of  the 
parent’s  level  of  education  on  the  education  level  of  their  children  appears  to  be  smaller  in 
Finland, Germany and Estonia, in particular, than in other countries 

At the same time, the influence of parents’ education levels on that of their children seems to 
have diminished over the long term in most countries, though this is less clear-cut in a number 
of  Member  States  where  the  influence  seems  to  be  strongest  —  in  the  Czech  Republic, 
Hungary and Poland, in particular. 

It is equally true that both men and women have a significantly better chance in all countries 
of obtaining a high-level job, as a manager, professional or technician, if their father had the 
same kind of job than if they were in any other occupation. In most countries, however, the 
influence on sons is greater than on daughters, especially in the new Member States and the 
southern EU countries. 

3.2. 

Children from a migration background and equal opportunities 

Evidence  suggests  that  children  face  a  higher  risk  of  poverty  than  adults  in  many  EU 
countries. There is also evidence that ethnic minorities and people with migrant background 
face a greater risk of poverty and thus a greater threat of social exclusion. A combination of 
these characteristics can of course add up to a greater risk of social exclusion. The focus in 
this section is therefore on those falling into both groups, namely children in migrant families 
or ethnic minority families.  

The  available  data  limit  the  possibility  to  analyse  the  situation  of  these  groups,  and  in  EU-
SILC  neither  ethnic  minorities  nor  migrant  background  are  explicitly  reported.  Instead,  a 
proxy is used in the analysis which compares children of parents who were born outside the 
EU  with  children  of  parents  born  in  the  EU  country  in  which  they  live.  For  ease  of 
presentation, children whose parents were born outside the EU are termed ‘migrant’ children 
and  those  whose  parents  were  born  in  the  country  of  residence  ‘home’  children.  For  the 

EN 

75 

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situation  of  children  in  ethnic  minority  families  the  Social  Situation  Report  relates  findings 
from a national study on the income situation among some ethnic groups in the UK.  

First, however, an indication is given of the relative importance of ethnic diversity across the 
EU, of the upward trend, and of the extent to which it differs across countries. 

Increasing ethnic diversity in the EU 

A significant number of people from different ethnic backgrounds live in the EU, and nearly 
all Member States are home to a wide diversity of people. Moreover, this ethnic diversity is 
tending  to  increase  in  most  parts  of  the  EU  as  a  result  of  continuing  inward  migration  at  a 
relatively  high  rate.  Over  the  6-year  period  2000-2005  net  inward  migration  is  estimated  to 
have added, on average, almost 0.3 % a year to the EU population, and was the main reason 
for population growth over this period (Figure 15, which is based on OECD estimates for 19 
EU countries: the 25 which were members in 2005 less Cyprus, Malta, the three Baltic States 
and Slovenia, the inclusion of which would change the picture only marginally, if at all).  

Figure 15 Net migration into 19 countries of the EU, 1970-2005 

n
o
i
t
a
l
u
p
o
p
f
o
%
s
a
s
t
n
a
r
g
M

i

0,45

0,40

0,35

0,30

0,25

0,20

0,15

0,10

0,05

0,00

-0,05

0
7
9
1

1
7
9
1

2
7
9
1

3
7
9
1

4
7
9
1

5
7
9
1

6
7
9
1

7
7
9
1

8
7
9
1

9
7
9
1

0
8
9
1

1
8
9
1

2
8
9
1

3
8
9
1

4
8
9
1

5
8
9
1

6
8
9
1

7
8
9
1

8
8
9
1

9
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

Source: Figures calculated on the basis of OECD Migration Outlook, 2007 
Note: Data only include the 19 EU Member States which are also members of the OECD 

The figures for inward migration, however, give only a very partial insight into the number of 
people  from  different  ethnic  backgrounds  living  in  the  EU,  since  they  simply  record  new 
arrivals.  They  take  no  account,  therefore,  of  the  number  of  migrants  already  resident  in  the 
EU or the descendants of migrants who may have arrived decades ago. The number of such 
people  is  largely  unknown  in  most  EU  countries.  In  view  of  the  sensitive  nature  of  data  on 
ethnicity, only a few Member States routinely collect such information. 

Two proxies can be used to obtain an indication of ethnic diversity in EU Member States: one 
is  citizenship  —  i.e.  the  number  of  people  who  do  not  have  citizenship  of  the  country  in 
which they live or of any other EU Member State — and the other is country of birth.  The 

EN 

76 

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country of birth tends to be more difficult to collect information on, though it is perhaps more 
indicative  of  the  population  from  different  ethnic  backgrounds  than  citizenship,  insofar  as 
citizenship can usually be obtained in most countries after a period of residence. The number 
of people born outside the EU living in Member States will, therefore, tend to be larger than 
the  number  of  non-EU  citizens,  the  more  so  the  quicker  it  is  to  obtain  citizenship  in  the 
country in question. Neither, however, are likely to give anywhere near a full picture of ethnic 
diversity in the EU. 

Nevertheless, there is another measure which could be used to give a fuller picture of ethnic 
diversity  across  the  EU  and  which  largely  avoids  the  problems  associated  with  collecting 
information on ethnic origin. This is the concept of ‘foreign descent’, defined as either being 
born outside the EU or having at least one parent who was born outside the EU, which would 
pick up second as well as first-generation migrants. Data on this concept, however, exist for 
only two Member States, Denmark and the Netherlands. These show that, even if the measure 
is not entirely satisfactory as an indicator of the number of people of different ethnic origin 
living  in  a  country,  since  it  still  leaves  out  of  account  third  or  subsequent-generation 
descendants of migrants, it does represent a significant improvement over country of birth as 
an indicator, and still more over citizenship. In Denmark, therefore, the measures indicate that 
25 %  of  people  of  foreign  descent  were  born  in  the  country  and  in  the  Netherlands,  almost 
50 %. 

The composition of non-nationals in EU countries  

Despite  their  limitations,  data  on  citizenship  provide  the  main  indication  of  the  number  of 
different ethnic groups living in the EU, of the relative importance  of the various groups in 
individual countries and of the way that this differs between countries. They show, first, that 
in all EU Member States, citizens from other parts of the EU and the rest of Europe account 
for most of the people without domestic citizenship; secondly, most of the people with non-
European  citizenship  are  from  relatively  near-by  countries,  e.g.  the  Middle  East  and  North 
Africa;  and,  thirdly,  that  the  relative  importance  of  people  with  citizenship  of  non-EU 
countries varies markedly across the EU, as do the particular countries which they are citizens 
of, partly reflecting colonial and historical links in the past (see pie charts). 

People  with  Turkish  citizenship,  therefore,  account  for  a  relatively  large  proportion  of  non-
nationals  in  Germany  (24 %),  Austria  (18 %),  the  Netherlands  (14 %)  and  Denmark  (11 %) 
but  are  less  important  elsewhere.  Those  from  Morocco  make  up  a  significant  proportion  of 
non-nationals  in  France  (around  15 %)  —  as  do  those  from  Algeria  (also  15 %)  —  Spain 
(14 %), the Netherlands (13 %) and Italy (12 %). However, a far greater number of people of 
North  African  descent  living  in  France  and  Spain  in  particular  are  likely  to  have  acquired 
French or Spanish citizenship. Similarly, in the UK, people with Indian citizenship represent 
some 6 % of non-nationals and from Pakistan, just 3 %; in both cases the number involved is 
likely  to  be  very  much  smaller  than  the  number  of  persons  of  Indian  and  Pakistani  descent 
living in the country. 

EN 

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Figures 16 Foreign population by country of nationality, 2005 

Austria 

18,9

18,7

Serbia & Montenegro

Turkey

Bosnia & Herzegovina

1,4

1,8

1,9

2,5

3,1

8,5

10,2

15,2

Belgium

17,9

Germany

Croatia

Poland

Romania

Macedonia

Hungary

Italy

Other

Italy

France

22,0

21,3

Netherlands

2,0

3,0

3,1

4,1

4,8

22,0

1,9

2,3

2,5

3,1

4,0

5,4

Morocco

Spain

Turkey

Germany

Portugal

Great Britain

Greece

Other

13,4

5,1

9,5

11,7

Bulgaria

Russian Federation

36,8

Ukraine

Greece

Armenia

Macedonia

Turkey

Moldova

Syria

Poland

6,4

6,6

8,9

China (incl Hong Kong)

Other

EN 

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Figures 16 Foreign population by country of nationality, 2005 (continued) 

1,4

1,5

1,6

1,7

2,3

5,8

6,4

46,8

35,7

Czech Republic

16,5

Ukraine

Slovak Republic

30,8

Vietnam

Poland

13,4

18,6

Denmark

11,2

7,2

5,2

5,2

5,1

2,8

3,5

Finland

4,8

4,2

4,1

23,0

Russian Federation

Germany

Bulgaria

Moldova

United States

Serbia & Montenegro

Other

Turkey

Iraq

Bosnia & Herzegovina

Norway

Germany

United Kingdom

Somalia

Sweden

Afghanistan

Iceland

Other

Russian Federation

Estonia

Sweden

Somalia

Serbia & Montenegro

Iraq

United Kingdom

12,9

Germany

China (incl Hong Kong)

7,6

3,1

3,8

4,3

Iran

Other

2,4

2,4

2,4

2,5

EN 

79 

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Figures 16 Foreign population by country of nationality, 2005 (continued) 

24,0

2,0

2,4

2,3

4,7

5,0

41,1

France

17,0

15,4

6,2

6,4

14,6

Portugal

Morocco

Algeria

Turkey

Italy

Spain

Tunisia

United Kingdom &
Northern Ireland
Germany

Belgium

Other

Germany

Turkey

Italy

24,2

Serbia & Montenegro

Greece

Poland

Croatia

7,5

Russian Federation

Austria

7,0

Bosnia & Herzegovina

1,8

2,1

2,4

2,5

3,1

4,0

4,3

Ukraine

Other

Greece

20,8

1,8

1,9

1,9
2,3

2,4

2,8

2,9

2,9

4,7

Albania

Bulgaria

Georgia

Romania

United States

Cyprus

55,6

Russian Federation

United Kingdom

Germany

Ukraine

Other

EN 

80 

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Figures 16 Foreign population by country of nationality, 2005 (continued) 

Hungary

9,7

Ireland

25,7

0,8
0,9
1,2
1,5
1,8
1,9

4,8

4,8

28,3

1,7
1,9
2,0

2,2

2,6

2,8

3,2

4,0

5,1

Italy

13,2

41,8

2,3

2,4

2,4

3,3

3,4

4,7

3,9

Romania

Ukraine

Germany

China (incl Hong
Kong)
Russian Federation

47,0

Vietnam

Poland

United States

Slovak Republic

Bulgaria

Other

United Kingdom &
Northern Ireland
USA

Nigeria

Germany

France

China

Romania

Spain

South Africa

Philippines

Other

Albania

Morocco

Romania

China (incl Hong
Kong)
Ukraine

Philippines

Tunisia

Macedonia

Serbia &
Montenegro
India

Other

46,1

12,3

10,4

EN 

81 

   EN 

 
Figures 16 Foreign population by country of nationality, 2005 (continued) 

Latvia

Russian Federation

Ukraine

Lithuania

Belarus

Estonia

United States

Germany

Armenia

Poland

Stateless

Other

Russian Federation

Stateless

Belarus

Ukraine

Poland

Armenia

Latvia

Kazakhstan

Germany

United States

Other

Portugal

France

Italy

Belgium

Germany

United Kingdom

Netherlands

Spain

Denmark

Sweden

Other

Lithuania

5,6

28,2

16,9

Luxembourg

43,6

37,0

6,6

10,8

0,7

1,1

1,6

2,0

2,5

5,9

9,1

10,6

12,6

EN 

82 

   EN 

 
Figures 16 Foreign population by country of nationality, 2005 (continued) 

43,2

Netherlands

14,4

Turkey

Morocco

Germany

United Kingdom

13,1

Belgium

Italy

Spain

8,2

United States

China (incl Hong Kong)

6,1

2,1

2,1

2,1

2,4

2,6

3,7

France

Other

Poland

Germany

Ukraine

22,9

Russian Federation

30,8

2,0

2,1

2,2

2,3

3,8

4,3

4,7

Portugal

21,8

21,9

Belarus

Vietnam

United States

Bulgaria

France

Armenia

United Kingdom

15,7

9,2

Other

Cape Verde

Brazil

Angola

Guinea Bissau

United Kingdom

Spain

10,4

Germany

France

United States

2,9

3,4

3,5

5,0

6,1

10,3

Sao Tome & Principe

6,7

8,0

Other

EN 

83 

   EN 

 
Figures 16 Foreign population by country of nationality, 2005 (continued) 

Romania

Moldova

Turkey

21,0

China (incl Hong Kong)

Italy

Greece

Syrian Arab Republic

8,4

Ukraine

Iraq

7,3

United States

Lebanon

Other

34,1

2,7

2,9

3,0

3,0

4,7

6,1

Slovakia

25,6

6,8

18,1

Ukraine

Czech Republic

Poland

Hungary

Russian Federation

Germany

Vietnam

United States

Bulgaria

Austria

Other

Bosnia & Herzegovina

Serbia & Montenegro

Croatia

Macedonia , ex Yug

Ukraine

48,2

China (incl Hong
Kong)
Russian Federation

Germany

Italy

Austria

Other

16,2

5,5

6,9

11,1

Slovenia
3,8

2,6

2,8

2,9

3,7

4,5

2,0

9,3

15,4

17,9

EN 

84 

   EN 

 
Figures 16 Foreign population by country of nationality, 2005 (continued) 

Spain

13,7

Morocco

Ecuador

Romania

Colombia

13,3

United Kingdom

35,8

8,5

2,5

2,6

2,6

3,6

4,1

6,1

Sweden

7,3

18,8

Argentina

Germany

Bolivia

Italy

Bulgaria

Other

Finland

Iraq

Norway

Denmark

Germany

8,3

Serbia & Montenegro

Bosnia & Herzegovina

7,4

Poland

United Kingdom

Iran

Other

2,6

3,0

3,0

3,1

3,8

6,5

4,1

United Kingdom

12,5

Ireland

India

United States

Italy

Germany

South Africa

Pakistan

France

Australia

Portugal

Other

   EN 

6,2

4,6

3,6

3,3

3,3

3,2

3,1

2,9

2,8

85 

39,4

54,5

EN 

 
 
Note: Data not available for CY and EE. For FR, 1999; AT, BG and EL: 2001; IE, PL, 2002; PT, 2003; BE, LV, UK, 2004. Data 
on Latvia do not include a group defined as "non-citizens of Latvia".  
Source: OECD 2004/2005. 

BOX 5 Roma 

One  of  the  most  numerous  ethnic  minority  groups  in  the  EU,  and  certainly  in  the  new 
Member States, is the Roma community. Although exact numbers are not known, estimates 
do  exist,  suggesting  that  people  of  Roma  origin  make  up  between  5 %  and  10 %  of  the 
population in Romania, Bulgaria, Slovakia and Hungary, and in these four countries alone 
amount to some 3-4 million people. 

Roma population in the new Member States  

Country 

Roma population 
from Censuses 
(‘000s) a) 

Estimates of Roma 
population 
(‘000s) b) 

Roma population 
as % of total based 
on estimates b) 

RO 

BG 

HU 
SK 

CZ 

535 

371 

190 

90 

12 

1500–2000 

550–800 

520–650 

480–520 

175–200 

7–9 

5–10 

5–8 

8–10 

1.7–2 

Sources:  
a) UNDP 2005, except for Slovakia (UNDP 2002). Census data relate to 2001 for Bulgaria, Czech Republic, Hungary and 
Slovakia and to 2002 for Romania. 
b) Needs Assessment: Roma Education Fund (2005); except Slovakia (UNDP 2002). 

Children in ethnic minority families 

There  are  no  data  available  at  EU  level  to  enable  the  link  between  ethnic  origin  and  the 
income  and  other  circumstances  of  households  to  be  examined.  The  EU-SILC,  however, 
contains  data  which  can  be  used  to  throw  some  light  on  this.  In  particular,  it  includes  two 
questions, one on the country of birth of respondents and the other one on their citizenship. It 
is  therefore  possible  to  distinguish,  within  the  EU-SILC  sample,  those  born  outside  the  EU 
from those who do not have citizenship of an EU Member State — i.e. non-EU nationals.  

It is important to recognise, however, that neither set of data is entirely satisfactory as a proxy 
for  people  belonging  to  ethnic  minority  groups.  A  significant  number  of  these  are  likely  to 
have been born in the EU country in which they live — and may be descendants of people 
who could have moved to the country several generations before — and have citizenship of 
the country in question. Accordingly, although there will be an overlap between each set of 
data  and  ethnic  minorities  properly  defined,  the  overlap  is  by  no  means  complete,  and  its 
extent  is  likely  to  vary  between  countries  depending  on  the  rules  governing  citizenship  and 
the eligibility of migrants to acquire this, as well as to the relative number of first-generation 
migrants  (i.e.  those  born  outside  the  EU)  as  compared  with  second,  third  and  so  on 
generations. The latter will depend partly on the rate of growth of inward migration, but also 
on the proportion of migrants who return home. 

So the two sets of data will tend to vary in terms of how far the results are indicative of the 
relative situation of ethnic minorities in particular countries. The data on non-EU nationals are 

EN 

86 

   EN 

 
 
 
 
likely to reflect more the situation of migrants who have arrived relatively recently and have 
not  yet  qualified  for  citizenship,  while  the  data  on  those  born  outside  the  EU  will  give  a 
stronger picture of those who have been in the EU for a longer period of time. The focus of 
the analysis below is on the latter group, but the results are similar for non-EU nationals. 

Irrespective  of  how  well  the  relative  situation  of  those  born  outside  the  EU  reflects  that  of 
ethnic minorities, the results are interesting in their own right as indicators of the situation of 
migrants in EU Member States. 

There  are  data,  however,  on  ethnic  origin  for  a  few  countries,  and  for  the  UK  at  least  an 
analysis is possible, which is presented below, of the relative situation of children in ethnic 
minority families. These data distinguish children of different ethnic origins, thereby drawing 
attention to the fact that ethnic minorities ought not to be treated as a homogeneous group and 
that the internal differences can be at least as important as those between the group and the 
ethnic majority living in a country. 

The EU-SILC data used in the analysis 

Although the data  on  which the analysis is based  come  from  the  EU-SILC  for  2005,  which 
covers 25 EU Member States, excluding Bulgaria and Romania, the relatively small number 
of people in most of the new Member States born outside the EU means that the sample size 
is  not  large  enough  to  provide  reliable  data  for  these  countries.  Equally,  for  the  other 
countries, it is not possible to distinguish reliably between those born in different parts of the 
world outside the EU — for example, those born in North Africa as opposed to those born in 
India or China — which, as the evidence for the UK demonstrates, is a serious limitation.  

The analysis compares children where both parents were born outside the EU with children of 
parents born in the EU country in which they live. It focuses on the income they have access 
to, income being defined as the disposable income of households, equivalised for differences 
in  their  size  and  composition36.  For  ease  of  presentation,  children  whose  parents  were  born 
outside  the  EU  are  termed  ‘migrant’  children  and  those  whose  parents  were  born  in  the 
country of residence ‘home’ children.  

The risk of poverty among children of parents born outside the EU 

‘Migrant’ children represent around 5-6 % of all children under 16 in the EU, the proportion 
ranging  from  12-13 %  in  Austria  and  Luxembourg  and  8-9 %  in  Belgium  and  the  UK  to 
below 1 % in Portugal, Poland and Slovakia. Such children tend to have both a lower level of 
income and a higher risk of poverty than those of ‘home’ children. This is universally the case 
throughout the EU. 

In 2004, the median income of ‘migrant’ children was less than 80 % of the median income of 
‘home’ children, except for the three new Member States — Estonia, Cyprus and Slovenia — 

36 

It  should  be  noted  that  the  relative  number  of  households  in  which  both  parents  were  born  abroad 
included in the EU-SILC survey may well understate the true number in the countries concerned to the 
extent that the sampling method used does not include these characteristics when seeking to ensure that 
the households surveyed are representative of the population as a whole. In practice, since the sample 
tends to be selected from household registers which are unlikely to be fully up to date, they  may not 
include recent arrivals. Added to this, there may be a natural reluctance among migrants to be involved 
in the survey. 

EN 

87 

   EN 

 
                                                 
for which data can be analysed (in the sense that the number born outside the EU included in 
the sample is large enough to be representative) (Figure 17). In Belgium and Luxembourg the 
median income of such children was less than 60 % of the income of ‘home’ children. 

Figure  17  Median  income  of  children  of  parents  born  outside  the  EU  relative  to  that  of  those 
with parents born in the country of residence, 2004 

% median income

100

80

60

40

20

0

100

80

60

40

20

0

BE

DK

DE

EE

IE

GR

ES

FR

IT

CY

LU

NL

AT

SI

FI

SE

UK

EU25

Source: EU-SILC, 2005 

Equally, in all countries without exception, the proportion of children with income below the 
at-risk-of-poverty  threshold  —  defined  as  below  60 %  of  the  national  median  —  was  much 
larger  among  ‘migrant’  children  than  among  ‘home’  children  (Figure  18).  Apart  from  in 
Estonia and (marginally) in Slovenia, moreover, the difference was greater than 10 percentage 
points. In Belgium, some 64 % of ‘migrant’ children had levels of equivalised income below 
the at-risk-of-poverty threshold, in Spain, the Netherlands and Luxembourg over 50 %, while 
in Ireland, Greece, France and the UK, the figure was over 40 %. 

Figure  18  Proportion  of  children  with  income  below  the  at-risk-of-poverty  threshold,  parents 
born outside the EU and parents born in the country of residence, 2004 

% of children of parents born ouside the EU/in country of residence 

64,3

60

50

40

30

20

10

0

BE

DK

DE

EE

IE

GR

ES

FR

IT

born outside the EU

CY

AT
born in country of residence

NL

LU

60

50

40

30

20

10

0

SI

FI

SE

UK

EU25

EN 

88 

   EN 

 
 
 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

These figures imply, together with the relatively large number of ‘migrant’ children in some 
cases, that such children account for a significant proportion of all children at risk of poverty 
in a number of EU Member States. In the EU as whole, therefore, ‘migrant’ children make up 
11-12 %  of  all  children  at  risk  of  poverty,  while  in  France,  they  make  up  around  23 %,  in 
Austria and Sweden 25-28 %, in Belgium almost a third and in Luxembourg just over a third. 

The risk of poverty among households with and without children 

The presence of children in the household, or family size, does not seem to be the main reason 
for the high risk of poverty among those whose parents were born outside the EU, although it 
does seem to be a contributory factor in a number of countries. People born outside the EU 
living in households without children also tend to be exposed to a higher risk of poverty than 
those living in childless households where all members were born in the country of residence. 
This is the case in all Member States without exception (Table 20). 

The  difference  was  particularly  large  (20  percentage  points  or  more)  in  Belgium,  France, 
Luxembourg  and  the  three  Nordic  Member  States.  In  Finland,  the  gap  at  risk  of  poverty 
between  those  born  in  the  country  of  residence  and  those  born  abroad  was  greater  in 
households without children than for households with children. However, Finland and Estonia 
are the only EU countries where this was the case. In all other Member States, therefore, the 
presence  of  children  in  households  seems  to  increase  the  risk  of  poverty  among  those  born 
outside the EU relative to those born in the country, in many cases markedly so (in Belgium, 
Ireland, Greece, Spain, Cyprus, the Netherlands and the UK, especially). 

Table  20  Risk  of  poverty  of  those  in  households  with  and  without  children  by  place  of  birth, 
2004 (% with income below the at-risk-of-poverty threshold) 

Those born in country 
of residence 

Those born outside 
EU 

 % point difference: born 
outside EU minus born in 
country 

BE 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
IT 
CY 
LU 
NL 
AT 
SI 
FI 
SE 
UK 
EU-25 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Without 
children 
12 
15 
14 
19 
21 
19 
19 
12 
16 
27 
5 
8 
10 
16 
14 
10 
18 
15 

With 
children
12
8
12
21
20
18
22
11
23
11
9
13
12
11
9
6
21
18

With 
children
64
39
33
26
40
43
53
41
33
30
53
51
35
19
30
28
40
40

Without 
children With children 
53 
31 
20 
5 
20 
25 
31 
30 
10 
18 
44 
38 
23 
9 
21 
21 
20 
23 

37
42
24
25
28
23
21
32
21
33
34
16
29
23
45
30
26
25

Without 
children
25
28
10
6
7
4
2
21
6
6
29
8
19
7
31
20
8
10

EN 

89 

   EN 

 
  
  
The household situation of ‘migrant’ children 

The  relatively  high  risk  of  poverty  among  migrant  children  might  be  due  to  their  specific 
household  circumstances,  to  their  coming  from  families  with  large  numbers  of  children  or, 
alternatively, being brought up by a lone parent. To throw some light on this, the household 
circumstances of such children can be compared with  those of children whose  parents  were 
born in the country in which they live. 

In most Member States, the household circumstances of ‘migrant’ children differ from those 
of ‘home’ children in that more of them either live with a single parent or in families with a 
large number of children or, in some cases, both. In the EU as a whole, therefore, there are 
both a higher proportion of ‘migrant’ children being brought up by a single parent (21 % as 
opposed to 12 %) and a higher proportion living in families with three or more children (30 % 
as opposed to 21 %) (Table 21). In some Member States, ‘migrant’ children are much more 
likely to live with a single parent (almost invariably their mother) than ‘home’ children, which 
is the case in Cyprus, the Netherlands and the UK. In others, they are far more likely to be one 
of three or more children, as in Belgium, Denmark, Ireland, Spain, Luxembourg and Austria. 
In  yet  others,  they  are  more  likely  to  be  living  in  both  types  of  household  than  ‘home’ 
children,  which  is  the  case  in  Germany,  France  and  Finland.  In  Greece,  Italy,  Slovenia  and 
Sweden, on the other hand, there is not much difference in these respects between ‘migrant’ 
and ‘home’ children. 

In  all  of  these  countries,  around  half  or  more  (over  65 %  in  Denmark,  Germany  and 
Luxembourg) of the children below the at-risk-of-poverty threshold with parents born outside 
the  EU  lived  in  households  with  at  least  three  children,  which  was  also  the  case  in  the 
Netherlands,  while  in  Ireland  and  France,  the  proportion  was  over  40 %.  By  contrast,  for 
children with at-risk-of-poverty-level income whose parents were born locally, the proportion 
was over 40 % in only two countries (the Netherlands and Finland) and below 30 % in all but 
another two (Ireland and Cyprus). 

EN 

90 

   EN 

 
Table 21 Children by place of parents’ birth and household type, 2004  

 % Division of children between each category

Parents born in country of residence 
3 or 
more 
adults 
with 
children 

2 
adults, 
3 
children 

2 
adults, 
1 or 2 
children 

Lone 
parent 

Parents born outside the EU 

Lone 
parent 

2 
adults, 
1 or 2 
children 

2 
adults, 
3 
children 

3 or 
more 
adults 
with 
children 

BE 
DK 
DE 
IE 
EL 
ES 
FR 
IT 
CY 
LU 
NL 
AT 
SI 
FI 
SE 
UK 
EU-25 

50 
56 
54 
40 
84 
68 
64 
68 
61 
58 
56 
54 
57 
51 
52 
49 
58 
Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

14 
16 
20 
15 
4 
4 
11 
6 
5 
7 
9 
10 
6 
12 
18 
26 
12 

6
2
4
13
6
13
3
11
8
8
3
13
20
3
2
5
9

31
25
22
32
6
15
22
15
27
27
33
22
18
34
28
20
21

14
15
31
20
7
6
19
8
12
9
20
3
10
28
21
38
21

25
34
32
35
73
36
40
62
62
31
39
48
74
26
43
29
40

50 
45 
34 
41 
8 
30 
38 
17 
5 
46 
38 
38 
10 
43 
34 
24 
30 

11
6
4
4
12
28
3
13
22
14
2
10
6
3
2
9
9

There  are  a  number  of  countries  where  household  circumstances  are  much  the  same  for 
children  whose  parents  were  born  outside  the  EU  and  where  the  parents  were  born  locally. 
This  is  the  case  in  Italy  and  the  UK  and  to  a  lesser  extent  in  Greece.  In  these  countries, 
therefore, differences in household circumstances do not seem to be a significant poverty-risk 
factor. 

Children whose parents were born abroad and household work intensity 

In 15 of the 17 Member States in which the number of people born outside the EU is large 
enough  for  the  data  to  be  meaningful  —  i.e.  all  except  Greece  and  Luxembourg  —  the 
proportion  of  children  living  in  households  in  which  no-one  was  working  was  larger  for 
‘migrant’ children than for ‘home’ children (Figure 19). Moreover, in all the countries apart 
from Estonia, the work intensity of the households in which they lived was less, on average, 
than those in which ‘home’ children lived37.  

In 12 of the 17 countries, therefore, the work intensity of the households of ‘migrant’ children 
was  less  than  one  (i.e.  signalling  that  not  everyone  of  working  age  was  in  employment 
throughout the year) for over 60 % of such children — in Belgium, Ireland and Finland, for 

37 

Work  intensity  is  measured  as  the  number  of  people  of  working  age  in  employment  in  a  household, 
weighted by the relative number of months during the year in which they worked (with a weight of one 
for those who worked throughout the year and a weight of 0.5 if they worked for 6 months), relative to 
the total number of working age in the household. No account I s taken of whether someone works part-
time or full-time, in the sense that both have a weight of one. 

EN 

91 

   EN 

 
 
 
 
 
                                                 
over 80 % of children. In stark contrast, the majority of ‘home’ children lived in households 
with a work intensity of one.  

The relatively low level of employment among people born outside the EU as compared with 
those born inside therefore seems to be a significant factor underlying the relatively high risk 
of poverty among their children. 

Figure  19  Children  of  parents  born  outside  the  EU  and  in  country  of  residence  by  work 
intensity (WI) of households in which they live, 2004 

% of children of parents born ouside the EU/in country of residence 

100

80

60

40

20

0

100

80

60

40

20

0

BE

DK

DE

EE

IE

G

ES

FR

IT

CY

LU

NL

AT

SI

FI

SE

UK

EU

left bar: born outside the EU; right bar: born in country of residence

WI=0

0<WI<1 WI=1

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

Children at risk of poverty and household work intensity 

The  issue  can  be  further  investigated  by  examining  the  work  intensity  of  the  households  in 
which ‘migrant’ children at risk of poverty live. The picture which emerges is by no means 
common across countries, especially as compared with the work intensity of similarly at-risk 
households of ‘home’ children. 

The  proportion  of  ‘migrant’  children  whose  income  was  below  the  at-risk-of-poverty 
threshold  in  2004  and  who  lived  in  households  where  no-one  was  working  varies  widely 
across the EU. In Ireland, the proportion was some 78 %, in Germany, the  Netherlands  and 
Finland  55-60 %,  and  in  Belgium  and  Sweden  45-50 %  (Table  22).  In  these  countries, 
therefore, the risk of poverty affecting these children seems to be attributable to a large extent 
to  a  lack  of  income  from  employment.  In  Belgium  and  Sweden,  moreover,  as  well  as  in 
Finland, a significant proportion of migrant children lived in households where, even though 
someone  was  working,  the  work  intensity  index  was  less  than  0.5  (signifying  that  less  than 
half the people of working age were in employment throughout the year).  

In both Ireland and Belgium, the corresponding proportion for ‘home’ children was also over 
a  half,  suggesting  perhaps  that  lack  of  employment  income  was  also  a  major  cause  of  low 
income among this group as well, whereas in the other countries, a much smaller proportion 
of these children lived in workless households. 

At the same time, in other countries (in 9 of the 17), a low level of work intensity does not 
seem to be a major explanation of the low income of ‘migrant’ children — as in the case of 

EN 

92 

   EN 

 
 
‘home’ children. In Greece and Spain less than 20 % of ‘migrant’ children with income below 
the  threshold  lived  in  households  with  a  work  intensity  of  less  than  0.5.  In  Italy,  Cyprus, 
Luxembourg  and  the  UK,  the  proportion  was  under  30 %,  in  Austria,  France  and  Denmark 
30-35 %. 

Table  22  Children  below  the  at-risk-of-poverty  threshold  by  place  of  parents’  birth  and 
household work intensity, 2004 

Parents born in country of residence 
Work intensity 

 % Division of children between each category 
Parents born outside the EU 
Work intensity 

BE 
DK 
DE 
EE 
IE 
EL 
ES 
FR 
IT 
CY 
LU 
NL 
AT 
SI 
FI 
SE 
UK 
EU-
25 

0 

55 
44 
35 
39 
50 
14 
10 
24 
19 
21 
9 
17 
16 
25 
29 
21 
14 

22 

0-0.5 
5 
12 
2 
15 
16 
13 
15 
13 
17 
9 
11 
6 
10 
18 
16 
11 
3 

0.5-1 
23 
24 
12 
27 
25 
54 
58 
43 
55 
62 
47 
46 
47 
40 
40 
26 
16 

13 

40 

1 

0 

0-0.5 

0.5-1 

1 

17 
20 
51 
20 
8 
19 
17 
20 
10 
8 
33 
31 
27 
18 
16 
42 
67 

25 

46 
30 
59 
31 
78 
3 
9 
21 
16 
3 
4 
57 
15 
41 
58 
46 
17 

26 

27 
5 
8 
17 
3 
7 
10 
12 
11 
25 
20 
2 
15 
0 
24 
18 
10 

12 

23 
57 
33 
13 
19 
79 
65 
47 
63 
39 
41 
25 
67 
43 
17 
25 
10 

41 

4 
8 
0 
38 
0 
11 
16 
20 
10 
32 
36 
16 
2 
16 
0 
11 
62 

21 

Source: Eurostat – EU-SILC Users' Data Base, version 27 June 2007. 

In  most  of  these  countries,  however  —  all  except  Cyprus,  Luxembourg  and  the  UK  —  the 
proportion of ‘migrant’ children with income below the threshold living in households with a 
work intensity of one (all members of working age in employment) was relatively small, only 
20 %  or  less.  This  was  much  the  same  as  in  households  with  children  whose  parents  were 
born locally.  

The implication is that the chances of having income below the threshold are relatively small 
for children living in households where both parents are working. A further implication is that 
having  only  one  parent  in  work  significantly  raises  the  risk  of  poverty  for  children  —  of 
parents born inside the EU as well as outside. However, employment alone is not sufficient to 
protect against the risk of poverty. In the UK, well over 60 % of children of both backgrounds 
with  income  below  the  threshold  live  in  households  where  everyone  is  working  (though  it 
should be noted that many of the parents concerned might be bringing up their children alone 
or working part-time). 

Ethnic minorities and child poverty risks in the UK 

Ethnic  minorities  are  far  from  being  a  homogeneous  group  with  similar  characteristics  and 
facing the same kinds of problem. In practice, the term covers a number of different sections 
of the population with varying legal rights and in differing circumstances depending in part on 

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whether or not they have citizenship of the country in which they live and the time they have 
been resident there. In some cases, the people concerned may be newly arrived migrants; in 
others, they may be the descendants of people who moved to the country several generations 
before or even many centuries before, as in the case of the Roma in many parts of Europe.  

Circumstances can vary, moreover, even between ethnic groups who have been in the country 
for  similar  periods  of  time,  depending  on,  for  instance,  their  cultural  and  social  ties  to  the 
country  in  question  or  the  colour  of  their  skin,  as  well  as,  of  course,  between  individuals 
within groups, according to their education level, their familiarity with the local language and 
social norms, the job they do and so on.  

As emphasised at the outset, however, there is a lack of data at EU level and in most Member 
States to enable different ethnic minorities to be distinguished from each other. The UK is an 
exception. Here data are routinely collected on ethnicity, in large measure to inform policy-
making and to serve as a basis for assessing the policies in place. It is therefore possible to 
examine  the  position  of  different  ethnic  groups  in  terms  of  their  household  circumstances, 
income and risk of poverty.  

At  the  same  time,  it  is  open  to  question  how  far  the  conclusions  from  these  data  can  be 
generalised  to  other  EU  Member  States,  since  circumstances  in  the  UK  are  not  the  same  as 
elsewhere.  In  particular,  there  are  relatively  large  numbers  of  people  from  minority  groups 
who have been in the country for several generations. Legislation against discrimination has 
also been in place for longer than in most other Member States.  

According to the Census of Population, in 2001, non-white ethnic minorities made up around 
8 %  of  the  UK  population.  Around  half  of  these  people  were  born  in  the  UK.  Overall,  the 
children of minority groups make up 12 % of the population of children in the UK but 20 % 
of  those  at  risk  of  poverty.  These  figures,  however,  conceal  major  differences  between 
children in different ethnic groups. Recent figures (from the British Family Resources Survey) 
indicate  that  the  risk  of  poverty  among  Black  African,  Pakistani  and  Bangladeshi  children, 
measured in these terms, is more than double the rate for white children (Table 23). 

Table  23  At  risk  of  poverty  rates  among  children  after  housing  costs,  Great  Britain  2002/03-
2004/05 

At risk of poverty rates, children 

White groups 

Black Caribbean 

Black African 

Indian 

Pakistani 

Bangladeshi 

25.1 

36.8 

55.7 

31.9 

60.0 

72.0 

Notes: Ethnic group is that of the household reference person. The at-risk-of-poverty threshold is defined as 60 % of median 
equivalised income. 
Source: Department of Work and Pensions. 

These proportions, however, vary between children living in different types of household. For 
white  children,  therefore,  children  with  a  lone  parent  make  up  the  largest  proportion  of  the 
total  living  in  households  with  income  below  the  threshold,  but  the  risk  is  highest  among 

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those with two parents, neither of whom is in full-time work (Table 24). Conversely the risk 
of poverty is  relatively low for children living in a household in which  there  is at  least one 
wage-earner; but because such households make up the majority of those with white children, 
they still account for nearly half of all white children at risk of poverty.  

Table 24 Risk of poverty among children by family type and household employment status: % 
at risk of poverty and % division of those at risk by household type 

Ethnic Group 

White groups 

Indian 

Pakistani/ 
Bangladeshi 

Risk of 
poverty/ 
division of 
children at 
risk 

Risk 

Division 

Risk 

Division 

Risk 

Division 

Risk 

Household type 

Lone 
parents 

Couple: at least 
1 in full-time 
work 

Couple: neither 
in full-time work 

Employment 
status 

Households 
with one or 
more earners 

48 

46 

55 

20 

63 

14 

59 

69 

12 

32 

19 

44 

46 

32 

19 

15 

62 

22 

86 

36 

83 

54 

82 

16 

15 

49 

24 

64 

54 

54 

25 

35 

Black 
Caribbean 

/Black African  Division 

Source: Department of Work and Pensions. 

By  contrast,  lone-parent  families  account  for  only  a  small  share  of  Indian,  Pakistani  and 
Bangladeshi children at risk of poverty, but they make up over two-thirds of Black Caribbean 
and  Black  African  children  at  risk.  The  risk  for  all  the  ethnic  minority  groups  is  high  for 
children in these circumstances (the proportion varying between 55 % and 63 %); but again 
the  risk  is  not  as  high  as  for  those  living  with  two  parents  neither  of  whom  is  in  full-time 
employment,  which  is  over  80 %  for  Indian,  Pakistani,  Bangladeshi  and  Black  Caribbean 
children.  

For Pakistani and Bangladeshi children, however, the risk of poverty for those living with two 
parents  with  at  least  one  of  them  in  full-time  work  is  also  relatively  high  (46 %),  and  even 
among Indian children, it is over 2½ times higher than among white children, highlighting the 
low earnings of these parents. Indeed, in all households with one or more earners, including 
those  not  in  full-time  work,  the  risk  of  poverty  is  over  50 %  for  Pakistani  and  Bangladeshi 
children, while for Indian children, it is much lower (24 %); but such households account for 
nearly two-thirds of Indian children with income below the threshold. 

The risk of poverty also varies between households with different numbers of children (Table 
25).  Whereas  the  majority  of  white,  Indian,  Black  Caribbean  and  Black  African  children  at 
risk of poverty live in families with one or two children, over two-thirds of poor Pakistani and 
Bangladeshi children at risk live in families with three or more children. For all ethnic groups, 
the  risk  of  poverty  from  living  in  a  larger  family  is  higher  than  if  they  lived  in  a  smaller 
family; but for Pakistani, Bangladeshi, Black Caribbean and Black African children the risk of 
poverty in a smaller family is still higher than for white children living in a large family.  

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Table 25 Risk of poverty among children by family size: risk of poverty and % division of those 
at risk by family size  

Ethnic Group 

White groups 

Indian 

Pakistani 

Bangladeshi 

Black Caribbean/ 
Black African 

Risk of poverty/ 
division of 
children at risk 

Family size 

1 or 2 
children 

3+ children 

Risk 

Division 

Risk 

Division 

Risk 

Division 

Risk 

Division 

Risk 

Division 

22 

62 

26 

55 

51 

32 

59 

29 

41 

53 

32 

38 

46 

45 

66 

68 

79 

71 

54 

47 

Source: Department of Work and Pensions. 

In order to reduce the risk of poverty for children from ethnic minorities, there is a need to 
focus  on  situations  in  which  the  risk  is  disproportionately  high  (such  as  children  living  in 
households  with  no-one  in  full-time  work)  and  situations  accounting  for  the  greatest 
proportion of children at risk (e.g. Black Caribbean and Black African children living with a 
lone parent). 

Conclusions 

Children whose parents were born outside the EU have both access to a lower median income 
and a higher risk of poverty than those whose parents were born in the country concerned. As 
such,  the  evidence  seems  indicative  of  the  disadvantage  in  terms  of  income  and  the  greater 
risk of social exclusion which migrants and ethnic minorities seem to experience. 

This disadvantage does not seem to be wholly linked to the presence of children themselves in 
such  households,  since  a  similar  disadvantage  is  evident  for  households  where  all  members 
were  born  outside  the  EU  but  where  there  are  no  children.  Nevertheless,  the  presence  of 
children seems to compound the disadvantage. In the EU as a whole, therefore, while children 
whose  parents  were  born  outside  the  EU  represented  5-6 %  of  all  children  in  the  EU,  they 
make up 11-12 % of all children whose income is below the at-risk-of-poverty threshold. In 
France, they make up over 20 % of children at risk of poverty, in Austria and Sweden over 
25 % and in Belgium and Luxembourg around a third. The relatively large number of children 
growing up in families with income below the threshold is of particular concern not only in 
itself but because of its implications for their future life chances.  

The  disadvantage  does,  however,  seem  to  be  linked  to  employment,  in  that  children  whose 
parents  were  born  outside  the  EU  are  far  more  likely  in  most  parts  of  the  EU  to  live  in 
households  where  no-one  of  working-age  is  employed  and  much  less  likely  to  live  in 

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households where everyone is in full-time employment. At the same time, it also seems to be 
linked  to  low  wage  levels  in  that  in  many  countries  a  large  proportion  of  the  children 
concerned live in households where one or more of their parents are in work. 

In the UK, which is one of the few EU Member States in which it is possible to examine the 
relative  income  level  and  household  circumstances  of  children  from  different  ethnic 
backgrounds, the evidence indicates that there are marked differences in both of these within 
the  ethnic  minority  group.  The  risk  of  poverty  is,  therefore,  much  higher  for  children  from 
some ethnic backgrounds than others (those in Bangladeshi or Pakistani families, for example, 
as compared with those in Indian families), which seems partly attributable to differences in 
family size.  

BOX 6 — Educational performance of students from a migration background 

Schools have a central role in addressing the challenges posed by migration flows, given the 
close  correlation  between  education  and  a  successful  working  life.  The  recently  published 
OECD  report38  explores  performance  and  school  achievement  of  students  with  a  migration 
family background. The report relies on the results of the OECD Programme for International 
Student Assessment (PISA) 2003, an internationally standardised assessment of performances 
in reading and mathematics administered on the part of 15-year-olds in schools.  

Only  in  14  OECD  countries  (8  European  Union  Member  States)39  was  the  immigrant 
population big enough to be considered significant (>3 % of 15-year-olds). In these countries, 
foreign-born students show a marked deficit in comparison with native students: 48 points on 
the PISA mathematics scale, i.e. more than one average school year’s progress40. The gap is 
reduced  to  30  points  when  socio-economic  factors  such  as  the  occupation  and  education  of 
parents are taken into account. The performance deficit of immigrant students varies widely 
across  countries:  from  almost  insignificant  in  Australia,  Canada  and  New  Zealand  to  more 
than  90  PISA  points  in  Belgium  and  Germany,  even  for  second-generation  immigrant 
children.  

The performance gap remains high (40 points) also for second-generation students. However, 
normally  they  perform  better  than  first-generation  students  as  they  do  not  face  the  same 
linguistic  and  cultural  problems.  Here  again  there  are  major  variations:  in  Canada, 
Luxembourg,  Sweden  and  Switzerland  second-generation  students  perform  significantly 
better  than  first-generation  ones,  while  in  Germany  and  New  Zealand  it  is  the  other  way 
round.  The  immigration  background  also  partly  explains  the  performance  variation  between 
schools.  Immigrant  students  tend  de  facto  to  be  more  or  less  directed  towards  schools  with 
lower  performance  expectations.  In  general  they  are  clustered  in  the  same  schools,  which 
often  present  a  more  disadvantaged  socio-economic  student  background  and,  in  some 
countries, poorer learning conditions. However, the distribution of immigrant students across 
schools  does  not  seem  to  account  for  international  variations  in  performance  gaps  between 

38 
39 

40 

Education at glance, OECD 2007. 
They  are:  Australia,  Austria,  Belgium  (with  separate  data  for  the  Flemish  and  French  Communities), 
Canada,  Denmark,  France,  Germany,  Luxembourg,  the  Netherlands,  New  Zealand,  Norway,  Sweden, 
Switzerland, United States. Overall, 41 countries participated in the PISA 2003 assessment. 
For  the  26  OECD  countries  in  which  a  sizeable number  of  15-year-olds  in  the  PISA  samples  were 
enrolled in at least two different grades, the difference between students in the two grades implies that 
one school year corresponds to an average of 41 score points on the PISA mathematics scale (for details 
on  the  methodology  see  OECD,  The  PISA  2003  Assessment  Framework  —  Mathematics,  Reading, 
Science and Problem Solving Knowledge and Skills, Paris, 2003). 

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immigrant and native students, even if high proportions of immigrant students in schools may 
impact  on  the  performance  levels.  Literature  on  the  latter  point  however  presents  mixed 
evidence41.  

Interestingly  enough,  data  show  no  negative  relationship  between  the  size  of  immigrant 
populations  and  overall  performance.  Countries  with  a  large  immigrant  population  in  many 
cases  also  have  good  overall  performances,  which  contradicts  the  idea  that  a  large  share  of 
immigrants in the population could be an obstacle to integration. Another interesting result of 
the OECD analysis is that, despite lower performance and a generally worse socio-economic 
background, immigrant students are very motivated learners with a positive attitude to school. 
The  indication,  in  all  countries  assessed,  is  of  higher  levels  of  interest  and  motivation  in 
mathematics and a more positive attitude to school in general than among native and second-
generation  peers.  They  claim  they  expect  to  complete  a  university  course  more  often  than 
native students. Finally, they report belief in their own ability in mathematics but then show 
higher levels of anxiety when performing specific tasks. 

41  

Where immigrant students succeed — A comparative review of performance and engagement in PISA 
2003, OECD 2006 

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Figure 20 Differences in mathematics performance by immigrant status (2003) 

Difference in mathematics performance between native and second-generation students

Difference in mathematics performance between native and first-generation students

Australia 

Austria 

Belgium 

Canada 

Denmark 

France 

Germany 

Luxembourg 

Netherlands 

New Zealand 

Norway 

Sweden 

Switzerland 

United States 

     OECD average

Hong Kong-China

Macao-China

Russian Federation 

-120

-100

-80

-60

-40

-20

0

20

Mathematics performance differences

Note: Statistically significant differences are marked in darker tones. 

Source: OECD PISA 2003. Table A6.1a 

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PART 2 - AREAS OF SOCIAL POLICY CONCERN: STATISTICAL PORTRAITS 

The structure of the Part Two: Part Two presents a series of statistical portraits that address 
a  range  of  social  policy  concerns  for  the  European  Union.  Virtually  all  the  main  European 
social policy domains are covered: population; education and training; labour market; social 
protection;  income,  social  inclusion  and  living  conditions;  gender  equality  and  health  and 
safety. The annexes present additional tables and explain terminology. 

The Structure of the statistical portraits: Each statistical portrait is presented in the form of 
tables, charts and commentary. Gender issues are covered not only by the two portraits in the 
domain  “Gender  equality”  but  also  by  other  portraits  and  the  statistical  annexes  where  a 
number of indicators are disaggregated by sex.  

Key indicators: Each portrait is built around one or two selected key indicators (see table in 
the  next  page).  The  first  two  portraits  provide  contextual  information,  one  on  the  economic 
situation, the other on demography, households and families. Both of them have a context key 
indicator whereas the social portraits 3-18 have social key indicators. Together, this set of key 
indicators provides not only a snapshot of today's social situation and its background, but also 
an  instrument  for  monitoring  and  comparing  progress  in  the  social  field  among  the  twenty-
seven Member States and the three Candidate Countries. 

Criteria in selecting the key indicators: The following criteria have been applied as much as 
possible in selecting the key indicators: 

1. 

Each indicator should be:  

(a) 

policy relevant at EU level; 

(b) 

comparable across the twenty-seven Member States; 

(c) 

available using Eurostat harmonised sources; 

(d)  measurable over time and; 

(e) 

easily understood. 

2. 

The  set  of  indicators  should  be  relatively  stable  over  time  to  ensure  continuity. 
However, a degree of flexibility is required to take account of changing policy needs 
and improvements in data availability.  

The  Structural  Indicators:  Sixteen  of  the  chosen  twenty-six  key  indicators  are  among  the 
Structural  Indicators,  which  are  used  in  order  to  monitor  the  progress  towards  the  agreed 
targets  based  on  the  Lisbon  Strategy  focusing  on  growth  and  jobs  (More  about  the  Lisbon 
Strategy can be found in the web address: http://europa.eu.int/growthandjobs/index_en.htm). 

Annexes:  A  summary  of  the  key  indicators  with  the  most  recent  data  for  each  geopolitical 
entity,  i.e.  a  country  or  a  group  of  countries  (EU-27,  EU-25  and  EA-13),  can  be  found  in 
Annex 1.1. Annex 1.2 consists of key indicator tables with time series for each geopolitical 
entity (mainly around the latest 10 available years). Detailed other statistical data covering the 
whole  report  can  be  found  in  Annex  1.3.  Symbols,  country  codes,  country  groupings,  other 
abbreviations and acronyms are explained in Annex 2. 

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Data used: The portraits in Section 2 and annexes 1.1, 1.2, and 1.3 are based mainly on data 
that were available in the end of September 2007. In some parts it has been possible to use 
data that became available later. An effort has been made to use the most recent data available 
and  to  present  coherent  data.  However,  since  this  publication  is  a  result  of  contributions  of 
tens of specialists, inconsistencies of data may have remained within it. 

Sources  of  additional  data:  Additional  or  more  recent  data  can  be  found  in  the  Eurostat 
website  http://europa.eu.int/comm/eurostat/,  where  one  also  can  download  free  pdf  files  of 
Eurostat  publications.  Printed  versions  of  Eurostat  publications  are  sold  by  the  worldwide 
network  of  sales  agents  of  the  Publications  Office  (Office  for  Official  Publications  of  the 
European Communities, which is the publishing house of the institutions and other bodies of 
the  European  Union).  The  priced  publications  are  available  from  EU  Bookshop  website 
http://bookshop.europa.eu, where you can place an order with the sales agent of your choice. A 
list  of 
the  website 
http://publications.europa.eu/others/agents/index_en.htm or you can ask a paper copy by sending a 
fax to +352 2929-42758. 

contact  details 

can  be 

agents' 

found 

these 

sales 

in 

Domain 

Statistical Portrait 

Selected key indicator(s) 
Structural Indicators are written in italics 
(see the previous page) 

Economy 
Population 

1  Economic situation 
2  Demography,  households  and 

Real GDP growth rate 
Total population 

Education and 
training 
Labour market 
(see also the portrait 
nr. 16) 

families 

3  Ageing of the population 
4  International  migration 

and 

asylum 

5  Education and its outcomes 
6  Lifelong learning 
7  Employment 

8  Unemployment 

9  Labour 

Market 

Policy 

expenditure 

Social protection 

10  Social  protection  expenditure 

and receipts 
11  Social benefits 

Income, social 
inclusion and living 
conditions 

12  Income distribution  
13  Low-income households 

14  Jobless  households  and 

low 

wages 

Gender equality 

15  Women  and  men  in  decision 

making 

Health and safety 

16  Earnings of women and men 
17  Life and health expectancies 

Old age dependency ratio 
Crude rate of net migration including 
adjustments and corrections 
Youth education attainment level 
Lifelong learning  
Employment rate 
Employment rate of older workers 
Unemployment rate 
Long-term unemployment rate 
Public expenditure on LMP measures 
(categories 2-7) as a percentage of GDP 
Expenditure on social protection as a 
percentage of GDP 
Old age and survivors benefits as a percentage 
of total social benefits 

and 

and 

and  

Sickness and health care benefits as a 
percentage of total social benefits 
Inequality of income distribution 
At-risk-of-poverty rate before social transfers
At-risk-of-poverty rate after social transfers 
People aged 18-59 living in jobless households
Children aged 0-17 living in jobless households 
Percentage of women in the lower or single 
House of the national or federal Parliament 

and 

Percentage of women in the European 
Parliament 
Gender pay gap in unadjusted form 
Life expectancy at birth 
and 
Healthy Life Years at birth 

18  Accidents 

and  work-related 

health problems 

Serious accidents at work 
Fatal accidents at work 

and 

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1. 

ECONOMIC SITUATION 

Economic growth in 2006 in the EU-27 reached 3.0% after the moderate growth of 1.8% in 
2005.  In  general,  the  new  Member  States  and  Candidate  Countries  outgrow  the  EU-15 
Member  States.  Between  2005  and  2006  government  debt  fell  as  a  percentage  of  GDP  in 
both the euro area and the EU-27, to 69.0% and 61.7% respectively at end-2006. 

Economic growth moderate in 2005 but gathered speed in 2006 

In  2006,  the  European  Union’s  (EU-27)  gross  domestic  product  rose  by  3.0%,  improving 
considerably the moderate growth rate observed in 2005 (+1.8%). Different growth patterns 
can  be  identified  when  looking  at  the  performance  of  individual  Member  States  in  2006.  A 
first  group  is  composed  mainly  by  the  biggest  Member  States  that  registered  GDP  growth 
lower  than  the  EU-27  average  or  grew  with  the  EU-27  average  rate:  Portugal  (1.3%),  Italy 
(1.9%),  France  (2.0%),  the  United  Kingdom  (2.8%),  Germany  (2.9%)  and  the  Netherlands 
(3.0%). A second group comprises Member States that attained robust growth rates: Belgium 
(3.2%),  Malta  (3.2%),  Denmark  (3.5%),  Cyprus  (3.8%),  Hungary  (3.9%),  Spain  (3.9%), 
Sweden  (4.2%)  and  Greece  (4.3%).  A  third  group  is  formed  by  Member  States  that 
experienced  high  growth  rates:  Finland  (5.5%),  Ireland  (5.7%),  Slovenia  (5.7%),  Bulgaria 
(6.1%),  Poland  (6.1%),  Luxembourg  (6.2%),  the  Czech  Republic  (6.4%),  Lithuania  (7.5%), 
Romania (7.7%), Slovakia (8.3%), Estonia (11.2%) and Latvia (11.9%).  

Preliminary  results  for  2007  indicate  that  EU-27  GDP  grew  by  3.4%  in  the  first  quarter  of 
2007  and  by  2.5%  in  the  second  quarter  (growth  rates  compared  to  the  same  quarter  of  the 
previous  year).  For  the  euro  area  (EA13)  the  corresponding  results  were  3.0%  and  2.5%, 
respectively. For the whole of the year 2007, GDP is projected to expand at rates of 2.9% for 
EU-27 and 2.6% for the euro area. 

GDP per head varies widely between Member States, but the gap tends to decrease 

In 2006, GDP per capita in the EU-27 amounted to 23 500 Euro, some 12% below the 26 600 
Euro per capita for the euro area. The highest figures occurred in Luxembourg (71 500 Euro), 
Ireland (41 100) and Denmark (40 500 Euro), the lowest in Bulgaria (3 300 Euro), Romania 
(4 500 Euro) and Poland (7 100 Euro).  

To  make  comparisons  among  Member  States  more  meaningful,  GDP  per  capita  can  be 
expressed in Purchasing Power Standards (PPS), thus eliminating the effect of different price 
levels. PPS are constructed in a way that renders one PPS equal to one Euro for the EU-27. 
GDP per head in the EU-27 thus is 23 500 PPS, while for the euro area, the figure of 25 800 
PPS,  although  still  ahead  of  the  EU-27  figure,  is  somewhat  lower  than  the  respective  value 
expressed in Euro, indicating that the purchasing power of one Euro is slightly lower in the 
euro  area  than  in  the  European  Union  as  a  whole.  For  easier  comparison,  GDP  per  head  in 
PPS is given relative to the EU-27 average. This figure for Luxembourg is a remarkable 178% 
above  the  EU-27  average.  The  second  highest  figure  is  that  of  Ireland,  still  44%  above  the 
average.  Denmark,  Austria  and  the  Netherlands  all  are  around  30%  above  the  average.  The 
biggest  differences  for  figures  below  the  EU-27  average  are  in  Bulgaria,  Romania,  Poland, 
Lithuania  and  Latvia  which  have  values  between  37%  and  58%  of  the  average.  However, 
their values in Euro are only about 14% to 30% of the average. Obviously, lower price levels 
tend to partly compensate for the lower GDP per head. Compared to the situation in 1995, it 
can be seen that the positions at the extremes remain more or less unchanged, but almost all 

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countries with relative values below 100 have moved somewhat closer to the EU-27 average. 
The  most  obvious  changes  were  for  Estonia,  which  passed  from  roughly  on  third  of  the 
average in 1995 to two thirds in 2006, and for Ireland, which recorded a figure for per capita 
GDP that was only slightly higher than the EU-27 average in 1995, while in 2006 it was 38% 
above, placing Ireland second among all Member States.  

Turning to Candidate Countries, GDP per head in PPS in Macedonia and Turkey is about one 
quarter  lower  than  the  lowest  value  observed  among  Member  States,  at  around  30%  of  the 
EU-27 value. Croatia, at 50% of the average, has a significantly higher GDP per head. 

Moderate inflation  

In July 2007, the annual inflation rate was 2.0% in the EU-27, down from 2.2% in June 2007. 
For  the  euro  area  a  slightly  lower  annual  inflation  rate  of  1.8%  has  been  observed  in  July 
2007, down from 1.9% in June 2007. A year earlier, slightly higher rates had been observed 
for the EU-27 (2.5%) and the euro area (2.4%). Among the Member States, the highest annual 
rates  in  July  2007  were  observed  in  Latvia  (9.5%),  Hungary  (8.3%)  and  Bulgaria  (6.8%); 
while the lowest rates were observed in Malta (-0.2%), Denmark (1.1%), France and Slovakia 
(1.2%  each).  Compared  with  July  2006,  annual  inflation  fell  in  seventeen  of  the  Member 
States  and  rose  in  9  countries,  remaining  at  the  same  level  in  one  of  them.  The  highest 
increases were registered in Hungary (from 3.2% to 8.3%), Latvia (from 6.9% to 9.5%) and 
Slovenia (from 1.9% to 4.0%). The biggest falls were those in Malta (from 3.6% to -0.2%), 
Slovakia  (from  5.0%  to  1.2%)  and  Romania  (from  6.2%  to  4.1%).  During  the  first  part  of 
2007  the  annual  rate  of  euro  area  inflation  was  below  the  2.0%  medium-term  stability 
threshold  defined  by  the  ECB.  The  12-month  average  rate  of  change  in  consumer  prices, 
which is less sensitive to transient effects, stood at 2.1% for the EU and 1.9% for the euro area 
in July 2007. 

Interest rates increased from a low level 

Long-term interest rates in the euro area increased during the first six months of 2007 up to 
4.64%, now no longer close to their historical lows of 3.14% in September 2005. In August 
2007 the aggregate interest rate for the euro area, as measured by 10-year government bond 
yields, stood at 4.42% (monthly average), compared with an annual average of 3.84% in 2006 
and  3.42%  in  2005.  The  most  distinguishing  feature  still  is  the  high  degree  of  convergence 
achieved.  Up  to  the  start  of  1999,  when  the  third  phase  of  monetary  union  began,  the  yield 
differentials  on  10-year  bonds  among  euro  area  members  narrowed  sharply  and  almost 
disappeared. Since then, yields have been at broadly similar levels throughout the euro area. 
In August 2007 the differential between Germany (the euro area member which usually has 
the  lowest  interest  rates)  and  Slovenia  (which  has  the  highest  rates)  was  a  mere  40  basis 
points.  

For  the  other  EU  Member  States  not  participating  in  the  single  currency  interest  rates  have 
been  slightly  higher  in  2006,  except  for  Denmark  and  Sweden.  Regarding  the  interest  rate 
differential with respect to the euro area, no clear tendency can be observed. 

Public deficit and debt decrease as percentage of GDP 

Public  deficit  is  defined  in  the  Maastricht  Treaty  as  general  government  net  borrowing 
according  to  the  European  system  of  accounts.  In  2006,  the  government  deficit  of  the  euro 
area  and  the  EU-27  improved  compared  to  2005.  In  the  euro  area,  the  government  deficit 

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decreased from 2.5% of GDP in 2005 to 1.5% in 2006, and in the EU-27 it fell from 2.4% in 
2005  to  1.6%  in  2006.  In  2006  the  largest  government  deficits  in  percentage  of  GDP  were 
recorded by Hungary (-9.2%), Italy (-4.4%), Portugal (-3.9%), Poland (-3.8%) and Slovakia (-
3.7%). Ten Member States registered a government surplus in 2006, with the largest surpluses 
in Denmark (+4.6%), Finland (+3.8%) and Estonia (+3.6%). In all, twenty-one Member States 
recorded an improved public balance relative to GDP, while five Member States registered a 
worsening and one remained unchanged. 

Regarding  Candidate  Countries,  Croatia  registered  a  deficit  of  2.2%  of  GDP  in  2006  (an 
improvement  on  the  3.8%  deficit  in  2005).  Turkey  recorded  a  surplus  (+0.4%)  in  2006, 
compared with a deficit of 0.3% in 2005. 

Public debt is defined in the Maastricht Treaty as consolidated general government gross debt 
at nominal value, outstanding at the end of the year. Between 2005 and 2006 government debt 
fell  as  a  percentage  of  GDP  in  both  the  euro  area  and  the  EU-27,  to  68.6%  and  61.4% 
respectively  at  end-2006.  The  lowest  ratios  of  government  debt  to  GDP  at  end-2006  were 
recorded in Estonia (4.0%), Luxembourg (6.6%), Latvia (10.6%) and Romania (12.4%). Ten 
Member  States  had  a  government  debt  ratio  higher  than  60%  of  GDP  in  2006  -  Italy 
(106.8%),  Greece  (95.3%),  Belgium  (88.2%),  Germany  (67.5%),  Malta  (64.7%),  Hungary 
(65.6%), Cyprus (65.2%), Portugal (64.8%), France (64.2%), and Austria (61.7%). 

Croatia and Turkey have reduced their relative government debt levels during recent years, at 
40.8% and 60.7% respectively at end-2006. 

Policy Context 

In March 2005, the European Council re-launched the Lisbon Strategy for Growth and Jobs 
by  focusing  on  jobs  and  growth  in  Europe  and  invited  the  Commission  to  present  a 
programme setting out the necessary actions at Community level to help delivering the Lisbon 
Agenda. The European Council reaffirmed that the renewed Lisbon strategy should be seen in 
the wider context of sustainable development. On 20th July 2005, the Commission presented 
the Community Lisbon Programme (CLP) which aims at contributing to the overall economic 
and  employment  policy  agenda  by  implementing  Community  policies  that  support  and 
complement national policies. However, the CLP is not only the Commission’s responsibility. 
The  Council  and  the  European  Parliament  are  responsible  for  ensuring  that  the  legislative 
actions outlined in the CLP are adopted. 

The  re-launch  entailed  a  new  governance  architecture  for  the  European  economic  reform 
process  clarifying  the  responsibility  for  implementing  individual  actions  of  the  revised 
Strategy between the national (Member States) or the Community level. While Member States 
have  outlined  their  economic  reform  efforts  at  the  national  level  in  national  reform 
the  Community  Lisbon  Programme  covers  policy  actions  at 
programmes  (NRPs), 
Community-level. 

In "A year of delivery" The European Commission's 2006 Annual Progress Report on Growth 
and Jobs, the Commission has looked at the progress made in National Reform Programmes 
and is proposing some country-specific recommendations to guide Member States. 

The  policy  actions  contained  in  the  CLP  cover  areas  where  purely  national  action  is 
insufficient because important cross-border externalities or economies of scale are concerned 
(e.g. investment in R&D). The actions are undertaken because of their important potential to 

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contribute to growth and jobs in the three key areas: 1) Making Europe a more attractive place 
to invest and work; 2) Knowledge and Innovation; 3) More and better Jobs. 

The EU’s medium-term economic policy strategy focuses on the contribution that economic 
policies can make to achieve the strategic Lisbon goal. This economic policy is laid down in 
the  Broad  Economic  Policy  Guidelines  (BEPGs),  which  make  both  general  and  country-
specific recommendations. 

On  12  April  2005,  the  European  Commission  adopted  the  Integrated  Guidelines  2005  – 
2008,  thus  bringing  together  for  the  first  time  the  Broad  Economic  Policy  Guidelines 
(BEPGs)  and  the  Employment  Guidelines  in  one  single  document.  The  integrated  policy 
guidelines  underline  the  link  between  the  Lisbon  programme  and  sustainable  development. 
They  highlight  that  long-term  growth  depends  on  addressing  a  range  of  resource  and 
environmental challenges which, if left unchecked, will act as a brake on future growth. The 
guidelines  lay  out  a  comprehensive  strategy  of  macroeconomic,  microeconomic  and 
employment  policies  to  redress  Europe’s  weak  growth  performance  and  insufficient  job 
creation. This integration of guidelines follows the move from annual to multi-annual BEPGs 
in 2003. The 2003-05 BEPGs had been subject to two implementation reports whose findings 
fed into the Integrated Guidelines.  

In order to participate in the euro area, Member States must fulfil legal convergence and the 
convergence  criteria  on  price  stability,  government  budgetary  position,  exchange  rate  and 
interest  rate.  At  least  once  every  two  years,  or  at  the  request  of  a  Member  State  with  a 
derogation, the Commission and the European Central Bank (ECB) shall report to the Council 
on the progress made in the fulfilment by the Member States of their obligations regarding the 
achievement of economic and monetary union. Among those Member States not participating 
in  the  euro  area,  Denmark  and  the  United  Kingdom,  negotiated  opt-out  clauses  before  the 
adoption of the Maastricht Treaty, and are not subject to regular convergence reports.  

A  specific  convergence  report,  drawn  up  by  the  Commission  in  May  2006  in  response  to  a 
request by Slovenia and Lithuania, concluded that Slovenia met all the conditions and could 
adopt  the  euro  on  1  January  2007,  while  Lithuania  retained  its  present  status.  The  Council 
endorsed the Commission’s assessments in July 2006.  

The  "regular"  Convergence  Report  was  adopted  by  the  European  Commission  on  5. 
December 2006. Progress with convergence towards the requirements of EMU is assessed in 
the Czech Republic, Estonia, Cyprus, Latvia, Hungary, Malta, Poland, Slovakia and Sweden. 
The  report  examines  whether  the  Member  States  without  an  opt-out  meet  the  convergence 
criteria on price stability, the government budgetary position, exchange rates and interest rates 
and  whether  they  ensure  compatibility  of  their  legislation  with  that  required  for  euro 
membership. The report indicates that none of the countries examined fulfils all conditions for 
adopting the euro at this stage. In this light, the Commission concludes that there should be no 
change in the status of the nine countries assessed as a “Member State with derogation.” 

The  European  Commission  adopted  in  May  2007  in  response  to  a  request  by  Cyprus  and 
Malta  specific  convergence  reports  on  these  countries  with  a  clear  verdict:  both  countries 
meet the necessary economic and legal conditions for joining the euro area and could adopt 
the  euro  on  1  January  2008.  The  Council  endorsed  the  Commission’s  assessments  in  June 
2007. 

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For  the  Candidate  Countries  the  so-called  Pre-Accession  Fiscal  Surveillance  Procedure  has 
been  established,  aiming  at  preparing  countries  for  the  participation  in  the  multilateral 
surveillance  and  economic  policy  co-ordination  procedures  currently  in  place  in  the  EU  as 
part of the Economic and Monetary Union. The Pre-Accession Economic Programmes (PEPs) 
are part of this procedure. 

Methodological Notes 

National  Accounts  figures  are  compiled  according  to  the  European  System  of  National  and 
Regional Accounts in the Community (ESA95). ESA95 is the subject of Council regulation 
No 2223/96 of June 25, 1996.  

Recent important methodological improvements to national accounts include the allocation of 
FISIM (Financial Intermediation Services Indirectly Measured) to user sectors/industries, and 
the  introduction  of  chained  volume  measures  to  replace  fixed-base  volume  measures.  Most 
Member States have fully implemented the new methods by now. However, some outstanding 
implementations  still  impact  on  the  comparability  of  data  and  on  the  availability  of  time 
series.  

Gross  domestic  product  indicates  the  size  of  a  country’s  economy  in  absolute  terms,  while 
GDP  in  relation  to  the  population  (GDP  per  capita)  provides  an  indication  comparable 
between economies of different size. To make international comparisons easier, some data are 
expressed  in  purchasing  power  standards  (PPS).  The  advantage  of  using  PPS  is  that  they 
eliminate distortions arising from the different price levels in the EU countries: they don't use 
exchange  rates  as  conversion  factors,  but  rather  purchasing  power  parities  calculated  as  a 
weighted average of the price ratios of a basket of goods and services that are homogeneous, 
comparable and representative in each Member State. 

Consumer price inflation is best compared at international level by the ‘harmonised indices of 
consumer prices’ (HICPs). They are calculated in each Member State of the European Union, 
Iceland and Norway. The EICP (European Index of Consumer Prices) as defined in Council 
Regulation  (EC)  No  2494/95  of  23  October  1995  is  the  official  EU  aggregate.  It  covers  15 
Member States until April 2004, 25 Member States starting from May 2004 until December 
2006  and  27  Member  States  starting  from  January  2007.  The  10  new  Member  States  are 
integrated into the EICP starting from May 2004 using a chain index formula. This means, for 
example, that the annual rate of change in October 2004 is the change from October 2003 to 
April  2004  of  the  15  old  Member  States  combined  with  the  change  from  April  2004  to 
October 2004 of the 25 Member States. The 2 new Member States – Bulgaria and Romania - 
are integrated into the EICP from January 2007 using a chain index formula. HICPs are used 
by the European Central Bank (ECB) for monitoring inflation in the economic and monetary 
union  and  the  assessment  of  inflation  convergence.  As  required  by  the  Treaty,  the 
maintenance  of  price  stability  is  the  primary  objective  of  the  ECB  which  defined  price 
stability ‘as a year-on-year increase in the harmonised index of consumer prices for the euro 
area  of  below  2%,  to  be  maintained  over  the  medium  term’.  A  more  stable  measure  of 
inflation is given by the 12-month average change that is the average index for the latest 12 
months  compared  with  the  average  index  for  the  previous  12  months.  It  is  less  sensitive  to 
transient changes in prices but it requires a longer time series of indices. 

Government bond yields are a good indicator of long-term interest rates, since the government 
securities market normally attracts a large part of available capital. They also provide a fairly 
good  reflection  of  a  country’s  financial  situation  and  of  expectations  in  terms  of  economic 

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policy. The significance of government bond yields as a measure of Economic and monetary 
union is recognised in the Treaty on European Union, where it appears as one of the criteria 
for moving to stage three of monetary union. 

Depending  on  whether  or  not  a  country’s  revenue  covers  its  expenditure,  there  will  be  a 
surplus or a deficit in its budget. If there is a shortfall in revenue, the government is obliged to 
borrow. Expressed as a percentage of GDP, a country’s annual (deficit) and cumulative (debt) 
financing  requirements  are  significant  indicators  of  the  burden  that  government  borrowing 
places  on  the  national  economy.  These  are  in  fact  two  of  the  criteria  used  to  assess  the 
government  finances  of  the  Member  States  that  are  referred  to  in  the  Maastricht  Treaty  in 
connection with qualifying for the single currency. The government deficit and debt statistics 
are due to be notified to the European Commission by EU Member States under the 'excessive 
deficit procedure'. The legal basis is the Treaty on European Union, Protocol on the Excessive 
Deficit Procedure (EDP), and Council Regulation 3605/93 (as amended). 

Links to other parts of the report 

Employment (2.7), Unemployment (2.8) and Economy (Annex 1.3.1). 

Further reading 

•  European Economy No. 7/2007, “Economic Forecasts, Autumn 2007”, DG Economic and 

Financial Affairs. (scheduled for November 2007) 

•  European  Economy  No.  8/2007,  “The  EU  Economy,  2007  Review”,  DG  Economic  and 

Financial Affairs. (scheduled for November 2007) 

•  European  Economy,  No.  4/2005,  “Integrated  Guidelines  2005-2008 

including  a 
Commission Recommendation on the Broad Economic Policy Guidelines”, DG Economic 
and Financial Affairs. 

Publications  and  additional  or  updated  data  on  national  accounts,  public  debt  and  deficit, 
consumer  prices 
from  Eurostat's  web-site 
are 
(europa.eu.int/comm/eurostat). 

available 

interest 

rates 

and 

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EU-
27

EU-
25

EA-
13

Key indicator 1
2.8
3.0

3.0

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Real GDP growth rate, 2006 (Growth rate of GDP volume) 

3.2

6.1

6.4

3.5

2.9 11.2 5.7

4.3

3.9

2.0

1.9

3.8 11.9 7.5

6.2

3.9

3.2

3.0

3.3

6.1

1.3

7.7

5.7

8.3

5.5

4.2

2.8

4.8f 3.1f

6.1

Source: Eurostat - National Accounts. "f" denotes a forecast by the Commission services.

280
260
240
220
200
180
160
140
120
100
80
60
40
20

GDP per capita in PPS (Index EU-27 = 100)

1995

2006

8
7
2

4
2
2

9
2
6 1
1
4
5 1
0
0
1
1

0
1
1

2
2
1

0
0
1

0
0
1

7
2
-
U
E

5
2
-
U
E

3
1
-
A
E

E
B

G
B

Z
C

9
7

4
7

7
3

2
3

2
3
1

7
2
1

0
3
1

4
1
1

4
4
1

3
0
1

6
1
1

3
1
1

2
2
1

4
0
1

2
0
1

2
9

K
D

E
D

E
E

E
I

L
E

S
E

R
F

T
I

8
6

6
3

8
8

5
7

2
3
1

4
2
1

6
3
1

9
2
1

4
2
6
8 1
1
1
0
1

0
2
1

9
1
1

2
1
1

Y
C

3
9

9
8

V
L

T
L

U
L

U
H

T
M
7
8

6
7

5
6

1
5

6
5

8
5

2
3

5
3

L
N

T
A

L
P

T
P

I

O S
9
R
8

I

K F
S

E
S

K
U

R
H

K
M

R
T

5
7

4
7

3
7

3
5

3
4

8
3

3
6

8
4

0
5

9
3

7
2

0
3

9
2

Note: Figures for 2006 are based on preliminary purchasing power parities. Figures for the United Kingdom, Croatia, FYROM and Turkey do not yet include the allocation of

"financial intermediation services indirectly measured" (FISIM) to user sectors. Therefore comparability across countries is reduced.

Source: Eurostat - National Accounts

Inflation rate, July 2007  (Annual rate of change in Harmonised Index of Consumer Prices (HICP)) 

9.5

8.3

6.8

6.5

5.1

4.1

4.0

10

%

8

6

4

2

0

-2

2.0

1.9

1.8

2.7

2.7

2.5

2.5

2.3

2.3

2.3

2.0

2.0

2.0

1.9

1.7

1.6

1.4

1.4

1.3

1.2

1.2

1.1

EU-27 EU-25 EA-13

LV

HU

BG

EE

LT

RO

SI

IE

EL

CZ

PL

ES

CY

PT

DE

LU

AT

UK

IT

FI

NL

SE

BE

FR

SK

DK

MT
-0.2

HR

MK

TR

Source: Eurostat - Price statistics 

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2. 

DEMOGRAPHY, HOUSEHOLDS AND FAMILIES 

On 1st January 2005 the population of the EU-27 stood at about 491 million. The trend is 
towards having fewer children and having them later in life, fewer and later marriages, a 
higher proportion of births outside marriage and smaller households. 

According to the trend scenario of Eurostat's 2004-based population projections the EU-27 
population  will  continue  to  rise  until  around  2020,  after  which  it  will  begin  to  fall.  The 
working age population is expected to decrease substantially by 2050. 

491 million inhabitants in the EU-27 

On 1st January 2005 the population of the EU-27 stood at about 491 million. For comparison: 
The  United  Nations  estimate  that,  at  the  beginning  of  2005,  the  world's  population  stood  at 
over 6 514 million person, of which over 1 312 million (20%) lived in China, 1 134 million in 
India  (17%)  and  300  million  (5%)  in  the  United  States  of  America.  The  share  of  the  EU's 
population  in  the  world  population  was  below  8%.  Within  the  EU-27,  Germany  has  the 
largest population. Its around 83 million inhabitants make up 17% of the Union's population 
while the United Kingdom, France and Italy each account for around 12-13% of the total. 

Rising number of older people 

Around 16% of the EU-27 population are less than 15 years of age. Persons of working age 
(between 15 and 64 years old) account for 67% of the EU-27 total. The remaining 17% are 
aged 65 and over. The number of elderly people has increased rapidly in recent decades. This 
trend is expected to continue in the coming decades, with important implications for the age 
structure  of  both  the  overall  population  and  the  working  age  population  (See  the  portrait 
"Ageing of the population" (2.3)). 

Slowdown in population growth preceding decline in population post-2025 

There has been a gradual slowing down of population growth in the Union over the last three 
decades. Over the period 1995-2003, the population increased on average by about 3 per 1000 
population  per  year  compared  with  an  annual  average  of  around  8  per  1000  population  per 
year in the 1960s. Since the mid-1980s, international migration has rapidly gained importance 
as  a  major  determinant  of  population  growth  (See  the  portrait  "International  migration  and 
asylum" (2.4)). 

According to Eurostat's 2004-based baseline population projection, the total population of the 
EU-27 is expected to increase by more than 5 million inhabitants over the next two decades. 
This population growth will mainly be a result of migration flows. Afterwards, the population 
will  start  to  decline  gradually  because  net  migration  will  no  longer  outweigh  the  "natural 
decline" (i.e. more deaths than live births). The population will fall to around 472 million by 
2050. 

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A rise in births outside marriage 

The fertility of post war generations has been steadily declining since the mid-1960s, but in 
recent  years  the  total  fertility  rate  has  remained  relatively  stable  at  around  1.5  children  per 
woman.  The  proportion  of  births  outside  marriage  continues  to  increase,  reflecting  the 
growing popularity of cohabitation: from 6% of all births in 1970 to around 30% in 2003. In 
Sweden and Estonia, more than half of the children born in 2003 had unmarried parents. The 
proportion  is  around  40%  in  several  other  countries  (Denmark,  France,  Latvia,  Finland, 
Slovenia and the United Kingdom). In contrast, lower levels, albeit increasing ones, are seen 
in many southern European countries like Greece, Italy and Spain. 

Trend towards smaller households 

The result of these and other trends (such as the increasing number of people living alone) is 
that  households  are  becoming  smaller  and  alternative  family  forms  and  non-family 
households are becoming more widespread. Although this pattern can be observed throughout 
the Union, there are significant variations between Member States. On average there were 2.4 
people per private household in EU-25 in 2003. [It would be useful to include a comparison to 
a historical figure here to show the trend] 

Methodological notes 

Sources:  Eurostat  -  Demographic  Statistics.  2004-based  Eurostat  population  projections  and 
European Union Labour Force Survey (LFS). 

Links to other parts of the report 

Ageing of the population (2.3), Migration and asylum (2.4) and Population (Annex 1.3.2) 

Further reading 

•  Population statistics, 2004 edition. Eurostat. 

•  Demographic  outlook  -  National  reports  on  the  demographic  developments  in  2005, 

Eurostat, 2007: 
http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-07-001/EN/KS-RA-07-001-
EN.PDF  

•  Statistics in Focus (Theme 3 - Population and social conditions), Eurostat:  

–  First demographic estimates for 2006, No. 41/2007.  

–  Long-term population projections at national level, No. 3/2006. 

–  Long-term population projections at regional level, No 28/2007 

http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-SF-07-028/EN/KS-SF-07-
028-EN.PDF 

EN 

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EU-
27

EU-
25

EA-
13

Key indicator 2

BE

BG CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Total population, 1.1.2005 (The number of inhabitants of the area on 1st January (or on 31st December of the previous year) in 1000 
inhabitants)

490 898

461 479

314 888

10 446

7 761

10 221

5 411

82 501

1 348

4 109

11 083

43 038

60 702

58 462

 749

2 306

3 425

 455

10 098

 403

16 306

8 207

38 174

10 529

21 659

1 998

5 385

5 237

9 011

60 060

4 444

2 035

71 610

Notes: 1) De jure  population, except for DE, EL, IE, HU, SI, FI, BG, HR and TR de facto population.  2) CY: Government controlled area.

Source: Eurostat - Demographic Statistics.

Total population, observed (1960-2005) and three 
trend scenario variants (2004-2050), EU-27 

Population living in private households by household type, 
EU-27, 2006

Observed

High Population

Baseline

Low Population

s
n
o

i
l
l
i

m

575

550

525

500

475

450

425

400

375

0
6
9
1

5
6
9
1

0
7
9
1

5
7
9
1

0
8
9
1

5
8
9
1

0
9
9
1

5
9
9
1

0
0
0
2

5
0
0
2

0
1
0
2

5
1
0
2

0
2
0
2

5
2
0
2

0
3
0
2

5
3
0
2

0
4
0
2

5
4
0
2

0
5
0
2

Sources: Eurostat - Demographic statistics and 2004-based Eurostat population projections, 
trend scenario (baseline, high and low population variants).

3 or more adults with 
dependent child(ren)
11.5%

Single men

5.0% Single women

7.1%

2 adults, 3 or more 
dependent children
7.6%

2 adults, 2 dependent 
children
15.2%

2 adults, both below 
65, no dependent 
children
13.2%

2 adults at least one 
aged at least 65, no 
dependent children
10.9%

2 adults, 1 dependent 
child
11.5%

1 adult with dependent 
child(ren)
4.3%

3 or more adults, no 
dependent children
13.6%

Notes: 1) EU-25 without DK, IE and SE. 2) Data for FI extracted from a special household sample. 3) 
Dependent children are all children aged 14 or less and people aged 15-24 who are a) children of the 
reference person ofthe household and b) inactive, i.e. neither employed nor unemployed, e.g. full-time 
students. Other people are classified here as adults.

Source: Eurostat - European Union Labour Force Survey, annual result.

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3. 

