EN    EN EN 
 
EN 1   EN  COMMISSION OF THE E UROPEAN COMMUNITIES 
Brussels, 5.2.2010 
SEC(2010) 98 final 
  
COMMISSION STAFF WORKING DOCUMENT 
Joint Report on Social Prot ection and Social Inclusion 
accompanying document to the  
COMMUNICATION FROM THE COMMISSI ON TO THE COUNCIL, THE 
EUROPEAN PARLIAMENT, THE EU ROPEAN ECONOMIC AND SOCIAL 
COMMITTEE AND THE COMMI TTEE OF THE REGIONS 
Proposal for  the Joint Report on Social Prot ection and Social Inclusion 2010  
Supporting document 
COM(2010)25 final 
 SEC(2010)99 
 
EN 2   EN TABLE OF CONTENTS 
1. Scope and Outline of the Report .................................................................................. 4 
2. The social situation in the EU-27................................................................................. 5 2.1. The social impact of the crisis...................................................................................... 5 2.2. Poverty and the crisis in public perception:  main results from EU wide opinion polls9 
2.3. Situation of the Member States' before th e crisis: the role of social protection in 
addressing inequalities and poverty ........................................................................... 10 
2.4. Employment growth doesn't automatica lly lead to a reduction of poverty................ 21 
2.5. The adequacy and sustainability of pension systems................................................. 24 2.6. Health care and long-term car e: ensuring sustainability a nd access to quality services 
for all ........................................................................................................................ .. 29 
2.7. Social protection over the economic cycle................................................................. 31 3. Responding to the crisis and preparing for recovery ................................................. 35 3.1. First evaluation of policy responses........................................................................... 35 3.2. Overview of main policy measures taken in response to the crisis............................ 37 
3.3. The need for effective and efficient soci al inclusion policies during and after the 
crisis ......................................................................................................................... .. 40 
3.4. Supporting the integration of the most excl uded in the labour market and in society 
as whole: the role of activation and a ccess to services .............................................. 41 
3.5. Income support: the specific role of minimum income schemes............................... 42 4. The use of the European Social Funds to  support social objectives during the crisis 
and in the long term.................................................................................................... 53 
4.1. ESF support for social protection and inclus ion: actions respondi ng to the crisis..... 55 
4.2. ESF support for social protection an d inclusion: long-term actions.......................... 59 
4.3. The European Globalisation Adjustment Fund (EGF)............................................... 61 5. The importance and extent of homelessness and housing exclusion ......................... 62 5.1. Housing vulnerability: the importance of  housing in the context of the current 
economic crisis........................................................................................................... 62 
5.2. Housing exclusion –- an important challenge for the EU population at large and 
particularly for those at risk of poverty...................................................................... 63 
5.3. The overall policy response — comprehe nsive strategies and better governance..... 70 
5.4. Causes of homelessness and housing exclusion and instruments .............................. 71 5.5. Monitoring and evaluation ......................................................................................... 75 
 
EN 3   EN 6. Effectiveness and efficiency in the health  sector: some considerations at a time of 
economic crisis........................................................................................................... 77 
6.1. Why more effectiveness and effici ency in health care is needed............................... 78 
6.2. Improving effectiveness and efficiency in the health sector: a look at a number of 
areas.......................................................................................................................... .. 93 
6.3. Conclusions.............................................................................................................. 1 05 
7. Long-term implications of the crisis for the sustainabi lity and adequacy of pensions
............................................................................................................................... ... 107 
7.1. Outcomes of pension reforms prior to the crisis ...................................................... 108 7.2. First effects of the crisis ........................................................................................... 115 7.3. Long-term implications of the crisis ........................................................................ 124 7.4. Policy implications................................................................................................... 126 8. Governance .............................................................................................................. 129 9. Annexes.................................................................................................................... 1 31 
9.1. Indicators................................................................................................................ .. 131 
9.2. Data sources ............................................................................................................. 1 37 
9.3. Annex to part 6 on Health ........................................................................................ 141 
9.4. Statistical tables........................................................................................................ 157 
 
EN 4   EN  
1. S COPE AND OUTLINE OF THE REPORT  
This supporting document was prepared by the Commission services to  accompany the 2010 
Joint Report on Social Protection and Soci al Inclusion [Commission proposal: COM(2010) 
xx]. It provides an assessment of the social si tuation in the 27 Member States, with special 
emphasis on the impacts of the economic crisis and Member States' responses to it. Against this background, and in addition to  more general topical discourse , specific aspects of social 
protection and social exclusion of long-standing concern are e xplored; the sustainability and 
adequacy of pensions; homelessness and hous ing exclusion; and the effectiveness and 
efficiency of healthcare spending.  
As this was not a year for formal cyclical reporting by Member States on Social Protection 
and Social Inclusion, the docum ent draws largely upon material and analysis produced for the 
Social Open Method of Coordination (Social OMC) under the aegis of the Social Protection 
Committee (SPC). In 2009, the SPC carried out important work to improve understanding of 
the context and nature of the policies and reform s that will be needed for successful recovery 
leading to a sustainable and inclusive social  market economy. In the spring and autumn, two 
reports reviewed the social impact of the crisis  and the policy responses of the Member States. 
The report on Growth, Jobs and Social Progress  looked back at ten years of the Lisbon 
Strategy and sought to draw lessons on how the social dimension of the strategy for 2020 
could be strengthened (see box at the end of chapter 2). Learning from the experience of 
Member States in past downturns, the report al so points to the long-term  challenges that will 
accompany recovery. Member States’ specific  reporting on their strategies to fight 
homelessness and housing exclusio n brings a timely focus on a key dimension of social 
exclusion that has become more  acute in the crisis. The SPC adopted a new update of the 
report on theoretical replacement rates of future  pensions. The health chapter is based on 
previous Joint Reports in this area as well as WHO and OECD work (including the 2008 Joint 
EC/OECD conference on improving the efficiency of  health systems). It also draws on recent 
Czech presidency conferences on this topic and the 2007 Luxembourg seminar on the rational 
use of resources in the health sector. 
There is a detailed table of contents, but in summary the re port is organised as follows. 
Section 2 contains an overview of the social situation in th e Member States, including the 
effects of the crisis. It considers the importance of social protection and the need to preserve 
adequate but sustainable protection. It also  looks at public perceptions of poverty and 
separately considers pensions , healthcare and long-term care. Section 3 surveys Member 
States’ policy responses to the crisis and looks at the need for strong policies for inclusion, 
activation, social services, and minimum inco mes both during and beyond the crisis. Section 4 
covers the role of the European Social F und and the European Globalisation Adjustment 
Fund. Section 5 considers homelessness and housing exclusion in more depth. Finally, section 
6 looks at healthcare ex penditure, section 7 the sustainabilit y and adequacy of pensions; and 
section 8 matters of governance.  
 