AGEING OF THE POPULATION 

In  2005,  there  were  around  81  million  elderly  people  aged  65  and  over  in  the  EU-27, 
compared with 38 million in 1960. Today there is one elderly person for every four people 
of working age (15-64). By 2050, the ratio is expected to be one elderly for every two people 
of working age. The proportion of very old people (aged 80 and more) is expected to almost 
triple in the EU-27, from 4% in 2004 to over 11% in 2050. 

Low fertility levels, extended longevity and baby-boomers’ ageing mean that the EU-27 
population is ageing 

Three  driving  forces  are  behind  the  ageing  of  the  population:  fertility  below  replacement 
levels,  a  fall  in  mortality  and  the  approach  of  the  baby-boomers  to  the  retirement  age.  The 
total  fertility  rate  in  the  EU  seems  to  have  reached  its  lowest  point  at  the  end  of  the  1990s 
(1.4) and has remained close to the level of 1.5 children per woman ever since. It is still low 
compared  to  2.6  in  1960.  Countries  with  the  highest  fertility  at  the  beginning  of  the  1980s 
(Greece, Spain, Ireland, Poland, Portugal and Slovakia) are those where it has subsequently 
fallen the most. In 2005, total fertility was below the level of 1.3 children per woman in the 
Czech Republic, Latvia, Poland, Slovenia and Slovakia. It was above 1.8 children per woman 
in  Denmark,  Ireland,  France,  and  Finland.  Life  expectancy  has  increased  over  the  last  50 
years  by  about  10  years  in  total,  due  to  improved  socio-economic  and  environmental 
conditions and better medical treatment and care (See portrait “Life and health expectancies” 
(2.17)). 

Between 1960 and 2005, the proportion of older people (65 years and over) in the population 
has risen from 10% to almost 17% in the EU-27. All the signs are that this trend will continue 
well  into  the  new  century  although  in  the  course  of  this  decade,  the  rate  of  change  will  be 
somewhat slower due to the drop in fertility during World War II. The proportion of people 
aged 65 and more in the total population is expected to rise in the period to 2050. In the EU-
27  it  is  expected  to  increase  from  17%  in  2005  to  30%  in  2050,  reflecting  an  underlying 
increase in the number of older persons from 81.0 million in 2005 to 141.3 million in 2050. 
The largest shares of elderly people in 2050 are expected in Spain (2050: 36%), Italy (35%), 
Bulgaria  (34%)  and  Greece  (33%),  and  the  lowest  in  Luxembourg  (22%),  the  Netherlands 
(24%) and Denmark (24%). 

Population growth fastest among the 'very old' 

The growth of the population aged 80 or more will be even more pronounced in the future as 
more people are expected to survive to higher ages. The proportion of very old people (aged 
80 and more) is expected to almost triple in the EU-27, from 4% in 2005 to 11% in 2050, with 
the  highest  proportions  expected  in  Italy,  Germany  and  Spain.  It  is  worth  noting  that  the 
population aged 55 to 64 will also grow considerably over the next fifteen years. 

Dwindling 'demographic' basis of support for older citizens 

In 1970, the EU-27 population aged 65 and over corresponded to 18% of what is considered 
to  be  the  working  age  population  (15-64  years).  In  2005,  this  old  age  dependency  ratio  has 

EN 

112 

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risen to almost 25%. All Member States are expected to see an increase in this ratio between 
now  and  2010  (to  an  EU  average  of  26%)  although  the  extent  of  the  rise  will  vary 
considerably between Member States. In the long run, the old age dependency ratio in the EU-
27 is expected to rise to 53% in 2050, while the young dependency ratio would remain more 
or less constant throughout the projection period 2005 to 2050. The total dependency ratio in 
the EU-25 is projected to increase from around 50% in 2004 to 77% in 2050. This means that, 
in 2004, for every four persons of working age, there were two persons of non-working age 
(i.e. young or elderly persons) - the ratio will increase to over three young or elderly persons 
for every 4 people of working age by 2050. 

Policy context 

In its communication on the green paper "Faced with demographic change, a new solidarity 
between the generations" (COM(2005) 94 final) the Commission concluded that “in order to 
face up to demographic change, Europe should pursue three essential priorities: 

•  Return to demographic growth. We must ask two simple questions: What value do we 
attach  to  children?  Do  we  want  to  give  families,  whatever  their  structure,  their  due 
place  in  European  society?  Thanks  to  the  determined  implementation  of  the  Lisbon 
agenda  (modernisation  of  social  protection  systems,  increasing  the  rate  of  female 
employment  and  the  employment  of  older  workers),  innovative  measures  to  support  the 
birth  rate  and  judicious  use  of  immigration,  Europe  can  create  new  opportunities  for 
investment, consumption and the creation of wealth. 

•  Ensure a balance between the generations, in the sharing of time throughout life, in the 
distribution of the benefits of growth, and in that of funding needs stemming from pensions 
and health-related expenditure. 

•  Find new bridges between the stages of life. Young people still find it difficult to get into 
employment.  An  increasing  number  of  “young  retirees”  want  to  participate  in  social  and 
economic life. Study time is getting longer and young working people want to spend time 
with their children. These changes alter the frontiers and the bridges between activity and 
inactivity.” 

Methodological notes 

Sources: Eurostat - Demographic Statistics, 2004-based (baseline) population projections. 

The old age dependency ratio shows the population aged 65 and over as a percentage of the 
working age population 15-64. 

The Eurostat set of population projections is just one among several scenarios of population 
evolution  based  on  assumptions  of  fertility,  mortality  and  migration.  The  current  trend 
scenario  does  not  take  into  account  any  future  measures  that  could  influence  demographic 
trends and comprises seven variants: the 'Baseline' variant as well as 'High population', 'Low 
population',  'No  migration',  'High  fertility',  'Younger  age  profile  population'  and  'Older  age 
profile population' variants, all available on the Eurostat’s website. It should be noted that the 
assumptions  adopted  by  Eurostat  may  differ  from  those  adopted  by  National  Statistical 
Institutes. Therefore, results can be different from those published by Member States.  

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Links to other parts of the report 

Demography,  households  and  families  (2.2),  Social  benefits  (2.11),  Life  and  health 
expectancies (2.17) and Population (Annex 1.3.2). 

Further reading 

•  “Population statistics”, 2004 edition. Eurostat. 

EU-
27

EU-
25

EA-
13

Key indicator 3
26.1
24.6

24.8

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Old age dependency ratio, 2005 (Population aged 65 and over as a percentage of the working age population (15-64) on 1st January)

26.3

24.8

19.8

22.7

27.8

24.3

16.4

26.8

24.4

24.9

29.3

17.3

24.1

22.3

21.3

22.7

19.3

20.8

23.5

18.7

25.2

21.1

21.8

16.3

23.8

26.5

24.3

24.9

15.8

8.9

Notes: 1) FR: Data for France refer to metropolitan France.  2) CY: Government controlled area.

Source: Eurostat - Demographic Statistics, 2004-based Eurostat population projections, trend scenario, baseline variant.

Population structure by major age groups, 
EU-27;   1960, 1970, …, 2050

1.5
8.5

1.8

9.9

2.3

11.2

3.1

10.6

3.3

12.3

4.7

12.8

5.8

14.8

80+ years
65-79 years
15-64 years
0-14 years

7.1

17.4

9.1

19.0

11.2

18.7

64.7

63.5

64.4

66.8

67.1

67.1

64.6

61.5

58.5

56.7

25.3

24.8

22.1

19.5

17.3

15.4

14.8

14.0

13.4

13.4

1960

1970

1980

1990

2000

2010

2020

2030

2040

2050

100

l

n
o
i
t
a
u
p
o
p

l

a
t
o
t

e
h
t

f
o
e
g
a
t
n
e
c
r
e
P

80

60

40

20

0

Note: 1960, 1970 and 1980  EU-25 instead of EU-27.

Sources: Eurostat - Demographic statistics (1960-2000) and 2004-based Eurostat population projections, trend scenario, baseline variant (2010-2050).

Old age dependency ratio; 1970, 2010 and 2050

1970

2010

2050

EU-
27

EU-
25

EA-13

LU

NL

DK

MT

SE

EE

CY

LV

LT

IE

UK

FI

FR

BE

HU

SK

PL

RO

AT

CZ

SI

DE

PT

EL

BG

IT

ES

Notes:  1) The bars within the three groups are in the ascending order of the year 2050.  2) FR: Data for France refer to metropolitan France.  3) CY: Government controlled area.  4) HR, MK and TR: No data.

Sources: Eurostat - Demographic statistics (1970) and 2004-based Eurostat population projections, trend scenario, baseline variant (2010 and 2050).

70

60

50

40

30

20

10

0

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4. 

INTERNATIONAL MIGRATION AND ASYLUM 

Net migration is the main component of annual population change in the EU. In 2005, the 
annual net migration rate was 3.6 per 1 000 population in the 27 Member States of the EU, 
representing  around  86%  of  total  population  growth.  In  2006  there  were  192 700  asylum 
requests in the EU-27. 

Important role of international migration in population growth 

In  most  of  the  EU  Member  States  international  migration  plays  an  important  role  in 
population  growth.  Between  2001  and  2005  net  migration  ranged  between  1.35  and  2.01 
million. In absolute numbers the net migration in countries such as Spain, Italy, France and 
United Kingdom reached the level of several hundred thousands (in Spain more than 600 000 
recorded as highest) in 2005. In relative terms, net migration was highest in Cyprus (1.92%), 
Ireland (1.61%) and Spain (1.49%). In 2005 only five of the EU-27 Member States reported a 
negative crude net migration rate – Latvia, Lithuania, the Netherlands, Poland and Romania. 
Indirect  sources  including  flows  registered  by  other  Member  States  indicate  the  same 
tendency for Bulgaria and Estonia where the data are currently not available. In addition, due 
to positive net migration, the Czech Republic, Italy, and Slovenia had a positive population 
increase  despite  negative  natural  growth.  Even  though  they  experienced  positive  net 
migration, the populations of Germany and Hungary declined due to higher negative natural 
increase.  

The estimated total annual number of immigrants to EU-27 Member States is over 3 millions 
while  the  number  of  emigrants  is  around  half  this.  When  expressed  in  relation  to  the  total 
population, immigration in 2005 accounted for 0.36 percent of the total number of inhabitants 
in  the  EU-27.  The  highest  numbers  of  immigrants  including  short-term  migrants  were 
reported by Germany and Spain (more than 700 000). In the United Kingdom, the number of 
immigrants who entered for a stay of at least one year was nearly 500 thousand according to 
national  statistics.  In  recent  years,  available  statistics  in  Italy  indicate  annual  flows  of  more 
300 000 immigrants per year.  

As  a  result  of  long-standing  positive  net  migration,  in  several  Member  States  there  are 
considerable populations of non-national citizens; that is, persons who are not citizens of their 
country of residence. According to official national statistics and Eurostat estimates, the total 
number of non-nationals living in the European Union Member States in 2005 was around 28 
million,  representing  5.7  percent  of  the  total  population.  In  absolute  terms,  the  largest 
numbers of foreign citizens reside in Germany, France, Spain, the United Kingdom and Italy. 

The  non-national  population  varied  from  less  than  1  percent  of  the  total  population  in 
Romania,  Bulgaria  and  Slovakia  to  39  percent  in  Luxembourg  in  2005.  In  addition  to 
Luxembourg, according to Eurostat estimates, the proportion of non-nationals also exceeds 10 
percent  in  Latvia,  Estonia  and  Cyprus.  Figures  for  Latvia  and  Estonia  include  persons  who 
have been resident in the country since before break-up of the Soviet Union but have not yet 
acquired citizenship of Latvia or Estonia. In half of the Member States, the proportion of non-
nationals  was  between  5  and  10  percent.  In  all  EU  Member  States,  except  Luxembourg, 
Belgium,  Ireland,  Malta,  Cyprus,  Hungary  and  Slovakia,  the  majority  of  non-nationals  are 
citizens of non-EU-27 countries.  

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The  citizenship  structures  of  foreign  populations  in  the  EU  Member  States  vary  greatly.  As 
well  as  geographical  proximity,  the  composition  of  the  non-national  population  in  each 
country  strongly  reflects  their  history,  labour  migration,  recent  political  developments  and 
historical  links.  For  example,  the  largest  non-national  groups  include  Turkish  citizens  in 
Germany, Denmark and the Netherlands; citizens of former colonies in Portugal (citizens of 
Cape Verde, Brazil and Angola) and in Spain (Ecuadorians and  Moroccans);  migrants from 
Albania  in  Greece;  citizens  from  other  parts  of  the  former  Yugoslavia  in  Slovenia;  Czech 
citizens in Slovakia; and citizens from CIS countries (particularly from Russia, Ukraine and 
Belarus) in Estonia, Latvia and Lithuania. 

192 700 asylum requests in the EU-27 in 2006 

In 2006 nearly 193 thousand requests for asylum were received in the EU-27. With this figure 
the level of requests is lower than in the five previous years. Compared to 2002, the number 
of new asylum applications in 2006 has fallen by more than half.  

Although  the  total  number  of  asylum  seekers  in  the  European  Union  has  decreased 
significantly  over  the  last  few  years,  developments  in  the  individual  Member  States  vary 
considerably.  While  most  countries  show  a  decrease,  some  countries  show  an  increasing 
number of asylum applications. 

The largest decreases (in absolute terms between 2005 and 2006) were recorded in France (-
16 300),  Austria  (-9 100),  and  Germany  (-7  900).  At  the  same  time  we  observe  the  largest 
increases in Sweden (+6 800), Greece (+3 200) and Netherlands (+2 100).  

In 2006, the United Kingdom received the largest number of applications: 28,320 (30 840 in 
2005)  followed  by  France  (26 300),  Sweden  (24 300),  Germany  (21 000).  However,  as  UK 
and Sweden are not able to distinguish between first and repeat applications, these figures are 
not fully comparable and should be interpreted with caution. In terms of overall population, 
Cyprus (5.9 applicants per 1 000 inhabitants), Malta (3.1), Sweden (2.7) and Austria (1.6) had 
the highest rates of asylum requests.  

The short and long term impacts of asylum on population change are complex and cannot be 
related simply to the number of applicants in a particular year. The consideration of an asylum 
application  may  take  12  months  or  longer,  meaning  that  some  applicants  who  have  not  yet 
received  a  decision  become  residents  of  the  destination  country,  even  if  only  temporarily. 
Member States differ, both in terms of national asylum law and practice, and in terms of how 
asylum is accounted for in the national migration statistics. In some Member States, persons 
waiting for a decision on their application may be authorised to work. Some persons granted 
asylum will later return to their countries of origin when the situation there changes.  

Policy context 

The Treaty of Amsterdam introduced a new Title IV (Visas, asylum, immigration and other 
policies  related  to  free  movement  of  persons)  into  the  EC  Treaty.  It  covers  the  following 
fields:  free  movement  of  persons;  controls  on  external  borders;  asylum,  immigration  and 
safeguarding of the rights of third-country nationals; judicial cooperation in civil matters and 
administrative cooperation.  

The  Treaty  of  Amsterdam  thus  established  Community  competence  in  the  fields  of 
immigration and asylum and transferred these areas from the intergovernmental third pillar to 

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the  community  first  pillar,  with  decisions  in  these  fields  being  shaped  in  Community 
instruments such as directives. The European Council  at  its  meeting  in  Tampere  in  October 
1999  called  for  the  development  in  the  following  5  years  of  a  common  EU  policy  in  these 
areas  including  the  following  elements:  partnership  with  countries  of  origin,  a  common 
European  asylum  system,  fair  treatment  of  third  country  nationals  and  management  of 
migration  flows.  The  Hague  Programme  of  4-5  November  2004  set  the  priorities  for  the 
current  period  (2005-2010)  and  stressed  the  importance  of  having  an  open  debate  on 
economic migration at EU level, which – together with the best practices in Member States 
and their relevance for the implementation of the Lisbon strategy – should be the basis for “a 
policy  plan  on  legal  migration  including  admission  procedures  capable  of  responding 
promptly to fluctuating demands for migrant labour in the labour market". This Policy Plan 
was adopted by the Commission in December 2005 and is currently being implemented: the 
Commission presented in November 2007 proposals for two directives on the rights of third-
country  nationals  and  on  the  admission  of  highly-skilled  migrants.  In  parallel,  measures 
aiming at reducing illegal immigration are also being presented, like the proposals to establish 
sanctions  for  the  employers  of  illegally  staying  immigrants,  presented  in  May  2007,  and  to 
establish common standards for the return of illegally staying immigrants. 

Asylum policy is also an important priority. After the adoption between 1999 and 2005 of a 
number  of  legislative  instruments  in  this  area,  the  Commission  launched  a  debate  about  the 
future direction of the European asylum policy with the presentation of a Green Paper in June 
2007. The results of the Green Paper consultation will inform a Policy Plan on Asylum to be 
presented in 2008.   

Methodological notes 

Source: Eurostat - Migration Statistics. 

Population  growth  rates  represent  the  relative  increase  of  the  total  population  per  1,000 
inhabitants during the year(s) in question. The increase in total population is made up of the 
natural increase (live births less deaths) and net migration. Net migration is estimated on the 
basis  of  the  difference  between  population  change  and  natural  increase  (corrected  net 
migration rate per 1,000 inhabitants). 

Total  immigration  flows  include  immigration  of  nationals  and  non-nationals,  and  the  latter 
category  encompasses  both  nationals  from  other  EU  countries  and  third-country  nationals. 
Different  Member  States  apply  different  definitions  of  migration.  Often,  statistics  are  based 
on a person registering as a resident in another country or on a stated intention to stay longer 
than a certain period in a country.  

Some countries record only permanent residents when counting the number of non-nationals, 
resulting in an underestimation of foreign (de facto) residents.  

Some  countries  include  some  dependents  in  their  figures  for  asylum  applications,  other 
countries  do  not.  The  same  applies  to  repeat  applications.  The  details  are  given  in  the  table 
“Asylum applications” in the part “2 Population” in Annex 1.3. 

A further valuable source on international migration and the foreign population in the EU is 
the EU Labour Force Survey (LFS). The LFS provides breakdowns by nationality according 
to  various  social-demographic  variables  such  as,  e.g.  gender,  age,  employment  status, 
educational attainment.  

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Links to other parts of the report 

Demography, households and families (2.2) and Population (Annex 1.3.2) 

Further reading 

•  “Population statistics”, 2004 edition. Eurostat.  

•  Statistics  in  Focus  (Population  and  social  conditions):  “First  results  of  the  demographic 
data  collection  for  2003  in  Europe”,  No.13/2004  and  “Acquisition  of  citizenship”  No. 
3/2004. Eurostat. 

•  “Patterns and trends in international migration in Western Europe”, 2000. Eurostat. 

•  Statistics in Focus (Population and social conditions): "Non-national populations in the EU 

Member States", No. 8/2006, Eurostat. 

•  “The  social  situation  in  the  European  Union  2002”,  pages  16-51,  2002.  European 

Commission, DG for Employment and Social Affairs and Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  "Asylum  applications  in  the 

European Union", No.110/2007, Eurostat. 

EU-
27

EU-
25

EA-
13

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 4

3.6

3.8

4.7

4.9

0.0

Crude rate of net migration including adjustments and corrections, 2005 (The difference between population change and natural 
increase (the latter is the surplus or deficit of live births over deaths) during the year per 1000 population. It has a positive value if there 
are more immigrants than emigrants and a negative one in the opposite case.)
3.5

0.1 15.9 3.6 14.8 3.3

5.5 19.0 -0.2 -2.6

-0.3

-0.4

-1.4

-0.3

2.4

1.9

3.6

1.7

3.2

1.0

6.8

3.2

1.7

0.6

3.0

6.0

1.2

0.0

Notes: 1) Conceptually net migration is the surplus or deficit of immigration into over emigration from a given area during the year and the crude rate of net migration is net migration per 1000 population. 
Since many countries either do not have accurate figures on immigration and emigration or have no figures at all, net migration  is calculated indirectly as the difference between total population change and 
natural increase (the surplus or deficit of live births over deaths) between two dates. It then includes adjustments and corrections, i.e. all changes in the population size that cannot be classified as births, 
deaths, immigration or emigration.  It is then used for the calculation of the crude rate of net net migration, which also consequently includes adjustments and corrections.
2) CY: Government-controlled area only.

Source: Eurostat - Population Statistics

Average annual rate of population change by 
component, EU-27, 1961-2005

per 1000 
population

8

6

4

2

0

-2

1961-
64

1965-
69

1970-
74

1975-
79

1980-
84

1985-
89

1990-
94

1995-
99

2000 2001 2002 2003 2004 2005

EU-25 Net migration
EU-25 Natural increase
EU-27 Net migration
EU-27 Natural increase

s
d
n
a
s
u
o
h
T

800

700

600

500

400

300

200

100

0

Asylum applications, EU-27 and EU-15, 
1990-2006

EU-27

EU-15

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Source: Eurostat - Demographic Statistics

Source: Eurostat - Migration Statistics

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5. 

EDUCATION AND ITS OUTCOMES 

Educational  attainment  levels  of  the  population  have  improved  significantly  over  the  last 
thirty years, particularly among women. In 2006, 78% of young people aged 20-24 in the 
EU-27  had  at  least  an  upper  secondary  qualification.  At  the  same  time,  however,  15%  of 
people aged 18-24 left the education system with only lower secondary education at best. 

Younger generation is better educated 

By  comparing  those  currently  leaving  the  education  system  with  older  generations,  it  is 
possible  to  monitor  the  trends  in  educational  attainment  over  a  long  time-period  of  around 
forty years. In 2006, 81% of the younger generation aged 25-29 had completed at least upper 
secondary  education  compared  with  only  60%  of  people  aged  55-59.  This  increase  of  the 
educational attainment level is particularly observable for women: 83% of young women aged 
25-29  years  had  completed  at  least  upper  secondary  education,  comparing  with  55% 
characterising  generation  of  their  mothers  (here:  women  aged  55-59  years).  For  men,  these 
proportions  get  respectively  79%  and  65%.  Today,  educational  attainment  level  is  higher 
among the young women than among young men in all EU-Member States.  

Almost one in six Europeans leaves school with a low educational attainment level 

Although  educational  attainment  levels  continue  to  improve,  15%  of  18-24  year-olds  in  the 
Union  are  not  in  education  or  training  even  though  they  have  not  completed  a  qualification 
beyond  lower  secondary  schooling.  Malta,  Portugal  and  Spain  have  the  highest  proportions 
(30%  or  more)  of  low-qualified  young  people  who  are  not  any  more  in  the  educational  or 
training  system.  In  virtually  all  Member  States,  women  (EU-27  average  of  13%)  are  less 
likely than men (EU-27 average of 18%) to be in this situation. 

Higher education tends to reduce the risk of unemployment… 

In  general,  higher  education  seems  to  reduce,  albeit  to  differing  degrees,  the  risks  of 
unemployment  in  all  Member  States.  In  EU-27,  the  unemployment  rate  of  25-64  years  old 
with  tertiary  education  stood  at  4.1%  in  2006  compared  with  7.3%  for  people  who  had 
completed  at  best  upper  secondary  education  and  10.1.%  among  those  who  had  not  gone 
beyond lower secondary schooling.  

…and increase income…  

The  200542  data  for  EU-25  show  also  that  a  person's  income  is  likely  to  be  considerably 
higher if he/she is better qualified. On average for the EU-25 overall, the median equivalised 
net  income  of  highly  educated  persons  (i.e.  completed  tertiary  education)  was  143%  of  the 
national median whereas it was 83% for those with a low-level education (i.e. completed at 
most  lower-secondary  schooling)  and  102%  for  those  with  medium  level  of  education  (i.e. 
completed  upper  secondary  or  postsecondary,  not  tertiary  education)  .  The  ratio  of  the 
incomes  between  the  well  and  low  educated  workers  was  largest  in  Portugal  (2.72)  and 
smallest in Germany and Sweden (1.36). The 2005 data also show that the at-risk-of-poverty 
rate among the highly educated was only 7% compared with 22% among those with a low-

42 

EU-SILC survey year 2005, income reference year mainly 2004. 

EN 

119 

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level education. For individuals with a medium level of education the at-risk-of-poverty rate 
was 13%. 

…and lead to more training opportunities 

Throughout  the  Union,  the  higher  the  educational  level  of  adults,  the  greater  the  training 
opportunities afforded to them. See also Lifelong learning (2.6). 

Policy context 

EC  Treaty  (Title  XI,  Chapter  3,  Art.  149(1):  "The  Community  shall  contribute  to  the 
development of quality education by encouraging co-operation between Member States and, 
if  necessary,  by  supporting  and  supplementing  their  action  …"  and  Art.  150(1):  "The 
Community shall implement a vocational training policy which shall support and supplement 
the action of the Member States …".  

At the Lisbon European Council held in March 2000, the Heads of State and Government set 
the  Union  a  major  strategic  goal  for  2010  "to  become  the  most  competitive  and  dynamic 
knowledge-based economy in the world, capable of sustainable economic growth with more 
and better jobs and greater social cohesion". In March 2001, the European Council adopted 
three strategic goals (and 13 associated concrete objectives) to be attained by 2010: education 
and training systems should be organised around quality, access, and openness to the world. A 
year  later,  it  approved  a  detailed  work  programme  ("Education  &  Training  2010")  for  the 
attainment of these goals and supported the ambition of the Ministers for Education to make 
education and training systems in Europe "a worldwide quality reference by 2010". 

In  its  Communication  on  the  success  of  the  Lisbon  strategy  (COM  (2003)685)  the 
Commission  outlined  that  Education  and  training  policies  are  central  to  the  creation  and 
transmission  of  knowledge  and  are  a  determining  factor  in  each  society's  potential  for 
innovation.  Nevertheless  the  Union  as  a  whole  is  currently  under-performing  in  the 
knowledge-driven  economy  in  relation  to  some  of  its  main  competitors.  Efforts  are  being 
made  in  all  the  European  countries  to  adapt  the  education  and  training  systems  to  the 
knowledge-driven  society  and  economy,  but  the  reforms  undertaken  are  not  up  to  the 
challenges  and  their  current  pace  will  not  enable  the  Union  to  attain  the  objectives  set.  The 
benchmarks  adopted  by  the  (Education)  Council  in  May  2003  will  for  the  most  part  be 
difficult  to  achieve  by  2010.  In  particular,  the  level  of  take-up  by  Europeans  of  lifelong 
learning is low and the levels of failure at school and of social exclusion, which have a high 
individual, social and economic cost, remain too high.  

Methodological notes 

Sources: Eurostat - European Union Labour Force Survey (LFS) and Community Statistics on 
Income and Living Conditions (EU-SILC).  

The levels of education are defined according to ISCED (International Standard Classification 
of Education - UNESCO 1997 version). Less than upper secondary corresponds to ISCED 0-
2, upper secondary level to ISCED 3-4 (including thus post-secondary non-tertiary education) 
and tertiary education to ISCED 5-6.  

The structural indicator on early school leavers shows the percentage of the population aged 
18-24 with at most lower secondary education and not in further education or training.  

EN 

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Links to other parts of the report 

Lifelong learning (2.6), Employment (2.7), Unemployment (2.8) and Education and training 
(Annex 1.3.3). 

Further reading 

•  “Education across Europe 2003”, 2004, Eurostat. 

•  “Key data on higher education in Europe - 2007 edition", 2007, DG Education and Culture, 

Eurostat and Eurydice (Information network on education in Europe). 
http://www.eurydice.org/ressources/eurydice/pdf/0_integral/088EN.pdf  

•  “The  transition  from  education  to  working  life:  Key  data  on  vocational  training  in  the 
European  Union”,  2001,  DG  Education  and  Culture,  Eurostat  and  Cedefop  (European 
Centre for the development of Vocational Training). 

•  “Education  and  training  2010.  The  success  of  the  Lisbon  strategy  hinges  on  urgent 

reforms”. European Commission, DG Education and Culture  

•  “Education at a glance 2006”, 2006, OECD. 

•  “Education for all – An international strategy to put the Dakar Framework for Action on 

Education for All into operation”, 2002, UNESCO, 
http://www.unesco.org/education/efa/index.shtml. 

•  Statistics in Focus on education (Theme 3 - Population and social conditions), Eurostat:  

–  Education in Europe, No. 13/2003.  

–  General indicators on transition from school to work, No. 4/2003. 

–  School  leavers  in  Europe  and  labour  market  effects  of  job  mismatches,  No. 

5/2003.  

–  Youth transitions from education to working life in Europe, No. 6/2003.  

–  Education in Europe, Key statistics 2002/2003, No. 10/2005 

–  17 million tertiary students in the EU, No.19/2005 

EN 

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EU-
27

EU-
25

EA-
13

BE BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Key indicator 5
Total
77.8 77.7 73.8 82.4 80.5 91.8 77.4 71.6 82.0 85.4 81.0 61.6 82.1 75.5 83.7 81.0 88.2 96.3 82.9 50.4 74.7 85.8 91.7 49.6 77.2 89.4 91.5 84.7 86.5 78.8 93.8
Women 80.7 80.9 77.6 85.6 81.1 92.4 81.5 73.5 89.8 89.1 86.6 69.0 84.3 79.4 90.7 86.2 91.2 74.5 84.7 52.8 79.6 86.7 93.8 58.6 77.8 91.4 91.7 87.0 88.6 80.3 94.9
74.8 74.7 70.1 79.1 80.0 91.1 73.4 69.8 74.1 81.8 75.5 54.6 80.0 71.7 76.1 75.9 85.3 64.0 81.2 48.1 69.9 84.9 89.6 40.8 76.6 87.7 91.2 82.3 84.5 77.3 92.8
Men

Youth education attainment level, 2006 (Percentage of the population aged 20 to 24 having completed at least upper secondary 
education)

:
:
:

44.7
51.7
38.9

Source: Eurostat - European Union Labour Force Survey

Early school-leavers by sex, 2006
Percentage of the population aged 18-24 with at most lower secondary education and not in further education or 
training

Women

Men

Total

%

SI

CZ

PL

SK

FI

AT

LT

DK

SE

IE

HU

BE

NL

UK

FR

EE

DE

EL

CY

LU

EU-
27

EA-
13

BG

LV

RO

IT

ES

PT MT

HR

TR MK

Source: Eurostat - EU-Labour Force Survey, 2006 

60

50

40

30

20

10

0

Unemployment rate for persons aged 25-64 years, by level of education and gender, EU-27, 2006

Unemployed persons as a % of the total active population

Women

Total

Men

%

11.7

10.1

8.9

8.0

7.3

6.7

4.6

4.1

3.6

14

12

10

8

6

4

2

0

Less than upper secondary

Source: Eurostat - EU-Labour Force Survey

Upper secondary and post-secondary, not
tertiary

Tertiary

EN 

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6. 

LIFELONG LEARNING 

In the Union (EU-27), 10% of the population aged 25-64 participated in education/training 
(over  the  four  weeks  prior  to  the  survey)  in  2006.  Such  learning  activities  are  more 
prevalent (between 20 and 33%) in Denmark,  Finland,  Sweden  and  the  United  Kingdom. 
On  the  other  hand,  in  many  countries  this  proportion  of  people  participating  in  lifelong 
learning is very small, lower than 10% of the 25-64 age-group.  

Women, the young and the qualified participate more in education and training 

The  annual  figures  on  participation  in  lifelong  learning  correspond  to  the  number  of  people 
interviewed during the Labour Force Survey who answer positively to the question whether 
they  have  participated  in  formal  or  non-formal  education  or  training  during  the  4  weeks 
preceding  the  survey.  According  to  these  figures  for  the  Union  as  a  whole,  the  level  of 
participation in such activities decreases with age: from 16% among those aged 25-34 to 5% 
for the 55-64 age group.  

Moreover,  the  level  of  education  attained  also  influences  the  chances  of  participation  in 
"lifelong learning" for people aged 25-64: in 2006, 19% of those with a tertiary qualification 
participated in education or training, compared to just 4% of those with low educational level.  

On the other hand, there were slightly more women (10.4%) than men (8.8%) participate in 
education and training. The gap in favour of women is particularly large in Baltic countries in 
the United Kingdom.  

Almost 6 out of 10 Europeans have not participated in lifelong learning during a whole 
year. 

An  ad  hoc  survey  on  participation  in  lifelong  learning  over  the  12  months  preceding  the 
survey  was  attached  to  the  LFS  in  2003.  When  asked  whether  they  had  participated  in  any 
kind of education and training, including self-learning, 4.4% of the respondents said that they 
had  participated  in  formal  education,  typically  leading  to  a  recognised  qualification,  while 
22.5% said that they had only used self-learning methods (including visiting libraries, using 
computers, self-study and broadcasting). However 58% answered that they had not taken any 
action to learn something during that year. The level of non participation is 70% or more in 
Poland  (70%),  Czech  Republic  (71%),  Lithuania  (72%),  Spain  (75%),  Greece  (83%)  and 
Hungary (88%).  

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Formal education 

1.4 

7.4 

0.8 

0.6 

7.9 

1.6 

Non-formal education 

58 

22.5 

Informal learning 

Source: LFS ad hoc module 2003 on lifelong learning 

Continuing vocational training in enterprises: joint agreements between social partners 
increase the chance for employees to be trained 

Continuing vocational training provided by enterprises is a crucial part of lifelong learning: it 
benefits not only the enterprises in improving competitiveness but also benefits employees by 
keeping up their employability and enhancing their quality of working life. 

The results of the second European survey of continuing vocational training (CVTS2 - 1999) 
reflect  a  pronounced  gap  between  the  North  and  the  South  of  Europe  regarding  the 
participation  rates  in  continuing  vocational  training  (courses).  Whereas  in  the  Scandinavian 
countries at least half of the employees of all enterprises participate in courses, in Greece and 
in Portugal this value is less than one fifth. In contrast, with respect to the training intensity in 
terms  of  ‘training  hours  per  participant’,  southern  EU  Member  States  perform  at  the  same 
level as the northern and central “training countries”. This pattern of the southern countries is 
repeated in most of the new eastern EU Member States. 

CVTS2 results indicate the importance of training in the service sector. In all the EU Member 
States, the training intensity is highest in this area of economic activity. 

Except  in  countries  where  continuing  vocational  training  is  generally  widespread,  the 
provision of training is biased towards larger enterprises. CVTS2 results have highlighted the 
fact  that  negotiated  joint  agreements  on  training  between  the  employers  and  employees  (or 
their  representatives)  are  important  measures  which  correct  for  this  bias  and  increase 
considerably  the  participation  in  continuing  vocational  training  courses in  small  enterprises. 
In  Portugal,  the  participation  rate  in  small  enterprises  with  training  agreements  is  38%, 
compared with just 4% in small enterprises without such agreements. 

At  the  EU-level,  participation  rate  in  CVT  is  a  spot  higher  for  men  (41%)  than  for  women 
(38%), however, this pattern is not observed for all countries, there being a significant bias in 
favour of men in the Czech Republic and in the Netherlands.  

Planning for the next Continuing Vocational Training Survey CVTS3 is currently underway 
and an underpinning regulation is in preparation. The CVTS3 survey will be implemented in 
2006 with reference year 2005, and first results will be available towards the end of 2007.  

EN 

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Age of students in formal education varies considerably 

An  alternative  way  of  measuring  "lifelong  learning"  is  to  look  at  the  proportion  of  students 
who  are  aged  30  or  over  in  formal  education.  In  tertiary  education  (i.e.  education  which 
focuses on university or equivalent post-secondary education), around 2.8 million students in 
the Union (EU-25) were aged 30 or over in 2002/03. About 1.5 millions were studying full-
time, 1.3 millions were studying part-time. This age group accounted for 11% of all full-time 
students and for 16.7% of all students, part-time as well as full-time. In some countries, the 
proportion  of  students  30  years  old  or  older  was  considerably  above  average.  That  was  the 
case in Sweden (36%), the United Kingdom (35%), Finland (27%) and Denmark and Latvia 
(25%).  In  for  example  Greece  (1%),  Cyprus  (3%),  Ireland  and  France  (9%)  the  percentage 
was below the average. 

Many adults are as well enrolled in formal education on upper secondary and post-secondary–
non-tertiary levels of education. In 2002/03, 4.6 million students on these levels were aged 30 
or  above.  Most  of  these  students  were  studying  part-time,  only  0.5  millions  were  studying 
full-time. The age group 30 years and above accounted for 14% of all upper secondary and 
post-secondary–non-tertiary  students  in  2002/03.  Also  this  percentage  varies  between 
countries. In the United Kingdom (41%), Sweden and Belgium (22%), and Finland (18%) the 
percentage was above the EU average. In Ireland, Malta, Lithuania, Germany, Cyprus, Greece 
and Latvia the percentage was 0.5% or below. 

Total public expenditure on education: 5.09% of EU-27 GDP in 2004 

Although investment in education is influenced by various factors (e.g. demographical aspects 
or  levels  of  participation  and  length  of  study),  the  percentage  of  national  wealth  devoted  to 
education tends to reflect the importance which governments attach to it. 

In 2004, total public resources allocated to the funding of all levels of education - including 
direct  public  expenditure  for  educational  institutions  and  public  transfers  for  education  to 
private entities - represented on average 5.09% of EU-27 GDP. 

In  EU-27,  primary  education  accounted  on  average  for  1.16%  of  GDP  in  2002,  secondary 
education accounted for 2.31%, while tertiary education accounted for 1.13%. The remaining 
0.49% includes the allocation for pre-primary education and allocation for education, which 
has not been allocated by level. 

In  EU-27,  a  government’s  contribution  to  education  varied  greatly  in  2004  from  3.29%  of 
GDP in Romania, 3.93% in Luxembourg and 4.21% in Slovakia to 6.71% in Cyprus, 7.35% 
in Sweden and 8.47% in Denmark. 

Policy context 

EC  Treaty  (Title  XI,  Chapter  3,  Art.  150(2):  "Community  action  shall  aim  to  …  facilitate 
access  to  vocational  training  …;  stimulate  co-operation  on  training  between  educational  or 
training establishments and firms; 

In it's Communication on the Future of the European Employment Strategy the Commission 
outlines  the  key  link  played  by  lifelong  learning  in  improving  quality  at  work  and 
productivity,  and  as  a  factor  promoting  labour  force  participation  and  social  inclusion.  In 
particular the growing inequality in access to training, to the disadvantage of less skilled and 

EN 

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older workers, is a priority. The current trend whereby firms' investment in training declines 
with the age of workers should be reversed. The 2001 Employment Guidelines included for 
the  first  time  a  horizontal  guideline  asking  for  "comprehensive  and  coherent  national 
strategies  for  lifelong  learning"  in  order  to  promote  employability,  adaptability  and 
participation  in  the  knowledge-based  society.  Member  States  were  also  invited  to  set,  and 
monitor  progress  towards,  targets  for  increasing  investment  in  human  resources  and 
participation in further education and training. 

A  Communication  on  "Making  a  European  Area  of  Lifelong  Learning  a  Reality" 
(COM(2001)  678  final  of  21.11.2001)  adopted  by  the  Commission  sets  out  proposals  for 
improving the participation of Europeans in lifelong learning activities. In this communication 
lifelong learning is defined as “all learning activity undertaken throughout life, with the aim 
of  improving  knowledge,  skills  and  competences  within  a  personal,  civic,  social  and/or 
employment-related  perspective”.  A  Report  from  the  Education  Council  to  the  European 
Council on "The concrete future objectives of education and training systems" was presented 
in  Stockholm  in  2001.  In  this  the  Ministers  of  Education  adopted  the  following  concrete 
strategic objectives: increasing the quality and effectiveness of education and training systems 
in  the  European  Union;  facilitating  the  access  of  all  to  the  education  and  training  systems; 
opening  up  education  and  training  systems  to  the  wider  world.  These  common  objectives 
provide a basis for Member States to work together at European level over the next ten years, 
following the “Detailed work programme on the follow-up of the objectives of Education and 
training systems in Europe” (Official Journal of the European Communities 2002/C 142/1), to 
contribute to the achievement of the goals set out by Lisbon, especially in the context of the 
Luxembourg and Cardiff processes. The Education/Youth Council of 30 May 2002 adopted a 
resolution  on  education  and  lifelong  learning  (Official  Journal  C  163  of  9  July  2002), 
reaffirming the need for a convergence of the Commission's Communication entitled Making 
a European area of lifelong learning a reality with the work programme on the follow-up of 
the objectives of the education and training systems, in order to achieve a comprehensive and 
coherent strategy for education and training. On 30 November 2002 the education Ministers 
of 31 European countries and the European Commission adopted the Copenhagen Declaration 
training 
vocational 
on 
(http://europa.eu.int/comm/education/copenhagen/index_en.html). 
Commission 
Communication  “Investing  efficiently  in  education  and  training:  an  imperative  for  Europe” 
(COM(2002)  779  final,  10.01.2003)  sets  out  the  Commission's  view  on  the  new  investment 
paradigm in education and training in the enlarged EU within the framework of the ambitious 
strategic  goal  set  by  the  Lisbon  European  Council  in  March  2000.  In  view  of  this  goal, 
Ministers in charge of education adopted in February 2002 the “Detailed work programme on 
the  objectives  of  education  and  training  systems”,  including  its  objective  1.5:  “Making  the 
most efficient use of resources”. 

education 
The 

in  European 

cooperation 

enhanced 

and 

In  its  Communication  on  the  success  of  the  Lisbon  strategy  (COM(2003)  685)  the 
Commission reconfirmed that education and training policies are central to  the  creation  and 
transmission  of  knowledge  and  are  a  determining  factor  in  each  society's  potential  for 
innovation.  Nevertheless  the  Union  as  a  whole  is  currently  under-performing  in  the 
knowledge-driven economy in relation to some of its main competitors. In particular, the level 
of take-up by Europeans of lifelong learning is low and the levels of failure at school and of 
social exclusion, which have a high individual, social and economic cost, remain too high. In 
addition  to  this  there  are  no  signs  of  any  substantial  increase  in  overall  investment  (be  it 
public or private) in human resources. A more rapid pace is therefore needed to make Europe 
"a worldwide quality reference by 2010".  

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In  the  Communication  'Mobilising  the  brainpower  of  Europe:  enabling  universities  to  make 
their full contribution to the Lisbon Strategy (COM(2005) 152 of 20.4.2005) the Commission 
identifies a funding gap in higher education between the EU and the US and calls for more 
resources for higher education. It estimates that a total annual investment of some 2% of GDP 
in higher education (compared to 1.3% currently) as the minimum. 

Methodological notes 

Sources: Eurostat - European Union Labour Force Survey (EU-LFS) - standard questionnaire 
2004  and  ad  hoc  module  2003  on  lifelong  learning),  Continuing  Vocational  and  Training 
Survey  (CVTS2  1999)  and  UOE  (UNESCO,  OECD  and  Eurostat)  questionnaires  on 
education statistics. 

For  the  annual  monitoring  of  progress  towards  lifelong  learning  for  all  the  results  from  the 
standard LFS are used which refer to persons who had received education or training during 
the  four  weeks  preceding  the  interview.  Due  to  the  implementation  of  harmonised  concepts 
and definitions in the survey, information on lifelong learning notices some breaks of series 
for several countries. 

EU Adult Education Survey (EU AES) has been developed between 2003 and 2005 and was 
implemented in EU countries in 2006 or 2007 The EU AES is expected to be repeated every 5 
years, its target population are 25 to 64 year olds and the reference year is the 12 months.  

The  EU  AES  has  been  also  drawn  on  the  experience  of  the  implementation  of  an  ad  hoc 
module  on  lifelong  learning  in  the  EU  LFS  in  2003.  Results  released  in  2005  enhance 
information on participation of adult population (aged 25-64 years) in formal education and 
training as well as in non- formal education and training and informal learning. First global 
results on participation over the past year have been included in the present report. 

The second survey of continuing vocational training in enterprises (CVTS2) was carried out 
in  2000/2001  in  all  the  15  old  EU-25  Member  States,  Norway,  seven  new  EU-25  Member 
States and two Candidate Countries.  

Links to other parts of the report 

Education  and  its  outcomes  (2.5),  Employment  (2.7),  Unemployment  (2.8),  Education  and 
training (Annex 1.3) 

Further reading 

•  “Education across Europe 2003”, 2004, Eurostat. 

•  “Key data on higher education in Europe - 2007 edition", 2007, DG Education and Culture, 

Eurostat and Eurydice (Information network on education in Europe). 
http://www.eurydice.org/ressources/eurydice/pdf/0_integral/088EN.pdf  

•  "European  Social  Statistics  -  Continuing  Vocational  Training  Survey  (CVTS2)  –  Data 

1999", Eurostat, 2002. 

•  "Education at a glance 2006", 2006, OECD. 

•  Statistics in Focus on education (Theme 3 - Population and social conditions), Eurostat:  

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–  Education in Europe, Key statistics, 2002/2003, No.10/2005 

–  17 million tertiary students in the EU, No.19/2005 

–  Lifelong learning in Europe, No.8/2005 

•  Statistics in Focus on finance of education (Theme 3 - Population and social conditions), 

Eurostat:  

–  Public  expenditure  on  education  in  the  EU-15  in  1999,  No.  22/2003-  Public 

expenditure on education in the ACC countries in 1999, No. 23/2003 

–  Spending on tertiary education in 2002, No.18/2005 

•  Statistics in focus on CVTS2 (Theme 3 - Population and social conditions), Eurostat:  

–  First  survey  on  continuing  vocational  training  in  enterprises  in  candidate 

countries, No. 2/2002. 

–  Continuing vocational training in enterprises in the European Union and Norway, 

No. 3/2002. 

–  Costs and funding of continuing vocational training in enterprises in Europe, No. 

8/2002. 

–  Providers  and  fields  of  continuing  vocational  training  in  enterprises  in  Europe, 

No. 10/2002. 

–  Disparities  in  access  to  continuing  vocational  training  in  enterprises  in  Europe, 

No. 22/2002. 

–  Working  time  spent  on  continuing  vocational  training  in  enterprises  in  Europe, 

No. 1/2003. 

•  “Making  a  European  Area  of  Lifelong  Learning  a  Reality",  COM(2001)  678  final  of 

21.11.2001. 

•  “Education  and  training  2010.  The  success  of  the  Lisbon  strategy  hinges  on  urgent 

reforms”. European Commission. 

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EU-
27

EU-
25

EA-
13

BE BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 6
9.6 10.1 8.2
Total
Women 10.4 11.0 8.6
7.9
8.8
Men

9.2

7.5
7.6
7.4

Life-long learning (adult participation in education and training), 2006
(Percentage of the population aged 25-64 participating in education and training over the four weeks prior to the survey)
5.6 29.2 7.5
5.9 33.8 7.3
5.4 24.6 7.8

1.3 15.0 4.3 23.1 32.1 26.6 2.1
1.3 16.3 4.6 27.0 36.5 31.2 2.1
1.3 13.8 4.0 19.3 27.9 22.0 2.0

5.5 15.6 13.1 4.7
5.6 15.9 14.0 5.1
5.5 15.3 12.2 4.3

1.9 10.4 7.5
1.8 11.5 7.8
7.2
9.3
2.0

7.1
7.8
6.5

4.9
6.6
2.9

3.8
4.4
3.1

7.5
8.9
6.1

3.8
4.0
3.7

6.1
6.5
5.7

6.9
9.3
4.1

8.2
8.7
7.6

6.5
8.6
4.2

1.3
1.3
1.3

:
:
:

2.0
2.4
1.6

Source: Eurostat - EU-Labour Force Survey.

Lifelong learning by age group and level of education, EU-27, 2006
Percentage of the population aged 25-64 participating in education and training over the four weeks prior to the survey

Lower secondary or less
23.4

Upper secondary and postsecondary, not tertiary

Tertiary

All 

%

18.7

15.0

15.5

18.3

16.8

8.9

9.6

6.0

3.7

9.7

8.2

4.6

7.6

6.4

3.3

12.1

4.1

4.6

2.0

25

20

15

10

5

0

25-64

25-34

35-44

45-54

55-64

Source: Eurostat - EU-Labour Force Survey.

Spending on Human Resources, 2003 and 2004 
Total public expenditure on education as a percentage of GDP

2003

2004

%

9

8

7

6

5

4

3

2

1

0

EU27 EU25 EA
(13)

DK

SE

CY

FI

BE

SL

FR

AT

HU

PL

PT

UK

LT

NL

EE

LV MT

IE

DE

IT

BG CZ

ES GR

SK

LU

RO

HR MK

TR

Source: Eurostat – Education Statistics

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7. 

EMPLOYMENT 

In 2006, employment growth of the EU-27 picked up to 1.6%, its highest level since 2000. 
After a rise of 0.9 point over 3 years from 2002 to 2005, average employment rate increased 
in  2006  by  1  percentage  point,  to  reach  64.4%.  The  share  of  part-time  employment  and 
temporary contracts keep on rising in 2006. 

Acceleration of employment growth in 2006 

In 2006, about 219 million people were in employment in the Union of 27 Member States, a 
rise of 7 million since 2001. From 2001 to 2006, the largest increase in the number of persons 
in employment in absolute terms was in Spain (+ 2.9 million in five years), in Italy and in the 
United Kingdom (+ 1.3 million).  

Employment  growth  has  been  accelerating  since  2002  in  the  EU-27.  Compared  to  the  year 
before, employment increased by 1.6% in the Union in 2006, after +0.7% in 2004 and +0.9% 
in  2005.  In  2006,  employment  growth  was  positive  in  all  27  Member  States.  In  Estonia, 
Latvia,  Ireland,  Luxembourg,  Spain  and  Poland,  employment  growth  was  3%  or  more.  In 
contrast,  employment  growth  was  less  than  1%  in  Germany,  France,  Hungary;  Malta 
Portugal,  and  United  Kingdom.  However  Germany,  Portugal  and  in  particular  the 
Netherlands, saw their employment grow again in 2006 after a bad performance in 2005. 

EU total employment rate rose by 1 percentage point in 2006 

In 2006, the employment rate for the population aged 15-64 ranged from 54.5% in Poland to 
77.4%  in  Denmark.  Denmark,  the  Netherlands,  Austria,  Sweden  and  United  Kingdom  have 
already reached the EU collective overall employment rate Lisbon target of 70% for 2010. In 
contrast, Bulgaria, Italy, Hungary, Mata, Poland, Romania and Slovakia showed employment 
rates below 60%. 

Compared  to  the  previous  years,  EU-27  average  employment  rate  rose  in  2006  by  1.0 
percentage point to reach 64.4%, after a rise of 0.9 point from 2002 to 2005. 

Positive trends in employment rate for women  

In 2006, the employment rate of women in the Union stood at 57.2%, up by 1.0 percentage 
point  in  one  year.  It  ranged  from  34.9%  in  Malta  to  73.4%  in  Denmark.  Twelve  Member 
States have already reached the EU collective female employment rate Lisbon target of more 
than 60% for 2010, but some of them are far from it: Greece, Italy, Malta and Poland had less 
than half of their women aged 15-64 in employment. 

Slight decrease in the gender gap in employment 

In 2006, the gender gap in employment rates in the Union went on narrowing, standing at 14.4 
percentage points, compared to 14.6 in 2005 and 16.6 in 2001. This decrease of gender gap 
reflects a great rise in employment rate for women (from 54.3% in 2001 to 57.2% in 2006) as 
well  as  a  slight  increase  for  men  (from  70.9%  in  2001  to  71.6%  in  2006).  In  Bulgaria, 
Denmark, Finland, the three Baltic countries, Slovenia and Sweden, the gender gap was less 
than 10 percentage points. In Malta, where the employment gender gap was the highest, the 
female employment rate was less than half of the male employment rate in 2006. In addition 

EN 

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to the female employment rate being systematically lower than the male rate, many women 
work part-time. 

Part-time work and temporary employment continued to rise  

The share of part-time employment has increased from 16.2% in 2001 to 18.1% in 2006. In 
Belgium, Denmark, Germany, Austria, Sweden and the United Kingdom, more than 20% of 
employment,  and  in  the  Netherlands  46.2%,  is  part-time.  At  the  other  end  of  the  scale,  in 
Bulgaria, Hungary and Slovakia, part-time employment was less than 5%. 

In the EU-27, 31.2% of women in employment were working part-time in 2006 against only 
7.7%  of  men.  Compared  to  one  year  before,  the share of part-time employment rose  by  0.3 
percentage point both for women and men. Female part-time work is particularly prevalent in 
the  Netherlands,  where  it  accounts  for  almost  three  quarters  of  female  employment,  and  in 
Germany (45.6%).  

EU-wide,  the  share  of  temporary  employment  increased  in  2006:  14.3%  of  the  employees 
hold a limited duration contract, up by 0.4 percentage point in one year, and 1.9 percentage 
points from 2001. Unlike part-time work, the share of temporary employment shows no huge 
difference for men and women (14.9% for women, 13.9% for men).  

36.3% of young people (15-24 years old) and 43.5% of people aged 55-64 are employed 
in the EU 

EU-wide  36.3%  of  the  young  people  (aged  15-24)  were  employed  in  2006,  up  by  0.4 
percentage  point  a  year  earlier  (33.3%  of  the  young  women  and  39.3%  of  the  young  men) 
varying from 21.7% in Hungary to 66.2% in the Netherlands. However, since 2001 the youth 
employment  rate  has  decreased  by  1.2  percentage  points.  The  differences  between  Member 
States and the decreasing trend may in part be explained by the proportion of people in this 
age group which remain in education.  

EU-wide, 43.5% of the people around the retirement age (55-64 years) were in employment in 
2006, an increase by 0.8 percentage points between 2005 and 2006, after an increase by 1.2 
percentage  points  between  2005  and  2006.  Denmark,  Estonia,  Ireland,  Cyprus,  Latvia, 
Portugal, Finland, Sweden and the United Kingdom have already reached the EU collective 
older  people's  employment  rate  Stockholm  target  of  50%  by  2010.  At  the  other  end  of  the 
scale, less than 30% of older people are working in Poland.  

In the EU-27, the employment rate of older people increased by 5.8 percentage points since 
2001, considerably more than in the case of prime age adults. The employment rate of women 
aged  55-64  increased  more  than  the  male  employment  rate  for  this  age  group.  Despite  this 
trend, the rate for males (52.6%) remained higher than that of females (34.8%). 

Looking  at  more  detailed  age  groups:  the  employment  rate  of  people  aged  55-59  stood  at 
55.9% while it was 28.0% among those aged 60-64. Beyond the age of 65, the employment 
rate  decreases  sharply.  In  the  EU-27,  less  than  5%  of  those  aged  65  and  over  were  in 
employment.  

Exit from the labour force at the age of 60.9 

In the EU-25, the average exit age from the labour force in 2005 was at the age 60.9. This exit 
age mirrors the trend of labour participation of older workers. In Ireland, Portugal, Romania, 

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and Sweden, the average exit age reached 63 years or more.  Men leave the labour force on 
average at the age of 61.4 while women do so about one year earlier. 

Policy context 

The Treaty of Amsterdam took an important step in committing the Union to a high level of 
employment as an explicit objective: "The objective of a high level of employment shall be 
taken  into  consideration  in  the  formulation  and  implementation  of  Community  policies  and 
activities" (Art.127(2)). 

The  Treaty  states  furthermore  that  "the  Community  shall  support  and  complement  the 
activities of the Member States in … equality between men and women with regard to labour 
market opportunities and treatment at work." (Art. 137). 

The Lisbon European Council in March 2000 concluded that "the employment rate is too low 
and  is  characterised  by  insufficient  participation  in  the  labour  market  by  women  and  older 
workers."  The  Lisbon  European  Council  defined  a  strategic  goal  for  the  next  decade  “to 
become the most competitive and dynamic knowledge-based economy in the world capable of 
sustainable economic growth with more and better jobs and greater social cohesion. (…) the 
overall aim should be to raise the employment rate to as close as possible to 70% by 2010 and 
to increase the number of women in employment to more than 60% by 2010. 

The Stockholm European Council in March 2001 agreed intermediate targets for employment 
rates (67% overall and 57% for women by 2005) and a target for employment participation of 
older workers by 2010 (50%).  

The  recent  2005-2008  Employment  Guidelines  (as  a  part  of  Integrated  Guidelines)  specify 
that Member States should implement policies aiming at achieving full employment, quality 
and productivity at work and social cohesion and inclusion (Guideline No 17). 

Besides these overarching objectives, specific guidelines are agreed to attract and retain more 
people in employment, increase labour supply and modernize social protection systems.  

In particular, Member States should promote a lifecycle approach (Guideline No 18) through 
a  renewed  endeavour  to  build  employment  pathways  for  young  people  and  to  reduce  youth 
unemployment;  resolute  action  to  increase  female  participation  and  reduce  gender  gaps  in 
employment,  unemployment  and  pay;  better  reconciliation  of  work  and  private  life  and 
provision of accessible and affordable childcare facilities and care for other dependants; and 
support for active aging, including appropriate working conditions, improved (occupational) 
health status and adequate incentives to work and discouragement of early retirement; modern 
social protection systems.  

Furthermore, Member States should improve matching of labour market needs (Guideline No 
20)  and  improve  adaptability  of  workers  and  enterprises,  through  promoting  flexibility 
combined with employment security and reducing labour market segmentation (Guideline No 
labour  cost  developments  and  wage-setting 
21)  and  ensuring  employment-friendly 
mechanisms (Guideline No 22).  

In the face of economic slowdown, the Spring Council invited the Commission to establish a 
European  Employment  Taskforce.  Under  the  chairmanship  of  Wim  Kok,  the  Taskforce 
reported to the Commission on practical reforms that can have the most direct and immediate 

EN 

132 

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impact  on  the  Employment  Strategy.  The  Report  identified  four  key  conditions  for  success: 
increasing  adaptability  of  workers  and  enterprises;  attracting  more  people  to  the  labour 
market;  investing  more  and  more  effectively  in  human  capital;  and  ensuring  effective 
implementation  of  reforms  through  better  governance.  The  Brussels  European  Council  of 
December 2003 invited the Commission and Council to consider the Taskforce's Report in the 
preparation of the 2004 Joint Employment Report.  

Following the Mid-term review, the Commission presented a Communication on growth and 
jobs of February 2005 which proposed a new start for the Lisbon strategy refocusing efforts 
on two goals: delivering a stronger, lasting growth and more and better jobs. This included a 
complete  revision  of  the  EES  governance  so  as  to  maximise  the  synergies  and  efficiency 
between national measures and Community action.  

The  Spring  European  Council  on  22  and  23  March  2005  adopted  the  European  Youth  Pact 
(7619/1/05,  conclusion  37  and  Annex  I).  A  part  of  this  Pact  is  the  sustained  integration  of 
young  people  into  the  labour  market.  The  European  Youth  pact  is  discussed  in  the 
Commission  communication  of  30  May  2005  "Addressing  the  concerns  of  young  people  in 
Europe  –  implementing  the  European  Youth  pact  and  promoting  active  citizenship" 
(COM(2005) 206 final). 

Methodological notes 

Sources:  Eurostat  Annual  Averages  of  Labour  Force  Data  consist  of  employment  by 
economic  activity  and  status  in  employment,  further  broken  down  by  sex  and  some  job 
characteristics. They are based on the EU Labour Force Survey (LFS) and on the European 
System  of  National  Accounts  (ESA  95).  All  other  data  come  from  the  EU  Labour  Force 
Survey (LFS).  

Quarterly  LFS  data  are  available  since  the  first  quarter  of  2005  in  all  EU  countries,  except 
Luxembourg. Data for France refer to metropolitan France (excluding overseas departments). 
French data for 2006 and German data for 2005 and 2006 are provisional. 

Employment  rates  represent  persons  in  employment  aged  15-64  as  a  percentage  of  the 
population of the same age. Persons in employment are those who during the reference week 
(of the Labour Force Survey) did any work for pay or profit, including unpaid family workers, 
for at least one hour or were not working but had a job or a business from which they were 
temporarily  absent.  The  classification  by  part-time  or  full-time  job  depends  on  a  direct 
question in the LFS. 

Links to other parts of the report 

Education  and  its  outcomes  (2.5),  Lifelong  learning  (2.6),  Unemployment  (2.8),  Labour 
Market Policy expenditure (2.9) and Labour market (Annex 1.3.4). 

Further reading 

•  “Employment  in  Europe  2006",  European  Commission,  Employment  and  Social  Affairs 

DG. 

•  Data in focus (Population and social conditions), n° 5/2007 "Labour market latest trends – 

4th quarter 2004 data", Eurostat. 

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133 

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•  Data  in  Focus  (Population  and social conditions) Theme 3, n° 14/2006 "European Union 

Labour Force Survey- Annual Results 2006", Eurostat. 

•  Economic  Policy  Committee  “Key  structural  challenges  in  the  acceding  countries:  the 
integration of the acceding countries into the Community’s economic policy co-ordination 
processes", European Commission, Economic and Financial Affairs DG, July 2003. 

•  “Employment  precarity,  unemployment  and  social  exclusion"  and  "Inclusion  through 

participation", European Commission DG Research reports 2000. 

•  “Increasing labour force participation and promoting active ageing” Joint report from the 

Commission and the Council to the Barcelona Council, 2002 

•  “Improving quality in work: a review of recent progress”, COM (2003) 728 of 26.11.2003 

•  Statistics  in  Focus  (Population  and  social  conditions),  n°  20/2006  “The  employment  of 

seniors in the European Union”, Eurostat. 

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EU-
27

EU-
25

EA-
13

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Key indicator 7a
Total
64.4 64.7 64.6 61.0 58.6 65.3 77.4 67.5 68.1 68.6 61.0 64.8 63.0 58.4 69.6 66.3 63.6 63.6 57.3 54.8 74.3 70.2 54.5 67.9 58.8 66.6 59.4 69.3 73.1 71.5 55.6
Females 57.2 57.4 56.7 54.0 54.6 56.8 73.4 62.2 65.3 59.3 47.4 53.2 57.7 46.3 60.3 62.4 61.0 54.6 51.1 34.9 67.7 63.5 48.2 62.0 53.0 61.8 51.9 67.3 70.7 65.8 49.4
71.6 72.0 72.6 67.9 62.8 73.7 81.2 72.8 71.0 77.7 74.6 76.1 68.5 70.5 79.4 70.4 66.3 72.6 63.8 74.5 80.9 76.9 60.9 73.9 64.6 71.1 67.0 71.4 75.5 77.3 62.0
Males

Employment rate, 2006 (Employed persons aged 15-64 as a percentage of the population of the same age group)

:
:
:

45.9
23.9
68.1

Key indicator 7b
Total
43.5 43.6 41.7 32.0 39.6 45.2 60.7 48.4 58.5 53.1 42.3 44.1 37.6 32.5 53.6 53.3 49.6 33.2 33.6 30.0 47.7 35.5 28.1 50.1 41.7 32.6 33.1 54.5 69.6 57.4 34.3
Females 34.8 34.9 32.9 23.2 31.1 32.1 54.3 40.6 59.2 39.1 26.6 28.7 35.2 21.9 36.6 48.7 45.1 27.8 27.1 11.2 37.2 26.3 19.0 42.8 34.5 21.0 18.9 54.3 66.9 49.1 25.7
52.6 52.8 50.8 40.9 49.5 59.5 67.1 56.4 57.5 67.0 59.2 60.4 40.1 43.7 71.6 59.5 55.7 38.7 41.4 50.4 58.0 45.3 38.4 58.2 50.0 44.5 49.8 54.8 72.3 66.0 44.4
Males

Employment rate of older workers, 2006 (Employed persons aged 55-64 as a percentage of the population of the same age group)

:
:
:

30.1
16.7
44.1

Source: Eurostat - Quarterly Labour Force Data (QLFD)

Employment rate by sex, 2006
Employed persons aged 15-64 as a percentage of the population of the same age group

100

%

90

80

70

60

50

40

30

20

10

0

Females

Males

Total

DK

NL

SE

UK

AT

CY

FI

IE

EE

PT

DE

SI

LV

CZ

ES

EU-
25

EA13 EU-
27

LT

LU

FR

BE

EL

SK

RO BG

IT

HU MT

PL

HR

TR MK

Source: Eurostat - Labour Force Survey (EU-LFS)

Employment rate by age group and sex, EU-27, 2006
Employed persons as a percentage of the total population of the same age group

%

80.6

67.9

71.9

74.3

57.9

49.1

53.5

88.1

81.8

80.0

Females

Males

Total

64.9

73.2

65.5

55.9

46.7

20.4

16.7

18.6

36.3

20.2

28.0

2.8

6.5

4.4

100

90

80

70

60

50

40

30

20

10

0

15-19

20-24

25-29

30-49

50-54

55-59

60-64

65+

Source: Eurostat - Labour Force Survey (EU-LFS)

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8. 

UNEMPLOYMENT 

In 2006, the unemployment rate went down to 7.9% in the EU-27. Women remained more 
concerned than males by unemployment, although the gap has been narrowing. 

EU-27 unemployment rate down in 2006 

In 2006, the total number of unemployed people in the EU-27 stood at 18.4 million, leaving 
the  unemployment  rate  (as  a  percentage  of  labour  force)  at  7.9%.  Compared  to  2005,  the 
unemployment  rate  decreased  by  0.8  point,  after  no  change  in  2005  and  decrease  of  0.3 
percentage  points  in  2005.  In  2006  the  unemployment  rate  went  down  in  all  countries  but 
Ireland,  Luxembourg,  Hungary,  Malta,  Portugal,  Romania  and  the  United  Kingdom.  In 
Denmark,  Ireland,  Cyprus,  Luxembourg,  the  Netherlands,  Austria,  and  the  United  Kingdom 
the unemployment rate remained below or around 5%. The unemployment rate was highest in 
Poland (13.8%) and in Slovakia (13.4%), despite remarkable decreases in a year by 3.9 and 
2.9 percentage points, respectively.  

Women more likely than men to be unemployed in most Member States  

The  female  unemployment  rate  (8.8%)  in  the  EU-27  remained  higher  than  the  male 
unemployment  rate  (7.2%)  in  2006,  although  this  gap  has  been  on  a  declining  trend.  The 
unemployment  rate  for  women  is  higher  than  that  for  men  in  most  Member  States,  except 
Ireland,  Estonia,  Latvia,  Lithuania,  Romania,  and  the  United  Kingdom.  The  unemployment 
gender gap remained high above 3 percentage points in Greece, Italy and Spain. 

Less people in long-term unemployment in 2006 compared to 2005 

In 2006, 3.6% of the labour force in the EU-27 had been unemployed for at least one year. 
The long-term unemployment rate in the EU-27 decreased in 2006 by 0.4 point compared to 
2005,  the  highest  decrease  since  2000.  In  Denmark  and  Cyprus,  less  than  1%  of  the  labour 
force was affected. In contrast, 7.8% of the active population in Poland and 10.2% in Slovakia 
had been unemployed for at least one year. At close to 5% it also remains high in Germany, 
Greece and Bulgaria.  

Women more affected than men by long-term unemployment 

Unemployment  among  women  remained  much  higher  than  for  men.  While  women  formed 
45%  of  the  EU-27  labour  force,  they  accounted  for  half  of  the  unemployed.  In  the  EU-27, 
similar to overall unemployment rates, long-term unemployment was more prevalent among 
women  than  men  (respectively  4.0%  and  3.3%),  with  the  largest  gender  differences  being 
found in the Czech Republic, Spain, Italy, Poland, Slovakia, and, above all Greece.  

High variations by country for the unemployment rate of young people 

The  unemployment  rate  among  young  people  (15-24  years  old)  in  the  EU-27  was  17.5% 
varying from 6.6% in the Netherlands to 29.8% in Poland. Compared to 2005, it decreased by 
0.9 percentage point. It went down from 18.6% in 2005 to 18% in 2006 for young women and 
from 16.4% to 15.2% for young men. 

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Policy context 

The  Luxembourg  Jobs  Summit  in  November  1997  observed  that  “the  encouraging  growth 
results will not enable to make up for the job losses in the early ‘90s or to achieve the rate of 
employment  growth  needed  to  get  most  of  the  unemployed  into  work”.  It  concluded  that  a 
European Employment Strategy was needed in order to turn back the tide of unemployment. 

The  Lisbon  European  Council  in  March  2000  concluded  that  "long-term  structural 
unemployment  and  marked  regional  unemployment  imbalances  remain  endemic  in  parts  of 
the Union." (Presidency conclusion No. 4). Four key areas were identified as part of an active 
employment policy. One of these was "improving employability and reducing skills gaps, in 
particular  by  …  promoting  special  programmes  to  enable  unemployed  people  to  fill  skill 
gaps." 

The recent 2005-2008 Employment Guidelines (as a part of Integrated Guidelines) continue 
stressing that Member States should implement policies aiming at achieving full employment, 
quality and productivity at work and social cohesion and inclusion (Guideline No 17). 

Besides these overarching objectives, specific guidelines are agreed to attract and retain more 
people in employment, increase labour supply and modernize social protection systems.  

In particular, Member States will promote a lifecycle approach (Guideline No 18) through a 
renewed endeavour to reduce youth unemployment; resolute action to reduce gender gaps in 
unemployment; and better reconciliation of work and private life.  

Additionally,  Member  States  should  ensure  inclusive  labour  markets,  enhance  work 
attractiveness,  and  make  work  pay  for  job  seekers,  including  disadvantaged  people  and  the 
inactive (Guideline No 19) through active and preventive labour market measures including 
early  identification  of  needs,  job  search  assistance,  guidance  and  training,  provision  of 
necessary  social  services;  continual  review  of  incentives  and  disincentives  from  the  tax  and 
benefit  systems;  and  development  of  new  sources  of  jobs  in  services  for  individuals  and 
businesses. 

Furthermore,  Member  States  should  increase  investment  in  human  capital  through  better 
education and skills. In particular, Member States should expand and improve investment in 
human capital (Guideline No 23) and adapt education and training systems in response to new 
competence requirements (Guideline No 24).  

The  Spring  European  Council  on  22  and  23  March  2005  adopted  the  European  Youth  Pact 
(7619/1/05,  conclusion  37  and  Annex  I).  A  part  of  this  Pact  is  the  sustained  integration  of 
young  people  into  the  labour  market.  The  European  Youth  pact  is  discussed  in  the 
Commission  communication  of  30  May  2005  "Addressing  the  concerns  of  young  people  in 
Europe  –  implementing  the  European  Youth  pact  and  promoting  active  citizenship" 
(COM(2005) 206 final). 

Methodological notes 

Source:  Eurostat  –  Harmonised  unemployment  rates  and  the  European  Union  Labour  Force 
Survey (LFS).  

EN 

137 

   EN 

 
Unemployed  people  -  according  to  the  Commission  Regulation  n°  1897/2000  and 
International Labour Organisation (ILO) standards - are those persons aged 15-74 who i) are 
without work, ii) are available to start work within the next two weeks and iii) have actively 
sought employment at some time during the previous four weeks or have found a job to start 
later,  i.e.  within  a  period  of  at  most  3  months.  Unemployment  rates  represent  unemployed 
persons  as  a  percentage  of  the  active  population  of  the  same  age.  The  active  population  (or 
labour force) comprises employed and unemployed persons. 

Links to other parts of the report 

Education and its outcomes (2.5), Employment (2.7), Labour Market Policy expenditure (2.9) 
and Labour market (Annex 1.3.4). 

Further reading 

•  “Employment  in  Europe  2006",  European  Commission,  Employment  and  Social  Affairs 

DG. 

•  Data in Focus (Population  and social conditions) Theme 3, n° 14/2006 "European Union 

Labour Force Survey- Annual Results 2006", Eurostat. 

EN 

138 

   EN 

 
EU-
27

EU-
25

EA-
13

BE

BG

CZ

DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT

RO

SI

SK

FI

SE

UK HR MK

TR

Key indicator 8a
8.2
7.9
Total
7.9
Females 8.8
9.3
9.0
7.4
7.1
7.2
Males

7.9
9.3
6.8

Unemployment rate, 2006 (Unemployed persons as a percentage of the active population)

9.0
9.3
8.6

7.1
8.8
5.8

3.9
4.5
3.3

8.4
9.2
7.7

5.9
5.6
6.2

4.4
4.1
4.6

9.5

8.5

8.9
6.8
13.6 11.6 10.4 8.8
5.4
5.6

8.7

6.3

4.6
5.4
4.0

6.8
6.2
7.4

5.6
5.4
5.8

4.7
6.2
3.5

7.5
7.8
7.2

7.3
8.9
6.5

3.9
4.4
3.5

4.7 13.8 7.7
5.2 14.9 9.0
4.4 13.0 6.5

7.3
6.1
8.2

6.0 13.4
7.2 14.7
4.9 12.3

7.7
8.1
7.4

7.1
7.2
6.9

5.3
4.9
5.7

11.1
12.7
9.8

:
:
:

9.9
10.3
9.7

Source: Eurostat - Unemployment rates (ILO definition)

Key indicator 8b

Long-term unemployment rate, 2006 (Long-term unemployed persons (12 months and more) as a percentage of the active population)

Total
3.6
Females 4.0
3.3
Males

3.6
4.0
3.2

3.6
4.2
3.1

4.2
4.9
3.7

5.0
5.2
4.8

3.9
4.9
3.1

0.8
0.9
0.7

4.7
5.2
4.4

2.8
2.6
3.1

1.4
0.9
1.8

4.8
8.0
2.6

1.8
2.8
1.2

4.0
4.3
3.7

3.4
4.5
2.6

0.9
1.2
0.7

2.5
1.9
3.0

2.5
2.4
2.5

1.4
1.6
1.2

3.4
3.4
3.3

2.9
2.5
3.1

1.7
1.8
1.6

1.3
1.3
1.3

7.8
8.6
7.1

3.8
4.4
3.3

4.2
3.6
4.7

2.9 10.2
3.5 11.2
9.4
2.4

1.9
1.8
2.1

1.1
0.9
1.2

1.2
0.8
1.5

6.7
7.7
5.8

:
:
:

2.5
3.3
2.3

Source: Eurostat - Quarterly Labour Force Data (QLFD)

Unemployment rate (UER) 1998-2006 and long-term unemployment rate (LT UER) 
1998-2006 by sex, EU-25 and EU-27 
Unemployed and long-term unemployed persons (12 months and more) as a percentage of the active 
population

%

13
12
11
10
9
8
7
6
5
4
3
2
1
0

1998

1999

2000

2001

2002

2003

2004

2005

2006

UER total EU-25
UER total EU-27
LT UER total EU-25
LT UER total EU-27

UER females EU-25
UER females EU-27
LT UER females EU-25
LT UER females EU-27

UER males EU-25
UER males EU-27
LT UER males EU-25
LT UER males EU-27

Source: Eurostat - Unemployment rates (ILO definition) and Quarterly Labour Force Data (QLFD)

16

14

12

10

8

6

4

2

0

Unemployment rate and long-term unemployment rate by sex, 2006
(in ascending order by total unemployment rate; Left bar: Females, Right bar: Males)

%

DK

NL

IE

CY

LU

AT

UK

LT

EE

SI

IT

LV

CZ

SE MT

RO HU

PT

FI EU27 EU25 EA13 BE

DE

ES

EL

BG FR

SK

PL

TR

Unemployed at least 12 months

Unemployed less than 12 months 3.6

Source: Eurostat - Labour Force Survey (EU-LFS)

EN 

139 

   EN 

 
 
9. 

LABOUR MARKET POLICY EXPENDITURE 

In 2005, Labour Market Policy (LMP) expenditure accounted for 2.2% of GDP on average 
among  the  fourteen  countries  that  provided  data  within  EU-15.  Expenditure  on  LMP 
measures  (or  Active  Labour  Market  Policies)  amounted  to  0.55%  (0.52%  for  the  EU-27), 
expenditure  on  labour  market  supports  (essentially  unemployment  benefits)  to  1.41% 
(1.36%  for  the  EU-27),  and  expenditure  in  labour  market  policy  services  (Public 
Employment  Services,  PES)  to  0.24%.  Figures  for  2005  confirm  the  existence  of 
considerable heterogeneity across Member States: LMP expenditure ranged from 4.1% in 
Denmark to 0.2% in Estonia. This variation is linked to the extent of non-targeted support 
in  some  countries  (i.e.  policies  which  do  not  target  exclusively  unemployed  and  other 
groups  with  weak  labour  market  attachment  and,  for  this  reason,  are  not  included  in  the 
coverage of the LMP data collection). 

Targeted policies 

Labour market policies are by definition restricted in scope and only cover those interventions 
which are targeted to the unemployed and other groups with particular difficulties in entering 
or remaining in the labour market. Primary target groups in all countries (with the exception 
of  Italy)  are  the  unemployed  who  are  registered  with  the  public  employment  services. 
However,  the  size  and  structure  of  expenditure  on  LMP  are  not  exclusively  driven  by  the 
political  commitment  to  combat  unemployment.  Other  factors,  such  as  the  demographic 
situation and the income level, may affect cross-country variation. 

Expenditure on services, measures and supports 

The LMP database distinguishes three main types of intervention which are broken down into 
nine different categories by type of action.  

LMP  services  (category  1)  covers  ad  hoc  information  services  and  more  formalised 
programmes  of  individual  assistance  to  jobseekers,  together  with  all  other  activities  of  the 
PES  not  specifically  covered  in  other  categories.  Note  that  the  functions  undertaken  by  the 
PES  vary  between  countries  and  this  is  reflected  in  expenditure  differentials.  In  2005, 
expenditure  on  LMP  services  accounted  for  just  over  25  billion  euro  amongst  the  EU-15 
countries – 11% of total LMP expenditure. 

LMP measures (categories 2-7) cover targeted programmes such as training, job rotation/job-
sharing, employment incentives, supported employment and rehabilitation, direct job creation 
and start-up incentives. These are commonly referred to as “active” expenditures. However, it 
should  be  taken  into  account  that  the  distinction  between  active  and  passive  (i.e. 
unemployment benefits) measures is increasingly blurred by the tendency to establish closer 
links  between  eligibility  to  the  latter  and  participation  to  the  former,  in  the  form  of 
individualised job-search assistance and early intervention by the public employment service. 
This  move  reflects  the  increasing  attention  to  the  notion  of  flexicurity  (see  below)  in  the 
setting of labour market policies. In the EU-15 countries, expenditure on LMP measures has 
fallen from a peak of 69 billion euro in 2002 to 56 billion in 2005, just under 25% of the total 
expenditure on LMP. 

EN 

140 

   EN 

 
LMP  supports  (categories  8-9)  cover  expenditure  on  out-of-work  income  maintenance 
(mostly unemployment benefits) and on early retirement and account for the largest share of 
LMP expenditure – on average 64% of the total in the EU-15, in 2005. 

Distribution of expenditure on LMP measures by type of action 

Concerning  the  “ranking”  of  the  categories  in  2005,  expenditure  is  highest  on  training 
programmes, as in previous years, accounting for 39.0% of expenditure on active measures. 
However,  “Direct  job  creation”  which  was  in  2002  the  second  most  important  category, 
accounts  in  2005  for  only  13.8%  of  total  expenditures  on  active  measures,  much  less  than 
expenditure  on  employment  incentives  (23.9%,  which  includes  not  only  subsidies  but  also 
reduction in taxes and social contributions to employers). Expenditure in the integration of the 
disabled  increased  significantly,  reaching  16.6%  of  the  total.  This  increase  is  even  more 
striking in view of the fact that most countries also undertake general employment measures 
which partly go to the benefit of disabled people. Start-up incentives represent nearly 6% of 
active  expenditures,  which  also  implies  a  sizable  increase  with  respect  to  1998  (2.2%).  Job 
rotation/job  sharing  remains  the  smallest  category  in  terms  of  expenditure,  accounting  for 
only 0.6% the total.  

Policy context 

The LMP data collection was developed as an instrument to monitor the evolution of targeted 
employment policies across the EU, following on the "Jobs Summit" held in Luxembourg in 
November 1997, which had launched the European Employment Strategy. More recently, the 
notion  of  flexicurity  has  come  to  the  forefront  of  the  EU  employment  agenda  (see  COM 
2007(359)),  specifically  including  the  provision  of  effective  Active  and  Passive  Labour 
Market Policies among the key instruments aimed at reconciling flexibility and security in the 
EU labour markets. The LMP database has been developed over the past years by Eurostat in 
close  co-operation  with DG Employment and Social Affairs, the EU-15 Member States and 
Norway,  as  well  as  the  OECD.  In  2005  the  project  has  been  extended  to  all  New  Member 
States as well as to Candidate Countries. Additionally, an agreement for a joint data collection 
has  been  concluded  with  the  OECD,  coming  into  effect  with  the  2004  wave  of  LMP  data 
(launched in June 2005). Data for all New Member States and EU27 should be available as of 
2008. 

Methodological notes 

The scope of the LMP database refers to Public interventions in the labour market aimed at 
reaching its efficient functioning and to correct disequilibria and which can be distinguished 
from  other  general  employment  policy  measures  in  that  they  act  selectively  to  favour 
particular groups in the labour market. 

The classification categories by type of action referred to in the graphs presented in this article 
include: 

LMP services - category 1: 

1  –  Labour  Market  Services:  all  services  and  activities  undertaken  by  the  PES  (Public 
Employment Services) together with services provided by other public agencies or any other 
bodies contracted under public finance, which facilitate the integration of the unemployed and 

EN 

141 

   EN 

 
other  jobseekers  in  the  labour  market  or  which  assist  employers  in  recruiting  and  selecting 
staff. 

LMP measures - categories 2-7:  

2 - Training: measures that aim to improve the employability of LMP target groups through 
training, and which are financed by public bodies. All training measures should include some 
evidence  of  classroom  teaching,  or  if  in  the  workplace,  supervision  specifically  for  the 
purpose of instruction. 

3  -  Job  rotation  and  job  sharing:  measures  that  facilitate  the  insertion  of  an  unemployed 
person  or  a  person  from  another  target  group  into  a  work  placement  by  substituting  hours 
worked by an existing employee. 

4 - Employment incentives: measures that facilitate the recruitment of unemployed persons 
and  other  target  groups,  or  help  to  ensure  the  continued  employment  of  persons  at  risk  of 
involuntary job loss. Employment incentives refer to subsidies for open market jobs where the 
public  money  represents  a  contribution  to  the  labour  costs  of  the  person  employed  and, 
typically, the majority of the labour costs are still covered by the employer. 

5  -  Supported  employment  and  rehabilitation:  measures  that  aim  to  promote  the  labour 
market integration of persons with reduced working capacity through supported employment 
and rehabilitation. 

6 - Direct job creation: measures that create additional jobs, usually of community benefit or 
socially  useful,  in  order  to  find  employment  for  the  long-term  unemployed  or  persons 
otherwise difficult to place. Direct job creation refers to subsidies for temporary, non-market 
jobs which would not exist or be created without public intervention and where the majority 
of the labour cost is normally covered by the public finance. 

7  -  Start-up  incentives:  Programmes  that  promote  entrepreneurship  by  encouraging  the 
unemployed and target groups to start their own business or to become self-employed. 

LMP supports - categories 8-9: 

8  -  Out-of-work  income  maintenance:  Programmes  which  aim  to  compensate  individuals 
for loss of wage or salary through the provision of cash benefits when:  

•  A  person  is  capable  of  working  and  available  for  work  but  is  unable  to  find  suitable 

employment. 

•  A  person  is  on  lay-off  or  enforced  short-time  work  or  is  otherwise  temporarily  idle  for 

economic or other reasons (including seasonal effects). 

•  A person has lost his/her job due to restructuring or similar (redundancy compensation). 

9 - Early retirement: Programmes which facilitate the full or partial early retirement of older 
workers who are assumed to have little chance of finding a job or whose retirement facilitates 
the placement of an unemployed person or a person from another target group. 

EN 

142 

   EN 

 
Links to other parts of the report 

Unemployment (2.8), Social benefits (2.11) and Social protection (Annex 1.3.5) 

Further reading 

•  Labour  Market  Policy  Database  -  Methodology,  Revision  of  June  2006  -  Eurostat 

methodologies and working Papers 

•  Labour  Market  Policy  Seminar  of  October  2006,  Eurostat  methodologies  and  working 

papers 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

1998 - Detailed Tables. Eurostat. 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

1999 - Detailed Tables. Eurostat. 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2000 - Detailed Tables. Eurostat. 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2001 - Detailed Tables. Eurostat. 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2002 - Detailed Tables. Eurostat. 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2003 - Detailed Tables. Eurostat 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2004 - Detailed Tables. Eurostat 

•  European  Social  Statistics  -  Labour  Market  Policy  -  Expenditure  and  Participants  -  Data 

2005 - Statistical book 

•  Men and women participating in Labour Market Policies, 2004, Statistics in focus 66/2007 

•  Expenditure on Labour Market Policies in 2004, Statistics in focus 12/2006 

•  Employment in Europe 2006 report – chapter 2 (flexicurity) and chapter 3 (active labour 

market policies). 

EN 

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EU-27 EU-15

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 9

Public expenditure on LMP measures (categories 2-7) as a percentage of GDP, 2005

0.5255 0.5444

0.8522 0.4315 0.1221 1.4327 0.6162 0.047 0.4807 0.0611 0.5826 0.6641 0.4605

:

0.1483 0.1475

:

0.197

:

0.8524 0.458 0.3593 0.517 0.1076 0.1958 0.1701518 0.7113 1.0973 0.1156

:

:

:

Notes:Category 1: Labour Market Services. 
Categories 2-7: Training - Job rotation and job sharing - Employment incentives - Supported employment and rehabilitation - Direct job creation - Start-up incentives.                                                                                                    
Categories 8-9: Out of work income maintenance and support - Early retirement. Estimates for EU-27, EU-15, BE, DK, DE, IE, EL, FR, NL, AT, PT, FI, UK

Source: Eurostat - Labour Market Policy Database (LMP)

%

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

EU-27

Public expenditure on LMP measures 
as a percentage of GDP, 2005

Labour Market Policy expenditure by type of action 
(categories 2-7), EU-27, 2005

LMP services (category 1)

LMP measures (2-7)

LMP supports (8-9)

Start-up 
incentives
6.1%

Direct job 
creation
14.0%

BG DK EE EL FR CY LT HU NL PL RO SK SE

Supported 
employment and 
rehabilitation
16.9%

Training 
38.6%

Job rotation and 
job sharing
0.6%

Employment 
incentives
23.8%

Notes: 1) No data for CY, MT

2) Estimates for EU-27, EU-15, BE, DK, DE, IE, EL, ES, FR, HU, NL, AT, PT, FI, SE, UK.

Source: Eurostat - Labour Market Policy Database (LMP)

3) LU, PL, SI, EU-27: Expenditure data on category 1 is not available.

Source: Eurostat - Labour Market Policy Database (LMP)

EN 

144 

   EN 

 
 
10. 

SOCIAL PROTECTION EXPENDITURE AND RECEIPTS 

There  are  considerable  differences  between  Member  States  for  the  expenditure  as  a 
percentage  of  GDP  and  even  more  in  terms  of  per-capita  PPSs.  Different  countries  have 
markedly  different  systems  for  financing  social  protection,  depending  on  whether  they 
favour social security contributions or general government contributions. 

The  weight  of  social  protection  expenditure  as  a  percentage  of  GDP  in  the  European 
Union shows major disparities between Member States 

In  2004  the  EU-25  countries  devoted  on  average  27.3%  of  their  GDP  to  social  protection 
gross (see methodological notes in portrait 11 "Social benefits") expenditure. In the same year 
this percentage was higher (27.7%) for the aggregate EA-1343, including this area five out of 
the  seven  EU  countries  having  ratios  above  the  average  (Belgium,  Germany,  France,  the 
Netherlands and Austria and, out of EA, Sweden and Denmark all had percentages between 
28.5%  and  33%)  and  excluding  the  countries  occupying  the  lowest  positions  in  ranked  EU 
figures; those last are the Baltic countries devoting to the social protection a part of their GDP 
that  is  less  than  half  as  much  as  done  by  the  countries  with  the  highest  ratios:  Latvia  with 
12.6%, Lithuania with 13.3% and Estonia with 13.4%.  

For  EU-25,  the  value  of  social  protection  expenditure  as  a  percentage  of  GDP  in  2004 
represented  a  stop  after  4  years,  dating  back  at  2000,  of  an  increasing  pattern.  For  the  time 
series of the ratio concerning EA-13 a roughly parallel increasing movement over the period 
2002-2004 (in countertendency with the downwards pattern between 1996 and 2000). These 
pattern are the result of the combined evolutions of social protection expenditures and GDP, 
so that the resulting percentages were affected by the gradual contraction in the growth rate of 
GDP registered between 2000 and 2003 and its new upwards movement in 2004.  

From  a  country-specific  perspective,  there  are  differences  within  EU  member  states  and 
exceptions  to  this  general  situation  that  have  to  be  taken  into  account.  The  general 
performance in 2004, characterized all through EU by larger GDP's growth rates than in the 
previous  year,  was  particularly  affecting  the  share  of  social  protection  expenditure  in  those 
countries where the GDP growth was quite strong: Czech Republic, Cyprus, Latvia, Hungary, 
Poland and Slovakia registered between 2003 and 2004 a reduction of the ratio. 

Between  the  European  countries  for  which  longer  time  series  are  available,  the  patterns  of 
social  protection  expenditure  as  a  percentage  of  GDP  showed  wide  disparities.  For  the 
majority  of  these  countries  (BE,  DK,  IE,  ES,  FR,  LU,  MT,  NL,  FI,  SE  and  UK)  the  period 
2000-2001 was the turning point, ending the decline characterizing the data since 1995-1996. 
The tendency was opposite, even if over a shorter period, in Slovakia, Latvia and Lithuania, 
which  showed  an  increasing  pattern  before  2000  followed  by  a  contraction  along  the 
subsequent five years. Just an increasing tendency characterized almost steadily all the years 
of the series in Slovenia (until 2002), Czech Republic (until 2003) and Portugal (until 2004). 
There was a less regular the tendency in the remaining countries. 

The  increase  of  the  ratio  between  2000  and  2004  was  marked  in  Malta  (2.5  percentage 
points),  Luxembourg  (3  percentage  points)  and  Portugal  (3.2  percentage  points),  with  an 

43 

EA13: All through the text what indicated as EA-13 refers to EA-12; data for Slovenia are not available.  

EN 

145 

   EN 

 
                                                 
overall  growth  over  the  period  levelled  off  at  15%  and,  even  more,  at  20%,  in  Ireland  (2.9 
percentage  points)  and  Cyprus  (3  percentage  points);  the  fall  in  Latvia  and  Slovakia  led  to 
loosing between a 10-18% of their ratio value with a reduction between 2.1 and 2.7 in terms 
of  percentage  points.  It  is  worth  noting  that  often  these  changes  in  the  ratio  can,  to  a  large 
extent,  be  related  to  strong  changes  in  the  speed  of  growth  of  GDP:  for  the  five  years 
considered, this is the case of Ireland, Luxembourg and Malta, on one hand, and, in Latvia on 
the other. 

Cross-country differences are more marked when expenditure is expressed in PPS per 
head of population 

When expressing the expenditure on social protection in terms of per capita PPSs (purchasing 
power  standards),  a  different  picture  is  obtained  with  respect  to  the  previous  analysis 
(expenditure  as  percentage  of  GDP)  in  the  extent  the  "distance"  between  countries  is 
somewhat more pronounced. The 2004 value for expenditure was set at 6188 for the EU-25 
countries, and at 6877 for the EA-13. 

Luxembourg44 gains positions with respect to the previous analysis and, with a value (12180 
PPS  per  capita)  roughly  as  twice  as  the  average  for  EU-25,  clearly  cut  off  all  the  other 
countries with high ranks, Sweden and Denmark (extra EA-13) in the first place. At the other 
extreme, again, the Baltic countries, whose values were around one fourth than EU-25’s. The 
disparities  between  countries  are  partly  related  to  differing  levels  of  wealth  and  also  reflect 
differences in social protection systems, demographic trends, unemployment rates and other 
social, institutional and economic factors. 

Two patterns of funding social protection 

In  2004,  the  main  sources  of  financing  for  social  protection  at  EU-25  level  were  the  social 
contributions,  representing  59.5%  of  all  receipts;  of  the  two  flows  composing  social 
contribution the wider contribute was derived from the employer’s contributions (38.6%); the 
remaining  one,  determined  by  contributions  originating  from  protected  persons45  (20.9%), 
ranked as the third financing source, following general government contributions (37.3%), i.e. 
contributions  derived  from  taxes.  The  incidence  of  social  contributions  rose  to  63%  for  the 
countries in EA-13.  Comparing the years  2000 and 2004 (see annex 1.3),  the  funding share 
between the above mentioned categories is quite steady for both the aggregates. 

The structure of funding is, rather, widely varying between countries, depending strongly on 
country-specific  rules  and  on  the  institutional  reasoning  behind  social  protection  systems 
(“Beveridgian”  or  “Bismarckian”  tradition).  Countries  like  the  Czech  Republic,  Estonia  and 
Belgium  were  characterized  by  higher  social  contributions  (more  than  70%).  Conversely, 
Denmark’s  and  Ireland’s  systems  relied  for  the  60%  of  their  total  receipts  on  government 
funding; Cyprus, the United Kingdom and Sweden followed with a taxes-related financing set 
over 45%. 

44 

45 

Luxembourg is a special case insofar as a significant proportion of benefits (primarily expenditure on 
health  care,  pensions  and  family  benefits)  are  paid  to  persons  living  outside  the  country;  if  this 
particular feature is left out of the calculation, expenditure falls to approximately 10200 PPS per capita. 
Employees, self-employed, pensioners and other persons. 

EN 

146 

   EN 

 
                                                 
General government contributions taking over from social contributions  

The proportion of general government contributions in total funding rose between 2000 and 
2004 by 1.9 percentage points for EU-25 and by 2.1 for EA-13.  

Most of the time, the evolution in the share accounted for by general government is the result 
of a decline in social contributions. On average, the largest changes (as absolute value) within 
the social contribution interested the share accounted for by protected persons in EU-25 and, 
rather, that by employers’ social contribution in EA-13.  

In these five years Cyprus, the Netherlands, United Kingdom, Latvia and Portugal's general 
government  contributions  increased  by  more  than  3  percentage  points  while  in  the  Czech 
Republic, Luxembourg and Slovakia their share in total receipts fell substantially.  

For a few countries there were over the period 2000-2004 significant evolutions concerning 
both the components of social contribution. Along these five years, the Czech Republic raised 
both  the  components  (altogether  5.4  percentage  points),  while,  on  the  contrary,  in  Portugal 
there was a contraction of the two (altogether -5.5 percentage points); a compensation, rather, 
took place in Hungary (employers’ -4.2, protected persons +3.4) and, with opposite direction, 
in the Netherlands (employers’ +4.6, protected persons -3.4).  

For information on the structure of expenditure on social benefits, see next portrait. 

Policy context 

The  EC  Treaty  (Article2)  states  that  "the  Community  shall  have  as  its  task  …  to  promote 
throughout the Community … a high level of … social protection."  

The Lisbon European Council of March 2000 attached great importance to the role of social 
protection  systems  in  the  achievement  of  the  overall  strategic  objective  it  established.  It  set 
out  the  objective  that  the  European  social  model,  with  its  developed  systems  of  social 
protection, must underpin the transformation to the knowledge economy. It went on to state 
that  these  systems  need  to  be  adapted  as  part  of  an  active  welfare  state  to  ensure  that  work 
pays, to secure their long-term sustainability in the face of an ageing population, to promote 
social inclusion and gender equality, and to provide quality health services. 

Subsequent European Councils, in particular Stockholm, Gothenburg and Laeken, decided to 
apply the Open Method of Coordination in specific sectors of social protection, in the field of 
pensions and health and long term care. Besides, the Commission presented its point of view 
on strengthening the social dimension of the Lisbon strategy by streamlining the open method 
of coordination in the field of social protection (COM(2003) 261 final).  

The  2005  Communication  providing  contribution  to  the  Hampton  Court  summit  highlights 
that the responsibility for determining most aspects of financing of social protection remains 
firmly  with  Member  States,  but  it  that  is  highly  relevant  to  enhance  exchanges  and  mutual 
knowledge on how Member States adapt to the various pressures that their social protection 
systems  are  facing.  The  2005  Commission  working  document,  Sustainable  Financing  of 
Social  Policies  in  the  European  Union  (SEC  (2005)  1774),  states  that  "it  is  clear  that 
financing arrangements are critical to ensuring that social policies contribute to growth and 
employment while preserving overall budgetary sustainability".  

EN 

147 

   EN 

 
Methodological notes 

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS). 

Social  protection  encompasses  all  interventions  from  public  or  private  bodies  intended  to 
relieve households and individuals of the burden of a defined set of risks or needs, provided 
that  there  is  neither  a  simultaneous  reciprocal  nor  an  individual  arrangement  involved.  The 
risks or needs that may give rise to social protection are classified by convention under eight 
"social  protection  functions".  See  Social  benefits  (2.11).  Excluded  are  all  insurance  policies 
taken out on the private initiative of individuals or households solely in their own interest.  

The 2004 data are provisional for CZ, DE, ES, FR, IT, LV, LT, NL, PL, PT, RO, SI, SK, SE 
and UK. The 2004 data for EU-25 are estimates. 

The GDP, PPS and population data were extracted in November 2006. This might explain any 
differences from national publications. 

Purchasing  Power  Parities  (PPPs)  convert  every  national  monetary  unit  into  a  common 
reference  unit,  the  purchasing  power  standard  (PPS),  of  which  every  unit  can  buy  the  same 
amount of consumer goods and services across the Member States in a given year. 

Links to other parts of the report 

Labour Market Policy expenditure (2.9), Social benefits (2.11), Income distribution (2.12) and 
Social protection (Annex 1.3.5). 

Further reading 

•  Methodology: "ESSPROS Manual 1996", Eurostat. 

•  “European  Social  Statistics  -  Social  protection  -  Expenditure  and  receipts  1996-2004”, 

2007, Eurostat.  

•  Statistics  in  Focus  (Population  and  social  conditions):  "Social  Protection  in  European 

Union", No. 99/2007, Eurostat. 

EN 

148 

   EN 

 
EU-
27

EU-
25

EA-
13

BE

BG CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU MT

NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 10

Expenditure on social protection as a percentage of GDP, 2004 

2004

:

27.3 27.7

29.3

:

19.6 30.7 29.5 13.4 17.0 26.0 20.0 31.2 26.1 17.8 12.6

13.3

22.6 20.7 18.8 28.5 29.1 20.0 24.9 14.9 24.3 17.2 26.7 32.9 26.3

:

:

:

Note: EA-13 is calculated without the Slovenian data.
Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

Expenditure on social protection in PPS per head of population, 2004

14 000

12 000

0
8
1
2
1

10 000

S
P
P

8 000

6 000

4 000

2 000

 0

6
5
7
8

0
7
4
8

2
6
0
8

6
5
0
8

0
9
8
7

2
7
7
7

9
3
2
7

4
9
9
6

7
9
8
6

7
8
8
6

7
5
2
6

8
8
1
6

2
3
2
5

0
3
8
4

8
3
4
4

9
7
3
4

2
8
0
4

6
0
4
3

1
3
1
3

1
0
0
3

8
6
8
2

3
1
2
2

4
6
0
2

5
2
6
1

8
4
4
1

0
2
2
1

9
8
0
1

LU

SE

DK

AT

NL

BE

FR

DE

UK

FI

EA-13

IT

EU-25

IE

EL

ES

SI

PT

CY

CZ

MT

HU

PL

SK

EE

LT

LV

RO

Notes: 1) EU-27, BG, HR, MK and TR: Not available. 2) EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

Social protection receipts as a percentage of total receipts, 2004

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

DK

IE

CY

UK

SE

LU

FI

IT

PT

LT

EU-
25

PL

AT

DE

EA-
13

LV

HU MT

SI

EL

FR

ES

SK

BE

EE

CZ

NL

General government contributions

Employer's social contributions 

Social contributions of protected persons  Other receipts

Notes: 1) EU-27, BG, RO, HR, MK and TR: Not available. 2) EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

EN 

149 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
11. 

SOCIAL BENEFITS 

In most Member States the largest share of social protection expenditure was assigned to 
the old age and survivors functions, followed by the sickness and health care function. The 
other functions accounted for less than 30% of the total.  

Social benefits are for social protection schemes the most considerable part of expenditure. In 
2004  out  of  the  total  EU-25  expenditure  on  social  protection,  social  benefits  accounted  for 
96.2%, administration costs 3.1% and other expenditure 0.7%.  

The old age and survivors functions account for the major part of benefits 

Among the risks covered by social protection benefits, "old-age" and "survivors'" received in 
EU-25 the largest part of expenditure: 45.9% of total benefits (12.0% of GDP). Countries in 
EA-1346 performed on average quite closely (46.5% of total benefits and 12.3% of GDP) to 
the  EU  globally  considered;  the  time  tendency  in  the  period  2000-2004  for  both  the 
aggregates was a slow decline. 

Differences in countries' distributions for this category of benefits should be read in parallel 
with the most important contributory factor: the age composition of the population. In Italy47, 
historically  (see  the  time  series  back  to  1995),  the  benefits  linked  to  old  age  and  survivors' 
functions  reach  the  highest  levels  in  EU:  in  2004  they  accounted  for  61.3%  of  the  total 
expenditure for benefits and for the highest level (15.4%) as a percentage of GDP (in January 
2004, 25.1% of the population aged 60 or over, while in EU-25 the percentage was 21.7%); 
nevertheless,  the  tendency  for  the  share  in  the  last  5  years  was  downwards.  In  Poland  the 
increasing tendency since 2000 brought the share of old age and survivors' benefits to end up 
in  2004  as  the  second  highest  value  in  EU  (60.1%  of  all  benefits).  Malta  (51.2%),  Greece 
(50.9%) and Latvia (50.0%) were also set fairly above the European average. Ireland48, with 
an age distribution stronger for young people than the European one (in January 2004, 28.4% 
of the population aged 20 or less while in EU-25 the percentage was 22.6%) and an incidence 
for those over 60 of the 15.2%, is in 2004 the country set to the lowest level in EU for benefits 
related to old age and survivors' not only in terms of the total expenditure for benefits but also 
in terms of GDP (3.8%) ;in addition, less and less expenditure in time were addressed to age-
related benefits (from 26.5% of total benefits in 1995 to 23.3% in 2004). 

Analyzing  the  situation  back  in  time  to  the  first  year  available  from  1995  onwards  for  the 
remaining countries, the share of the functions old age and survivor’s developed differently in 
direction  and  speed  through  the  Member  States,  with  the  strongest  relative  increases  in 
Portugal, Finland and the Netherlands, and an important decline in Luxembourg.  

Sickness  and  health  care  benefits  gained  importance  in  most  of  the  countries  with 
respect to the other functions 

46 
47 

48 

EA13: All through the text what indicated as EA-13 refers to EA-12; data for Slovenia are not available.  
In  Italy  such  benefits  also  include  severance  allowances  (TFR-trattamento  di  fine  rapporto),  which 
partly  come  under  unemployment  expenditure.  These  benefits  add  up  to  some  4.1%  of  total  social 
benefits. 
For  Ireland  no  data  are  available  on  (funded)  occupational  pension  schemes  for  private-sector 
employees (by an estimate for 2004 missing amount was about 1.3% of GDP).  

EN 

150 

   EN 

 
                                                 
In  2004,  the  expenditure  for  sickness/health  care  made  up,  both  in  EU-25  and  EA-13,  a 
percentage slightly greater than 28% of all benefits (respectively 7.4% and 7.5% of the GDP). 
For both the aggregates, such values were the result of an increasing tendency, which for the 
EA-13 started back in 1996. 

This class of benefits was the one with the highest relative importance in Ireland (42.1% of 
total benefits and 6.9% of GDP), with an increase from 1995 to 2004 of 5.9 percentage points. 
The Czech Republic spent on sickness/health care more than one third of its 2004 expenditure 
for  benefits  (and  6.7%  of  the  GDP)  but  still,  in  spite  of  the  increasing  tendency  started  in 
2000,  the  level  was  1.9  percentage  points  below  that  recorded  in  1995.  The  lowest  shares 
were  in  Poland  (19.5 %)  and  Denmark  (20.6 %).  In  Denmark  this  share,  however,  slowly 
increasing  in  time,  corresponded  in  2004  to  6.1%  of  its  GDP,  far  apart  from  the  3.8% 
recorded in Poland. 

The measures to cope with health needs absorbed less than 4 % of GDP in Lithuania, Poland 
and  Latvia,  although  in  Latvia  the  increase  of  the  share  in  terms  of  the  overall  benefits’ 
expenditure was more sustained (6.5 percentage points from 1997). The share of sickness and 
health  care  benefits  of  GDP  was  highest  in  France  (8.8%),  the  Netherlands  (8.1%)  and 
Sweden (8.0 %). 

The share of sickness and health care expenditure as a percentage of the expenditure for all 
the  benefits  was  increasing  in  most  countries  during  1995-2004,  especially  in  the  United 
Kingdom, Finland and Sweden. The most important exceptions were Portugal and Germany, 
where the share decreased by 12 % and 16 %, respectively.  

Differing pattern for the other social benefits 

At  an  overall  level,  the  third  type  of  benefits  for  relative  importance  was  the  one  including 
measures covering against the burden of disability (8.1% of total benefits, 2.1% of GDP). In 
the area EA-13 this percentage went down to the 7.3% (1.9%). If on one hand, the share of 
disability  expenditure  was  pretty  much  higher  than  the  average  in  countries  like  Sweden 
(14.8%),  Denmark  (13.9%),  Luxembourg49  (13.5%)  and  Finland  (13.2%),  on  the  other,  it 
stood  quite  below  the  European  level  in  Cyprus,  Greece,  Ireland  and  France  (all  less  than 
6%). 

Nearly  the  same  relative  importance  as  the  previous  function  characterizes  in  EU-25  the 
function family/children. The share of 7.8% in terms of total expenditure for benefits (2.1% of 
GDP) is close but smaller than the portion of resource dedicated in EA-13. From a country-
specific perspective there is rather a greater variability, with a range reaching the upper limit 
with  the  17.4%  of  Luxembourg  and  the  lower  limit  with  Spain,  Italy,  Poland  and  the 
Netherlands well below the 5%. 

The function unemployment accounted for the 6.5% of all benefits in EU-25. The high figures 
found in Spain (12.9%) and Belgium (12.5%) set the share for EA-13 at a higher level, 7.4%. 
Expenditure on this function was less than the 3% of the total in Estonia, Lithuania, Italy, the 
United  Kingdom  and  Hungary.  It  is  worth  noting  that  the  spending  on  of  unemployment 
benefits does not always correlate with the level of unemployment in the various countries, as 

49 

In  Luxembourg  a  new  “dependence  insurance”  scheme  was  introduced  in  1999.  These  benefits 
accounted for 4.5% of total social benefits in 2004. According to the 1996 ESSPROS Manual, most of 
these benefits should be recorded under old-age benefits.  

EN 

151 

   EN 

 
                                                 
there  are  substantial  differences  in  coverage,  the  duration  of  benefits  and  the  level  of 
unemployment benefit. 

See also the previous portrait "Social protection expenditure and receipts". 

Policy context 

In  recent  years  the  cooperation  on  the  European  level  in  the  field  of  social  protection,  in 
particular  pensions,  health  and  long  term  care,  has  made  considerable  progress.  This 
development was characterised by the creation of the "Social Protection Committee" bringing 
together senior officials from Member States and the Commission and by the introduction of 
the Open Method of Coordination in the field of pensions and in the field of health care and 
care for the elderly.  

This  evolution  was  initiated  by  the  European  Council  of  Lisbon  in  March  2000,  which 
mandated  the  preparation,  on  the  basis  of  a  Commission  Communication,  of  a  study  on  the 
future  evolution  of  social  protection  systems.  The  Commission  adopted  in  October  2000  a 
Communication (COM (2000) 622 final) on the "Future Evolution of Social Protection from a 
Long-Term  Point  of  View:  Safe  and  Sustainable  Pensions".  The  European  Council 
highlighted  the  need  for  a  "comprehensive  approach"  to  the  challenge  of  an  ageing  society 
and stressed the importance of both social policy and financial objectives. The 2001 Laeken 
European  Council  endorsed  the  proposition  of  objectives  and  working  methods  in  order  to 
apply  the  Open  Method  of  Coordination  in  the  domain  of  pension  policy.  Member  States 
presented a first round of National Strategy Reports in 2002 and a second in 2005. These have 
been  synthesized  by  the  Commission  in  the  Joint  Report  on  Social  Protection  and  Social 
Inclusion,  endorsed  by  the  European  Council  in  2006  and  in  a  Commission  Services  Paper 
(SEC(2006)304),  Synthesis  Report  on  Adequate  and  Sustainable  Pensions  (and  its  annexes 
including country summaries and horizontal analysis).  

In  the  area  of  health  care,  the  Gothenburg  European  Council  of  2001  asked  the  Council,  in 
conformity with the Open Method of Coordination, to prepare an initial report for the Spring 
European Council in 2002 on orientations in the field of health care and care for the elderly. 
This report based on a Communication from the Commission (COM (2001) 723) stressed that 
health care and long-term care systems in the European Union face the challenge of ensuring 
at  the  same  time  the  following  three  key  objectives:  accessibility,  quality  and  financial 
viability of health and care systems. These three broad goals were endorsed by the Council in 
an initial orientation report on health care and care for the elderly to the Barcelona European 
Council in March 2002. The 2003 Spring European Council highlighted the need to intensify 
the  cooperative  exchange  in  the  field  and  in  April  2004  the  Commission  presented  a 
communication  (COM(2004)  304),which  proposed 
the  Open  Method  of 
Coordination to the area of health and long term care.  

to  extend 

Indeed,  in  a  communication  from  December  2005  (COM  2005  (706))  the  Commission 
proposed  to  create  from  Autumn  2006  a  streamlined  framework  for  further  development  of 
the Open Method of Coordination for social protection and social inclusion. It took account of 
experience gained to date in the development of the OMC and of wider developments, notably 
the revision of the Lisbon Strategy. It aimed to create a stronger, more visible OMC with a 
heightened  focus  on  policy  implementation,  which  will  interact  positively  with  the  revised 
Lisbon  Strategy,  while  simplifying  reporting  and  expanding  opportunities  for  policy 
exchange.  In  March  2006,  the  European  Council  adopted  a  new  framework  for  the  social 
protection and social inclusion process, with a new set of common objectives. These include 

EN 

152 

   EN 

 
three  overarching  objectives  and  objectives  for  each  of  the  three  policy  areas  of  social 
inclusion, pensions and health and long-term care. 

In  June  2006,  the  Social  Protection  Committee  adopted  a  set  of  common  indicators  in  the 
newly streamlined social protection and social inclusion process, including indicators for the 
fields of pensions and health. These indicators are meant to show the evolution as regards the 
objectives.  The  whole  list  consists  of  a  portfolio  of  14  overarching  indicators  (+11  context 
indicators)  meant  to  reflect  the  newly  adopted  overarching  objectives  and  of  three  strand 
portfolios  for  social  inclusion,  pensions,  and  health  and  long-term  care.  In  its  report,  the 
Indicators  Group  working  under  the  auspices  of  the  Social  Protection  Committee  has 
identified a number of dimensions for which indicators need to be further developed, notably 
in  the  areas  of  social  inclusion  (child  well-being,  material  deprivation,  housing),  pensions 
(employment of older workers and private pensions) and health and long term care for which 
the list of indicators adopted is only preliminary.  

A  key  feature  of  the  Open  Method  of  Coordination  (OMC)  is  the  joint  analysis  and 
assessment  by  the  European  Commission  and  the  Council  of  the  National  Action  Plans 
submitted  by  the  Member  States.  The  Joint  Reports  assess  progress  made  in  the 
implementation  of  the  OMC,  set  key  priorities  and  identify  good  practice  and  innovative 
approaches of common interest to the Member States. Member States submitted for the first 
time  integrated  National  Reports  on  strategies  for  social  inclusion,  pensions,  healthcare  and 
long-term care in the autumn 2006. These were synthesised in the 2007 Joint Report on Social 
Protection  and  Social  Inclusion  and  its  supporting  documents  on  horizontal  analysis 
(SEC(2007)329) and country analysis (SEC(2007)272). 

Methodological notes 

Source: Eurostat - European system of integrated social protection statistics (ESSPROS). 

See also the previous portrait Social Protection expenditure and receipts. Social benefits are 
recorded without any deduction of taxes (gross) or other compulsory levies payable on them 
by  beneficiaries.  "Tax  benefits"  (tax  reductions  granted  to  households  for  social  protection 
purposes)  are  generally  excluded.  Social  benefits  are  divided  up  into  the  following  eight 
functions:  Sickness/healthcare,  Disability,  Old 
age,  Survivors,  Family/children, 
Unemployment,  Housing,  Social  exclusion  not  elsewhere  classified  (n.e.c.).  The  Old  age 
function covers the provision of social protection against the risks linked to old age: loss of 
income,  inadequate  income,  lack  of  independence  in  carrying  out  daily  tasks,  reduced 
participation  in  social  life,  and  so  on.  Medical  care  of  the  elderly  is  not  taken  into  account 
(reported under Sickness/health care function). Placing a given social benefit under its correct 
function is not always easy. In most Member States, a strong interdependence exists between 
the  three  functions  Old  age,  Survivors  and  Disability.  For  the  purposes  of  better  EU-wide 
comparability, the Old age and Survivors functions have been grouped together. FR, IRL and 
PT record disability pensions paid to persons of retirement age as benefits under the disability 
function as opposed to the old age function. 

The 2004 data are provisional for CZ, DE, ES, FR, IT, LV, LT, NL, PL, PT, RO, SI, SK, SE 
and UK. The 2004 data for EU-25 are estimates. 

The  GDP  and  population  data  were  extracted  in  November  2006.  This  might  explain  any 
differences from national publications. 

EN 

153 

   EN 

 
Links to other parts of the report 

Ageing of the population  (2.3),  Social  protection expenditure  and receipts (2.10) and Social 
protection (Annex 1.3.5). 

Further reading 

•  Methodology: "ESSPROS Manual 1996", Eurostat. 

•  “European  Social  Statistics  -  Social  protection  -  Expenditure  and  receipts  1996-2004”, 

2007, Eurostat.  

•  Statistics  in  Focus  (Population  and  social  conditions):  "Social  Protection  in  European 

Union", No. 99/2007, Eurostat. 

EN 

154 

   EN 

 
EU-
27

EU-
25

EA-
13

BE

BG CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU MT

NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 11a

Old age and survivors benefits as a percentage of total social benefits, 2004 

2004

:

45.9 46.5

44.1

:

41.1 37.2 43.5 43.7 23.3 50.9 43.7 43.6 61.3 48.3 50.0

47.3

36.5 42.5 51.2 41.6 48.2 60.1 47.2 37.9 44.7 40.1 36.9 40.1 44.6

:

:

: 

EU-
27

EU-
25

EA-
13

BE

BG CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU MT

NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 11b

Sickness and health care benefits as a percentage of total social benefits, 2004 

2004

:

28.3 28.2

27.7

:

35.3 20.6 27.2 31.5 42.1 26.5 30.8 30.0 25.9 24.1 24.5

29.5

25.0 29.5 27.0 30.4 25.0 19.5 30.4 35.9 32.7 30.1 25.5 25.4 30.4

:

:

:

Note: EA-13 is calculated without the Slovenian data.
Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

Structure of social protection expenditure in EU-25, 
2004

Social benefits
96.2%

Old age
39.8%

Disability
7.8%

Sickness/ Health 
care
27.2%

Survivors
4.3%

Housing
1.9%

Unemployment
6.3%

Family/ Children
7.5%

 Social exclusion
1.4%

Administration 
costs
3.1%

Other expenditure
0.7%

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

Social benefits by groups of functions as a percentage of total benefits, 2004 

100%

80%

60%

40%

20%

0%

28.3

45.9

28.2

46.5

IT

PL MT EL

LV CY AT

LT PT EA-
13

EU-
25

SI UK BE ES EE FR DE HU NL CZ SE SK RO DK FI

LU IE

Notes: 1) EU-27, BG, HR, MK and TR: Not available. 2) EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

housing / social
exclusion

unemployment 

family / children

disability

sickness / health
care

old age / survivors

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12. 

INCOME DISTRIBUTION 

As a population-weighted average for EU-27 Member States in survey year 2005 (income 
reference year 2004) the top (highest income) 20% of a Member State's population received 
4.9 times as much of the Member State's total income as the bottom (poorest) 20% of the 
Member State's population. This gap between the most and least well-off people is smallest 
in Sweden (3.3), Slovenia (3.4), and Denmark (3.5). It is widest in Portugal (6.9), Lithuania 
(6.9), Latvia (6.7) and Poland (6.6). 

Member  States  with  lower  levels  of  average  income  tend  to  have  higher  levels  of 
inequality 

In  200550,  the  median51  equivalised  disposable  annual  income  for  thirteen  out  of  the  EU-25 
countries,  including  Germany,  France  and  UK,  was  over  13 000  PPS.  Luxembourg  is  an 
outlier with 27 298 PPS, followed by United Kingdom with 17 792 PPS. A north/south divide 
remains  apparent  amongst  former  EU-15  countries,  with  income  levels  in  Portugal,  Greece 
and  Spain  ranging  between  8 347  and  11 726  PPS.  Italy  differentiates  itself  from  its 
Mediterranean  neighbours  with  an  average  annual  disposable  income  of  13 730  PPS.  An 
east/west, old/new divide is also apparent, although Cyprus (14 646 PPS), Malta (11 021 PPS) 
and  Slovenia  (11 745  PPS)  have  median  incomes  similar  to  those  of  ‘old’  Member  States. 
Median incomes are lowest in some of the Baltic States (less than 5 000 PPS). 

Income distribution can be measured by looking at how total equivalised disposable income is 
shared  among  different  strata  of  the  population  according  to  the  level  of  income.  As  a 
population-weighted  average  amongst  the  Member  States  in  survey  year  2005  (income 
reference  year  2004)  the  top  (highest  income)  20%  of  the  population  received  4.9  times  as 
much  of  the  total  income  as  the  bottom  (lowest  income)  20%  of  the  population.  This 
indicator,  the  inequality  of  income  distribution  (S80/S20  income  quintile  share  ratio),  is 
generally higher in the southern and non-continental Member States (Portugal and Lithuania 
being  the  highest  with  6.9  -  although  Estonia,  Greece,  Spain,  Ireland,  Italy,  Latvia,  Poland, 
Lithuania  and  the  UK  also  find  themselves  above  the  average).  At  the  other  extreme  are 
Sweden (3.3), Slovenia (3.4) and Denmark (3.5). 

Another way of looking at income inequality is to compare the Lorenz curve of actual income 
distribution to the line of perfectly equal income distribution52. Amongst the EU-25 member 

50 

51 

52 

From 2005, cross country comparable data from EU-SILC is available for all EU-25 countries. For EU-
15  countries  except  Germany,  the  United  Kingdom  and  the  Netherlands,  EU-SILC  data  was  also 
available for 2004. For Belgium, Denmark, Greece, Ireland, Luxembourg, Austria and Norway, data is 
available from a 2003 preliminary version of EU-SILC. Bulgaria, Romania and Turkey have launched 
EU-SILC in 2006. In this edition the data for the two new Member States (Bulgaria and Romania) and 
for  Croatia  and  Turkey  are  obtained  from  national  sources  which  are  not  fully  comparable  with  EU-
SILC.  Trends  in  transition  years  cannot  be  interpreted  reliably.  Due  to  differences  between  these 
underlying  sources,  the  indicators  cannot  be  considered  to  be  fully  comparable  either  between 
themselves or with EU aggregates or with data reported in earlier years.  
The median value is generally preferred as the measure of central tendency of incomes since it is less 
affected by values at the extremes of the distribution (rich and poor).  
This can be expressed mathematically as the Gini coefficient (a mathematical expression of the ratio of 
the amount of graph between the line of perfectly-equal distribution and the curve of actual distribution 
to the total amount of graph below the line of perfectly-equal distribution). 

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states, the country closest to equality was Sweden (coefficient 23) and the most unequal was 
Portugal (38). The EU-25 average coefficient was 30. 

In  general,  Member  States  with  higher  levels  of  inequality  tend  to  have  a  lower  level  of 
average  income  (with  the  exception  of  the  United  Kingdom,  which  has  both  above  average 
income and above average inequality). 

Policy context 

The EC Treaty (Article 2) states that "The Community shall have as its task … the raising of 
the  standard  of  living  and  quality  of  life…".  Article  3  continues  "the  activities  of  the 
Community shall include … the strengthening of economic and social cohesion;"  

The  Lisbon  European  Council  in  March  2000  set  itself  "a  new  strategic  goal  for  the  next 
decade: to become the most competitive and dynamic knowledge-based economy in the world 
capable  of  sustainable  economic  growth  with  more  and  better  jobs  and  greater  social 
cohesion."  See  also  Communication  adopted  by  the  Commission  in  March  2000  entitled 
"Building an Inclusive Europe". 

The  Lisbon  Strategy  was  relaunched  in  2005  focussing  on  growth  and  jobs.  Summit 
presidency conclusions reaffirmed that the Open Method of Coordination in the field of social 
inclusion  would  continue  in  parallel,  "feeding-in"  to  the  Lisbon  Strategy  and  Sustainable 
Development Strategy (and vice versa). 

The  Social  Policy  Agenda  (COM(2000)  379  final)  states  that  "social  transfers  covering 
pensions  and  social  security  do  not  only  contribute  to  balance  and  re-distribute  incomes 
throughout lifetimes and across social groups, but also support better quality in employment, 
with consequent economic benefits." 

In  March  2006  the  Employment,  Social  Policy,  Health  and  Consumer  Affairs  (EPSCO) 
Council  adopted  streamlined  objectives  across  the  Open  Method  of  Coordination  in  social 
inclusion, pensions and healthcare. 

A list of statistical “structural indicators” was agreed at the Nice summit in December 2000, 
including  7  indicators  in  the  field  of  social  cohesion.  This  list  has  been  updated  for  the 
Synthesis  Report  from  the  Commission  to  the  Barcelona  Council  in  March  2002.  This 
approach  has  been  further  developed  by  the  Indicators  Sub-Group  of  the  Social  Protection 
Committee, who proposed a list of “cohesion indicators” which was adopted by the Laeken 
summit in December 2001. The Indicators Sub Group continues to refine and extend this list. 
In  May  2006,  the  Social  Protection  Committee  endorsed  new  best  practice  criteria  for 
indicator  design  and  adopted  proposals  for  a  portfolio  of  overarching  indicators  and  for 
streamlining the social inclusion, pensions and health portfolios, setting the framework for the 
monitoring of national strategy reports which covered the period 2006-2008. 

Methodological notes 

Sources:  

-  Eurostat  -  European  Community  Household  Panel  (ECHP),  Users'  Data  Base  version 
December 2003; for data until 2001 

- national data in the transition period 

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For  EU-25  Eurostat  –  Community  Statistics  on  Income  and  Living  Conditions  EU-SILC 
(2005)  income  data  2004;  except  for  UK,  income  year  2005  and  for  IE  moving  income 
reference period (2004-2005).  

New member states: For Bulgaria and Romania data is derived from the national Household 
Budget Survey (HBS), 2005, income data 2005. 

Candidate countries: For Croatia data is derived from the national Household Budget Survey 
(HBS)  2004,  income  data  2004,  for  Turkey  data  is  derived  from  the  national  Household 
Income, Consumption and Expenditure (HICE) survey 2004, income data 2004. 

EU aggregates are Eurostat estimates are obtained as a population size weighted average of 
national data. 

In EU-SILC the total income of each household (net or gross - from 2007 all countries using 
EU-SILC will supply gross data) is calculated by adding together the income received by all 
the members of the household from all component sources in the year preceding the survey 
year  for  most  participant  countries53.This  includes  income  from  work,  private  income  (e.g. 
from investments or property), as well as pensions and other social transfers directly received. 
During  the  transition  period  to  full  implementation,  no  account  is  taken  of  indirect  social 
transfers,  imputed  rent  for  owner-occupied  accommodation,  mortgage  interest  payments, 
receipts  in  kind  (for  former  EU-15  Member  States:  it  is  taken  into  account  for  the  new 
member states). These income components will be mandatory only from 2007. As the weight 
of  these  income  components  varies  between  countries,  there  is  some  limitation  on  the  full 
comparability  of  income  statistics.  Moreover,  due  to  the  practical  differences  in  the 
underlying  national  data  sources  during  the  transition  period,  derived  indicators  cannot  be 
considered to fully comparable either between countries or over time.  

In order to take account of differences in household size and composition in the comparison 
of  income  levels,  the  household's  total  income  is  divided  by  its  'equivalent  size',  computed 
using  the  modified  OECD  equivalence  scale.  This  scale  gives  a  weight  of  1.0  to  the  first 
person aged 14 and over, 0.5 to the second and each subsequent person aged 14 and over, and 
0.3 to each child aged under 14 in the household.  

To  calculate  the  income  quintile  share  ratio,  persons  are  first  ranked  according  to  their 
equivalised income and then divided into 5 groups of equal size known as quintiles. S80/S20 
income  quintile  share  ratio  represents  the  sum  of  the  income  received  by  the  20%  of  the 
population with the highest income (top quintile) to that received by the 20% of the population with 
the lowest income (lowest quintile). 

Links to other parts of the report 

Social  protection  expenditure  and  receipts  (2.10),  Low-income  households  (2.13),  Jobless 
households and low wages (2.14) and Income, social inclusion and living conditions (Annex 
1.3.6). 

53 

In  EU-SILC  2005  income  data  is  from  2004;  except  for  UK,  income  year  2005  and  for  IE,  moving 
income reference period (2004-2005). 

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Further reading 

•  “European social statistics: Income, Poverty and Social Exclusion 2nd report", 2003 edition.  

•  Statistics in Focus (Population and social conditions): “Poverty and social exclusion in the 

EU after Laeken-part 1”, No.8/2003. Eurostat. 

•  Statistics in Focus (Population and social conditions): “Poverty and social exclusion in the 

EU after Laeken-part 2”, No.9/2003. Eurostat. 

•  Statistics in Focus (Population and social conditions): “Monetary poverty in EU Acceding 

and Candidate Countries”, No.21/2003. Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  “Social  protection:  cash  family 

benefits in Europe”, No.19/2003. Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  “The  social  protection  in  Europe”, 

No.3/2003. Eurostat. 

•  Statistics in Focus (Population and social conditions): “Monetary poverty in new Member 

States and Candidate Countries”, No.12/2004. Eurostat. 

•  Statistics in Focus (Population and social conditions): “Poverty and social exclusion in the 

EU”, No.16/2004. Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  "In  Work  Poverty  ",  No.  5/2005. 

Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  "Income  poverty  and  social 

exclusion in EU25", No. 13/2005. Eurostat. 

•  Statistics  in  Focus  (Population  and  social  conditions):  "Material  Deprivation  in  the  EU", 

No. 21/2005. Eurostat. 

•  “Joint  Report  on  Social  Protection  and  Social  Inclusion  2007”,  2007,  European 
for  Employment,  Social  Affairs  and  Equal 

Commission,  Directorate-General 
Opportunities. 

•  “A new partnership for cohesion – Third report on Economic and Social Cohesion”, 2004. 

European Commission, Regional Affairs DG.  

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EU-
27

EU-
25

EA-
13

BE

BG

CZ

D K

DE

EE

IE

EL

ES

FR

IT

C Y

LV

LT

LU

HU

MT N L

AT

PL

PT R O

SI

SK

FI

SE

U K H R MK

T R

Key indicator 12

Inequality of incom e distribution (S8 0/S 20 incom e quintile share ratio), 2005 (The ratio o f total income receive d by the 20%  of the 
popula tion  with  the highest income (top q uintile) to th at received by the  20 % o f th e po pulation with the  lowest income (lowest quintile). Income 
must be u ndersto od a s disposable equivali sed income.)

4 .9 s 4.9  s  4.6 s

4. 0

3.7  i  3 .7 b  3 .5

3.8  b

5. 9

5.0

5.8

5 .4

4 .0

5.6 4.3  b  6. 7 b  6 .9 b 

3 .8

4.0 b   4.1 b  4.0 b   3.8 6.6  b  6. 9 b  4.9 i 3.4 b  3.9 b  3.6

3.3 5.8  b 4.8 i

:

10.0  i

Source:  SILC(2005) income dat a  2004; except for UK, income year  2005 and for IE moving  income reference period (2004-2005). 
(1)  BG and RO  National HBS  2005, income dat a 2005. 
(2)  HR National HBS 2004, inc ome data 2004, TR National HICE survey  2004, income dat a 2004.
EU Aggregat es: Eurostat estimates are obtained as a population size  weighted average of  national data.

n
o
i
t
u
b
i
r
t
s
d
e
m
o
c
n

i

i

f
o

y
t
i
l

a
u
q
e
n
I

8

7

6

5

4

3

2

1

0

Level of income and inequality of income distribution (S80/S20 income quintile share ratio), 2005

LT

LV

PL

EE

PT

EL

ES

HU

SK

CZ

MT

SI

IT

EU-25

CY

UK

IE

BE

NL

FR

DE

FI

SE

AT

DK

Median annual equivalised disposable income in EUR

5 000

10 000

15 000

20 000

25 000

Source: SILC(2005) income  data 2004; except for UK,  income year 2005 and for IE moving income reference  period  (2004-2005). 
(1) BG and RO National HBS 2005, income  data  2005. 
(2) HR National HBS 2004, income data 2004, TR National HICE survey 2004, income data 2004.
EU Aggregates:  Eurostat estimates are obtained  as a population size weighted average of national data.

Gini coefficient, 2005

MK

TR

43

HR

UK

34

SE

FI

30

23

SK

SI

26

26

24

RO

31

38

PT

36

PL

AT

26

27

28

EU-
27

45
40
35
30
25
20
15
10
5
0

EU-
25 EA-13

30

29

BE

BG

28

25

26

24

26

CZ

DK

DE

34

EE

32

33

IE

EL

32

28

ES

28

26

29

33

FR

NL

MT

HU

LU

36

LV

36

LT

IT

CY

Source: SILC(2005) income  data 2004; except for UK,  income year 2005 and for IE moving income reference  period  (2004-2005). 
(1) BG and RO National HBS 2005, income  data  2005. 
(2) HR National HBS 2004, income data 2004, TR National HICE survey 2004, income data 2004.
EU Aggregates:  Eurostat estimates are obtained  as a population size weighted average of national data.

EN 

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13. 

LOW-INCOME HOUSEHOLDS 

In 2005 around 16% of households in the EU-27 had an equivalised disposable income that 
was  less  than  60%  of  their  respective  national  median  in  2005  –  these  citizens  are 
considered to be at risk of poverty54. Using 60% of the national median equivalised income 
as a cut-off threshold, the proportion of people at-risk-of-poverty after social transfers had 
been taken into account was highest in Lithuania and Poland, followed by Ireland, Greece, 
and  Spain.  It  was  lowest  in  Sweden  (9%),  followed  by  the  Czech  Republic  (10%)  and  the 
Netherlands (11%). The proportion of people being at-risk-of-poverty was still relatively low 
(12%) in Denmark, Austria and Finland. In this context it should be remembered that with 
the  at-risk-of-poverty  rates  we  are  analysing  relative  poverty  within  each  country  and 
relative  to  median  income  and  not  absolute  poverty  by  reference  to  an  independent  or 
common cut-off threshold. When analysing the hypothetical case of the complete absence 
of  social  transfers  (except  pensions),  in  EU-27  countries  an  average  of  26%  of  the 
population would be at-risk-of-poverty. In the majority of countries, social benefits reduce 
the proportion of people at risk of poverty between 25% and 50%.  

The  household  types  most  at-risk-of-poverty  are  single  parents  with  dependent  children, 
single elderly people and single females 

While  the  overall  at-risk-of-poverty  rate  for  EU-27  is  16%  using  income  data  for  2004-5 
(survey  data  2005),  some  household  types  are  exposed  to  a  much  greater  poverty  risk  than 
others.  In  EU-25  countries  single  parents  with  dependent  children  have  the  highest  poverty 
risk  –  31%  have  an  equivalised  disposable  income  lower  than  60%  of  national  median 
equivalised income.  

Households composed  of a  single adult  older than 65 had  an at-risk-of-poverty rate  of 25% 
(EU-25)  using  2005  figures.  The  poverty  risk  of  single  adults  aged  65  and  over  is  very 
unevenly distributed across member states, with values ranging from 7% in Luxembourg, the 
Netherlands and Poland, to 62% in Ireland and 70% in Cyprus.  

A  quarter  (25%)  of  single  females  was  at  risk  of  poverty  in  EU-25  countries  in  2005.  In 
Ireland (53%) and Cyprus (59%) well over half of single females were at risk of poverty in 
2005. In only six EU-25 countries (Czech Republic 16%, Hungary 15%, Luxembourg 13%, 
the  Netherlands  12%,  Poland  12%  and  Slovakia  16%)  the  at-risk-of-poverty  rate  for  single 
females  was  equal  to  or  below  the  EU-25  average  at-risk-of-poverty  rate  for  all  household 
types  (16%).  Poland  seems  to  be  atypical  in  this  respect  as  it  is  the  only  country  where  the 
poverty risk of single females is lower than the national average (and also lower that of single 
male households).  

The  poverty  risk  of  single  parents  and  their  dependent  children  varies  much  between 
countries 

In  Malta  (49%)  and  Lithuania  (48%)  almost  half  of  households  composed  of  single  parents 
and  their  dependent  children  were  at-risk-of  poverty.  Ireland  (45%)  and  Greece  (44%)  also 
record  a  comparatively  high  proportion  of  those  households  at-risk-of-poverty.  The  poverty 
risk of single parent households is lowest in the Nordic Member States. Within the EU, the 

54 

See the first footnote in the portrait nr. 12 "Income distribution". 

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lowest poverty risk for this household type is in Sweden (18%), followed by Finland (20%) 
and Denmark (21%).55 

Uneven poverty risk between generations  

The distribution of poverty risk among different age groups follows a U-shaped curve in most 
countries. In 2005 19% of young people under 24 lived in low income households in EU-25 
member  states.  For  working  age  adults  (aged  24-64)  the  risk  of  living  in  a  low  income 
household was lowest (14%). 19% of people aged 65 and over lived at risk of poverty in EU-
25 countries in 2005.  

Women (compared with men) and children (compared with adults) are more likely to be 
poor 

In the survey used for compiling the risk of poverty, no information can be obtained about the 
allocation of income within a household, and in particular, between people of different gender 
living  in  one  household,  so  some  caution  is  necessary  in  interpreting  these  figures.  In  a 
household  composed  of  more  than  one  individual,  we  cannot  automatically  assume  that  all 
household  members  have  equal  access  to  money,  and  therefore  cannot  know  whether  they 
should  be  considered  as  "poor"  or  "not  poor".  What  we  can  say,  is  that  certain  types  of 
households are more at risk of poverty than others.  

Throughout Europe in 2005, the probability of living in a household which can be considered 
to  be  at  risk-of-poverty  is  slightly  more  prevalent  among  women  than  among  men  (EU-25 
average of 17% versus 15%), although in Denmark, Luxembourg, the Netherlands, Romania 
and Slovakia there is parity, whilst for Hungary and Poland, it is men who are very slightly 
more at risk.  

Among household types composed of a single individual, where questions of intra-household 
allocation are irrelevant, 25% of single women households were at risk of poverty in the EU-
25 in 2005, compared to 22% of single men households. However, there is no uniform picture 
of this across countries: While Ireland (53% of single women at risk of poverty compared to 
45% of men) and Cyprus (59% of single women at risk of poverty compared to 29% of men) 
had a very high poverty risk for single women in 2005, this does not hold for all countries. 
Indeed, in eight EU-27 countries, the poverty risk was higher for single men than for single 
women, with the difference in poverty rates being particularly marked (5 percentage points or 
more difference) in Lithuania, Hungary, the Netherlands and Poland.  

In 2005 (EU-25), the proportion of children (under the age of 18) living in a household with 
low income (19%) is higher than for the adult population (15%). The proportion of children 
living  in  a  low  income  household  is  highest  in  Spain  (24%),  Italy  (24%),  Lithuania  (27%), 
Poland  (29%)  and  Portugal  (24%).  By  contrast,  in  2005,  children  in  Denmark,  Cyprus  and 
Finland were less likely to live in 'poor' households than adults. In this context, it also has to 
be noted, that households composed of two adults and three or more dependent children were 
50% more likely to be at-risk-of-poverty than other household types (24% compared to 16% 
for all household types). 

55 

The  EFTA  countries  among  Scandinavian  countries  also  record  a  low  risk  of  poverty  with  14%  for 
Iceland and 19% for Norway. 

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The impact of benefits on the proportion of poor people is significant 

A  comparison  of  the  number  of  people  on  low  incomes  before  social  benefits  other  than 
pensions and those on low incomes after social benefits (i.e. old age pensions and survivors' 
benefits are included in income both 'before' and 'after'), illustrates one of the main purposes 
of such benefits: their redistributive effect and, in particular, their ability to alleviate the risk 
of poverty and reduce the percentage of population having to manage with a low income.  

In  2005,  the  average  at-risk-of-poverty  rate  in  EU-27  countries  was  26%  before  social 
transfers  other  than  pensions  were  taken  into  account  and  16%  when  calculated  after  social 
transfers were taken into account. So social transfers were successful in lifting 38% of persons 
with low income above the poverty line.  

Social benefits other than pensions reduce the percentage of people at risk of poverty in all the 
countries,  but  to  very  disparate  degrees.  The  reduction  is  smallest  (less  than  25%)  in  some 
Mediterranean  States  (Greece,  Spain,  Italy,  Cyprus,  Malta  and  Portugal),  Latvia,  Estonia, 
Bulgaria and the candidate country Turkey. The reduction is greatest in Sweden (69%). The 
Czech Republic, Denmark, France, Hungary, the Netherlands, Austria, Slovenia and Finland 
also record reductions due to social transfers of 50% or more.  

In  the  absence  of  social  benefits  other  than  pensions,  in  2005  in  four  member  states 
(Denmark,  Ireland,  Poland  and  the  United  Kingdom)  30%  or  more  of  the  population  would 
have been at-risk-of-poverty.  

EU poverty gap over one fifth of threshold value 

Looking at income below the poverty line identifies those people at risk of income poverty, 
but does not show how whether these persons can really be considered as poor56. The relative 
median  at-risk-of-poverty  gap  measures  the  difference  between  the  at-risk-of-poverty 
threshold (60% of national median equivalised income and the median equivalised disposable 
income of persons below the at-risk-of-poverty threshold, expressed as a percentage of the at-
risk-of-poverty threshold. Measuring the gap between the median level of income of the poor 
and the at-risk-of-poverty threshold provides an insight into the depth of income poverty - the 
poverty  gap.  In  2005,  the  relative  median  at-risk-poverty  gap  equalled  23%  in  EU-25 
countries  and  EU-15  countries.  While  the  average  EU-25  at-risk-of-poverty  threshold 
measured 8 275 Euros in the EU-25, this amounts to a relative poverty gap of roughly 1 903 
Euros  in  equivalised  disposable  income.  The  at-risk-of-poverty  threshold  varied  between 
17 087 Euros in Luxembourg and 726 Euros in Romania. This illustrates the high differences 
in income in member states and that the poverty risk indicator and other derived from it are 
measures  of  relative  poverty.  It  should  be  noted  here  that  median  income  levels,  whether 
compared nominally (in Euros or national currency) or with a measure of purchasing power 
standards (PPS) are markedly lower in most new Member States than in the EU-15 countries.  

More than 35 million people in EU-15 living in persistent risk of poverty  

In 2001, 9% of the EU-15 population were living in a low-income household and had been in 
this situation for at least two of the three preceding years. This figure suggests that more than 

56 

The at-risk-of-poverty rate measures low income, not wealth. Households may have low income for a 
certain year, but still not be "poor" because they have some wealth to draw on.  

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half of all people in low income households are living at-persistent-risk-of-poverty. In 2001, 
the at-persistent-risk-of-income-poverty rate ranged from around 6% in Germany, Denmark, 
Netherlands  and  Finland  up  to  15%  in  Portugal.  No  data  is  currently  available  for  New 
Member States for this indicator57. 

Low income does not necessarily by itself imply low living standards, and in the short term 
consumption expenditure can sometimes be maintained in a number of ways, including use of 
accumulated savings, asset sales and access to credit. Typically it is the cumulative negative 
impact  of  persistent  and/or  multiple  disadvantages,  which  may  lead  to  poverty  and  social 
exclusion. The high levels of persistent risk reported for certain countries are consequently a 
source of particular concern. 

Policy context 

Art.136  of  the  EC  Treaty  lists  "the  combating  of  exclusion"  as  one  of  the  six  objectives  of 
European  social  policy.  Art.137.1  cites  the  integration  of  people  excluded  from  the  labour 
market as one of the fields in which Community action should support and complement the 
activities  of  Member  States.  Art.137.2  creates  scope  for  action  at  Community  level  by 
encouraging  "co-operation  between  Member  States  through  initiatives  aimed  at  improving 
knowledge,  developing  exchanges  of  information  and  best  practices,  promoting  innovative 
approaches and evaluating experiences in order to combat social exclusion." 

The  Lisbon  European  Council  in  March  2000  concluded  that  "the  number  of  people  living 
below the poverty line and in social exclusion in the Union is unacceptable" and that "the new 
knowledge-based  society  offers  tremendous  potential  for  reducing  social  exclusion" 
(Presidency  conclusion  No.32).  This  conclusion  was  reinforced  at  the  Nice  and  Stockholm 
summits in December 2000 and Spring 2001. 

The Social Policy Agenda (COM (2000) 379 final) also addresses the issues of poverty and 
social exclusion. The main objective is "to prevent and eradicate poverty and exclusion and 
promote  the  integration  and  participation  of  all  into  economic  and  social  life."  (Section 
4.2.2.1). 

The  Lisbon  Council  agreed  that  Member  States’  policies  for  combating  social  exclusion 
should be based on an Open Method of Coordination combining common objectives, National 
Action Plans and a programme presented by the Commission to encourage cooperation in this 
field. The Nice European Council in December 2000 adopted the common objectives in the 
fight  against  social  exclusion  and  poverty:  "to  facilitate  participation  in  employment  and 
access by all to the resources, rights, goods and services; to prevent the risks of exclusion; to 
help the most vulnerable; to mobilise all relevant bodies." 

Key  elements  of  the  Open  Method  of  Coordination  are  the  definition  of  commonly  agreed 
objectives for the European Union (EU) as a whole, the development of appropriate national 

57 

During the transition to data collection under the EU-SILC regulations, statistics are currently neither 
available for the ‘new’ Member States, in the absence of a comparable national source of longitudinal 
panel data nor for more recent years. As the majority of countries have launched EU-SILC in 2005 and 
it requires four years of survey data to produce the ‘persistent risk of poverty’ indicator, results covering 
all  EU-25  member  states  will  first  be  available  for  the  survey  year  2008.  First  results  for  countries 
which  have  launched  an  advance  version  of  EU-SILC  in  2003  will  be  available  for  the  survey  year 
2006.  

EN 

164 

   EN 

 
                                                 
action plans to meet these objectives, and the periodic reporting and monitoring of progress 
made. 

Similar  approaches  were  subsequently  adopted  in  many  other  areas,  including  economic 
policy,  employment,  education,  sustainable  development,  social  inclusion,  social  protection, 
etc.  

Efforts  were  made  since  2003  to  create  better  links  between  separate  processes  (notably 
between social inclusion and social protection themes on the one hand and Broad Economic 
Policy  Guidelines  and  European  Employment  Strategy  on  the  other),  and  these  links  came 
under intense scrutiny during the mid-term review of the Lisbon Strategy. It was eventually 
decided to continue in parallel, with each policy 'pair' feeding-in to the other. 

In  March  2006  the  Employment,  Social  Policy,  Health  and  Consumer  Affairs  (EPSCO) 
Council  adopted  streamlined  objectives  across  the  Open  Method  of  Coordination  in  social 
inclusion, pensions and healthcare. 

Commonly agreed indicators have been developed by the Indicators Sub-Group of the Social 
Protection Committee. A first set of indicators was adopted at the Laeken European Council 
in December 2001. In May 2006, the Social Protection Committee endorsed new best practice 
criteria  for  indicator  design  and  adopted  proposals  for  a  portfolio  of  overarching  indicators 
and  for  streamlining  the  social  inclusion,  pensions  and  health  portfolios,  setting  the 
framework for the monitoring of national strategy reports which cover the period 2006-2008. 

Methodological notes 

Sources:  

For  EU-25  Eurostat  –  Community  Statistics  on  Income  and  Living  Conditions  EU-SILC 
(2005)  income  data  2004;  except  for  UK,  income  year  2005  and  for  IE  moving  income 
reference period (2004-2005).  

New member states: For Bulgaria and Romania data is derived from the national Household 
Budget Survey (HBS), 2005, income data 2005.  

Candidate countries: For Croatia data is derived from the national Household Budget Survey 
(HBS)  2004,  income  data  2004,  for  Turkey  data  is  derived  from  the  national  Household 
Income, Consumption and Expenditure (HICE) survey 2004, income data 2004. 

EU aggregates are Eurostat estimates are obtained as a population size weighted average of 
national data. 

The  poverty  risk  or  relative  monetary  poverty  rate  (indicator:  at-risk-of-poverty  rate)  is 
measured in terms of the proportion of the population with an equivalised income below 60% 
of the median equivalised disposable income in each country. The median income is preferred 
over the mean income as it is less affected by extreme values of the income distribution.  

The  relative  median  at-risk-of-poverty  gap  is  defined  the  difference  between  the  at-risk-of-
poverty  threshold  (cut-off  point:  60%  of  median  equivalised  disposable  income)  and  the 
median  equivalised  disposable  income  of  persons  below  the  at-risk-of-poverty  threshold, 
expressed  as  a  percentage  of  the  at-risk-of-poverty  threshold.  See  the  portrait  "Income 
distribution" (2.12) for definition of income concepts and notes on data.  

EN 

165 

   EN 

 
Links to other parts of the report 

Employment  (2.7),  Social  protection  expenditure  and  receipts  (2.10),  Income  distribution 
(2.12),  Jobless  households  and  low  wages  (2.14),  and  Income,  social  inclusion  and  living 
conditions (Annex 1.3.6). 

Further reading 

•  “European  social  statistics:  Income,  Poverty  and  Social  Exclusion  2nd  Report”,  2003 

edition. Eurostat. 

•  Statistics in Focus (Population and social conditions): “Monetary poverty in EU Acceding 
and  Candidate  Countries”,  No.21/2003.  “Poverty  and  social  exclusion  in  the  EU  after 
Laeken-part1”,  No.8/2003.  “Social  protection:  cash  family  benefits 
in  Europe”, 
No.19/2003.  “Persistent  income  poverty  and  social  exclusion  in  the  European  Union”, 
No.13/2000.  “The  social  protection  in  Europe”,  No.3/2003.  “Income  poverty  in  the 
European  Union:  Children,  gender  and  poverty  gaps",  No.12/2000.  “Social  benefits  and 
their  redistributive  effect  in  the  EU",  No.9/2000.  “Social  exclusion  in  the  EU  Member 
States”,  No.1/2000.  “Low  income  and  low  pay  in  a  household  context  (EU-12)”, 
No.6/1998. Eurostat. 

•  “Joint  Report  on  Social  Protection  and  Social  Inclusion  2007”,  2007,  European 
for  Employment,  Social  Affairs  and  Equal 

Commission,  Directorate-General 
Opportunities. 

EN 

166 

   EN 

 
EU-
27

EU-
2 5

EA-
13

BE

BG C Z D K D E

EE

IE

EL

ES

F R

IT

CY

LV

L T

LU

HU MT

NL

AT

PL

PT

RO

SI

SK

F I

SE

UK

HR MK T R

Key indicator 13a

At-risk-of-poverty rate before socia l transf ers , 2005 (The percentage of persons with an equivalised disposable income, before soci al 
transfers, below the risk-of- poverty threshold, which is set at 60% of the nati onal median equi vali sed  disposable  income (after social 
transfers). Retire ment and survivo r's pensions a re coun ted as i nco me  before transfers and not as social  transfer s.)

T otal
2 6 s 26 s  24 s
F emales 2 6 s 27 s  25 s
2 5 s 25 s  23 s
Ma les

28
29
27

17  i 21 b 
19  i 22 b 
15  i 20 b 

30
31
28

2 4
23  b
24  b
2 5
22  b  2 3

32
34
30

23
24
21

24
25
23

26
27
25

23
25
22

22  b  26  b  2 6 b 
23  b  27  b  2 7 b 
20  b  24  b  2 5 b 

23
23
23

29 b  21 b   22  b  2 4 3 0 b 
29 b  22 b   22  b  2 5 2 9 b 
30 b  20 b   21  b  2 3 3 1 b 

26
26
25

24  i 26 b  22 b   28
24  i 27 b  22 b   29
23  i 25 b  22 b   27

2 9 3 1 b  31 i
3 0 3 2 b  34 i
2 7 2 9 b  29 i

:
:
:

28  i
29  i
26  i

Key indicator 13b

At-risk-of-poverty rate after soc ial transfers, 2 005 (The p ercenta ge o f persons with a n eq uivalised d isp osa ble inco me be low the r isk-
o f-po ver ty threshold, which is set at 60 % of th e n atio nal me dian equivalised disposable income.)

T otal
1 6 s 16 s  15 s
F emales 1 7 s 17 s  16 s
1 5 s 15 s  14 s
Ma les

15
15
14

14 i  10 b 
15 i  11 b 
13  i 10 b 

12
12
12

12  b  1 8
2 0
13  b
1 7
11  b

20
21
19

20
21
18

20
21
19

13
14
12

19
21
17

16  b  19  b  2 1 b 
18  b  20  b  2 1 b 
15  b  18  b  2 0 b 

13
13
13

13 b  15 b   11  b  1 2 2 1 b 
13 b  16 b   11  b  1 3 2 0 b 
14 b  14 b   11  b  1 1 2 1 b 

19
20
19

18 i  12 b  13 b   12
18  i 14 b  13 b   13
18  i 11 b  13 b   11

9
1 9 b 18 i
1 0 1 9 b  20 i
1 9 b 16 i
9

:
:
:

26  i
27  i
26  i

Notes: 1)  HR: National HBS 2004, income data 2004. 2) BG and RO National HBS 2005, income data 2005.  3) TR National HICE survey 2004, income data 2004.
4) EU Aggregates: Eurostat estimates are obtained as a population s ize weighted average of national data.

Source: SILC(2005) income data 2004; except for UK, income year 2005 and for IE moving income reference period (2004-2005). 

At-risk-of-poverty rate before and 
after social transfers, 2005

After transfers

Reduction in %

0%

TR

25%

ESEL

IT

LT

IEPL
LV & PT UK

EE & RO

CY

EA-13

HR 
EU-27 & EU-25

50%

BG

MT

SK
NL

BE
HU

LU

FR

SI

FI

DK

DE AT

CZ

SE

75%

%

35

30

25

20

15

10

5

0

0

5

10

15

20

25

30

35

Before transfers

%

Notes: 1)  HR: National HBS 2004, income data 2004. 2) BG and RO National HBS 2005, income data 2005.  3) TR National HICE survey 2004, income data 2004.
4) EU Aggregates: Eurostat estimates are obtained as a population s ize weighted average of national data.

Source: SILC(2005) income data 2004; except for UK, income year 2005 and for IE moving income reference period (2004-2005). 

At-risk-of-poverty rate after social transfers and relative m edian at-risk-of-poverty gap, 2005 (survey year)

At-risk-of-poverty rate after social transfers

Relative median at-risk-of-poverty gap

8
2

7
2

0
3

6
2

1
2

1
2

1
2

3
2

3
2

2
2

9
8 1
1

8
1

9
1

8
1

9
1

9
1

9
1

8
1

4
3

6
2

4
2

4
2

5
2

4
2

4
2

0
2

8
1

8
1

9
1

8
1

0
2

0
2

0
2

0
2

9
1

9
1

9
1

7
1

6
1

6
1

6
1

5
1

5
1

4
1

6
1

2
1

2
1

0
1

3
1

3
1

3
1

5
1

5
1

2
1 1
1

3
2 1
1

4
1

2
1

9

%

3
2

1
2

40

35

30

25

20

15

10

5

0

EU-
27

EU-
25

EA-
13

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

HR MK TR

Notes: 1)  HR: National HBS 2004, income data 2004. 2) BG and RO National HBS 2005, income data 2005.  3) TR National HICE survey 2004, income data 2004.
4) EU Aggregates: Eurostat estimates are obtained as a population s ize weighted average of national data.

Source: SILC(2005) income data 2004; except for UK, income year 2005 and for IE moving income reference period (2004-2005). 

167 

EN 

14.     

   EN 

 
14. 

JOBLESS HOUSEHOLDS AND LOW WAGES 

An important cause of poverty and social exclusion is the lack of a job or low wages from 
employment. In 2007 9.3% of people aged 18-59 were living in jobless households both in 
the EU-27 and EU-25 countries. For children aged 0-17 these figures were 9.4% in EU-27 
and 9.3 in EU-25.  

Persons living in households where no people of working age are in employment are 3 
times more likely to be poor than people living in households where at least one person is 
working 

In  2007  at  EU  level  around  9%  of  children  aged  0-17  and  adults  aged  18-59  (excluding 
students  aged  18-24  living  with  other  students)  were  living  in  jobless  households,  i.e. 
households where no member was in employment. Amongst adults, the proportion was lowest 
in  Cyprus  (4.5%)  and  Portugal  (5.8%)  followed  by  Estonia,  Spain  and  Slovenia  (6.0%).  In 
contrast, Belgium (12.5%), Hungary (11.8%) and Poland (11.7%) record much higher rates. 
Rates amongst children are generally similar to those for adults, but in Slovenia; Greece, and 
Luxembourg children live in jobless households much less frequently than adults – whilst in 
Bulgaria,  Ireland,  Hungary  and  the  United  Kingdom  the  proportions  of  children  living  in 
jobless households are noticeably higher than for adults. 

Amongst the enlarged EU-25 in 2005, persons who are unemployed (40%) or 'other inactive' 
(25%) have significantly  higher risk of living in low income households  than those at work 
(8%). However, having a job is not a sufficient condition to escape the risk of poverty. Having 
children  increases  poverty  risk  from  15%  (households  without  dependent  children)  to  17% 
(households  with  dependent  children).  The  impact  of  children  is  least  noticeable  for 
households  where  all  persons  of  working  age  are  working  full-time,  but  is  particularly 
significant for jobless households.  

Working poor: a complex picture 

Although people in employment are less likely to live in a low-income household, i.e. to be 
"working  poor",  the  risk  of  poverty  is  not  removed.  An  employee's  standard  of  living  (as 
measured by income) is only partly determined by his/her wage. Indeed, in many cases, low 
wages  received  by  one  member  of  a  household  are  "compensated  for"  by  higher  wages 
received by one or more other members of the household. Similarly, a household may receive 
income other than wages (income from self-employed work or other types of income such as 
social benefits, income from property, etc.). Lastly, the standard of living depends not only on 
the resources available but also on the size of the household as well as its economic (number 
of people in employment, etc.) and demographic (number of children and other dependants, 
etc.)  characteristics.  All  low-wage  employees  do  not,  therefore,  live  in  low-income 
households. Inversely, employees whose wages are above the low-wage threshold may - e.g. 
if they have a number of dependants - be living in poor households. 

EU-wide, 6% of employees are poor 

In 2001, for the EU-25, the at-risk-of-poverty rate for employees is about 8%. It is higher in 
Estonia,  Spain,  Italy,  Latvia  (2002  data),  Lithuania,  Luxembourg,  Poland,  Portugal  and 
Slovak Republic (2003 data). In all the countries analysed, the at-risk-of-poverty rate among 
employees  is  –  as  might  be  expected  –  lower  than  the  at-risk-of-poverty  rate  among  the 

EN 

168 

   EN 

 
population as a whole. At EU level and for most countries in 2001, the at-risk-of-poverty rate 
of employees is less than half that of the total population.  

It is not necessarily the countries with the highest at-risk-of-poverty rates that have the highest 
proportions  of  employees  living  at-risk-of-poverty,  but  there  does  seem  to  be  a  correlation. 
Denmark has some of the lowest at-risk-of-poverty rates both for the population as a whole 
and for employees, while Portugal has some of the highest at-risk-of-poverty rates both for the 
population as a whole and for employees. 

Policy context 

The  system  of  financial  incentives  is  one  of  the  main  determinants  of  participation  in  the 
labour market and has been an important consideration both for the Employment Guidelines 
and the Broad Economic Policy Guidelines , and the future EES will place more emphasis on 
this issue. The objective of "Making work pay" should be pursued both from the point of view 
of the jobseeker and from that of the employer. In line with the recommendations of the Joint 
Report  on  increasing  labour  force  participation,  there  is  a  need  for  a  systematic  review  of 
tax/benefit  systems  with  a  particular  focus on  eliminating  unemployment  and  poverty  traps, 
encouraging  women  to  enter,  remain  in  or  reintegrate  into  the  labour  market  after  an 
interruption,  and  on  retaining  older  workers  longer  in  employment.  In  addition  taxation  on 
labour particularly for the low-skilled workers should be such as to reduce the attractiveness 
of undeclared work and to encourage job creation.  

See also Low-income households (2.13) 

Methodological notes 

Sources:  Eurostat  –  European  Union  Labour  Force  Survey  (data  on  population  living  in 
jobless  households).  European  Community  Household  Panel  (ECHP)  UDB,  version 
December 2003, 2001 data, wave 8, Eurostat - Community Statistics on Income and Living 
Conditions, advance launch, 2003 and Eurostat – “4th round” of data collection from national 
sources, 2005.  

See Income distribution (2.12) for income concept and definition of equivalised income. For 
definition of low-income (or poor) households, see Low-income households (2.13). 

Links to other parts of the report 

Employment  (2.7),  Social  protection  expenditure  and  receipts  (2.10),  Income  distribution 
(2.12),  Low-income  households  (2.13)  and  Income,  social  inclusion  and  living  conditions 
(Annex 1.3.6). 

Further reading 

•  “European  social  statistics:  Income,  Poverty  and  Social  Exclusion  2nd  Report”,  2003 

edition. Eurostat. 

•  “Joint  Report  on  Social  Protection  and  Social  Inclusion  2007”,  2007,  European 
for  Employment,  Social  Affairs  and  Equal 

Commission,  Directorate-General 
Opportunities. 

EN 

169 

   EN 

 
•  Statistics in Focus (Population and social conditions): “Monetary poverty in EU Acceding 
and  Candidate  Countries”,  No.21/2003.  “Poverty  and  social  exclusion  in  the  EU  after 
Laeken-part1”,  No.8/2003.  “Social  protection:  cash  family  benefits 
in  Europe”, 
No.19/2003.  “Persistent  income  poverty  and  social  exclusion  in  the  European  Union”, 
No.13/2000. “The social protection in Europe”, No.3/2003. 

EN 

170 

   EN 

 
EU-
27

EU-
25

EA-
13

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK TR

Key indicator 14a

People aged 18-59 living in jobless households, 2007
Share of persons/women/men aged 18-59 who are living in households where no-one works. Students aged 18-24 who live in households composed solely 
of students of the same age class are counted neither in the numerator nor in the denominator

:
:
:

:

:
:
:

:

Total
Females10.3 e10.3 e 9.7 14.4 9.9
Males

9.3 e  9.3 e 8.8 e  12.5 10.0 6.5
8.1
8.3 e 8.2 e 8 e 10.7 10.1 4.9

:
:
:

9.5
6.0
9.9 p 5.7
9.2 p 6.3

7.8
5.7
6.4

8.0
4.5
6.0 10.9 p 9.1
9.1 10.0 12.0 p 10.3 4.9
4.1
5.6 9.7 p 7.8
6.0

7.1
7.7
6.4

6.3
6.3
6.4

7.5 11.8 6.9
8.6 12.9 8.3
6.3 10.7 5.6

6.5
7.7
5.4

Source: Eurostat - European Union Labour Force Survey.

Key indicator 14b

Children aged 0-17 living in jobless households, 2007
Share of persons aged 0-17 who are living in households where no-one works

7.6 11.7 5.8
6.0
8.7 12.8 6.1 10.7 6.9
5.1
6.5 10.5 5.4

8.6

9.6

8.8
9.6
8.1

:
:
:

:
:
:

10.9
12.7
8.9

:
:
:

9.4 e  9.3 e 7.7 e  13.5 12.9 7.9

:

9.3 p 7.3 11.2 3.9

5.0

9.8

5.8

3.7

8.6

6.9

4.0 14.0 8.4

5.9

6.1

9.5

4.8

9.4

2.5 10.5

:

:

16.7

:

Source: Eurostat - European Union Labour Force Survey.

Population in jobless households, 2007

%

Females 18-59

Males 18-59

Total 18-59

Children 0-17

18

16

14

12

10

8

6

4

2

0

EU-
27

EU-
25

EA-
13

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK

HR MK TR

Source: Eurostat - European Union Labour Force Survey

At-risk-of-poverty rates among the persons living in households with working age adults, where no adult is 
working, 2005                     

%

63

78

78

81

74

58

57

51

54

51

28

24

19

27

28

28

100

90

80

70

60

50

40

30

20

10

0

83

82

73

without dependent children

with dependent children

76

70

71

68

63

54

47

42

30

21

62

61

56

53

52

54

56

40

36

34

18

15

16

24

21

33

31

27

20

14

65

42

38

BE BG CZ DK DE EE

IE

EL

ES

FR

IT CY LV LT LU HU MT NL AT PL

PT RO SI

SK FI

SE UK HR MK TR

EU-
25

Notes: 1)  BG, HR: National HBS 2004, income data 2004. 2) RO National HBS 2005, income data 2005.  3) TR National HICE survey 2004, income data 2004.
4) EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.

Source: SILC(2005) income data 2004; except for UK, income year 2005 and for IE moving income reference period (2004-2005). 

EN 

171 

   EN 

 
 
 
15. 

WOMEN AND MEN IN DECISION MAKING 

In  the  lower  or  single  houses  of  national  parliaments  women  continue  to  be  under-
represented in all Member States as the percentages of seats occupied by women in these 
bodies ranged in August 2007 from 9.2% in Malta to 47.3% in Sweden. The average of the 
27  Member  States’  percentages  is  23.1%.  In  the  European  Parliament  women's  share  of 
the national seats varied from no seats (Cyprus and Malta) to 51.9% (the Netherlands) in 
October 2007. Women occupied then 31.2% of the seats of the European Parliament. 

Balanced participation of women and men in decision making is a key element in achieving 
gender equality and a fundamental requirement for well functioning democracies, which take 
into  account  the  interests  and  needs  of  the  whole  population.  There  is  however  a  persisting 
imbalance in the European Union concerning the participation of women and men at the level 
of decision making in politics, management, trade unions, universities, civil society and in the 
judiciary. Women are still far from taking an equal part in the decision making process. To 
tackle their under-representation is a structural and multifaceted challenge.  

Political decision making  

European  level:  Among  the  Members  of  the  European  Parliament  there  were  31.2%  of 
women in October 2007, varying from no women from Cyprus and Malta to 57.9% (14 of 17) 
from  the  Netherlands.  Eight  of  the  twenty-seven  (29.6%)  Commissioners  of  the  European 
Commission were then women. 

National level: As an average in EU-27 (EU-25) Member States in August 2007, only 23.1% 
(23.6%) of the seats of the lower or single House of the national or federal Parliament were 
occupied  by  women.  These  percentages  had  risen  6.4  percentage  points  in  nine  years.  The 
discrepancies between countries in August 2007 were fairly large, from a minimum share of 
9.2% in Malta to a maximum of 47.3% in Sweden. The corresponding percentages of senior 
minister  posts  of  the  national  governments  in  April/May  2007  were  23.5%  for  EU-27  and 
24.5% for EU-25. The extremes were Cyprus and Romania with no women in the government 
and Finland with 60.0%.  

Regional  level:  The  regional  institutions  are  not  necessarily  comparable  in  terms  of  power 
level  and  competency  areas  given 
the  existing  differences  between  political  and 
administrative systems. Eleven Member States do not have regional councils and seven do not 
have regional governments58.  

The regional council is the regional legislative assembly which has the legislative power on 
regional level According to data collected in autumn 2006, as an average in the 16 of the EU-
27 Member States in which there exist regional councils, 26% of the members in and 14% of 
the presidents of the regional councils were women. The lowest percentages were observed in 
Hungary (12% women as members and 15% as presidents in Megyei Közgyülés), Italy (12% 
and 18% in Consiglio) and Slovakia (12% and not available in Zastupitelstvo) and the highest 
ones  in  Sweden  (47%  and  45%  in  Landstingsfullmäktige),  Finland  (43%  and  21%  in 
Maakuntavaltuusto) and partly in France (49% and 4% in Conseil Régional). 

58 

In  addition  in  Portugal  an  UK  only  a  limited  part  of  the  country  is  covered  by  regional  councils  and 
governments. 

EN 

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The  regional  government  is  the  institution  that  is  the  governing  authority  of  a  regional 
political  unit59.  It  has  the  highest  executive  powers  at  the  regional  level.  According  to  data 
collected in autumn 2006, as an average in the 20 of the EU-27 Member States in which there 
exist regional governments, 24% of the members in and 8% of the presidents of the regional 
governments were women. The lowest percentages were observed in Portugal (6% women as 
members  and  0%  as  presidents  in  Governo  (Madeira/Açores)  and  Poland  (8%  and  0%  in 
Zarząd województwa) and the highest ones in Sweden (46% and 30% in Landstingsstyrelsen) 
and Finland (49% and 21% in Maakuntahallitus).  

Local  level:  For  the  local  councils  in  the  countries  of  the  European  Union,  data  are 
incomplete  and  not  always  comparable,  due  to  the  large  differences  in  local  level  political 
decision-making. Data available for 1997 pointed to a female participation rate near to 20% in 
the local councils of the EU-15. 

Balanced  participation  in  decision-making  will  be  helped  by  better  reconciliation 
between work and family life 

Reconciliation between work and family life is a key factor in women's accession to decision 
making posts. A study carried out by the Women's Institute60 in Spain shows that women who 
have  acceded  to  managerial  posts  are  more  likely  to  be  single  than  men,  and  have  fewer 
children than their male counterparts. It further shows that the family may still constitute an 
important obstacle to the promotion of women to executive posts. 

A  project  co-financed  by  the  Gender  Equality  programme61  discussed  the  status  of  elected 
representatives  in  local  councils  in  Europe  and  the  difficulties  met  by  women  in  taking  up 
local  mandates.  It  showed  that  problems  with  time  management  are  a  significant  limiting 
factor.  Fulfilling  local  mandates  often  implies  time  schedules  not  compatible  with  raising 
children,  if  fathers  do  not  share  family  responsibilities  or  adequate  and  affordable  childcare 
services are not available. 

Policy context  

Equal  treatment  of  women  and  men  is  a  fundamental  principle  of  Community  law.  The 
persistent  under-representation  of  women  in  all  areas  of  decision-making  making  represents 
an important obstacle to the democratic development of the European Union, to its cohesion 
and globally to its competitiveness, which requires action to be taken at Community level.  