EN 5   EN 2. T HE SOCIAL SITUATION IN THE EU-27 
2.1. The social impact of the crisis 
As the EU was been hit by the most severe  global recession in decades, strong policy 
intervention has focused on recovery with au tomatic stabilisers playing a major role in 
absorbing the shock and in mitigating the econo mic and social consequences of the crisis. 
However, the human costs of the crisis are difficult to evaluate fully as yet. Despite the prospect of economic recover y, the full impact of the cris is on labour markets and public 
finances is still unfolding and ther e are risks of jobless recovery.  
2.1.1. Forecast 2009-2010  
The latest economic forecast published by the Commission on 3 November 2009 points to the 
first signs of economic recovery. The dramatic fall in EU GDP has come to an end. GDP in 
the European Union is projected to fall by 4.1
 % in 2009 and to grow again by 0.7  % in 2010 
and 1.6  % in 2011. However, the full impact of the crisis on labour markets and public 
finances is still to emerge. Looking ahead, em ployment is expected to  contract by about 2.3  % 
in 2009 and by a further 1.2  % in 2010, resulting in nearly 8 million job losses over the two 
years, in contrast to the net job creatio n of 9½ million during 2006-2008. Unemployment is 
likely to reach 10.3  % in 2010, and social expenditure may rise from 27.5  % to 30.8  % of GDP 
between 2007 and 2010.  
Public finances have also been hit hard. The total EU government deficit is projec ted to triple 
this year (from 2.3  % of GDP in 2008 to 6.9  % in 2009) and to rise further in 2010 to 7.5  %. 
This deterioration follows in part from the wo rking of automatic stabilisers, not least on the 
revenue side and from the discretionary measures taken to support the economy. 
The scope, magnitude and effects of the crisis  vary greatly among the EU Member States. 
According to the Commission forecast,  all Member States but Poland (+1.2  % in 2009) will 
experience a fall in GDP in 2009, with estimates ranging from -18  % in Latvia and Lithuania 
to -0.7  % in Cyprus. Gradual recovery is expected  for 2010, as GDP growth is expected to 
turn positive again in two thirds of the EU c ountries. Among the five largest EU economies, 
real GDP is expected to c ontract this year by about -5  % in Germany, -4.7  % in Italy, -4.6  % in 
the United Kingdom, -3.7  % in Spain, and -2.2  % in France. Of these countries, Germany, 
France, Italy and the UK are expected to return to positive growth in 2010.   
2.1.2. Labour market trends 
At EU level, employment growth has come to a standstill, with the employment rate 
contracting in the second quarter of 2009 to reach 64.8  % in the EU-27 as against 66  % one 
year before. Unemployment rates increased from 6.7% in March 2008 to reach 9.5  % in 
November 2009 and could go up to 10.3  % in 2010 if policies and labour market behaviour 
remain unchanged.  
At national level, the impact of the crisis varies  greatly. Between the second quarter of 2008 
and the second quarter of 2009 employment c ontracted in most EU countries. It fell 
considerably – by 4pp or more – in Ireland, Spain and the three Baltic States, but remained 
stable in Germany, Luxembourg, the Netherlands and Poland. 
 
EN 6   EN In some Member States, the rise in unemployment has been especially stark. In Spain it 
reached 19.4% in November 2009, as against 9.5% in March 08. During the same period it 
also more than doubled in Ireland (12.9% as agai nst 5.2%), in Estonia (15.2% as against 4%), 
Lithuania (14.6% as agai nst 4.3%) and Latvia (22.3% as against 6.1%). 
Some categories of workers have been partic ularly hit by the cris is, including the young, the 
low skilled, employees on temporary contracts, EU  mobile workers, migrants and the elderly. 
Youth unemployment rate reached 21.4% in the EU27 in November 2009 compared with 
14.7% at the end of 2007. Since the start of the crisis, the unemployment rate of non-EU 
workers grew faster than for other workers and reached 18.18.9% in the third quarter of 2009, 
as against 13.6% one year before. 
Data available from a few Me mber States show that the number of workers with flexible 
working time arrangements  varies greatly across countries. In Belgium, 185  000 workers 
were on reduced time in August 2009 as against 120  000 one year before. In Ireland the 
number of workers on reduced working time rose from 20  880 in Q3 2007 to 89  250 in Q3 
2009. In Austria, similar schemes covered 62  000 workers in June 2009, up from 8  800 in 
December 2008 (falling to below 40  000 workers in September 2009). In Bulgaria, 20  000 
workers have come under a similar scheme  since its launch in January 2009. In Germany , 
short-time working was dramatically expanded to cover more than 1.4 million in June 2009 , 
compared with 50  000 one year before. The results of  such differences in scope and 
magnitude can be seen in the differences in the impact of large GDP drops on unemployment. In Germany, in particular, the significant dr op in GDP led only to a moderate increase in 
unemployment (from 7.2% in August 2008 to 7 .6% in November 2009). Luxembourg also 
notes that the sustained promotion of part tim e work arrangements may have contained the 
growth in unemployment rates ob served in the last quarter of  2008 and limited the number of 
unemployed. 
2.1.3. Take-up of benefits 
The direct impact of the recession is appare nt in the growing number of unemployment 
benefit recipients during 2008 a nd into the third quarter of 2009. The crisis has had no clear 
impact on the percentage of older workers cl aiming early retirement benefits, apart from 
upward trends reported in May 2009 in LT, PL and EL.  
Table 2.1a: Countries that have reported sign ificant increases in unemployment benefits
 
claimant since the ou tset of the crisis 
AT: +32.6% between 09-08 and 09-09  ES: +46% between 08-08 and 08-09 
BE: +7.6% between 08-08 and 08-09 IE: +80% between 09-08 and 09-09 
BG: +27.8% between 07-08 and 07-09 FR: +18% between 07-08 and 07-09 
CZ: +80% between 08-08 and 08-09 LV: + 98.7% between 12-08 and 09-09 
DK: +85% between Q4-08 and Q2-09 LT: +216% between 09-08 and 09-09 
DE: +6% between 09-08 and 09-09 LU: +37% between 08-08 and 08-09 
EE: +188% between 08-08 and 08-09  
Source: SPC/ISG questionnaire on th e social impact of the crisis 
The impact in terms of social  assistance claimants became cl ear in the second and third 
quarters of 2009 (See Table 2.1b).  The pressure on last-resort schemes depends both on how 
 
EN 7   EN early the crisis hit the different countries, and on the varying cove rage and duration of 
unemployment schemes. Claimant numbers continue d to increase in the countries first hit or 
most affected by the crisis. Pressure on last  resort schemes has also started increasing 
significantly (by more than 10%) in another fi ve countries. In Denmark and Slovakia, this 
surge followed a period of str ong decline. In  Hungary, Poland1, and the UK the percentage 
dropped slightly. 
Table 2.1b: Countries that have reported signif icant increases in the claimants of social 
assistance since the outset of the crisis 
Countries already reporting a surge in so cial assistance claimants in spring 2009  
15000250003500045000
123 45 67 89 1 0 1 1 1 2 123 45 67 89 1 0 1 1 1 2
2008 2009IE Emergency
SocialAssistance
Ri itIE
 10356085
1 2345678 9 1 0 1 1 1 2 1 234 56789 1 0 1 1 1 2
2008 2009LT Recipients of social
benefit (x1000)LT
 
AT: +10.6% between Q3-08 and Q3-09,  
250000300000350000400000
1 23 456789 1 0 1 1 1 2 1 23 456789 1 0 1 1 1 2
2008 2009PT beneficiaries of Social
assistancePT
  
Countries reporting a surge in social assistance claimants in the autumn 2009  
6000065000700007500080000
123456789 1 0 1 1 1 2 123456789 1 0 1 1 1 2
2008 2009DK Recipients of cash benefitsDK
 CZ: +11% between February 08 and February 09 
CY: +15% between 2008 and September 2009  
                                                 
1 The reason of social benefits dr opping in Poland can be unchanged income criteria for social benefits 
since 2006 while during last fe w years the income of Polish house holds have been noticeably risen 
(there is particularly observed earnings increase). 
 