Political support was manifested by the Council in recommendation 96/694 of 2nd December 
1996 on the Balanced Participation of Women in the decision-making process. However, the 
Commission’s report published in March 2000 on the implementation of this recommendation 
concluded that despite the overall positive outcome of policies applied since 1996, the level of 
improvement did not match expectations and that further action was required. In this context 
it is worthwhile noting the efforts and considerable progress made in most Member States to 
increase the participation of women in decision-making processes in recent years, even if the 

59 

60 

61 

In  France  (Président  du  conseil  régional)  and  Greece  (prefect/nomarchis)  the  regional  government 
consists of only one person. 
Instituto  de  la  Mujer  (An  autonomous  public  body),  “El  acceso  de  las  mujeres  a  los  puestos  de 
dirección”.  The  study  "Access  of  women  to  Executive  Posts"  by  Ester  Barberà,  Professor  of  Basic 
Psychology at the Universidad de Valencia. 
Why not Women Town Counsellors? http://perso.orange.fr/ellesaussi/index.htm (Bibliographie) 

EN 

173 

   EN 

 
                                                 
situation  varies  significantly  between  countries.  Nevertheless,  much  remains  to  be  done  to 
improve the overall representation of women in decision-making across the Union.  

Moreover, in the framework of the follow-up of the 1995 Beijing Platform for Action, it was 
decided to develop benchmarks and indicators at EU level to monitor its implementation. One 
area of concern of the Platform relates to women in power and decision-making. Therefore, 
the Council of the European Union adopted on 22 October 1999 conclusions on the subject of 
gender balance in all decision-making processes and took note of the Union Presidency report 
on Indicators and Benchmarking for Women in the Decision-making process in the political 
field. 

Furthermore, in 2003, the Council of the European Union adopted new conclusions on women 
and men in economic decision making and took note of the Union Presidency report including 
nine indicators on Representation of Women and Men in Economic Decision-making Centres.  

The  Commission's  Roadmap  for  equality  between  women  and  men  (2006-2010)  includes 
among  its  six  priority  areas  for  action  on  gender  equality  the  promotion  of  equal 
representation of women and men in decision-making.  

Alongside policy actions to tackle the under-representation of women in power and decision-
making, the European Commission has recognised in a number of reports the need for reliable 
and comparable data in order to systematically monitor the current situation and the progress 
that is being made. Consequently, in 2002 the Commission initiated the process to establish a 
regular  collection  and  publication  of  data  on  decision-making  across  Europe.  The  resulting 
database is accessible free on-line62 and currently covers decision-making positions within the 
EU  institutions,  the  27  EU  Member  States,  EEA  countries  (Iceland,  Liechtenstein  and 
Norway)  and  two  candidate  countries  (Turkey  and  Croatia).  It  is  an  important  source  of 
information  for  policy  makers,  researchers,  students  and  all  those  interested  in  knowing  the 
state of play in decision-making.  

Methodological notes 

Since  Eurostat  doesn’t  collect  data  in  this  domain,  other  sources  have  been  used.  They  are 
given in the tables and graphs. 

Links to other parts of the report 

Education  and  its  outcomes  (2.5),  Earnings  of  women  and  men  (2.16)  and  Gender  equality 
(Annex 1.3.7). 

Further reading 

•  Database  of  the  European  Commission  on  women  and  men  in  decision  making  : 

http://europa.eu.int/comm/employment_social/women_men_stats/index_en.htm 

•  Report  on  equality  between  women  and  men  (in  the  European  Union)  2007,  European 
Commission,  Catalogue  No.  KE-AJ-07-001-EN-C,  ISBN  92-79-03496-0,  ISSN  1680-
2381; Document drawn up on the basis of COM(2007)49. 

62 

The database is hosted on the website of DG-Employment, Social Affairs and Equal Opportunities and 
can be consulted at http://ec.europa.eu/employment_social/women_men_stats/index_en.htm 

EN 

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•  ETAN  report  on  Women  and  sciences:  Promoting  excellence  through  mainstreaming 

gender equality, 2000. 

•  Women in science : Report "She Figures": 

http://ec.europa.eu/research/science-society/pdf/she_figures_2006_en.pdf 

EU-
27

EU-
25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 15a
25.5

23.1

23.6

Percentage of women in the lower or single House of the national or federal Parliament, August 2007

34.7

22.1

15.5

36.9

31.6

21.8

13.3

13.0

36.0

18.5

17.3

14.3

19.0

24.8

23.3

10.4

9.2

36.7

32.2

20.4

21.3

11.2

12.2

19.3

42.0

47.3

19.7

21.7

28.3

9.1

Notes:   1) The data are provided by national or federal Parliaments by 31 August 2007 and extracted on 2 October 2007. 
2) The most adequate EU-27, EU-25 and EA-13 averages are conceptually different for nPs/fPs from those for the EP reflecting the nPs'/fPs' and EP's conceptually different status. For nPs/fPs these are averages of the percentages of the corresponding Member States, whereas for 
EP they are percentages of women among all MEPs from the corresponding Member States. For the sake of completeness, the for nPs/fPs less adequate averages for are given here: The percentages of women in all the nPs/fPs put together as a whole are are 23.3% for EU-27, 
23.9% for EU-25 and 24.9% for EA-13.

Source: The Inter-Parliamentary Union (http://www.ipu.org/wmn-e/classif.htm)

Key indicator 15b
32.9

31.2

30.8

Percentage of women in the European Parliament, October 2007

33.3

44.4

20.8

42.9

32.3

50.0

38.5

33.3

32.1

43.6

16.7

0.0

22.2

38.5

50.0

37.5

0.0

51.9

27.8

14.8

25.0

34.3

42.9

35.7

35.7

47.4

25.6

.

.

.

Notes: 1) The data was extracted on 2 October 2007.
2)The most adequate EU-27, EU-25 and EA-13 averages are conceptually different for EP from those for the nPs/fPs reflecting the EP's and nPs'/fPs' conceptually different status. For EP these are percentages of women among all MEPs from the corresponding Member States, 
wheras for nPs/fPs they are averages of the percentages of the corresponding Member States. For the sake of completeness, the for EP less adequate averages are given here: For EP the average of the percentages of the corresponding Member States is 32.5% in EU-27, 31.9% 
in EU-25 and 35.6% in EA-13. 

Source: The European Parliament (http://www.europarl.europa.eu/members/expert/searchForm.do?language=EN)

Percentage of women and men in the lower or single House of the national or federal Parliament (nP/fP) and in the European 
Parliament (EP), August 2007 (nP/fP) and October 2007 (EP)

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

3
1
-
A
E

7
2
-
U
E

E
S

K
D

U
L

S
E

G
B

T
L

T
A

K
S

U
H

T
P

K
U

Z
C

T

I

T
M

K
M

R
T

Note: The bars within the first two groups are ordered by the average of the percentages of women in nP/fPand EP and within then third group (Candidate Countries) by the percentage of women in nP/fP.

Sources: The Inter-Parliamentary Union (http://www.ipu.org/wmn-e/classif.htm) and the European Parliament (http://www.europarl.europa.eu/members/expert/searchForm.do?language=EN).

Percentage of women and men of the senior ministers (sr min) of the national governments and of the commissioners of the European 
Commission (EC), April/May 2007

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

70.4

74.0

75.5

76.5

40.0

52.6

52.9

59.1

62.5

62.5

64.3

72.2

76.2

76.9

76.9

77.8

78.6

78.6

78.9

80.0

80.0

80.0

82.6

83.3

84.2

88.2

88.2

93.8

94.4

100.0

100.0

100.0

73.3

84.2

29.6

C
E

26.0

24.5

23.5

3
1
-
A
E

5
2
-
U
E

7
2
-
U
E

60.0

47.4

47.1

40.9

37.5

37.5

35.7

27.8

23.8

23.1

23.1

22.2

21.4

21.4

21.1

20.0

20.0

20.0

17.4

16.7

15.8

11.8

6.3

11.8

5.6

I

F

K
D

S
E

E
S

E
D

K
U

T
A

L
N

G
B

U
L

T
M

T

I

T
L

E
E

V
L

E
B

E

I

U
H

L
P

Z
C

L
E

R
F

T
P

I

K S
S

26.7

15.8

R
H

K
M

0.0
R
T

0.0
Y
C

0.0
O
R

Sources: 1)European Commission, Directorate-General for Employment, Social Affairs and Equal Opportunities, Database on women and men in decision-making (http://europa.eu.int/comm/employment_social/women_men_stats/out/measures_out416_en.htm), 
2) European Commission (http://ec.europa.eu/commission_barroso/index_en.htm).
3) MK: National source (http://www.vlada.mk/english/gov_members.htm), 2 October 2007.

EP
men

EP
women

nP/fP
men

nP/fP
women

sr min
men

sr min
women

EN 

175 

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16. 

EARNINGS OF WOMEN AND MEN 

In the EU-27, the average gross hourly earnings of women in 2005 were estimated at 15% 
less  than  the  gross  hourly  earnings  of  men63.  The  smallest  differences  are  found  in 
Belgium, Malta and Slovenia, the biggest in Germany, Estonia, Cyprus, Slovakia, Finland 
and the United Kingdom. At EU level the difference remains fairly the same since 1994, the 
first  date  for  which  data  are  available.  To  reduce  gender  pay  differences  both  direct  pay-
related  discrimination  and  indirect  discrimination  related  to  labour  market  participation, 
occupational choice and career progression have to be addressed. 

Important  pay  differences  between  men  and  women  persist  in  Europe,  with  the 
difference between men’s and women’s average gross hourly earnings around 15% 

According  to  national  Structure  of  Earnings  Surveys  (SES)  and  other  national  earnings 
surveys, Statistics on Income and Living Conditions (EU-SILC: EL, IE and AT for 2003; BE, 
EL,  ES,  IE,  IT,  AT,  PT,  UK  for  2004  and  2005)  and  the  European  Community  Household 
Panel (ECHP: BE and IT for 2001), the gender pay gap – difference in average gross hourly 
earnings  as  a  percentage  of  men’s  average  gross  hourly  earnings  –  varied  between  4%  and 
25% in 2005. Women’s earnings remain on average below those of men in all EU countries. 
The  statistics  show  that  development  over  time  varies  at  country  level64.  Differences 
decreased  in  many  Member  States  (BE,  EE,  IE,  GR,  CY,  LV,  LU,  HU,  MT,  NL,  RO,  SI, 
UK),but  slightly  increased  in  Denmark  and  Finland.  In  the  remaining  countries  pay 
differences were fairly stable over time65. 

The  pay  differences  are  related  both  to  differences  in  the  personal  and  job 
in  employment  and  to  differences  in  the 
characteristics  of  men  and  women 
remuneration of these characteristics 

Women  and  men  in  employment  show  important  differences  with  respect  to  their  personal 
and  job  characteristics,  including  labour  market  participation,  employment,  earnings,  the 
sector  and  occupational  employment  structures  as  well  as  job  status,  job  type  and  career 
progression.  The  differences  in  pay  are  particularly  high  among  older  workers,  the  high-
skilled and those employed with supervisory or managerial job status. They also vary between 
different sectors of activity and different occupations. The statistics on annual gross earnings 
(full-time workers) from 2005 show gender pay gaps in two sectors of activity, Industry and 
Wholesale  and  retail  trade;  Repair  of  motor  vehicles  and  personal  &  household  goods,  for 
which data are available for most countries. Gender pay gaps vary between 10% in Belgium 
and  35%  in  Hungary  for  Industry  which  is  a  strongly  male  dominated  sector.  They  vary 
between 19% in Belgium and 36% in the Slovakia for Wholesale and retail trade etc. which is 
a  sector  slightly  dominated  by  women.  In  most  countries  the  gender  pay  gaps  are  bigger  in 
Wholesale and retail trade etc. than in Industry. 

63 

64 

65 

Sources: Gender Pay Gap statistics are from national sources for CZ, EE, FR, CY, LV, LT, LU, HU, 
MT, NL, PL, SI, SK, SE and from the European Community Household Panel survey (ECHP) for BE, 
DK, DE, EL, ES, IE, IT, AT, PT, FI, UK for data until 2001. In 2002, the ECHP source was replaced 
either by national sources or by the European Survey on Income and Living Conditions (EU-SILC). 
Cross national and over time comparisons must be interpreted with caution, due to the multiplicity of 
data sources and to methodological differences in the national estimates. 
Apart from changes that can be attributed to breaks in the statistical series. 

EN 

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Women have managerial responsibilities much less frequently than men in the Member States 
for which data are available from the European Labour Force Survey. In the EU-25 Member 
States,  32%  of  managers  are  women  in  2005,  a  slight  increase  since  2000.  The  highest 
percentages of women among managers are found in Lithuania and Latvia, while the lowest 
percentages are in Malta and Cyprus. 

Women are furthermore often in non-standard employment such as fixed-term and part-time 
work. In the  EU-25,  31.4%  of  women  were working part-time in 2004,  against  7%  of  men. 
Compared  to  2001,  the  share  of  part-time  employment  rose  by  3.1  percentage  points  for 
women and 1.5 percentage points for men. The share of female part-timers exceeded 30% in 
France, Denmark and Luxembourg, 40% in Sweden, Austria, Belgium, United Kingdom and 
Germany  and  even  reached  75%  in  the  Netherlands.  Conversely,  the  share  of  part-timers 
among female workers was very low in Bulgaria, Slovakia, Hungary, the Czech Republic and 
Latvia.. Men are thus not only more concentrated in higher paid sectors and occupations, but 
within these sectors and occupations they are also more likely than women to hold managerial 
responsibilities and if they do so the earnings are relatively higher. 

Furthermore,  while  both  men  and  women  have  lower  earnings  in  female-dominated  sectors 
and occupations, this wage penalty is more pronounced for women. Finally, independently of 
the initial pay differential the gender pay differential widens considerably throughout working 
life. 

Both  the  above  differences  in  the  composition  of  the  male  and  female  workforce  and 
differences  in  the  remuneration  of  the  personal  and  job  characteristics  between  men  and 
women  contribute  to  the  overall  gender  differences  in  pay.  As  shown  in  Employment  in 
Europe 2005, in particular differences in the male and female workforce composition related 
to  the  sector  of  employment  and  the  occupational  category  contribute  significantly  to  the 
gender differences in pay. Since such compositional differences can be due to various forms 
of  indirect  discrimination  such  as  traditions  and  social  norms  and  constraints  on  choices 
related  to  education,  labour  market  participation,  occupation  and  career  progression  both 
types of gender differences and both forms of potential discrimination - direct pay-related one 
and indirect one related to the above choices – have to be addressed to reduce the differences 
in pay. 

Policy context  

The  important  gender  differences  which  persist  in  the  European  labour  markets  need  to  be 
tackled to promote economic growth, employment and social cohesion. 

The EC Treaty (Article 141) states that "Each Member State shall ensure that the principle of 
equal pay for male and female workers for equal work or work of equal value is applied. For 
the purpose of this Article, ‘pay’ means the ordinary  basic  or  minimum  wage  or  salary  and 
any  other  consideration,  whether  in  cash  or  in  kind,  which  the  worker  receives  directly  or 
indirectly, in respect of his employment, from his employer. Equal pay without discrimination 
based on sex means: 

(a) that pay for the same work at piece rates shall be calculated on the basis of the same unit 
of measurement; 

(b) that pay for work at time rates shall be the same for the same job. 

EN 

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Council Directive 75/117/EEC of 10 February 1975 on the approximation of the laws of the 
Member States relating to the application of the principle of equal pay for men and women. 

The 2000 Employment Guidelines (No.19): “They (Member States) will initiate positive steps 
to promote equal pay for equal work or work of equal value and to diminish differentials in 
incomes between women and men.” The 2001 Employment Guidelines further specified that 
actions are needed to address gender differences in pay in both the private and public sectors 
and  that  the  impact  of  policies  on  gender  differences  in  pay  should  be  identified  and 
addressed. The 2002 Employment Guidelines also asked to set targets to tackle the differences 
in pay and to include in the strategy, inter alia, a review of job classification and pay systems 
to eliminate gender bias, improving statistical and monitoring systems, and awareness-raising 
and  transparency  as  regards  differences  in  pay.  The  2003  Employment  Guidelines  says  that 
policies  will  aim  to  achieve  by  2010  a  substantial  reduction  in  the  gender  pay  gap  in  each 
Member  State,  through  a  multi-faceted  approach  addressing  the  underlying  factors  of  the 
gender pay gap, including sectoral and occupational segregation, education and training. 

Communication from the Commission to the Council, the European Parliament, the Economic 
and  Social  Committee  and  the  Committee  of  the  Regions  on  "Employment  and  social 
policies: a framework for investing in quality”. 

The Employment Committee Report on Indicators of Quality in Work contains indicators on 
earnings under the form of transition tables.  

Methodological notes 

The  Gender  Pay  Gap  in  unadjusted  form  is  given  as  the  difference  between  average  gross 
hourly  earnings  of  male  paid  employees  and  of  female  paid  employees  as  a  percentage  of 
average  gross  hourly  earnings  of  male  paid  employees.  The  population  consists  of  all  paid 
employees aged 16-64 that are "at work 15+ hours per week". 

Sources:  The  gender  pay  gap  is  based  on  several  data  sources,  including  the  European 
Community Household Panel (ECHP), the EU Survey on Income and Living Conditions (EU-
SILC) and national sources. 

Administrative data are used for Luxembourg and the Labour Force Survey is used for France 
(up to 2002) and Malta. All other sources are national surveys except as follows: 

2004, 2005: Statistics on Income and Living Conditions (EU-SILC) – BE, EL, ES, IE, IT, AT, 
PT and UK (provisional) 

2003: Statistics on Income and Living Conditions - EL, IE and AT 

2002: European Community Household Panel (ECHP) - EL 

2001 and before: European Community Household Panel (ECHP) - BE, DE, IT, DK, IE, UK, 
EL, ES, PT, AT, FI. 

EU-27, EU-25 and EU-15 estimates are population-weighted averages of the latest available 
national values adjusted, where possible, to take into account a change in the data source.  

CZ – Figures are based on median earnings of employees working 30 or more planned hours 
per week. 

EN 

178 

   EN 

 
DK - A change of data source from 2002 is estimated to have increased the gender pay gap 
value by 4 percentage points. 

DE - From 2002 national earnings surveys and the German Socio-Economic Panel have been 
used.  This  change  of  source  is  estimated  to  have  increased  the  gender  pay  gap  value  by  1 
percentage point. 

ES  -  From  2002  data  from  tax  returns  and  the  labour  force  survey  have  been  used.  This  is 
estimated to have increased the gender pay gap value by 3 percentage points 

FR - A change of data source in 2003 is estimated to have decreased the gender pay gap value 
by 1 percentage point 

FI  -  A  change  of  data  source  from  2002  is  estimated  to  have  increased  the  gender  pay  gap 
value by 4 percentage points 

UK - A change of data source from 2002 is estimated to have increased the gender pay gap 
value by 2 percentage points 

The gender pay gap is not adjusted for age, occupation and sector. In May 2002, the ECHP 
Working Group concluded that an adjusted gender pay gap cannot be calculated on the basis 
of the ECHP.  

Annual harmonised earnings data relate to enterprises with 10 or more employees, except for  

HU – enterprises employing more than 4 employees 

ES – enterprises employing more than 5 employees 

BE, LU, UK, CZ, CY and SK – enterprises from all size groups 

All data relate to full-time employees except for CZ, EE, LV and SI for which data relate to 
full-time equivalents. 

Eurostat quarterly labour force data (QLFD) consist of employment by economic activity and 
status  in  employment,  further  broken  down  by  sex  and  some  job  characteristics.  They  are 
based on the EU Labour Force Survey (LFS) and on European System of National Accounts 
(ESA 95). 

Quarterly  LFS  data  are  available  since  the  first  quarter  of  2003  in  all  EU  countries,  except 
Germany (provides quarterly estimates until German LFS becomes quarterly from 2005) and 
Luxembourg. Data for France refer to metropolitan France (excluding overseas departments). 

The classification by part-time full-time job depends on a direct question in the LFS, except 
for  the  Netherlands  where  it  depends  on  a  threshold  on  the  basis  of  the  number  of  hours 
usually worked. 

Links to other parts of the report  

Employment (2.7), Labour market and Gender equality (Annex 1.3.7). 

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Further reading 

(COM(2007)  424  final)  Communication  from  the  Commission  to  the  European  Parliament, 
the  Council,  the  European  Economic  and  Social  Committee  and  the  Committee  of  the 
Regions - Tackling the pay gap between women and men, July 2007. 

Link to communication: 
http://ec.europa.eu/employment_social/news/2007/jul/genderpaygap_en.pdf  

Gender equality policy: 
http://ec.europa.eu/employment_social/gender_equality  

Study on 'The gender pay gap: origins and policy responses': 
http://ec.europa.eu/employment_social/publications/2006/ke7606200_en.pdf  

European Year of Equal Opportunities for All: 
http://equality2007.europa.eu  

Fourth European Working conditions survey: 
http://www.eurofound.europa.eu/ewco/surveys/EWCS2005/index.htm  

"Report  on  equality  between  women  and  men  –  2007",  February  2007,  European 
Commission,  Directorate-General  for  Employment,  Social  Affairs  and  Equal  Opportunities, 
Unit G.1 

The gender pay gap — Origins and policy responses - A comparative review of 30 European 
countries,  July  2006,  European  Commission  Directorate-General  for  Employment,  Social  Affairs 
and Equal Opportunities, Unit G.1 

Gender  Equality:  a  step  ahead  -  A  Roadmap  for  the  future,  Report  from  the  conference 
organised  by  the  European  Commission  on  4  and  5  May  2006,  July  2006,  European 
Commission  Directorate-General  for  Employment,  Social  Affairs  and  Equal  Opportunities 
Unit G.1 

A  Roadmap  for  equality  between  women  and  men  2006-2010,  April  2006,  European 
Commission,  Directorate-General  for  Employment,  Social  Affairs  and  Equal  Opportunities, 
Unit G.1 

"Report on equality between women and men, 2006", February 2006, European Commission 

Directorate-General for Employment, Social Affairs and Equal Opportunities, Unit G.1 

‘Making work pay’ debates from a gender perspective - A comparative review of some recent 
policy  reforms  in  thirty  European  countries,  September  2005,  European  Commission 
Directorate-General for Employment, Social Affairs and Equal Opportunities, Unit G.1 

“Employment  in  Europe  2005”,  European  Commission,  Employment  and  Social  Affairs  DG, 
September 2005. 

25th CEIES seminar: Gender statistics — Occupational segregation: extent, causes and consequences, 
2004 edition, Stockholm, Monday 21 and Tuesday 22 June 2004, EUROSTAT, ISSN 1725-1338,  

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•  “Employment  in  Europe  2003”,  European  Commission,  Employment  and  Social  Affairs 

DG, September 2003. 

•  Working  paper  of  the  Commission  services  on  gender  pay  gaps  in  European  labour 

markets (SEC(2003)937) 

•  “Employment in Europe 2002", section "Assessing gender pay gaps in the EU", September 

2002. European Commission, Employment and Social Affairs DG. 

•  Panorama of the European Union (Population and social conditions): “The life of women 

and men in Europe. A statistical portrait”. Eurostat 2002. 

•  OECD Employment Outlook 2002 - Chapter 2 "Women at Work: Who are They and How 

are They Faring?" 

•  Statistics in Focus (Population and social conditions): “Earnings of men and women in the 
EU: the gap narrowing but only slowly”, No. 5/2001 and “Women’s earnings in the E.U: 
28% less than men’s”, No. 6/1999. Eurostat. 

•  European Parliament: - Resolution and report on equal pay for work of equal value 

•  “Industrial  Relations  in  Europe",  2000.  European  Commission,  Employment  and  Social 

Affairs DG. 

•  Indicators on gender pay equality: The Belgian presidency’s report, 2001. 

•  "The  adjusted  gender  pay  gap:  a  critical  appraisal  of  the  standard  decomposition 
techniques".  Network  of  experts  on  employment  and  equality  between  women  and  men, 
DG Employment and Social Affairs. 

•  The  gender  pay  gap  and  the  gender  mainstreaming  pay  policy:  synthesis  report  of  the 
gender  pay  equality  in  EU  Member  States.  Network  of  experts  on  employment  and 
equality between women and men, DG Employment and Social Affairs.  

•  Report  on  Equality  between  Women  and  Men 

in 

the  European  Union,  2005, 

COM(2005)44 final. 

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EU-
27

EU-
25

EA-
13

Key indicator 16

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Gender pay gap in unadjusted form, 2005 (Difference between men's and women's average gross hourly earnings as a percentage of men's average gross hourly earnings. The population 
consists of all paid employees aged 16-64 that are 'at work 15+ hours per week')

15s

15s

15s

7

16

19

18

22

25

9p

9p

13p

12

9

25

16

15

14

11

4

18

18

10

9

13

8p

24

20

16

20p

:

:

:

Notes:                                                                                                                                                                                                                                                                                                                                                                                                              
CZ: Only full-time employees in enterprises with more than 9 employees are included. Figures are based on median earnings.
CY, BG: Only full-time employees are included.
HU: Only full-time employees in enterprises with more than 5 employees are included.
NL: Data are based on annual earnings including overtime pay and non-regular payments. 
PL: Only employees in enterprises with more than 9 employees are included.
SI: 2005 data, Employees in public enterprises and employees in private enterprises with more than 2 employees are included.
SE:  Data are based on full-time equivalent monthly salaries, not hourly earnings.                                                                                                                           

Administrative data are used for Luxembourg and the Labour Force Survey is used for France (up to 2002) and Malta.
2004, 2005: Statistics on Income and Living Conditions (EU-SILC) – BE, EL, ES, IE, IT, AT, PT and UK (provisional)
2003: Statistics on Income and Living Conditions - EL, IE and AT
2002: European Community Household Panel (ECHP) - EL
2001 and before: European Community Household Panel (ECHP) - BE, DE, IT, DK, IE, UK, EL, ES, PT, AT, FI.

%

40

35

30

25

20

15

10

5

0

Gender pay gap in unadjusted form, 2004 and 2005

2004

2005

Source: Eurostat - Harmonised statistics on earnings

EU-27 EU-25 EA-13

MT

BE

SI

EL

IE

IT

PT

PL

HU

FR

ES

RO

LU

LT

BG

SE

LV

AT

DK

NL

CZ

FI

UK

DE

SK

CY

EE

Notes: BE, IT: 2000-2001 data. EL, FR: Break in series, due to a change in the data source.

Administrative data are used for Luxembourg and the Labour Force Survey is used for France (up to 2002) and Malta.
2004, 2005: Statistics on Income and Living Conditions (EU-SILC) – BE, EL, ES, IE, IT, AT, PT and UK (provisional)
2003: Statistics on Income and Living Conditions - EL, IE and AT
2002: European Community Household Panel (ECHP) - EL
2001 and before: European Community Household Panel (ECHP) - BE, DE, IT, DK, IE, UK, EL, ES, PT, AT, FI.

Difference between men's and women's annual average earnings as a percentage of men's annual average earnings (full-time employees 
in sections C - F and G (NACE Rev. 1.1), 2005.

C - F Industry

G Wholesale and retail trade

%

40

35

30

25

20

15

10

5

0

MT

IT

PT

SI

EL

PL

BE

FR

HU

IE

LU

LV

SE

LT

AT

RO

DK

BG

ES

NL

CZ

FI

UK

DE

SK

EE

CY

Notes: Reference year ES (sectors C-F): 2000; EL FR CY MT PL (sectors C - F and sector G): 2003. CZ LT RO: expressed in full-time units. The bars are in the order of the bars of previous graph in order make it easy to compare the two graphs.

Source: Eurostat, statistics on annual gross earnings

EN 

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   EN 

 
 
 
17. 

LIFE AND HEALTH EXPECTANCIES 

Life expectancy in EU-27 was 80.8 years for women and 74.6 for men in EU-27 in 2003. In 
all  twenty-seven  Member  States  and  Croatia  and  the  former  Yugoslav  Republic  of 
Macedonia women live longer than men.  

Women can expect to live 6.2 years longer than men in EU-27 

From 1960 to 2005, life expectancy of women and men has risen quite steadily in almost all 
countries. Throughout the Union, women live longer than men. In 2003, the life expectancy of 
women in EU-27 was 80.8 years while that for men was 74.6 years which makes a difference 
of 6.2 years. Across the EU, considerable differences can be observed: life expectancy at birth 
varied for men from less than 66 years in Latvia and Lithuania to 78.5 years in Sweden and 
for women from around 76 in Bulgaria, Latvia and Romania to almost 84 years in Spain and 
France. 

Differences in life expectancy without disability less distinct between women and men 

Health  expectancies  are  a  group  of  health  indicators  combining  data  on  mortality  and 
disability  /  morbidity.  The  structural  indicator  Healthy  Life  Years  (HLY)  measures  the 
number of remaining years that a person of a specific age is still expected to live without any 
severe  or  moderate  limitation  in  functioning  because  of  health  problems  /  without  any 
disability. A woman could expect to live 52 years without disability in Estonia and Finland, 
and up to over 68 years in Denmark and Malta. For men the Healthy Life Years ranged from 
48  in  Estonia  to  68.5,  again  Denmark  and  Malta  reporting  the  highest  values.  In  most 
countries  the  HLY  for  women  were  higher  than  for  men,  but  the  differences  were 
substantially smaller than for life expectancy. And, in five countries, men could expect to live 
about  as  long  as  women  without  disability  (Belgium,  Denmark,  Germany,  Spain  and 
Luxembourg), and in 4 countries even longer than women (Cyprus, the Netherlands, Portugal 
and Sweden). 

Circulatory diseases and cancer remained the major causes of death  

Mortality patterns differ significantly according to age and sex. As a general rule, mortality is 
higher  among  men  than  women  in  all  age  groups.  For  both  men  and  women  in  EU-27, 
circulatory diseases were the major cause of death in 2005, accounting for 38% of deaths for 
men  and 45% for women.  The  second  most  frequent  cause  of death was cancer responsible 
for  28%  of  deaths  for  men  and  22%  of  women  in  2005.  Amongst  the  cancers,  malignant 
neoplasm of larynx and trachea/bronchus/lung were the most common cause of death for men 
(29% of all deaths due to cancer) while for women it was breast cancer (17% of all deaths due 
to cancer). Considering all ages, diseases of the respiratory system were the 3rd most frequent 
cause  of  death  (8%  of  all  deaths).  However,  as  illustrated  by  the  chart,  diseases  of  the 
digestive  system  were  far  more  frequent in  the  middle  age  groups.  More  than  163 000  men 
died through external causes of injury and poisoning in 2005; that were 7% of all deaths. This 
cause of death is particularly prominent for younger men (15-39) where almost half of deaths 
were  due  to  external  causes.  With  less  than  4%  of  all  deaths,  external  causes  played  a  less 
prominent role for women. 

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Density of health care professionals is getting higher 

Between 1995 and 2005, the density of physicians, dentists and nurses (expressed per 100 000 
opulation)  increased  in  almost  all  Member  States  but  the  figures  across  Europe  vary.  For 
doctors,  they  ranged  from  around  400  per  100 000  population  in  Belgium  and  Lithuania  to 
less than 240 in Poland, Romania, Slovenia and the United Kingdom. For dentists as many as 
95  per  100 000  population  were  reported  for  Cyprus  but  only  37  per  100 000  for  Poland. 
Density  of  physicians  increased  strongest  in  Ireland,  Luxembourg  and  Spain  while  Italy, 
Poland and Lithuania reported an overall slight decrease of their density rates (and Hungary 
with a decrease of 8% even a quite substantial one).  

Eight Member States discharged over 20,000 in-patients per 100 000 population in 2005 

The number of hospital discharges of in-patients ranged from less than 7,000 in Cyprus and 
Malta to over 20,000 in the Czech Republic, Germany, Latvia, Lithuania, Hungary, Austria, 
Romania and Finland. These differences may partly reflect the differences in organisation of 
healthcare services. Following the International Classification of Diseases (ICD), the highest 
share  of  discharges  was  reported  for  diseases  of  the  circulatory  system  (around  14%  of 
discharges  for  the  countries  with  available  data  by  diagnosis,  the  number  of  discharges  per 
100 000 ranging from less than 1,000 in Cyprus and Malta and 4,475 in Lithuania), followed 
by discharges for diseases of the digestive system (almost 10% of all discharges, in the Czech 
Republic,  Germany,  Austria  and  Romania,  more  than  2,000  in-patients  are  discharged  per 
year  due  to  digestive  diseases).  Cancers  and  injuries  also  played  an  important  role,  each 
accounting for around 9% of all hospital discharges. 

The number of hospital beds further decreases 

For many years the total number of hospital beds has decreased continuously in the EU. For 
EU-27,  it  decreased  over  20%  between  1995  and  2005.  With  up  to  400  beds  per  100 000 
inhabitants,  Denmark,  Spain,  Italy,  Cyprus,  Portugal  and  the  United  Kingdom  reported  the 
lowest number of beds per 100 000 in EU-27. The Czech Republic reported the highest rate 
with  850  hospital  beds  per  100 000  population,  followed  by  Germany  (846)  and  Lithuania 
(815).  All  these  numbers  refer  to  all  available  beds  in  both  public  and  private  hospitals.  A 
considerable share of the observed reduction in hospital beds is likely to have been caused by 
the  drop  in  the  length  of  hospital  stay  which  can  be  observed  all  across  the  EU.  Another 
reason  are  the  financial  constraints  which  arose  during  the  1990s  and  which  have  led  to  a 
rationalisation  of  healthcare  services  everywhere.  The  increased  demand  for  healthcare  for 
elderly people, many of whom are suffering from chronic disability and diseases, has in most 
cases been met by transferring beds for acute or psychiatric care to long-term care, while total 
numbers are still declining. 

Policy context 

The EC Treaty (Title XIII Public Health, Article 152) states that "Community action, which 
shall  complement  national  policies,  shall  be  directed  towards  improving  public  health, 
preventing human illness and diseases, and obviating sources of danger to human health. Such 
action shall cover the fight against the major health scourges, by promoting research into their 
causes, their transmission and their prevention, as well as health information and education." 

The Commission adopted a  White Paper entitled “Together for Health: A Strategic Approach 
for  the  EU  2008-2013”  in  October  2007.  This  White  Paper  establishes  a  broad  cross-policy 

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framework  to  respond  to  a  wide  range  of  health  challenges  such  as  health  inequalities,  the 
impact  of  population  ageing  on  society,  globalisation,  and  communicable  diseases  in  a 
comprehensive  and  coherent  way.  It  aims  to  provide  a  sense  of  direction  and  focus  to  EU 
health action and aims to pursue the following three general objectives: 

•  Foster good health in an ageing Europe by promoting good health throughout the lifespan;  

•  Protect citizens from health threats;  

•  and Support dynamic health systems and new technologies.  

In addition, principles such as solidarity, the need to reduce inequities, to promote investment 
in  health,  to  mainstream  health  in  all  policies,  and  to  strengthen  the  EU's  voice  in  global 
health are set out as horizontal issues underpinning all health action under the White Paper.  

The White Paper sets out a framework under which actions can be taken and proposes a set of 
18  concrete  priority  actions.  The  White  Paper  also  foresees  the  creation  of  a  structured  co-
operation  mechanism  to  implement  the  objectives  of  the  strategy  which  would  allow  the 
Commission, together with the Member States, to identify priorities, define indicators, foster 
good practice exchange, produce guidelines and measure progress. 

The  new  programme  of  Community  action  in  the  field  of  health  (2008-2013),  will  help  to 
support the implementation of this strategy. 

On  6  December  2007,  the  Council  adopted  conclusions  on  the  Health  Strategy  White 

Paper  that  welcome  its  objectives  and  principles;  emphasise  e.g.  health  in  all  policies, 

prevention,  threats  and  health  and  competitiveness;  underline  the  issues  of  gender  and 

migration and ask the Commission to present ideas for the implementation mechanism. 

In  October  2004  the  Council  endorsed  the  application  of  the  Open  Method  of  Coordination 
for  Social  Inclusion  and  Social  Protection  also  to  the  health  care  and  long  term  care  field. 
Member States agreed that the OMC can usefully be applied to this field to stimulate policy 
development, highlight common challenges and facilitate mutual learning (COM (2005) 706). 
Member States last reported on the challenges faced by their health care and long-term care 
systems, current reforms and planned policies, in the National Reports on Strategies for Social 
Protection  and  Social  Inclusion  in  the  autumn  200666.  Common  conclusions  were  drawn  in 
the Joint Report on social protection and social inclusion, adopted by the Council in February 
2007. 

Member States identified as a priority the need to: ensure equal access for all; reduce health 
inequalities in outcomes; guarantee safe and high-quality care; and manage the introduction of 
new  technology  for  health  and  independent  living.  More  rational  use  of  resources  is  an 
essential  factor  in  rendering  healthcare  systems  sustainable  and  in  maintaining  high  quality, 
which  needs  to  be  exploited  by  all  countries.  Some  countries  may  need  to  expand  their 
financial  and  human  resources  to  ensure  adequate  coverage  of  the  whole  population. 
Improved  coordination,  promotion  of  healthy  life  styles  and  prevention  could  be  win-win 

66 

Available at: http://ec.europa.eu/employment_social/social_inclusion/naps_en.htm 

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strategies,  contributing  both  to  improved  health  status  and  to  reduced  expenditure  growth. 
Different  policies  need  to  intervene;  social  protection  can  contribute  by  ensuring  access  to 
healthcare and prevention  for those who  need  it most but who  are  also the most  difficult to 
reach.  

Given  demographic  ageing  and  societal  change,  Member  States  consider  the  needs  for  long 
term  care  as  a  new  social  risk  that  needs  to  be  covered  by  social  protection  and  they  are 
committed to ensuring near universal access. They search for the right balance between public 
and  private  responsibilities  and  formal  and  informal  care,  while  recognising  the  need  for 
enabling  support  for  informal  carers.  Stronger  coordination  between  healthcare  and  social 
services, support for informal carers and exploiting new technology can help people to stay as 
long as possible in their own home. 

The European Commission has been also developing a new framework for "safe, high-quality 
and efficient cross-border healthcare". In the autumn 2006 it has published a Communication 
"Consultation  regarding  Community  action  on  health  services"  (SEC(2006)1195)  and 
launched  a  public  consultation.  The  contributions  to  the  consultation  were  summarised  in  a 
Summary Report67 and on that basis the Commission is developing proposals for a Directive 
on  the  application  of  patients'  rights  in  cross-border  healthcare  and  an  accompanying 
Communication. 

As well as setting out relevant legal definitions and general provisions, this new framework 
will be structured around three main areas: 

-  common  principles  in  all  EU  health  systems,  setting  out  which  Member  State  shall  be 
responsible  for  ensuring  compliance  with  the  common  principles  for  healthcare  and  what 
those  responsibilities  include,  in  order  to  ensure  that  there  is  clarity  and  confidence  with 
regard  to  which  authorities  are  setting  and  monitoring  healthcare  standards  throughout  the 
EU; 

-  a  specific  framework  for  cross-border  healthcare:  the  directive  will  make  clear  the 
entitlements of patients to have healthcare in another Member State, including the limits that 
Member States can place on such healthcare abroad, and the level of financial coverage that is 
provided for cross-border healthcare, based on the principle that patients are entitled to obtain 
reimbursement up to the amount that would have been paid had they obtained that treatment 
at home;  

-  European  cooperation  on  health  services:  the  directive  will  establish  a  framework  for 
European  cooperation  in  border  regions  and  in  areas  such  as  recognition  of  prescriptions 
issued  in  other  countries,  European  reference  networks,  health  technology  assessment,  data 
collection  and  quality  and  safety,  in  order  to  enable  the  potential  contribution  of  such 
cooperation to be realised effectively and on a sustained basis.  

Methodological notes 

Life  expectancy  at  birth  is  the  average  number  of  years  a  person  would  live  if  age-specific 
mortality  rates  observed  for  a  certain  calendar  year  or  period  were  to  continue.  Life 
expectancy  without  disability  (or  Healthy  Life  Years)  is  calculated  by  the  Sullivan  method 

67 

Summary Report is available at 
http://ec.europa.eu/health/ph_overview/co_operation/mobility/results_open_consultation_en.htm . 

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and  uses  mortality  data  from  demographic  statistics  and  prevalence  figures  of  persons  not 
being  limited  in  functioning/disability.  For  the  time  period  1995-2001,  prevalence  figures 
from the European Community Household Panel (ECHP) were used. For 2002 and 2003 the 
prevalence was estimated on the basis of the trend of the 1995-2001 ECHP data. For 2004 and 
2005, the Statistics on Income and Living Conditions survey (SILC) was used for calculating 
the  prevalence.  The  change  of  the  data  source  for  calculating  the  prevalence  (the  SILC 
question used for calculating the prevalence is not similar to the ECHP one) created a break in 
series  in  2004.  To  be  able  to  present  calculations  at  birth  (ECHP  and  SILC  data  covering 
population 16 years and more), Eurostat has, for all countries and for both genders, considered 
that the disability rate between the ages 0 and 14 is the half of the prevalence in the next age 
group (16-19). Data on perceived health are based on a self-evaluation question addressed to 
persons interviewed in the Statistics on Income and Living Conditions survey (SILC). For the 
total population (particularly aged 65 and over), the percentages on (very) bad health may be 
somewhat higher due to the fact that a significant number of people suffering important health 
problems live in homes or institutions for long-term nursing care which are not covered by the 
surveys. Practising physicians, dentists or nurses provide services directly to patients. Data on 
practising  health  care  professionals  are  best  used  to  describe  the  availability  of  health  care 
human  resources,  because  all  persons  included  here  immediately  produce  for  the  final 
demand. However, not all countries can provide data for practising health care professionals. 
Please note that the 'professionally active' or 'licensed to practise' data shown for a number of 
countries are not fully comparable due to the different concepts used. Total hospital beds are 
all hospital beds which are regularly maintained and staffed and immediately available for the 
care of admitted patients. Data on the number of beds reported to Eurostat are normally given 
as an annual average of beds in use during the year of reporting or according to concepts of 
registration or budgetary or planned approval. A hospital discharge is the formal release of a 
patient from a hospital after a procedure or course of treatment. Data shown refer to hospital 
in-patients  and  to  the  main  diagnosis.  Causes  of  death  (COD)  data  refer  to  the  underlying 
cause which – according to the World Health Organisation (WHO) – is "the disease or injury 
which initiated the train of morbid events leading directly to death, or the circumstances of the 
accident  or  violence  which  produced  the  fatal  injury".  COD  data  are  derived  from  death 
certificates. The medical certification of death is an obligation in all Member States. 

Links to other parts of the report 

Ageing in the population (2.3) and Health and safety (Annex 1.3.8). 

Further reading 

•  "Health statistics: Key data on Health 2002", 2002 edition. Eurostat. 

•  "Health in Europe", data 1998-2003, pocketbook, 2005 edition. Eurostat 

•  "Health statistics: Atlas of Mortality", 2002 edition. Eurostat. 

•  Eurostat  -  Demographic  Statistics  and  European  Community  Household  Panel  (ECHP) 

UDB version December 2003.  

•  OECD Health data 2006. 

•  "European social statistics – Population statistics", 2006 edition. Eurostat. 

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•  The  future  of  healthcare  and  care  for  the  elderly:  guaranteeing  accessibility,  quality  and 

financial viability – COM (2001) 723 

•  Modernising  social  protection  for  the  development  of  high-quality,  accessible  and 
sustainable  health  care  and  long-term  care:  support  for  the  national  strategies  using  the 
‘open method of coordination’ – COM (2004) 304 

•  Follow-up  to  the  high  level  reflection  process  on  patient  mobility  and  healthcare 

developments in the European Union – COM (2004) 301 

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EU-
27

EU-
25

EA-
13

BE BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Key indicator 17a

Life expectancy at birth, 2005 (The mean number of years that a newborn child is expected to live if subjected throughout her/his life to the mortality 
conditions (age specific probabilities of dying) of the year of her/his birth)

Females 80.8 81.2 82.0 81.9 76.2 79.3 80.5 82.0 78.2 81.7 81.6 83.7 83.8 82.8 81.1 76.5 77.3 82.2 77.2 81.4 81.7 82.3 79.3 81.3 75.7 80.9 78.1 82.5 82.9 81.1 78.8 75.9
74.6 75.1 76.0 76.2 69.0 72.9 76.0 76.7 67.3 77.3 76.8 77.0 76.7 77.1 76.8 65.4 65.3 76.6 68.7 77.3 77.3 76.7 70.8 74.9 68.7 73.9 70.2 75.6 78.5 77.1 71.8 71.6
Males

:
:

Notes: FR: 2004; EU-27, EU-25, EU-15, Euro-zone, IT: 2003 data.

Sources: Eurostat - Demographic statistics

Key indicator 17b
61.9p
:
Females
61.7p
:
Males

:
:

Source: Eurostat - Health Statistics.

Healthy Life Years at birth, 2005 (The mean number of years that a newborn child is expected to live in healthy condition if subjected throughout her/his life 
to the current morbidity and mortality conditions (age specific probabilities of becoming sick/dying))
59.9p 68.2p 55.1p 52.2p 64.1p 67.2p 63.1p 64.3p 67.0p 57.9p 53.1p 54.3p 62.1p 53.9p 70.1p 63.1p 59.6p 66.6p 56.7p
57.9p 68.4p 55.0p 48.0p 62.9p 65.7p 63.2p 62.0p 65.8p 59.5p 50.6p 51.2p 62.2p 52.0p 68.5p 65.0p 57.8p 61.0p 58.4p

59.9p 56.4p 52.4p 63.1p 65.0p
56.3p 54.9p 51.7p 64.2p 63.2p

:
:

:
:

:
:

:
:

Major causes of death by age-group, EU-27, 2005

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

0 
1 - 4

10 - 14
5 - 9

15 - 19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 - 74

75 - 79

80 - 84

Other

External causes of
injury and
poisoning

Cancer

Diseases of the
digestive system

Diseases of the
respiratory system

Diseases of the
circulatory system

Total

Notes: 1) BE: 1997; DK: 2001; IT: 2002; SE: 2004.   Source: Eurostat - Mortality Statistics.

2) Cancer = Malignant neoplasms including leukaemias and lymphomas.
3) In the age group 0 (= less than 1 year) the principal causes of death were 'Certain conditions originating in the perinatal 
period' (48.7%) and 'Congenital malformations and chromosomal abnormalities' (26.5%), which in the graph are included 
in 'Other'.

Persons discharged from hospitals per 100,000 population, 2005 or closest  year available (2002-2004)

30 000

25 000

20 000

15 000

10 000

4
6
0

3
1

5
0
5

3
1

5
3
1

0
1

0
8
8

9

0
8
7

0
1

7
1
6

6

1
7
8

6

2
5
8

9
1

8
0
1

0
2

4
6
1

0
2

5
0
3

0
2

4
1
5

0
2

4
2
1

9
1

3
2
9

7
1

2
4
2

7
1

1
5
7

4
1

8
2
9

4
1

8
5
3

5
1

6
3
9

5
1

4
8
0

6
1

5
4
4

6
1

9
0
8

6
2

6
5
2

5
2

0
3
0

3
2

1
1
4

2
2

7
0
3

3
1

1
8
8

9

5 000
Notes: 2001 except: BE, DK, ES, FR, LU, AT, UK, SI and TR: 2000; EU-15, DE, EE, IT, HU and PL: 1999; EL: 1998. UK includes only England.

Source: Eurostat - Health and safety statistics.

 0

CY

MT

PT

NL

ES

UK

IE

SE

IT

SI

DK

BE

FR

LU

EE

SK

BG

LV

DE

RO

FI

LT

CZ

HU

AT

EL

PL

MK

HR

TR

Notes: 2005 data , except IT, MT, FI: 2004; DK, SE, UK: 2003; DE, LV, HU, PT: 2002.

Source: Eurostat - Health and safety statistics.

EN 

189 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
18. 

ACCIDENTS AND WORK-RELATED HEALTH PROBLEMS 

In 2004, around 3.2% of workers in EU-15 were victims of a working accident resulting in 
more than three days' absence, 5.3% including accidents with no absence from work or an 
absence of up to 3 days. From 1998, the number of accidents at work with more than three 
days' absence decreased in by 21% (the value of the index 1998 = 100 was 79 in 2004) in 
EU-25 and by 22% in EU-15. In 2005 around 500 million working days were lost in as a 
result  of  accidents  at  work  and  work-related  health  problems  in  EU-27.  Road  transport 
fatalities  decreased  29%  from  1995  to  2005  in  EU-27,  but  there  were  still  around  45 000 
deaths  on  EU-27  roads  recorded  in  2005.  During  the  ten-year  period  1996-2005  over 
540 000 people lost their lives in road accidents in EU-27. 

Working accidents more frequent among younger and low seniority workers 

In 2004, around 4.0 million accidents at work - that resulted in more than three days’ absence 
-  were  recorded  in  the  15  old  Member  States  of  the  EU.  Including  the  accidents  with  no 
absence from work or an absence of up to three days, the estimated total number of accidents 
at  work  in  the  EU-15  is  6.4  million  in  2004.  This  represents  respectively  estimated  rates  of 
3 180 and 5 250 accidents at work per 100 000 employed people, or put another way, 5.3% of 
all workers were the victims of an accident at work during the year (3.2% for accidents with 
an absence of more than 3 days). There was a substantial drop in this rate (accidents resulting 
in more than three days absence) of 22% between 1998 and 2004 (index = 78 in 2004 and 100 
in  1998).  In  addition,  4 366  fatal  accidents  in  the  course  of  work  were  recorded  in  2004  in 
EU-15, of which 40% were road traffic or transport accidents during work. The incidence rate 
is 3.8 fatalities per 100 000 employed people against 6.1 in 1994 and 3.9 in 2003 (-38% and -
3%  respectively).  The  new  Member  States  and  candidate  countries  are  gradually 
implementing  the  European  Statistics  of  Accidents  at  Work  (ESAW)  data  collection 
methodology. In EU-25, between 1998 and 2004, the incidence rate of fatal accidents at work 
has decreased by 24% and the incidence rate of non-fatal accidents at work by 21%.  

These proportions differ of course on the economic activity and the size of the enterprise, as 
well as the age, sex and working conditions of the workers. The construction industry has the 
highest incidence  of accidents  resulting in more than three days  absence, though decreasing 
since  1994:  6 300  per  100 000  workers  in  2004  against  9 000  in  1994.  Agriculture  has  the 
second highest incidence: 5 100 in 2004 (6 500 in 1994). For fatal accidents agriculture has 
the highest incidence, around 12 per 100 000 workers in 2004 and construction has the second 
highest,  around  10  per  100  000  workers.  In  addition  one  must  bear  in  mind  that  systematic 
and annual data are not available for some economic activities, like fishing, which according 
to ad hoc surveys are at a high risk of accidents. When including accidents up to three days 
absence  (1998-1999  data  from  the  ad  hoc  module  in  the  European  Union  Labour  Force 
Survey),  the  accident  rate  is  particularly  high  in  the  fishing  industry  (where  the  risk  of  an 
accident is 2.4 times greater than the average for all branches in the EU). Taking all economic 
activities together, the risk of accidents was in 2004 the highest in local units employing 10 to 
49 people and those employing 50-249 people. In these size categories the incidence rate of 
accidents  at  work  was  1.3  an  1.4  times  higher,  respectively,  than  in  local  units  employing 
more  than  250  people.  For  non-fatal  accidents  at  work  the  incidence  rates  are  the  highest 
among the young workers. Among those aged 18-24 years the incidence rate is 30-70% higher 
than in the other age category. In contrast, the incidence of fatal accidents tends to increase 
considerably  with  age.  Men  are  2.5  times  more  likely  than  women  to  have  an  accident  - 

EN 

190 

   EN 

 
resulting  in  more  than  three  days  absence  -  and  about  12  times  more  likely  to  have  a  fatal 
accident. This result is a function of men’s jobs and sectors of activity which tend to be more 
high-risk  than  those  of  women.  There  are  also  relatively  more  women  who  work  part-time 
which reduces their exposure to risk 

Accidents at work: 138 million days lost to the economy 

In  addition  to  the  major  impact  of  these  accidents  in  human  terms,  they  also  have  a  high 
socio-economic cost: though, according to previous data, for 37% of accidents there was no 
absence from work or the resulting absence was only up to three days, in 2004 for 30% the 
absence  was  more  than  three  days  but  less  than  two  weeks  and  for  29%  the  absence  was 
between  two  weeks  and  three  months.  For  the  remaining  4%  of  accidents,  the  consequence 
was  an  absence  of  three  months  or  more,  or  permanent  partial  or  total  disability.  It  is 
estimated  that  138  million  work  days  were  lost  in  2004  in  the  EU15  owing  to  accidents  at 
work, i.e. a mean of 22 days per accident for those who had an absence due to an accident at 
work (33 days per accident with more than three days absence) and the equivalent of one day 
of  work  lost  per  year  for  every  person  in  employment.  Additionally,  5%  of  the  victims  say 
they  had  to  change  to  a  different  type  of  work  or  another  job,  or  to  reduce  working  hours. 
Finally, about 14% of the victims of accidents at work suffer more than one accident per year. 
Accidents at work are estimated to cause annually costs of 55 billion euros in EU-15. Most of 
these costs are due to lost working time, but on the other hand, reliable data on other type of 
costs  of  accidents  at  work  (e.g.  health  care  costs)  are  difficult  to  collect  and  therefore  such 
costs have probably been underestimated in the above figure. 

460 million working days lost due to work-related health reasons 

According to the results of the Fourth European Survey on Working Conditions, carried out 
by the European Foundation for the Improvement of Living and Working Conditions in 2005, 
there was an average of 4.6 annual days off work because of health-related reasons for each 
worker  in  the  EU-27.  Of  these,  2.2  days  were  due  an  accident  at  work  or  a  work-related 
illness.  This  equals  to  roughly  460  lost  working  days  due  to  work-related  health  reasons. 
These  figures  do  not  include  the  days  lost  due  to  permanent  disability  as  only  employed 
persons were questioned. According to the same survey 35% of the workers of EU-27 say that 
their  work  affects  their  health,  ranging  from  61%  in  agriculture  to  21%  in  financial 
intermediation.  The  most  often  reported  work-related  health  problems  were  backache, 
muscular  pain,  fatigue  and  stress.  Physical  risk  factors  like  vibration,  noise,  handling  of 
chemicals,  painful  and  tiring  positions  as  well  as  repetitive  movement  continue  to  affect  a 
significant  proportion  of  the  workforce.  Meanwhile  the  occurrence  of  violence  at  work 
appears  to  be  increasing,  especially  in  certain  sectors  like  health  and  education  where  15% 
and 8% of workers, respectively report violence at work.  

About 630 000 commuting accidents in EU-15 

The  number  of  commuting  accidents  (accidents  on  the  way  to  and  from  work)  resulting  in 
more than three days’ absence was estimated at approximately 630 000 in 2003 in EU-15 (in 
addition to accidents at work). The incidence rate was 430 per 100 000. The number of fatal 
commuting  accidents,  which  were  chiefly  road  traffic  and  transport  accidents,  was  around 
3 000 for EU-15. 

EN 

191 

   EN 

 
EU-27 roads claimed around 45 000 lives in 2005 

For the EU-27 as a whole, the number of road accident fatalities decreased 29% from 1995 to 
2005, when around 45 000 deaths were caused by road accidents. During the ten-year period 
1996-2005 over 540 000 people lost their lives in road accidents in EU-27. The annual data 
1995-2005 per country is given in the annex 1.3.8. 

In  all  Member  States  and  Candidate  Countries  (no  data  available  Turkey)  there  died  much 
more men than women in transport accidents (road transport and other transport accidents) in 
the  year  2000.  The  lowest  standardised  death  rates  were  observed  in  Malta  (13  women  per 
million women and 62 men per million men), the Netherlands (28 and 77), Sweden (23 and 
85)  and  the  United  Kingdom  (26  and  88)  and  the  highest  ones  in  Cyprus  (44  and  281), 
Lithuania (90 and 410) and Latvia (105 and 345). 

Home and leisure accidents 

There were an estimated 430 000 home and leisure accidents in the EU-15 in 1995 (men had 
240 000,  women  190 000).  Accidents  are  most  likely  to  occur  at  home  (32%  of  the  total 
number of accidents among men, 46% among women) followed by sporting accidents (18% 
among men, 10% among women). 

Policy context 

The  EC  Treaty  (Article  137)  states  that  "the  Community  shall  support  and  complement  the 
activities  of  the  Member  States  in  …  (the)  improvement  in  particular  of  the  working 
environment to protect workers’ health and safety." Art.140 adds that "the Commission shall 
encourage  cooperation  between  the  Member  States  and  facilitate  the  coordination  of  their 
action in all social policy fields under this chapter, particularly in matters relating to … (the) 
prevention of occupational accidents and diseases". 

On 20.6.2001 the Commission gave the Communication on “Employment and social policies: 
a framework for investing in quality”. It takes forward the Social Policy Agenda commitment 
and the Lisbon strategy reinforced by Nice and Stockholm, to promote quality in employment. 
In particular it defines the approach of improving quality of work and ensures its integration 
in employment and social policies. For this purpose it establishes a set of indicators on quality 
in work to be used within the framework of the European Employment Strategy.  

The lists of indicators of both the Synthesis Report and the Employment Committee Report 
on Indicators of Quality in Work include the evolution (index 1998=100) of the incidence rate 
of  accidents  at  work,  as  defined  by  the  number  of  accidents  at  work  per  100 000  people  in 
employment.  

More  recently,  on  21.02.2007,  the  Commission  adopted  a  Communication  (COM(2007)  62 
final)  on  “Improving  quality  and  production  at  work:  Community  strategy  2007-2012  on 
health  and  safety  at  work”  and  on  25.07.2007  the  Council  adopted  a  Resolution  on  “a  new 
Community  strategy  on  health  and  safety  at  work  (2007–2012)”.  Among  other,  the 
Community  strategy  2007-2012  identify  research  priorities  including  psychosocial  issues, 
musculoskeletal  disorders,  dangerous  substances,  knowledge  of  reproductive  risks, 
occupational  health  and  safety  management,  risks  associated  with  several  cross-factors  (e.g. 
work organisation and workplace design issues, ergonomics, combined exposure to physical 
and  chemical  agents)  and  potential  risks  associated  with  nanotechnologies.  The  Council 

EN 

192 

   EN 

 
Resolution  states  as  one  of  the  main  objectives:  “to  achieve  an  ongoing,  sustainable  and 
consistent  reduction  in  accidents  at  work  and  occupational  illnesses"  and  it  supports  the 
Commission  in  seeking  to  reduce  the  incidence  rate  of  accidents  at  work  by  25%  at 
Community level. National strategies should seek to establish measurable targets for reducing 
incidence  of  occupational accidents  and  illnesses for relevant categories of worker, types of 
company and/or sectors.  

In  its  2001  Transport  White  Paper,  the  Commission  proposed  the  ambitious  goal  to  save 
yearly 25.000 lives on European roads by the target date of 2010. This target has meanwhile 
been  endorsed  by  the  European  Parliament  and  all  Member  States.  In  2003,  the  European 
Road Safety Action Programme was tabled, containing many concrete measures proposed to 
achieve  this  goal.  And  in  February  2006,  the  Commission  has  issued  a  mid-term  review  on 
our common endeavours to halve road fatalities. Summing up, Europe has achieved a lot in 
the last five years, but we need to do more together to achieve our objective. 

The  "CARS21"  Report  of  December  2005  and  the  mid-term  review  of  the  Transport  White 
paper of June 2006 provide some guidance on the strategic direction of the European Union 
concerning road safety. 

In Europe, the agreed method to more road safety is the principle of "shared responsibility". 
Beyond all institutional rhetoric, each and everyone has a role to play to make Europe’s road 
safer.  In  this  respect,  the  European  Road  Safety  Charter  is  central,  inviting  all  members  of 
society,  be  they  for  instance  a  local  school,  a  rural  association  or  a  large  multinational 
company, to make their own measurable contribution to improving road safety. 

Finally,  road  safety  initiatives  are  -  or  should  be  -  underpinned  by  solid  statistical  data  on 
accident  causes  and  other  relevant  issues.  The  collection  and  analysis  of  data,  today  in  the 
European  CARE  accident  data  base,  tomorrow  in  the  European  Road  Safety  Observatory  is 
essential to devise effective and proportionate measures to improve road safety. 

To achieve its objectives, the Commission proposes legislation and political action, but makes 
also some funding available through the European Research Framework Programmes and its 
Road Safety Subvention Programme. 

Methodological notes 

Sources:  Eurostat  -  European  Statistics  on  Accidents  at  Work  (ESAW),  ad  hoc  module  on 
accidents at work and occupational diseases in the 1999 Labour Force Survey and Transport 
Statistics.  European  Commission  Transport  DG  -  Community  Road  Accident  database 
(CARE). European Home and Leisure Accident Surveillance System (EHLASS).  

For  road  accidents,  people  killed  are  all  those  killed  within  30  days  of  the  accident.  For 
Member States not using this definition, corrective factors were applied. 

The data on working accidents relate to almost 90% of people in employment in the EU-15. 
The  new  Member  States  are  in  the  process  of  implementing  the  full  ESAW  methodology. 
Only those working accidents that lead to more than three days absence are included in  the 
annual ESAW data but accidents with no absence from work or resulting in an absence from 
work from one to three days were also covered in the ad hoc module on accidents at work and 
occupational diseases in the 1999 Labour Force Survey which is being repeated in 2007. The 
ESAW  incidence  rates  have  been  calculated  for  only  nine  major  branches  of  economic 
activity (NACE Rev. 1 sections).  

EN 

193 

   EN 

 
The fourth European Survey on Working Conditions was carried out in 2005 by the European 
Foundation  for  the  Improvement  of  Living  and  Working  Conditions.  The  previous  surveys 
were carried out in 1990, 1996 and 2000. 

The  EHLASS  (European  Home  and  Leisure  Accident  Surveillance  System)  was  introduced 
by the Council Decision 93/683/EEC of 29 October 1993 introducing a Community system of 
information on home and leisure. Since 1999 the EHLASS system has been integrated into the 
Community Programme of Prevention of Injuries. 

Links to other parts of the report 

Health and safety (Annex 1.3.8). 

Further reading 

•  http://ec.europa.eu/transport/roadsafety/index_en.htm  

•  Work  and  Health  in  the  EU  –  A  statistical  portrait.  Panorama  series  -  2003  edition  - 

Eurostat. 

•  “European social statistics – Accidents at work and work-related health problems – Data 

1994-2000” – Detailed tables series - 2002 edition - Eurostat. 

•  Statistics in Focus (Transport): "EU road safety 2004: Regional differences", No 14/2007; 

Eurostat.  

•  “European  Statistics  on  Accidents  at  Work  -  Methodology",  2001  Edition.  Eurostat  and 

DG Employment and social affairs, “Health and safety at work” series. 

•  “Panorama of transport” (2007 edition), 2007. Eurostat. 

•  “Fourth  European  Survey  on  Working  Conditions"  European  Foundation  for  the 

Improvement of Living and Working Conditions (http://www.eurofound.europa.eu). 

•  “Guidance on work-related stress - Spice of life or kiss of death?", European Commission, 

16 December 2002.  

•  Communication  from  the  Commission  COM(2007)  62  final  of  21.2.2007  "Improving 
quality and productivity at work: Community strategy 2007-2012 on health and safety at 
work". 

•  Council Resolution of 25 June 2007 on a new Community strategy on health and safety at 

work (2007-2012) [O.J. C145 of 30.06.2007, page 1]. 

EN 

194 

   EN 

 
EU-
27

EU-
25

EA-
13

BE

BG CZ DK DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU HU MT NL

AT

PL

PT RO SI

SK

FI

SE UK HR MK

TR

Key indicator 18a

Serious accidents at work, 2004 (Index of the number of serious accidents at work per 100 thousand persons in employment 
(1998=100))

Total
Females
Males

:
:
:

79
89
81

:
:
:

65
71
65

58
61
60

81
94
77

79
90
77

73
77
74

124
126
132

94
87
95

66
65
67

92
98
95

90
107
87

75
77
78

103
100
104

79
:
:

82
81
80

94
96
97

79
93
75

83
77
86

73
95
72

79
72
86

84
92
82

75
84
75

103
97
107

98
109
93

54
62
52

83
90
83

86
85
88

88
81
89

:
:
:

:
:
:

82
: 
: 

Source: Eurostat - European Statistics on Accidents at Work (ESAW)

Key indicator 18b

Fatal accidents at work, 2004 (Index of the number of fatal accidents at work per 100 thousand persons in employment (1998=100))

:

76

:

93

84

78

35

100

75

84

67

59

68

50

92 i

98

113 20 i

96

90 i

84

107

86

82

103

77

64

102

81

90

:

:

64

Note: In CY, LU and MT the values are based on small annual numbers. 
Source: Eurostat - European Statistics on Accidents at Work (ESAW)

Accidents at work by type of activity, EU-15, 2004

Construction

Agriculture, hunting and forestry

Transport, storage and communication

Manufacturing

Hotels and restaurants

6 257

5 068

3 719

3 564

3 041

Wholesale and retail trade; repairs

2 191

Financial intermediation and real estate activities

1 444

1 000

2 000

3 000

4 000

5 000

6 000

7 000

per 100 000 employed persons

Source: Eurostat - European Statistics on Accidents at Work (ESAW)

Number of transport accident deaths per million population (SDRs) by sex, 2004

Females

Males

Total

7
3
2

7
2
2

9
3
5 2
1
2

4
4
8 2
2
2

3
5
2

9
5
2

0
1
4

5
4
3

286

1
8
6 2
5
2

216

240

8
5
7 1
3
1

7
5
1

8
5
1

98 100 100 103

8
7
2 1
6
1

9
7
1

4
8
1

3
8
1

113 113 118 119

8
2
0 1
1
1
77

84

6
0
1
70

8
8
57

8
2
1

85

86

5
5 4

6 3
2

2
4

5
4

0
4

3
4

4
4

4
4

6
4

136 141 142 143 143 149 155 158 159 164

0
5

2
5

6
5

8
5

5
5

0
5

1
7

0
6

4
6

4
6

3
6

5
6

2
7

4
4

1
3
2

136

9
4

8
1
1

69

4
2

5
0
0 1
9

400

350

300

250

200

150

100

50

0

5
7 8
2 7
54
51
6
38

8
2

3
2

3
1

T
M

L
N

E
S

K
U

E
D

E

I

K
D

I

F

R
F

T
A

3
1
-
A
E

5
2
-
U
E

7
2
-
U
E

S
E

U
L

G
B

Z
C

K
S

I

S

E
B

E
E

O
R

U
H

T
P

L
P

T

I

L
E

Y
C

T
L

V
L

K
M

R
H

R
T

Notes: 1) BE 1997, DK 2001, RO 2003 and HR 2002 data. 2) TR: No data. 3) SDR = Standardised death rate - As most causes of death vary significantly with people's age and sex, the use of SDRs improves comparability over time and 
between countries, as they aim at measuring death rates independently of different age structures of populations. The SDRs used here are calculated by using the World Health Organisation’s standard European population.

Source: Eurostat - Mortality Statistics.

EN 

195 

   EN 

 
Annexes to Part 2

Annex 1.1   Key indicators per geopolitical entity*, latest year available

Annex 1.2   Key indicators per geopolitical entity*, time series (mainly latest 10 years, when available)

Annex 1.3   Other statistical tables per geopolitical entity*

1  Economy

2  Population

3  Education and training

4  Labour market

5  Social protection

6  Income, social inclusion and living conditions

7  Gender equality

8  Health and safety

Annex 2      Symbols, country codes and country groupings, other abbreviations and acronyms   

* geopolitical entity = a country or a group of countries (EU-27, EU-25 and EA-13)

EN 

196 

EN 

 
  
 
ANNEX 1.1 - KEY INDICATORS PER GEOPOLITICAL ENTITY - LATEST YEAR AVAILABLE 

EN 

197 

EN 

 
  
Reading notes and other notes are after the table.

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain France

Italy Cyprus

Latvia Lithuania

Unit

Time

Sex

EU-27

EU-25 EA-13

3.0

3.0

2.8

BE

3.2

BG

6.1

CZ

6.4

DK

3.5

DE

2.9

490 898

461 479

314 888

10 446

7 761

10 221

5 411

82 501

%

2006

1 000

1.1.2005

EE

11.2

1 348

IE

5.7

EL

4.3

ES

3.9

FR

2.0

IT

1.9

4 109

11 083

43 038

60 702

58 462

Domain

Nr Key indicator

Economy

Population

1

2

Real GDP growth rate

Total population

3 Old age dependency ratio

4

5

Education 
and training

Crude rate of net migration including adjustments and corrections

Youth education attainment level

6

Lifelong learning   

Labour 
market

7a Employment rate

7b Employment rate of older workers

8a Unemployment rate

8b

Long-term unemployment rate

9

Public expenditure on LMP measures (categories 2-7) as a percentage of GDP

10 Expenditure on social protection as a percentage of GDP

11a Old age and survivors benefits as a percentage of total social benefits

11b Sickness and health care benefits as a percentage of total social benefits

12

Inequality of income distribution

13a At-risk-of-poverty rate before social transfers

13b At-risk-of-poverty rate after social transfers

14a People aged 18-59 living in jobless households

14b Children aged 0-17 living in jobless households

15a Percentage of women in the single or lower House of the national or federal Parliament

15b Percentage of women in the European Parliament

16 Gender pay gap in unadjusted form   

17a Life expectancy at birth

Social 
protection

Income, 
social 
inclusion 
and living 
conditions

Gender 
equality

Health and 
safety

.

total

total

total

total

females

males

total

females

males

total

females

males

total

females

males

total

females

males

total

females

males

total

total

total

total

total

total

females

males

total

females

males

total

males

total

2005

2005

2006

2006

2006

2006

2006

2006

2005

2004

2004

2004

2005

2005

2005

2007

2007

8/2007

females

10/2007

females

2003

2005

females

females

males

%

per 1 000

%

%

%

%

%

%

%

%

%

%

Ratio

%

%

%

%

%

%

%

Year

17b Healthy Life Years at birth

Year

2005

females

18a Serious accidents at work (1998 = 100)

18b Fatal accidents at work (1998 = 100)

2004

males

total

females

males

2004

total

Index

point

Index
point

24.6

3.6

77.8

80.7

74.8

9.6

10.4

8.8

64.4

57.2

71.6

43.5

34.8

52.6

7.9

8.8

7.2

3.6

4.0

3.3

0.525

:

:

:

24.8

3.8

77.7

80.9

74.7

10.1

11.0

9.2

64.7

57.4

72.0

43.6

34.9

52.8

7.9

9.0

7.1

3.6

4.0

3.2

:

27.3

45.9

28.3

4.9 s

4.9 s 

26 s

26 s

25 s

16 s

17 s

15 s

9.3 e 

26 s 

27 s 

25 s 

16 s 

17 s 

15 s 

9.3 e

8.3 e

9.4 e 

23.1

31.2

15 s

80.8

74.6

:

:

:

:

:

:

8.2 e

9.3 e

23.6

30.8

15 s

81.2

75.1

:

:

79

89

81

76

26.1

4.7

73.8

77.6

70.1

8.2

8.6

7.9

64.6

56.7

72.6

41.7

32.9

50.8

7.9

9.3

6.8

3.6

4.2

3.1

:

27.7

46.5

28.2

4.6 s

24 s

25 s

23 s

15 s

16 s

14 s

8.8 e 

9.7

8 e

7.7 e 

25.5

32.9

15 s

82.0

76.0

26.3

4.9

82.4

85.6

79.1

7.5

7.6

7.4

61.0

54.0

67.9

32.0

23.2

40.9

8.2

9.3

7.4

4.2

4.9

3.7

24.8

0.0

80.5

81.1

80.0

1.3

1.3

1.3

58.6

54.6

62.8

39.6

31.1

49.5

9.0

9.3

8.6

5.0

5.2

4.8

19.8

3.5

91.8

92.4

91.1

5.6

5.9

5.4

65.3

56.8

73.7

45.2

32.1

59.5

7.1

8.8

5.8

3.9

4.9

3.1

22.7

1.2

77.4

81.5

73.4

29.2

33.8

24.6

77.4

73.4

81.2

60.7

54.3

67.1

3.9

4.5

3.3

0.8

0.9

0.7

27.8

1.0

71.6

73.5

69.8

7.5

7.3

7.8

67.5

62.2

72.8

48.4

40.6

56.4

8.4

9.2

7.7

4.7

5.2

4.4

24.3

0.1

82.0

89.8

74.1

6.5

8.6

4.2

68.1

65.3

71.0

58.5

59.2

57.5

5.9

5.6

6.2

2.8

2.6

3.1

16.4

15.9

85.4

89.1

81.8

7.5

8.9

6.1

68.6

59.3

77.7

53.1

39.1

67.0

4.4

4.1

4.6

1.4

0.9

1.8

26.8

3.6

81.0

86.6

75.5

1.9

1.8

2.0

61.0

47.4

74.6

42.3

26.6

59.2

8.9

13.6

5.6

4.8

8.0

2.6

24.4

14.8

61.6

69.0

54.6

10.4

11.5

9.3

64.8

53.2

76.1

44.1

28.7

60.4

8.5

11.6

6.3

1.8

2.8

1.2

24.9

3.3

82.1

84.3

80.0

7.5

7.8

7.2

63.0

57.7

68.5

37.6

35.2

40.1

9.5

10.4

8.7

4.0

4.3

3.7

29.3

5.5

75.5

79.4

71.7

6.1

6.5

5.7

58.4

46.3

70.5

32.5

21.9

43.7

6.8

8.8

5.4

3.4

4.5

2.6

0.852

0.432

0.122

1.433

0.616

0.047

0.481

0.061

0.583

0.664

0.461

29.3

44.1

27.7

4.0

28

29

27

15

15

14

12.5

14.4

10.7

13.5

34.7

33.3

7

81.9

76.2

:

:

:

:

:

:

61.9 p

61.7 p

65

71

65

93

:

:

:

19.6

41.1

35.3

3.7 i 

3.7 b 

30.7

37.2

20.6

3.5

30

31

28

12

12

12

:

:

:

:

36.9

42.9

18

80.5

76.0

29.5

43.5

27.2

3.8 b

23 b

24 b

22 b 

12 b 

13 b

11 b

9.5

9.9 p

9.2 p

9.3 p

31.6

32.3

22

82.0

76.7

13.4

43.7

31.5

5.9

24

25

23

18

20

17

6.0

5.7

6.3

7.3

21.8

50.0

25

78.2

67.3

17.0

23.3

42.1

5.0

32

34

30

20

21

19

7.8

5.7

6.4

11.2

13.3

38.5

9p

81.7

77.3

26.0

50.9

26.5

5.8

23

24

21

20

21

18

8.0

9.1

6.0

3.9

13.0

33.3

9p

81.6

76.8

20.0

43.7

30.8

5.4

24

25

23

20

21

19

6.0

10.0

5.6

5.0

36.0

32.1

13p

83.7

77.0

31.2

43.6

30.0

4.0

26

27

25

13

14

12

10.9 p 

12.0 p 

9.7 p

9.8

18.5

43.6

12

83.8

76.7

21 b 

22 b 

20 b 

10 b 

11 b 

10 b 

6.5

8.1

4.9

7.9

15.5

20.8

19

79.3

72.9

59.9 p

57.9 p

68.2 p

68.4 p

55.1 p

55.0 p

52.2 p

48.0 p

64.1 p

62.9 p

67.2 p

65.7 p

63.1 p

63.2 p

64.3 p

62.0 p

81

94

77

78

79

90

77

35

73

77

74

100

DE

124

126

132

75

EE

94

87

95

84

IE

66

65

67

67

92

98

95

59

90

107

87

68

EL

ES

FR

26.1

61.3

25.9

5.6

23

25

22

19

21

17

9.1

10.3

7.8

5.8

17.3

16.7

9

82.8

77.1

67.0 p

65.8 p

75

77

78

50

IT

17 i

19 i

15 i

14 i 

15 i 

13 i

10.0

9.9

10.1

12.9

22.1

44.4

16

76.2

69.0

:

:

58

61

60

84

females

10.3 e 

10.3 e

CY

3.8

 749

17.3

19.0

83.7

90.7

76.1

7.1

7.8

6.5

69.6

60.3

79.4

53.6

36.6

71.6

4.6

5.4

4.0

0.9

1.2

0.7

:

17.8

48.3

24.1

LV

11.9

2 306

LT

7.5

3 425

24.1

-0.2

81.0

86.2

75.9

6.9

9.3

4.1

66.3

62.4

70.4

53.3

48.7

59.5

6.8

6.2

7.4

2.5

1.9

3.0

22.3

-2.6

88.2

91.2

85.3

4.9

6.6

2.9

63.6

61.0

66.3

49.6

45.1

55.7

5.6

5.4

5.8

2.5

2.4

2.5

0.148

0.147

12.6

50.0

24.5

13.3

47.3

29.5

4.3 b 

6.7 b 

6.9 b 

22 b 

23 b 

20 b 

16 b 

18 b 

15 b 

4.5

4.9

4.1

3.7

14.3

0.0

25

81.1

76.8

26 b 

27 b 

24 b 

19 b 

20 b 

18 b 

7.1

7.7

6.4

8.6

19.0

22.2

16

76.5

65.4

26 b 

27 b 

25 b 

21 b 

21 b 

20 b 

6.3

6.3

6.4

6.9

24.8

38.5

15

77.3

65.3

57.9 p

59.5 p

53.1 p

50.6 p

54.3 p

51.2 p

103

100

104

92 i

79

:

:

98

CY

LV

82

81

80

113

LT

Domain

Nr Key indicator

Unit

Time

Sex

EU-27

EU-25 EA-13

BE

BG

CZ

DK

EN 

198 

EN 

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain France

Italy Cyprus

Latvia Lithuania

 
  
 
Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

4
Croatia FYROM

Turkey

HR

MK

TR Sex

Time

Unit

Key indicator

Nr Domain

LU

6.2

 455

21.3

6.0

96.3

74.5

64.0

8.2

8.7

7.6

63.6

54.6

72.6

33.2

27.8

38.7

4.7

6.2

3.5

1.4

1.6

1.2

:

22.6

36.5

25.0

3.8

23

23

23

13

13

13

7.5

8.6

6.3

4.0

23.3

50.0

14

82.2

76.6

94

96

97

20 i

LU

HU

3.9

10 098

22.7

1.7

82.9

84.7

81.2

3.8

4.4

3.1

57.3

51.1

63.8

33.6

27.1

41.4

7.5

7.8

7.2

3.4

3.4

3.3

0.197

20.7

42.5

29.5

MT

3.2

 403

19.3

2.4

50.4

52.8

48.1

5.5

5.6

5.5

54.8

34.9

74.5

30.0

11.2

50.4

7.3

8.9

6.5

2.9

2.5

3.1

:

18.8

51.2

27.0

29 b 

29 b 

30 b 

13 b 

13 b 

14 b 

11.8

12.9

10.7

14.0

10.4

37.5

11

77.2

68.7

79

93

75

96

21 b 

22 b 

20 b 

15 b 

16 b 

14 b 

6.9

8.3

5.6

8.4

9.2

0.0

4

81.4

77.3

70.1 p

68.5 p

83

77

86

90 i

NL

3.0

AT

3.3

PL

6.1

PT

1.3

RO

7.7

SI

5.7

16 306

8 207

38 174

10 529

21 659

1 998

SK

8.3

5 385

FI

5.5

SE

4.2

UK

2.8

5 237

9 011

60 060

20.8

-1.4

74.7

79.6

69.9

15.6

15.9

15.3

74.3

67.7

80.9

47.7

37.2

58.0

3.9

4.4

3.5

1.7

1.8

1.6

23.5

6.8

85.8

86.7

84.9

13.1

14.0

12.2

70.2

63.5

76.9

35.5

26.3

45.3

4.7

5.2

4.4

1.3

1.3

1.3

18.7

-0.3

91.7

93.8

89.6

4.7

5.1

4.3

54.5

48.2

60.9

28.1

19.0

38.4

13.8

14.9

13.0

7.8

8.6

7.1

25.2

3.6

49.6

58.6

40.8

3.8

4.0

3.7

67.9

62.0

73.9

50.1

42.8

58.2

7.7

9.0

6.5

3.8

4.4

3.3

21.1

-0.3

77.2

77.8

76.6

1.3

1.3

1.3

58.8

53.0

64.6

41.7

34.5

50.0

7.3

6.1

8.2

4.2

3.6

4.7

21.8

3.2

89.4

91.4

87.7

15.0

16.3

13.8

66.6

61.8

71.1

32.6

21.0

44.5

6.0

7.2

4.9

2.9

3.5

2.4

16.3

0.6

91.5

91.7

91.2

4.3

4.6

4.0

59.4

51.9

67.0

33.1

18.9

49.8

13.4

14.7

12.3

10.2

11.2

9.4

23.8

1.7

84.7

87.0

82.3

23.1

27.0

19.3

69.3

67.3

71.4

54.5

54.3

54.8

7.7

8.1

7.4

1.9

1.8

2.1

26.5

3.0

86.5

88.6

84.5

32.1

36.5

27.9

73.1

70.7

75.5

69.6

66.9

72.3

7.1

7.2

6.9

1.1

0.9

1.2

24.3

3.2

78.8

80.3

77.3

26.6

31.2

22.0

71.5

65.8

77.3

57.4

49.1

66.0

5.3

4.9

5.7

1.2

0.8

1.5

0.852

0.458

0.359

0.517

0.108

0.196

0.170

0.711

1.097

0.116

28.5

41.6

30.4

22 b 

22 b 

21 b 

11 b 

11 b 

11 b 

6.5

7.7

5.4

5.9

36.7

51.9

18

81.7

77.3

73

95

72

84

29.1

48.2

25.0

3.8

24

25

23

12

13

11

7.6

8.7

6.5

6.1

32.2

27.8

18

82.3

76.7

20.0

60.1

19.5

24.9

47.2

30.4

6.6 b 

6.9 b 

30 b 

29 b 

31 b 

21 b 

20 b 

21 b 

11.7

12.8

10.5

9.5

20.4

14.8

10

79.3

70.8

26

26

25

19

20

19

5.8

6.1

5.4

4.8

21.3

25.0

9

81.3

74.9

84

92

82

86

75

84

75

82

79

72

86

107

AT

14.9

37.9

35.9

4.9 i

24 i

24 i

23 i

18 i 

18 i

18 i

9.6

10.7

8.6

9.4

11.2

34.3

13

75.7

68.7

:

:

103

97

107

103

26 b 

27 b 

25 b 

12 b 

14 b 

11 b 

6.0

6.9

5.1

2.5

12.2

42.9

1

80.9

73.9

59.9 p

56.3 p

98

109

93

77

SI

24.3

44.7

32.7

17.2

40.1

30.1

3.4 b 

3.9 b 

26.7

36.9

25.5

3.6

28

29

27

12

13

11

:

:

:

:

42.0

35.7

20

82.5

75.6

32.9

40.1

25.4

3.3

29

30

27

9

10

9

:

:

:

:

47.3

47.4

16

82.9

78.5

26.3

44.6

30.4

5.8 b

31 b 

32 b 

29 b 

19 b

19 b 

19 b

10.9

12.7

8.9

16.7

19.7

25.6

20 p

81.1

77.1

22 b 

22 b 

22 b 

13 b 

13 b 

13 b 

8.8

9.6

8.1

10.5

19.3

35.7

24

78.1

70.2

56.4 p

54.9 p

52.4 p

51.7 p

63.1 p

64.2 p

65.0 p

63.2 p

54

62

52

64

83

90

83

102

86

85

88

81

88

81

89

90.0

4.0 b 

4.1 b 

4.0 b 

62.1 p

62.2 p

53.9 p

52.0 p

63.1 p

65.0 p

59.6 p

57.8 p

66.6 p

61.0 p

56.7 p

58.4 p

4.8 f

4 444

24.9

1.9

93.8

94.9

92.8

2.1

2.1

2.0

55.6

49.4

62.0

34.3

25.7

44.4

11.1

12.7

9.8

6.7

7.7

5.8

:

:

:

:

4.8 i

31 i

34 i

29 i

18 i

20 i

16 i

:

:

:

:

3.1 f

2 035

15.8

-0.4

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

.

:

78.8

71.8

:

:

:

:

:

:

.

:

75.9

71.6

:

:

:

:

:

:

6.1

.

2006

%

Real GDP growth rate

1.1.2005

1 000

Total population

2005

2005

2006

%

Old age dependency ratio

per 1 000 Crude rate of net migration including adjustments and corrections

%

Youth education attainment level

71 610

8.9

0.0

44.7

total

total

total

total

51.7 females

38.9 males

2.0

total

2006

%

Lifelong learning   

2.4 females

1.6 males

45.9

total

2006

%

Employment rate

23.9 females

68.1 males

30.1

total

2006

%

Employment rate of older workers

16.7 females

44.1 males

9.9

total

2006

%

Unemployment rate

10.3 females

9.7 males

2.5

total

2006

%

Long-term unemployment rate

3.3 females

2.3 males

:

:

:

:

10.0 i

28 i

total

total

total

total

total

total

29 i

females

26 i males

2005

2004

2004

2004

2005

2005

%

%

%

%

Public expenditure on LMP measures (categories 2-7) as a percentage of GDP

Expenditure on social protection as a percentage of GDP

Old age and survivors benefits as a percentage of total social benefits

Sickness and health care benefits as a percentage of total social benefits

Ratio

Inequality of income distribution

%

At-risk-of-poverty rate before social transfers

26 i

total

2005

%

At-risk-of-poverty rate after social transfers

27 i

females

26 i males

:

:

total

2007

%

People aged 18-59 living in jobless households

females

21.7

28.3

9.1 females

8/2007

: males

:

total

2007

.

:

:

females

10/2007

females

females

2003

2005

: males

%

%

%

%

Children aged 0-17 living in jobless households

Percentage of women in the single or lower House of the national or federal Parliament

Percentage of women in the European Parliament

Gender pay gap in unadjusted form   

Year

Life expectancy at birth

:

females

2005

Year

Healthy Life Years at birth

: males

82

total

2004

Index Serious accidents at work (1998 = 100)

: 

females

:  males

64

total

2004

point

Index
point

Fatal accidents at work (1998 = 100)

Economy

Population

Education 
and training

Labour 
market

Social 
protection

Income, 
social 
inclusion 
and living 
conditions

Gender 
equality

Health and 
safety

1

2

3

4

5

6

7a

7b

8a

8b

9

10

11a

11b

12

13a

13b

14a

14b

15a

15b

16

17a

17b

18a

18b

HU

MT

NL

PL

PT

RO

SK

FI

SE

UK

HR

MK

TR Sex

Time

Unit

Key indicator

Nr Domain

Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

4
Croatia FYROM

Turkey

EN 

199 

EN 

 
  
 
READING NOTES FOR THE KEY INDICATORS 

1

2

3
4
5

6

7a

7b

8a

8b

9

10

11a

11b

12

13a

13b

14a

14b

15a

15b

16

17a

17b

18a

18b

In EU-27 the growth rate of Gross Domestic Product volume was 3.0 % in 2006.

In EU-27 there were 490 million 898 thousand inhabitants on 1.1.2005. 

In EU-27 the number of persons aged 65 and over is estimated to have corresponded to 24.6 % of what is considered to be the working age population (15-64 years) in 2005.
In EU-27 the difference between population change and natural increase (the latter is the surplus or deficit of live births over deaths) is estimated to have been +3.6 per 1000 inhabitants (more immigrants than emigrants) in 2005. 
In EU-27, 77.8 % of the population aged 20 to 24 had completed at least upper secondary education (Baccalauréat, Abitur, apprenticeship or equivalent) in 2006. 

In EU-27, 9.6 % of the population aged 25-64 had participated in education or training over the four weeks prior to the survey in 2006.

In EU-27, 64.4 % of the population aged 15-64 were in employment in 2006.

In EU-27, 43.5 % of the population aged 55-64 were in employment in 2006.

In EU-27, 7.9 % of the active population (i.e. labour force i.e. those at work and those aged 15-74 years seeking work) were unemployed in 2006.

In EU-27 in 2006 3.6 % of the active population (i.e. labour force i.e. those at work and those aged 15-74 years seeking work) had been unemployed for at least one year. 

In EU-27 public ependiture on Labour Market Policy measures (categories 2-7) represented 0.525 % of Gross Domestic Product in 2005.  

In EU-25 social protection expenditure represented 27.3 % of Gross Domestic Product (GDP) in 2004.

In EU-25 old-age and survivors benefits made up 45.9 % of total benefits in 2004.

In EU-25 sickness and health care benefits made up 28.3 % of total benefits in 2004.

In EU-27 Member States in survey year 2005 (income reference year mainly 2004) as a population-weighted average the top (highest income) 20 % of a Member State's population received 4.9 times as much of the Member State's total income as 
the bottom (poorest) of the Member State's population.

In EU-27 in 2005 before social transfers, 26 % of the population would have been living below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income (after social transfers). Retirement and survivor's 
pensions are counted as income before transfers and not as social transfers.

In EU-27 in 2005 after social transfers, 16 % of the population were actually living below the risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income (after social transfers).

In EU-27, 9.3 % of the population aged 18-59 were living in households where no-one works in 2007. Students aged 18-24 who live in households composed solely of students of the same age class are counted neither in numerator nor in 
denominator.

In EU-27, 9.4 % of the children aged 0-17 were living in households where no-one works in 2007.

In EU-27 Member States in August 2007 as an average, 23.1 % of the seats (president and members) of the single or lower houses of the national or federal Parliaments were occupied by women. For example, in Sweden 47.3 % of the seats in the 
single house of the national parliament were occupied by women in August 2007.

In the European Parliament 31.2 % of the seats were occupied by women in October 2007.

In EU-27 women's average gross hourly earnings were 15 % less than the men's average gross hourly earnings in 2005. The population consists of all paid employees aged 16-64 that are 'at work 15+ hours per week'.

In EU-27 the mean number of years that a newborn girl/boy is expected to live if subjected throughout her/his life to the mortality conditions of the year 2003 (age specific probabilities of dying) is 80.8/74.6 years. (The EU-27 figures refer indeed to the 
year 2003, not to 2005).

In Belgium the mean number of years that a newborn girl/boy is expected to live in healthy condition if subjected throughout her/his life to the morbidity and mortality conditions of the year 2005 (age specific probabilities of becoming sick/dying) is 
61.9/61.7 years. 
In EU-25, the number of serious working accidents (resulting in more than three days' absence) per 100 000 persons in employment, went down by 21 % from 1998 to 2004.

In EU-25, the number of fatal working accidents per 100 000 persons in employment, went down by 24 % from 1998 to 2004.

NOTES:

1) Reference year: For each key social indicator the data of latest year sufficiently available is given. If data for this year is missing for some geopolitical entity, but data of a close year exists, this data is given and written in italics .

2) Flag codes: The letters ('flag codes') added to data (e.g. the 'f' in the HR value '4.8f' of the first key indicator in this table) indicate the following specific charasteritics: 'b' = "break in the series", 'e' = "estimated value", 'f' = "forecast", 'i'  = "more 
information in corresponding portrait or in the Eurostat web site http://epp.eurostat.ec.europa.eu", 'p' = "provisional value" and 's' = "Eurostat estimate".

3) Special values: The two special values used have the meaning: ':' = "not available" and '.' = "not applicable".

4) FYROM = The former Yugoslav Republic of Macedonia. 

EN 

200 

EN 

 
  
ANNEX 1.2 - KEY INDICTORS PER GEOPOLITICAL ENTITY - TIME SERIES (MAINLY LATEST 10 YEARS, WHEN AVAILABLE) 

EN 

201 

EN 

 
  
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 1
1.8
1996
2.7
1997
2.9
1998
3.0
1999
3.9
2000
2.0
2001
1.2
2002
1.3
2003
2.5
2004
1.8
2005
3.0
2006
2.9
2006Q3
3.5
2006Q4
3.4
2007Q1
2.5
2007Q2

1.8
2.7
3.0
3.1
3.9
2.0
1.2
1.3
2.4
1.8
3.0
2.8
3.5
3.4
2.6

1.5
2.6
2.8
3.0
3.8
1.9
0.9
0.8
2.0
1.5
2.8
2.5
3.3
3.0
2.5

Real GDP growth rate (Growth rate of GDP volume, annual and year-on-year quarterly growth rates)

1.2
3.5
1.7
3.4
3.7
0.8
1.5
1.0
3.0
1.1
3.2
2.5
3.7
3.1
2.3

-9.4
-5.6
4.0
2.3
5.4
4.1
4.5
5.0
6.6
6.2
6.1
6.7
5.7
6.2
6.6

4.0
-0.7
-0.8
1.3
3.6
2.5
1.9
3.6
4.5
6.4
6.4
6.3
6.1
6.4
6.0

2.8
3.2
2.2
2.6
3.5
0.7
0.5
0.4
2.1
3.1
3.5
3.0
3.5
2.7
0.6

1.0
1.8
2.0
2.0
3.2
1.2
0.0
-0.2
1.1
0.8
2.9
2.7
3.7
3.3
2.5

4.4
11.1
4.4
0.3
10.8
7.7
8.0
7.2
8.3
10.2
11.2
11.1
11.0
10.1
7.6

8.3
11.3
8.2
10.7
9.0
5.7
6.1
4.3
4.4
6.0
5.7
8.1
4.6
8.1
5.4

2.4
3.6
3.4
3.4
4.5
5.1
3.8
4.8
4.7
3.7
4.3
4.5
4.4
4.6
4.1

2.4
3.9
4.5
4.7
5.0
3.6
2.7
3.1
3.3
3.6
3.9
3.5
4.1
4.3
3.9

1.1
2.2
3.5
3.3
3.9
1.9
1.0
1.1
2.5
1.7
2.0
2.0
2.1
1.9
1.2

0.7
1.9
1.4
1.9
3.6
1.8
0.3
0.0
1.2
0.1
1.9
1.3
2.7
2.3
2.0

1.9
2.3
5.0
4.8
5.0
4.0
2.0
1.8
4.2
3.9
3.8
3.5
3.7
4.0
3.7

3.9
8.4
4.7
3.3
6.9
8.0
6.5
7.2
8.7
10.6
11.9
11.9
11.7
11.2
11.0

5.1
8.5
7.5
-1.5
4.1
6.6
6.9
10.3
7.3
7.6
7.5
6.4
6.9
8.3
8.0

1.5
5.9
6.5
8.4
8.4
2.5
3.8
1.3
3.6
4.0
6.2
6.2
5.9
7.3
:

1.3
4.6
4.9
4.2
5.2
4.1
4.4
4.2
4.8
4.1
3.9
3.9
3.3
2.7
1.2

:
:
:
:
:
-1.6
2.6
-0.3
0.1
3.1
3.2
2.8
3.4
3.5
3.7

3.4
4.3
3.9
4.7
3.9
1.9
0.1
0.3
2.2
1.5
3.0
2.8
2.7
2.5
2.6

2.6
1.8
3.6
3.3
3.4
0.8
0.9
1.2
2.3
2.0
3.3
3.0
3.4
3.5
3.5

6.2
7.1
5.0
4.5
4.3
1.2
1.4
3.9
5.3
3.6
6.1
6.3
7.2
6.9
6.8

3.6
4.2
4.8
3.9
3.9
2.0
0.8
-0.7
1.5
0.5
1.3
1.5
1.6
2.0
1.6

3.9c
-6.1c
-4.8c
-1.2
2.1
5.7
5.1
5.2
8.5
4.1
7.7
8.3
7.7
6.0
5.6

3.7
4.8
3.9
5.4
4.1
3.1
3.7
2.8
4.4
4.1
5.7
5.6
5.5
7.2
5.9

6.9
5.7
3.7
0.3
0.7
3.2
4.1
4.2
5.4
6.0
8.3
9.8
9.6
9.0
9.4

3.7
6.1
5.2
3.9
5.0
2.6
1.6
1.8
3.7
2.9
5.5
3.2
7.4
5.5
4.4

1.3
2.3
3.7
4.5
4.3
1.1
2.0
1.7
4.1
2.9
4.2
3.6
3.8
3.0
3.4

2.8
3.1
3.4
3.0
3.8
2.4
2.1
2.8
3.3
1.8
2.8
3.2
2.9
4.2
1.9

6.0
6.8
2.5
-0.9
2.9
4.4
5.6
5.3
3.8
4.3
4.8f
4.7
4.8
7.0
6.6

0.0
1.4
3.4
4.3
4.5
-4.5
0.9
2.8
4.1
3.8f
3.1f
:
:
:
:

7.0
7.5
3.1
-4.7
7.4
-7.5
7.9
5.8
8.9
7.4
6.1
4.8
5.2
6.9
3.9

Notes: Quarterly growth rates are in comparison to the same quarter of the previous year and are based on raw, i.e. not seasonally adjusted data, except for Greece and Portugal.

"f": forecast by the Commission Services.

Source: Eurostat - National Accounts.  

EN 

202 

EN 

 
  
 
EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 2a
:

:

1950

:

1960

1970

1980

1990

1995

1996

1997

1998

1999

2000

2001

2002

2003

402 607

435 474

457 053

470 388

476 491

477 333

478 102

480 383

481 076

482 188

482 958

484 541

486 520

376 423

252 205

406 870

273 235

426 081

286 751

438 712

294 670

446 428

300 681

447 426

301 474

448 376

302 241

449 174

304 520

450 053

305 172

451 169

306 225

452 151

307 514

452 755

309 035

454987 p

310 934

8 639

9 129

9 660

9 855

9 948

10 131

10 143

10 170

10 192

10 214

10 239

10 263

10 310

10 356

Total population, 1st January (The number of inhabitants of the area on 1st January (or on 31st December of the previous year) in 1000 inhabitants),
Observed
:

28 009

41 647

47 101

68 376

10 027

2 969

7 566

4 251

6 926

8 437

 295

:

:

:

:

:

:

:

:

:

7 829

8 464

8 846

8 767

8 427

8 385

8 341

8 283

8 230

8 191

7 929

7 892

7 846

9 638

9 906

10 316

10 362

10 333

10 321

10 309

10 299

10 290

10 278

10 267

10 206

10 203

4 565

4 907

5 122

5 135

5 216

5 251

5 275

5 295

5 314

5 330

5 349

5 368

5 384

72 543

78 269

78 180

79 113

81 539

81 817

82 012

82 057

82 037

82 163

82 260

82 440

82 537

1 209

1 356

1 472

1 571

1 448

1 425

1 406

1 393

1 379

1 372

1 367

1 361

1 356

2 836

2 943

3 393

3 507

3 598

3 620

3 655

3 694

3 732

3 778

3 833

3 900

3 964

4 028
4 109

8 300

8 781

9 584

10 121

10 595

10 674

10 745

10 808

10 861

10 904

10 931

10 969

11 006

11 041
11 083

30 327

33 588

37 242

38 826

39 343

39 431

39 525

39 639

39 803

40 050

40 477

40 964

41 664

42 345
43 038

45 465

50 528

53 731

56 577

57 753

57 936

58 116

58 299

58 497

58 825

59 200

59 586

59 970

60 340
60 702

50 026

53 685

56 388

56 694

56 844

56 844

56 876

56 904

56 909

56 924

56 961

56 994

57 321

57 888
58 462

 572

 612

510e

 573

 645

 656

 666

 675

 683

 690

 698

 706

 715

 730
 749

2 104

2 352

2 509

2 668

2 501

2 470

2 445

2 421

2 399

2 382

2 364

2 346

2 331

2 319
2 306

2 756

3 119

3 404

3 694

3 643

3 615

3 588

3 562

3 536

3 512

3 487

3 476

3 463

3 446
3 425

 313

 339

 363

 379

 406

 412

 417

 422

 427

 434

 439

 444

 448

 452
 455

9 961

10 322

10 709

10 375

10 337

10 321

10 301

10 280

10 253

10 222

10 200

10 175

10 142

10 117
10 098

 327

 303

 315

 352

 369

 371

 374

 377

 379

 380

 391

 395

 397

 400
 403

11 417

12 958

14 091

14 893

15 424

15 494

15 567

15 654

15 760

15 864

15 987

16 105

16 193

16 258
16 306

7 030

7 455

7 546

7 645

7 943

7 953

7 965

7 971

7 982

8 002

8 021

8 065

8 102

8 140
8 207

29 480

32 671

35 413

38 038

38 581

38 609

38 639

38 660

38 667

38 654

38 254

38 242

38 219

38 191
38 174

8 826

8 698

9 714

9 996

10 018

10 043

10 073

10 110

10 149

10 195

10 257

10 329

10 407

10 475
10 529

18 319

20 140

22 133

23 211

22 194

22 133

22 054

21 989

21 946

21 908

21 876

21 833

21 773

21 711
21 659

:

1 581

1 718

1 893

1 996

1 989

1 990

1 987

1 985

1 978

1 988

1 990

1 994

1 995

1 996
1 998

:

3 970

4 537

4 963

5 288

5 356

5 368

5 379

5 388

5 393

5 399

5 379

5 379

5 379

5 380
5 385

3 988

4 413

4 614

4 771

4 974

5 099

5 117

5 132

5 147

5 160

5 171

5 181

5 195

5 206

5 220
5 237

6 986

7 471

8 004

8 303

8 527

8 816

8 837

8 844

8 848

8 854

8 861

8 883

8 909

8 941

8 976
9 011

50 616

52 200

55 546

56 285

57 157

57 943

58 095

58 239

58 395

58 580

58 785

59 000

59 217

59 438

59 700
60 060

:

4 127

4 403

4 598

4 778

4 669

4 494

4 572

4 501

4 554

4 442

4 437

4 444

4 442

4 442
4 444

:

1 384

1 617

1 878

1 873

1 957

1 972

1 991

2 002

2 013

2 022

2 031

2 039

2 024

2 030
2 035

:

27 120

34 881

44 021

55 495

61 204

62 338

63 485

64 642

65 787

66 889

67 896

68 838

69 770

70 692
71 610

2004
2005
Note: De jure  population, except for DE, IE, HU, SI, FI, BG and TR de facto  population.

457 162 p
461 479

488 632
490 898

312 901
314 888

10 211
10 221

10 396
10 446

82 532
82 501

7 801
7 761

5 398
5 411

1 351
1 348

Source: Eurostat - Demographic Statistics, except TR: 1960-2000: Council of Europe.

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 2b

2005

2010

2015

2020

2025

2030

2035

2040

2045

2050

487 881

492 838

495 353

496 408

496 268

494 784

491 703

486 992

480 398

472 050

458 490

310 108

464 054

315 076

467 306

317 922

469 270

319 426

470 057

319 662

469 365

318 861

467 007

317 112

463 044

314 278

457 270

310 018

449 831

304 395

10 425

10 554

10 674

10 790

10 898

10 984

11 031

11 029

10 982

10 906

Total population, 1st January (The number of inhabitants of the area on 1st January (or on 31st December of the previous year) in 1000 inhabitants), 
Eurostat 2004-based population projections, trend scenario, baseline variant
2 305

42 920

10 524

38 137

60 183

10 096

10 197

11 083

58 189

16 331

82 600

21 654

1 346

4 077

5 411

3 429

7 737

8 140

 739

 404

 456

2 000

7 439

7 130

6 796

6 465

6 175

5 908

5 644

5 373

5 094

10 122

10 012

9 902

9 812

9 693

9 523

9 320

9 109

8 894

5 465

5 498

5 526

5 557

5 577

5 573

5 539

5 486

5 430

82 824

82 864

82 676

82 108

81 146

79 885

78 447

76 697

74 642

1 314

1 279

1 248

1 224

1 202

1 182

1 163

1 145

1 126

4 323

4 555

4 756

4 922

5 066

5 198

5 317

5 413

5 478

11 269

11 390

11 427

11 394

11 316

11 208

11 062

10 872

10 632

44 603

45 264

45 559

45 556

45 379

45 095

44 646

43 918

42 834

61 486

62 616

63 571

64 392

65 118

65 705

65 995

65 949

65 704

58 631

58 630

58 300

57 751

57 071

56 276

55 330

54 158

52 709

 784

 828

 866

 897

 921

 939

 952

 964

 975

2 240

2 174

2 115

2 068

2 022

1 979

1 942

1 909

1 873

3 345

3 258

3 182

3 134

3 092

3 045

2 995

2 941

2 881

 477

 499

 521

 544

 567

 589

 608

 626

 643

9 982

9 834

9 693

9 588

9 484

9 362

9 224

9 072

8 915

 423

 439

 454

 468

 479

 488

 495

 501

 508

16 672

16 957

17 209

17 429

17 589

17 662

17 636

17 537

17 406

8 256

8 358

8 441

8 501

8 520

8 491

8 430

8 340

8 216

37 830

37 428

37 065

36 836

36 542

36 053

35 373

34 547

33 665

10 686

10 762

10 771

10 730

10 660

10 560

10 425

10 244

10 009

21 345

20 917

20 342

19 746

19 244

18 787

18 304

17 755

17 125

2 015

2 019

2 017

2 014

2 006

1 989

1 965

1 935

1 901

5 376

5 347

5 309

5 271

5 237

5 186

5 107

5 001

4 876

4 738

5 233

5 294

5 353

5 405

5 439

5 443

5 412

5 353

5 283

5 217

9 010

9 187

9 373

9 575

9 769

9 911

9 997

10 060

10 128

10 202

59 880

60 924

61 934

62 930

63 792

64 388

64 659

64 736

64 637

64 330

4 551i

4 532i

4 454i

4 367i

4 271i

4 164i

4 047i

3 926i

3 806i

3 686i

:

:

:

:

:

:

:

:

:

:

73 193i

78 081i

82 640i

86 774i

90 565i

93 876i

96 573i

98 651i

100 189i

101 208i

Note:  Data for France refer to metropolitan France.

Sources: 1) Eurostat - 2004-based population projections, trend scenario, baseline variant, except 
2) HR and TR: United Nations, Population Division - Population Estimates and Projections, Medium variant projection  - 2005 data is estimate and 2010-2050 data from the 'Medium variant projection' (http://unstats.un.org/unsd/cdb/cdb_series_xrxx.asp?series_code=13660). 

EN 

203 

EN 

 
  
 
EU-27

EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 3a
1950
:
1960
:
1970
:
1980
:
1990
20.6
1995
21.9
1996
22.3
1997
22.5
1998
22.8
1999
23.0
2000
23.2
2001
23.6
2002
23.8
2003
24.1
2004
24.3

:
15.5
18.4
20.9
20.8
22.1
22.5
22.7
22.9
23.1
23.4
23.7
24.0
24.2
24.5

:
:
:
:
21.0
22.6
23.0
23.3
23.6
23.9
24.3
24.6
25.0
25.3
25.7

Old age dependency ratio (Population aged 65 and over as a percentage of the working age population (15-64) on 1st January (or on 31st December of the previous year)),
Observed

:
18.5
21.2
21.9
22.1
23.8
24.3
24.7
25.0
25.3
25.5
25.7
25.8
26.0
26.1

:
11.2
14.0
17.8
19.5
22.2
22.6
22.7
23.1
23.4
23.8
24.7
24.9
24.9
24.9

:
14.6
17.9
21.6
19.0
19.3
19.4
19.6
19.7
19.8
19.8
19.8
19.7
19.7
19.7

13.8
16.4
18.9
22.2
23.2
22.7
22.5
22.4
22.3
22.2
22.2
22.2
22.3
22.3
22.5

:
17.0
21.4
23.9
21.6
22.5
22.8
23.0
23.2
23.3
23.9
24.5
25.2
25.9
26.8

:
:
17.7
19.0
17.5
20.2
20.9
21.5
22.0
22.2
22.4
22.7
23.0
23.5
23.9

17.7
19.2
19.3
18.2
18.6
17.8
17.6
17.4
17.2
17.0
16.8
16.6
16.5
16.4
16.4

10.5
14.2
17.2
20.6
20.4
22.2
22.6
23.0
23.4
23.8
24.2
24.7
25.3
25.8
26.4

11.1
12.7
15.2
17.1
20.2
22.3
22.7
23.2
23.7
24.1
24.5
24.7
24.8

24.7
24.6

17.2
18.7
20.6
22.1
21.1
23.0
23.4
23.8
24.1
24.4
24.6
24.7
24.9
25.0
25.1

:
14.0
16.7
20.3
21.5
24.0
24.7
25.2
25.8
26.3
26.8
27.4
27.9
28.5
28.9

:
:
:
15.7
17.2
17.2
17.2
17.1
17.1
17.0
17.0
17.0
17.4
17.6
17.5

:
:
18.0
19.6
17.7
20.5
20.9
21.4
21.8
22.0
22.1
22.6
22.9
23.3
23.6

:
:
15.9
17.4
16.2
18.5
19.0
19.5
20.0
20.5
20.8
21.3
21.7
22.0
22.3

:
15.9
19.1
20.3
19.3
20.6
20.9
21.2
21.3
21.4
21.4
20.7
20.8
20.9
21.0

:
13.6
17.0
20.9
20.0
20.9
21.2
21.3
21.6
21.8
22.0
22.2
22.3
22.4
22.6

:
:
:
12.5
15.7
16.3
16.8
17.4
17.6
17.8
17.9
18.1
18.5
18.7
19.0

12.2
14.6
16.2
17.4
18.6
19.3
19.5
19.6
19.8
19.9
20.0
20.1
20.2
20.3
20.5

15.5
18.4
22.7
24.3
22.1
22.5
22.7
22.8
22.9
22.9
22.9
22.8
22.9
22.7
22.8

:
9.5
12.6
15.5
15.4
16.6
16.9
17.2
17.4
17.5
17.6
18.0
18.2
18.4
18.6

10.5
12.4
14.9
17.8
20.0
21.9
22.2
22.6
23.0
23.4
23.7
24.2
24.5
24.7
24.9

:
:
13.0
16.3
15.6
18.0
18.4
18.6
19.1
19.4
19.7
20.0
20.4
20.6
20.9

:
:
14.8
16.4
15.5
17.4
18.0
18.5
19.0
19.4
19.8
20.2
20.6
21.0
21.4

:
11.1
14.4
16.7
16.0
16.3
16.4
16.5
16.6
16.6
16.6
16.5
16.3
16.3
16.3

10.5
11.6
13.6
17.6
19.8
21.1
21.5
21.7
21.9
22.0
22.2
22.4
22.7
22.9
23.3

15.2
17.8
20.7
25.3
27.7
27.4
27.4
27.4
27.3
27.1
26.9
26.8
26.6
26.5
26.4

:
:
:
:
17.0
18.2
18.2
18.2
18.2
18.2
24.4
23.4
23.7
24.2
24.6

:
:
:
:
:
12.8
13.2
13.4
13.8
14.2
14.6
14.9
15.3
15.5
15.6

:
6.4
8.2
8.4
7.1
7.8
7.9
8.0
8.1
8.2
8.3
8.3
8.4
8.5
8.7

:
18.0
20.5
23.3
24.1
24.5
24.5
24.5
24.5
24.4
24.3
24.3
24.3
24.3
24.3
.

Notes: 1) FR: Data for France refer to metropolitan France.  2) CY: Government controlled area.

Source: Eurostat - Demographic Statistics

EU-27

EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 3b
24.6
2005
26.0
2010
31.8
2020
39.8
2030
48.1
2040
52.8
2050
Notes: 1) FR: Data for France refer to metropolitan France.  2) CY: Government controlled area.

Old age dependency ratio (Population aged 65 and over as a percentage of the working age population (15-64) on 1st January (or on 31st December of the previous year)),
Eurostat 2004-based population projections, trend scenario, baseline variant
22.3
23.4
26.0
33.4
39.3
44.9

21.8
23.6
30.8
40.4
47.7
55.6

22.7
24.3
31.2
35.1
40.3
48.3

26.5
28.0
34.4
38.5
41.5
40.9

23.8
25.4
37.0
45.0
46.1
46.7

16.3
16.9
23.5
31.7
38.1
50.6

21.1
21.2
25.1
29.6
39.6
51.1

25.2
26.5
31.5
39.0
48.9
58.1

18.7
18.8
27.1
35.7
39.7
51.0

23.5
26.3
30.3
40.8
50.4
53.2

20.8
22.2
29.0
36.7
41.6
38.6

19.3
20.4
30.0
36.0
35.9
40.6

21.3
21.6
24.7
31.5
36.7
36.1

24.1
25.2
28.0
33.4
37.4
44.1

17.3
19.1
25.5
32.9
36.1
43.2

29.3
31.3
36.6
45.2
59.8
66.0

24.9
25.9
33.2
40.7
46.9
47.9

24.4
25.4
30.0
38.9
54.3
67.5

26.8
28.0
32.5
39.1
49.8
58.8

16.4
17.5
22.5
28.3
35.9
45.3

24.3
24.7
28.7
33.4
36.6
43.1

27.8
31.0
35.1
46.0
54.6
55.8

22.7
24.8
31.2
37.1
42.1
40.0

19.8
21.9
31.8
37.1
43.8
54.8

24.8
25.6
33.0
40.4
48.8
60.9

26.3
26.4
32.2
41.3
47.2
48.1

26.1
27.9
33.3
42.1
51.8
55.6

24.8
26.3
32.1
40.3
48.5
52.8

24.3
25.1
30.3
37.4
43.8
45.3

24.9
25.3i
30.1i
35.3i
38.1i
42.4i

15.8
:
:
:
:
:

8.9
9.2i
11.1i
15.6i
21.6i
28.3i

Sources: 1) Eurostat - 2004-based population projections, trend scenario, baseline variant, except 
2) HR and TR: United Nations, Population Division - Population Estimates and Projections, Medium variant projection (http://unstats.un.org/unsd/cdb/cdb_series_xrxx.asp?series_code=13660). 

EN 

204 

EN 

 
  
 
EU-
27

EU-
25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

1.3
1.5
1.4
4.6
1.2
2.1
1.6
3.0
4.0

Key indicator 4
1.2
1994
1.4
1995
1.2
1996
4.3
1997
1.1
1998
2.0
1999
1.0
2000
2.8
2001
3.8
2002
2003
2004
2005
2006

4.4
4.1
3.8
:

4.1
3.8
3.6
:

1.8
2.0
1.9
6.6
1.4
2.6
3.1
3.9
5.3

5.7
5.1
4.7
:

1.7
0.2
1.5
1.0
1.1
1.6
1.3
3.5
3.9

3.4
3.4
4.9
:

0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.9
0.0

0.0
0.0
0.0
0.0

Crude rate of net migration including adjustments and corrections (The difference between population change and natural increase (the surplus or deficit of live births over deaths) during the 
year per 1000 population)
-14.2
-10.9
-9.5
-4.9
-4.8
-0.8
0.2
0.1
0.1

1.4
1.5
1.9
2.1
3.8
5.7
9.4
10.6 p
15.8

-0.8
1.6
3.6
5.6
5.0
5.4
6.9
11.8
8.3

11.0
10.3
9.1
8.2
6.2
6.1
5.7
6.6
9.7

9.4
10.5
8.5
8.6
8.9
10.4
7.9
7.5
5.8

2.4
-0.5
1.6
1.6
1.1
23.7
3.4
5.9
5.1

-0.1
-0.3
-0.3
-0.2
-0.1
0.8
0.8
1.0
1.1

-9.0
-5.5
-4.1
-3.9
-2.4
-1.7
-2.3
-2.2
-0.8

-6.6
-6.5
-6.5
-6.3
-6.2
-5.9
-5.8
-0.7
-0.5

-0.5
-0.5
-0.3
-0.3
-0.3
-0.4
-0.5
-0.4
-0.5

-0.7
-0.9
-0.9
-0.6
-0.2
-0.1
-0.2
0.0
-0.1

0.0
0.4
-1.7
-0.7
-2.7
5.4
1.4
2.5
1.1

1.0
1.0
1.0
1.2
0.9
0.9
0.6
-0.8
1.2

2.7
1.7
2.7
2.2
1.9
1.7
3.1
2.2
6.1

1.7
1.7
1.7
1.7
1.7
1.6
1.6
1.0
0.3

0.4
0.3
0.5
0.2
1.1
2.5
2.2
2.2
4.3

0.7
0.8
0.8
0.9
0.9
0.7
0.5
1.2
1.0

5.8
1.3
0.7
0.7
1.2
1.5
2.7
3.2
3.5

7.4
7.3
6.6
5.7
5.1
4.1
2.7
3.1
3.5

3.9
4.9
3.4
1.1
0.6
2.5
2.0
3.3
2.7

2.0
5.5
3.3
2.3
2.1
1.8
1.9
2.2
1.8

2.0
2.5
2.5
3.0
3.5
3.9
4.9
5.7
6.8

0.9
0.5
0.4
0.3
0.2
0.3
0.3
0.2
0.2

1.3
1.0
1.4
1.9
2.8
2.8
3.6
3.5
1.7

1.4
2.0
1.8
1.5
3.6
2.8
2.8
3.1
2.1

2.5
1.8
3.5
3.4

1.3
0.9
1.2
1.9

1.7
1.0
1.0
0.3

0.1
0.1
0.1
0.1

7.8
11.7
15.9
:

3.2
3.7
3.6
3.6

14.9
14.3
14.8
13.9

2.7
1.7
3.3
1.5

10.6
9.6
5.5
6.4

17.1
21.3
19.0
11.0

-0.4
-0.5
-0.2
-1.1

-1.8
-2.8
-2.6
-1.4

4.6
3.4
6.0
:

1.5
1.8
1.7
1.9

4.2
4.8
2.4
2.5

0.4
-0.6
-1.4
-1.6

4.7
7.6
6.8
3.5

-0.4
-0.2
-0.3
-0.9

6.1
4.5
3.6
2.5

-0.3
-0.5
-0.3
-0.3

1.8
0.9
3.2
3.1

0.3
0.5
0.6
0.7

1.1
1.3
1.7
2.0

3.2
2.8
3.0
5.6

3.0
3.8
3.2
2.6

:

4.4
:
:
:
:
:
0.5
3.4
1.9
2.8
2.6
1.9

1.4
-0.7
2.2
-1.0
-1.0
-0.8
-1.2
-1.3
-12.2
-1.4
-0.1
-0.4
-0.3

: 
1.7
1.7
1.8
1.6
1.1
-0.2
-0.9
-0.9
-0.8
0.0
0.0
0.0

Notes: 1) Conceptually net migration is the surplus or deficit of immigration into over emigration from a given area during the year and the crude rate of net migration is net migration per 1000 population. 
Since many countries either do not have accurate figures on immigration and emigration or have no figures at all, net migration  is calculated indirectly as the difference between total population change and natural increase (the surplus or deficit of live births over deaths) between two dates. It then 
includes adjustments and corrections, i.e. all changes in the population size that cannot be classified as births, deaths, immigration or emigration.  It is then used for the calculation of the crude rate of net net migration, which also consequently includes adjustments and corrections.
2) CY: Government-controlled area only. 1998 break in series - before 1998 France metropolitan, from 1998 - whole France.

Source: Eurostat - Population Statistics

EN 

205 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 5

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Youth education attainment level (Percentage of the population aged 20 to 24 having completed at least upper secondary education)

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

:
:
:
:
:
76.6
76.6
76.7
76.9
77.1
77.4
77.8

:
:
:
:
:
79.3
79.2
79.3
79.4
79.9
80.1
80.7

:
:
:
:
:
73.8
74.0
74.0
74.5
74.3
74.7
74.8

:
:
:
:
:
76.6
76.5
76.7
77.1
77.2
77.5
77.7

:
:
:
:
:
79.5
79.3
79.4
79.7
80.2
80.3
80.9

:
:
:
:
:
73.7
73.7
74.0
74.5
74.3
74.7
74.7

:
:
:
:
71.6
73.1
72.7
72.9
73.1
73.5
73.6
73.8

:
:
:
:
74.6
76.5
76.0
76.2
76.3
77.2
77.2
77.6

:
:
:
:
68.5
69.6
69.3
69.6
69.8
69.9
70.1
70.1

77.6
80.2
80.1
79.6
76.2 i 
81.7 b 
81.7
81.6
81.2
81.8
81.8
82.4

80.7
83.8
82.4
82.9
80.1 i 
85.6 b 
85.2
84.8
84.6
84.8
85.3
85.6

74.6
76.6
77.9
76.4
72.3 i 
78.0 b 
78.3
78.5
77.9
78.9
78.4
79.1

:
:
:
:
:
75.2
78.1 b 
77.4
76.3
76.1
76.5
80.5 p 

:
:
:
:
:
77.0
79.0 b 
79.5
77.3
77.5
77.1
81.1 p 

:
:
:
:
:
73.4
77.2 b 
75.2
75.4
74.9
75.9
80.0 p 

:
:
:
92.2
91.8
91.2
90.6
92.2
92.1
91.4
91.2
91.8

:
:
:
91.6
91.6
91.7
91.3
92.0
91.5
91.8
91.1
92.4

:
:
:
92.8
92.0
90.7
89.8
92.4
92.8
91.0
91.3
91.1

89.3
74.6 b 
73.6
76.3
73.2
72.0
78.4 i 
78.6
76.2 b 
76.2
77.1
77.4

87.8
77.4 b 
77.3
79.3
77.9
76.5
81.7 i 
82.6
78.5 b 
78.1
80.5
81.5

90.9
71.8 b 
69.9
73.0
67.8
67.5
74.8 i 
74.3
73.8 b 
74.3
73.8
73.4

79.4
74.9 b 
74.8
:
74.6
74.7
73.6
73.3
72.5
72.8
71.5 b 
71.6

79.6
74.5 b 
75.1
:
74.5
74.8
73.6
73.8
73.4
74.2
72.5 b 
73.5

79.1
75.2 b 
74.5
:
74.7
74.6
73.6
72.6
71.6
71.5
70.4 b 
69.8

:
:
:
83.1
83.0
79.0 b 
79.8
81.4
81.5
80.3
82.6
82.0

:
:
:
85.5
88.6
83.7 b 
85.2
85.8
85.1
87.5
87.6
89.8

:
:
:
80.7
77.1
74.2 b 
74.7
77.1
77.9
73.2
77.6
74.1

73.8
77.3
77.4
:
82.0
82.6
83.9
84.0
85.1 p 
85.3 p 
85.8 p 
85.4

78.9
82.8
82.1
:
85.0
85.6
87.4
87.3
88.5 p 
88.4 p 
88.9 p 
89.1

68.8
72.0
72.9
:
79.1
79.7
80.4
80.7
81.6 p 
82.3 p 
82.6 p 
81.8

73.8
75.3
76.8
76.4
78.6
79.2
80.2
81.1
81.7
83.0
84.1
81.0 p 

78.2
79.2
80.7
82.1
82.8
84.6
84.8
86.0
86.8
86.8
88.5
86.6 p 

68.9
70.7
72.2
70.6
74.3
73.6
75.3
76.1
76.6
79.2
79.7
75.5 p 

59.0
61.5
63.7
64.6 i 
65.2 i 
66.0
65.0
63.7
62.2
61.2
61.8
61.6

64.4
67.4
69.3
70.4 i 
71.7 i 
71.9
71.4
70.3
69.2
68.4
68.5
69.0

53.7
55.6
58.1
58.8 i 
58.7 i 
60.1
58.8
57.4
55.5
54.4
55.4
54.6

78.6
75.2
76.3
78.9
80.0
81.6
81.8
81.7
81.8 b 
81.4
82.6
82.1

80.7
76.7
77.3
80.8
81.4
83.5
83.2
82.8
83.3 b 
83.0
85.0
84.3

76.3
73.5
75.1
76.8
78.6
79.6
80.3
80.5
80.4 b 
79.7
80.1
80.0

58.9
60.9
62.4
65.3
66.3
69.4 b 
67.9
69.6
71.0
73.4
73.6
75.5 p 

62.7
64.8
66.7
70.0
70.4
74.2 b 
73.0
74.3
75.1
78.6
78.1
79.4 p 

55.0
56.8
57.9
60.6
62.1
64.5 b 
62.7
64.8
66.8
68.2
69.2
71.7 p 

:
:
:
:
80.8
79.0
80.5
83.5
79.5
77.6
80.4
83.7 p 

:
:
:
:
85.6
82.8
84.9
89.5
87.0
83.8
89.1
90.7 p 

:
:
:
:
75.1
74.4
75.4
76.7
71.3
70.7
71.1
76.1 p 

Total
:
:
:
83.2
81.3
78.9 i 
80.5
81.3 b 
84.2
85.0
87.8
88.2
Females
:
:
:
86.2
84.5
82.9 i 
83.8
83.2 b 
87.9
88.5
91.8
91.2
Males
:
:
:
80.3
78.2
75.0 i 
77.1
79.4 b 
80.6
81.5
83.9
85.3

51.9
49.5
53.1
:
71.2 b 
77.5
68.0
69.8
72.7 b 
72.5
71.1
69.3

52.3
47.8
53.0
:
72.8 b 
75.8
69.0
65.5
75.6 b 
73.4
75.8
74.5

51.5
51.2
53.2
:
69.6 b 
79.2
67.0
74.0
69.7 b 
71.6
66.6
64.0

:
:
:
78.5
74.6 b 
76.5
71.7 i 
77.1 b 
75.4
79.5
79.9
81.0

:
:
:
86.4
82.3 b 
82.4
77.5 i 
84.3 b 
80.9
85.1
85.2
86.2

:
:
:
70.8
67.2 b 
70.9
66.2 i 
70.0 b 
70.1
74.2
74.7
75.9

:
:
77.7
81.5
85.2
83.5
84.7
85.9
84.7 b 
83.5
83.4
82.9

:
:
77.9
81.4
85.3
84.0
85.0
86.3
86.1 b 
84.9
84.9
84.7

:
:
77.5
81.5
85.2
83.0
84.5
85.5
83.4 b 
82.0
81.9
81.2

:
:
:
:
:
40.9
40.1
39.0
45.1 b 
51.0
53.7
50.4 p 

:
:
:
:
:
40.2
38.7
42.2
48.8 b 
52.4
57.0
52.8 p 

:
:
:
:
:
41.6
41.4
36.1
41.3 b 
49.8
50.5
48.1 p 

:
67.6
70.3
72.9
72.3
71.9
72.7
73.1
75
75
75.6
74.7

:
71.0
74.3
76.7
76.3
75.7
76.8
77.4
78.0
78.9
79.9
79.6

:
64.2
66.5
69.1
68.4
68.2
68.7
68.8
72.0
71.2
71.4
69.9

79.2
80.5
81.8
84.4
84.7
85.1 b 
85.1
85.3
84.2
85.8 i 
85.9
85.8

74.5
77.8
80.1
82.4
82.9
84.9 b 
85.3
84.6
83.4
86.5 i 
87.3
86.7

84.1
83.3
83.6
86.5
86.6
85.3 b 
84.9
86.1
85.1
85.1 i 
84.6
84.9

:
:
85.1
84.5
81.6 i 
88.8 b 
89.7
89.2
90.3
90.9
91.1
91.7

:
:
88.1
87.1
84.3 i 
91.7 b 
91.8
91.9
92.8
93.1
93.3
93.8

:
:
81.9
81.7
78.8 i 
85.8 b 
87.7
86.5
87.9
88.7
88.9
89.6

45.1
46.2
47.1
39.3 b 
40.1
43.2
44.4
44.4
47.9
49.6
49.0
49.6

52.0
52.7
53.9
44.8 b 
46.7
51.8
53.0
52.9
55.5
58.7
57.5
58.6

38.3
39.9
40.4
33.8 b 
33.6
34.6
35.9
36.1
40.4
40.8
40.8
40.8

:
:
82.0
81.0
77.8
76.1
77.3
76.3
75.0
75.3
76.0
77.2 p 

:
:
82.7
81.2
79.1
77.0
77.5
77.7
75.7
76.1
76.8
77.8 p 

:
:
81.3
80.8
76.3
75.2
77.1
74.8
74.3
74.6
75.2
76.6 p 

:
84.4
85.7
86.8
85.8
88.0 b 
88.2
90.7
90.8
90.5
90.5
89.4

:
86.6
88.7
88.5
87.1
90.8 b 
90.3
93.3
94.0
94.1
93.2
91.4

:
82.1
82.8
85.1
84.5
85.4 b 
86.3
88.3
87.7
87.1
88.0
87.7

:
:
:
93.4
93.3
94.8
94.4
94.5
94.1
91.7
91.8
91.5

:
:
:
93.0
93.4
94.8
95.1
95.4
94.5
92.0
92.6
91.7

:
:
:
93.7
93.3
94.8
93.8
93.5
93.7
91.3
91.0
91.2

82.4
81.9
85.9
85.2
86.8
87.7 b 
86.1
85.8
85.3
84.5
83.4
84.7 p 

84.2
83.1
87.2
85.2
88.8
90.0 b 
89.4
89.0
87.6
87.0
85.7
87.0 p 

80.6
80.8
84.6
85.3
84.8
85.4 b 
82.8
82.6
83.0
81.9
81.0
82.3 p 

88.1
86.3
86.6
87.5
86.3
85.2
85.5 b 
86.7
85.8
86.0
87.5
86.5

86.1
87.1
88.2
88.1
87.5
87.6
86.8 b 
88.3
87.2
87.2
88.7
88.6

90.0
85.5
85.0
86.9
85.1
82.8
84.2 b 
85.2
84.3
84.8
86.4
84.5

64.0
62.2
65.8
:
75.3 b 
76.6
76.9
77.1
78.7
77.0
78.2
78.8

62.0
60.0
64.5
:
75.9 b 
77.3
78.4
77.6
78.9
78.0
78.9
80.3

65.9
64.3
67.1
:
74.7 b 
75.9
75.4
76.6
78.4
76.0
77.4
77.3

:
:
:
:
:
:
:
90.6
91.0
93.5
93.8
:

:
:
:
:
:
:
:
91.8
92.6
94.6
94.9
:

:
:
:
:
:
:
:
89.4
89.5
92.6
92.8
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
38.6
39.6
42.8
44.2
42.0
44.0
44.7

:
:
:
:
:
46.4
48.6
52.2
52.6
49.3
51.3
51.7

:
:
:
:
:
32.0
32.0
34.8
37.2
35.8
37.8
38.9

Notes: 1) Reference period: From 27 October 2006, this indicator is based on annual averages of quarterly data instead of one unique reference quarter in spring. This improves both the accuracy and reliability of the results thanks to a better coverage of all weeks of the year and an increased sample size. Annual averages are used from 2005 onwards for all 
countries. Spring data are used between 2000 and 2002 for DE, FR, LU, CY, MT and SE, and for 2003-2004 for DE and CY. The average of the two semi-annual surveys is used for LV and LT for 2000-2001 and from 2002 for HR. Before 2000, all results are based on the spring survey.
2) Estimations are performed by Eurostat in case of outliers or missing information in the quarterly series.
3) Educational attainment level: From 1998 data onwards ISCED 3c levels of duration shorter than 2 years do not fall any longer under the level ‘upper secondary’ but under ‘lower secondary’. This change implies revised results in DK (from 2001), ES, CY and IS compared to results published before December 2005. The definition could not be implemented on 
1998-2005 data in EL, IE and AT where all ISCED 3c levels are still included.
4) Changes in survey characteristics: Due to changes in the survey characteristics, data lack comparability with former years in IT (from 1993), DK and DE (from 1996), PT (from 1998), BE and UK (from 1999), PL (1999 – quarter 1 for that year), FI (from 2000), SE and BG (from 2001), LV and LT (from 2002), DK and HU (from 2003), AT (from 2004), DE (from 20
5) Students living abroad for one year or more and conscripts on compulsory military service are not covered by the EU Labour Force Survey, which may imply lower rates than those available at national level. This is especially relevant for the indicator 'youth education attainment level' in CY.
6) The indicator covers non-nationals who have stayed or intend to stay in the country for one year or more. 
7) FR data do not cover the overseas departments (DOM). TR (youth education attainment level): national data.
8) In case of missing country data the EU aggregates are provided using the closest available year result

Source: Eurostat - European Union Labour Force Survey

EN 

206 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 6

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Lifelong learning (adult participation in education and training) (Percentage of the population aged 25-64 participating in education and training over the four weeks prior to the survey)

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

:
:
:
:
:
7.1 e 
7.1 e 
7.2
8.5 b 
9.3
9.7
9.6

:
:
:
:
:
7.5 e 
7.6 e 
7.7
9.1 b 
10.0
10.4
10.4

:
:
:
:
:
6.7 e 
6.6 e 
6.6
7.9 b 
8.6
8.9
8.8

:
:
:
:
:
7.5 e 
7.5 e 
7.6
9.0 b 
9.9
10.2
10.1

:
:
:
:
:
8.0 e 
8.0 e 
8.2
9.7 b 
10.6
11.0
11.0

:
:
:
:
:
7.1 e 
6.9 e 
6.9
8.3 b 
9.1
9.4
9.2

:
:
:
:
5.5 e
5.2 e
5.2 e
5.3 e
6.5 b
7.4
8.2
8.2

:
:
:
:
5.3 e
5.2 e
5.2 e
5.4
6.6 b
7.5
8.4
8.6

:
:
:
:
5.7 e
5.3 e
5.2 e
5.2
6.4 b
7.2
8.0
7.9

2.8
2.9
3.0
4.4
6.9 b 
6.2 i 
6.4
6.0
7.0
8.6 b 
8.3
7.5 p 

2.3
2.5
2.6
3.8
6.1 b 
5.7 i 
5.9
6.0
6.9
8.5 b 
8.5
7.6 p 

3.3
3.4
3.4
5.0
7.8 b 
6.7 i 
6.9
5.9
7.0
8.7 b 
8.2
7.4 p 

:
:
:
:
:
:
1.4
1.2
1.3
1.3
1.3
1.3

:
:
:
:
:
:
1.4
1.2
1.4
1.3
1.2
1.3

:
:
:
:
:
:
1.3
1.2
1.1
1.2
1.3
1.3

:
:
:
:
:
:
:
5.6
5.1 b 
5.8
5.6
5.6

:
:
:
:
:
:
:
5.4
5.4 b 
6.0
5.9
5.9

:
:
:
:
:
:
:
5.8
4.8 b 
5.5
5.2
5.4

16.8
18.0
18.9
19.8
19.8
19.4 b 
18.4
18.0
24.2 b 
25.6
27.4
29.2

18.9
20.1
21.4
21.9
23.0
21.8 b 
20.7
20.5
27.4 b 
29.1
31.2
33.8

14.8
16.0
16.4
17.9
16.7
17.1 b 
16.1
15.6
21.0 b 
22.1
23.6
24.6

:
5.7
5.4
5.3
5.5
5.2
5.2
5.8
6.0 i 
7.4 i 
7.7
7.5

:
4.8
4.8
4.6
5.0
4.8
4.8
5.5
5.6 i 
7.0 i 
7.4
7.3

:
6.4
6.0
6.0
6.0
5.6
5.7
6.1
6.4 i 
7.8 i 
8.0
7.8

:
:
4.3
6.3
6.5
6.5 b 
5.4
5.4
6.7
6.4
5.9
6.5

:
:
5.7
7.8
8.4
8.2 b 
6.9
6.9
8.2
7.5
7.3
8.6

:
:
2.7
4.6
4.4
4.5 b 
3.8
3.6
5.0
5.1
4.3 u 
4.2 u 

4.3
4.8
5.2
:
:
:
:
5.5
5.9 b 
6.1
7.4
7.5

4.3
4.8
5.3
:
:
:
:
6.4
6.8 b 
7.1
8.6
8.9

4.4
4.8
5.2
:
:
:
:
4.7
5.1 b 
5.1
6.2
6.1

0.9
0.9
0.9
1.0
1.3
1.0
1.2
1.1
2.6 b 
1.8
1.9
1.9

0.9
0.8
0.8
1.0
1.3
1.0
1.1
1.1
2.7 b 
1.8
1.8
1.8

1.0
1.1
1.1
1.0
1.2
1.0
1.2
1.1
2.6 b 
1.8
1.9
2.0

4.3
4.4
4.4
4.2
5.0
4.1 b 
4.4
4.4
4.7
4.7
10.5 b 
10.4

4.8
4.8
4.9
4.6
5.4
4.5 b 
4.9
4.8
5.1
5.1
11.4 b 
11.5

3.8
3.9
4.0
3.8
4.5
3.7 b 
4.0
4.0
4.3
4.2
9.7 b 
9.3

2.9
2.7
2.9
2.7
2.6
2.8
2.7
2.7
7.0 b 
7.0
7.0
7.5

3.0
2.8
3.0
2.8
2.7
3.1
3.0
3.0
7.1 b 
7.1
7.2
7.8

2.8
2.5
2.8
2.5
2.4
2.6
2.5
2.4
7.0 b 
7.0
6.9
7.2

3.8
4.1
4.6
4.8
5.5
4.8 b 
4.5
4.4
4.5
6.3 b 
5.8
6.1

3.6
4.0
4.5
4.6
5.2
4.8 b 
4.6
4.6
4.8
6.7 b 
6.2
6.5

4.0
4.2
4.6
5.0
5.9
4.8 b 
4.4
4.2
4.2
5.9 b 
5.4
5.7

:
:
:
:
2.6
3.1
3.4
3.7
7.9 b 
9.3
5.9 b 
7.1

:
:
:
:
2.2
3.2
3.4
3.8
8.5 b 
9.6
6.3 b 
7.8

:
:
:
:
3.1
3.1
3.4
3.6
7.1 b 
9.0
5.4 b 
6.5

Total
:
:
:
:
3.9
2.8
3.5
3.0 b 
3.8
5.9 b 
6.0
4.9 p 
Females
:
:
:
:
5.3
3.6
4.6
4.0 b 
4.7
7.4 b 
7.7
6.6 p 

Males
:
:
:
:
2.4
1.9
2.3
1.9 b 
2.8
4.2 b 
4.2
2.9 u 

2.9
2.9
2.8
5.1 b 
5.3
4.8
5.3
7.7
6.5 b 
9.8
8.5
8.2

2.3
1.9
2.1
4.8 b 
4.4
3.9
4.7
6.4
6.1 b 
10.1
8.5
8.7

3.5
3.9
3.6
5.4 b 
6.2
5.7
5.9
8.9
6.8 b 
9.5
8.5
7.6

:
:
:
:
:
:
:
7.3
7.8
8.4
7.9
6.9 p 

:
:
:
:
:
:
:
9.2
10.0
10.8
10.6
9.3 p 

:
:
:
:
:
:
:
5.1
5.4
5.7
5.0
4.1 p 

:
:
2.9
3.3
2.9
2.9
2.7
2.9
4.5 b 
4.0
3.9
3.8

:
:
3.0
3.6
3.1
3.3
3.1
3.3
4.9 b 
4.6
4.6
4.4

:
:
2.7
3.0
2.6
2.4
2.2
2.6
4.0 b 
3.4
3.2
3.1

:
:
:
:
:
4.5
4.6
4.4
4.2
4.3 b 
5.3
5.5

:
:
:
:
:
3.5
3.4
3.8
3.6
3.8 b 
4.5
5.6

:
:
:
:
:
5.6
5.8
4.9
4.7
4.8 b 
6.1
5.5

13.1
12.5
12.6
12.9
13.6
15.5
15.9
15.8
16.4 b 
16.4
15.9
15.6

12.2
11.7
11.5
11.8
12.7
14.7
15.2
15.5
16.8 b 
16.8
16.1
15.9

13.9
13.2
13.8
13.9
14.5
16.3
16.5
16.0
16.1 b 
16.1
15.6
15.3

7.7
7.9
7.8
:
9.1
8.3
8.2
7.5
8.6 b 
11.6 i 
12.9
13.1

6.3
6.1
6.7
:
8.4
7.4
7.7
7.3
8.6 b 
12.2 i 
13.5
14.0

9.2
9.7
9.0
:
9.8
9.2
8.7
7.6
8.6 b 
10.9 i 
12.3
12.2

:
:
:
:
:
:
4.3
4.2
4.4
5.0 b 
4.9
4.7

:
:
:
:
:
:
4.9
4.7
4.9
5.7 b 
5.4
5.1

:
:
:
:
:
:
3.7
3.6
3.9
4.3 b 
4.3
4.3

3.3
3.4
3.5
3.1 b 
3.4
3.4
3.3
2.9
3.2
4.3 b 
4.1
3.8 p 

3.5
3.5
3.4
3.2 b 
3.5
3.5
3.6
3.1
3.4
4.4 b 
4.2
4.0 p 

3.0
3.2
3.7
3.0 b 
3.2
3.2
2.9
2.6
3.0
4.1 b 
4.0
3.7 p 

:
:
0.9
1.0
0.8
0.9
1.0
1.0
1.1
1.4 p 
1.6
1.3

:
:
0.8
0.9
0.7
0.8
1.0
1.0
1.2
1.4 p 
1.6
1.3

:
:
1.1
1.1
1.0
0.9
1.1
1.0
1.1
1.3 p 
1.5
1.3

:
:
:
:
:
:
7.3
8.4
13.3 b 
16.2
15.3
15.0

:
:
:
:
:
:
7.9
8.9
14.7 b 
17.6
17.2
16.3

:
:
:
:
:
:
6.7
7.9
12.0 b 
14.8
13.6
13.8

:
:
:
:
:
:
:
8.5
3.7 b 
4.3
4.6
4.3

:
:
:
:
:
:
:
8.8
3.9 b 
4.8
5.0
4.6

:
:
:
:
:
:
:
8.2
3.5 b 
3.8
4.3
4.0

:
16.3
15.8
16.1
17.6
17.5 b 
17.2
17.3
22.4 b 
22.8
22.5
23.1

:
17.5
17.4
17.0
19.1
19.6 b 
19.7
20.0
26.2 b 
26.4
26.1
27.0

:
15.2
14.3
15.3
16.2
15.5 b 
14.7
14.5
18.6 b 
19.2
19.0
19.3

:
26.5
25.0
:
25.8
21.6
17.5 b 
18.4
31.8 b 
32.1
32.1
:

:
28.4
27.2
:
28.6
24.1
19.7 b 
21.2
35.4 b 
36.5
36.5
:

:
24.7
22.8
:
23.2
19.2
15.4 b 
15.7
28.4 b 
27.9
27.9
:

:
:
:
:
19.2
20.5 b 
20.9
21.3
26.8 b 
29.4
27.5
26.6 p 

:
:
:
:
22.3
23.6 b 
24.4
24.9
30.9 b 
33.7
32.0
31.2 p 

:
:
:
:
16.3
17.5 b 
17.5
17.8
22.7 b 
25.0
23.0
22.0 p 

:
:
:
:
:
:
:
1.9
1.8
1.9
2.1
:

:
:
:
:
:
:
:
1.9
1.9
2.0
2.1
:

:
:
:
:
:
:
:
2.0
1.8 u 
1.8 u 
2.0
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
1.0
1.0
1.0
1.2
1.1
1.9
2.0

:
:
:
:
:
1.2
1.2
1.3
1.7
1.5
2.4
2.4

:
:
:
:
:
0.8
0.7
0.7
0.7
0.8
1.3
1.6

Notes: 1) Reference period: From 27 October 2006, this indicator is based on annual averages of quarterly data instead of one unique reference quarter in spring. This improves both the accuracy and reliability of the results thanks to a better coverage of all weeks of the year and an increased sample size. Annual averages are used from 2005 onwards for all 
countries. Spring data are used between 2000 and 2002 for DE, FR, LU, CY, MT and SE, and for 2003-2004 for DE and CY. The average of the two semi-annual surveys is used for LV and LT for 2000-2001 and from 2002 for HR. Before 2000, all results are based on the spring survey.
2) Estimations are performed by Eurostat in case of outliers or missing information in the quarterly series.
3) Changes in survey characteristics: Due to the implementation of harmonised concepts and definitions in the survey, information on education and training lack comparability with former years: a) from 2003 in CZ, DK, EL, IE, CY, HU, NL, AT, SI, FI, SE, NO, CH, from 2004 in BE, LT, IT, IS, MT, PL, PT, UK and RO, and from 2005 in ES due to wider coverage of  
taught activities. b) from 2003 in SK  due to restrictions for self-learning. c) in 2003 and 2004 in DE due to the exclusion of personal interest courses.  d) in 2001 and 2002 in SI due to the exclusion of certain vocational training. e) 1999 in NL, 2000 in PT, 2003 in FR, 2003 in CH  due to changes in the reference period (formerly one week preceding the survey; addit
Due to changes in the survey characteristics, data lack comparability with former years in IT (from 1993), DK and DE (from 1996), PT (from 1998), BE and UK (from 1999), PL (1999 – quarter 1 for that year), FI (from 2000), SE and BG (from 2001), LV and LT (from 2002), DK and HU (from 2003), AT (from 2004), DE (from 2005).
4) FR data do not cover the overseas departments (DOM). TR (youth education attainment level): national data.
5) In case of missing country data, the EU aggregates are provided using the closest available year result.

Source: Eurostat - European Union Labour Force Survey.

EN 

207 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 7a

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Employment rate (Employed persons aged 15-64 as a percentage of the population of the same age group)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

60.7
61.2
61.8
62.2
62.5
62.3
62.5
62.9
63.4
64.4

51.4
52.0
53.0
53.7
54.3
54.4
54.8
55.4
56.2
57.2

70.0
70.3
70.7
70.8
70.9
70.3
70.3
70.3
70.8
71.6

60.6
61.2
61.9
62.4
62.8
62.8
62.9
63.3
63.9
64.7

51.1
51.8
52.9
53.6
54.3
54.7
55.0
55.7
56.5
57.4

70.2
70.6
71.0
71.2
71.3
71.0
70.8
70.9
71.3
72.0

58.5
59.3
60.5
61.5
62.2
62.4
62.6
63.0
63.7
64.6

47.7
48.7
50.2
51.4
52.4
53.1
53.6
54.5
55.6
56.7

69.3
69.9
70.8
71.6
72.0
71.7
71.5
71.5
71.8
72.6

56.8
57.4
59.3
60.5
59.9
59.9
59.6
60.3
61.1
61.0

46.5
47.6
50.4
51.5
51.0
51.4
51.8
52.6
53.8
54.0

67.1
67.1
68.1
69.5
68.8
68.3
67.3
67.9
68.3
67.9

:
:
:
50.4
49.7
50.6
52.5
54.2
55.8
58.6

:
:
:
46.3
46.8
47.5
49.0
50.6
51.7
54.6

:
:
:
54.7
52.7
53.7
56.0
57.9
60.0
62.8

:
67.3
65.6
65.0
65.0
65.4
64.7
64.2
64.8
65.3

:
58.7
57.4
56.9
56.9
57.0
56.3
56.0
56.3
56.8

:
76.0
74.0
73.2
73.2
73.9
73.1
72.3
73.3
73.7

74.9
75.1
76.0
76.3
76.2
75.9
75.1
75.7
75.9
77.4

69.1
70.2
71.1
71.6
72.0
71.7
70.5
71.6
71.9
73.4

80.5
79.9
80.8
80.8
80.2
80.0
79.6
79.7
79.8
81.2

63.7
63.9
65.2
65.6
65.8
65.4
65.0
65.0
66.0
67.5

55.3
55.8
57.4
58.1
58.7
58.9
58.9
59.2
60.6
62.2

71.9
71.9
72.8
72.9
72.8
71.8
70.9
70.8
71.3
72.8

:
64.6
61.5
60.4
61.0
62.0
62.9
63.0
64.4
68.1

:
60.3
57.8
56.9
57.4
57.9
59.0
60.0
62.1
65.3

:
69.6
65.8
64.3
65.0
66.5
67.2
66.4
67.0
71.0

57.6
60.6
63.3
65.2
65.8
65.5
65.5
66.3
67.6
68.6

45.9
49.0
52.0
53.9
54.9
55.4
55.7
56.5
58.3
59.3

69.1
72.1
74.5
76.3
76.6
75.4
75.2
75.9
76.9
77.7

55.1
56.0
55.9
56.5
56.3
57.5
58.7
59.4
60.1
61.0

39.3
40.5
41.0
41.7
41.5
42.9
44.3
45.2
46.1
47.4

72.1
71.7
71.1
71.5
71.4
72.2
73.4
73.7
74.2
74.6

49.5
51.3
53.8
56.3
57.8
58.5
59.8
61.1
63.3
64.8

34.6
35.8
38.5
41.3
43.1
44.4
46.3
48.3
51.2
53.2

64.5
66.8
69.3
71.2
72.5
72.6
73.2
73.8
75.2
76.1

59.6
60.2
60.9
62.1
62.8
63.0
63.3
63.1
63.1
63.0

52.4
53.1
54.0
55.2
56.0
56.7
57.2
57.4
57.6
57.7

66.9
67.4
68.0
69.2
69.7
69.5
69.4
68.9
68.8
68.5

51.3
51.9
52.7
53.7
54.8
55.5
56.1
57.6
57.6
58.4

36.4
37.3
38.3
39.6
41.1
42.0
42.7
45.2
45.3
46.3

66.5
66.8
67.3
68.0
68.5
69.1
69.6
70.1
69.9
70.5

:
:
:
65.7
67.8
68.6
69.2
68.9
68.5
69.6

:
:
:
53.5
57.2
59.1
60.4
58.7
58.4
60.3

:
:
:
78.7
79.3
78.9
78.8
79.8
79.2
79.4

Total
:
62.3
61.7
59.1
57.5
59.9
61.1
61.2
62.6
63.6
Females
:
58.6
59.4
57.7
56.2
57.2
58.4
57.8
59.4
61.0
Males
:
66.2
64.3
60.5
58.9
62.7
64.0
64.7
66.1
66.3

59.9
60.5
61.7
62.7
63.1
63.4
62.2
62.5
63.6
63.6

45.3
46.2
48.6
50.1
50.9
51.6
50.9
51.9
53.7
54.6

74.3
74.5
74.5
75.0
75.0
75.1
73.3
72.8
73.3
72.6

:
59.9
58.8
57.5
58.6
60.4
61.8
62.3
63.3
66.3

:
55.1
53.9
53.8
55.7
56.8
57.9
58.5
59.3
62.4

:
65.1
64.1
61.5
61.9
64.3
66.1
66.4
67.6
70.4

52.4
53.7
55.6
56.3
56.2
56.2
57.0
56.8
56.9
57.3

45.4
47.2
49.0
49.7
49.8
49.8
50.9
50.7
51.0
51.1

59.7
60.5
62.4
63.1
62.9
62.9
63.5
63.1
63.1
63.8

:
:
:
54.2
54.3
54.4
54.2
54.0
53.9
54.8

:
:
:
33.1
32.1
33.9
33.6
32.7
33.7
34.9

:
:
:
75.0
76.2
74.7
74.5
75.1
73.8
74.5

68.5
70.2
71.7
72.9
74.1
74.4
73.6
73.1
73.2
74.3

58.0
60.1
62.3
63.5
65.2
66.2
66.0
65.8
66.4
67.7

78.8
80.2
80.9
82.1
82.8
82.4
81.1
80.2
79.9
80.9

67.8
67.9
68.6
68.5
68.5
68.7
68.9
67.8
68.6
70.2

58.6
58.8
59.6
59.6
60.7
61.3
61.6
60.7
62.0
63.5

77.1
77.0
77.6
77.3
76.4
76.4
76.4
74.9
75.4
76.9

58.9
59.0
57.6
55.0
53.4
51.5
51.2
51.7
52.8
54.5

51.3
51.7
51.2
48.9
47.7
46.2
46.0
46.2
46.8
48.2

66.8
66.5
64.2
61.2
59.2
56.9
56.5
57.2
58.9
60.9

65.7
66.8
67.4
68.4
69.0
68.8
68.1
67.8
67.5
67.9

56.5
58.2
59.4
60.5
61.3
61.4
61.4
61.7
61.7
62.0

75.5
75.9
75.8
76.5
77.0
76.5
75.0
74.2
73.4
73.9

65.4
64.2
63.2
63.0
62.4
57.6
57.6
57.7
57.6
58.8

59.1
58.2
57.5
57.5
57.1
51.8
51.5
52.1
51.5
53.0

71.9
70.4
69.0
68.6
67.8
63.6
63.8
63.4
63.7
64.6

62.6
62.9
62.2
62.8
63.8
63.4
62.6
65.3
66.0
66.6

58.0
58.6
57.7
58.4
58.8
58.6
57.6
60.5
61.3
61.8

67.0
67.2
66.5
67.2
68.6
68.2
67.4
70.0
70.4
71.1

:
60.6
58.1
56.8
56.8
56.8
57.7
57.0
57.7
59.4

:
53.5
52.1
51.5
51.8
51.4
52.2
50.9
50.9
51.9

:
67.8
64.3
62.2
62.0
62.4
63.3
63.2
64.6
67.0

63.3
64.6
66.4
67.2
68.1
68.1
67.7
67.6
68.4
69.3

60.3
61.2
63.4
64.2
65.4
66.2
65.7
65.6
66.5
67.3

66.2
67.8
69.2
70.1
70.8
70.0
69.7
69.7
70.3
71.4

69.5
70.3
71.7
73.0
74.0
73.6
72.9
72.1
72.5
73.1

67.2
67.9
69.4
70.9
72.3
72.2
71.5
70.5
70.4
70.7

71.7
72.8
74.0
75.1
75.7
74.9
74.2
73.6
74.4
75.5

69.9
70.5
71.0
71.2
71.4
71.3
71.5
71.6
71.7
71.5

63.1
63.6
64.2
64.7
65.0
65.2
65.3
65.6
65.9
65.8

76.6
77.3
77.7
77.8
78.0
77.6
77.7
77.8
77.6
77.3

:
:
:
:
:
53.4
53.4
54.7
55.0
55.6

:
:
:
:
:
46.7
46.7
47.8
48.6
49.4

:
:
:
:
:
60.5
60.3
61.8
61.7
62.0

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
48.8
47.8
46.9
45.8
46.1
46.0
45.9

:
:
:
25.8
26.3
27.0
25.7
24.3
23.8
23.9

:
:
:
71.8
69.4
66.9
65.9
67.8
68.2
68.1

Source: Eurostat - Quarterly Labour Force Data (QLFD)

EU-
27

EU-
25

EA-
13

Key indicator 7b

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Employment rate of older workers (Employed persons aged 55-64 as a percentage of the population of the same age group)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

36.2
36.2
36.5
36.9
37.7
38.5
40.0
40.7
42.3
43.5

26.1
26.1
26.7
27.4
28.2
29.1
30.7
31.6
33.5
34.8

47.1
47.0
46.9
47.1
47.7
48.4
49.9
50.3
51.5
52.6

35.7
35.8
36.2
36.6
37.5
38.7
40.2
41.0
42.5
43.6

25.5
25.5
26.3
26.9
27.8
29.2
30.7
31.7
33.7
34.9

46.6
46.6
46.7
46.9
47.7
48.8
50.3
50.7
51.8
52.8

33.4
33.5
33.8
34.3
35.1
36.4
37.8
38.6
40.4
41.7

22.9
22.9
23.7
24.3
25.1
26.6
27.9
29.0
31.5
32.9

44.5
44.5
44.4
44.8
45.5
46.7
48.1
48.5
49.7
50.8

22.1
22.9
24.6
26.3
25.1
26.6
28.1
30.0
31.8
32.0

12.9
14.0
15.7
16.6
15.5
17.5
18.7
21.1
22.1
23.2

31.7
32.1
33.8
36.4
35.1
36.0
37.8
39.1
41.7
40.9

:
:
:
20.8
24.0
27.0
30.0
32.5
34.7
39.6

:
:
:
10.3
14.7
18.2
21.0
24.2
25.5
31.1

:
:
:
33.2
34.2
37.0
40.5
42.2
45.5
49.5

:
37.1
37.5
36.3
37.1
40.8
42.3
42.7
44.5
45.2

:
22.9
23.2
22.4
23.1
25.9
28.4
29.4
30.9
32.1

:
53.2
53.6
51.7
52.6
57.2
57.5
57.2
59.3
59.5

51.7
52.0
54.5
55.7
58.0
57.9
60.2
60.3
59.5
60.7

40.3
42.0
45.8
46.6
49.7
50.4
52.9
53.3
53.5
54.3

62.7
61.3
62.6
64.1
65.5
64.5
67.3
67.3
65.6
67.1

38.1
37.7
37.8
37.6
37.9
38.9
39.9
41.8
45.4
48.4

28.7
28.3
28.8
29.0
29.4
30.6
31.6
33.0
37.5
40.6

47.5
47.2
46.8
46.4
46.5
47.3
48.2
50.7
53.5
56.4

:
50.2
47.5
46.3
48.5
51.6
52.3
52.4
56.1
58.5

:
41.6
39.2
39.0
42.1
46.5
47.3
49.4
53.7
59.2

:
62.0
58.9
55.9
56.7
58.4
58.9
56.4
59.3
57.5

40.4
41.7
43.7
45.3
46.8
48.0
49.0
49.5
51.6
53.1

21.6
23.1
25.6
27.2
28.7
30.8
33.1
33.7
37.3
39.1

58.9
60.2
61.7
63.2
64.6
65.0
64.6
65.0
65.7
67.0

41.0
39.0
39.3
39.0
38.2
39.2
41.3
39.4
41.6
42.3

24.6
23.5
24.4
24.3
22.9
24.0
25.5
24.0
25.8
26.6

59.1
56.0
55.7
55.2
55.3
55.9
58.7
56.4
58.8
59.2

34.1
35.1
35.0
37.0
39.2
39.6
40.7
41.3
43.1
44.1

18.0
18.8
18.9
20.2
21.7
21.9
23.3
24.6
27.4
28.7

51.2
52.6
52.2
54.9
57.7
58.4
59.2
58.9
59.7
60.4

29.0
28.3
28.8
29.9
31.9
34.7
36.8
37.3
37.9
37.6

25.0
24.4
25.4
26.3
27.8
30.8
32.9
33.8
35.2
35.2

33.2
32.5
32.3
33.6
36.2
38.7
40.9
41.0
40.7
40.1

27.9
27.7
27.6
27.7
28.0
28.9
30.3
30.5
31.4
32.5

14.8
15.0
15.0
15.3
16.2
17.3
18.5
19.6
20.8
21.9

42.0
41.4
41.2
40.9
40.4
41.3
42.8
42.2
42.7
43.7

:
:
:
49.4
49.1
49.4
50.4
49.9
50.6
53.6

:
:
:
32.1
32.2
32.2
32.7
30.0
31.5
36.6

:
:
:
67.3
66.9
67.3
68.9
70.8
70.8
71.6

Source: Eurostat - Quarterly Labour Force Data (QLFD)

Total
:
39.5
40.9
40.4
38.9
41.6
44.7
47.1
49.2
49.6
Females

:
28.3
30.6
32.6
31.1
34.1
36.7
39.3
41.7
45.1

Males
:
54.4
54.4
50.6
49.2
51.5
55.3
57.6
59.1
55.7

23.9
25.1
26.4
26.7
25.6
28.1
30.3
30.4
31.7
33.2

12.9
15.5
17.2
16.4
15.2
18.4
20.6
22.2
24.9
27.8

35.4
35.2
35.8
37.2
35.9
37.7
39.7
38.3
38.3
38.7

:
36.3
36.6
36.0
36.9
41.7
44.1
47.9
49.5
53.3

:
27.5
26.6
26.7
30.0
35.2
38.8
41.9
45.3
48.7

:
48.1
49.9
48.4
46.2
50.5
51.3
55.8
55.2
59.5

17.7
17.3
19.4
22.2
23.5
25.6
28.9
31.1
33.0
33.6

10.3
9.6
11.3
13.3
14.9
17.6
21.8
25.0
26.7
27.1

27.0
27.0
29.7
33.2
34.1
35.5
37.8
38.4
40.6
41.4

:
:
:
28.5
29.4
30.1
32.5
31.5
30.8
30.0

:
:
:
8.4
10.2
10.9
13.0
11.5
12.4
11.2

:
:
:
50.8
50.4
50.8
53.8
53.4
50.8
50.4

32.0
33.9
36.4
38.2
39.6
42.3
44.3
45.2
46.1
47.7

19.9
20.3
23.1
26.1
28.0
29.9
31.8
33.4
35.2
37.2

44.3
47.5
49.6
50.2
51.1
54.6
56.7
56.9
56.9
58.0

28.3
28.4
29.7
28.8
28.9
29.1
30.3
28.8
31.8
35.5

17.0
17.1
17.6
17.2
18.4
19.3
20.8
19.3
22.9
26.3

40.3
40.5
42.6
41.2
40.1
39.6
40.4
38.9
41.3
45.3

33.9
32.1
31.9
28.4
27.4
26.1
26.9
26.2
27.2
28.1

26.1
24.1
24.5
21.4
20.4
18.9
19.8
19.4
19.7
19.0

43.1
41.5
40.6
36.7
35.6
34.5
35.2
34.1
35.9
38.4

48.5
49.6
50.1
50.7
50.2
51.4
51.6
50.3
50.5
50.1

36.1
38.0
40.3
40.6
40.3
42.2
42.4
42.5
43.7
42.8

63.2
62.9
61.4
62.1
61.6
61.9
62.1
59.1
58.1
58.2

52.1
51.5
49.6
49.5
48.2
37.3
38.1
36.9
39.4
41.7

44.6
44.5
43.3
43.8
42.9
32.6
33.3
31.4
33.1
34.5

60.7
59.5
56.9
56.0
54.3
42.7
43.5
43.1
46.7
50.0

21.8
23.9
22.0
22.7
25.5
24.5
23.5
29.0
30.7
32.6

14.6
16.1
13.4
13.8
15.8
14.2
14.6
17.8
18.5
21.0

29.4
31.8
31.1
32.3
35.9
35.4
33.2
40.9
43.1
44.5

:
22.8
22.3
21.3
22.4
22.8
24.6
26.8
30.3
33.1

:
9.4
10.3
9.8
9.8
9.5
11.2
12.6
15.6
18.9

:
39.1
36.8
35.4
37.7
39.1
41.0
43.8
47.8
49.8

35.6
36.2
39.0
41.6
45.7
47.8
49.6
50.9
52.7
54.5

33.3
34.1
38.0
40.4
45.0
47.2
48.3
50.4
52.7
54.3

38.1
38.4
40.1
42.9
46.6
48.5
51.0
51.4
52.8
54.8

62.6
63.0
63.9
64.9
66.7
68.0
68.6
69.1
69.4
69.6

60.4
60.0
60.7
62.1
64.0
65.6
66.3
67.0
66.7
66.9

65.1
66.1
67.3
67.8
69.4
70.4
70.8
71.2
72.0
72.3

48.3
49.0
49.6
50.7
52.2
53.4
55.4
56.2
56.9
57.4

38.5
39.2
39.9
41.7
43.0
44.5
46.3
47.0
48.1
49.1

58.4
59.1
59.7
60.1
61.7
62.6
64.8
65.7
66.0
66.0

:
:
:
:
:
24.8
28.4
30.1
32.6
34.3

:
:
:
:
:
16.9
20.3
21.0
23.8
25.7

:
:
:
:
:
34.2
38.1
40.9
43.0
44.4

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
36.3
35.8
35.7
33.5
33.2
31.0
30.1

:
:
:
20.8
21.2
23.3
22.1
20.0
17.1
16.7

:
:
:
52.4
51.0
48.7
45.4
46.9
45.4
44.1

EN 

208 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 8a

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Unemployment rate (Unemployed persons as a percentage of the active population)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

:
:
:
8.6
8.4
8.8
9.0
9.0
8.7
7.9

:
:
:
10.0
9.7
10.0
10.0
10.1
9.7
8.8

:
:
:
7.5
7.5
8.0
8.1
8.2
7.9
7.2

:
9.3
9.0
8.6
8.4
8.7
9.0
9.0
8.7
7.9

:
11.1
10.7
10.1
9.7
9.9
10.1
10.2
9.8
9.0

:
7.9
7.7
7.3
7.3
7.7
8.1
8.1
7.9
7.1

10.5
10.0
9.1
8.2
7.8
8.2
8.7
8.8
8.6
7.9

13.2
12.7
11.6
10.4
9.8
10.0
10.4
10.4
10.0
9.3

8.5
8.0
7.3
6.5
6.3
6.8
7.3
7.5
7.4
6.8

9.2
9.3
8.5
6.9
6.6
7.5
8.2
8.4
8.4
8.2

11.9
11.6
10.3
8.5
7.5
8.6
8.9
9.5
9.5
9.3

7.3
7.7
7.1
5.6
5.9
6.7
7.6
7.5
7.6
7.4

:
:
:
16.4
19.5
18.1
13.7
12.0
10.1
9.0

:
:
:
16.2
18.6
17.3
13.2
11.5
9.8
9.3

:
:
:
16.7
20.2
18.9
14.1
12.5
10.3
8.6

:
6.4
8.6
8.7
8.0
7.3
7.8
8.3
7.9
7.1

:
8.1
10.3
10.3
9.7
9.0
9.9
9.9
9.8
8.8

:
5.0
7.3
7.3
6.7
5.9
6.2
7.1
6.5
5.8

Source: Eurostat - Unemployment rates (ILO definition)

5.2
4.9
5.2
4.3
4.5
4.6
5.4
5.5
4.8
3.9

6.2
6.0
5.8
4.8
5.0
5.0
6.1
6.0
5.3
4.5

4.4
3.9
4.6
3.9
4.1
4.3
4.8
5.1
4.4
3.3

9.1
8.8
7.9
7.2
7.4
8.2
9.0
9.5
9.5
8.4

11.6
11.1
9.9
8.7
8.9
9.4
10.1
10.5
10.3
9.2

7.3
7.1
6.4
6.0
6.3
7.1
8.2
8.7
8.8
7.7

9.6
9.2
11.3
12.8
12.4
10.3
10.0
9.7
7.9
5.9

8.9
8.3
10.1
11.8
12.2
9.7
9.9
8.9
7.1
5.6

10.3
9.9
12.5
13.8
12.6
10.8
10.2
10.4
8.8
6.2

9.9
7.5
5.7
4.2
4.0
4.5
4.7
4.5
4.3
4.4

9.9
7.3
5.6
4.2
3.8
4.1
4.3
4.1
4.0
4.1

9.9
7.7
5.7
4.3
4.1
4.7
5.0
4.9
4.6
4.6

9.8
10.8
12.0
11.2
10.7
10.3
9.7
10.5
9.8
8.9

15.2
16.7
18.1
17.1
16.1
15.6
15.0
16.2
15.3
13.6

6.4
7.0
7.9
7.4
7.1
6.8
6.2
6.6
6.1
5.6

16.7
15.0
12.5
11.1
10.3
11.1
11.1
10.6
9.2
8.5

22.6
21.1
18.0
16.0
14.8
15.7
15.3
14.3
12.2
11.6

13.1
11.2
9.0
7.9
7.5
8.1
8.2
8.0
7.0
6.3

11.5
11.1
10.5
9.1
8.4
8.7
9.5
9.6
9.7
9.5

13.3
12.9
12.2
10.9
10.0
9.8
10.6
10.6
10.7
10.4

10.1
9.5
9.0
7.6
7.0
7.8
8.5
8.8
8.8
8.7

11.3
11.3
10.9
10.1
9.1
8.6
8.4
8.0
7.7
6.8

15.3
15.4
14.8
13.6
12.2
11.5
11.3
10.5
10.1
8.8

8.7
8.8
8.4
7.8
7.1
6.7
6.5
6.4
6.2
5.4

:
:
:
4.9
3.8
3.6
4.1
4.6
5.2
4.6

:
:
:
7.2
5.3
4.5
4.8
6.0
6.5
5.4

:
:
:
3.2
2.6
2.9
3.6
3.6
4.3
4.0

Total
:
13.2
13.7
16.4
16.5
13.5
12.4
11.4
8.3
5.6
Females
:
11.7
12.3
14.1
14.3
12.8
12.2
11.8
8.3
5.4
Males
:
14.6
15.1
18.6
18.6
14.2
12.7
11.0
8.2
5.8