EN 8   EN 1000012500150001750020000
123 45 678 9 1 0 1 1 1 21 2 34 567 89 1 0 1 1 1 2
2008 2009LV persons with
guaranteed minimumincome (GMI) benefitLV
 130000150000170000190000
1 234 56789 1 0 1 1 1 2 1 23456789 1 0 1 1 1 2
2008 2009SK recipients of
assistance in materialneedSK
 
Source: SPC/ISG questionnaire on th e social impact of the crisis 
2.1.4. Housing 
The impact of the crisis on housing markets and the housing situation of people varied greatly 
across the EU. Housing prices have continued to fall in Ireland (-18% between Q1-08 and 
Q1-09), Spain (-8.34 between Q2-08 and Q2-09) , and LV (-10% between Q1-08 and Q1-09), 
NL (-5.6% between August 08 and August 09) a nd FI (-1.5% between Q2-08 and Q2-09). In 
the United Kingdom, prices ha ve started recovering after th e initial fall obs erved in 2008 
(+7% between January and September 09). Rents  have increased more than general inflation 
in BG (+66% between Q2-08 and Q2-09), LV (+23%), and the Netherlands (+2.9%). Increases in the number of non-performing housing loans were recorded in Belgium, and 
Latvia.  
The number of housing repossessions  has increased  in Denmark (+46.3% in 2009), Spain 
(+126% in 2008), Greece (+17% in 2008), Ireland (+30% betwee n June 08 and June 09), the 
Netherlands (+14.5% between June 08 and June  09) and the United Kingdom (from 10000 in 
Q2-08 to 11400 in Q2-09). This indicates the pot ential severity of the crisis, even though 
repossessions still concern limited numbers of  mortgage holders (e .g. 1594 mortgage holders 
in Denmark, 58686 in ES, 0.38% of mortgage holders in the UK).  
In addition, the consequences of repossessions on families vary greatly across Member States, 
depending on the support mechanisms in place when  people lose their homes. The number of 
beneficiaries of specifi c support schemes to renters has incr eased in IE (+41%  between Q2-08 
and Q2-09) and PT (+40% between June 08 and June 09 even though it concerns a limited number of families benefiting from the Social  Integration Income: 21381) as well as the 
number of beneficiaries of schemes to suppor t mortgage holders in IE: (+144% between Q2-
08 and Q2-09). Finally, the requests and waiting time for social housing  have increased  in 
Ireland, Luxembourg and the UK.  
2.1.5. Over-indebtedness 
Over-indebtedness can be monitored through admi nistrative data on app lications for loan 
arrangements or the number of ‘non-performing’ loans. Worsening over-indebtedness of 
households was initially reported in Greece, Latvia, Lithuania, Austria and Portugal. New evidence shows that over-indebtedness and applications for loan arrangements are now 
increasing in Belgium, Bulgaria, Luxembour g, Austria and (to a minor extent) Portugal. 
These increases also partly reflect long-term tr ends in the consumption pattern of households. 
 
EN 9   EN According to the spring report, debts linked to utility bills  have also increa sed in Lithuania 
and Latvia. In Latvia, for example, unpaid bills  for heating energy at the end of the heating 
season amounted to 15.8 million lats, which is about 66.3  % higher compared to the previous 
heating season, when debts amounted to 9.5 million lats. At the beginning of the 2009 heating 
season, total unpaid heating bills in La tvia came to 1.63 million lats, about 54  % higher than 
in 2008. Over-indebtedness has increased in FR and HU, and difficulties in accessing credit are reported in LT and PL.  
2.2. Poverty and the crisis in public perception : main results from EU wide opinion 
polls 
According to a Flash Eurobarometer conducted in early July for the European Commission, 
citizens’ perceptions are that the economic crisis has had a serious impact on their lives. Although primarily viewed in this way in so me of the southern and eastern European 
countries, the crisis has also made a deep  impression in previously economically sound 
countries, such as Ireland. Over all, about one fifth of Eur opeans say their households are 
facing financial difficulties and a similar percentage say that, on occasion, they have had no 
money to settle ordinary bills or to buy food in the last 12 m onths. A quarter of EU citizens 
expect the situation to get worse in the comi ng year, while just over half foresee no change 
and about one in six think that things will improve. The proportion of Danish, Finnish and 
Swedish citizens who are optimis tic about both the present si tuation and future economic 
prospects is greater than in the other EU Member States. 
Another Eurobarometer survey, carried out in  September 2009, sheds some light on the many 
facets of poverty and social exclusion in the context of the crisis. The survey examined, 
among other things, people’s awareness of the ex tent of poverty within the European Union, 
the perceived personal and societ al reasons behind poverty, who is thought to be most at risk, 
if people feel somehow threat ened by the possible prospect  of poverty, how poverty may 
prevent people from taking full advantage of so ciety, as well as how easy or difficult they 
perceive access to financial services to be. People’s perception of the urgency of government 
action to combat poverty is also examined, togeth er with the level of administration felt to be 
mainly responsible for taking action. 
EU citizens are strongly awa re of the problem of poverty  and social exclusion in today’s 
society: three out of four Europeans (73
 %) feel that poverty in th eir country is widespread. 
However, the extent to which pove rty is seen as widespread di ffers greatly from country to 
country. In Bulgaria, Hungary, and Romania 90  % or more of citizens perceive it to be 
widespread. Conversely, fewer than four in ten think that poverty is widespread in Denmark 
(31  %), Cyprus (34  %) and Sweden (37  %). 
High unemployment (52  %) and insufficient wages and salaries (49  %) are the most widely 
perceived ‘societal’ explanations for poverty , together with insufficient social benefits and 
pensions (29  %) and the excessive cost of decent housing (26  %). Meanwhile, a lack of 
education, training or skills (37  %), as well as ‘inherited’ poverty (25  %) and addiction (23  %) 
are the most widely perceived ‘personal’ reas ons behind poverty. 
Over half of Europeans (56  %) believe that the unemployed are most at risk of poverty , 
while 41  % believe that the elderly are most vulnerable, and 31  % see those with a low level of 
education, training or skills as  most at risk. Other social  categories considered most 
vulnerable by Europeans are people in precariou s employment, people with disabilities, and 
those suffering from some form of long-term illness. 
 
EN 10   EN Close to nine out of ten Europeans (87  %) believe that poverty hampers people’s chances  of 
gaining access to decent housing, while eight out of ten feel that being poor limits access to 
higher education or adult learning, and 74  % believe that it damages their chances of finding a 
job. A majority of Europeans (60  %) believe that access to a d ecent basic school education is 
affected, and 54  % believe that the ability to maintain a network of friends and acquaintances 
is limited by poverty. 
While the majority of Europeans do not report  difficulties in gaining access to financial 
services, the picture for the most  vulnerable is very different. 70  % of the unemployed  in the 
EU find it difficult to get a mortgage according to the survey results, as against 49  % of the 
general population. A further 58  % of unemployed people, compar ed with an EU average of 
34 %, have problems getting loans, and 47  % find it difficult to get a credit card (the EU 
average is 27  %). 72  % of Europeans who have difficulties making ends meet find it difficult 
to get a mortgage, 64  % find it difficult to get a loan, and 55  % find it difficult to get a credit 
card. 
On average, 89  % of Europeans say that urgent action is needed by their national 
governments  to tackle poverty. Across Europe, 53  % feel that their na tional governments are 
primarily responsible for combating poverty. Ev en if Europeans do not regard the European 
Union as primarily responsible for combatin g poverty, its role is  nonetheless seen as 
important by many (28  % see it as ‘very important’, and 46  % ‘somewhat important’). 
2.3. Situation of the Member States' before the cr isis: the role of social protection in 
addressing inequalities and poverty 
2.3.1. At the outset of the crisis the situat ion of Member States varied greatly 
As highlighted above, not all Memb er States were in the same si tuation when hit by the crisis. 
In particular, the size and structure of social protection varied greatly, as illustrated in Figure 
2.1. Generally, richer countries spend a larger share of thei r GDP on social protection, and 
periods of economic growth had allowed ma ny governments in the EU  to devote more 
resources to social policy inte rvention. The structure of social  protection expenditure shows 
that old-age pensions and sickness and healthca re benefits represent the bulk of spending in 
all EU Member States, and have also been the areas where most reforms have taken place. Social protection plays a redistributive role ove r the life-cycle, insuring people against social 
risks and helping reduce poverty. 
 