:
14.3
14.0
13.7
12.9
12.2
10.5
10.4
8.9
6.8

:
13.6
13.6
12.9
11.5
11.0
10.4
10.2
8.7
6.2

:
15.1
14.4
14.4
14.2
13.3
10.6
10.6
9.1
7.4

2.7
2.7
2.4
2.3
2.0
2.7
3.7
5.1
4.5
4.7

3.9
4.0
3.3
3.1
2.6
3.7
4.7
7.1
5.8
6.2

2.0
1.9
1.8
1.8
1.7
2.0
3.0
3.7
3.5
3.5

9.0
8.4
6.9
6.4
5.7
5.8
5.9
6.1
7.2
7.5

8.1
7.8
6.3
5.6
5.0
5.4
5.6
6.1
7.4
7.8

9.7
9.0
7.5
7.0
6.3
6.2
6.1
6.1
7.0
7.2

:
:
:
6.7
7.6
7.5
7.6
7.4
7.3
7.3

:
:
:
7.4
9.3
9.3
9.1
9.0
9.0
8.9

:
:
:
6.4
6.9
6.6
6.9
6.6
6.5
6.5

4.9
3.8
3.2
2.8
2.2
2.8
3.7
4.6
4.7
3.9

6.6
5.0
4.4
3.6
2.8
3.1
3.9
4.8
5.1
4.4

3.7
3.0
2.3
2.2
1.8
2.5
3.5
4.3
4.4
3.5

4.4
4.5
3.9
3.6
3.6
4.2
4.3
4.8
5.2
4.7

5.4
5.4
4.7
4.3
4.2
4.4
4.7
5.3
5.5
5.2

3.6
3.8
3.3
3.1
3.1
4.0
4.0
4.4
4.9
4.4

10.9
10.2
13.4
16.1
18.2
19.9
19.6
19.0
17.7
13.8

13.0
12.2
15.3
18.1
19.8
20.9
20.4
19.9
19.1
14.9

9.1
8.5
11.8
14.4
16.9
19.1
19.0
18.2
16.6
13.0

6.8
5.1
4.5
4.0
4.0
5.0
6.3
6.7
7.6
7.7

7.6
6.3
5.2
4.9
5.0
6.0
7.2
7.6
8.7
9.0

6.1
4.1
4.0
3.2
3.2
4.1
5.5
5.8
6.7
6.5

5.3
5.4
6.6
7.2
6.6
8.4
7.0
8.1
7.2
7.3

5.7
5.3
5.9
6.4
5.9
7.7
6.4
6.9
6.4
6.1

5.0
5.5
7.2
7.8
7.2
9.1
7.6
9.1
7.8
8.2

6.9
7.4
7.3
6.7
6.2
6.3
6.7
6.3
6.5
6.0

7.1
7.5
7.5
7.0
6.8
6.8
7.1
6.8
7.0
7.2

6.8
7.3
7.1
6.5
5.6
5.9
6.3
5.8
6.1
4.9

:
12.6
16.4
18.8
19.3
18.7
17.6
18.2
16.3
13.4

:
13.1
16.4
18.6
18.7
18.7
17.7
19.2
17.2
14.7

:
12.2
16.3
18.9
19.8
18.6
17.4
17.4
15.5
12.3

12.7
11.4
10.2
9.8
9.1
9.1
9.0
8.8
8.4
7.7

13.0
12.0
10.7
10.6
9.7
9.1
8.9
8.9
8.6
8.1

12.3
10.9
9.8
9.1
8.6
9.1
9.2
8.7
8.2
7.4

9.9
8.2
6.7
5.6
4.9
4.9
5.6
6.3
7.4
7.1

9.5
8.0
6.8
5.3
4.5
4.6
5.2
6.1
7.3
7.2

10.2
8.4
6.6
5.9
5.2
5.3
6.0
6.5
7.5
6.9

6.8
6.1
5.9
5.3
5.0
5.1
4.9
4.7
4.8
5.3

5.8
5.3
5.2
4.8
4.4
4.5
4.3
4.2
4.3
4.9

7.6
6.8
6.5
5.8
5.5
5.6
5.5
5.0
5.1
5.7

:
:
:
:
:
14.7
14.1
13.6
12.6
:

:
:
:
:
:
16.5
15.6
15.6
13.8
:

:
:
:
:
:
13.2
12.8
12.0
11.6
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
6.5
8.3
10.3
10.5
10.3
10.2
9.9

:
:
:
6.3
7.4
9.4
10.1
9.7
10.2
10.3

:
:
:
6.6
8.7
10.7
10.7
10.5
10.2
9.7

EU-
27

EU-
25

EA-
13

Key indicator 8b

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Long-term unemployment rate (Long-term unemployed persons (12 months and more) as a percentage of the active population)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

:
:
:
4.0
3.9
4.0
4.1
4.2
4.0
3.6

:
:
:
4.7
4.6
4.7
4.7
4.7
4.5
4.0

:
:
:
3.4
3.3
3.5
3.7
3.7
3.6
3.3

:
4.4
4.1
3.9
3.8
3.9
4.0
4.1
3.9
3.6

:
5.4
5.0
4.7
4.5
4.6
4.6
4.7
4.5
4.0

:
3.6
3.4
3.2
3.2
3.3
3.5
3.6
3.5
3.2

5.4
5.0
4.4
3.9
3.6
3.6
3.9
4.0
3.8
3.6

7.0
6.5
5.8
5.1
4.6
4.5
4.7
4.9
4.5
4.2

4.1
3.8
3.4
3.0
2.8
2.8
3.2
3.4
3.3
3.1

5.4
5.6
4.8
3.7
3.2
3.7
3.7
4.1
4.4
4.2

7.1
7.1
5.9
4.6
3.5
4.3
4.2
4.7
5.0
4.9

4.2
4.5
4.0
3.0
2.9
3.2
3.3
3.7
3.8
3.7

:
:
:
9.4
12.1
12.0
8.9
7.2
6.0
5.0

:
:
:
9.2
11.4
11.4
8.6
7.0
6.0
5.2

:
:
:
9.6
12.6
12.5
9.2
7.3
6.1
4.8

:
2.0
3.2
4.2
4.2
3.7
3.8
4.2
4.2
3.9

:
2.6
4.2
5.2
5.1
4.5
5.0
5.3
5.3
4.9

:
1.5
2.4
3.5
3.4
3.0
2.9
3.4
3.4
3.1

1.5
1.3
1.1
0.9
0.9
0.9
1.1
1.2
1.1
0.8

1.9
1.7
1.3
1.1
1.0
1.0
1.0
1.3
1.2
0.9

1.2
0.9
1.0
0.8
0.8
0.7
1.2
1.1
1.1
0.7

4.6
4.5
4.1
3.7
3.7
3.9
4.5
5.4
5.0
4.7

6.2
6.0
5.2
4.6
4.6
4.8
5.2
6.0
5.5
5.2

3.4
3.4
3.2
3.0
3.0
3.3
3.9
4.8
4.7
4.4

:
4.2
5.0
5.9
6.0
5.4
4.6
5.0
4.2
2.8

:
4.1
4.5
5.0
5.4
4.4
4.4
4.4
4.2
2.6

:
4.4
5.5
6.7
6.6
6.3
4.8
5.6
4.2
3.1

5.6
3.9
2.4
1.6
1.3
1.3
1.5
1.6
1.5
1.4

4.6
2.8
1.6
1.0
0.8
0.8
1.0
1.0
0.8
0.9

6.2
4.7
3.0
2.0
1.7
1.8
1.9
2.0
1.9
1.8

5.3
5.8
6.5
6.1
5.5
5.3
5.3
5.6
5.1
4.8

9.2
10.1
10.7
10.1
9.0
8.6
8.9
9.4
8.9
8.0

2.8
3.1
3.7
3.5
3.2
3.1
3.0
3.0
2.6
2.6

8.7
7.5
5.7
4.6
3.7
3.7
3.7
3.4
2.2
1.8

13.0
11.6
9.0
7.4
6.0
5.9
5.7
5.0
3.4
2.8

6.1
4.9
3.6
2.8
2.3
2.3
2.4
2.2
1.4
1.2

4.7
4.5
4.1
3.5
3.0
3.0
3.7
3.9
4.0
4.0

5.5
5.3
4.9
4.3
3.6
3.5
4.1
4.3
4.5
4.3

3.9
3.8
3.4
2.9
2.4
2.6
3.4
3.5
3.5
3.7

7.3
6.8
6.7
6.3
5.7
5.1
4.9
4.0
3.9
3.4

10.0
9.1
9.0
8.4
7.6
6.9
6.6
5.5
5.2
4.5

5.6
5.3
5.2
4.8
4.4
4.0
3.8
2.9
2.9
2.6

:
:
:
1.2
0.8
0.8
1.0
1.2
1.2
0.9

:
:
:
2.2
1.1
1.0
1.3
1.6
1.7
1.2

:
:
:
0.5
0.6
0.5
0.7
0.9
0.8
0.7

Source: Eurostat - Quarterly Labour Force Data (QLFD)

Total
:
7.5
5.3
8.0
9.3
7.2
6.0
5.8
4.3
2.5

Females
:
7.0
4.4
6.5
7.7
6.8
6.0
6.2
4.5
2.4

Males
:
7.9
6.1
9.4
10.8
7.6
6.0
5.5
4.2
2.5

0.9
0.9
0.7
0.6
0.6
0.7
0.9
1.1
1.2
1.4

1.3
1.1
0.9
0.6
0.6
0.9
0.9
1.4
1.2
1.6

0.7
0.7
0.6
0.5
0.5
0.6
0.9
0.8
1.2
1.2

:
7.9
7.6
7.9
7.2
5.5
4.4
4.6
4.1
2.5

:
7.5
7.6
7.5
6.3
4.6
4.4
4.3
3.7
1.9

:
8.3
7.6
8.3
8.1
6.4
4.3
4.8
4.4
3.0

4.5
4.2
3.3
3.1
2.6
2.5
2.4
2.7
3.2
3.4

4.0
3.8
2.9
2.5
2.1
2.2
2.3
2.6
3.2
3.4

4.9
4.5
3.7
3.5
3.0
2.8
2.5
2.8
3.3
3.3

:
:
:
4.4
3.7
3.3
3.2
3.4
3.4
2.9

:
:
:
4.2
2.7
2.4
2.4
3.0
3.2
2.5

:
:
:
4.5
3.9
3.5
3.4
3.7
3.4
3.1

2.3
1.5
1.2
0.8
0.6
0.7
1.0
1.6
1.9
1.7

3.1
1.8
1.5
1.0
0.7
0.9
1.1
1.6
1.9
1.8

1.8
1.3
0.9
0.6
0.5
0.6
1.0
1.5
1.9
1.6

1.3
1.3
1.2
1.0
0.9
1.1
1.1
1.3
1.3
1.3

1.6
1.8
1.5
1.2
1.1
1.2
1.1
1.4
1.4
1.3

1.0
1.0
0.9
0.9
0.7
1.0
1.1
1.3
1.2
1.3

5.0
4.7
5.8
7.4
9.2
10.9
11.0
10.3
10.2
7.8

6.7
6.3
7.4
9.1
10.8
12.3
11.7
11.0
11.4
8.6

3.7
3.5
4.5
6.0
7.8
9.7
10.3
9.6
9.3
7.1

3.2
2.2
1.8
1.7
1.5
1.7
2.2
2.9
3.7
3.8

3.5
2.8
2.1
2.0
1.9
2.2
2.7
3.4
4.2
4.4

3.0
1.7
1.5
1.4
1.2
1.4
1.8
2.6
3.2
3.3

2.5
2.3
2.9
3.7
3.3
4.6
4.3
4.8
4.0
4.2

2.9
2.5
2.8
3.4
3.0
4.3
4.1
3.8
3.4
3.6

2.1
2.2
3.0
3.9
3.5
4.8
4.6
5.5
4.6
4.7

3.4
3.3
3.3
4.1
3.7
3.5
3.5
3.2
3.1
2.9

3.3
3.3
3.1
4.2
4.0
3.6
3.6
3.4
3.3
3.5

3.6
3.3
3.5
4.1
3.5
3.4
3.4
3.1
2.9
2.4

:
6.5
7.8
10.3
11.3
12.2
11.4
11.8
11.7
10.2

:
7.1
8.3
10.2
11.3
12.5
11.7
12.4
12.3
11.2

:
6.0
7.4
10.3
11.3
11.9
11.3
11.3
11.2
9.4

4.9
4.1
3.0
2.8
2.5
2.3
2.3
2.1
2.2
1.9

5.0
3.9
2.8
2.7
2.3
2.0
2.0
2.0
1.9
1.8

4.9
4.3
3.2
2.8
2.7
2.5
2.6
2.3
2.4
2.1

3.1
2.6
1.9
1.4
1.0
1.0
1.0
1.2
1.2
1.1

2.0
1.8
1.4
1.0
0.8
0.8
0.8
1.0
1.0
0.9

4.0
3.2
2.2
1.7
1.2
1.2
1.2
1.4
1.4
1.2

2.5
1.9
1.7
1.4
1.3
1.1
1.1
1.0
1.0
1.2

1.5
1.2
1.0
0.9
0.8
0.7
0.7
0.6
0.7
0.8

3.3
2.4
2.2
1.9
1.7
1.4
1.4
1.2
1.3
1.5

:
:
:
:
:
8.9
8.4
7.3
7.4
6.7

:
:
:
:
:
10.7
9.5
8.9
8.4
7.7

:
:
:
:
:
7.4
7.4
6.0
6.5
5.8

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
1.1
1.4
2.7
2.2
3.5
3.5
2.5

:
:
:
1.5
1.9
3.0
2.7
3.8
4.0
3.3

:
:
:
1.0
1.3
2.5
2.1
3.4
3.3
2.3

EN 

209 

EN 

 
  
 
EU27 

EU15 

BE

BG

CZ

DK

DE

EE

IE

GR

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SK

SI

FI

SE

UK

HR

MK

TR

:
:

:
0.801

Key indicator 9
1998
1999
2000
2001
2002
2003
2004
2005

0.525462 0.544446

0.758

0.628

0.736

0.738

0.705

:

:

:

:

:

Public expenditure on LMP measures (categories 2-7) as a percentage of GDP

1.074
0.996

0.972

0.966

0.869

0.99

0.916

:
:

:

:

:

:

0.472

:
:

:

:

0.117

0.116

0.132

1.643
1.831

1.666

1.629

1.65

1.517

1.524

0.955
1.07

0.988

0.957

1.037

0.951

0.857

:
:

:

:

:

0.048

0.041

0.928
0.867

0.787

0.722

0.636

0.589

0.495

:
0.269

0.258

0.274

0.186

0.098

0.155

0.498
0.632

0.659

0.605

0.562

0.561

0.55

0.985
1.046

1.013

0.956

0.901

0.819

0.722

0.483
0.538

0.546

0.608

0.643

0.665

0.532

0.852169 0.431529 0.122067 1.432737 0.616207 0.047032 0.480742 0.061099 0.582582 0.664139 0.460517

:
:

:

:

:

:

:

:

:
:

:

:

:

:
:

:

:

:

0.085

0.076

0.152

0.154

0.148258 0.147456

:
:

:

:

:

:

:

:

:
:

:

:

:

:

0.204

0.197017

:
:

:

:

:

:

:

:

0.923
0.922

1.083

1.119

1.137

1.153

0.907

0.325
0.408

0.385

0.427

0.407

0.45

0.433

:
:

:

:

:

:

:

0.394
0.317

0.354

0.466

0.427

0.51

0.545

:
:

:

:

:

0.109

0.103

:
:

:

:

:

:

0.071

:
:

:

:

:

:

:

0.996
0.91

0.746

0.675

0.692

0.735

0.767

2.222
1.978

1.532

1.44

1.368

1.033

1.005

:
0.198

0.199

0.161

0.16

0.157

0.154

0.852375 0.457974 0.359288 0.516965 0.107565 0.195762 0.170152 0.711316 1.097303 0.115571

:
:

:

:

:

:

:

:

:
:

:

:

:

:

:

:

:
:

:

:

:

:

:

:

Notes:Category 1: Labour Market Services. 
Categories 2-7: Training - Job rotation and job sharing - Employment incentives - Supported employment and rehabilitation - Direct job creation - Start-up incentives.                                                                                                                                                                                  
Categories 8-9: Out of work income maintenance and support - Early retirement. 2005: estimates for EU-27, EU-15, BE, DK, DE, IE, EL, FR, NL, AT, PT, FI, UK

Source: Eurostat - Labour Market Policy Database (LMP)

EU-
27

EU-
25

EA-
13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 10
27.3
1995
27.6
1996
27.3
1997
27.0
1998
27.0
1999
26.7
2000
26.8
2001
27.4
2002
2003
27.8
2004
27.7

:
:
:
:
:
26.6
26.8
27.0
27.4
27.3

:
:
:
:
:
:
:
:
:
:

Expenditure on social protection as a percentage of GDP

27.4
28.0
27.4
27.1
27.0
26.5
27.3
28.0
29.1
29.3

:
:
:
:
:
:
:
:
:
:

17.4
17.6
18.6
18.5
19.2
19.5
19.4
20.2
20.2
19.6

31.9
31.2
30.1
30.0
29.8
28.9
29.2
29.7
30.7
30.7

28.2
29.3
28.9
28.8
29.2
29.2
29.3
29.9
30.2
29.5

:
:
:
:
:
14.0
13.1
12.7
12.9
13.4

18.8
17.6
16.4
15.2
14.6
14.1
15.0
16.0
16.5
17.0

22.3
22.9
23.3
24.2
25.5
25.7
26.7
26.2
26.0
26.0

21.6
21.5
20.8
20.2
19.8
19.7
19.5
19.8
19.9
20.0

30.3
30.6
30.4
30.0
29.9
29.5
29.6
30.4
30.9
31.2

24.2
24.3
24.9
24.6
24.8
24.7
24.9
25.3
25.8
26.1

:
:
:
:
:
14.8
14.9
16.3
18.5
17.8

:
:
15.3
16.1
17.2
15.3
14.3
13.9
13.4
12.6

:
13.4
13.8
15.2
16.4
15.8
14.7
14.1
13.6
13.3

20.7
21.2
21.5
21.2
20.5
19.6
20.8
21.4
22.2
22.6

:
:
:
:
20.7
19.3
19.3
20.3
21.1
20.7

:
16.5
17.2
17.1
17.0
16.3
17.1
17.1
17.9
18.8

30.6
29.6
28.7
27.8
27.1
26.4
26.5
27.6
28.3
28.5

28.7
28.6
28.6
28.3
28.7
28.2
28.6
29.1
29.5
29.1

:
:
:
:
:
19.5
20.8
21.2
20.9
20.0

21.0
20.2
20.3
20.9
21.4
21.7
22.7
23.7
24.2
24.9

:
:
:
:
:
13.2
13.2
13.4
12.6
14.9

:
24.0
24.5
24.8
24.7
24.9
25.3
25.3
24.6
24.3

18.4
19.3
19.6
20.0
20.0
19.3
18.9
19.0
18.2
17.2

31.5
31.4
29.1
27.0
26.2
25.1
24.9
25.6
26.5
26.7

34.3
33.6
32.7
32.0
31.7
30.7
31.3
32.3
33.3
32.9

28.2
28.0
27.5
26.9
26.4
27.1
27.5
26.4
26.4
26.3

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

Note: EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

EN 

210 

EN 

 
  
 
 
EU-
27

EU-
25

EA-
13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 11a
45.5
1995
1996
45.7
46.4
1997
46.6
1998
46.6
1999
46.7
2000
46.7
2001
46.4
2002
2003
46.3
2004
46.5

:
:
:
:
:
46.7
46.4
45.9
45.8
45.9

:
:
:
:
:
:
:
:
:
:

Old age and survivors benefits as a percentage of total social benefits

43.1
42.5
43.4
44.0
44.0
44.1
44.7
44.9
44.3
44.1

:
:
:
:
:
:
:
:
:
:

39.7
40.4
42.9
43.9
43.5
43.3
42.9
42.4
41.2
41.1

37.7
38.9
39.4
38.3
38.0
38.1
38.0
37.7
37.2
37.2

42.7
41.7
42.1
42.4
42.2
42.4
42.8
42.6
42.8
43.5

:
:
:
:
:
45.3
44.2
44.9
44.8
43.7

26.5
25.7
25.4
25.8
25.1
25.1
24.4
23.5
23.1
23.3

52.1
53.2
52.7
53.9
52.0
49.7
51.4
50.5
50.8
50.9

43.9
44.7
45.6
45.5
45.4
46.2
45.1
44.7
44.0
43.7

43.5
43.6
43.8
43.9
44.2
44.4
44.4
43.8
43.5
43.6

63.4
63.2
63.9
64.0
64.2
63.2
62.3
62.1
62.1
61.3

:
:
:
:
:
48.8
46.9
49.5
47.0
48.3

:
:
55.0
56.4
56.4
57.1
55.1
55.0
51.9
50.0

:
47.2
47.6
46.6
48.5
47.8
47.6
47.5
47.6
47.3

45.1
43.6
43.7
43.2
40.2
39.9
37.4
37.4
37.2
36.5

:
:
:
:
41.1
41.4
42.4
43.2
41.3
42.5

51.4
51.7
50.5
51.0
52.1
51.8
54.0
53.1
52.4
51.2

38.0
39.5
40.6
41.0
41.8
42.4
41.9
41.6
40.7
41.6

46.9
47.3
47.9
48.0
47.6
48.4
48.6
48.4
48.0
48.2

:
:
:
:
:
55.8
56.9
57.0
58.4
60.1

41.1
44.4
44.3
44.1
44.9
44.7
45.8
45.4
46.2
47.2

:
:
:
:
:
:
:
:
:
37.9

:
46.1
45.6
45.5
45.2
45.2
45.5
46.5
45.0
44.7

38.1
36.4
36.4
36.3
36.5
37.2
38.3
38.4
39.2
40.1

32.8
33.8
33.8
34.4
35.2
35.8
36.6
36.9
37.0
36.9

37.4
39.2
39.6
39.9
39.5
39.4
39.8
39.4
40.3
40.1

43.1
44.0
45.8
45.2
46.4
48.8
46.3
45.3
44.7
44.6

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

Note: EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

EU-
27

EU-
25

EA-
13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 11b
28.3
1995
1996
27.6
27.0
1997
27.2
1998
27.4
1999
27.8
2000
28.2
2001
28.1
2002
2003
28.2
2004
28.2

:
:
:
:
:
27.1
27.8
27.9
28.1
28.3

:
:
:
:
:
:
:
:
:
:

Sickness and health care benefits as a percentage of total social benefits

23.6
24.6
23.8
24.0
24.4
24.2
24.2
23.9
27.0
27.7

:
:
:
:
:
:
:
:
:
:

37.2
36.9
34.7
33.6
33.1
33.7
34.3
35.0
35.5
35.3

17.8
17.7
18.1
19.3
19.6
20.2
20.3
20.9
20.5
20.6

31.0
29.6
28.4
28.1
28.2
28.3
28.5
28.0
27.9
27.2

:
:
:
:
:
32.1
31.9
31.1
31.8
31.5

36.2
35.2
36.6
37.8
40.0
41.0
42.2
41.6
41.8
42.1

26.0
25.1
25.2
24.2
24.5
26.5
25.8
26.2
26.5
26.5

28.6
28.9
28.7
28.8
29.6
29.4
30.0
29.9
30.1
30.8

28.3
28.2
27.9
28.2
28.1
28.8
29.1
29.4
29.7
30.0

23.2
23.2
23.3
23.6
23.6
25.1
26.1
25.4
25.0
25.9

:
:
:
:
:
27.2
26.6
25.2
25.8
24.1

:
:
18.0
16.8
16.7
16.7
19.4
19.9
23.3
24.5

:
30.3
31.4
32.5
30.4
29.8
30.1
30.0
29.8
29.5

24.9
26.1
25.5
25.2
25.8
25.4
25.3
25.3
24.7
25.0

:
:
:
:
27.4
27.9
27.6
27.9
29.7
29.5

24.4
23.2
25.1
24.3
24.0
25.6
25.5
25.4
25.9
27.0

28.5
27.6
27.4
28.2
29.2
29.3
30.4
30.7
31.1
30.4

25.6
25.1
25.6
25.9
26.3
25.4
25.4
25.3
24.9
25.0

:
:
:
:
:
19.8
19.4
20.4
20.1
19.5

36.2
31.5
31.8
32.0
32.4
32.0
31.3
30.9
28.8
30.4

:
:
:
:
:
:
:
:
:
35.9

:
30.8
30.7
30.9
30.7
30.7
31.4
31.3
32.4
32.7

33.0
37.5
37.0
36.1
34.0
34.9
35.0
34.2
32.9
30.1

20.9
21.4
21.9
22.7
22.9
23.8
24.5
24.8
25.1
25.5

22.0
22.1
22.9
24.4
25.3
27.0
26.8
27.2
26.0
25.4

24.0
24.0
24.0
25.3
25.5
25.5
27.6
28.5
29.9
30.4

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

Note: EA-13 is calculated without the Slovenian data.

Source: Eurostat - European System of integrated Social Protection Statistics (ESSPROS)

EN 

211 

EN 

 
  
 
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 12

Inequality of income distribution (S80/S20 income quintile share ratio) (The ratio of total income received by the 20% of the population with the highest income (top quintile) to that received by the 20% of the 
population with the lowest income (lowest quintile). Income must be understood as equivalised disposable income.

:
:
:
:
:
3.7 i 
3.8 i 
3.8 i 
3.6 i 
4.0 i 
3.7 i 

:
:
:
:
:
:
:
:
:
:
4.6 s

4.6
4.0
3.7
3.6
3.6
3.5
3.6
:
:
:
3.8 b

2.9 i 
:
2.9 i 
:
3.0 i 
:
3.0 i 
: i 
3.6 b 
3.4
3.5

4.5
4.2
4.0
4.0
4.2
4.3
4.0
: i 
4.3 b 
4.0
4.0

:
:
:
:
:
:
3.4 i 
:
:
:
3.7 b 

:
:
:
4.6 s 
4.6 s 
4.5 s 
4.5 s 
: i 
4.6 s 
4.8 s 
4.9 s 
a ous

:
:
:
:
:
:
:
:
:
:
4.9 s
u os a

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Sou ces
1) EU-15 countries 
a) 1995-2001: European Community Household Panel, Users' Data Base version December 2003, except National Surveys for DK, SE (all), FR, FI, UK (2001), NL (2000,2001).     
b) From 2002 National Surveys except from 2003 BE, DK, EL, IE, LU and AT: EU-SILC; from 2004 ES, FR, IT, PT, FI and SE: EU-SILC and from 2005 DE, NL and UK: EU-SILC. 
2) New Member States 
a) National surveys until 2004, EE until 2003, BG, RO until 2005. 
b) EU-SILC from 2005, EE from 2004
3) Candidate countries: national surveys
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.

4.5
4.3
4.4
4.2
4.4
4.2
3.9 bi 
3.9 i 
3.8 i 
4.2 b 
4.0

5.9
6.0
6.5
5.9
5.7
5.4
5.5
5.1 bi 
5.1 i 
5.1 b 
5.4

:
:
: i 
:
:
:
: i 
: i 
4.1 i 
: i 
4.3 b 

:
:
:
:
:
6.3 i 
6.1 i 
6.1 i 
5.9 i 
7.2 b 
5.9

5.9
5.6
5.3
5.1
4.9
4.8
4.8
: i 
: i 
5.7 b 
5.6

5.1
5.1
5.0
5.2
4.9
4.7
4.5
: i 
5.0 b 
5.0
5.0

6.5
6.3
6.6
6.5
6.2
5.8
5.7
: i 
6.4 b 
5.9
5.8

:
:
:
:
:
5.5 i 
: i 
:
:
:
6.7 b 

:
:
:
:
:
5.0
4.9 i 
:
:
:
6.9 b 

4.3
4.0
3.6
3.7
3.9
3.7
3.8
: i 
4 b 
3.9
3.8

:
:
:
:
:
3.3 i 
3.1 i 
3.0 i 
3.3 i 
: i 
4.0 b 

:
:
:
:
:
4.6 i 
: i 
: i 
: i 
: i 
4.1 b 

4.2
4.4
3.6
3.6
3.7
4.1 ip 
4.0 ip 
4.0 ip 
4.0 ip 
: i 
4.0 b 

4.0
3.8
3.6
3.5
3.7
3.4
3.5
: i 
4.1 b 
3.8
3.8

:
:
:
:
:
4.7 i 
4.7 i 
:
:
:
6.6 b 

7.4
6.7
6.7
6.8
6.4
6.4
6.5
7.3 ip 
7.4 ip 
6.9 b 
6.9 b 

:
:
:
:
:
4.5 i 
4.6 i 
4.7 i 
4.6 i 
4.8 i 
4.9 i

:
:
:
:
:
3.2 i 
3.1 i 
3.1 i 
3.1 i 
: i 
3.4 b 

:
:
:
:
:
:
: i 
:
:
:
3.9 b 

:
3.0
3.0
3.1
3.4
3.3
3.7 bi 
3.7 i 
3.6 i 
3.5 b 
3.6

:
:
3.0 i 
:
3.1 i 
:
3.4 i 
3.3 bi 
: i 
3.3 b 
3.3

5.2
5.0
4.7
5.2
5.2
5.2 bi 
5.4 i 
5.5 i 
5.3 i 
: i 
5.8 b

:
:
:
:
:
:
: i 
: i 
4.6 i 
: i 
4.8 i

:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
: i 
10.8 i 
9.9 i 
: i 
10.0 i

EN 

212 

EN 

 
  
 
EU-27 EU-25 EA-13
Key indicator 13a

BE

BG

LU
At-risk-of-poverty rate before social transfers (The percentage of persons with an equivalised disposable income, before social transfers, below the at-risk-of-poverty threshold, which is set at 60% of the 
national median equivalised disposable income (after social transfers). Retirement and survivor's pensions are counted as income before transfers and not as social transfers.).

RO

MK

HR

HU

MT

DE

CY

UK

DK

EE

SK

ES

SE

FR

CZ

AT

PT

NL

EL

PL

LV

LT

SI

IE

FI

IT

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

2005

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

:
:
:
:
:
:
:
:
:
:
26 s

:
:
:
:
:
:
:
:
:
:
26 s

:
:
:
:
:
:
:
:
:
:
25 s

:
:
:
24 s 
24 s 
23 s 
24 s 
: i 
25 s 
26 s 

26 s 

:
:
:
25 s 
24 s 
24 s 
26 s 
: i 
26 s 
26 s 
27 s 

:
:
:
23 s 
23 s 
22 s 
24 s 
: i 
23 s 
24 s 
25 s 

:
:
:
:
:
:
:
:
:
:

24 s

:
:
:
:
:
:
:
:
:
:
25 s

:
:
:
:
:
:
:
:
:
:
23 s

27
27
26
25
24
23
23
: i 
29 b 
27 p

28

28
28
27
27
26
25
25
: i 
30 b 
28 p
29

26
25
25
24
23
22
21
: i 
28 b 
27 p
27

: 
: 
: 
: 
: 
18 i
19 i
17 i
16 i
18 i
17 i

:
:
:
:
:
19 i 
20 i 
18 i 
16 i 
20 i
19 i

: 
: 
: 
: 
: 
16 i
18 i
15 i
14 i
15 i
15 i

:
:
:
:
:
:
18 i 
:
:
:

:
:
:
:
:
:
29 i 
: i 
32 b 
30

22
22
22
22
21
20
21
:
:
:

:
:
:
:
:
26 i 
25 i 
25 i 
25 i 
26 b 

21 b 

30

23 b

24

:
:
:
:
:
:
19 i 
:
:
:
22 b 

:
:
:
:
:
:
18 i 
:
:
:
20 b 

:
:
:
:
:
:
: i 
: i 
33 b 
31
31

:
:
:
:
:
:
: i 
: i 
30 b 
29
28

23
23
23
22
21
22
: i 
:
:
:
24 b

21
21
21
21
20
19
: i 
:
:
:
22 b 

:
:
:
:
:
26 i 
26 i 
26 i 
26 i 
27 b 
25

:
:
:
:
:
25 i 
25 i 
25 i 
23 i 
25 b 
23

34
34
32
32
30
31
30
: i 
31 b 
33

32

35
35
34
34
32
33
32
: i 
33 b 
35
34

32
32
31
30
28
29
29
: i 
30 b 
31
30

23
22
23
22
22
22
23
: i 
24 b 
23

23

24
23
23
23
23
23
24
: i 
25 b 
24
24

22
22
22
21
22
22
21
: i 
23 b 
21
21

27
26
27
25
23
22
23
22 bi 
22 i 
25 b 

24

27
26
27
25
23
23
25
24 bi 
23 i 
26 b 
25

27
26
27
25
23
21
22
21 bi 
21 i 
24 b 
23

26
26
26
25
24
24
26 bi 
26 i 
24 i 
26 b 

26

27
27
26
25
25
25
27 bi 
27 i 
25 i 
27 b 
27

26
25
25
24
24
24
26 bi 
26 i 
24 i 
25 b 
25

23
23
22
21
21
21
22
: i 
: i 
24 b 

:
:
: i 
:
:
:
: i 
: i 
20 i 
: i 

:
:
:
:
:
22 i 
: i 
:
:
:

Total
:
:
:
:
:
23 i 
24 i 
:
:
:

25
24
22
23
24
23
23
: i 
23 b 
22

:
:
:
:
:
17 i 
17 i 
15 i 
17 i 
: i 

:
:
:
:
:
19 i 
: i 
: i 
: i 
: i 

23

22 b 

26 b 

26 b 

23

29 b 

21 b 

24
24
23
22
21
21
23
: i 
: i 
25 b 
25

22
22
22
20
20
20
21
: i 
: i 
22 b 
22

:
:
: i 
:
:
:
: i 
: i 
21 i 
: i 
23 b 

:
:
: i 
:
:
:
: i 
: i 
18 i 
: i 
20 b 

Females
:
:
:
:
:
24 i 
24 i 
:
:
:
27 b 

Males
:
:
:
:
:
23 i 
24 i 
:
:
:
25 b 

26
25
22
23
24
22
23
: i 
24 b 
23
23

24
23
22
23
24
23
24
: i 
23 b 
22
23

:
:
:
:
:
21 i 
: i 
:
:
:
27 b 

:
:
:
:
:
23 i 
: i 
:
:
:
24 b 

:
:
:
:
:
17 i 
17 i 
15 i 
17 i 
: i 
29 b 

:
:
:
:
:
16 i 
17 i 
15 i 
17 i 
: i 
30 b 

:
:
:
:
:
20 i 
: i 
: i 
: i 
: i 
22 b 

:
:
:
:
:
18 i 
: i 
: i 
: i 
: i 
20 b 

24
24
23
21
21
22 ip 
22 ip 
22 ip 
23 ip 
: i 

22 b 

24
24
24
22
22
23 ip 
23 ip 
23 ip 
24 ip 
: i 
22 b 

24
23
22
21
21
21 ip 
21 ip 
21 ip 
22 ip 
: i 
21 b 

24
25
24
24
23
22
22
: i 
25 b 
25

:
:
:
:
:
30 i 
31 i 
:
:
:

27
27
27
27
27
27
24
26 ip 
26 ip 
27 b 

24

30 b 

26

27
27
26
27
26
25
25
: i 
26 b 
26
25

22
22
22
22
21
20
19
: i 
23 b 
24
23

:
:
:
:
:
30 i 
30 i 
:
:
:
29 b 

:
:
:
:
:
31 i 
31 i 
:
:
:
31 b 

29
28
29
28
28
28
24
: i 
: i 
28 b 
26

26
26
26
26
27
26
25
: i 
: i 
25 b 
25

: 
: 
: 
: 
: 
21 i
22 i
23 i
22 i
23 i
24 i

:
:
:
:
:
22 i 
23 i 
23 i 
23 i 
24 i
24 i

: 
: 
: 
: 
: 
21 i
22 i
23 i
22 i
23 i
23 i

:
:
:
:
:
18 i 
17 i 
16 i 
16 i 
: i 

:
:
:
:
:
:
: i 
:
:
:

:
23
23
22
21
19
29 bi 
28 i 
28 i 
29 b 

26 b 

22 b 

28

:
:
:
:
:
18 i 
18 i 
18 i 
18 i 
: i 
27 b 

:
:
:
:
:
17 i 
16 i 
15 i 
15 i 
: i 
25 b 

:
:
:
:
:
:
: i 
:
:
:
22 b 

:
:
:
:
:
:
: i 
:
:
:
22 b 

:
24
24
23
22
21
30 bi 
29 i 
29 i 
29 b 
29

:
23
23
21
19
18
28 bi 
27 i 
27 i 
28 b 
27

:
:
:
:
:
:
17 i 
29 bi 
: i 
30 b 

29

:
:
:
:
:
:
: i 
31 bi 
: i 
33 b 
30

:
:
:
:
:
:
: i 
26 bi 
: i 
28 b 
27

32
29
30
30
30
29 bi 
28 i 
28 i 
29 i 
: i 

31 b 

35
32
33
33
32
32 bi 
30 i 
30 i 
30 i 
: i 
32 b 

29
27
27
26
27
26 bi 
27 i 
26 i 
28 i 
: i 
29 b 

:
:
:
:
:
:
: i 
: i 
31 i 
: i 

31 i

:
:
:
:
:
:
: i 
: i 
33 i 
: i 
34 i

:
:
:
:
:
:
: i 
: i 
29 i 
: i 
29 i

:
:
:
:
:
:
:
:
:
:

:

:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:

Sources: Eurostat - Various. 
1) EU-15 countries 
a) 1995-2001: European Community Household Panel, Users' Data Base version December 2003, except National Surveys for DK, SE (all), FR, FI, UK (2001), NL (2000,2001).     
b) From 2002 National Surveys except from 2003 BE, DK, EL, IE, LU and AT: EU-SILC; from 2004 ES, FR, IT, PT, FI and SE: EU-SILC and from 2005 DE, NL and UK: EU-SILC.
2) New Member States 
a) National surveys until 2004, EE until 2003, BG, RO until 2005. 
b) EU-SILC from 2005, EE from 2004
3) Candidate countries: national surveys
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.

TR

:
:
:
:
:
:
: i 
31 i 
31 i 
: i 

28 i

:
:
:
:
:
:
: i 
31 i 
32 i 
: i 
29 i

:
:
:
:
:
:
: i 
30 i 
29 i 
: i 
26 i

EN 

213 

EN 

 
  
 
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 13b

At-risk-of-poverty rate after social transfers (The percentage of persons with an equivalised disposable income below the at-risk-of-poverty threshold, which is set at 60% of the national median equivalised 
disposable income.)

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

:
:
:
:
:
:
:
:
:
:
16 s

:
:
:
:
:
:
:
:
:
:
17 s

:
:
:
:
:
:
:
:
:
:
15 s

:
:
:
15 s 
16 s 
16 s 
16 s 
: i 
15 s 
16 s 
16 s 

:
:
:
16 s 
17 s 
17 s 
17 s 
: i 
16 s 
17 s 
17 s 

:
:
:
14 s 
15 s 
15 s 
15 s 
: i 
14 s 
15 s 
15 s 

:
:
:
:
:
:
:
:
:
:
15 s

:
:
:
:
:
:
:
:
:
:
16 s

:
:
:
:
:
:
:
:
:
:
14 s

16
15
14
14
13
13
13
: i 
15 b 
15
15

17
17
15
15
14
14
15
: i 
16 b 
16 p
15

15
14
13
12
11
12
12
: i 
14 b 
14 p
14

:
:
:
:
:
14 i 
16 i 
14 i 
14 i 
15 i 
14 i 

:
:
:
:
:
15 i 
17 i 
15 i 
16 i 
17 i 
15 i 

:
:
:
:
:
13 i 
14 i 
12 i 
12 i 
13 i 
13 i

:
:
:
:
:
:
8 i 
:
:
:
10 b 

:
:
:
:
:
:
8 i 
:
:
:
11 b 

:
:
:
:
:
:
7 i 
:
:
:
10 b 

10 i 
:
10 i 
:
10 i 
:
10 i 
: i 
12 b 
11
12

:
:
:
:
:
:
: i 
: i 
12 b 
11
12

:
:
:
:
:
:
: i 
: i 
11 b 
11
12

15
14
12
11
11
10
11
:
:
:
12 b 

16
16
13
12
12
11
: i 
:
:
:
13 b

13
12
11
10
10
10
: i 
:
:
:
11 b

:
:
:
:
:
18 i 
18 i 
18 i 
18 i 
20
18

:
:
:
:
:
19 i 
19 i 
19 i 
20 i 
21 b 
20

:
:
:
:
:
17 i 
17 i 
17 i 
17 i 
19 b 
17

19
19
19
19
19
20
21
: i 
20 b 
21
20

20
21
20
20
20
21
23
: i 
21 b 
23
21

17
18
18
18
17
19
20
: i 
19 b 
19
19

22
21
21
21
21
20
20
: i 
21 b 
20
20

22
21
22
22
21
20
22
: i 
21 b 
21
21

21
21
21
20
20
19
19
: i 
20 b 
19
18

19
18
20
18
19
18
19
19 bi 
19 i 
20 b 
20

19
18
21
18
19
19
20
21 bi 
20 i 
21 b 
21

19
18
20
18
18
17
17
18 bi 
18 i 
19 b 
19

15
15
15
15
15
16
13 bi 
12 i 
12 i 
13 b 
13

16
16
16
15
16
16
13 bi 
13 i 
13 i 
14 b 
14

15
14
14
14
15
15
12 bi 
12 i 
12 i 
13 b 
12

20
20
19
18
18
18
19
: i 
: i 
19 b 
19

21
21
20
19
18
19
20
: i 
: i 
20 b 
21

19
19
19
17
18
18
19
: i 
: i 
18 b 
17

:
:
: i 
:
:
: i 
: i 
: i 
15 i 
: i 
16 b 

:
:
: i 
:
:
: i 
: i 
: i 
17 i 
: i 
18 b 

:
:
: i 
:
:
: i 
: i 
: i 
14 i 
: i 
15 b 

Total
:
:
:
:
:
17 i 
17 i 
:
:
:
21 b 
F emales
:
:
:
:
:
17 i 
17 i 
:
:
:
21 b 
Males
:
:
:
:
:
17 i 
18 i 
:
:
:
20 b 

12
11
11
12
13
12
12
: i 
11 b 
12
13

13
11
12
13
13
12
13
: i 
12 b 
13
13

11
11
11
12
12
12
12
: i 
11 b 
12
13

:
:
:
:
:
16 i 
: i 
:
:
:
19 b 

:
:
:
:
:
16 i 
: i 
:
:
:
20 b 

:
:
:
:
:
17 i 
: i 
:
:
:
18 b 

:
:
:
:
:
11 i 
11 i 
10 i 
12 i 
: i 
13 b 

:
:
:
:
:
12 i 
12 i 
10 i 
12 i 
: i 
13 b 

:
:
:
:
:
11 i 
11 i 
9 i 
12 i 
: i 
14 b 

:
:
:
:
:
15 i 
: i 
: i 
: i 
: i 
15 b 

:
:
:
:
:
15 i 
: i 
: i 
: i 
: i 
16 b 

:
:
:
:
:
15 i 
: i 
: i 
: i 
: i 
14 b 

11
12
10
10
11
11 ip 
11 ip 
11 ip 
12 ip 
: i 
11 b 

12
12
11
10
11
11 ip 
12 ip 
12 ip 
12 ip 
: i 
11 b 

11
11
10
10
10
10 ip 
11 ip 
11 ip 
12 ip 
: i 
11 b 

13
14
13
13
12
12
12
: i 
13 b 
13
12

15
16
14
15
14
14
14
: i 
14 b 
14
13

12
12
11
11
10
9
9
: i 
12 b 
11
11

:
:
:
:
:
16 i 
16 i 
:
:
:
21 b 

:
:
:
:
:
16 i 
15 i 
:
:
:
20 b 

:
:
:
:
:
16 i 
16 i 
:
:
:
21 b 

23
21
22
21
21
21
20
20 ip 
19 ip 
20 b 
19

24
22
23
22
22
22
20
: i 
: i 
22 b 
20

21
20
20
19
19
19
20
: i 
: i 
19 b 
19

:
:
:
:
:
17 i 
17 i 
18 i 
17 i 
18 i 
18 i 

:
:
:
:
:
18 i 
17 i 
18 i 
18 i 
18 i 
18 i

:
:
:
:
:
17 i 
17 i 
18 i 
17 i 
18 i 
18 i

:
:
:
:
:
11 i 
11 i 
10 i 
10 i 
: i 
12 b 

:
:
:
:
:
12 i 
12 i 
11 i 
11 i 
: i 
14 b 

:
:
:
:
:
11 i 
10 i 
9 i 
9 i 
: i 
11 b 

:
:
:
:
:
:
: i 
:
:
:
13 b 

:
:
:
:
:
:
: i 
:
:
:
13 b 

:
:
:
:
:
:
: i 
:
:
:
13 b 

:
8
8
9
11
11
11 bi 
11 i 
11 i 
11 b 
12

:
9
9
11
12
13
12 bi 
12 i 
12 i 
11 b 
13

:
8
8
8
9
9
10 bi 
11 i 
11 i 
10 b 
11

:
:
8 i 
:
8 i 
: i 
9 i 
11 bi 
: i 
11 b 
9

:
:
:
:
:
: i 
: i 
12 bi 
: i 
12 b 
10

:
:
:
:
:
: i 
: i 
10 bi 
: i 
10 b 
9

20
18
18
19
19
19 bi 
18 i 
18 i 
18 i 
: i 
19 b

22
20
19
21
21
21 bi 
19 i 
19 i 
19 i 
: i 
19 b 

19
16
16
17
18
16 bi 
17 i 
17 i 
17 i 
: i 
19 b

:
:
:
:
:
: i 
: i 
: i 
18 i 
: i 
18 i

:
:
:
:
:
: i 
: i 
: i 
19 i 
: i 
20 i

:
:
:
:
:
: i 
: i 
: i 
17 i 
: i 
16 i

:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
: i 
25 i 
26 i 
: i 
26 i

:
:
:
:
:
:
: i 
25 i 
26 i 
: i 
27 i

:
:
:
:
:
:
: i 
25 i 
25 i 
: i 
26 i

Sources: Eurostat - Various. 
1) EU-15 countries 
a) 1995-2001: European Community Household Panel, Users' Data Base version December 2003, except National Surveys for DK, SE (all), FR, FI, UK (2001), NL (2000,2001).     
b) From 2002 National Surveys except from 2003 BE, DK, EL, IE, LU and AT: EU-SILC; from 2004 ES, FR, IT, PT, FI and SE: EU-SILC and from 2005 DE, NL and UK: EU-SILC 
2) New Member States 
a) National surveys until 2004, EE until 2003, BG, RO until 2005. 
b) EU-SILC from 2005, EE from 2004
3) Candidate countries: national surveys
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.

EN 

214 

EN 

 
  
 
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 14a

People aged 18-59 living in jobless households
Share of persons/women/men aged 18-59 who are living in households where no-one works. Students aged 18-24 who live in households composed solely of students of the same age class are counted neither in the numerator 
nor in the denominator

:
:
:
:
:
:

:
:
:
:
:
:

10.2 e  10.1 e 
10.3 e  10.2 e 
10.3 e  10.2 e 
10.4 i 
10.3 i 
10.3 e  10.2 e 

:
:
:
:

14.1
14.1
14.3
14.4

10.2 e  13.0 b 
9.6 e 
9.4 b 
9.4 e 
9.5 e 
9.6 i 
9.5 e 

12.4
13.8
14.2
14.4
13.7
13.5

9.8 e
9.3 e 

9.8 e
9.3 e

9.3 e
8.8 e 

14.3
12.5

:
:
:
:

:
:
:
:
:
:

16.2
16.0
16.3
16.3

:
:
:
:
11.5 e  14.8 b 
:
10.9 e 
:
11.4 e  11.4 e  10.7 b 
11.6 e  11.4 e  10.5 e 
11.4 e  11.3 e  10.6 e 
11.5 i 
10.6 i 
11.4 i 
11.2 e  11.2 e  10.3 e 
10.2 e
10.8 e
10.8 e
9.7
10.3 e  10.3 e

14.5
16.2
16.6
16.2
16.0
15.4
16.4
14.4

:
:
:
:
:
:
8.9 e 
9.1 e 
9.1 e 
9.4 i 
9.3 e 
8.8 e
8.3 e

:
:
:
:
:
:
8.8 e 
8.9 e 
9.0 e 
9.3 i 
9.2 e 
8.8 e 
8.2 e

:
:
:
:

12.1
12.3
12.4
12.4

8.9 e  11.2 b 
8.3 e 
8.1 b 
8.2 e 
8.5 e 
8.7 i 
8.8 e 
8.5 e
8 e

10.4
11.5
11.9
12.7
11.3
11.6
12.3
10.7

:
:
:
:
:
15.5
17.3 b 
16.6
15.3
13.7
13.0

11.6
10.0

:
:
:
:
:
16.3
17.8 b 
17.0
15.8
14.2
13.5
12.0
9.9

:
:
:
:
:
14.6
16.8 b 
16.1
14.7
13.2
12.6
11.1
10.1

:
:
5.3
6.2
7.2
7.8
7.9
7.3
7.7
8.0
7.4

7.3
6.5

:
:
6.6
7.7
8.8
9.5
9.5
9.1
9.7
9.6
9.0
8.8
8.1

:
:
3.9
4.6
5.6
6.1
6.2
5.6
5.8
6.4
5.8
5.8
4.9

:
:
:
:
:
:
:
7.6
8.6
8.5
7.7

6.9
:

:
:
:
:
:
:
:
8.0
9.3
8.8
7.8
7.3
:

:
:
:
:
:
:
:
7.2
7.8
8.3
7.7
6.4
:

10.6
10.9
11.4
11.1
10.5
9.7
9.7
10.0
10.6
11.1
11.0 p 

10.5 p
9.5

11.7
11.8
12.4
12.0
11.4
10.7
10.5
10.7
11.2
11.4
11.2 p 
10.7 p
9.9 p

9.5
9.9
10.5
10.1
9.5
8.8
8.9
9.4
10.0
10.8
10.9 p 
10.3 p
9.2 p

:
:
9.6
8.7
10.4
9.6
11.0
10.8
10.9
9.5
8.5

6.0
6.0

:
:
9.9
8.9
10.4
9.6
11.1
10.9
10.5
8.7
7.0
5.8
5.7

:
:
9.3
8.5
10.5
9.7
10.9
10.6
11.3
10.2
10.2
6.1
6.3

13.5
12.9
12.5
:
9.8
8.6
8.8
8.5
8.9
8.6
8.4

7.9
7.8

14.6
14.1
13.6
:
11.1
9.8
10.2
9.7
10.2
10.1
9.8
9.3
5.7

12.5
11.8
11.5
:
8.5
7.4
7.4
7.3
7.6
7.2
7.2
6.5
6.4

10.3
9.8
10.0
9.6
9.6
9.2
8.8
8.9
8.5
8.5
8.5

8.1
8.0

12.9
12.4
12.5
12.1
12.1
11.7
11.2
11.2
10.8
10.7
10.7
10.1
9.1

7.5
7.1
7.2
7.0
7.0
6.7
6.4
6.5
6.2
6.2
6.4
6.1
6.0

12.5
12.1
11.3
10.2
8.5
7.5
7.4
7.3
7.2
7.3
6.7

6.3
6.0

13.2
12.8
12.1
11.0
9.3
8.2
8.3
8.0
7.8
7.9
7.2
6.8
10.0

11.9
11.4
10.5
9.4
7.7
6.8
6.6
6.6
6.5
6.7
6.2
5.8
5.6

11.0
10.9
11.4
11.3
11.3
10.7
10.3
10.4
10.5
10.8
10.7

10.9
10.9 p 

12.1
12.1
12.6
12.5
12.5
11.9
11.6
11.8
11.7
12.0
11.8
12.0
12.0 p 

9.9
9.7
10.2
10.1
10.1
9.4
8.9
9.1
9.4
9.5
9.6
9.9
9.7 p

11.9
12.0
12.2
12.0
11.7
11.2
10.8
10.2
9.7
9.1
9.5

9.2
9.1

13.9
13.8
14.1
13.8
13.5
13.0
12.4
11.8
11.3
10.4
10.8
10.6
10.3

9.9
10.1
10.3
10.2
9.8
9.4
9.1
8.6
8.1
7.9
8.3
7.8
7.8

Total
:
:
:
10.4
8.8
9.2
10.0
10.5 b  9.1 b 

:
:
:
14.0
14.9 b 
15.0
12.8

8.7
7.8
8.1

6.8
7.1

7.4
8.1
6.6

7.0
6.3

Females

:
:
:
14.5
16.4 b 
15.4
13.2

:
:
:
11.2
8.5
8.6
10.0
10.3 b  9.7 b 

8.6
8.4
7.6
6.2
7.7

7.4
8.0
6.4
6.9
6.3
Males

:
:
:
13.4
13.4 b 
14.6
12.3

:
:
:
9.5
9.0
9.8
10.1
10.7 b  8.5 b 

8.9
7.1
8.7
7.5
6.4

7.4
8.3
6.9
7.2
6.4

6.5
7.6
7.0
7.3
6.7
6.9
6.7
6.3
7.5 i 
7.1
6.7

7.1
7.5

8.1
9.6
8.9
9.0
8.4
8.8
8.1
7.0
9.0 i 
8.5
8.1
8.9
8.6

5.0
5.6
5.2
5.5
5.1
5.0
5.3
5.6
6.0 i 
5.7
5.4
5.4
6.3

:
15.8
15.7
15.8
14.2
13.5
13.2
13.0
11.6 b 
11.9
12.3

11.6
11.8

:
17.5
17.1
17.1
15.6
14.6
14.3
14.0
12.2 b 
12.7
13.1
12.6
12.9

:
14.1
14.1
14.5
12.8
12.4
12.0
12.0
10.9 b 
11.1
11.6
10.6
10.7

:
:
:
:
:
7.4
7.8
7.2
7.9
8.6
8.2

6.7
6.9

:
:
:
:
:
8.8
9.9
8.6
9.7
10.4
9.9
8.2
8.3

:
:
:
:
:
6.0
5.7
5.8
6.2
6.8
6.5
5.2
5.6

:
:
:
:
:
5.6
4.9
5.3
5.2
5.0
5.2

4.9
4.5

:
:
:
:
:
7.1
6.3
6.5
6.1
6.1
6.2
5.9
4.9

:
:
:
:
:
3.9
3.4
3.9
4.3
3.8
4.2
3.7
4.1

11.0
10.2
8.9
8.8
7.8
7.6
6.9
6.7
8.0
8.0
8.0

7.4
6.5

12.5
11.6
10.5
10.6
9.4
9.4
8.5
8.1
9.3
9.3
9.0
8.6
7.7

9.5
8.8
7.4
7.1
6.3
5.8
5.4
5.3
6.7
6.7
6.9
6.2
5.4

7.0
8.1
7.7
8.4
8.2
8.3
7.9
7.5
7.4
8.8 i 
8.7

8.8
7.6

8.4
9.6
9.1
10.0
9.8
10.0
9.6
8.8
8.6
10.0 i 
9.6
9.8
8.7

5.6
6.7
6.3
6.9
6.5
6.5
6.2
6.2
6.1
7.6 i 
7.7
7.8
6.5

:
:
9.8
:
:
:
13.8
15.1
14.8
15.8
15.3

13.5
11.7

:
:
10.7
:
:
:
14.7
16.1
15.9
16.8
16.6
14.6
12.8

:
:
8.8
:
:
:
12.9
14.1
13.7
14.8
14.0
12.3
10.5

5.9
6.3
5.9
5.1 b 
4.7
4.6
4.3
4.6
5.5
5.3
5.5

5.8
5.8

6.8
7.3
7.0
6.1 b 
5.3
5.1
4.9
5.2
6.1
5.7
5.8
6.4
6.1

5.0
5.1
4.8
4.0 b 
4.1
4.1
3.7
3.9
4.8
5.0
5.1
5.3
5.4

:
:
6.8
7.3
7.8
8.4
8.7
11.3 b 
11.1
11.1
10.4

9.7
9.6

:
:
7.8
8.3
8.6
9.3
9.6
12.5 b 
12.4
11.7
11.3
10.6
10.7

:
:
5.8
6.3
7.0
7.4
7.7
10.1 b 
9.8
10.4
9.4
8.8
8.6

:
8.8
8.7
8.3
9.6
9.0
8.2
8.0
8.7
7.5
6.7

7.2
6.0

:
9.7
9.4
9.0
10.5
9.6
9.4
8.9
9.6
8.0
7.1
7.8
6.9

:
7.9
8.0
7.5
8.7
8.4
7.1
7.0
7.8
7.0
6.3
6.6
5.1

:
:
:
9.0
9.8
10.9
10.0
10.9
10.1
10.8
10.2

9.6
8.8

:
:
:
9.9
10.9
11.4
10.5
11.4
10.9
11.6
10.9
10.2
9.6

:
:
:
8.1
8.8
10.3
9.6
10.4
9.3
10.0
9.5
9.0
8.1

:
:
:
:
:
:
:
:
10.9
11.0
10.5

9.5
:

:
:
:
:
:
:
:
:
10.3
10.9
10.0
9.0
:

:
:
:
:
:
:
:
:
11.6
11.2
11.0
10.1
:

:
:
:
:
:
:
:
:
:
:
:

:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

13.7
13.5
12.9
12.5
11.8
11.4
11.2
11.3
10.9
11.0
11.0

10.7
10.9

15.7
15.5
15.0
14.6
13.9
13.5
13.2
13.3
12.9
13.0
12.8
12.5
12.7

11.8
11.6
10.9
10.3
9.6
9.1
9.1
9.2
8.9
9.0
9.2
8.8
8.9

:
:
:
:
:
:
:
14.0
13.2
11.2
12.5

12.9
:

:
:
:
:
:
:
:
15.8
14.4
12.0
13.6
14.0
:

:
:
:
:
:
:
:
12.2
12.0
10.3
11.5
11.7
:

:
:
:
:
:
:
:
:
:
:
:

:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:

:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:
:

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

2006
2007

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007

Source: Eurostat - European Union Labour Force Survey

EN 

215 

EN 

 
  
 
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 14b
:
1995
:
1996
:
1997
1998
:
1999
2000
2001
2002
2003
2004

:
:
:
:
:
:
:
:
:
:
:
:
9.6 e 
9.6 e 
10.0 e  9.9 e 
9.8 e 
9.9 e 
9.8 i 
10.0 i 

8.6 e  11.3 b 
8.1 e 
7.8 b 
8.1 e 
8.3 e 
8.3 i 

10.8
12.9
13.8
13.9
13.2

12.3
12.3
11.8
12.9

2005

2006
2007

9.7 e 

9.6 e 

8.1 e 

9.6 e
9.4 e 

9.5 e
9.3 e

7.8 e
7.7 e 

12.9

13.5
13.5

Children aged 0-17 living in jobless households
Share of persons aged 0-17 who are living in households where no-one works
:
:
:
:
:
4.8
3.9
3.9
3.4
2.6

17.0
16.3
15.7
:
11.7
10.2
10.4
10.8
11.8
11.8

11.5
11.2
10.5
9.0
7.3
6.5
6.4
6.6
6.0
6.3

:
:
:
8.9
10.2
8.6
11.2
10.1
9.0
9.6

9.2
9.6
10.1
9.8
9.9
9.4
9.2
9.6
9.4
9.5

8.3
9.1
10.2
10.0
9.5
9.0
8.9
9.3
10.3
10.9

8.3
8.6
8.5
8.2
8.3
7.6
7.0
7.2
7.0
5.7

6.0
5.1
5.2
5.0
5.2
5.3
5.3
5.1
4.6
4.5

:
:
:
:
:
:
:
5.7
5.7
6.0

:
:
5.1
6.1
7.2
8.0
8.0
7.6
8.4
9.0

8.1

8.2
7.9

5.7

5.0
:

10.7 p 

10.3 p
9.3 p

9.1

8.2
7.3

12.0

11.3
11.2

4.1

3.6
3.9

5.4

5.1
5.0

9.5

9.5
9.8

5.6

5.4
5.8

3.5

3.9
3.7

:
:
:
:
:
:
19.0
18.7
16.6
15.6

14.5

14.5
12.9

:
:
:
10.0
12.0 b 
13.0
10.7
10.6 b 
7.2
7.2

8.3

7.1
8.6

:
:
:
:
:
:
:
8.4
6.1
6.5

6.2

5.3
6.9

3.7
4.5
4.2
4.0
4.0
4.1
3.4
2.8
3.9 i 
3.4

2.7

3.7
4.0

:
15.0
14.9
15.6
15.5
13.5
13.5
14.3
12.6 b 
13.2

14.2

13.3
14.0

:
:
:
:
:
7.9
7.9
7.6
8.0
9.2

8.9

8.2
8.4

9.7
8.9
7.5
7.5
6.9
8.0
6.0
6.0
7.0
7.0

7.0

6.2
5.9

3.7
4.9
4.3
4.4
4.2
4.3
4.1
4.4
4.3
5.6 i 

6.3

7.2
6.1

:
:
:
:
:
:
:
:
:
:

:

11.2
9.5

5.1
5.1
5.2
4.6 b 
4.5
3.9
3.6
4.2
5.0
4.3

4.3

4.7
4.8

:
:
6.9
7.5
7.3
7.2
6.8
9.8 b 
10.2
11.1

10.4

10.0
9.4

:
3.8
3.2
3.5
4.1
4.0
3.8
3.8
4.0
3.8

2.7 u 

3.6
2.5

:
:
:
9.3
10.6
12.5
9.3 u 
12.1
11.8
12.8

13.8

11.8
10.5

:
:
:
:
:
:
:
:
5.7
5.7

6.6

4.9
:

:
:
:
:
:
:
:
:
:
:

:

:
:

20.4
20.1
18.9
18.9
18.4
17.0
16.9
17.4
17.0
16.8

16.5

16.2
16.7

:
:
:
:
:
:
:
10.3
10.4
7.4

8.7

9.8
:

:
:
:
:
:
:
:
:
:
:

:

:
:

:
:
:
:
:
:
:
:
:
:

:

:
:

Source: Eurostat - European Union Labour Force Survey

EN 

216 

EN 

 
  
 
EU-
27

EU-
25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 15a
18.5
8/1998
19.9
11/1999
20.8
11/2000
12/2001
20.8
11/2002
21.5
22.9
11/2003
24.1
11/2004
11/2005
24.4
24.8
11/2006
25.5
8/2007

16.8
18.2
18.5
19.6
20.3
21.1
22.1
22.3
22.6
23.1

17.4
18.9
19.3
19.7
20.4
21.4
22.4
22.8
23.1
23.6

Percentage of women in the lower or single House of the national or federal Parliament

12.7
23.3
23.3
23.3
23.3
35.3
34.7
34.7
34.7
34.7

10.8
10.8
10.8
26.2
26.2
26.3
26.3
22.1
22.1
22.1

15.0
15.0
15.0
15.0
17.0
17.0
17.0
17.0
15.5
15.5

37.4
37.4
37.4
38.0
38.0
38.0
38.0
36.9
36.9
36.9

26.2
30.9
30.9
31.1
32.2
32.2
32.8
31.8
31.6
31.6

10.9
17.8
17.8
17.8
17.8
18.8
18.8
18.8
18.8
21.8

12.0
12.0
12.0
12.0
13.3
13.3
13.3
13.3
13.3
13.3

6.3
6.3
8.7
8.7
8.7
8.7
14.0
13.0
13.0
13.0

24.7
21.6
28.3
28.3
28.3
28.3
36.0
36.0
36.0
36.0

10.9
10.9
10.9
10.9
12.1
12.2
12.2
12.2
12.2
18.5

11.1
11.1
11.1
9.8
9.8
11.5
11.5
11.5
17.3
17.3

5.4
5.4
7.1
10.7
10.7
10.7
10.7
16.1
14.3
14.3

9.0
17.0
17.0
17.0
18.0
21.0
21.0
21.0
19.0
19.0

17.5
17.5
10.6
10.6
10.6
10.6
20.6
22.0
24.8
24.8

20.0
16.7
16.7
16.7
16.7
16.7
20.0
23.3
23.3
23.3

8.3
8.3
8.3
8.3
9.1
9.8
9.8
9.1
10.4
10.4

5.8
9.2
9.2
9.2
9.2
7.7
9.2
9.2
9.2
9.2

36.0
36.0
36.0
36.0
34.0
36.7
36.7
36.7
36.7
36.7

26.2
26.8
26.8
26.8
33.9
33.9
33.9
33.9
32.2
32.2

13.0
13.0
13.0
20.2
20.2
20.2
20.2
20.4
20.4
20.4

13.0
18.7
17.4
18.7
19.1
19.1
19.1
21.3
21.3
21.3

7.3
7.3
7.3
10.7
10.7
10.7
11.4
11.2
11.2
11.2

7.8
7.8
12.2
12.2
12.2
12.2
12.2
12.2
12.2
12.2

14.7
12.7
14.0
14.0
17.3
19.3
16.7
16.7
20.0
19.3

33.5
37.0
36.5
36.5
36.5
37.5
37.5
37.5
38.0
42.0

40.4
42.7
42.7
42.7
45.0
45.3
45.3
45.3
47.3
47.3

18.2
18.4
18.4
17.9
17.9
17.9
17.9
19.7
19.7
19.7

7.9
7.9
20.5
20.5
20.5
17.8
17.8
21.7
21.7
21.7

3.3
7.5
6.7
6.7
17.5
18.3
18.3
19.2
28.3
28.3

2.4
4.2
4.2
4.2
4.4
4.4
4.4
4.4
4.4
9.1

Note: The EU-27, EU-25 and EA-13 figures are averages of the percentages of the corresponding Member States. 

Source: The Inter-Parliamentary Union (http://www.ipu.org/wmn-e/classif.htm).

EU-
27

EU-
25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 15b
.
1979
.
1984
.
1989
.
1994
.
1999
:
2004
32.9
10/2007

.
.
.
.
.
29.5 i
30.8

.
.
.
.
.
.
31.2

Percentage of women in the European Parliament

8.3
16.6
12.5
32.0
29.0
29.2
33.3

.
.
.
.
.
.
44.4

.
.
.
.
.
16.7
20.8

31.2
37.5
37.5
43.7
37.5
35.7
42.9

14.8
19.7
30.8
34.3
37.3
31.3
32.3

.
.
.
.
.
33.3
50.0

13.3
13.3
6.6
26.6
26.6
38.5
38.5

.
8.3
4.1
12.0
16.0
29.2
33.3

.
.
15.0
31.2
34.3
33.3
32.1

22.2
21.0
23.4
28.7
40.2
39.7
43.6

13.5
8.6
11.1
12.6
11.4
17.9
16.7

.
.
.
.
.
0.0
0.0

.
.
.
.
.
22.2
22.2

.
.
.
.
.
38.5
38.5

16.6
50.0
50.0
33.3
33.3
50.0
50.0

.
.
.
.
.
33.3
37.5

.
.
.
.
.
0.0
0.0

20.0
28.0
28.0
32.2
35.4
44.4
51.9

.
.
.
.
38.0
33.3
27.8

.
.
.
.
.
13.0
14.8

.
.
12.5
8.0
20.0
25.0
25.0

.
.
.
.
.
.
34.3

.
.
.
.
.
42.9
42.9

.
.
.
.
.
28.6
35.7

.
.
.
.
43.8
35.7
35.7

.
.
.
.
40.9
57.9
47.4

14.8
12.3
14.8
18.3
24.1
24.4
25.6

.
.
.
.
.
.
.

.
.
.
.
.
.
.

.
.
.
.
.
.
.

Notes: 1) The EU-15 and Euro-zone figures are percentages of women among all members of EP from the corresponding member states. In January 2005 the average of the percentages of the 15 old member states was 32.6%  and the average of the percentages of Euro-zone member states was 
32.2%. 2) The percentages of 1979, 1984, ..., 2004 are based on the situation after the elections of each legislature.

Sources: The European Parliament' s press service and web site (http://www.europarl.eu.int/whoswho/default.htm).

EN 

217 

EN 

 
  
 
EU-27 EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 16

1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

17 s
17 s
17 s
16 s
17 s
16 s
16 s
16 s
16 s
15 s
15 s
15 s

17 s
17 s
17 s
16 s
17 s
16 s
16 s
16 s
16 s
15 s
15 s
15 s

17 s
17 s
16 s
16 s
16 s
15 s
16 s
16 s
16 s
16 s
15 s
15 s

Gender pay gap in unadjusted form (Difference between men's and women's average gross hourly earnings as a percentage of men's average gross hourly earnings. The population consists of all 
paid employees aged 16-64 that are 'at work 15+ hours per week')

13
12
10
10
9
11
13
12
:
:
6b
7

:
:
:
:
:
:
:
22 r
21 r
18 r
16 r
16

:
:
21
21
25
22
22
20
19
19
19
19

11
15
15
13
12
14
15
15
18 b
18
17
18

21
21
21
21
22
19
21
21
22 b
23
23
22

29
27
27
28
26
26
25
24
24
24
24
25

19
20
21
19
20
22
19
17
:
14 b
11 p
9 p

13
17
15
13
12
13
15
18
17
11b
10
9 p

10
13
14
14
16
14
15
17
21 b
18
15
13 p

13
13
13
12
12
12
13
14
13
12b
12
12

8
8
8
7
7
8
6
6
:
:
7 p
9

33
29
28
27
26
27
26
26
25
25
25
25

:
:
:
:
20
20
20
16
16
16
15
17

:
27
22
23
22
16
16
16
16
17
16
15

20
19
19
19
18
17
15
16
17
15
14
14

:
22
23
24
23
21
21
20
16
12 r
14 r
11

:
:
:
:
:
:
11
9
6
4
4
4

23
23
23
22
21
21
21
19
19
18
19
18

:
22
20
22
21
21
20
20
:
17 b
18
18

:
:
:
:
:
15

12
11
11
10
10

10
5
6
7
6
5
8
10
8
9
5 b
9 

21
21
24
24
20
17
17
18
17
18
14 b
13

:
14
15
14
11
14
12
11
9
:
8 p
8 p

:
:
:
:
:
23
22
23
27
23
24
24

:
:
17
18
19
19
17
17
20 b
20
20
20

16
15
17
17
18
17
18
18
17
16
17
16

28
26
24
21
24
22
21
21
23b
22
22
20 p

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

Notes: 1) EU-27 EU-25 and EU-15 estimates are population-weighted averages of the latest available national values adjusted, where possible, to take into account a change in the data source.
2) CZ – Figures are based on median earnings of employees working 30 or more planned hours per week.
3) DK - A change of data source from 2002 is estimated to have increased the gender pay gap value by 4 percentage points.
4) DE - From 2002 national earnings surveys and the German Socio-Economic Panel have been used. This change of source is estimated to have increased the gender pay gap value by 1 percentage point.
5) ES - From 2002 data from tax returns and the labour force survey have been used. This is estimated to have increased the gender pay gap value by 3 percentage points
6) FR - A change of data source in 2003 is estimated to have decreased the gender pay gap value by 1 percentage point
7) FI - A change of data source from 2002 is estimated to have increased the gender pay gap value by 4 percentage points
8) UK - A change of data source from 2002 is estimated to have increased the gender pay gap value by 2 percentage points

Sources: The gender pay gap is based on several data sources, including the European Community Household Panel (ECHP), the EU Survey on Income and Living Conditions (EU-SILC) and national sources.

Administrative data are used for Luxembourg and the Labour Force Survey is used for France (up to 2002) and Malta. All other sources are national surveys except as follows:

2004, 2005: Statistics on Income and Living Conditions (EU-SILC) – BE, EL, ES, IE, IT, AT, PT and UK (provisional)

2003: Statistics on Income and Living Conditions - EL, IE and AT

2002: European Community Household Panel (ECHP) - EL

2001 and before: European Community Household Panel (ECHP) - BE, DE, IT, DK, IE, UK, EL, ES, PT, AT, FI.

EN 

218 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 17a

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Life expectancy at birth (The mean number of years that a newborn child is expected to live if subjected throughout her/his life to the current mortality conditions (age specific probabilities of dying))

1950
1960
1970
1980
1990
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

1950
1960
1970
1980
1990
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

:
:
:
:
:
:
:
:
:
:
:
:
80.9
80.8
:
:

:
:
:
:
:
:
:
:
:
:
:
:
74.5
74.6
:
:

:
:
:
:
:
:
:
:
:
:
:
:
81.3
81.2
:
:

:
:
:
:
:
:
:
:
:
:
:
:
75.0
75.1
:
:

:
:
:
:
79.7
80.9
81.1
81.4
81.5
81.7
:
82.2
82.2
82.0
:
:

:
:
:
:
72.8
74.0
74.2
74.7
74.9
75.2
:
75.5
76.0
76.0
:
:

:
72.8
74.2
76.7
79.5
80.4
80.7
80.7
80.7
81.0
81.0
81.2
81.2
81.1
81.8
81.9

:
66.8
67.9
69.9
72.7
73.5
73.9
74.2
74.4
74.4
74.6
75.0
75.1
75.3
76.0
76.2

:
71.1
73.5
73.9
74.7
74.9
74.5
73.8
74.6
75.0
75.0
75.4
75.5
75.9
76.2
76.2

:
67.5
69.1
68.4
68.0
67.4
67.4
67.0
67.4
68.3
68.3
68.5
68.8
68.9
69.0
69.0

:
73.5
73.1
74.0
75.5
76.8
77.5
77.6
78.2
78.3
78.5
78.6
78.7
78.6
79.2
79.3

:
67.8
66.1
66.9
67.6
69.7
70.4
70.5
71.2
71.5
71.7
72.1
72.1
72.0
72.6
72.9

:
:
:
:
77.8
77.9
78.4
78.6
79.0
79.0
79.2
79.3
79.4
79.8
80.2
80.5

:
:
:
:
72.0
72.7
73.1
73.6
74.0
74.2
74.5
74.7
74.8
75.0
75.4
76.0

:
71.7
73.6
76.2
78.5
79.9
80.1
80.5
80.8
81.0
81.2
81.5
81.3
81.3
81.9
82.0

:
66.5
67.5
69.6
72.0
73.3
73.6
74.1
74.6
74.8
75.1
75.6
75.7
75.8
76.5
76.7

:
:
:
:
75.0
74.3
75.6
75.9
75.4
76.0
76.2
76.4
77.0
77.1
77.9
78.2

:
:
:
:
64.7
61.5
64.3
64.3
64.1
64.9
65.5
64.9
65.3
66.1
66.5
67.3

:
:
:
:
77.7
78.3
78.7
78.7
79.1
78.9
79.2
79.9
80.5
80.8
81.4
81.7

:
:
:
:
72.1
72.8
73.1
73.4
73.4
73.4
74.0
74.5
75.2
75.9
76.5
77.3

:
:
76.1
77.5
79.5
80.1
80.2
80.4
80.3
80.5
80.6
81.0
81.1
81.2
81.3
81.6

:
:
71.6
73.0
74.7
75.0
75.1
75.4
75.5
75.5
75.5
76.0
76.2
76.5
76.6
76.8

:
:
:
78.5
80.6
81.8
82.0
82.3
82.4
82.4
82.9
83.2
83.2
83.0
83.7
83.7

:
:
:
72.3
73.4
74.4
74.5
75.2
75.3
75.3
75.8
76.2
76.3
76.3
76.9
77.0

:
:
:
:
:
:
:
:
82.6
82.7
83.0
83.0
82.9
82.7
83.8
:

:
:
:
:
:
:
:
:
74.8
75.0
75.3
75.5
75.7
75.8
76.7
:

:
:
:
:
80.4
81.6
81.8
82.1
82.2
82.7
82.9
83.2
83.2
82.8
:
:

:
:
:
:
73.9
75.1
75.5
75.9
76.1
76.6
77.0
77.2
77.4
77.1
:
:

:
:
:
:
:
:
:
:
:
:
:
:
81.0
81.6
82.1
81.1

:
:
:
:
:
:
:
:
:
:
:
:
76.4
77.4
76.8
76.8

Females
:
:
75.0
75.4
76.3
75.1
75.9
76.6
76.7
77.0
77.5
77.6
77.5
77.8
77.7
77.3
Males
:
:
66.8
65.4
66.5
63.3
64.6
65.5
66.0
66.3
66.8
65.9
66.2
66.4
66.3
65.3

:
:
:
:
78.7
80.6
80.2
80.0
80.8
81.4
81.3
80.7
81.5
80.8
82.3
82.2

:
:
:
:
72.4
73.0
73.3
74.0
73.7
74.4
74.6
75.1
74.7
74.8
75.9
76.6

:
:
:
:
:
:
:
:
:
:
:
:
76.0
75.9
76.2
76.5

:
:
:
:
:
:
:
:
:
:
:
:
64.7
65.6
65.9
65.4

:
70.2
72.1
72.8
73.8
74.8
75.0
75.5
75.6
75.6
76.2
76.7
76.7
76.7
77.2
77.2

:
65.9
66.3
65.5
65.2
65.5
66.3
66.7
66.5
66.7
67.6
68.2
68.3
68.4
68.7
68.7

:
:
:
72.8
:
79.6
79.6
80.0
80.0
79.4
80.3
81.2
81.3
80.8
81.2
81.4

:
:
:
68.0
:
74.8
74.8
75.2
74.9
75.3
76.2
76.6
76.3
76.4
77.4
77.3

:
:
:
:
80.3
80.5
80.5
80.7
80.8
80.5
:
80.8
80.7
81.0
81.5
81.7

:
:
:
:
73.8
74.6
74.7
75.2
75.2
75.4
:
75.8
76.0
76.3
76.9
77.3

:
:
73.5
76.1
79.0
80.1
80.2
80.7
81.0
81.0
81.2
81.7
81.7
81.5
82.1
82.3

:
:
66.5
69.0
72.3
73.4
73.7
74.1
74.5
74.9
75.2
75.7
75.8
75.9
76.4
76.7

:
:
:
:
:
:
:
77.0
77.4
:
78.0
78.4
78.8
78.8
79.2
79.3

:
:
:
:
:
:
:
68.5
68.9
:
69.6
70.0
70.3
70.5
70.6
70.8

:
66.6
69.6
74.9
77.5
79.0
79.0
79.3
79.6
79.7
80.2
80.5
80.6
80.6
81.5
81.3

:
61.0
63.6
67.9
70.6
71.7
71.6
72.2
72.4
72.6
73.2
73.5
73.8
74.2
75.0
74.9

:
:
70.4
72.0
73.1
73.3
72.7
73.1
73.6
74.1
74.6
74.8
74.7
75.0
75.5
75.7

:
:
65.8
66.7
66.7
65.3
64.9
65.0
66.0
66.9
67.5
67.4
67.4
67.7
68.3
68.7

:
:
:
:
77.8
78.5
79.0
79.1
79.2
79.5
79.9
80.4
80.5
80.3
80.8
80.9

:
:
:
:
69.8
70.8
71.1
71.1
71.3
71.8
72.2
72.3
72.6
72.5
73.5
73.9

:
72.7
73.1
74.4
75.7
76.5
77.0
76.9
77.0
77.4
77.5
77.7
77.7
77.7
78.0
78.1

:
67.9
66.8
66.7
66.7
68.4
68.9
68.9
68.6
69.0
69.2
69.5
69.8
69.8
70.3
70.2

:
:
:
:
79.0
80.4
80.7
80.7
81.0
81.2
81.2
81.7
81.6
81.9
82.5
82.5

:
:
:
:
71.0
72.9
73.1
73.5
73.6
73.8
74.2
74.6
74.9
75.2
75.4
75.6

:
:
77.3
79.0
80.5
81.7
81.7
82.0
82.1
82.0
82.0
82.2
82.2
82.5
82.8
82.9

:
:
72.3
72.8
74.8
76.2
76.6
76.8
76.9
77.1
77.4
77.6
77.8
78.0
78.4
78.5

:
:
:
:
:
79.3
79.5
79.7
79.8
79.9
80.3
80.5
80.6
80.5
81.0
81.1

:
:
:
:
:
74.0
74.3
74.7
74.8
75.0
75.5
75.8
76.0
76.2
76.8
77.1

:
:
:
:
76.1
:
:
:
:
:
77.7
78.0
:
78.2
78.9
78.8

:
:
:
:
68.4
:
:
:
:
:
70.7
71.0
:
71.2
72.0
71.8

:
:
:
:
:
74.0
74.8
74.7
74.5
:
75.2
76.1
75.6
75.7
75.8
75.9

:
:
:
:
:
69.8
70.3
70.3
70.2
:
70.8
70.9
70.6
70.9
71.5
71.6

:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:

Sources: Eurostat - Demographic statistics.

EN 

219 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Key indicator 17b

Healthy Life Years at birth (The mean number of years that a newborn child is expected to live in healthy condition if subjected throughout her/his life to the current morbidity and mortality conditions (age specific probabilities of becoming 
sick/dying))

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

68.5 e
68.3
65.4 e
68.4
69.1
68.8
69.0 e
69.2 e
58.1pb
61.9p

64.1
66.5
63.3
66.0
65.7
66.6
66.9 e
67.4 e
58.4pb
61.7p

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
63.3 p
:
:
59.9pb

:
:
:
:
:
:
62.8 p
:
:
57.9pb

61.1
60.7 e
61.3 e
60.8
61.9
60.4
61.0 e
60.9 e
68.8pb
68.2p

61.7
61.6
62.4
62.5
62.9
62.2
62.8 e
63.0 e
68.3pb
68.4p

64.5
64.3 e
64.3 e
64.3 e
64.6 e
64.5 e
64.5 e
64.7 e
:
55.1pb

60.8
61.9 e
62.1 e
62.3 e
63.2 e
64.1 e
64.4 e
65.0 e
:
55.0pb

:
:
:
:
:
:
:
:
53.3p
52.2p

:
:
:
:
:
:
:
:
49.8p
48.0p

Sources: Eurostat - Health statistics.

69.6
68.7
68.3
69.4
68.2
68.8
68.5 e
68.4 e

70.5 e
68.4
:
71.3
68.2
:
71.3
68.2
:
72.1
69.5
67.6
72.9
69.3
66.9
73.0 e
69.2 e
66.5
73.9 e
69.9 e
65.9 e
65.4 e
74.4 e
70.2 e
64.3pb 65.2pb 62.5pb 64.1pb 70.2pb
67.0p
63.1p
64.1p

62.5
63.1
62.8
63.3
63.2 e
63.3
63.7 e
63.9 e

64.3p

67.2p

66.9
66.4
66.5
66.7
66.3
66.7
66.7 e
66.7 e

67.4
65.1
64.0
68.0
65.5
63.2
67.9
65.2
64.0
68.7
65.6
63.9
69.7
66.5
63.3
69.8
66.0
63.3
70.4 e
66.6 e
63.5 e
63.4 e
70.9 e
66.8 e
62.5pb 63.7pb 62.5pb 61.2pb 67.9pb
65.8p
63.2p
62.9p

59.6
60.2
59.2
60.1
60.1
60.5
60.4 e
60.6 e

65.7p

62.0p

:
:
:
:
:
:
:
69.6
:
57.9p

:
:
:
:
:
:
:
68.4
:
59.5pb

:
:
:
:
:
:
:
:
:
53.1p

:
:
:
:
:
:
:
:
:
50.6p

Females
:
:
:
:
:
:
:
:
:
54.3p
Males

:
:
:
:
:
:
:
:
:
51.2p

:
:
:
:
:
:
:
:
60.2p
62.1p

:
:
:
:
:
:
:
:
59.1p
62.2p

:
:
:
:
:
:
:
57.8 p
:

:
:
:
:
:
:
65.7 p
:
:
53.9pb 70.1pb 63.1pb

61.5
61.4
61.1 e
61.4
60.2
59.4
59.3 e
58.8 e
:

:
:
:
:
:
:
:
53.5 p
:

:
:
:
:
:
:
65.1 p
:
:
52.0pb 68.5pb 65.0pb

62.1
62.5
61.9
61.6
61.4
61.9
61.7 e
61.7 e
:

:
:
:
:
68.0
68.5
69.0 e
69.6 e
60.2pb
59.6p

62.3
62.2
63.4
63.6
64.6
64.2
65.6 e
66.2 e
58.1pb
57.8p

66.8
:
:
:
:
:
68.9
:
:
66.6pb

59.9
:
:
:
:
:
62.5
:
:
61.0pb

60.5
60.4
61.1
60.7
62.2
62.7
61.8 e
61.8 e
52.0pb
56.7p

58.2
59.3
59.1
58.8
60.2
59.5
59.7 e
59.8 e
55.1pb
58.4p

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
59.9p

:
:
:
:
:
:
:
:
:
56.3p

:
:
:
:
:
:
:
:
:
56.4p

:
:
:
:
:
:
:
:
:
54.9p

:
57.7
60.0
57.6
61.3 e
58.3
61.8
57.4
61.9
56.8 e
61.0
56.9
61.9 e
56.8 e
56.5 e
62.2 e
52.9pb 60.9pb
63.1p
52.4p

:
54.6
62.1
55.5
61.7
55.9
62.0
55.8
63.1
56.3
61.9
56.7
62.4 e
57.0 e
57.3 e
62.5 e
53.1pb 62.0pb
64.2p
51.7p

61.8 e
61.2 e
62.2 e
61.3 e
61.2 e
60.8 e
60.9 e
60.9 e
:
65.0pb

60.8
60.9 e
60.8 e
61.2 e
61.3 e
61.1 e
61.4 e
61.5 e
:
63.2pb

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

EN 

220 

EN 

 
  
 
EU-
27

EU-
25

EA-
13

Key indicator 18a

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

:
:
:
100
100
99
95
88
83
79

:
:
:
100
101
104
101
97
94
89

:
:
:
100
100
98
94
89
84
81

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Serious accidents at work (Index of the number of serious accidents at work per 100 thousand persons in employment (1998=100))

110
99
96
100
96
82b
83
72
68
65

100
98
95
100
96
101
88
80
76
71

110
98
96
100
96
80 b
84
73
67
65

147
131
106
100
84
100 b
90
84
65
58

:
:
:
:
:
100
84
85
67
61

:
:
:
:
:
100 b
93
84
69
60

:
96
91
100
93
91
91
89
80
81

:
:
:
100
97
95
97
97
90
94

:
:
:
100
92
90
89
85
77
77

82
84
100
100
95
89
90
82
76
79

83
90
104
100
103
99
95
92
86
90

81
83
99
100
93
88
91
81
75
77

106
103
101
100
99
96
88
82
74
73

98
102
99
100
99
99
94
87
77
77

107
103
102
100
99
96
89
83
75
74

85
77
83
100
106
105
132
125
128
124

:
:
:
100
138
130
181
130
137
126

:
:
:
100
140
114
120
123
135
132

62
104 b
115
100
:
:
:
100 b
105
94

:
112
120
100
:
:
:
100 b
103
87

:
100
113
100
:
:
:
100 b
105
95

118
129
113
100
93
88
86
83
71
66

118
126
106
100
88
76
77
76
67
65

119
130
116
100
96
92
89
86
73
67

92
95
95
100
107
108
106
103
100
92

80
88
91
100
109
113
110
105
106
98

93
96
96
100
108
109
108
106
102
95

104
101
101
100
101
102
98
99
95
90

102
102
103
100
106
111
110
117
112
107

104
100
101
100
101
101
94
95
92
87

102
102
100
100
99
99
92
83
80
75

97
98
97
100
102
104
88
86
84
77

103
103
100
100
99
98
96
85
82
78

:
:
:
:
100
112
112
92
103
103

:
:
:
:
100
118
123
92
98
100

:
:
:
:
100
112
110
92
105
104

Total
90
88
90
100
97
94
85
86
82
82
Females
:
:
:
100
85
95
87
84
84
81
Males
:
:
:
100
93
84
87
85
81
80

98
100
98
100
105
104
97
109
107
94

93
101
96
100
99
100
101
116
118
96

96
99
98
100
107
105
98
111
107
97

:
:
:
100
75
66
116
108
84
79

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

123
110
103
100
93
94
86
84
83
79

:
:
:
100
92
94
90
91
93
93

:
:
:
100
93
94
85
81
80
75

106 e
92 e
112 e
100
113
77
94
91
90
83

:
:
:
100
108
77
86
76
78
77

:
:
:
100
114
78
97
96
95
86

108
109
107
100
108 b
105
92
100 b
82
73

:
:
:
:
:
:
:
100 b
85
95

:
:
:
:
:
:
:
100 b
82
72

164
107 b
105
100
99
92
83
84
79
79

:
124
106
100
99
93
73
75
71
72

:
104
106
100
100
92
86
87
82
86

:
:
113
100
78
85
78
76
82
84

:
:
:
100
85
85
80
81
90
92

:
:
:
100
87
86
78
85
80
82

109
109
100
100
92
88
91
74
72
75

:
:
104
100
75
87
94
83
77
84

:
:
98
100
96
89
95
74
74
75

:
:
106
100
100
106
113
104
111
103

:
:
:
100
94
101
112
96
117
97

:
:
:
100
102
109
117
108
111
107

109
110
106
100
102
98
94
94
98
98

:
:
:
100
101
98
95
100
109
109

:
:
:
100
99
97
92
92
93
93

95
96
107
100
92
88
84
77
68
54

:
:
:
100
96
88
83
84
76
62

:
:
:
100
91
87
84
75
66
62

106
98
98
100
91
89
87 b
85
83
83

107
96
98
100
90
89
87 b
85
86
90

107
101
99
100
93
89
87 b
86
84
83

76
92
81
100
107
111
113
101
94
86

73
84
76
100
103
106
106
96
95
85

77
94
83
100
108
113
116
104
95
88

119
103
102
100
106
106
110
108
107
88

130
103
99
100
109
110
111
110
109
81

117
103
102
100
106
105
108
106
104
89

:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
94
107
100
84
85
90
84
83
82

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

Source: Eurostat - European Statistics on Accidents at Work (ESAW)

EU-
27

EU-
25

EA-
13

Key indicator 18b

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Fatal accidents at work (Index of the number of fatal accidents at work per 100 thousand persons in employment (1998=100))

1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

:
:
:
100
88
87
85
81
80
76

190
177
100
100
106
100
124
82
78
93

116
120
116
100
96
100
104
85
83
84

103
112
116
100
76
96
96
87
84
78

106
97
74
100
71
61
55
65
57
35

136
159
123
100
109
95
89
112
105
100

120
102
114
100
79
56
78
81
67
75

71
56
120
100
:
:
:
100
121
84

116
100
76
100
170
73
78
104
81
67

127
107
115
100
91
85
81
79
67
59

88
90
103
100
85
85
79
65
69
68

96
82
84
100
68
66
62
42
57
50

:
:
:
:
100
46 i
62 i
107 i
83 i
92 i

:
:
:
100
115
90
140
123
66
98

Total
98
102
83
100
91
78
105
115
138
113

113 i
271 i
184 i
100
40 i
149 i
37 i
52 i
70 i
20 i

117
101
97
100
107
95
71
109
80
96

109 i
100 i
42 i
100
74 i
38 i
46 i
30 i
91 i
90 i

:
114
140
100
107
106
79
90
91
84

131
118
104
100
100
100
94
100
94
107

:
:
109
100
83
96
92
89
90
86

103
127
108
100
79
104
117
98
87
82

:
:
105
100
93
103
97
95
111
103

118
118
130
100
113
102
122
141
136
77

96
109
81
100
89
71
71
65
75
64

117
71
117
100
75
88
98
82
81
102

177
162
169
100
85
85
105
91
89
81

100
119
100
100
88
106
92
85
70
90

:
:
:
:
:
:
:
:
:
:

:
:
:
:
:
:
:
:
:
:

:
121
120
100
104
68
92
75
64
64

Notes: 1) CY, LU, MT: The values are based on small annual numbers of fatalities. 
Source: Eurostat - European Statistics on Accidents at Work (ESAW)

EN 

221 

EN 

 
  
 
ANNEX 1.3 - OTHER STATISTICAL TABLES PER GEOPOLITICAL ENTITY 

EN 

222 

EN 

 
  
1  ECONOMY

European
Union - 27

European
Union - 25

Euro area -
13

Belgium Bulgaria

Czech 
Republic

Denmark

Germany Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of 
Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Gross domestic product at current market prices

2005, Bn Euro

2006, Bn Euro

10 989

10 888

8 052

11 579

11 457

8 433

 299

 314

 22

 25

 100

 114

 208

 220

2 245

2 322

 11

 13

 161

 175

 181

 195

 908

 981

1 718

1 423

1 792

1 475

 14

 15

 13

 16

 21

 24

 29

 33

 89

 90

 5

 5

 509

 534

 245

 258

 244

 272

 149

 155

 80

 97

 28

 30

 38

 44

 157

 167

 288

 306

1 805

1 910

 31

 34

 5

5 f

 291

 319

Note: Figures for United Kingdom, Croatia, FYROM and Turkey do not include the allocation of "financial intermediation services indirectly measured" (FISIM) to user sectors. Therefore comparability between these countries and the other countries (that already allocate FISIM) is reduced.

GDP volume growth rates

Annual growth rate, 2004

Annual growth rate, 2005

Annual growth rate, 2006

Compared to the same quarter of 
the previous year, 2007Q1

Compared to the same quarter of 
the previous year, 2007Q2

2.5

1.8

3.0

3.4

2.5

2.4

1.8

3.0

3.4

2.6

2.0

1.5

2.8

3.0

1.1

3.2

6.6

6.2

6.1

3.0

3.1

6.2

2.5

2.3

6.6

4.5

6.4

6.4

6.4

6.0

2.1

3.1

3.5

2.7

0.6

1.1

0.8

2.9

8.3

10.2

11.2

4.4

6.0

5.7

4.7

3.7

4.3

3.3

3.6

3.9

3.3

10.1

8.1

4.6

4.3

2.5

7.6

5.4

4.1

3.9

2.5

1.7

2.0

1.9

1.2

1.2

0.1

1.9

4.2

3.9

3.8

8.7

10.6

11.9

7.3

7.6

7.5

3.6

4.0

6.2

4.8

4.1

3.9

0.1

3.1

3.2

2.2

1.5

3.0

2.3

2.0

3.3

5.3

3.6

6.1

1.5

0.5

1.3

8.5

4.1

7.7

4.4

4.1

5.7

5.4

6.0

8.3

3.7

2.9

5.5

4.1

2.9

4.2

3.3

1.8

2.8

3.8

4.3

4.8 f

4.1

3.8 f

3.1 f

2.3

4.0

11.2

8.3

7.3

2.7

3.5

2.5

3.5

6.9

2.0

6.0

7.2

9.0

5.5

3.0

4.2

7.0

2.0

3.7

11.0

8.0

:

1.2

3.7

2.6

3.5

6.8

1.6

5.6

5.9

9.4

4.4

3.4

1.9

6.6

:

:

8.9

7.4

6.1

6.9

3.9

Note: Quarterly growth rates are calculated from raw (i.e. non-seasonally adjusted) data, except for Greece and Portugal.

GDP per head (Index EU-27=100, in PPS)

1995

2006

100

100

105

104

116

110

129

122

32

37

74

79

132

127

130

114

36

68

103

144

75

88

92

102

116

113

122

104

89

93

32

56

35

58

224

278

51

65

87

76

124

132

136

129

43

53

75

74

:

38

73

89

48

63

108

116

124

120

112

119

39

50

:

27

30

29

Note: Figures for 2006 are based on preliminary PPP. 

GDP per head in Euro

2006

23 500

24 700

26 600 29 800

3 300

11 100

40 500

28 200

9 800

41 100 17 600 22 300

28 400

25 100 18 900

7 100

7 000 71 500

8 900 12 400 32 700 31 100

7 100 14 700

4 500 15 200

8 200 31 700 33 700

31 500

7 700

2 400 f

4 400

Household consumption expenditure per head  (Index EU-27=100, in Euro)

2006

100

105

112

116

17

40

144

122

38

138

86

94

119

110

91

34

34

203

35

59

114

127

33

70

23

59

35

120

117

148

32

Note: Household consumption expenditure includes the consumption expenditure of non-profit institutions serving households, except for Croatia and Turkey.

Net saving (% of GDP)

2005 (% of GDP)

:

:

6.4

7.9

2.1

4.9

8.2

6.8

13.5

11.9

6.0

6.8

5.5

3.8

:

4.1

6.3

:

:

:

11.3

9.6

4.7

-3.4

Gross compensation per employee (Index EU27=100, in Euro)

2005

100

104

111

144

10

35

142

110

30

137

:

87

131

106

72

20

24

164

41

53

120

121

27 e

:

Notes: 1) Both compensation and employees use the domestic concept, i.e. they are attributed to a country according to the residence of the production unit, not the residence of the employee. 2) The value for PL is estimated by the Commission Services.

:

:

9.8

1.8

10.4

10.8

4.5

64

26

122

130

135

:

:

General government debt (% of GDP)

2004

2005

2006

62.1

62.7

61.4

General government deficit (-) / surplus (+) (% of GDP)

2004

2005

2006

-2.8

-2.4

-1.6

62.4

63.1

61.9

-2.8

-2.5

-1.6

69.6

70.3

68.6

94.2

92.2

88.2

37.9

29.2

22.8

-2.8

-2.5

-1.5

0.0

-2.3

0.4

Source: Eurostat  - National and Financial Accounts.

Annual inflation rate compared to the same month of the previous year

July 2006

May 2007

June 2007

July 2007

2.5

2.1

2.2

2.0

2.4

2.1

2.1

1.9

2.4

1.9

1.9

1.8

2.4

1.3

1.3

1.3

2.3

2.0

3.2

7.8

4.5

5.3

6.8

30.4

30.2

30.1

-3.0

-3.5

-2.9

2.4

2.4

2.6

2.5

44.0

36.3

30.3

65.6

67.8

67.5

1.9

4.6

4.6

2.0

1.7

1.3

1.1

-3.8

-3.4

-1.6

2.1

2.0

2.0

2.0

5.1

4.4

4.0

1.8

1.9

3.6

4.5

5.9

6.0

6.5

29.5

27.4

25.1

98.6

98.0

95.3

46.2

43.0

39.7

64.9

66.7

64.2

103.8

106.2

106.8

70.2

69.1

65.2

14.5

12.5

10.6

19.4

18.6

18.2

6.4

6.2

6.6

59.4

61.6

65.6

72.7

70.8

64.7

52.4

52.3

47.9

63.8

63.4

61.7

45.7

47.1

47.6

58.3

63.7

64.8

18.8

15.8

12.4

27.6

27.4

27.1

41.4

34.2

30.4

44.1

41.4

39.2

52.4

52.2

47.0

40.4

42.1

43.2

43.2

43.7

40.8

1.3

1.2

2.9

2.9

2.7

2.8

2.7

-7.3

-5.1

-2.5

-0.3

1.0

1.8

3.9

2.6

2.6

2.7

4.0

2.4

2.5

2.3

-3.6

-2.9

-2.5

2.2

1.2

1.3

1.2

-3.5

-4.2

-4.4

-4.1

-2.4

-1.2

-1.0

-0.4

-0.3

-1.5

-0.5

-0.6

-1.2

-0.1

0.7

-6.5

-7.8

-9.2

2.3

1.9

1.9

1.7

2.8

1.9

1.7

2.3

6.9

7.8

8.9

9.5

4.4

5.0

5.0

5.1

3.4

2.3

2.3

2.0

3.2

8.4

8.5

8.3

-4.9

-3.1

-2.5

3.6

-1.0

-0.6

-0.2

-1.7

-0.3

0.6

-1.2

-1.6

-1.4

-5.7

-4.3

-3.8

-3.4

-6.1

-3.9

-1.5

-1.4

-1.9

-2.3

-1.5

-1.2

-2.4

-2.8

-3.7

1.7

2.0

1.8

1.4

2.0

1.9

1.9

2.0

1.4

2.3

2.6

2.5

3.0

2.4

2.4

2.3

6.2

3.9

3.9

4.1

1.9

3.1

3.8

4.0

5.0

1.5

1.5

1.2

2.3

2.7

3.8

1.4

1.3

1.4

1.6

0.8

2.4

2.5

1.8

1.2

1.3

1.4

-3.4

-3.3

-2.7

-4.1

-3.8

-2.2

2.4

2.5

2.4

1.9

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

21

:

:

76.9

69.6

60.7

-5.8

-0.3

0.4

:

:

:

:

EN 

223 

EN 

 
  
 
12-month average annual inflation rate, 12-month average rate

July 2007

2.1

2.1

1.9

1.8

5.5

2.0

1.6

1.7

5.1

2.7

3.0

2.6

1.4

2.0

1.8

7.5

4.5

2.1

7.5

0.7

1.6

1.7

1.9

2.5

4.4

2.8

2.7

1.3

1.5

2.6

Note: The annual inflation rate measures the price change between the current month and the same month the previous year. The 12-month average rate compares the average Harmonized Indices of Consumer Prices (HICPs) in the latest 12 months to the average of the previous 12 months. 
Source: Eurostat - Price statistics.

Interest rates: 10-year government bond yields, monthly average

August 2006

June 2007

July 2007

August 2007

4.22

4.90

4.87

4.70

4.16

4.98

4.95

4.76

Interest rates: 10-year government bond yields, annual average

1999

2000

2001

2002

2003

2004

2005

2006

:

:

:

:

:

:

:

4.08

:

:

:

:

4.34

4.44

3.70

4.03

3.96

4.64

4.60

4.42

4.66

5.44

5.00

4.91

4.14

4.12

3.42

3.84

3.92

4.64

4.62

4.44

4.75

5.59

5.13

4.99

4.18

4.15

3.43

3.81

4.66

4.57

4.79

4.79

:

:

:

:

6.45

5.36

3.87

4.18

3.85

4.53

4.59

4.45

:

:

6.31

4.88

4.12

4.75

3.51

3.78

3.93

4.64

4.58

4.39

4.91

5.64

5.08

5.06

4.31

4.30

3.40

3.81

3.88

4.56

4.50

4.30

4.49

5.26

4.80

4.78

4.07

4.04

3.35

3.76

4.38

5.42

5.59

:

11.39

10.48

10.15

8.42

5.25

4.39

3.98

4.30

3.88

4.62

4.59

4.40

4.71

5.51

5.01

5.01

4.13

4.08

3.33

3.76

4.19

4.80

4.79

4.62

6.30

6.10

5.30

5.12

4.27

4.26

3.59

4.07

3.89

4.62

4.60

4.40

4.73

5.53

5.12

4.96

4.12

4.10

3.39

3.78

3.90

4.62

4.58

4.39

4.61

5.39

4.94

4.86

4.13

4.10

3.41

3.80

4.17

4.77

4.76

4.58

4.73

5.58

5.19

5.03

4.25

4.26

3.56

4.05

4.28

4.44

4.44

4.44

:

:

7.63

5.70

4.74

5.80

5.16

4.13

4.36

5.62

5.28

5.32

:

:

7.57

5.41

4.90

4.86

3.88

4.13

4.28

4.57

4.89

4.80

:

:

8.15

6.06

5.32

4.50

3.70

4.08

4.00

4.74

4.83

:

4.66

5.52

4.86

4.70

4.03

4.18

3.37

3.89

7.49

6.71

6.58

6.80

:

:

7.95

7.09

6.82

8.19

6.60

7.12

4.34

5.12

5.18

4.94

:

:

6.19

5.82

5.04

4.69

4.56

4.32

3.90

4.61

4.57

4.38

4.63

5.40

4.96

4.89

4.12

4.10

3.37

3.78

3.92

4.62

4.58

4.39

4.68

5.56

5.07

4.97

4.15

4.15

3.39

3.80

5.62

5.52

5.60

5.68

:

:

10.68

7.36

5.78

6.90

5.22

5.23

4.06

4.74

4.73

4.56

4.78

5.59

5.16

5.01

4.18

4.14

3.44

3.91

7.41

7.05

6.86

6.92

:

:

:

:

:

:

:

7.23

3.92

4.79

4.72

4.82

:

:

:

:

6.40

4.68

3.81

3.85

5.13

4.66

4.70

4.65

:

:

8.04

6.94

4.99

5.03

3.52

4.41

3.94

4.62

4.59

4.39

4.72

5.48

5.04

4.98

4.13

4.11

3.35

3.78

3.84

4.44

4.45

4.25

4.98

5.37

5.11

5.30

4.64

4.42

3.38

3.70

4.49

5.49

5.46

5.19

5.01

5.33

5.01

4.91

4.58

4.93

4.46

4.37

Notes: 1) The interest rate figures for the 27 EU Member States refer to the EMU convergence criterion series. 2) Euro area including Greece.

Source: Eurostat - Financial indicators. 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

1  ECONOMY

European
Union - 27

European
Union - 25

Euro area -
13

Belgium Bulgaria

Czech 
Republic

Denmark

Germany Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of 
Macedonia

Turkey

EN 

224 

EN 

 
  
 
2 POPULATION

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium

Bulgaria

Czech 
Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia

Lithuania

Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria

Poland

Portugal

Romania Slovenia Slovakia

Finland

Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

9 961

 327

11 417

7 030

29 480

8 826

18 319

1 581

3 970

4 413

7 471

52 200

4 127

1 384

27 120

Total population (1000)

1.1.1960

1.1.1980

1.1.2000

1.1.2003, revised after 2001 census 
round

1.1.2004

1.1.2005

402 607

376 459

252 205

9 129

7 829

9 638

4 565

72 543

1 209

457 053
482 188

426 074
452 090

286 751

306 225

9 855

8 846

10 316

10 239

8 191

10 278

5 122

5 330

78 180

82 163

1 472
1 372

486 520

488 632

490 898

456 902

459 119

310 934

312 901

461 479

314 888

10 356

10 396

10 446

7 846

7 801

10 203

10 211

7 761

10 221

5 384

5 398

5 411

82 537

82 532

82 501

Population growth rates (per 1000 population), 2005
Total increase

4.2

Natural increase

Net migration

0.6

3.6

4.7

0.8

3.8

5.7

0.9

4.7

6.3

1.4

4.9

-5.5

-5.5

0.0

3

-0.6

3.5

3

1.7

1.2

-0.8

-1.8

1.0

2 836

3 393

3 778

3 964

4 028

4 109

24

8.1

15.9

8 300

30 327

45 465

50 026

 572

2 104

2 756

9 584

10 904

37 242

40 050

53 731

58 825

56 388

56 924

 510
690

2 509
2 382

3 404
3 512

11 006

11 041

11 083

41 664

42 345

43 038

59 970

60 340

60 702

57 321

57 888

58 462

3.8

0.2

3.6

16.6

1.8

14.8

7.6

4.1

3.6

4.9

-0.6

5.5

 715

 730

 749

22.7

3.7

19.0

2 331

2 319

2 306

-5.1

-4.9

-0.2

3 463

3 446

3 425

-6.5

-3.9

-2.6

1 356

1 351

1 348

-2.1

-2.2

0.1

The increase in total population is made up of the natural increase (live births less deaths) and net migration. Net migration is estimated on the basis of the difference between population change and natural increase (corrected net migration).

Population structure (percentage of total), 2005

Total

0-19

20-59

60-79

80 and over

100

22.4

55.9

17.7

4.0

100

22.3

55.8

17.8

4.1

100

21.5

55.7

18.5

4.3

Population by age group (in thousands), 2005

0-14

15-24

25-54

55-64

65 and over

80 and over

79 311

62 831

74 801

58 406

49 598

37 762

211 915

199 118

136 871

55 462

81 379

19 705

52 280

76 873

18 946

35 688

54 969

13 628

100

23.1

54.9

17.7

4.3

1 795

1 261

4 439

1 151

1 800

 448

100

20.5

56.7

19.7

3.1

1 073

1 062

3 309

 987

1 331

 242

100

21.4

58.9

16.7

3.0

1 527

1 366

4 552

1 341

1 435

 308

Population by main group of citizenship, in thousands, 2006 1)
463 646

492 975

Total

316 690

10 511

7 719

10 251

465 070

27 904

435 793

294 994

27 853

21 697

9 611

 900

7 693

9 993

 26

 258

100

24.5

54.6

16.8

4.1

100

20.3

54.8

20.6

4.3

1 018

11 925

597

9 678

2 275

35 834

708

813

221

9 696

15 367

3 557

5 428

5 157

270

82 438

75 149

7 289

Nationals

Non-nationals

Nationals of other EU-25 
member states
Non-EU-25 nationals 3)

8 286

19 619

8 276

19 577

6 495

15 201

Population by main group of citizenship, in percentages, 2006 1)
94.0

94.3

Nationals

Non-nationals

Nationals of other EU-25 
member states
Non-EU-25 nationals 3)

5.7

1.7

4.0

6.0

1.8

4.2

93.1

6.9

2.1

4.8

 612

 289

91.4

8.6

5.8

2.7

 4

 22

 87

 171

 72

198

2 677

4 612

99.7

0.3

0.0

0.3

97.5

2.5

0.9

1.7

95.0

5.0

1.3

3.6

91.2

8.8

3.2

5.6

100

23.4

54.9

18.6

3.1

208

210

558

149

222

42

1 345

1 103

242

 5

237

82.0

18.0

0.4

17.6

100

27.9

56.8

12.6

2.7

851

638

1 771

391

458

110

4 209

3 895

314

 213

101

92.5

7.5

5.1

2.4

100

19.9

56.9

19.8

3.4

1 598

1 377

4 867

1 234

2 007

376

100

19.9

58.5

17.3

4.3

100

24.9

54.3

16.3

4.5

100

19.1

55.9

20.1

4.9

6 241

5 285

11 203

7 870

8 256

6 099

19 807

25 116

25 696

4 477

7 228

1 845

6 545

9 968

2 752

7 032

11 379

2 898

11 125

10 241

884

43 758

39 756

4 003

62 999

59 489

3 510

58 752

56 081

2 671

 88

796

 836

3 167

1 110

2 400

 224

2 447

92.1

7.9

0.8

7.2

90.9

9.1

1.9

7.2

94.4

5.6

1.8

3.8

95.5

4.5

0.4

4.2

100

26.7

56.8

13.9

2.6

144

119

322

75

89

20

766

668

98

 55

43

87.2

12.8

7.1

5.7

100

22.8

55.0

19.1

3.1

341

360

965

259

381

70

2 295

1 838

457

 6

451

80.1

19.9

0.2

19.7

100

25.1

54.7

17.4

2.8

 585

 526

1 444

 353

 517

 96

3 403

3 370

 33

 2

 31

99.0

1.0

0.1

0.9

10 709

10 222

10 142

10 117

10 098

-2.1

-3.8

1.7

100

21.9

56.8

18.0

3.3

1 580

1 322

4 409

1 209

1 578

338

 313

 363

 434

 448

 452

 455

9.8

3.8

6.0

100

24.5

56.7

15.6

3.2

 85

 52

 206

 47

 65

 15

 469

 287

 182

 155

 27

61.2

38.8

33.0

5.7

 315

 380

14 091

15 864

7 546

8 002

35 413

38 654

9 714

10 195

22 133

21 908

1 893

1 988

4 963

5 399

4 771

5 171

 397

 400

 403

16 193

16 258

16 306

8 102

8 140

8 207

38 219

38 191

38 174

10 407

10 475

10 529

21 773

21 711

21 659

1 995

1 996

1 998

5 379

5 380

5 385

5 206

5 220

5 237

4.2

1.8

2.4

1.8

3.2

-1.4

7.2

0.4

6.8

-0.4

-0.1

-0.3

3.8

0.2

3.6

-2.2

-1.9

-0.3

2.9

-0.3

3.2

0.8

0.2

0.6

3.6

1.9

1.7

100

24.7

57.2

15.3

2.8

71

59

170

50

54

11

100

24.5

56.4

15.6

3.5

3 009

1 949

7 122

1 938

2 289

574

10 077

9 920

156

404

392

12

16 334

15 643

691

 25

131

98.5

1.5

0.2

1.3

 8

4

 234

458

97.0

3.0

2.0

1.0

95.8

4.2

1.4

2.8

100

22.1

56.0

17.7

4.2

1 323

1 011

3 602

959

1 312

347

8 266

7 452

814

 227

587

90.2

9.8

2.8

7.1

100

24.5

58.4

14.6

2.5

6 377

6 287

16 715

3 776

5 018

966

100

21.3

56.5

18.4

3.8

1 647

1 328

4 596

1 168

1 791

401

100

23.9

56.8

16.9

2.4

3 437

3 363

9 489

2 195

3 175

517

100

20.7

58.7

17.6

3.0

287

268

914

222

306

60

38 157

37 457

700

10 570

10 294

276

 15

685

98.2

1.8

0.0

1.8

 81

195

97.4

2.6

0.8

1.8

21 610

21 584

2 003

1 954

26

 6

20

99.9

0.1

0.0

0.1

49

 3

46

97.6

2.4

0.1

2.3

100

24.8

59.1

13.7

2.4

100

23.5

55.4

17.2

3.9

919

869

915

651

2 434

2 154

538

626

127

685

831

203

5 389

5 364

26

5 256

5 142

114

 14

12

 38

76

99.5

0.5

0.3

0.2

97.8

2.2

0.7

1.4

8 303

8 861

8 941

8 976

9 011

4

1.1

3.0

100

24.0

52.8

17.9

5.3

1 584

1 097

3 596

1 181

1 554

482

9 048

8 568

480

 213

267

94.7

5.3

2.4

2.9

56 285

58 785

4 598

4 442

1 878

2 022

44 021

66 889

59 438

59 700

60 060

4 442

4 442

4 444

2 024

2 030

2 035

69 770

70 692

71 610

5.5

2.3

3.2

-0.2

-2.1

1.9

1.6

2

-0.4

12.6

12.6

0.0

100

24.7

54.2

16.7

4.4

100

22.3

55.6

19.3

2.8

10 848

7 833

712

590

24 808

1 897

6 954

9 617

2 636

501

745

125

60 393

56 968

3 425

1 280

2 145

94.3

5.7

2.1

3.6

4 443

4 405

38

:

:

99.1

0.9

:

:

100

28.0

56.6

13.8

1.5

 406

 329

 880

 197

 222

 30

2 039

:

:

:

:

:

:

:

:

100

37.4

54.1

:

:

20 503

12 918

29 661

4 361

:

:

72 520

72 228

 292

 151

 141

99.6

0.4

0.2

0.2

Notes: 1) Table includes Eurostat estimates.  2) CY: Government controlled area only.  3) EE and LV: The non-EU nationals group for Estonia includes persons of 'undetermined' citizenship. For Latvia, this includes the "non-citizens of Latvia"; PL: A large number of persons were recorded in the census as 'unknow citizenship' and are included in non-EU nationals group.

EN 

225 

EN 

 
  
 
Immigration by main group of citizenship, 2005 1)

  Total

Nationals

Non-nationals

Nationals of other EU-25 
member states

Non-EU-25 nationals

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

81 913

13 113

68 800

33 647

35 153

:
:

:

:

:

60 294

1 718

58 576

14 742

43 834

52 458

707 352

22 469

128 051

29 989

576 301

12 707

17 282

286 047

290 254

:

:

:

:

:

86 900

19 700

67 200

54 800

12 400

:

:

:

:

:

719 284

36 573

:

:

440 301

24 419

47 530

2 540

682 711

134 797

392 771

21 879

1 886

 639

1 247

6 789

4 705

2 084

13 512

24 298

1 186

2 134

12 326

22 164

131 096

551 615

1 197

133 600

23 625

14 234

369 146

7 645

 769

478

 411

1 673

9 840

 322

2 486

21 842

Notes: 1) According to national definitions of international migration. 2) BE and IT: 2003. 3) FR: figure covers only nationals of non-EU countries and of the New Member States (NMS-12), i.e. excluding immigration of nationals of EU-15 countries. 4) HU, PT and HR: 2004.

Emigration by main group of citizenship, 2005

  Total

Nationals

Non-nationals

Nationals of other EU-25 
member states

Non-EU-25 nationals

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

41 897

18 454

23 443

16 263

7 180

:
:

:

:

:

24 065

2 269

21 796

2 365

19 431

45 869

628 399

26 249

144 815

19 620

483 584

8 456

11 164

234 458

249 126

:

:

:

:

:

17 000

:

:

:

:

:

:

:

:

:

68 011

19 290

48 721

7 360 :
41 361 :

:

:

:

48 706

39 866

8 840

10 003

 316

9 687

2 450

1 237

1 213

15 571

13 306

2 265

2 419

6 421

1 506

8 181

 240

973

 447

1 818

10 841

1 487

9 354

7 594

1 760

3 820

 354

3 466

 201

3 265

Notes: 1) According to national definitions of international migration. 2) BE, IT: 2003; HU, PT, HR: 2004.

:

:

:

:

:

:

:

:

:

:

92 297 117 822

28 882

16 367

:

:

:

:

:

:

15 041

1 747

63 415 101 455

9 364

16 761

3 704

13 294

9 410

1 745

7 665

21 355

8 611

12 744

65 229

496 469

13 932

89 067

51 297

407 402

18 383

16 857

1 526

26 591

38 950

36 824

62 505

:

:

4 124

12 637

 897

1 677

2 807

11 617

4 444

3 221

4 490

8 254

17 969

124 939

33 328

282 463

 322

1 204

83 399

68 650

22 242

10 680

59 415

21 170

23 984

47 480

12 345

18 519

11 639

28 961

:

:

:

:

:

:

:

:

:

10 938

:

:

:

8 605

2 077

6 528

 343

6 185

2 784

1 704

1 080

12 369

38 118

328 408

9 737

2 632

22 266

174 270

15 852

154 138

6 812

5 871

941

 251

829

1 458

1 174

8 792

7 060

46 742

107 396

 19

922

2 671

 524

2 147

 172

1 975

1 300

1 277

 23

 2

 21

:

:

:

:

:

:

:

:

:

:

Net migration by main group of citizenship, 2005 1)
1 769 367

  Total

1 776 601

1 499 645

 51 009

  0  36 229

6 734

81 578

 140

66 245

39 974

641 199

205 115

324 211

14 416

-  564

- 8 782

 2 750

17 268

 952 - 22 824

56 400

- 12 878

38 400

- 7 234

6 436

3 403

9 152

26 724

193 314

8 299

-  758

- 1 035

Note: Net migration is estimated on the basis of the difference between total population change and natural increase, i.e. including statistical corrections.

Crude marriage rate (per 1 000 population)
1960

1970

1980

1990

2000

2005

:

7.87

6.75

6.30

5.19

4.88

:

7.89

6.65

6.18

5.15

4.81p

8.05

7.63

6.18

5.87

5.10

4.61

7.13

7.59

6.73

6.48

4.40

4.12

8.76

8.61

7.87

6.87

4.36

4.33

7.72

9.19

7.60

8.80

5.39

5.06

7.84

7.38

5.16

6.13

7.19

6.67

9.46

7.36

6.34

6.50

5.09

4.71

9.99

9.08

8.78

7.50

4.01

4.56

5.47

7.03

6.39

5.08

5.04

4.88

6.98

7.67

6.47

5.81

4.48

5.50

7.78

7.34

5.89

5.68

5.38

4.83

7.00

7.75

6.21

5.06

5.05

4.53

7.72

7.35

5.72

5.64

4.99

4.28

:

8.61

7.63

9.67

14.08

7.76

11.02

10.17

9.80

8.87

3.88

5.45

10.13

9.53

9.23

9.82

4.83

5.84

7.12

6.36

5.90

6.05

4.92

4.44

8.87

9.35

7.50

6.40

4.71

4.39

5.95

7.85

8.76

7.05

6.60

5.88

7.76

9.48

6.37

6.40

5.53

4.52

8.30

7.07

6.15

5.89

4.90

4.75

8.24

8.58

8.64

6.70

5.49

5.42

7.84

9.38

7.39

7.18

6.23

4.61

10.74

7.19

8.23

8.30

6.20

6.56

8.84

8.28

6.51

4.26

3.62

2.88

7.91

7.92

7.95

7.63

4.81

4.85

7.41

8.84

6.15

5.01

5.05

5.58

6.70

5.38

4.52

4.73

4.50

7.51

8.46

7.43

6.56

5.19

4.92 5.23p

8.88

8.46

7.24

5.84

4.96

4.98

8.58

8.96

8.54

8.34

7.03

7.12

:

:

8.23

:

:

9.05

Total fertility rate

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

1960

1970

1980

1990

2000

2005

2.59 e

2.34

1.88

1.64

1.48

2.54

2.25

1.68

1.62

1.66

1.61 p

2.31

2.17

2.05

1.81

1.30

1.31

2.11

1.90

2.10

1.90

1.14

1.28

2.57

1.95

1.55

1.67

1.78

1.80

2.37

2.03

1.56

1.45

1.38

1.34

:

2.16

:

2.05

1.38

1.50

3.76

3.93

3.25

2.09

1.88

1.86

Note: The total fertility rate is the average number of children that would be born alive to a woman during her lifetime if current fertility rates were to continue.

Percentage of live births outside marriage

1960
1970

1980

1990

2000

2003

2005

Crude divorce rate (per 1 000 population)

1960
1970

1980

1990

2000

2005

5.1  e

5.5 e

8.7 e

17.4 e

27.0 p

30.6 p

:

0.6

0.9

1.5

1.7

1.9

:

0.9

1.5

1.6

1.8

0.5

0.7

1.1

1.4

1.7

2.1p

8.1p

2.0p

5.1  e

5.1  e

5.1  e

5.1  e

5.7

9.7

11.6

22.0

31.0 p

:

0.5

0.7

1.5

2

2.6

2.9

8.5

10.9

12.4

38.4

46.1

49.0

:

1.2

1.5

1.3

1.3

1.9

5.5 e

8.7 e

8.6

21.8

28.5

31.7

1.4

2.2

2.6

3.1

2.9

3.1

5.8

9.8

46.4

44.6

44.9

45.7

1.5

1.9

2.7

2.7

2.7

2.8

5.1  e

5.5 e

8.7 e

15.3

23.4

27.0

29.2

1

1.3

1.8

1.9

2.4

2.7p

5.1  e

5.1  e

5.9

9.9

27.1

54.5

57.8

58.5

2.1

3.1

4.1

3.7

3.1

3

5.11

9.11

14.6

31.5 p

31.4

32.0

0

0

:

:

0.7

0.8p

Note: The crude divorce rate is the ratio of the number of divorces to the mean population in a given year.

2.28

2.40

2.23

1.39

1.26

1.33

5.1  e

5.5 e

8.7 e

2.2

4.0 p

4.8

5.1

0.3

0.4

0.7

0.6

1

1.2

2.86

2.90

2.20

1.36

1.23

1.35

2.73

2.47

1.95

1.78

1.88

1.92

5.1  e

5.1  e

5.5 e

8.7 e

30.1

42.6

2.37

2.38

1.64

1.33

1.26

1.31

5.1  e

5.5 e

8.7 e

6.5

9.7 p

45.2 p

13.6 p

47.4

13.8

0.7

0.8

1.5

1.9

1.9

:

0

0

0.2

0.5

0.7

0.8p

5.10

9.10

9.6

17.7 p

23.2 p

26.6

0

0

0

0.6

0.9

1.7p

3.51

2.54

:

:

1.60

1.40

5.1  e

5.12

9.12

0.7

2.3 p

3.5

4.4

:

0.3

0.3

0.6

1.7

2

:

2.01

1.90

2.01

1.24

1.31

5.1  e

5.5 e

8.7 e

16.9

40.3

44.2

44.6

2.4

4.6

5

4

2.6

2.8

2.60

2.40

1.99

2.03

1.39

1.27

5.1  e

5.13

9.13

7.0

22.6

29.5

28.4

0.9

2.2

3.2

3.4

3.1

3.3

2.28

1.76

1.47

1.60

1.76

1.70

5.1  e

5.5 e

8.7 e

12.8

21.9

25.0

27.2

0.5

0.6

1.6

2

2.4

2.3

3.62

2.02

1.99

2.05

1.72

2.02

1.98

1.91

1.87

1.32

1.31 1.48

3.12

2.57

1.60

1.62

1.72

1.71

2.69

2.29

1.65

1.46

1.36

1.40

2.98

2.20

2.28

2.04

1.35

1.24

3.15

3.01

2.25

1.56

1.55

1.40

2.33

2.89

2.50

1.83

1.39

1.32

2.18

2.10

2.11

1.46

1.26

1.26

3.03

2.41

2.31

2.09

1.30

1.25

2.72

1.83

1.63

1.78

1.73

1.80

2.20

1.92

1.68

2.13

1.54

1.77

2.72

2.43

1.90

1.83

1.64

1.78

2.21

1.80

1.93

1.66

1.46

1.41

:

:

:

:

1.88

1.46 2.2

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.1  e

5.4

7.1

13.1

29.0

32.3

35.0

1.7

2.2

2.6

2.4

2.4

2.5

1.5

1.1

1.8

10.9

16.8

20.0

:

:

:

:

:

:

2.1

4.1

11.4

24.9

30.7

34.9

0.5

0.8

1.8

1.9

2.2

2

12.8

17.8

23.6

31.3

35.3

36.5

1.1

1.4

1.8

2.1

2.4

2.4

5.0

4.7

6.2

12.1

15.8

18.5

0.5

1

1.1

1.1

1.1

1.8

7.3

9.2

14.7

22.2

26.9

30.7

0.1

0.1

0.6

0.9

1.9

2.2

:

:

:

25.5

28.2

28.6

2

0.4

1.5

1.4

1.4

1.5

8.5

13.1

24.5

37.1

42.5

46.7

1

1.1

1.2

0.9

1.1

1.3

6.2

5.7

7.6

18.3

23.3

26.0

0.6

0.8

1.3

1.7

1.7

2.1

5.8

13.1

25.2

39.2

40.0

40.4

0.8

1.3

2

2.6

2.7

2.6

18.6

39.7

47.0

55.3

56.0

55.5

1.2

1.6

2.4

2.3

2.4

2.2

8.0

11.5

27.9

39.5

41.5

42.9

0.5

1.1

2.7

2.7

2.7

2.6

:

:

7.0

9.0 p

10.1

10.5

1.2

1.2

1.2

2.3

2

1.1

:

:

:

:

:

:

12.4

0.7

0.3

0.5

0.4

0.7

0.8

6.18

5.68

4.36

2.99

2.52

5.1  e

:

2.9

4.5

:

:

:

0.4

0.3

0.4

0.5

0.5

1.4

EN 

226 

EN 

 
  
 
Proportion of marriages dissolved by divorce, by marriage cohort (%), 2000

1950
1960

1970

1980

1984

:

:

:

:

:

:

:

:

:

:

Note: UK: Scotland and Northern Ireland not included.

Mean marriage duration at divorce by marriage cohort, years, 2000

1950

1960

1970

1980

1984

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

Note: UK: Scotland and Northern Ireland not included.

Population structure for main age groups for selected years  (1 000 inhabitants)

Population aged 0-14            2010

2020

2030

2040

2050

Population aged 15-64          2010

2020

2030

2040

2050

Population aged 65+             2010

2020

2030

2040

2050

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

71 919

69 649

65 839

62 416

60 412

310 537

302 553

287 679

269 804

254 878

81 598

97 068

115 848

130 824

134 541

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

15

29

39

41

:

17.5

17.8

16.3

16.0

1 729

1 694

1 693

1 634

1 599

6 980

6 879

6 574

6 380

6 285

1 846

2 217

2 717

3 015

3 022

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

 952

 845

 679

 622

 588

5 164

4 475

3 915

3 376

2 800

1 322

1 475

1 580

1 646

1 706

1 374

1 364

1 252

1 126

1 118

7 177

6 479

6 157

5 699

5 023

1 571

2 059

2 283

2 495

2 753

:

29

42

46

45

:

14.2

12.9

11.8

12.0

 985

 887

 910

 912

 850

3 589

3 535

3 405

3 256

3 271

 891

1 104

1 263

1 370

1 309

:

18

30

38

38

:

12.5

13.0

12.3

12.5

11 315

10 766

10 303

9 429

8 904

54 593

53 242

48 535

44 644

42 205

16 915

18 669

22 308

24 374

23 533

:

:

:

:

:

:

:

:

:

:

 193

 205

 182

 160

 166

 899

 810

 765

 734

 670

 222

 233

 256

 269

 289

Notes: 1) Population refers to 1st January population of the respective years. 2) Data for France refer to metropolitan France.

Source: 2004-based Eurostat population projections, trend scenario, baseline variant.

Population growth rates (per 100 population) compared to 2004 population for main age groups for selected years (percentage change)

Population aged 0-14            2010

2020

2030

2040

2050

Population aged 15-64          2010

2020

2030

2040

2050

Population aged 65+             2010

2020

2030

2040

2050

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

-3.8

-6.8

-11.9

-16.5

-19.2

1.2

-1.4

-6.2

-12.0

-16.9

8.4

28.9

53.9

73.8

78.7

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

-3.8

-5.8

-5.8

-9.1

-11.0

2.4

0.9

-3.6

-6.4

-7.8

3.7

24.5

52.6

69.3

69.7

-13.9

-23.5

-38.6

-43.7

-46.8

-3.7

-16.5

-27.0

-37.0

-47.8

-0.8

10.6

18.5

23.4

27.9

-11.6

-12.2

-19.4

-27.5

-28.1

-0.8

-10.4

-14.9

-21.2

-30.6

10.4

44.7

60.4

75.3

93.5

-3.2

-12.9

-10.6

-10.4

-16.5

0.4

-1.1

-4.8

-8.9

-8.5

10.8

37.2

56.9

70.3

62.7

-7.0

-11.5

-15.3

-22.5

-26.8

-1.7

-4.1

-12.6

-19.6

-24.0

13.8

25.6

50.1

64.0

58.4

-10.4

-5.2

-15.7

-25.7

-23.1

-1.9

-11.6

-16.5

-19.9

-26.8

1.5

6.7

17.1

23.2

32.5

Notes: 1) Population refers to 1st January population of the respective years. 2) Data for France refer to metropolitan France.

Source: 2004-based Eurostat population projections, trend scenario, baseline variant.

-

-

:

:

:

-

-

:

:

:

 906

 943

 854

 857

 877

2 908

3 113

3 284

3 281

3 166

 509

 700

 928

1 178

1 435

7.7

12.1

1.5

2.0

4.3

6.2

13.7

19.9

19.8

15.6

13.4

56.0

106.7

162.5

219.6

:

6

9

13

14

:

14.4

15.5

13.5

13.5

1 596

1 600

1 428

1 340

1 308

7 557

7 414

7 108

6 489

5 870

2 116

2 413

2 780

3 233

3 454

-0.1

0.1

-10.6

-16.2

-18.2

1.1

-0.8

-4.9

-13.2

-21.4

7.3

22.4

41.1

64.0

75.2

:

3

6

12

14

:

28.6

22.6

16.6

15.4

6 612

6 459

5 313

5 046

4 912

30 297

30 072

28 841

25 656

22 644

7 694

9 027

11 226

13 944

15 278

7.5

5.0

-13.6

-18.0

-20.1

4.3

3.5

-0.7

-11.7

-22.1

7.7

26.4

57.1

95.2

113.9

:

17

29

35

37

:

15.7

15.8

14.4

14.1

11 196

10 911

10 627

10 575

10 350

39 960

39 521

38 720

37 738

37 426

10 330

13 139

15 771

17 683

17 928

0.6

-1.9

-4.5

-4.9

-7.0

2.5

1.4

-0.6

-3.2

-4.0

5.3

34.0

60.8

80.3

82.8

2

3

5

8

9

:

22.1

20.5

17.4

16.9

8 181

7 546

6 619

6 301

5 909

38 414

37 145

34 737

30 690

28 201

12 035

13 608

15 715

18 340

18 599

-0.4

-8.2

-19.4

-23.3

-28.1

-0.3

-3.6

-9.9

-20.4

-26.8

8.2

22.4

41.3

64.9

67.2

:

:

:

:

:

:

:

:

:

:

 130

 134

 141

 128

 130

 549

 583

 588

 606

 590

 105

 149

 193

 219

 255

-11.1

-8.6

-3.8

-12.4

-11.2

10.3

17.3

18.2

21.8

18.7

20.8

71.1

122.2

151.5

193.4

:

:

: :

:

:

:

:

:

:

:

 306

 342

 305

 261

 277

1 544

1 385

1 287

1 224

1 108

 389

 388

 430

 457

 488

-14.0

-4.1

-14.4

-26.8

-22.3

-2.7

-12.7

-18.9

-22.9

-30.2

3.7

3.5

14.5

21.8

30.1

:

:

:

:

:

:

:

:

:

 497

 477

 455

 400

 394

2 308

2 148

1 976

1 863

1 717

 540

 558

 661

 732

 770

-18.3

-21.7

-25.2

-34.3

-35.2

-0.5

-7.4

-14.8

-19.7

-26.0

4.2

7.7

27.6

41.2

48.7

:

14

28

40

41

:

17.1

16.5

13.8

13.5

 85

 88

 98

 103

 107

 322

 347

 356

 369

 394

 70

 86

 112

 136

 142

0.8

4.2

15.9

21.7

25.9

6.4

14.4

17.5

21.8

29.8

9.2

34.8

76.5

112.9

123.5

:

:

:

:

:

:

:

:

:

:

1 461

1 397

1 339

1 258

1 228

6 852

6 325

6 028

5 679

5 182

1 668

1 972

2 118

2 287

2 505

-9.0

-13.0

-16.6

-21.7

-23.6

-1.3

-8.9

-13.2

-18.2

-25.4

6.5

25.8

35.2

45.9

59.9

:

:

:

:

:

:

:

:

:

:

10

16

27

35

37

17.0

17.1

15.7

13.7

13.4

 68

 71

 74

 72

 74

 294

 294

 298

 311

 309

 60

 88

 107

 112

 125

2 972

2 803

2 849

2 869

2 754

11 214

11 168

10 782

10 428

10 568

2 486

3 239

3 957

4 339

4 083

-6.1

-2.0

1.3

-0.9

1.5

7.0

7.1

8.4

13.2

12.4

15.0

69.3

105.7

114.0

140.7

-1.4

-7.1

-5.5

-4.9

-8.7

2.0

1.6

-1.9

-5.1

-3.8

10.4

43.9

75.8

92.8

81.4

:

18

29

37

39

:

11.3

13.1

12.6

12.5

1 230

1 182

1 150

1 061

1 009

5 562

5 569

5 236

4 898

4 705

1 464

1 690

2 135

2 471

2 502

-7.1

-10.7

-13.1

-19.8

-23.7

0.6

0.7

-5.3

-11.4

-14.9

16.1

34.1

69.3

96.0

98.5

:

:

:

:

:

:

:

:

:

:

5 579

5 372

5 172

4 551

4 381

27 159

24 943

23 121

22 062

19 399

5 093

6 750

8 248

8 760

9 885

-15.2

-18.4

-21.4

-30.8

-33.4

1.9

-6.4

-13.3

-17.2

-27.2

2.9

36.3

66.6

76.9

99.6

:

4

11

19

21

:

22.8

20.8

18.0

17.2

1 677

1 625

1 431

1 367

1 311

7 122

6 954

6 638

6 085

5 502

1 888

2 192

2 591

2 973

3 196

1.7

-1.5

-13.2

-17.1

-20.5

0.8

-1.6

-6.0

-13.9

-22.1

7.2

24.4

47.1

68.8

81.5

:

:

:

:

:

:

:

:

:

:

3 231

3 022

2 517

2 254

2 139

14 951

13 848

12 910

11 501

9 920

3 164

3 472

3 817

4 549

5 066

-9.4

-15.3

-29.4

-36.8

-40.0

-0.4

-7.8

-14.0

-23.4

-33.9

1.0

10.8

21.8

45.2

61.7

:

:

:

:

:

:

:

:

:

:

 272

 273

 258

 237

 244

1 410

1 333

1 245

1 170

1 065

 333

 411

 503

 558

 592

-6.6

-6.3

-11.6

-18.6

-16.3

0.4

-5.1

-11.4

-16.7

-24.2

10.8

36.8

67.5

86.0

97.2

:

:

:

:

:

:

:

:

:

:

 801

 751

 703

 632

 609

3 887

3 658

3 405

3 163

2 741

 658

 861

1 078

1 206

1 388

-15.2

-20.5

-25.6

-33.1

-35.5

1.9

-4.1

-10.8

-17.1

-28.2

6.1

38.9

73.8

94.4

123.8

:

23

35

44

49

:

15.7

15.7

15.3

14.6

 872

 871

 859

 812

 796

3 526

3 311

3 161

3 109

3 014

 897

1 224

1 423

1 432

1 407

-5.3

-5.4

-6.6

-11.7

-13.5

1.1

-5.0

-9.3

-10.8

-13.6

10.3

50.5

74.9

76.1

73.1

:

32

42

50

52

:

14.9

14.5

13.4

13.4

1 512

1 637

1 680

1 628

1 664

5 999

5 905

5 943

5 960

6 060

1 677

2 033

2 289

2 472

2 478

-5.5

2.4

5.1

1.8

4.1

2.8

1.2

1.8

2.1

3.8

8.8

31.9

48.5

60.4

60.7

:

23

34

42

43

:

16.4

13.3

11.9

11.5

10 369

10 253

10 145

9 656

9 442

40 413

40 419

39 490

38 310

37 765

10 142

12 258

14 754

16 771

17 123

-4.8

-5.9

-6.9

-11.3

-13.3

3.0

3.1

0.7

-2.3

-3.7

6.3

28.5

54.6

75.7

79.4

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

EN 

227 

EN 

 
  
 
Population structure (percentage of total) for main age groups for selected years

Population aged 0-14            2010

2020

2030

2040

2050

Population aged 15-64          2010

2020

2030

2040

2050

Population aged 65+             2010

2020

2030

2040

2050

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

15.5

14.8

14.0

13.5

13.4

66.9

64.5

61.3

58.3

56.7

17.6

20.7

24.7

28.2

29.9

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

16.4

15.7

15.4

14.8

14.7

66.1

63.8

59.8

57.9

57.6

17.5

20.5

24.8

27.3

27.7

12.8

12.4

11.0

11.0

11.5

69.4

65.9

63.4

59.8

55.0

17.8

21.7

25.6

29.2

33.5

13.6

13.8

12.9

12.1

12.6

70.9

65.4

63.5

61.1

56.5

15.5

20.8

23.6

26.8

30.9

18.0

16.0

16.3

16.5

15.7

65.7

64.0

61.0

58.8

60.2

16.3

20.0

22.7

24.7

24.1

Notes: 1) Population refers to 1st January population of the respective years. 2) Data for France refer to metropolitan France.

Source: 2004-based Eurostat population projections, trend scenario, baseline variant.

Indicators of population structure for main age groups for selected years

Population aged 0-14            2010

2020

2030

2040

2050

Population aged 15-64          2010

2020

2030

2040

2050

Population aged 65+             2010

2020

2030

2040

2050

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

23.2

23.0

22.9

23.1

23.7

26.3

32.1

40.3

48.5

52.8

49.5

55.1

63.2

71.6

76.5

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

24.8

24.6

25.8

25.6

25.4

26.4

32.2

41.3

47.2

48.1

51.2

56.8

67.1

72.8

73.5

18.4

18.9

17.4

18.4

21.0

25.6

33.0

40.4

48.8

60.9

44.0

51.9

57.8

67.2

81.9

19.1

21.1

20.3

19.8

22.2

21.9

31.8

37.1

43.8

54.8

41.0

52.9

57.4

63.6

77.0

27.4

25.1

26.7

28.0

26.0

24.8

31.2

37.1

42.1

40.0

52.2

56.3

63.8

70.1

66.0

13.7

13.0

12.7

12.0

11.9

65.9

64.4

59.8

56.9

56.5

20.4

22.6

27.5

31.1

31.6

20.7

20.2

21.2

21.1

21.1

31.0

35.1

46.0

54.6

55.8

51.7

55.3

67.2

75.7

76.9

14.7

16.4

15.1

13.8

14.8

68.4

64.9

63.6

63.1

59.6

16.9

18.7

21.3

23.1

25.6

21.5

25.3

23.8

21.8

24.8

24.7

28.7

33.4

36.6

43.1

46.2

54.0

57.2

58.4

67.9

21.0

19.8

16.9

16.1

16.0

67.3

65.5

64.8

61.7

57.8

11.7

14.7

18.3

22.2

26.2

31.2

30.3

26.0

26.1

27.7

17.5

22.5

28.3

35.9

45.3

48.7

52.8

54.3

62.0

73.0

14.2

14.0

12.6

12.1

12.3

67.1

64.9

62.8

58.7

55.2

18.7

21.1

24.6

29.2

32.5

21.1

21.6

20.1

20.6

22.3

28.0

32.5

39.1

49.8

58.8

49.1

54.1

59.2

70.4

81.1

14.8

14.2

11.7

11.3

11.5

67.9

66.0

63.6

57.5

52.9

17.3

19.8

24.7

31.2

35.6

21.8

21.5

18.4

19.7

21.7

25.4

30.0

38.9

54.3

67.5

47.2

51.5

57.3

74.0

89.2

18.2

17.2

16.3

16.0

15.8

65.0

62.2

59.5

57.2

57.0

16.8

20.6

24.2

26.8

27.2

28.0

27.6

27.4

28.0

27.7

25.9

33.2

40.7

46.9

47.9

53.9

60.8

68.1

74.9

75.6

14.0

12.9

11.6

11.4

11.2

65.5

63.7

60.9

55.5

53.5

20.5

23.4

27.5

33.1

35.3

21.3

20.3

19.1

20.5

21.0

31.3

36.6

45.2

59.8

66.0

52.6

56.9

64.3

80.3

87.0

16.6

15.4

15.3

13.4

13.3

70.0

67.4

63.8

63.6

60.5

13.4

17.2

20.9

23.0

26.2

23.7

22.9

23.9

21.1

22.0

19.1

25.5

32.9

36.1

43.2

42.8

48.4

56.8

57.2

65.2

13.7

16.2

15.1

13.4

14.8

68.9

65.5

63.7

63.0

59.1

17.4

18.3

21.2

23.6

26.1

19.9

24.7

23.7

21.3

25.0

25.2

28.0

33.4

37.4

44.1

45.1

52.7

57.1

58.7

69.1

14.9

15.0

14.7

13.4

13.7

69.0

67.5

63.9

62.2

59.6

16.1

17.5

21.4

24.4

26.7

21.5

22.2

23.0

21.5

23.0

23.4

26.0

33.4

39.3

44.9

44.9

48.2

56.4

60.8

67.9

17.9

17.0

17.3

17.0

16.6

67.5

66.6

62.9

60.7

61.3

14.6

16.4

19.8

22.3

22.1

26.5

25.5

27.6

27.9

27.1

21.6

24.7

31.5

36.7

36.1

48.1

50.2

59.1

64.6

63.2

14.6

14.4

14.1

13.6

13.8

68.6

65.2

63.6

61.6

58.1

16.8

20.4

22.3

24.8

28.1

21.3

22.1

22.2

22.1

23.7

24.3

31.2

35.1

40.3

48.3

45.6

53.3

57.3

62.4

72.0

16.2

15.7

15.4

14.6

14.5

69.6

64.8

62.2

62.9

60.8

14.2

19.5

22.4

22.5

24.7

23.3

24.3

24.8

23.2

23.9

20.4

30.0

36.0

35.9

40.6

43.7

54.3

60.8

59.1

64.5

17.8

16.3

16.2

16.3

15.8

67.3

64.9

61.3

59.1

60.7

14.9

18.8

22.5

24.6

23.5

26.5

25.1

26.4

27.5

26.1

22.2

29.0

36.7

41.6

38.6

48.7

54.1

63.1

69.1

64.7

14.9

14.0

13.5

12.6

12.3

67.4

66.0

61.5

58.1

57.3

17.7

20.0

25.0

29.3

30.4

22.1

21.2

22.0

21.7

21.5

26.3

30.3

40.8

50.4

53.2

48.4

51.5

62.8

72.1

74.7

14.7

14.5

14.2

12.9

13.0

71.8

67.3

63.3

62.4

57.6

13.5

18.2

22.5

24.7

29.4

20.5

21.5

22.4

20.6

22.6

18.8

27.1

35.7

39.7

51.0

39.3

48.6

58.1

60.3

73.6

15.7

15.1

13.4

13.1

13.1

66.6

64.6

62.3

58.4

55.0

17.7

20.3

24.3

28.5

31.9

23.5

23.4

21.6

22.5

23.8

26.5

31.5

39.0

48.9

58.1

50.0

54.9

60.6

71.4

81.9

15.1

14.9

13.1

12.3

12.5

70.0

68.1

67.1

62.8

57.9

14.9

17.0

19.8

24.9

29.6

21.6

21.8

19.5

19.6

21.6

21.2

25.1

29.6

39.6

51.1

42.8

46.9

49.1

59.2

72.7

13.5

13.5

12.9

12.1

12.8

70.0

66.1

62.1

59.5

56.0

16.5

20.4

25.0

28.4

31.2

19.3

20.5

20.7

20.3

22.9

23.6

30.8

40.4

47.7

55.6

42.9

51.3

61.1

68.0

78.5

15.0

14.2

13.5

12.6

12.8

72.7

69.4

65.7

63.2

57.9

12.3

16.4

20.8

24.2

29.3

20.6

20.5

20.6

20.0

22.2

16.9

23.5

31.7

38.1

50.6

37.5

44.0

52.3

58.1

72.8

16.5

16.1

15.8

15.2

15.3

66.6

61.3

58.1

58.1

57.8

16.9

22.6

26.1

26.7

26.9

24.7

26.3

27.2

26.1

26.4

25.4

37.0

45.0

46.1

46.7

50.1

63.3

72.2

72.2

73.1

16.5

17.1

16.9

16.2

16.3

65.3

61.7

60.0

59.2

59.4

18.2

21.2

23.1

24.6

24.3

25.2

27.7

28.3

27.3

27.5

28.0

34.4

38.5

41.5

40.9

53.2

62.1

66.8

68.8

68.4

17.0

16.3

15.8

14.9

14.7

66.3

64.2

61.3

59.2

58.7

16.7

19.5

22.9

25.9

26.6

25.7

25.4

25.7

25.2

25.0

25.1

30.3

37.4

43.8

45.3

50.8

55.7

63.1

69.0

70.3

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

Notes: 1) Population refers to 1st January population of the respective years. 2) Data for France refer to metropolitan France. 3) Young age dependency ratio: Population aged between 0-14 as a percentage of population aged between 15 and 64.

4) Old age dependency ratio: Population aged 65 and more as a percentage of population aged between 15 and 64. 5) Total age dependency ratio: Sum of young age and old age dependency ratios.

Source: 2004-based Eurostat population projections, trend scenario, baseline variant.

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

2 POPULATION

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium

Bulgaria

Czech 
Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia

Lithuania

Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria

Poland

Portugal

Romania Slovenia Slovakia

Finland

Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EN 

228 

EN 

 
  
3  EDUCATION AND TRAINING

European
Union - 27

European
Union - 
25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EU-27

EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Training enterprises as a percentage of all enterprises by size class, 1999

10-49 employees

50-249 employees

250 or more employees

All size classes

:

:

:

:

:

:

:

:

:

:

:

:

66

93

100

282 f

24

34

62

19 f

Percentage of employees of all enterprises participating in CVT courses by gender, 1999

Total

Males

Females

:

:

:

:

:

:

:

:

:

Hours in CVT courses per participant by economic activity (*), 1999

NACE D

NACE G

NACE J

NACE K

NACE O

Other

Total

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

41

: 

: 

29

29

34

38

31

28

31

13

16

5.5 f

19

35

20

50

72

46

35

62

84

96

69

42

46

35

24

24

41

46

22

20

25

95

98

100

96

53

52

54

41

30

41

60

42

42

41

71

87

98

75

32

34

29

29

21

35

40

15

20

27

58

85

96

9 f

75

98

100

146 f

19

18

5.9 f

26

42

46

32

19

26

31

41

40

43

40

32

28

41

59

43

40

11

43

78

18

15

14

16

49

32

34

43

44

38

39

31

58

86

70

93

98

793 f

1625 f

25

25

26

46

36

44

43

54

38

42

46

48

44

33

25

37

36

38

49

36

20

48

81

24

26

27

23

30

32

35

43

39

30

32

:

:

:

:

:

:

:

:

:

:

:

:

:

:

49

70

91

53

12

13

12

31

26

32

56

27

34

34

37

60

80

43

10

10

9

39

45

29

48

19

45

41

67

83

99

71

36

34

4.0 f

47

26

43

53

37

28

39

32

51

79

37

12

13

11

34

42

19

47

30

44

38

:

:

:

:

:

:

:

:

:

:

:

:

:

:

85

96

98

465 f

41

44

1.4 f

39

35

48

43

26

32

37

68

91

96

72

31

31

32

28

26

49

33

15

25

29

36

52

63

39

16

17

15

24

29

36

43

27

25

28

17

46

78

22

17

17

17

44

24

55

44

38

34

38

8

13

38

57 f

8

8

7.2 f

33

31

27

57

45

56

42

35

72

96

48

32

32

33

20

14

27

47

34

31

24

:

:

:

:

:

:

:

:

:

:

:

:

:

:

78

97

99

82

50

48

53

35

26

38

49

31

36

36

88

99

99

91

61

60

61

34

23

26

36

26

28

31

85

91

98

87

49

50

46

29

15

27

41

15

26

26

:

:

:

27 f

:

:

3.8 f

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

(*) NACE D:  Manufacturing, NACE G: Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods, NACE J: Financial intermediation, NACE K: Real estate, renting and business activities, NACE O: Other community, social and personal service activities, Other (C, E, F, H, I) Mining and quarrying; Electricity, 
gas, water; Construction; Hotels and restaurants; Transport, communication.

Percentage of employees in small and large enterprises with and without 'a joint agreement' participating in CVT courses, 1999

small - with

small - without

large - with

large - without

:

:

:

:

:

:

:

:

:

:

:

:

48

23

61

57

25

4

31

12

45

22

58

44

57

45

56

54

40

24

50

30

27

11

28

29

57

26

59

57

14

2

31

23

39

9

50

31

44

22

65

54

34

9

58

37

:

:

:

:

34

7

25

14

24

4

23

13

49

19

55

44

18

6

26

16

:

:

:

:

53

29

45

37

: 

: 

45

36

23

8

25

27

38

4

52

30

14

1

18

6

30

13

57

42

:

:

:

:

53

39

67

52

65

47

70

62

52

31

52

52

:

:

:

:

:

:

:

:

Source: Eurostat - Continuing Vocational Training Survey 2 (CVTS2)

EU-27

EU-25 EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

3  EDUCATION AND TRAINING European

Union - 27

European
Union - 
25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

:

:

:

244 f

:

:

8.5 f

:

:

:

:

:

:

:

:

:

:

:

EN 

229 

EN 

 
  
 
 
4  LABOUR MARKET

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of 
Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Total employment (thousands)

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Self-employed in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Part-time workers in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

213602

215619

218991

94280

95527

97308

119322

120092

121683

16.5

16.3

16.2

12.7

12.5

12.3

19.6

19.3

19.2

17.2

17.8

18.1

30

30.9

31.2

7

7.4

7.7

Temporary contract workers in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Services in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

13.2

13.9

14.3

13.8

14.4

14.9

12.7

13.5

13.9

68.1

68.4

68.7

80.7

81.2

81.6

57.8

58.1

58.2

201054

202962

205994

88492

89749

91343

112563

113213

114651

137340

138439

140386

59169

60137

61237

78172

78302

79149

4172

4212

4259

1799

1839

1870

2373

2374

2389

15.6

15.3

15.3

11.6

11.4

11.3

18.8

18.5

18.4

17.7

18.4

18.8

31.4

32.4

32.7

7

7.4

7.7

13.7

14.4

14.9

14.3

15

15.5

13.2

14

14.4

69.8

70.1

70.3

83

83.4

83.7

59.2

59.4

59.4

15.5

15.3

15.3

11.7

11.6

11.5

18.3

18.2

18.2

17.7

18.9

19.5

32.9

34.5

35.1

6.3

6.9

7.4

15.3

16.2

16.7

16.3

17

17.6

14.5

15.5

15.9

70

70.3

70.6

83.6

84.1

84.5

59.4

59.5

59.5

16.3

16.3

16.3

13.1

13.1

12.7

18.7

18.7

19

21.4

22

22.2

40.5

40.5

41.1

6.8

7.6

7.4

8.7

8.9

8.7

11.7

11.4

10.9

6.4

6.8

6.9

77.1

77.4

77.5

89.4

89.2

89.9

67.5

68

67.6

3403

3495

3580

1598

1629

1677

1805

1866

1902

28.5

27.8

27.8

21.9

21.9

21.3

34.4

32.9

33.5

2.4

2.1

2

2.7

2.5

2.5

2.1

1.7

1.5

7.4

6.4

6.2

7

6.2

6.1

7.7

6.7

6.3

51.1

51.6

51.8

58.7

59.7

60.5

44.6

44.7

44.3

4945

4993

5076

2155

2158

2193

2791

2836

2883

18.8

18

18

12.1

11.7

12.1

23.9

22.8

22.4

4.9

4.9

5

8.3

8.6

8.7

2.3

2.1

2.2

9.1

8.6

8.7

10.7

9.8

10.1

7.8

7.6

7.5

57.6

57.9

58.4

70.9

71.1

71.5

47.3

47.9

48.5

2748

2767

2822

1278

1290

1317

1470

1478

1505

38879

38822

39092

17484

17671

17813

21394

21151

21278

6.4

6.3

6.4

3.8

3.8

4.1

8.7

8.5

8.5

22.2

22.1

23.6

33.8

33

35.4

12.1

12.7

13.3

9.5

9.8

8.9

10.3

11.3

10

8.7

8.5

8

75.8

76

76

87.9

87.7

88.1

65.3

65.7

65.3

10.9

11.2

11.2

7.9

8.5

8.5

13.3

13.5

13.5

22.3

24

25.8

41.6

43.5

45.6

6.5

7.8

9.3

12.4

14.1

14.5

12.2

13.8

14.1

12.7

14.4

14.7

71.3

71.9

72.3

84.3

84.6

84.9

60.2

61

61.5

592

604

637

295

305

319

298

299

318

9.6

8.1

8.1

6.3

5.1

4.8

12.9

11.1

11.4

8

7.8

7.8

10.6

10.6

11.3

5.4

4.9

4.3

2.6

2.7

2.7

1.8

2

2.2

3.5

3.4

3.3

59.5

61

62

71

72.5

75.5

48

49.1

48.3

1870

1958

2042

787

831

868

1084

1127

1175

4313

4369

4452

1642

1672

1725

2671

2697

2727

18503

24977

24256

19212

25089

24333

19848

25278

24754

7245

7680

8046

11475

11582

11707

9509

9517

9744

11258

13502

14747

11532

13506

14816

11802

13571

15010

17.6

16.9

16.4

7.5

7.1

6.7

25

24.2

23.5

16.8

:

:

31.5

:

:

6.1

:

:

4.1

3.7

3.4

4.6

4.2

3.9

3.7

3.1

2.9

66.2

66.5

66.7

86

86.8

87.4

51.8

51.5

51.4

40.6

40.8

40.7

35.5

36

35.7

43.8

43.7

43.8

4.6

5

5.7

8.5

9.3

10.2

2.2

2.3

2.9

11.9

11.8

10.7

14

14.3

13

10.5

10.1

9.1

62.6

62.7

:

72.9

73.5

:

56.3

56

:

14.8

14.6

14.5

11.8

11.7

11.2

16.8

16.6

16.8

8.7

12.4

12

17.9

24.2

23.2

2.8

4.5

4.3

32.5

33.3

34

35.2

35.7

36.7

30.6

31.7

32

65.1

65.3

65.4

84

84.4

85.1

52.6

52.5

52

8.8

8.9

8.9

6.2

6.1

6.1

11

11.3

11.4

16.7

17.2

17.2

30.1

30.7

30.6

5.3

5.7

5.7

12.8

13.3

13.5

14

14

14

11.8

12.6

13

75.6

75.9

76.2

87.4

87.9

88.5

65.3

65.3

65.2

25.7

24.6

24.3

20.3

18.9

18.8

29.1

28.2

27.9

12.7

12.8

13.3

25

25.6

26.5

4.8

4.6

4.7

11.8

12.3

13.1

14.5

14.7

15.8

9.9

10.5

11.2

67

67.3

67.5

80.1

80.9

81.3

58.2

58.2

58.3

354

366

372

154

159

164

200

208

209

22.6

22.1

20.6

15.2

15.3

14.2

28.2

27.3

25.6

8.6

8.9

7.7

13.6

14

12.1

4.8

5

4.3

12.9

14

13.1

17.7

19.5

19

8.5

9

7.9

74.1

74.7

75.2

86.7

87.5

87.7

64

64.6

65.5

1008

1024

1073

492

496

523

516

528

550

1425

1461

1486

698

717

737

728

744

749

13.2

11.6

11.7

12.1

9.7

9.9

14.3

13.4

13.4

10.4

8.3

6.5

13.2

10.4

8.3

7.7

6.3

4.7

9.5

8.4

7.1

7.3

6.2

5.4

11.6

10.7

8.8

60.9

62.3

61.5

72.9

75.4

75.9

49.5

50

48

18.7

17.1

15.8

16.3

14.7

13.9

21

19.4

17.8

8.4

7.1

9.9

10.5

9.1

12

6.5

5.1

7.9

6.3

5.5

4.5

3.9

3.6

2.7

8.7

7.6

6.4

56.2

57.1

58.1

66.5

68

70.5

46.3

46.5

45.9

299

307

318

123

129

137

176

179

181

6.7

6.5

6.2

5.5

5.7

5.1

7.5

7.1

7.1

16.4

17.4

17.1

36.3

38.2

36.2

2.5

2.5

2.6

4.8

5.3

6.1

5.8

5.8

6.6

4.1

4.9

5.7

77.4

77.6

77.9

91

91.6

92

68.8

68.7

68.7

3879

3879

3905

1773

1775

1781

2106

2104

2124

14.2

13.8

12.7

10.1

9.8

9.1

17.7

17.1

15.8

4.7

4.1

4

6.3

5.8

5.6

3.2

2.7

2.6

6.8

7

6.7

6.1

6.4

6

7.5

7.6

7.4

62

62.7

63

74.9

76.1

76.4

51.1

51.4

51.6

150

153

154

45

47

49

105

106

106

11.7

11.7

11.8

5.3

5.2

5

14.5

14.7

14.9

8.7

9.6

10.1

19.3

21.1

21.8

4.1

4.5

4.8

4

4.5

3.8

5.8

6.1

6

3.1

3.7

2.7

:

:

:

:

:

:

:

:

:

8205

8208

8306

3636

3672

3729

4569

4537

4577

4139

4158

4198

1860

1880

1903

2279

2278

2295

13795

14116

14577

6230

6307

6506

7565

7809

8072

5123

5123

5160

2339

2357

2370

2784

2765

2790

9103

9115

9291

4178

4135

4239

4926

4979

5052

13.8

14.1

13.9

11

11.1

10.8

16.1

16.6

16.5

45.5

46.1

46.2

74.7

75.1

74.7

22.3

22.6

23

14.8

15.5

16.6

16.5

16.9

18

13.4

14.3

15.4

79.1

79.4

79.8

90.8

90.9

91.2

69.6

70

70.4

19.9

19.4

18.8

16.1

15.9

15.8

23

22.3

21.4

19.8

21.1

21.8

38

39.3

40.2

4.9

6.1

6.5

9.6

9.1

9

9

8.8

8.9

10.2

9.3

9.1

64.8

65.1

65.9

76.6

77.6

78.2

54.7

54.4

55.2

26.7

25.8

25.7

24.1

23.1

22.9

28.9

27.9

28

10.8

10.8

9.8

14

14.3

13

8.2

8

7.1

22.7

25.7

27.3

21.5

24.7

26

23.7

26.5

28.5

53.9

53.9

53.9

65.5

65.7

65.9

44.2

44.2

44.1

26.2

25.6

24.4

24

23.9

23

27.9

26.9

25.7

11.3

11.2

11.3

16.3

16.2

15.8

7.1

7

7.4

19.8

19.5

20.6

21.1

20.4

21.7

18.7

18.7

19.5

:

:

:

:

:

:

:

:

:

31.5

32.2

31

31.1

31.7

30.2

31.8

32.7

31.8

10.6

10.2

9.7

11.2

10.5

9.8

10.2

10

9.5

2.5

2.4

1.8

2

1.9

1.6

2.9

2.8

2

36.4

:

:

40.9

:

:

32.5

:

:

943

949

961

430

434

438

513

516

524

17.1

16.9

16.7

14.3

14.1

13.7

19.5

19.2

19.2

9.3

9

9.2

11

11.1

11.6

7.9

7.2

7.2

17.8

17.4

17.3

19.1

19.3

19.3

16.7

15.7

15.5

54

54.5

55.3

65.6

66.3

67.8

44.4

44.9

45.3

2168

2215

2302

977

983

1010

1191

1232

1292

12.3

13

13

7.2

7.1

7.5

16.4

17.6

17.2

2.7

2.5

2.8

4.2

4.1

4.7

1.4

1.3

1.3

5.5

5

5.1

5.1

4.9

5.2

6

5.1

5

61

62.6

62.7

74.3

75.9

76.5

49.4

51.3

51.3

2365

2398

2432

1136

1156

1172

1229

1241

1260

4311

4327

4404

2066

2057

2087

2245

2270

2318

28467

28732

28961

13169

13343

13473

15297

15389

15488

1561

1573

1605

696

706

727

865

867

878

11.8

11.7

11.9

7.9

7.8

7.8

15.3

15.3

15.8

13.5

13.7

14

18.4

18.6

19.2

9

9.2

9.3

16.1

16.5

16.4

19.5

20

20

12.6

12.9

12.6

69

69.1

69.3

84.6

84.8

85.3

54.6

54.5

54.3

4.7

4.7

4.7

2.5

2.5

2.5

6.8

6.7

6.7

23.6

24.7

25.1

36.3

39.6

40.2

12

11.5

11.8

15.5

16

17.3

17.5

17.7

19.1

13.5

14.2

15.4

75.2

75.4

75.7

89.3

89.5

89.6

61.7

62.4

62.8

12.8

12.7

13

7.6

7.7

8

17.2

17.1

17.3

25.8

25.4

25.5

43.9

42.7

42.6

10.3

10.4

10.6

6

5.7

5.8

6.5

6.2

6.4

5.5

5.2

5.1

:

:

:

:

:

:

:

:

:

23.4

23.8

21.2

22.5

23.2

19.6

24.2

24.2

22.5

8.5

10.1

9.4

11.2

13.4

11.7

6.3

7.3

7.5

12.2

12.4

12.9

12.4

12.3

12.6

12.1

12.4

13.1

53.7

:

:

63.9

:

:

45.5

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

21794

22103

22373

5768

5732

5822

16026

16371

16552

:

:

:

:

:

:

:

:

:

6.9

5.9

7.9

15.3

13.5

17.8

3.9

3.3

4.4

:

:

13.3

:

:

13.1

:

:

13.3

:

:

:

:

:

:

:

:

:

Industry in % of total employment

EN 

230 

EN 

 
  
 
Industry in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Agriculture in % of total employment

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Total unemployment (thousands)

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

Youth unemployment rate (15 to 24 years)

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

25.4

25.1

25

13.7

13.4

13.1

34.8

34.7

34.7

6.6

6.4

6.3

5.5

5.4

5.3

7.4

7.2

7.1

20694.9

20094.4

18434.8

10279.3

9992.1

9216.1

10415.6

10102.3

9218.7

18.9

18.4

17.3

19.6

18.7

18

18.4

18.1

16.7

Very long-term unemployment (24 months or more) in % active population

Total 2004
Total 2005

Total 2006

Females 2004

Females 2005

Females 2006

Males 2004

Males 2005

Males 2006

2.4

2.3

2.1

2.7

2.6

2.3

2.1

2.1

1.9

2.3

2.3

2.1

2.7

2.6

2.3

2

2

1.9

25.1

24.9

24.7

13

12.7

12.4

34.9

34.7

34.7

5.1

5

4.9

4

3.9

3.8

5.9

5.9

5.9

25.5

25.3

25.1

13

12.6

12.3

35.4

35.3

35.3

4.5

4.4

4.3

3.4

3.3

3.2

5.3

5.2

5.1

20.9

20.6

20.5

9.2

9.3

8.8

30

29.5

29.8

2

2

2

1.4

1.4

1.3

2.5

2.4

2.5

26.6

27

27.6

23.8

23.5

23.5

29

30

31.1

22.3

21.4

20.6

17.5

16.8

15.9

26.4

25.3

24.6

38.4

38.3

37.9

26.3

26.2

25.8

47.8

47.5

47.1

4

3.8

3.7

2.8

2.7

2.7

4.9

4.6

4.4

21

20.9

20.9

10.7

10.8

10.4

30.2

29.9

30.2

3.1

3.1

3.1

1.5

1.5

1.4

4.6

4.4

4.5

26.4

25.9

25.5

14.1

13.8

13.6

37

36.3

35.8

2.2

2.2

2.2

1.6

1.6

1.5

2.8

2.7

2.7

19495.3

19055.5

17400.6

9792.6

9556.3

8790.7

9702.7

9499.2

8609.9

12882.4

12659.7

11734

6689.9

6520

6105.9

6192.6

6139.7

5628.1

379.1

390.4

383.2

188.2

194.2

192.2

190.9

196.2

191

400

334.4

305.7

178

151.6

149.3

222

182.8

156.4

425.7

410.2

371.7

224.5

223.5

202.4

201.2

186.7

169.2

159.6

139.7

113.8

81.2

71.5

62.2

78.4

68.2

51.6

3931

3892.7

3431.8

1955.7

1906.8

1690.6

1975.3

1985.8

1741.2

18.7

18.3

17.1

19.5

18.7

17.9

18

17.9

16.5

17.9

17.4

16.5

19.5

18.6

18

16.6

16.4

15.2

2.4

2.2

2.2

2.9

2.7

2.5

2

1.9

1.9

21.2

21.5

20.5

22.4

22.1

22.6

20.2

21

18.8

2.6

2.9

2.8

3.1

3.4

3.3

2.3

2.5

2.5

25.8

22.3

19.5

24.3

21

20.3

27

23.4

18.9

5.2

4.3

3.6

5.2

4.3

3.7

5.2

4.3

3.5

21

19.2

17.5

19.5

19.1

18.7

22.2

19.3

16.6

2.6

2.6

2.4

3.3

3.2

3

2.1

2.1

1.9

8.2

8.6

7.7

7.4

8.6

7.5

8.9

8.6

7.9

0.4

0.4

0.3

0.4

0.4

0.3

0.4

0.4

0.3

14.4

14.1

13.6

14.5

13.8

14

14.3

14.4

13.2

3.4

3.2

3.2

4

3.6

3.5

3

3

2.9

34.7

33.7

33.1

25.4

24

21.4

44

43.7

45

5.8

5.3

4.9

3.6

3.5

3.1

8

7.2

6.6

63.6

52.2

40.5

28.9

23.3

19.2

34.7

28.9

21.3

21.7

15.9

12

22.4

14.9

14.7

21.2

16.6

10

3.3

2.8

1.7

3

2.7

1.4

3.5

2.8

1.9

27.6

27.6

27.6

12.6

11.9

11.3

38.5

39.2

39.6

6.2

5.9

5.7

1.4

1.3

1.3

9.8

9.3

9

22.9

22.9

:

10.9

10.5

:

30.3

30.7

:

14.5

14.4

:

16.2

16

:

13.5

13.4

:

29.5

29.5

29.6

12.4

12.1

11.4

40.8

41.2

42

5.4

5.2

5

3.6

3.5

3.4

6.6

6.4

6.1

20.8

20.5

20.4

10.1

9.9

9.4

30.1

29.9

30.1

3.6

3.6

3.4

2.5

2.2

2.1

4.6

4.7

4.7

28.8

28.6

28.4

16.6

16

15.6

36.9

37

37

4.2

4.1

4.1

3.3

3.1

3.1

4.9

4.8

4.7

88.5

505.6

2143.8 2631.2 1960.4

89

93.4

33.3

34.9

37.1

55.2

54.1

56.3

477.3

1912.5 2681.5 1888.6

434.5

1837.1 2646.5 1673.4

317.5

1192.1 1349.7 1035.6

301.8

1049.6 1380.3

986.2

272.1

1045.6 1352.6

872.7

188.2

175.5

162.4

951.7

1281.5

924.8

862.9

1301.3

902.4

791.5

1293.9

800.7

8.9

8.6

8.6

8.5

8

8

9.3

9.1

9.1

0.8

0.8

0.7

0.4

0.4

0.4

1.1

1.1

1

26.9

26

25.2

36.3

34.8

34.7

19.1

18.7

17.7

3.1

3

2.7

5.3

5.2

4.6

1.6

1.4

1.3

23.9

19.7

17.9

30.1

23.4

21.6

19.4

16.7

15

1.8

1.1

0.9

2.8

1.7

1.4

1.1

0.7

0.5

21.9

22.7

23.2

23.1

24.4

25.3

20.9

21.3

21.7

1.9

2

2

2

2.2

2.2

1.7

1.8

1.9

23.5

24

21.6

27.2

27.4

25.3

20.6

21.5

19.1

2.6

2.4

2.1

3.6

3.2

2.7

2

1.8

1.6

20.4

20.3

20.5

9.2

8.8

9.4

29.3

29.3

29.2

5.5

5

4.2

4.1

3.6

2.9

6.6

6.1

5.3

16.4

19.2

17.3

9.3

10.4

9

7.1

8.8

8.3

10.5

13

10.4

11.6

14.2

11.2

9.4

11.9

9.7

0.4

0.4

0.3

0.6

0.7

0.3

0.3

0.3

0.3

26.5

26.5

27

17.5

16.9

15.8

35.2

35.5

37.5

12.5

11.2

11.5

9.6

7.7

8.3

15.4

14.5

14.5

28

28.9

29.5

20.2

20.7

19.4

35.6

36.9

39.6

15.8

14

12.4

13.3

11.3

10.1

18.2

16.6

14.6

21.3

21.1

20.8

7.9

7.6

7.1

29.7

29.7

29.8

1.3

1.3

1.3

1

0.9

0.9

1.4

1.5

1.5

118.3

184.1

10.1

101

79.5

56.4

47.9

34.8

61.9

53.1

44.7

18.1

13.6

12.2

21.3

16.2

14.7

16

11.8

10.5

2.6

2.7

1.5

2.6

2.4

1

2.7

3.1

1.9

133

89.4

93.7

65.8

42.7

90.5

67.1

46.8

22.7

15.7

9.8

22.9

15.3

9.6

22.5

15.9

10

3.7

2.9

1.5

4

2.9

1.4

3.4

2.8

1.6

9.1

9.7

5.9

5

5.6

4.2

4.1

4.1

16.8

13.7

16.2

22.3

16.2

15.2

12

11.7

17

0.3

0.4

0.4

0.3

0.3

0.5

0.3

0.5

0.4

32.9

32.4

32.3

22.6

21.2

20.9

41.6

41.9

41.8

5.1

4.9

4.8

2.6

2.7

2.7

7.3

6.8

6.6

252.5

302.2

316.7

115.7

143.2

152.1

136.8

158.9

164.6

15.5

19.4

19.1

14.4

19

19.8

16.2

19.6

18.6

1.3

1.5

1.5

1.2

1.4

1.4

1.3

1.6

1.6

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

11.7

11.7

12

4.4

4.5

4.7

7.4

7.1

7.3

16.8

16.4

16.3

17.4

16

14.8

16.3

16.8

17.5

1.9

1.6

1.4

1.5

1

0.8

2.1

1.9

1.7

17.7

17.4

17

7.1

7

6.8

26.1

25.9

25.5

3.3

3.2

3.1

2.1

2.1

2

4.2

4.1

4.1

22.8

23.1

23

10.7

10.7

10.7

33.1

33.8

33.7

12.4

11.8

11.1

12.7

11.7

11.1

12.2

11.9

11.1

26.9

26.9

26.9

16.2

16

16.1

35.7

35.8

35.8

19.2

19.2

19.2

18.2

18.2

18.1

20.1

20

20.2

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

30.6

:

:

25.6

:

:

35

:

:

33

:

:

33.5

:

:

32.5

:

:

387.1

402.1

335.7

182.9

193.6

169.1

204.2

208.5

166.6

188.4

3230.3

365

208.3

3045.4

422.3

195.8

2344.3

427.8

94.2

1549.6

192.2

101.4

1492.5

224.1

799.6

704.5

728.4

308.7

284.1

97.9

94.2

107

97.9

1142.1

233.1

276

1680.6

172.9

1552.9

198.1

1202.2

194.8

490.8

420.3

452.5

8

8.2

6.6

8.1

8.4

7.1

7.9

8

6.1

0.6

1

0.9

0.7

0.9

0.9

0.6

1

0.9

9.4

10.3

9.1

9.8

10.1

9.2

9

10.5

9

0.5

0.7

0.7

0.5

0.7

0.7

0.5

0.7

0.7

39.6

36.9

29.8

41.9

38.3

31.6

37.7

35.7

28.3

5

5.3

4.1

5.5

5.8

4.5

4.7

4.8

3.8

15.3

16.1

16.3

17.6

19.1

18.4

13.5

13.6

14.5

1.5

1.9

2.2

1.8

2.3

2.6

1.3

1.6

1.9

21.9

20.2

21.4

18.9

18.4

20.2

24.2

21.6

22.3

3.3

2.5

2.2

2.6

2

2

3.9

3

2.4

35.7

35.4

35.1

24.1

23.5

22.7

45.3

45.2

45

10.3

10.1

9.7

10.3

10.2

9.5

10.3

10

9.8

63.3

66

60.8

31.4

32.8

33.9

31.9

33.2

26.9

16.1

15.9

13.9

19.2

17.8

16.8

13.9

14.5

11.6

1.8

1.8

1.7

1.9

1.9

2

1.8

1.7

1.5

34.6

33.7

33.8

23.3

22.1

21.7

44.5

43.5

43.8

4.4

3.7

3.6

2.4

2

1.9

6.1

5.1

5

25.8

25.8

25.8

12.3

12.2

11.8

38.3

38.6

38.9

5.2

5.1

4.9

3.1

3.1

3

7.1

6.9

6.8

22.6

22.4

22.3

9.8

9.5

9.5

34.8

34.3

34.1

2.2

2.2

2.1

0.9

1

0.9

3.5

3.3

3.2

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

483

430

355.4

231.8

204.7

174.6

251.2

225.4

180.8

228.8

219.7

204.3

111.3

109.1

103.5

117.6

110.6

100.8

295.5

1372

343

1408.5

330.3

1595.7

135.5

160.3

160.1

160

182.7

170.2

571.7

588.8

680.9

800.3

819.8

914.8

33.1

30.1

26.6

31

28.8

27

34.7

31

26.4

8.2

8.4

7.9

8.8

8.7

8.3

7.7

8.1

7.5

20.7

20.1

18.7

19.4

19.5

18.4

22

20.6

19

1

1

1

0.8

0.9

0.8

1.1

1.2

1.1

16.3

21.1

21.3

16.9

21.1

21.5

15.7

21.1

21.1

0

0.4

0.4

:

0.3

0.3

0

0.5

0.5

12.1

12.9

14.1

10.7

11.1

12.1

13.4

14.5

15.9

0.5

0.5

0.6

0.3

0.3

0.3

0.6

0.7

0.8

29.9

:

:

18.6

:

:

38.9

:

:

16.5

:

:

17.5

:

:

15.6

:

:

:

:

:

:

:

:

:

:

:

33.2

32.3

28.9

38.2

35.1

31.1

29.4

30.2

27.2

5.7

5.5

5.1

6.9

6.3

5.9

4.7

4.9

4.5

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

2479.3

2508.8

2442.8

615

647

670.3

1864.3

1861.8

1772.5

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

0

0

0

0

0

0

0

0

0

17.3

16.8

16

16.4

16.6

16.5

17.8

16.9

15.8

1.8

1.9

1.3

1.9

2.1

1.7

1.7

1.8

1.1

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

4  LABOUR MARKET

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of 
Macedonia

Turkey

EN 

231 

EN 

 
  
 
5  SOCIAL PROTECTION

European
Union - 
27

European
Union - 25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Expenditure on social protection in PPS per head of population

2004

:

6 188

6 887

7 890

Structure of social protection expenditure, 2004

Total social benefits

Administration costs

Other expenditure

Social benefits by group of functions, 2004

Old age and survivors benefits

% total social benefits

% GDP
Sickness, health care 

% total social benefits

% GDP
Disability

% total social benefits

% GDP

Unemployment

% total social benefits

% GDP

Family and children

% total social benefits

% GDP

:

:

:

:

:

:

:

:

:

:

:

:

:

Housing and social exclusion not elsewhere classified

% total social benefits

% GDP

:

:

96.2

95.6

95.3

3.1

0.7

3.4

1.0

3.4

1.3

45.9

12.0

28.3

7.4

8.1

2.1

6.5

1.7

7.8

2.1

3.4

0.9

46.5

12.3

28.2

7.5

7.3

1.9

7.4

2.0

7.9

2.1

2.7

0.7

44.1

12.3

27.7

7.7

6.8

1.9

12.5

3.5

7.1

2.0

1.8

0.5

Receipts of social protection by type (as a percentage of total receipts)

General government contributions

2000

2004

Employers' social contributions

2000

2004

Social contributions paid by protected persons

2000

2004

Other receipts

2000

2004

: 

: 

: 

: 

: 

: 

: 

: 

35.4

37.3

38.7

38.6

22.3

20.9

3.7

3.2

31.6

33.7

41.5

40.6

22.8

22.4

4.0

3.3

25.3

27.0

49.9

49.3

22.3

21.8

2.5

1.9

Note: EA-13 is calculated without the Slovenian data.