EN 11   EN Figure 2.1 Expenditure on social protection benefi ts - gross, by function, in % of GDP — 
2007 
05101520253035
eu27 lv ee ro lt bg sk ie pl mt cz cy lu es si hu pt gr fi uk it de nl at be dk fr seOld age and survivors Sickness/Health care
Disability Family/Children
Unemployment Housing and Social exclusion n.e.c.
 
Source: Eurostat – ESSPROS 2007 
2.3.2. Risk of poverty vary greatly across the EU 
In 2008, 17% of the EU population was at risk of poverty, living on less than 60% of the 
national median income. The aggregate figure hides marked differences across Member 
States, ranging from 9-12% in the Czech Re public, the Netherlands, Slovakia, Denmark, 
Hungary, , Austria, , Slovenia a nd Sweden to 20-26% in Spain, Greece, Lithuania, Bulgaria 
Romania and Latvia. However, being at risk of poverty relates to very different living 
standards across the EU, as illustrated by the large differences in the levels of poverty thresholds apparent in figure 2.2 (right axis). Even when correct ed for differences in the cost 
of living, poverty thresholds ar e five times higher in the UK at  the top of the ranking after 
Luxembourg (which is clearly an  outlier) than in the two count ries at the bottom (Romania 
and Bulgaria).  
 
EN 12   EN Figure 2.2: At-risk-of-poverty rate and illust rative value of the at-risk-of-poverty 
thresholds (single adult household); 2008 
051015202530
EU
27EU
15NMS
10c zn ls k d k * d kh ua ts is e f r l u f i b e d e m ti ec yp lp te e i tu ke le sl tb gr ol v% of total population
0300060009000120001500018000
In Purchasing Power Standard sAt-risk-of-poverty rate (left axis)
Value of thresholds for a single household (right axis)
 
Source: EU-SILC (2008). dk*: values including imputed rent2 
Over the last decades a shift in poverty risk s was observed from the elderly towards younger 
people. Child poverty remained stable or in creased in many EU countries with some 
exceptions (CZ, EE, IE, LT, PL - see figure 2.4) , while poverty risks ge nerally decreased for 
the elderly as a consequence of the maturi ng of pension systems (including reforms of 
minimum pensions). Today, both children and the elderly3 face a risk-of-poverty of 20% and 
19% against 17% for the overall population. Howe ver, age patterns of poverty differ across 
countries. 
                                                 
2 Two values are presented for Denmark, with and without imputed rent. See footnote below and 
methodological note in annex. 
3 To evaluate the relative position of older people, only monetary income (notably deriving from 
pensions) is taken into account. The wealth of pensio ners, in particular house ownership (and associated 
imputed rents), private savings, private pensions, or specific housing supplements which have a strong 
effect on the income distribution of pensioners, are not taken into account, nor are other non-monetary benefits (free healthcare, transport, etc.). For this reason, the poverty risk of older people may be 
somewhat overestimated. The possibility to include imputed rent in the definition of income will be 
examined by the ISG in the coming years. 
 
EN 13   EN Figure 2.3: At-risk of povert y rate by age group, 2008  
0510152025303540
eu27 cz nl si sk dk cy at se be dk* hu mt fi fr lu ie de ee uk es it pl pt bg lt el lv roChildren (aged 0-17)
Working age
population (aged 18-64)
Elderly (aged 65+)Cyprus 
elderly 
poverty: 
49%Latvia 
elderly 
poverty: 
51%
 
Source: EU-SILC (2008). dk*: values including imputed rent 
2.3.3. Poverty trends across countries and age groups 
As the 2008 SILC data becomes available it is now  possible to observe first evolutions in at-
risk-of-poverty rates. Figure 2.4 presents the evol ution of the at-risk-of poverty rate for the 
EU-25 and 25 Member States separately. The analysis excludes Romania and Bulgaria for 
which EU-SILC comparable data are only availa ble starting from 2007. It has to be kept in 
mind that at-risk-of-poverty rates figures are su bject to confidence inte rvals of 1 percentage 
point at the most aggregated le vel, and therefore changes over  time are only meaningful for 
changes of more than 2 to 3 pe rcentage points (depending on th e breakdown). At EU-25 level, 
the at-risk-of poverty rate remained at 16% between 2005 and 2008, at 16%, and over the 
period both children and the elderly experien ced risks of poverty by 3 percentage points 
higher than the overall population, with child pov erty increasing slightly  from 19% to 20% in 
2008.  
This overall stability at EU level hides grea t diversity. When looking at the old Member 
States (EU-15) and the Member States who joined in 2004 (NMS10) separately, the data shows that in the EU-15 the elde rly (65+) are at higher risk of  poverty than both children and 
working age population (20% agai nst respectively 18% and 15 %). This relation remained 
stable over the period. On the contrary, in the NMS10 they experienced much lower risks of 
poverty in 2005 than children and the working age population (8% against 25% and 17% respectively). This reflects par tly the age orientation of social  protection in these countries 
where pensions used to appear relatively gene rous compared to weak support to families with 
children. During the period, the relative situation of childre n and the elderly evolves rapidly, 
with the child at-risk-of-povert y rate dropping by 5 percentage poi nts and the elderly risk of 
poverty rate increasing by 4 percentage points.  
 
EN 14   EN In most of the old EU-15 Member States, the risk  of poverty remained rather stable for all age 
groups. Exceptions are in Germany, Finland and Sweden where it increased for all age 
groups, while in Greece and France it increa sed for children while it was decreasing the 
elderly. Ireland, and to lesser de gree Portugal are the only countri es to have re duced the risk 
of poverty for all age groups between 2005 and 2008. 
This first insight in recent trends calls for further analysis, especially of the reforms that were 
implemented in EU countries during the period. The supporting document to the Joint Report 2009 contains interesting elements drawn fr om the National Strategy Reports 2008-2010 and 
the SPC report on minimum inco me provision for the elderly
4 that could support this analysis, 
but would need further elabora tion. It lists new measures ta ken in the area of child poverty, 
and it provides information on the recent evolution of pension systems that could help explaining the strong trends obs erved for both children and the elderly in some countries. 
Large increases in the at-risk-of poverty rate of the elderly have been observed in a number of 
Member States, especially in those that have experienced str ong economic growth, 
accompanied by a strong increase in wages in the years before the crisis. Further analysis would be needed to fully understa nd the deterioration of the relati ve situation of the elderly in 
these countries. However, there are indications that where pens ions were indexed to prices 
and not to wages, at-risk-of poverty rates for th e elderly have increased dramatically. In some 
MS, however, some of the impacts of reform s to improve minimum income pensions and 
reduce poverty rates may have been dampened by faster increases in the income of the 
working age population (e.g. ES, CY, FI and UK). In some cases, an improvement of the 
relative income situation of the elderly may ha ve resulted from a strengthening of pension 
benefits (e.g. IE). This illustrates that the t ype of indexation of benefits can significantly 
influence the evolution of the relative income position of the elderly over time compared to 
the working age population. This applies specifi cally to minimum income pensions which 
play an important role in averting poverty in old age. 
Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 
5101520253035
2005 2006 2007 2008eu25 All eu25 0-17
eu25 18-64 eu25 65+
 5101520253035
2005 2006 2007 2008
eu15 All eu15 0-17
eu15 18-64 eu15 65+
 
                                                 
4 Minimum income provision for older people and their contribution to adequacy in retirement, SPC 
study 2006 
 
EN 15   EN Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 
5101520253035
2005 2006 2007 2008
nms10 All nms10 0-17
nms10 18-64 nms10 65+
 5101520253035
2005 2006 2007 2008be All be 0-17
be 18-64 be 65+
 
5101520253035
2005 2006 2007 2008cz All cz 0-17
cz 18-64 cz 65+
 5101520253035
2005 2006 2007 2008
dk All dk 0-17
dk 18-64 dk 65+ 
5101520253035
2005 2006 2007 2008
de All de 0-17
de 18-64 de 65+ 510152025303540
2005 2006 2007 2008ee All ee 0-17
ee 18-64 ee 65+
 
5101520253035
2005 2006 2007 2008 ie All ie 0-17
ie 18-64 ie 65+
 5101520253035
2005 2006 2007 2008
el All el 0-17
el 18-64 el 65+
 
 
EN 16   EN Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 
5101520253035
2005 2006 2007 2008
es All es 0-17
es 18-64 es 65+
 5101520253035
2005 2006 2007 2008 fr All fr 0-17
fr 18-64 fr 65+
 
5101520253035
2005 2006 2007 2008 it All it 0-17
it 18-64 it 65+
 51525354555
2005 2006 2007 2008
cy All cy 0-17
cy 18-64 cy 65+
 
51525354555
2005 2006 2007 2008
lv All lv 0-17
lv 18-64 lv 65+
 5101520253035
2005 2006 2007 2008 lt All lt 0-17
lt 18-64 lt 65+
 
5101520253035
2005 2006 2007 2008
lu All lu 0-17
lu 18-64 lu 65+
 5101520253035
2005 2006 2007 2008
hu All hu 0-17
hu 18-64 hu 65+ 
 
EN 17   EN Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 
5101520253035
2005 2006 2007 2008
mt A ll mt 0-17
mt 18-64 mt 65+
 5101520253035
2005 2006 2007 2008nl All nl 0-17
nl 18-64 nl 65+ 
5101520253035
2005 2006 2007 2008at All at 0-17
at 18-64 at 65+
 5101520253035
2005 2006 2007 2008pl All pl 0-17
pl 18-64 pl 65+ 
5101520253035
2005 2006 2007 2008 pt All pt 0-17
pt 18-64 pt 65+
 5101520253035
2005 2006 2007 2008si A ll si 0-17
si 18-64 si 65+ 
5101520253035
2005 2006 2007 2008sk A ll sk 0-17
sk 18-64 sk 65+
 5101520253035
2005 2006 2007 2008fi All fi 0-17
fi 18-64 fi 65+
 
 
EN 18   EN Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 
5101520253035
2005 2006 2007 2008
se A ll se 0-17
se 18-64 se 65+5101520253035
2005 2006 2007 2008
uk All uk 0-17
uk 18-64 uk 65+
Source: EU-SILC 
2.3.4. Living standards vary greatly across the EU 
Material deprivation rates complement the pict ure given through the at-risk of poverty rates 
by providing an estimate of the proportion of  people whose living conditions are severely 
affected by a lack of resources. The material deprivation rate provid es a headcount of the 
number of people who cannot afford  to pay their rent, mortgage or utility bills, keep their 
home adequately warm, face unexpected expens es, eat meat or proteins regularly, go on 
holiday, or cannot afford to buy a televisi on, a washing machine, a car or a telephone5.  
17% of Europeans live in these difficult condi tions. However, in Bulgaria, Latvia, Hungary, 
Poland and Romania more than 30% of people ar e affected. The material deprivation rate 
complements the at-risk of poverty rate by reflec ting the differences in living standards across 
the EU, as it,, depends as much on the level of  development of the country as on the social 
policies operating redistribution. These disparitie s in material deprivation rates reflect the 
large differences in GDP per capita that remain  between EU countries. This emphasizes that 
the fight against poverty in the EU will benefit from a greater economic growth as well as from greater territorial cohesion within the EU.  
                                                
 
5 The indicator recently adopted by  the social protection committee me asures the percentage of the 
population that cannot afford at least 3 of the 9 items quoted above. 
 
EN 19   EN Figure 2.5: At-risk-of poverty and material deprivation rates (%) and at-risk-of-poverty 
thresholds (€-PPS per year for a single household); 2008 
0102030405060
EU
27EU
15NMS
10lu nl se dk es fi uk be ee de fr mt ie at cz it si el cy pt lt sk pl lv hu ro bg% of total population
0300060009000120001500018000
In Purchasing Power StandardsAt-risk-of-poverty rate (left axis)
Material deprivation rate (left axis)
Value of thresholds for a single household (right axis)
 
Source: EU-SILC (2008). Material deprivation data for Denmark refers to 2007 
2.3.5. The evolution of inequalities and poverty in the last decade 
The design of the tax-benefit sy stem is crucial in determining the way and extent to which it 
affects income inequalities and redistributes resources to the poor. Important features include 
the progressivity of taxes and benefits and the degree of targeting and conditionality of benefits, which can create disi ncentive effects, if badly designed. Available evidence 
highlights the large variation across Member States in net cash support for low-income 
households. EU data show that social transfers other than pe nsions effectiv ely reduce poverty 
risks but the degree to which they do so vari es substantially across Member States (ranging 
from a poverty reduction effect of 50% or more in some countries to one of 17% or less in 
others). This largely reflects differences in th e size of expenditure, which varies from 12% to 
30% of GDP, but the composition of expenditu re, the quality of interventions, and, more 
broadly, the efficiency and effectiveness of soci al protection also play  an important role.  
 
EN 20   EN Figure 2.6 – Impact of social transfers (excluding pensions ) on the at-risk-of-poverty 
rate for the total populatio n (percentage reduction), 2007 
010203040506070
EU25EU27 el lv es it bg ee ro lt cy pt pl uk mt de sk fr be nl lu si at fi ie cz dk se hu
 
Source: EU-SILC 2008 
Despite the clear redistributive effect of social protection, in equalities have often increased 
and poverty and social exclus ion remain a major issue in most EU countries. Most increases 
in inequalities  happened between the mid-1980s and th e mid-1990s. Over the last 10 years 
inequalities have remained stable in most c ountries, but a few stand out as exceptions. Behind 
these overall developments, divergent trends were  observed at different levels of the income 
distribution. In most countries, top incomes grew  relatively faster th an middle incomes. In 
some countries, low incomes caught up with me dian incomes, while in other countries 
inequalities also widened at the bottom of the distribution. 
According to national sour ces gathered by the OECD, relative poverty risks  increased in 
most Member States between the mid-1980s and th e mid-1990s and in most  cases they either 
increased or remained stable between the mi d-1990s and the mid-2000s. Fully comparable EU 
data available for the last three years confirm th e stability of relative pov erty, but at the same 
time show that living standards improved in  the new Member States, as measured by material 
deprivation rates (Figure 2.7)6. 
                                                 
6 See also SPC report on "Growth, Jobs and Social Progress: a contribu tion to the evaluation of the social 
dimension of the Lisbon Strategy", 2009 
 
EN 21   EN Figure 2.7: Trends in poverty rates and ma terial deprivation, Total population - 2005-
2008 
05101520253035404550
2005 2006 2007 2008 2005 2006 2007 2008
Risk of poverty Material Deprivation% of total populationEU27 EU15 NMS10
 
Source: EU-SILC (2008, 2007, 2006, 2005); Without BG and RO 
2.4. Employment growth doesn't automatica lly lead to a reduction of poverty 
Significant progress has been made in raising employment rates across Europe  - especially 
for women - and also in reversing negative trends  such as the decline in the participation of 
older workers. Indeed, unemployment rates fell  significantly in the EU  (from 8.7% in 2000 to 
7.1% in 2007) while the increa sed participation of older wo rkers and of women as second 
earners (notably through the availability of part -time work) has helped to improve the income 
of many households. 
The experience of this decade has confirmed that having a job remains the best safeguard 
against poverty and exclusion , since the poverty risk face d by unemployed working age 
adults is more than five times higher than t hose in work (44% against 8%), and the inactive 
(other than retired) f ace a risk-of-poverty that is three ti mes higher than that  of the employed 
(27% against 8%).  
 