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

: 

: 

: 

: 

: 

: 

: 

: 

3 131

8 470

7 239

1 625

5 232

4 830

4 438

7 772

6 257

3 406

1 220

1 448

12 180

2 868

3 001

8 056

8 062

2 213

4 082

1 089

4 379

2 064

6 897

8 756

6 994

96.5

3.5

0.0

97.1

2.9

:

96.4

3.4

0.2

98.6

1.4

:

95.9

96.9

97.4

93.9

96.6

4.0

0.2

3.1

0.0

2.4

0.2

4.1

2.0

2.7

0.7

98.3

1.7

:

97.4

96.8

98.2

2.2

0.4

3.1

0.1

1.5

0.3

98.0

2.0

:

98.8

93.4

1.2

0.0

4.8

1.8

97

1.7

1.3

97.9

93.3

1.9

0.2

2.2

4.4

97.8

2.2

:

97.8

96.4

2.0

0.2

3.4

0.1

96.8

3.2

:

96.4

98.1

3.6

0.0

1.9

0.0

41.1

7.8

35.3

6.7

7.9

1.5

3.9

0.7

8.4

1.6

3.4

0.6

25.0

19.6

49.7

53.2

24.1

25.9

1.2

1.2

37.2

11.1

20.6

6.1

13.9

4.1

9.5

2.8

43.5

12.4

27.2

7.7

7.7

2.2

8.6

2.4

43.7

5.8

31.5

4.2

9.1

1.2

1.6

0.2

23.3

3.8

42.1

6.9

5.3

0.9

8.3

1.3

13.0

3.9

10.5

3.0

12.7

1.7

15.5

2.5

5.8

1.7

2.5

0.7

1.5

0.2

5.5

0.9

63.9

63.5

9.1

10.2

20.3

19.6

6.7

6.7

31.8

34.5

38.5

36.3

27.6

27.6

2.1

1.7

20.6

21.2

79.2

78.0

:

0.6

0.2

0.1

58.3

60.8

25.1

23.1

15.1

14.5

1.5

1.6

50.9

12.8

26.5

6.7

5.0

1.3

5.9

1.5

6.9

1.7

4.7

1.2

29.2

30.5

38.2

37.3

22.6

23.5

10.0

8.7

43.7

8.5

30.8

6.0

7.5

1.5

12.9

2.5

3.5

0.7

1.7

0.3

27.4

30.3

52.4

50.9

16.3

16.4

3.9

2.4

43.6

12.8

30.0

8.8

5.8

1.7

7.8

2.3

8.5

2.5

4.4

1.3

30.4

30.4

46.0

45.5

19.9

20.6

3.8

3.5

61.3

15.4

25.9

6.5

6.1

1.5

2.0

0.5

4.4

1.1

0.3

0.1

40.6

42.4

42.8

41.2

14.9

14.8

1.6

1.6

48.3

8.5

24.1

4.2

4.3

0.8

4.9

0.9

50.0

6.1

24.5

3.0

9.8

1.2

3.4

0.4

11.4

2.0

10.5

1.3

6.9

1.2

1.8

0.2

45.0

52.7

9.4

8.8

27.9

26.7

17.7

11.8

30.2

33.4

52.6

48.9

17.1

17.7

0.0

0.0

47.3

6.1

29.5

3.8

10.2

1.3

1.6

0.2

8.8

1.1

2.6

0.3

38.9

39.5

53.7

54.0

5.9

6.0

1.5

0.4

36.5

8.1

25.0

5.5

13.5

3.0

4.7

1.0

17.4

3.8

2.9

0.6

46.9

44.6

24.7

27.3

23.8

24.5

4.6

3.6

42.5

8.6

29.5

6.0

10.3

2.1

2.9

0.6

12.1

2.5

2.6

0.5

31.6

33.0

47.0

42.8

12.8

16.2

8.7

8.0

51.2

9.5

27.0

5.0

6.7

1.2

6.9

1.3

5.2

1.0

2.9

0.5

30.5

32.5

45.3

44.4

21.5

19.8

2.6

3.3

41.6

11.1

30.4

8.1

10.9

2.9

6.3

1.7

4.8

1.3

6.0

1.6

14.4

19.2

29.4

34.0

38.1

34.7

18.1

12.1

48.2

13.6

25.0

7.1

8.3

2.3

6.0

1.7

10.7

3.0

1.8

0.5

32.7

34.6

39.0

37.2

27.0

26.8

1.3

1.4

60.1

11.8

19.5

3.8

11.5

2.3

3.5

0.7

4.6

0.9

0.8

0.2

32.4

34.8

30.1

27.7

25.1

24.0

12.4

13.5

47.2

11.0

30.4

7.1

10.4

2.4

5.7

1.3

5.3

1.2

1.0

0.2

39.1

42.2

35.6

31.7

17.4

15.7

7.9

10.4

37.9

5.6

35.9

5.3

7.1

1.0

3.6

0.5

11.1

1.6

4.3

0.6

: 

: 

: 

: 

: 

: 

: 

: 

44.7

10.6

32.7

7.8

8.1

1.9

3.1

0.7

8.6

2.0

2.8

0.7

31.5

31.6

27.0

27.1

39.3

39.9

2.2

1.3

40.1

6.6

30.1

5.0

9.6

1.6

6.2

1.0

10.7

1.8

3.3

0.5

31.0

28.8

48.3

49.8

18.5

20.0

2.2

1.4

36.9

9.6

25.5

6.6

13.2

3.4

9.8

2.5

11.5

3.0

3.1

0.8

43.2

44.3

37.7

39.4

12.1

10.9

7.1

5.4

40.1

12.7

25.4

8.0

14.8

4.7

6.2

2.0

9.6

3.0

3.9

1.2

45.8

48.7

40.5

40.8

9.4

8.6

4.3

1.9

44.6

11.5

30.4

7.8

9.2

2.4

2.6

0.7

6.7

1.7

6.4

1.7

46.4

49.7

29.9

32.5

22.5

16.2

1.2

1.7

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EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

5  SOCIAL PROTECTION

European
Union - 
27

European
Union - 25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EN 

232 

EN 

 
  
 
6 INCOME, SOCIAL INCLUSION AND 

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium

Bulgaria

Czech 
Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia

Lithuania

Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria

Poland

Portugal

Romania Slovenia

Slovakia

Finland

Sweden

United 
Kingdom

Croatia

LIVING CONDITIONS

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

1a At-risk-of-poverty rate by age and gender SILC(2005)

16 s

19 s

15 s

14 s

16 s

14 s

14 s

15 s

19 s

16 s

21 s

15 s

17 s

15 s

14 s

16 s

13 s

13 s

14 s

19 s

17 s

22 s

15 

18 

14 

13 

15 

12 

11 

13 

21 

20 

22 

14 i

18 i

13 i

12 i

15 i

12 i

13 i

12 i

18 i

9 i

23 i

10 b

18 b

9 b

8 b

10 b

9 b

9 b

10 b

5 b

2 b

7 b

12 

10 

12 

12 

13 

11 

11 

11 

18 

17 

18 

12 b

12 b

12 b

11 b

13 b

12 b

11 b

12 b

14 b

11 b

17 b

18 

21 

18 

16 

19 

17 

17 

17 

20 

10 

26 

IE

20 

23 

19 

17 

20 

16 

15 

17 

33 

30 

36 

EL

20 

20 

19 

18 

21 

17 

16 

18 

28 

25 

30 

ES

FR

20 

24 

19 

17 

20 

16 

15 

17 

29 

26 

32 

13 

14 

13 

12 

13 

12 

11 

12 

16 

15 

18 

IT

19 

24 

18 

16 

20 

16 

15 

18 

23 

19 

25 

CY

LV

LT

16 b

13 b

17 b

15 b

19 b

11 b

10 b

13 b

51 b

47 b

53 b

19 b

22 b

19 b

17 b

20 b

18 b

18 b

18 b

21 b

12 b

26 b

21 b

27 b

19 b

18 b

19 b

19 b

20 b

18 b

17 b

6 b

22 b

LU

13 

19 

11 

11 

12 

12 

11 

13 

7 

9 

5 

HU

MT

NL

13 b

20 b

12 b

12 b

12 b

13 b

13 b

13 b

6 b

4 b

8 b

15 b

22 b

13 b

12 b

14 b

12 b

11 b

13 b

16 b

16 b

17 b

11 b

15 b

9 b

9 b

10 b

10 b

10 b

10 b

5 b

5 b

6 b

AT

12 

15 

12 

11 

13 

11 

11 

11 

14 

10 

17 

PL

PT

RO

SI

SK

21 b

29 b

18 b

19 b

17 b

20 b

21 b

20 b

7 b

5 b

9 b

19 

24 

18 

18 

19 

16 

15 

16 

28 

28 

28 

18 i

25 i

17 i

17 i

17 i

17 i

17 i

16 i

17 i

12 i

21 i

12 b

12 b

12 b

10 b

14 b

10 b

10 b

10 b

20 b

11 b

26 b

13 b

19 b

12 b

11 b

12 b

13 b

13 b

13 b

7 b

3 b

10 b

FI

12 

10 

12 

11 

13 

11 

11 

10 

18 

11 

23 

SE

UK

HR

9 

9 

9 

9 

10 

9 

9 

8 

11 

6 

14 

19 b

22 b

18 b

17 b

19 b

16 b

16 b

17 b

26 b

24 b

28 b

18 i

15 i

19 i

17 i

20 i

14 i

14 i

14 i

32 i

26 i

37 i

Total population

Children aged 0-17*

People aged 18+*

People aged 18-64'

People aged 65+

Total

Men

Women

Total

Men

Women

Total

Men

Women

At-risk-of-poverty threshold (illustrative values), PPS 

- One-person household

- Two adults with two dep. children

16 s

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

9 486

2 033 i

4 662 b

9 581

9 431

19 920

4 269 i

9 791 b

20 119

19 805

2 869

6 025

9 004

6 518

7 035

8 720

8 238 8 787 b 2 402 b

2 341 b

16 375

3 379 b

6 613 b

9 688 b

10 562

2 877 b

5 008

1 504 i 7 047 b

3 118 b

8 501

8 582

10 675

4 464 i

18 909

13 689

14 774

18 312

17 299 18 453 b 5 044 b

4916 b

34 387

7 095 b 13 887 b

20 345

22 181

6 041 b

10 517

3 158 i 14 799 b

6 548 b

17 851

18 021

22 418

9 374 i

1b Relative median at-risk-of-poverty gap by gender and selected age group 

Total population

Children aged 0-17*

People aged 18+*

People aged 18-64*

People aged 65+ 

Total

Men

Women

Total

Men

Women

Total

Men

Women

2 Inequality of income : S80/S20 income quintile share ratio 

:

:

:

:

:

:

:

:

:

:

:

23 s

23 s

22 s

23 s

21 s

25 s

26 s

24 s

18 s

18 s

18 s

21 s

22 s

21 s

22 s

20 s

23 s

24 s

23 s

18 s

18 s

18 s

18 

18 

18 

19 

16 

19 

20 

18 

14 

16 

13 

20 i

23 i

19 i

20 i

19 i

23 i

24 i

21 i

15 i

11 i

17 i

18 b

18 b

18 b

19 b

17 b

19 b

19 b

19 b

8 b

: u

6 b

16 

18 

16 

14 

16 

22 

22 

22 

8 

7 

9 

19 b

17 b

20 b

21 b

18 b

20 b

22 b

20 b

17 b

20 b

16 b

24 

30 

22 

29 

19 

29 

31 

28 

11 

13 

11 

20 

23 

18 

19 

17 

22 

22 

22 

10 

12 

10 

24 

23 

24 

24 

24 

24 

24 

24 

24 

22 

25 

25 

29 

25 

26 

24 

29 

29 

28 

22 

23 

20 

17 

15 

17 

17 

17 

17 

19 

17 

15 

13 

17 

24 

28 

23 

24 

22 

27 

27 

28 

18 

16 

18 

19 b

17 b

21 b

18 b

22 b

19 b

17 b

21 b

21 b

20 b

23 b

27 b

31 b

26 b

33 b

22 b

33 b

36 b

30 b

11 b

13 b

10 b

28 b

30 b

28 b

32 b

24 b

31 b

33 b

30 b

13 b

18

18

20

18

20

20

20

20

13

11 bu

13 b

16 u

13 u

19 b

19 b

18 b

20 b

18 b

20 b

21 b

19 b

9 b

8 bu

11 b

18 b

20 b

17 b

18 b

16 b

18 b

18 b

18 b

14 b

17 b

12 b

21 b

21 b

22 b

23 b

20 b

22 b

26 b

20 b

12 b

11 bu

12 b

15 

14 

15 

17 

15 

18 

19 

17 

14 

12 

15 

30 b

33 b

29 b

30 b

28 b

30 b

31 b

30 b

17 b

19 b

16 b

26 

28 

25 

25 

25 

28 

28 

28 

17 

16 

18 

22 i

23 i

21 i

21 i

21 i

22 i

22 i

22 i

19 i

16 i

20 i

19 b

17 b

20 b

21 b

19 b

19 b

22 b

17 b

20 b

17 b

20 b

23 b

24 b

23 b

25 b

23 b

25 b

26 b

24 b

16 b

: u

16 b

14 

11 

14 

16 

13 

17 

18 

17 

10 

9 

11 

19

17

19

23

17

23

26

20

10

9 u

11

23 b

21 b

23 b

25 b

22 b

26 b

29 b

23 b

19 b

18 b

20 b

24 i

26 i

23 i

24 i

23 i

23 i

25 i

20 i

24 i

21 i

24 i

S80/S20

4.9 s

4.9 s

4.6 s

4

3.7 i

3.7 b

3.5

3.8 b

5.9

5

5.8

5.4

4

5.6

4.3 b

6.7 b

6.9 b

3.8

4 b

4.1 b

4 b

3.8

6.6 b

6.9

4.9 i

3.4 b

3.9 b

3.6

3.3

5.8 b

4.8 i

7a Relative income of people aged 65+ (relative to the complementary age groups) (%) 

Total

7b Aggregate replacement ratio (%)

Total

:

:

0.86 s

0.86 s

0.73

0.84 i

0.83 b

0.70

0.93 b

0.73

0.65

0.79

0.75

0.90

0.85

0.57 b

0.74 b

0.81 b

0.97

1.01 b

0.83 b

0.88 b

0.95

1.09 b

0.76

0.51 s

0.52 s

0.42

0.6 i

0.51

0.35

0.46 b

0.47

0.43

0.49

0.56

0.57

0.58

0.28

0.61

0.47

0.62

0.61

0.54

0.43

0.67

0.58

0.59

11 At-risk-of-poverty rate by most frequent activity status and by gender (Age 18+)

-

-

-

Total

At work

Not at work

Unemployed

Retired

Other inactive

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

15 s

14 s

16 s

8 s

9 s

7 s

23 s

22 s

23 s

39 s

43 s

36 s

16 s

15 s

17 s

26 s

26 s

26 s

15 s

13 s

16 s

7 s

8 s

6 s

22 s

21 s

23 s

36 s

41 s

33 s

16 s

15 s

16 s

25 s

25 s

25 s

14 

13 

15 

4 

5 

3 

24 

24 

24 

31 

31 

31 

19 

20 

18 

26 

25 

26 

14 i

12 i

17 i

6 i

5 i

6 i

19 i

15 i

22 i

34 i

37 i

31 i

16 i

11 i

20 i

15 i

16 i

14 i

8 b

8 b

9 b

3 b

3 b

4 b

15 b

15 b

15 b

51 b

57 b

47 b

6 b

4 b

7 b

16 b

17 b

15 b

12 

12 

12 

5 

5 

5 

22 

24 

21 

26 

39 

14 

16 

15 

16 

31 

33 

30 

12 b

11 b

13 b

5 b

5 b

6 b

19 b

19 b

19 b

40 b

43 b 

38 b

13 b

12 b

15 b

19 b

22 b

17 b

17 

15 

19 

7 

7 

8 

31 

30 

31 

60 

62 

58 

23 

11 

28 

31 

35 

29 

18 

17 

20 

6 

6 

5 

34 

37 

32 

47 

53 

35 

30 

30 

30 

34 

38 

32 

19 

18 

21 

13 

14 

12 

26 

25 

27 

32 

38 

28 

25 

22 

29 

25 

26 

25 

19 

17 

20 

10 

11 

9 

28 

28 

28 

35 

41 

31 

25 

25 

23 

28 

25 

29 

13 

12 

13 

6 

7 

5 

20 

19 

20 

29 

34 

25 

13 

13 

14 

27 

25 

28 

18 

16 

20 

9 

10 

6 

25 

23 

27 

44 

50 

39 

16 

15 

17 

28 

25 

29 

17 b

15 b

19 b

7 b

6 b

7 b

32 b

33 b

31 b

37 b

46 b

31 b

49 b

46 b

51 b

19 b

16 b

21 b

19 b

17 b

20 b

9 b

9 b

9 b

31 b

32 b

31 b

59 b

64 b

53 b

24 b

19 b

26 b

31 b

31 b

31 b

19 b

18 b

20 b

10 b

10 b

10 b

29 b

28 b

29 b

63 b

65 b

60 b

17 b

8 b

22 b

29 b

26 b

31 b

11 

11 

11 

9 

9 

9 

13 

14 

13 

46 

45 

48 

6 

7 

4 

14 

19 

13 

12 b

12 b

12 b

10 b

10 b

9 b

15 b

14 b

15 b

48 b

52 b

45 b

10 b

9 b

10 b

17 b

12 b

20 b

13 b 

12 b 

14 b 

5 b 

7 b 

3 b 

19 b 

22 b 

18 b 

48 b 

55 b 

23 bu 

17 b 

18 b 

13 b 

18 b 

18 b 

18 b 

9 b 

9 b 

9 b 

6 b 

6 b 

5 b 

14 b 

15 b 

13 b 

27 b 

27 b 

27 b 

5 b 

4 b 

5 b 

19 b 

26 b 

16 b 

12 

10 

13 

7 

7 

6 

18 

17 

18 

48 

53 

42 

12 

10 

14 

22 

26 

21 

18 b 

19 b 

17 b 

14 b 

15 b 

12 b 

22 b 

23 b 

21 b 

46 b 

48 b 

43 b 

11 b 

11 b 

10 b 

26 b 

25 b 

27 b 

18 

18 

19 

12 

13 

11 

27 

26 

27 

28 

33 

24 

25 

25 

25 

28 

23 

30 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

0.86 b

0.85 b

0.75

0.80

0.73 b

0.42

0.55

0.46

0.58

0.41 b

12 b 

10 b 

14 b 

5 b 

5 b 

4 b 

19 b 

17 b 

21 b 

25 b 

24 b 

26 b 

17 b 

11 b 

21 b 

22 b 

23 b 

21 b 

12 b 

11 b 

12 b 

9 b 

9 b 

9 b 

15 b 

16 b 

15 b 

39 b 

41 b 

38 b 

7 b 

4 b 

8 b 

19 b 

18 b 

19 b 

12 

10 

13 

4 

4 

4 

22 

20 

23 

36 

39 

31 

17 

11 

21 

27 

29 

25 

9 

8 

10 

5 

6 

5 

15 

13 

16 

26 

33 

19 

10 

7 

13 

26 

26 

26 

18 b

17 b

19 b

8 b 

9 b 

8 b 

32 b

32 b

32 b

55 b

55 b

55 b

28 b 

27 b

29 b 

35  b

39 b

34 b

:

:

18 i

16 i

20 i

10 i

10 i

10 i

23 i

22 i

25 i

34 i

40 i

28 i

23 i

23 i

24 i

21 i

16 i

24 i

Former
Yugoslav 
Republic 
of
MK

Turkey

TR

:

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:

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26 i

36 i

22 i

21 i

23 i

22 i

21 i

23 i

22 i

22 i

23 i

:

:

2 044 i

4 292 i

:

:

:

34 i

36 i

32 i

32 i

32 i

32 i

32 i

31 i

34 i

31 i

36 i

10 i

:

:

22 i

21 i

23 i

23 i

22 i

28 i

21 i

21 i

21 i

30 i

39 i

17 i

5 i

7 i

0 i

23 i

27 i

22 i  

EN 

233 

EN 

 
  
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
      
       
       
       
       
       
      
        
      
         
      
      
        
      
       
       
       
       
       
      
        
      
         
      
        
        
      
       
       
       
       
       
      
        
      
         
      
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
         
      
        
        
       
       
       
       
       
      
      
         
      
        
        
       
       
       
       
       
      
      
         
        
        
        
       
       
       
       
       
      
      
         
      
        
      
       
       
       
       
       
      
      
      
    
      
        
        
      
       
       
       
       
       
      
      
      
    
      
        
        
      
       
       
       
       
       
      
      
      
    
      
      
          
        
         
         
       
       
         
        
        
        
    
        
        
          
        
         
         
       
       
         
      
        
        
    
        
        
          
        
         
         
       
         
         
        
        
        
    
        
        
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
        
      
    
      
      
        
      
       
       
       
       
       
      
        
      
    
      
        
        
      
       
       
       
       
       
      
        
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
        
      
       
       
       
       
       
      
      
      
    
      
      
 
100 s

100 s

100 

Distribution of at-risk-or-poverty population
-

Total

Total 

-

-

At work

Not at work

Unemployed

Retired

Other inactive

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

Total 

Men

Women 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

45 s

55 s

28 s

17 s

10 s

72 s

28 s

45 s

16 s

8 s

8 s

26 s

11 s

15 s

30 s

7 s

22 s

44 s

56 s

25 s

16 s

9 s

75 s

28 s

47 s

15 s

7 s

7 s

25 s

13 s

13 s

35 s

8 s

27 s

Context 11: At-risk-of-poverty rate before social transfers by gender and selected age group 

Before all social transfers except old-age/survivors' pensions
Total population

26 s

Children aged 0-17 years

People aged 18 years and 
more

People aged 18-64 years

People aged 65 years and 
more

Total

Men

Women

Total

Men

Women

Total

Men

Women

Before all social transfers including old-age/survivors' pensions

Total population

Children aged 0-17 years

People aged 18 +

People aged 18-64

People aged 65 +

Total

Men

Women

Total

Men

Women

Total

Men

Women

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

26 s

34 s

24 s

31 s

24 s

23 s

23 s

25 s

24 s

23 s

25 s

21 s

24 s

23 s

22 s

24 s

23 s

22 s

20 s

25 s

43 s

35 s

45 s

42 s

48 s

33 s

31 s

35 s

90 s

89 s

90 s

19 s

25 s

42 s

32 s

44 s

41 s

47 s

32 s

30 s

34 s

90 s

89 s

90 s

44 

56 

14 

9 

5 

86 

35 

51 

21 

11 

11 

29 

13 

16 

36 

11 

25 

28 

34 

27 

25 

28 

27 

26 

28 

26 

25 

26 

42 

34 

44 

40 

48 

32 

30 

35 

92 

92 

91 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

17 i

24 i

16 i

14 i

18 i

15 i

15 i

14 i

20 i

10 i

26 i

39 i

31 i

41 i

37 i

44 i

29 i

27 i

31 i

75 i

73 i

76 i

100 b

100 

100 b

100 

100 

100 

100 

100 

100 

100 b

100 b

100 b

100 

100 b

100 b

100 b

100 

100 b

100 

43 b

57 b

23 b

13 b

10 b

77 b

30 b

46 b

38 b

18 b

20 b

20 b

5 b

15 b

19 b

7 b

12 b

21 b

34 b

18 b

17 b

20 b

20 b

19 b

21 b

11 b

7 b

14 b

39 b

35 b

40 b

36 b

43 b

30 b

27 b

32 b

88 b

91 b

87 b

47 

53 

23 

13 

11 

77 

34 

42 

9 

7 

3 

29 

12 

17 

38 

16 

23 

30 

25 

31 

30 

33 

29 

27 

30 

42 

44 

41 

38 

25 

42 

38 

45 

29 

27 

31 

94 

91 

96 

41 b

59 b

20 b

10 b

10 b

80 b

31 b

48 b

21 b

10 b

11 b

31 b

13 b

18 b

28 b

8 b

19 b

23 b

29 b

22 b

20 b

23 b

23 b

23 b

24 b

15 b

12 b

18 b

43 b 

30 b

46 b

44 b

49 b

33 b

30 b

35 b

95 b

94 b

96 b

39 

61 

24 

11 

13 

76 

28 

48 

19 

12 

7 

30 

4 

26 

27 

11 

16 

24 

31 

22 

20 

24 

22 

22 

23 

22 

11 

28 

39 

34 

40 

36 

43 

29 

28 

30 

83 

83 

83 

46 

54 

18 

11 

7 

82 

35 

47 

11 

8 

3 

15 

11 

3 

57 

15 

41 

32 

40 

30 

27 

32 

27 

25 

29 

44 

38 

48 

40 

41 

39 

36 

42 

30 

28 

33 

88 

87 

88 

45 

55 

33 

21 

12 

67 

23 

44 

8 

4 

4 

28 

14 

15 

31 

6 

25 

23 

23 

23 

21 

24 

20 

19 

21 

32 

29 

35 

39 

25 

42 

40 

45 

31 

29 

32 

83 

81 

85 

45 

55 

29 

19 

9 

71 

25 

46 

13 

6 

8 

20 

14 

6 

38 

6 

32 

24 

29 

23 

21 

25 

21 

20 

22 

32 

29 

35 

39 

32 

40 

37 

43 

29 

27 

31 

83 

84 

83 

45 

55 

26 

16 

10 

74 

29 

45 

14 

8 

6 

28 

13 

15 

32 

8 

24 

26 

34 

24 

23 

25 

25 

24 

25 

21 

19 

22 

45 

36 

47 

44 

50 

35 

33 

36 

96 

96 

95 

42 

58 

23 

17 

6 

77 

26 

52 

14 

7 

7 

18 

10 

9 

45 

8 

36 

23 

31 

22 

20 

24 

21 

19 

22 

25 

21 

28 

43 

33 

45 

41 

49 

33 

30 

35 

85 

83 

86 

42 b

58 b

22 b

13 b

10 b

78 b

30 b

48 b

5 b

3 b

3 b

47 b

20 b

26 b

26 b

6 b

19 b

40 b

60 b

27 b

13 b

13 b

73 b

27 b

47 b

22 b

12 b

9 b

34 b

9 b

26 b

17 b

5 b

11 b

22 b

20 b

26 b

31 b

22 b

25 b

20 b

24 b

16 b

15 b

18 b

22 b

26 b

24 b

24 b

24 b

54 b

27 b

51 b

57 b

29 b

21 b

32 b

29 b

34 b

22 b

20 b

24 b

88 b

87 b

88 b

15 b

32 b

40 b

35 b

42 b

38 b

44 b

32 b

31 b

33 b

79 b

78 b

79 b

42 b

58 b

28 b

15 b

14 b

72 b

27 b

44 b

27 b

15 b

11 b

22 b

3 b

19 b

23 b

9 b

14 b

26 b

34 b

24 b

23 b

25 b

25 b

25 b

24 b

20 b

8 b

26 b

42 b

38 b

43 b

40 b

46 b

33 b

33 b

33 b

86 b

85 b

87 b

48 

52 

46 

28 

18 

54 

20 

34 

8 

4 

4 

8 

6 

2 

38 

9 

28 

23 

35 

20 

20 

20 

22 

22 

23 

10 

12 

9 

40 

38 

41 

38 

43 

31 

29 

33 

87 

88 

86 

47 b

53 b

46 b

26 b

21 b

54 b

21 b

32 b

17 b

8 b

8 b

28 b

10 b

18 b

9 b

3 b

6 b

29 b

44 b

26 b

26 b

25 b

29 b

30 b

29 b

11 b

7 b

14 b

50 b

48 b

50 b

48 b

53 b

41 b

40 b

42 b

90 b

90 b

90 b

46 b

54 b

20 b

17 b

3 b

80 b

29 b

51 b

10 b

9 b

1 bu

18 b

16 b

2 b

53 b

5 b

48 b

21 b

30 b

18 b

17 b

20 b

18 b

17 b

19 b

22 b

20 b

22 b

37 b

33 b

38 b

34 b

41 b

27 b

24 b

30 b

81 b

80 b

82 b

49 b

51 b

36 b

22 b

15 b

64 b

27 b

36 b

17 b

7 b

10 b

10 b

4 b

6 b

37 b

16 b

20 b

22 b

28 b

20 b

20 b

20 b

22 b

21 b

23 b

10 b

10 b

10 b

37 b

28 b

39 b

36 b

43 b

28 b

25 b

30 b

95 b

95 b

95 b

44 

56 

32 

20 

12 

68 

24 

44 

9 

5 

4 

27 

11 

17 

31 

8 

23 

24 

36 

21 

20 

23 

23 

22 

23 

16 

11 

20 

43 

39 

44 

40 

48 

33 

30 

36 

87 

86 

87 

50 b

50 b

34 b

20 b

14 b

66 b

29 b

36 b

29 b

15 b

14 b

17 b

7 b

10 b

20 b

7 b

13 b

30 b

39 b

27 b

29 b

26 b

31 b

32 b

30 b

11 b

8 b

13 b

51 b

46 b

52 b

51 b

54 b

45 b

45 b

45 b

88 b

88 b

88 b

46 

54 

36 

21 

16 

63 

24 

39 

8 

4 

4 

29 

14 

16 

25 

6 

20 

26 

31 

24 

24 

25 

22 

22 

23 

32 

32 

32 

41 

34 

42 

40 

45 

32 

30 

33 

82 

83 

82 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

24 i

34 i

21 i

21 i

22 i

22 i

22 i

21 i

22 i

21 i

20 i

43 i

40 i

43 i

42 i

44 i

36 i

36 i

36 i

77 i

78 i

76 i

100 b

100 b

100 

100 

100 b

41 b

59 b

19 b

11 b

7 b

81 b

30 b

52 b

4 b

2 b

2 b

42 b

11 b

31 b

35 b

17 b

18 b

26 b

28 b

25 b

24 b

27 b

24 b

23 b

24 b

33 b

26 b

37 b

42 b

32 b

44 b

42 b

47 b

35 b

34 b

37 b

84 b

83 b

84 b

45 b

55 b

41 b

21 b

20 b

59 b

23 b

35 b

26 b

13 b

13 b

16 b

4 b

12 b

17 b

7 b

10 b

22 b

30 b

20 b

19 b

20 b

21 b

21 b

22 b

12 b

8 b

15 b

40 b

35 b

42 b

38 b

45 b

33 b

30 b

35 b

91 b

88 b

93 b

42 

58 

17 

9 

8 

83 

33 

50 

19 

12 

7 

39 

11 

28 

24 

10 

15 

28 

31 

27 

26 

29 

27 

27 

27 

27 

19 

32 

40 

32 

43 

40 

46 

31 

30 

31 

92 

89 

94 

45 

55 

35 

21 

15 

65 

24 

40 

8 

6 

3 

31 

9 

22 

26 

10 

16 

29 

35 

27 

24 

29 

28 

27 

29 

23 

13 

30 

42 

36 

44 

40 

47 

30 

28 

32 

94 

90 

97 

47 b

53 b

35 b

20 b

15 b

65 b

28 b

37 b

7 b

4 b

3 b

47 b

19 b

29 b

10 b

5 b

5 b

31 b

41 b

28 b

25 b

30 b

26 b

24 b

28 b

35 b

30 b

38 b

43 b

42 b

43 b

39 b

47 b

31 b

28 b

34 b

91 b

89 b

92 b

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

31 i

20 i

34 i

31 i

36 i

24 i

22 i

25 i

73 i

75 i

71 i

38 i

30 i

40 i

38 i

42 i

31 i

29 i

32 i

77 i

81 i

75 i

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

28 i

36 i

24 i

22 i

26 i

23 i

22 i

25 i

30 i

23 i

37 i

31 i

32 i

31 i

29 i

33 i

29 i

26 i

31 i

55 i

55 i

55 i

EN 

234 

EN 

 
  
      
    
     
     
     
     
     
    
    
    
       
    
    
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
          
      
       
       
       
       
       
      
      
      
         
        
      
          
      
       
         
       
         
       
        
      
      
         
        
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
        
       
       
         
       
       
      
        
        
           
      
        
        
        
       
         
         
         
         
        
        
        
           
      
        
        
        
         
         
         
         
         
        
        
        
           
        
        
        
      
       
       
       
       
       
      
        
      
         
      
      
        
      
         
       
       
       
       
      
        
      
         
      
        
        
      
       
         
       
         
       
        
        
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
         
         
         
        
        
        
           
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
        
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
 
At-risk-of-poverty rate by household type

Incidence

-

Households without dependent 
children

One-person households

Two-adult households

Other households

Total

Total

Men 

Women

Aged  < 65 yrs

Aged  65+

Both < 65 yrs

At least one 65+

-

Households with dependent 
children

Total

Single parents

Two-adult households

at least 1dep child

1 dep. child

2 dep. children

3+ dep. children

Other households

Distribution of at-risk-or-poverty population

-

Households without dependent 
children

One-person households

Total

Total

Men 

Women

Aged  < 65 yrs

Aged  65+

Both aged  < 65 yrs

At least one age  65+

Two-adult households

Other households

-

Households with dependent 
children

Total

Single parents

 Two-adult households

Other households

at least 1 dep. child

1 dep. child

2 dep. children

3+ dep. children

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

15 s

15 s

24 s

22 s

25 s

22 s

25 s

10 s

16 s

10 s

24 s

21 s

26 s

22 s

27 s

9 s

16 s

9 s

17 s

16 s

31 s

11 s

14 s

24 s

17 s

28 s

11 s

14 s

22 s

16 s

45 s

47 s

19 s

7 s

12 s

10 s

9 s

8 s

10 s

7 s

20 s

7

13 s

10 s

9 s

8 s

12 s

7 s

55 s

53 s

9 s

9 s

16 s

11 s

11 s

8 s

9 s

 17 s

10 s

9 s

13 

22 

20 

24 

19 

27 

8 

17 

5 

16 

33 

9 

10 

20 

18 

44 

22 

9 

13 

12 

10 

8 

12 

3 

56 

14 

7 

10 

17 

8 

At-risk-of-poverty rate by accommodation tenure status and by gender and selected age group

Incidence

-

-

Owner-occupier or rent-free

Total

Tenant

Men

Women

Total

Men

Women

Distribution of at-risk-or-poverty population

-

-

Owner-occupier or rent-free

Tenant

Total

Men

Women

Total

Men

Women

:

:

:

:

:

:

:

:

:

:

:

:

14 s

13 s

14 s

23 s

22 s

23 s

64 s

30 s

34 s

36 s

17 

19 

13 s

12 s

14 s

21 s

21 s

22 s

60 s

27 s

33 s

40 s

18 s

21 s

10 

9 

11 

29 

29 

29 

49 

22 

26 

51 

25 

27 

13 i

33 i

23 i

36 i

22 i

39 i

7 i

9 i

9 i

15 i

25 i

10 i

17 i

32 i

15 i

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

14 i

12 i

15 i

25 i

23 i

26 i

:

:

:

:

:

:

7 b

16 b

16 b

16 b

19 b

14 b

7 b

2 b

3 b

14 b

41 b

9 b

11 b

25 b

9 b

31 b

14 b

6 b

9 b

9 b

6 b

10 b

2 b

5 b

69 b

16 b

10 b

22 b

11 b

9 b

8 b

7 b

8 b

19 b

17 b

20 b

58 b

27 b

31 b

42 b

19 b

24 b

15 

26 

26 

25 

28 

21 

5 

13 

1 

9 

21 

4 

5 

14 

5 

65 

47 

23 

24 

34 

12 

8 

10 

0 

35 

12 

4 

7 

11 

1 

7 

7 

8 

21 

22 

20 

42 

20 

22 

58 

28 

30 

14 b

23 b

23 b

23 b

24 b

20 b

10 b

11 b

4 b

11 b

25 b

8 b

7 b

11 b

9 b

59 b

33 b

13 b

20 b

22 b

11 b

13 b

11 b

2 b

41 b

12 b

9 b

10 b

7 b

4 b

8 b

8 b

9 b

18 b

17 b

18 b

38 b

18 b

20 b

62 b

28 b

34 b

19 

36 

35 

37 

32 

41 

15 

11 

8 

18 

40 

13 

12 

25 

13 

45 

26 

9 

17 

12 

14 

9 

5 

4 

55 

16 

11 

9 

9 

10 

18 

16 

18 

34 

33 

34 

91 

39 

52 

9 

5 

5 

20 

48 

44 

53 

34 

62 

14 

20 

9 

19 

45 

12 

13 

26 

11 

38 

19 

8 

10 

6 

13 

7 

7 

6 

62 

17 

6 

11 

20 

8 

15 

15 

16 

37 

36 

38 

61 

30 

31 

39 

18 

21 

19 

28 

19 

32 

19 

35 

15 

27 

13 

21 

44 

14 

18 

33 

28 

48 

11 

2 

8 

3 

7 

7 

16 

14 

52 

4 

8 

24 

3 

13 

20 

19 

21 

18 

16 

19 

83 

38 

45 

17 

8 

10 

18 

34 

21 

43 

19 

47 

11 

29 

13 

21 

37 

14 

23 

36 

18 

44 

10 

3 

7 

3 

7 

5 

14 

15 

56 

3 

9 

20 

9 

14 

18 

17 

20 

32 

31 

33 

84 

39 

45 

16 

8 

9 

13 

20 

19 

20 

18 

21 

8 

13 

10 

13 

26 

8 

9 

20 

15 

46 

21 

8 

13 

11 

9 

10 

11 

5 

54 

11 

8 

16 

14 

5 

9 

8 

10 

20 

20 

21 

46 

21 

25 

54 

25 

29 

16 

28 

19 

34 

21 

34 

10 

20 

9 

22 

35 

15 

21 

35 

21 

42 

17 

5 

12 

6 

10 

5 

12 

9 

58 

5 

10 

21 

9 

13 

17 

15 

18 

29 

27 

31 

72 

31 

41 

28 

13 

15 

27 b

20 b

48 b

29 b

59 b

27 b

70 b

14 b

47 b

11 b

41 b

42 b

40 b

37 b

45 b

19 b

11 b

13 b

11 b

19 b

35 b

9 b

9 b

14 b

8 b

31 b

14 b

18 b

39 b

13 b

57 b

46 b

16 b

4 b

12 b

5 b

11 b

7 b

26 b

8 b

21 b

7 b

14 b

10 b

11 b

11 b

5 b

9 b

43 b

54 b

6 b

6 b

15 b

9 b

8 b

15 b

14 b

17 b

23 b

20 b

25 b

84 b

37 b

46 b

16 b

7 b

9 b

9 b

10 b

11 b

9 b

14 b

18 b

18 b

19 b

24 b

21 b

26 b

78 b

35 b

43 b

22 b

9 b

13 b

18 b

32 b

35 b

30 b

30 b

33 b

17 b

9 b

9 b

23 b

48 b

15 b

18 b

44 b

14 b

34 b

17 b

6 b

11 b

9 b

8 b

8 b

4 b

4 b

66 b

15 b

12 b

15 b

15 b

10 b

20 b

19 b

21 b

33 b

31 b

35 b

95 b

42 b

53 b

5 b

2 b

2 b

8 

14 

15 

13 

17 

7 

6 

7 

3 

17 

32 

13 

17 

20 

14 

25 

12 

6 

6 

10 

2 

6 

5 

2 

75 

8 

12 

24 

20 

11 

9 

9 

10 

25 

24 

26 

56 

26 

30 

44 

23 

22 

10 b

19 b

24 b

15 b

26 b

10 b

9 b

4 b

6 b

17 b

27 b

15 b

15 b

26 b

11 b

34 b

16 b

7 b

9 b

12 b

4 b

9 b

3 b

6 b

66 b

10 b

13 b

16 b

15 b

12 b

13 b

13 b

13 b

19 b

20 b

18 b

90 b

44 b

46 b

10 b

5 b

5 b

11 b

21 b

15 b

24 b

23 b

20 b

13 b

18 b

4 b

18 b

49 b

12 b

16 b

34 b

10 b

33 b

10 b

2 b

7 b

4 b

5 b

7 b

12 b

5 b

67 b

8 b

9 b

19 b

20 b

11 b

14 b

13 b

14 b

20 b

18 b

22 b

76 b

37 b

39 b

24 b

10 b

14 b

8 b

14 b

17 b

12 b

17 b

7 b

7 b

4 b

4 b

13 b

26 b

9 b

10 b

20 b

6 b

37 b

19 b

10 b

9 b

16 b

3 b

12 b

4 b

2 b

63 b

9 b

9 b

19 b

23 b

3 b

7 b

7 b

7 b

17 b

18 b

17 b

43 b

22 b

21 b

57 b

28 b

30 b

12 

19 

14 

23 

17 

23 

9 

11 

6 

13 

27 

9 

11 

20 

9 

47 

23 

7 

16 

13 

10 

10 

8 

6 

53 

8 

9 

15 

13 

8 

10 

9 

11 

17 

17 

17 

51 

23 

28 

49 

22 

26 

13 b

16 b

25 b

12 b

26 b

7 b

14 b

6 b

14 b

25 b

40 b

17 b

23 b

45 b

23 b

24 b

7 b

4 b

3 b

6 b

2 b

6 b

2 b

9 b

76 b

5 b

10 b

17 b

18 b

27 b

20 b

21 b

20 b

25 b

25 b

25 b

94 b

47 b

47 b

6 b

3 b

3 b

19 

37 

34 

39 

28 

42 

15 

28 

9 

20 

31 

15 

24 

42 

15 

41 

11 

3 

8 

3 

8 

7 

15 

8 

59 

4 

13 

19 

9 

14 

17 

17 

18 

29 

28 

30 

74 

34 

39 

26 

12 

14 

14 i

26 i

20 i

29 i

20 i

30 i

10 i

12 i

12 i

21 i

27 i

11 i

16 i

44 i

23 i

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

18 i

18 i

18 i

22 i

21 i

23 i

:

:

:

:

:

:

16 b

44 b

35 b

49 b

43 b

45 b

12 b

12 b

6 b

10 b

22 b

9 b

10 b

17 b

6 b

51 b

27 b

7 b

20 b

11 b

16 b

7 b

8 b

8 b

49 b

6 b

8 b

17 b

8 b

10 b

11 b

9 b

12 b

26 b

25 b

27 b

80 b

33 b

47 b

20 b

9 b

11 b

8 b

16 b

18 b

16 b

23 b

12 b

10 b

4 b

5 b

17 b

32 b

13 b

17 b

24 b

13 b

23 b

10 b

2 b

7 b

6 b

4 b

6 b

2 b

6 b

77 b

6 b

9 b

23 b

17 b

22 b

13 b

13 b

12 b

18 b

16 b

19 b

79 b

38 b

41 b

21 b

9 b

12 b

14 

30 

27 

32 

26 

36 

6 

8 

3 

9 

20 

7 

5 

12 

8 

64 

45 

17 

28 

27 

19 

10 

7 

1 

36 

9 

7 

7 

12 

2 

8 

7 

9 

21 

21 

22 

50 

21 

29 

50 

23 

27 

11 

19 

19 

20 

20 

19 

5 

4 

4 

8 

18 

4 

4 

9 

12 

57 

42 

19 

23 

27 

15 

9 

4 

1 

43 

16 

4 

8 

11 

4 

6 

5 

6 

17 

17 

17 

42 

19 

23 

58 

27 

32 

19 b

27 b

24 b

28 b

22 b

32 b

11 b

24 b

14 b

19 b

37 b

11 b

14 b

27 b

15 b

52 b

20 b

8 b

12 b

10 b

10 b

10 b

14 b

7 b

49 b

16 b

6 b

11 b

11 b

5 b

14 b

13 b

15 b

32 b

33 b

32 b

53 b

25 

28 b

47 

23 b

24 b

23 i

42 i

33 i

47 i

30 i

49 i

16 i

31 i

10 i

14 i

24 i

12 i

10 i

24 i

13 i

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

18 i

:

:

12 iu

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

11 i

19 i

:

:

:

:

6 i

14 i

11 i

29 i

39 i

8 i

14 i

44 i

34 i

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

26 i

:

:

23 i

:

:

:

:

:

:

:

:  

EN 

235 

EN 

 
  
        
      
       
       
       
       
       
      
        
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
        
      
         
      
      
          
        
       
       
       
       
         
      
        
        
         
        
        
        
      
       
       
       
       
       
      
        
      
         
        
        
          
        
         
         
       
       
       
        
        
        
           
        
        
        
        
       
       
       
       
       
      
      
      
         
        
        
        
      
       
       
       
       
       
      
      
      
         
      
      
          
        
       
       
       
       
         
      
      
        
         
        
        
        
        
       
       
       
       
         
      
      
      
         
        
        
        
      
       
       
       
       
       
      
      
      
         
      
        
        
        
       
       
       
       
       
      
      
        
         
        
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
          
      
         
         
         
         
         
        
        
        
           
      
      
        
      
       
       
         
         
       
      
        
      
           
      
      
        
      
       
         
         
         
       
        
      
      
           
      
      
        
      
       
       
         
         
         
      
        
      
           
      
      
          
        
         
         
         
         
       
        
        
      
           
      
        
        
      
         
         
       
       
       
      
        
        
         
        
        
          
        
         
         
       
       
         
        
        
        
           
        
        
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
         
         
       
        
        
        
           
        
      
          
        
       
         
         
         
         
      
      
        
         
        
        
        
        
         
       
       
       
       
      
      
      
         
        
        
        
      
         
       
         
         
       
        
      
      
           
      
      
          
        
       
         
       
       
         
      
      
        
         
        
        
        
        
       
       
       
       
         
      
        
      
         
        
        
          
        
       
       
       
       
         
      
        
        
         
        
        
        
        
       
       
       
       
       
      
      
      
         
        
        
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
     
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
         
       
       
       
       
      
      
      
         
      
      
     
    
        
      
         
       
         
         
       
      
      
      
         
      
      
    
        
      
         
       
       
         
       
      
      
      
         
      
      
At-risk-of-poverty rate by work intensity of the household

Incidence

-

-

Households without dependent 
children

WI = 0

Households with dependent 
children

0 < WI < 1

WI = 1

WI = 0

0 < WI < 0.5

0.5 <= WI < 1

WI = 1

Distribution of at-risk-or-poverty population

-

-

Households without dependent 
children

WI = 0

Households with dependent 
children

0 < WI < 1

WI = 1

WI = 0

0 < WI < 0.5

0.5 <= WI < 1

WI = 1

:

:

:

:

:

:

:

:

:

:

:

:

:

:

29 s

28 s

11 s

5 s

10 s

5 s

60 s

62 s

40 s

18 s

7 s

39 s

17 s

6 s

17 s

19 s

10 s

5 s

11 s

5 s

17 s

15 s

10 s

27 s

14 s

10 s

30 s

11 s

25 

7 

2 

72 

36 

15 

3 

22 

6 

3 

34 

8 

19 

7 

25 i

19 b

27 

8 i

1 i

61 i

29 i

10 i

1 i

:

:

:

:

:

:

:

7 b

1 b

78 b

47 b

13 b

3 b

15 b

10 b

1 b

27 b

12 b

27 b

8 b

6 

5 

51 

13 

6 

5 

28 

7 

12 

20 

2 

9 

23 

29 b

8 b

4 b

53 b

28 b

7 b

5 b

57 

12 

5 

81 

56 

15 

7 

33 b

23 

9 b

6 b

18 b

7 b

16 b

10 b

8 

5 

19 

12 

20 

14 

51 

8 

5 

74 

37 

13 

5 

16 

6 

3 

34 

12 

21 

8 

28 

12 

11 

54 

47 

23 

11 

11 

16 

8 

7 

9 

34 

15 

42 

13 

6 

68 

40 

24 

10 

13 

15 

4 

8 

10 

38 

12 

21 

11 

4 

63 

42 

16 

4 

15 

12 

5 

16 

11 

28 

13 

30 

9 

5 

70 

46 

24 

5 

17 

9 

4 

14 

14 

37 

5 

47 b

54 b

40 b

15 

12 b

9 b

17 b

5 b

71 b

83 b

34 b

14 b

3 b

46 b

19 b

8 b

15 b

5 b

82 b

64 b

22 b

12 b

18 b

22 b

15 b

13 b

7 b

13 b

5 b

10 b

13 b

9 b

35 b

7 b

8 b

25 b

13 b

9 b

3 b

15 b

14 b

24 b

21 b

7 

5 

36 

54 

17 

12 

8 

6 

6 

4 

13 

37 

25 

18 b

10 b

7 b

56 b

42 b

23 b

10 b

11 b

10 b

8 b

8 b

9 b

25 b

28 b

34 b

16 b

3 b

1 b

73 b

29 b

15 b

5 b

8 b

4 b

53 b

27 b

16 b

7 b

19 b

14 b

4 b

1 b

24 b

8 b

40 b

5 b

9 b

6 b

17 b

5 b

28 b

21 b

21 

11 

4 

52 

33 

14 

6 

15 

14 

7 

10 

9 

32 

13 

24 b

14 b

8 b

62 b

43 b

22 b

15 b

10 b

9 b

3 b

16 b

18 b

27 b

17 b

33 

11 

7 

61 

38 

27 

10 

11 

11 

5 

7 

8 

38 

21 

:

:

:

:

:

:

:

:

:

:

:

:

:

:

31 b

14 b

6 b

4 b

54 b

27 b

12 b

3 b

25 b

10 b

3 b

17 b

11 b

25 b

9 b

6 b

6 b

76 b

38 b

15 b

11 b

7 b

7 b

4 b

14 b

12 b

28 b

27 b

27 

11 

3 

56 

28 

7 

3 

22 

20 

6 

16 

10 

17 

8 

20 

12 

5 

42 

28 

8 

4 

13 

18 

13 

14 

7 

16 

21 

38 b

18 b

5 b

54 b

41 b

21 b

9 b 

18 b

9 b 

8 b

27 b

4 b

15 b

19 b

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

Notes: 1)  HR: National HBS 2004, income data 2004. 2) BG and RO National HBS 2005, income data 2005.  3) TR National HICE survey 2004, income data 2004.
4) EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
* The age breakdowns for RO,HR and TR refer to 0-15 and 16+ population respectively, not 0-17 and 18+ population

Source: SILC(2005) income data 2004; except for UK, income year 2005 and for IE moving income reference period (2004-2005). 

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

6 INCOME, SOCIAL INCLUSION AND 

European
Union - 27

European
Union - 25

Euro area - 
13

Belgium

Bulgaria

Czech 
Republic

LIVING CONDITIONS

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia

Lithuania

Luxem-
bourg

Hungary

Malta

Nether-
lands

Austria

Poland

Portugal

Romania Slovenia

Slovakia

Finland

Sweden

United 
Kingdom

Croatia

MK
Former
Yugoslav 
Republic 
of 
Macedonia

TR

Turkey

EN 

236 

EN 

 
  
        
      
       
       
       
       
       
      
      
      
         
      
      
          
        
       
         
       
       
       
        
        
      
         
      
      
          
        
         
         
       
         
         
        
        
        
           
        
        
        
      
       
       
       
       
       
      
      
      
         
      
      
        
      
       
       
       
       
       
      
      
      
         
      
      
        
        
       
       
       
       
       
      
      
      
         
        
        
          
        
         
         
       
       
         
        
      
        
         
        
        
        
      
       
       
       
       
       
      
        
      
         
      
      
          
        
         
         
       
       
       
        
        
      
         
      
      
          
      
         
         
         
         
         
        
        
        
           
        
      
        
      
       
       
         
         
       
      
        
      
           
      
      
          
        
       
       
         
       
       
      
      
        
           
      
        
        
        
       
       
       
       
       
      
      
      
         
      
      
          
      
       
         
       
       
       
        
      
      
         
        
      
 
7  GENDER EQUALITY

European
Union - 27

European
Union - 25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland

Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Percentage of women as members in regional councils, autumn 2006

18
Notes: 1) The regional council is the regional legislative assembly which has the legislative power on regional level. 2) DE: Data from March 2005.

31

33

26

15

:

.

:

.

.

.

39

49

12

Percentage of women as members in regional governments, autumn 2006

Note: The regional government is the institution that is the governing authority of a regional political unit.

Source: European database - Women and men in decision-making (http://ec.europa.eu/employment_social/women_men_stats/measures_in41_en.htm).

24

:

:

37

13

13

27

20

.

16

.

33

Women in local councils, 1997
Number of seats

Number of seats occupied by women

Percentage of seats occ. by women

:

:

:

:

:

:

:

:

:

 12 912

 2 565

19.9

:

:

:

:

:

:

 4 658

 177 193

 1 261

 30 973

27.1

17.5

:

:

:

  883

  103

11.7

:

:

:

:

:

:

.

:

:

:

18

 94 886

 18 237

19.2

.

.

:

:

:

.

37

:

:

:

.

.

:

:

:

.

.

 1 105

  114

10.3

12

.

:

:

:

.

.

:

:

:

28

30

17

17

.

24

29

8

6

16

 11 072

 7 508

 2 475

22.4

  929

12.4

:

:

:

 7 337

 1 057

14.4

:

:

:

.

.

:

:

:

12

43

47

18

.

:

:

:

49

46

17

 12 482

 11 006

 23 325

 3 932

 4 533

 6 164

31.5

41.2

26.4

:

:

:

:

:

:

:

:

:

:

1

1

:

:

:

Notes: Local data are incomplete. Due to the huge differences in local level political decision-making data provided are not always comparable. D: No data available for Saxony-Anhalt and Mecklenburg-Vorpommern. A: Only data from Styria available.

Source: European database - Women in decision making (http://www.db-decision.de/FactSheets/lokal_E.htm).

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

7  GENDER EQUALITY

European
Union - 27

European
Union - 25

Euro 
area - 13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland

Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EN 

237 

EN 

 
  
 
8  HEALTH AND SAFETY

European
Union - 27

European
Union - 25

Euro area 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

Healthy life years at 65, in percentage of the total life expectancy at 65, 2005

Males

Females

Source: Eurostat - Health and safety statistics.

:

:

: 

: 

:

:

55.2p

46.8p

:

:

44.8p

38.8p

81.3p

73.8p

38.2p

29.4p

26.1p

19.1p

54.1p

49.5p

55.5p

51.7p

55.7p

42.6p

46.5p

42.6p

55.9p

47.0p

39.8p

25.1p

40.3p

31.6p

39.0p

24.4p

55.9p

45.0p

37.5p

29.0p

64.6p

57.2p

63.1p

54.1p

39.5p

32.6p

58.3p

54.7p

38.7p

26.3p

Percentage of the population aged 16 and over who feel that their health is bad or very bad, by sex, 2005

Males

Females

:

:

: 

: 

:

:

6.7p

9.5p

:

:

11.6p

14.3p

5.5p

8.4p

8.7p

9.6p

14.1p

17.9p

3.7p

3.5p

8.4p

9.4p

10.1p

14.9p

8.7p

8.2p

8.1p

11.0p

11.3p

11.4p

17.7p

25.2p

15.3p

23.0p

6.9p

8.8p

18.8p

24.5p

5.1p

6.2p

4.5p

5.8p

7.2p

9.4p

16.7p

20.5p

15.8p

24.9p

Source: Eurostat - Health and safety statistics (SILC data)

Standardised death rates (SDR) per 100 000 population by sex, 2005

Males
Diseases of the circulatory system

Cancer
Diseases of the respiratory system

External causes of injury and poisoning

Females
Diseases of the circulatory system

Cancer
Diseases of the respiratory system

External causes of injury and poisoning

326

241

67

64

216

136

33

23

301

241

66

62

198

137

33

23

265

234

62

57

178

127

28

22

309

288

113

78

196

149

42

33

833

226

64

73

551

129

28

20

531

314

55

89

357

172

26

34

322

253

80

63

195

197

59

30

304

215

58

45

211

135

30

18

692

308

56

204

377

137

12

46

275

212

99

45

168

158

72

15

319

218

58

50

265

113

40

14

209

233

95

49

140

103

40

15

188

249

48

70

111

121

24

29

274

240

52

50

179

129

21

19

290

150

53

70

203

99

34

39

804

297

63

224

434

137

14

54

750

289

83

271

436

139

19

60

272

216

67

61

191

123

32

26

644

331

73

108

401

173

32

34

317

183

93

35

233

120

39

16

240

240

85

37

148

157

46

19

287

216

52

67

203

133

25

24

491

296

69

103

303

155

27

26

256

216

95

58

188

111

48

17

Notes: EU-27, EU-25, EA-13, FI, SE: 2004; IT: 2002; DK: 2001; BE: 1997. 

 Source: Eurostat - Health and safety statistics.

:

:

:

:

821

236

97

106

601

132

46

28

49.0p

44.4p

36.2p

31.3p

37.1p

31.2p

59.9p

52.5p

60.7p

56.7p

14.7p

17.6p

14.8p

20.0p

9.7p

10.4p

5.0p

7.1p

6.6p

7.2p

359

272

84

94

234

148

35

33

644

304

85

95

426

147

38

22

335

189

60

108

182

116

24

38

278

182

41

62

172

139

27

28

264

217

95

40

172

157

71

17

:

:

:

:

526

308

84

87

372

147

34

29

:

:

:

:

684

209

52

44

566

119

33

17

Practising physicians per 100 000 inhabitants

1995

2005

:

:

:

:

:

:

345

400

345

365

300

355

251

:

307

341

307

319

210

352

393

:

268

380

323

339

386

383

220

258

278

292

405

401

204

328

303

278

:

349

186

:

266

347

232

229

254

268

181

217

:

230

292

304

207

245

288

348

:

236

204

:

231

245

: 

: 

:

:

:

:

:

:

:

:

:

:

:

:

Notes: 1) LU, AT, PL, PT, SI: 2004.  2) FR, LT, MK: professionally active physicians; IE, IT, MT: physicians licensed to practise

Source: Eurostat - Health and safety statistics.

Practising dentists per 100 000 inhabitants

1995

2005

:

:

:

:

:

:

76

83

65

84

61

67

85

:

71

76

58

89

44

55

Notes: 1) LU, AT, PL, SI, SK: 2004  2) FR, IT, LT, NL, MK: professionally active dentists; IE, ES, MT: dentists licensed to practise

Source: Eurostat - Health and safety statistics.

Practising nurses per 100 000 inhabitants

2000

2005

:

:

:

:

:

:

540

611

397

405

760

808

1232

1393

940

975

586

626

:

:

Notes: 1) DK, LU, NL, PL, PT, FI: 2004; FR refer to France Metropolitaine. 2) FI: nurses professionally active; LU: nurses licensed to practise

Source: Eurostat - Health and safety statistics.

102

:

:

:

36

52

68

68

40

60

74

95

35

62

48

72

53

75

35

45

:

48

47

49

42

51

46

37

:

:

27

47

:

60

37

44

82

87

87

82

39

47

56

:

56

68

19

:

:

:

:

:

:

:

:

:

464

:

:

:

275

376

558

591

:

549

:

938

715

715

496

493

353

365

:

:

685

747

:

:

330

342

:

:

833

955

:

:

:

:

:

:

EN 

238 

EN 

 
  
 
Persons discharged from hospitals per 100 000 by ICD diagnosis, 2005

All diagnosis (except healthy newborns)

inlcuding :
Infectious and parasitic diseases

Cancer

Diseases of the blood

Endocrine, nutritional and metabolic diseases
Mental and behavioural disorders

Diseases of the nervous system

Diseases of the eye and adnexa

Diseases of the ear and mastoid process 

Diseases of the circulatory system

Diseases of the respiratory system

Diseases of the digestive system

Diseases of the skin and subcutaneous tissue

Diseases of the musculoskeletal system and 
connective tissue

Diseases of the genitourinary system

Pregnancy, childbirth and the puerperium

Certain conditions originating in the perinatal period

Congenital malformations, deformations and 
chromosomal abnormalities

Symptoms, signs and abnormal clinical and 
laboratory findings, not elsewhere classified

Injury, poisoning and certain other consequences of 
external causes

Factors influencing health status and contact with 
health services

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

Notes: IT, MT, FI: 2004; DK, SE, UK: 2003; DE, LV, HU, PT: 2002 

Source: Eurostat - Health and safety statistics.

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

16084

19852

23030

15936

20164

17923

13505

409

1244

678

1715

535

2061

406

1563

159

555

447

479

153

110

2135

1441

1698

149

644

616

674

502

187

3003

3180

1637

123

517

722

657

659

172

3703

1598

2079

213

419

216

381

115

88

2228

1424

1378

465

2270

127

578

636

1572

128

329

1138

1179

804

459

199

3300

1258

2079

502

104

152

3243

2025

1624

386

869

129

249

108

316

182

85

1255

1401

1230

152

383

310

233

286

315

245

1390

982

1362

1052

1473

1949

1943

1733

1512

830

859

1281

1622

1230

1179

1141

1128

1832

516

720

2422

50

217

227

156

128

245

199

102

740

90

72

148

128

140

167

115

1109

1102

643

192

1351

1634

1317

1956

1552

1987

1191

1370

963

1320

2054

2303

273

220

358

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

10780

16445

14928

6617

20108

22411

17242

25256

6871

10135

26809

184

916

93

181

265

186

140

64

1339

1147

1270

293

1277

259

1331

158

440

364

537

547

107

1973

1005

1697

126

342

415

425

335

118

2481

1144

1462

146

428

83

165

46

80

239

28

780

657

684

115

185

168

74

710

623

1386

1180

970

1567

973

970

1336

154

469

435

159

272

204

174

96

116

151

27

720

1054

695

743

898

1461

1324

861

287

2286

1396

346

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

868

1648

117

410

1089

1121

553

202

4475

2404

1943

281

1744

114

376

1086

649

612

128

2275

1436

1665

416

158

1129

1457

1671

1976

1248

1330

339

138

155

104

225

503

1982

1263

208

157

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

43

183

68

105

61

72

114

37

694

541

592

125

997

98

192

128

179

77

67

1528

731

916

652

2779

147

795

1369

1161

983

280

3696

1796

2439

104

102

410

195

296

972

62

32

770

571

858

3058

1599

1353

421

136

83

183

2045

956

1021

580

848

2853

77

766

101

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

9880

20305

15358

19124

20514

14751

13064

13307

9881

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

981

396

1275

1791

403

1764

137

659

1026

517

323

163

2588

2785

2071

114

463

542

357

523

83

1863

1265

1377

155

398

736

618

420

185

3054

1660

1889

613

1859

170

415

1693

841

165

103

3229

1616

1517

419

1465

207

1032

443

1828

340

1164

122

311

906

415

97

83

2442

957

1183

121

179

371

289

119

65

1452

1197

1177

129

332

977

361

469

79

1849

1147

1179

116

212

360

206

218

73

1554

1424

1039

352

253

310

206

110

261

172

147

1186

1418

1697

893

1101

1242

1043

1212

1631

1569

1019

1335

798

709

732

772

1249

1349

595

1069

223

531

49

328

151

152

250

217

150

164

154

135

109

115

128

416

778

754

49

94

277

689

565

1449

1269

1736

559

160

1279

1515

1586

1972

1396

1238

1042

579

888

683

1692

460

531

998

532

200

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

833

682

832

684

741

608

742

745

1034

612

939

850

:

398

970

846

804

548

700

560

519

:

395

339

:

735

622

401

452

380

1099

766

1083

815

1096

:

909

786

545

744

528

437

755

771

769

645

392

365

783

662

574

484

829

677

801

704

609

:

:

389

588

545

544

470

247

241

Hospital beds per 100 000 inhabitants

1995

2005

Notes: BG, PT, TR: 2004; DK, PL: 2003; SK: 1996

Source: Eurostat - Health and safety statistics.

Number of persons killed in road  accidents

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

63 104

58 995

41 592

59 382

55 523

39 224

60 308

56 530

38 968

59 056

55 275

38 125

57 746

54 194

37 673

55 860

52 349

36 494

53 960

50 488

35 608

53 126

49 769

34 303

49 765

46 570

31 411

46 842

43 481

28 698

44 872

41 274

27 110

1 449

1 356

1 364

1 500

1 397

1 470

1 486

1 315

1 214

1 162

1 089

1 264

1 014

 915

1 003

1 047

1 012

1 011

 959

 960

 943

 957

1 588

1 562

1 597

1 360

1 455

1 486

1 334

1 431

1 447

1 382

1 286

 582

 514

 489

 499

 514

 498

 431

 463

 432

 369

 331

9 454

8 758

8 549

7 792

7 772

7 503

6 977

6 842

6 613

5 842

5 361

 332

 213

 280

 284

 232

 204

 199

 224

 164

 170

 168

 437

 453

 473

 458

 414

 418

 412

 378

 337

 379

 399

2 411

2 157

2 105

2 182

2 116

2 037

1 880

1 634

1 605

1 670

1 614

5 749

5 482

5 604

5 957

5 738

5 776

5 516

5 347

5 394

4 749

4 442

8 891

8 541

8 444

8 918

8 487

8 079

8 160

7 655

6 058

5 530

5 339

7 020

6 676

6 713

6 314

6 633

6 410

6 682

6 775

6 015

5 692

5 426

 118

 128

 115

 111

 113

 111

 98

 94

 97

 117

 102

 611

 550

 525

 627

 604

 588

 517

 518

 493

 516

 442

 672

 667

 725

 829

 748

 641

 706

 697

 709

 752

 760

 70

 71

 60

 57

 58

 76

 70

 62

 53

 49

 46

1 589

1 370

1 391

1 371

1 306

1 200

1 239

1 429

1 326

1 296

1 278

 14

 19

 18

 17

 4

 15

 16

 16

 16

 13

 17

1 334

1 180

1 235

1 149

1 186

1 166

1 085

 987

1 028

 804

 750

1 210

1 027

1 105

 963

1 079

 976

 958

 956

 931

 878

 768

6 900

6 359

7 310

7 080

6 730

6 294

5 534

5 827

5 640

5 712

5 444

2 711

2 730

2 521

2 126

2 028

1 874

1 671

1 668

1 542

1 294

1 247

2 845

2 845

2 863

2 778

2 505

2 499

2 461

2 398

2 235

2 418

2 641

 415

 389

 357

 309

 334

 313

 278

 269

 242

 274

 258

 660

 640

 828

 860

 671

 647

 625

 626

 648

 608

 560

 441

 404

 438

 400

 431

 396

 433

 415

 379

 375

 371

 572

 537

 541

 531

 580

 591

 583

 560

 529

 480

 440

3 765

3 740

3 743

3 581

3 564

3 580

3 598

3 581

3 658

3 368

3 336

:

:

:

:

:

 655

 647

 627

 701

 608

 597

:

:

:

:

:

:

:

 107

 176

 118

 155

 143

6 004

5 428

5 125

6 083

5 713

5 510

4 386

4 274

3 966

4 428

4 525

: 49 438

In last ten years available, 1996-2005 

540 917 505 453 347 614 13 353

9 821 14 340

4 540 72 009

2 138

4 121 19 000 54 005 75 211 63 336

1 086

5 380

7 234

 602 13 206

 151 10 570

9 641

61 930 18 701 25 643

3 023

6 713

4 042

5 372 35 749

Note:Persons killed are all persons deceased within 30 days of the accident. For the countries not following it, corrective factors were applied.

Sources: European Commission: DG for Energy and Transport (CARE Community Road Accident Database) and Eurostat.

EU-27

EU-25

EA-13

BE

BG

CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

HR

MK

TR

8  HEALTH AND SAFETY

European
Union - 27

European
Union - 25

Euro area 
13

Belgium Bulgaria

Czech 
Republic

Denmark Germany Estonia

Ireland Greece

Spain

France

Italy

Cyprus

Latvia Lithuania

Luxem-
bourg

Hungary Malta

Nether-
lands

Austria

Poland

Portugal Romania Slovenia Slovakia

Finland Sweden

United 
Kingdom

Croatia

Former
Yugoslav 
Republic 
of Macedonia

Turkey

EN 

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EN 

 
  
ANNEX 2: SYMBOLS, COUNTRY CODES AND COUNTRY GROUPINGS, OTHER ABBREVIATIONS AND ACRONYMS 

EN 

240 

EN 

 
  
Symbols 

Symbols used in the tables 

The special values are codes which replace real data: 

: 

. 

“not available” 

“not applicable” 

Flags are codes added to data and defining a specific characteristic: 

b 

e 

f 

i 

p 

r 

s 

u 

“break in series (see explanatory texts)” 

“estimated value” 

“forecast” 

“more information is in the note in the end of the table or in the Eurostat web site http://epp.eurostat.cec.eu.int/” 

“provisional value” 

“revised value” 

“Eurostat estimate” 

“unreliable or uncertain data (see explanatory texts)” 

Other symbols 

% 

percent 

EN 

241 

EN 

 
  
 
 
 
 
 
 
 
 
Country codes and country groupings 

Country codes 

AT 

DE 

FI 

IT 

MT 

SE 

Austria 

BE 

Belgium 

Germany 

DK   Denmark  

Finland 

Italy 

Malta 

Sweden 

FR 

LU 

NL 

SI 

France 

Luxembourg 

Netherlands 

Slovenia 

BG 

EE 

HR 

LV 

PL 

SK 

Bulgaria 

Estonia 

Croatia 

Latvia 

Poland 

Slovakia 

CY 

EL 

HU 

LT 

PT 

TR 

Cyprus 

Greece 

Hungary 

Lithuania 

Portugal 

Turkey 

CZ 

ES 

IE 

MK1 

RO 

UK 

Czech Republic 

Spain 

Ireland 

The former Yugoslav Republic of Macedonia (FYROM) 

Romania 

United Kingdom 

Country groupings 

EU-27 

EU-25 

The 27 Member States of the European Union from 1.1.2007: BE, BG, CZ, DK, DE, EE, IE, EL, ES, FR, IT, CY, LV, LT, LU, HU, MT, NL, AT, PL, PT, RO, SI, SK, FI, SE and 
UK. 

The 25 Member States of the European Union between 1.5.2004-31.12.2006: BE, CZ, DK, DE, EE, IE, EL, ES, FR, IT, CY, LV, LT, LU, HU, MT, NL, AT, PL, PT, SI, SK, FI, SE 
and UK. 

EU-15 

The 15 Member States of the European Union between 1.1.1995-30.4.2004: BE, DK, DE, IE, EL, ES, FR, IT, LU, NL, AT, PT, FI, SE and UK. 

EA-13 

The 13 countries of the euro area from 1.1.2007: BE, DK, IE, EL, ES, FR, IE, IT, LU, NL, AT, PT, SI and FI). 
Also called as ‘euro zone’, ‘euroland’ and ‘euro group’. 

NMS-12  The twelve new Member States are BG, CZ, EE, CY, LV, LT, HU, MT, PL, RO, SI and SK (i.e. the Member States which are members of EU-27 but were not members of EU-15.) 

The old Member States are the EU-15 states (see above). 

The new Member States are the NMS-12 states (see above). 

The Candidate Countries are Croatia, the former Yugoslav Republic of Macedonia (FYROM) and Turkey. 

The southern Member States are Greece, Spain, Italy, Cyprus, Malta and Portugal. 

The Nordic Member States are Denmark, Finland and Sweden. 

The Benelux countries are Belgium, the Netherlands and Luxembourg. 

1 

Provisional code which does not prejudge in any way the definitive nomenclature for this country, which will be agreed following the conclusion of negotiations currently 
taking place at the United Nations. 

EN 

242 

EN 

 
  
                                                 
The Baltic States are Estonia, Latvia and Lithuania. 

Other abbreviations and acronyms 

COICOP 

Classification of Individual Consumption by Purpose 

CVT 

CVTS2 

EC 

ECB 

ECHP 

Continuing Vocational Training 

Second Survey of Continuing Vocational Training 

European Communities 

European Central Bank 

European Community Household Panel 

ECHP UDB 

European Community Household Panel – Users’ Database 

ESAW 

European Statistics on Accidents at Work 

ESSPROS 

European System of integrated Social Protection Statistics 

EU 

Eurostat 

GCSE 

GDP 

HBS 

HICP 

ICD  

ILO 

European Union 

The Statistical Office of the European Communities 

General Certificate of Secondary Education 

Gross Domestic Product 

Household Budget Survey 

Harmonised Index on Consumer Prices 

International Classification of Diseases and Health Related Problems 

International Labour Organisation 

ISCED 

International Standard Classification of Education 

LLL 

LFS 

LMP 

Lifelong Learning 

Labour Force Survey 

Labour Market Policy 

NACE Rev. 1  

Statistical Classification of Economic Activities in the European Community 

n.e.c. 

NUTS 

OECD 

not elsewhere classified 

Nomenclature of Territorial Units for Statistics 

Organisation for Economic Co-operation and Development 

EN 

243 

EN 

 
  
PPS 

QLFD 

SES 

SDR 

UOE 

Purchasing Power Standard 

Quarterly Labour Force Data 

Structure of Earnings Survey 

Standardised Death Rate 

UNESCO/OECD/Eurostat 

UNESCO 

United Nations Educational, Scientific and Cultural Organisation 

EN 

244 

EN