EN 22   EN Figure 2.8: At-risk-of-poverty rate of the une mployed and of the inactive (not retired) 
vs. people employed, people aged 18+, 2008 
010203040506070
eu27 cz nl sk hu lu at dk fr se si mt be de fi ie pl cy it pt uk es el lt bg ee ro lvEmployed
Unemployed
Inactive (not retired)
 
Source: EU-SILC 2008 
However, having a job is not always a guara ntee against the risk  of poverty and the working 
poor  represent one third of the working age a dults at-risk-of-poverty. In 2008, 8% of the 
people in employment were li ving under the poverty threshold. This figure has not improved 
since 2005. In-work poverty is linked to empl oyment conditions such as low pay, low skills, 
precarious employment or under-employment.  
Figure 2.9: In-work poverty, overall and by type  of contract, people in employment aged 
18+, 2008 
0510152025
eu27 cz be dk hu mt nl si fi ie cy at sk bg de ee fr se it lt lu uk es lv pl pt el roWorking poor: total 18+
Permanent contract
Temporary contract
 
 
EN 23   EN Source: EU-SILC 2008 
Since 2000, the rise in temporary work (s ee Figure 2.10), part-time work (including 
involuntary part-time working) along with sometimes stagna ting wages has increased the 
number of individuals with low yearly earnin gs. These trends have particularly affected 
women and the young. In addition, evidence shows that workers working part-time or on 
temporary contracts are generally paid less per hour  after controlling for differences in 
education and experience , and for many, these jobs are not stepping stones towards 
better jobs . 
Figure 2.10: Increase in the share of workers  on temporary contracts, by age 2000-2008, 
EU27 
051015202530354045
2000 2001 2002 2003 2004 2005 2006 2007 2008
Total 15 to 24 25 to 49 50+Young 
workers: +14%
Older 
workers: +9%Total: +15%
Prime age 
workers: +24%
 
Source: EU - Labour Force Survey 
In-work poverty is also related to low work intensity  in the household, i.e. where there are 
too few adults in the household working, or working enough, to make a living (too few hours 
or only part of the year). Among these, singl e and lone parent households not working full 
time, as well as one-earner families face the highest risks of poverty.  
The last decade has also seen the persistence of groups of people who remain outside or on 
the margins of the labour market , often facing multiple barriers to entry (including low 
skills, care responsibilities, age, migrant background, disabili ty and other discriminatory 
factors, etc.). The worst-off are those house holds in which nobody works. In 20082008 in the 
EU27, 9.2% of adults of working age and 9.2% of children were li ving in jobless households 
as against 10.1% and 10.2% in 2001. The crisis is likely to increase the number of families 
having to rely entirely on social benefits. In 2008, the percentage of  children in jobless 
households has already started to increase significan tly in Ireland (13.1% against 11.5% in 
2007), Spain (6.5% up from 5.3%), Italy (6.7 % up from 5.8%), Lithuania (9.9% up from 
8.5%), and Hungary (14.6% up from 13.9).  
 
EN 24   EN Figure 2.11 EU-27 - Employment and unemployment rates and shares of children and 
adults (aged 18-59 and not students) liv ing in jobless households; 2001-0808 — % 
68101214
2001 2002 2003 2004 2005 2006 2007 20085860626466
Adults (18-59, not students) living in jobless households (left axis)
Children  living in jobless households (left axis)
Unemployment rate (left axis)
Employment rates (right axis)
 
Source: EU Labour Force Survey 
National experiences from past crises show that  long-term unemployment or inactivity tend to 
persist long after recovery ha s set in. In some countries, in creasing numbers of people are 
moving onto long-term sickness and disability benefits or early retirement schemes. Of these 
people, many are likely never to enter or re turn to the labour market. Some short-term 
responses to sudden increases in unemploym ent can exacerbate thes e trends and should 
therefore be avoided. 
2.5. The adequacy and sustainability of pension systems 
How does the income of the elderly compare to the rest of the populatio n? Currently, pension 
systems have significantly reduced poverty am ong older people, though the risk of poverty is 
higher older people than for the general population  and, on average, people aged 65+ have an 
income which is around 83% of the income fo r younger people, ranging from 54% in Latvia 
to more than 100% in Hungary. However, single  elderly women still f ace a much higher risk 
of poverty than single men. 
 
EN 25   EN Figure 2.12: Relative income of the elderl y: median income of people aged 65+  
as a ratio of the income of people aged 0-64, 2008 
0,000,200,400,600,801,001,20
lv
cy
ee
bg
dk
dk 1
lt
fi
uk
ie
be
mt
se
es
cz
sk
pt
nlsi
ro
el
de
it
at
fr
lu
pl
hu
male female
 
Source: SILC (2008) Income reference year 2007; except for UK (income year 2008) and for IE (moving income 
reference period 2007-2008). 
Note: To evaluate the relative position of older people, only monetary income (notably deriving from pensions) 
is taken into account. The wealth of pensioners, in particular house ownership (and associated imputed rents) and 
private savings, which have a strong effect on the inco me distribution of pensioners, are not taken into account, 
nor are other non-monetary benefits (free healthcare, tran sport, etc.). The possibility to include imputed rent in 
the definition of income will be examined by the ISG in the coming years. 
One of the ways to ensure both the sustainabilit y of pension systems and an adequate level of 
income for pensioners is to extend working lives . The EU's target under the growth and jobs 
strategy is to reach a 50% employment ra te for older workers by 2010. In 2007, the 
employment rate for older workers in th e EU-27 was 45% compared to 37% in 2001.  
The future adequacy and sustainability of pensions can be assessed using theoretical 
replacement rates. They show how  changes in pension rules can affect pension levels in the 
future. A look at the link between theoretical replacement rates and the evolution of pension 
expenditure shows that developmen ts in pension promises can involve a heavy future cost in 
the light of an ageing society, if labour market  patterns remain constant. Put more simply, a 
country with an ageing population which aims to maintain the same replacement rate will 
inevitably need to devote more resources to pe nsions. The burden of this could be dampened 
by increasing the size of available resources, either by increasing employment and/or capital, 
or minimising administration costs. 
Future levels of pensions in relation to earnings (income replacement levels) will depend on 
different factors, notably the pace of accrual of pension entitlements (which is linked to 
developments in the labour market), the matu ration of pension schemes and the effect of 
reforms. However, most Member States are in a situation where reforms of statutory schemes 
will lead to a decrease of replacement rates at given retirement ages. This most probably 
 
EN 26   EN reflects of reforms that have lowered future bene fit levels at a fixed retirement age in order to 
cope with increasing longevity and the expenditure this would otherwise entail7. As a result 
many Member States have also increased in centives to work longer. Measures include 
increasing retirement age, flexible retirement options, increasing contributory periods needed 
for a full pension, and designing work incentives into pension schemes. These offer ways and 
means to bring effective retirement age into lin e with expected increases  in life expectancy.
 
                                                 
7 Given that the employment rate has risen, more people will be entitled to pensions in their own right – 
and thus for instance the need to have high replacemen t rates for a husband to support his wife in old 
age has been reduced. It is also important to point out that more people are surviving to receive state 
pensions and they are receiving them for longer – so while on a year-on-year basis they might be 
getting lower pensions, when looking at the overall transfer during retirement they might be getting 
more than previous generations. 
 
EN 27   EN Table 2.2: Change in theoretical replacement rates for a worker  with average earnings retiring at 65 after 40 years, 2006-2046 
NET
Total TotalStatutory 
pensionType of 
Statutory 
Scheme (DB, 
NDC or DC), 
2046Occupational 
and 
supplementary 
pensionsType of 
Occupational or 
Supplementary 
Scheme (DB or 
DC), 2046Statutory 
pens ions , 
2006Occupational 
and Voluntary 
pensions, 2006Statutory pensions ( 
or in some cases 
Social Security): 
Current (2006) and  
Assumed (2046)Occupational 
and voluntary 
pensions: 
Estimate of 
current (2006)Occupational 
and voluntary 
pensions: 
Assumption 
(2046)Evolution of 
statutory 
pens ions  
expenditures 
between 2007 
and 2045 
(source 
EPC/AWG)***
BE 4 5 0 DB 5 DC 100 55 16.36 NA 4.25 4,8
BG 15 15 15 DB and DC / NA / NA /  2,9
CZ -21 -16 -16 DB / 100 / 28 /  1,8
DK 7 20 -10 DB 30 DC 100 78 0.9 8.8 12.7 0,8
DE 12 - 9 D B 1 1 D C 90 70 19. 5 NA 4 1,7
EE 11 9 9 DB and D C / 100 / 22 / 0,8
EL -7 -12 -12 DB / NA / 20 / 8,6
ES -12 -9 -9 DB / 89 / 28.3 / 5,9
FR -17 -16 -16 DB / 100 / 20 /  1,3
IE -11 -10 -2 DB -9 DC 100 55 9.5 10-15 10 3,1
IT 3 -3 -17 DB and NDC 14 DC 100 22(M)/17(F)* 33 5.7 6.91 1,6
CY 14 11 11 DB / 100 / 16.6 /  6,2
LV -12 -11 -11 NDC and DC / 100 / 20 /  2,8
LT -3 1 1 DB and DC / 89 / 26 /  4,3
LU 0- 1 - 1 D B / 9 2 / 2 4 /  1 1 , 1
HU 5 13 13 DB and DC / 100 / 26.5 /  3,9
MT -9 -8 -8 DB / 100 / 30 / 4,7
NL 6 11 2 DB 10 DB 10 0 91 7 9.8 11.5 -12.5 4,3
AT 51 1 D B / 100 / 22.8 / 1,6
PL -19 -16 -16 NDC and D C / 77 / 19.52 / -0,7
PT -20 -20 -20 DB / 81 / 33 / 1,3
RO 52 39 39 DB and DC / NA / 29 /  7,7
SI 2 -4 -4 DB / 100 / 24.35 /  6,9
SK 2 1 1 DB and DC / 100 / 28.75 /  2,2
FI -11 -12 -12 DB / 100 / 21.6 /  4,2
SE -13 -13 -11 NDC and DC -2 DC 100 90 17.2 4.5 4.5 1,8
UK -4 -2 -3 DB 0 DC 100 53 (M)/56(F) 19.85% (17.25%) 9 8 1,8Contribution rates** Coverage rate (%) GROSS Replacement RateAssumptions Change in Theoretical replacement rates in percentage points (2006-2046)
 
Source: ISG calculations done using the OECD APEX  model or national mode ls, EPC/AWG projections 
*Note: Figures as of June 2008  
**Note: Contribution rates used for statutory schemes and also an y occupational or private schemes included in the base case, t hus providing indicators for the representativeness of the base case. Contribution rates 
correspond to overall contribution rates as a share of gross wages (for employees and employers) used as assumptions for the ca lculation of theoretical replacement rates.  Contribution rates may differ from current 
levels reflecting for instance projected increases in contribution rates, in particular as regards assumptions used for second pillar schemes. DK refers to contributions to the ATP (statutory supplementary labour 
market pension), though it should be recalle d that the financing of the first pillar mainly comes from the general budget. For CY one fourth (4%) comes from the general state budget. For LU one third (8 %) also 
comes from the general state budget. For MT of the breakdown is 10  % from the employee, 10 % from the employer and 10 % from th e state. For PL this corresponds to old-age contributions (19.52 % of wages) 
and disability and survivor's contributions (13% of wages). For PT this corresponds to  a general estimate (ratio between overal l contributions and aggregate wages declared to social security).  In Portugal the TRR 
will fall partly due to the introduction of the sustainability fact or related to life expectancy. It should be noted that the a ctual pension cuts resulting from the sustainab ility factor have been lower than previously 
expected in the 2006 projections. ***Note: AWG projections figures include funded tiers  of statutory schemes and statutory earl y retirement schemes 
 
EN 28   EN However, as the work histories required for a fu ll pension are being extended it is important to 
protect vulnerable group s and cater for career breaks whic h should not be unduly penalised in 
the pension system. While the most vulnera ble groups are often protected by minimum 
income provision (see Figure 2.3 above for risk-of-poverty among the elderly), persisting 
labour market differences between men and women translate into income inequalities in old 
age. Member States have legislated to equalis e pension eligibility ages for men and women to 
help ensure that women can have a decent re tirement income. Furthermore, care burdens, 
which still mainly fall on women, and the wa y they result in lowe r pensions, are being 
monitored, and an increasing number of countries  are beginning to give pension entitlements 
for care-related absences from the labour market. 
Figure 2.13: Accumulated difference in net theore tical replacement rates for an average earner 
entering the labour market at 25 and retiring at the statutory retirement age with a 1, 2 or 3 
year career break for childcare compared with no break 
-8-6-4-2024
FR
CZ
ES
LU
MT
FI
AT
BE
EL
SE
EE
SK
IE
DE
DK
LT
IT
UK
PL
CY
HU
PT
NL
BG
LV
SI
RO
 1 year 2 years 3 years
 
Source: SPC/ISG 
Note: the values for CZ, ES, LU and MT are equal to 0 and should not be interpreted as missing.  
Given the current economic downturn and incr easing unemployment, protecting the pension 
entitlements of future pensioners during periods  of unemployment is also an emerging feature 
in most pension systems across the EU. The ri sk of unemployment is well covered by public 
pension schemes in many Member States. Nevert heless, it is definitely  less true for funded 
pensions and the preservation of pension enti tlements during unemployment is typically less 
generous than for periods of child care. However, it is important to monitor such protection of 
pension entitlements together with the eff ects on work incentives in order to prevent 
becoming a new dependency traps. 
 
EN 29   EN Figure 2.14. Accumulated difference in net theore tical replacement rates for an average earner 
entering the labour market at 25 and retiring at  the statutory retirement age with a 1, 2 or 3 
year career break due to unemploym ent compared with no break* 
-7-6-5-4-3-2-1012
MT
PT
FR
CZ
ES
HU
BG
EL
DK
IE
NL
AT
LT
EE
SI
UK
BE
SE
LU
CY
DE
PL
LV
IT
FI
SK
RO
 1 year 2 years 3 years
 
Source: SPC/ISG* The unem ployment break is assumed to take place in the years just prior to old age retirement 
which is assumed here to be the statutory retirement age for men. Note: the values for MT and PT are equal to 0 
and should not be interpreted as missing. 
2.6. Health care and long-term care: ensuri ng sustainability and access to quality 
services for all 
The availability, affordability and quality of he alth and long-term care systems can strongly 
contribute to ensuring healthy, independent liv ing and improving labour market participation 
and productivity. However, there are inequaliti es in health between and within countries. 
Between EU Member States there is a 14 year gap in life expectancy at birth for men and an 8 
year gap for women. Within Memb er States differences in life  expectancy at birth between 
lowest and highest socioeconomic groups can reach 10 years for men and 6 years for women.8 
Spending on health and long-term care represen ts a significant share of GDP and is on a 
secular rise. There is a growing share of GDP  spent on healthcare in view of ageing, 
technological development, grow ing patient expectations and in creased risky behaviour (for 
example, alcohol abuse or obesity in childre n and young adults). This trend is yet more 
marked, if combined with low economic grow th, low labour market participation and high 
unemployment which limit increases in revenues.  Hence, improving the value for money of 
healthcare systems through enhancing effectiveness,  efficiency and prior ity setting have been 
deemed an urgent task. 
Member States are in very di fferent positions to face these challenges. In fact, there are 
substantial differences in heal th outcomes and health expend iture across the EU, with those 
reporting lower life expect ancy (Bulgaria, Romania, the Ba ltic states, Hungary) also reporting 
                                                 
8 Communication from the Commission: Solidarity in Health. Reducing health inequalities in the EU, 
COM(2009)567/4.  
 
EN 30   EN the lowest total health expend iture as a percentage of GDP (Figure 2.15). In many of these 
countries, out-of-pocket expenditure is a large part of total expenditure (by EU standards), 
making health care more difficult to access for those who need it most. (Figure 2.16). 
Figure 2.15: Total expenditure on healthcare  and life expectancy in the EU Member 
States 
BE
BGCZDKDE
EEELES FRIT
CY
LVLTLU
HUMTAT
PLPT
ROFISE
UK
EU 27IENL
SI
SK
70727476788082
56789 1 0 1 1 1 2
Total healthcare expenditure as a % of GDP, 2007Life expectancy, 2007
 
Source: Life expectancy - EUROSTAT 2006 for FR and IT , 2007 for the rest of th e EU MS, Total healthcare 
expenditure as a % of GDP - OECD health data 2007 and WHO health data 2006 for the non-OECD EU MS 
Figure 2.16: Out-of-pocket expend iture on healthcare and lif e expectancy in the EU 
Member States 
BE
BGCZDKDE
EEELES FRIT
CY
LVLTLU
HUMTAT
PLPT
ROFISE
UK
EU 27IENL
SI
SK
70727476788082
5 1 01 52 02 53 03 54 04 55 0
Out-of-pocket payments as a % of total healthcare expenditure, 2007Life expectancy, 2007
 
Source: Life expectancy - EUROSTAT 2006 for FR and IT, 2007 for the rest of the EU MS; Out-of-pocket 
payments as a % of total healthcare expenditure - OECD health data 2007 and WHO health data 2005 for the 
non-OECD EU MS 
 
EN 31   EN The current crisis can place an additional economic constraint in countries where the health 
and social care sector is alre ady under-resourced, social protec tion expenditure (as percentage 
of GDP) is low and the financial situation of  households is poor (Baltic States, Romania, 
Bulgaria in terms of public expenditure) or in  countries which have just recently faced a 
macroeconomic stabilisation programme and wher e the financial situat ion of households is 
reduced (Hungary). 
The impact of the economic crisis was felt st rongly in some new Member-States (Estonia, 
Latvia, Lithuania, Romania, Hungary), as well  as in older and rich er ones (United Kingdom, 
Ireland and Spain). However, the health care sectors in the new Member-States are more 
vulnerable to economic crisis than in the UK,  Ireland and Spain because the total health 
expenditure as a proportion of GDP is low (5 % in Estonia, 5.5% in Romania, 5.9% in 
Lithuania, 6.4% in Latvia as compared to 8.4% in United Kingdom, Spain, Hungary, 7.5% in 
Ireland) and the out-of-pocket payments as a proportion of the total health expenditure are 
high (38.6% in Latvia, 32.2% in Lithuania, 25.3% in Romania, 22.6% in Hungary, 20.5% in 
Estonia as compared to 11.9% in UK, 12.4% in Ireland and 21.5% in Spain).  
Therefore, the role of private funding in adjust ing for public health f unding deficits remains a 
particular concern especially in the newer Memb er-States, as several of them have increased 
the amount of out-of-pocket payments.  
2.7. Social protection over the economic cycle 
Social protection systems can play a crucial ro le as automatic stabilisers and sustain the 
productive capacity of the economy. In some  countries, however, there are significant 
weaknesses and gaps in social sa fety nets. In others with mature social protection systems to 
cushion the impact of the crisis, financial sustainability is ques tioned in the long run. 
Countries faced with major public finance defici ts are left with littl e room for manoeuvre to 
address the social consequences of the crisis. Th is is of particular concern for those who also 
have weaker levels of protec tion (e.g. Lithuania, Latvia, Romania). Mapping the at-risk-of-
poverty rate of the tota l population against total social protection expend iture as a percentage 
of GDP gives a first indication of the importan ce of social security expenditure in reducing 
social vulnerability, and also the efficiency of  social protection systems in reducing poverty. 
The graph below also illustrates the different situations faced by Member States at the onset 
of the economic crisis. 
 
EN 32   EN Figure 2.17: Total social protection expenditu re and at-risk-of-poverty rate of the total 
population in EU Member States 
BE
BGCZDK
DE
EEEL
ESFR
IT
CY
LTLUHU
MTAT
PLPT
ROFISE
UK
IENL
SI
SK
101520253035
51 0 1 5 2 0 2 5At-risk-of-poverty rate total population, 2008Social protection expenditure in % of GDP, 2007 
 
Source: ESSPROS 2007, EU-SILC 2008  
Note: The horizontal and perpendicular lines depict the EU averages of the variables 
An analysis of the evolution of social spending and public deficits against the economic cycle 
can illustrate to what extent  social spending is counter-cyc lical, both in good times and bad. 
Ideally, increases in social protection expenditu re should be seen as  part of a recovery 
package, rather than a permanent feature, thus acting as an automatic stabiliser.  
The ratio of social protection expenditure as a share of GDP declined during the periods of 
rapid growth in the second half of 1990s, afte r having increased shar ply in the early 1990s 
when growth rates were very low. In recent ye ars, a trend can be observed towards increased 
resources devoted to social protection from  general government budgets. Promoting labour 
market participation in addition to improving th e fairness, efficiency and effectiveness of 
social spending will be crucial for all countries. This will help to ensure counter-cyclicality to 
promote economic growth and to  address fiscal imbalances. 
 
EN 33   EN Figure 2.18: Expenditure on social protection bene fits since 1994 in the EU in relation to 
the fiscal situation, % of GDP 
EU-27
-4,0-3,0-2,0-1,00,01,02,03,04,05,06,07,08,09,010,011,0
1994
1995
1996
19971998
1999
2000
20012002
2003
2004
2005
2006
20072008
2009
2010%
-12,0-9,0-6,0-3,00,03,06,09,012,015,018,021,024,027,030,033,0
% of GDP
Real GDP growth (lhs) Unemployment rate (lhs) Budget balance (rhs) Social protection expenditure (rhs) 
Source: AMECO database9 
Analysis shows that Member States have taken steps to reshape social protection systems  so 
that they encourage activity and inclusion. Howeve r, it is also clear that for social protection 
systems to function well, their modernisation ne eds to be accompanied by effective strategies 
for growth and more and better jobs. 
                                                 
9 The AMECO database is based on National Accounts.  
In this extract from AMECO the sum of "Social transfers in kind" and "Social benefits other than social transfers 
in kind" in accordance w ith European System of Accounts 1995 (ESA95) has been used. Generally 
speaking the results for total expe nditure on social protection is so mewhat lower than in ESSPROS. For 
details on the main differences compared with the European System of Inte grated Social Protection 
Statistics (ESSPROS) in the way social benefits in  cash and kind are distinguished please refer to 
Manual on sources and methods for the compilation of COFOG Statistics, page 65-66, Eurostat,  
http://epp.eurostat.ec.eu ropa.eu/cache/ITY_OFFPUB/KS-RA-0 7-022/EN/KS-RA-07- 022-EN.PDF  
 
EN 34   EN ‘Growth, Jobs and Social Progress’: a co ntribution to evaluating the social 
dimension of the Lisbon Strategy 
The report on Jobs, Growth and Social Progress  was adopted by the Social Protection 
Committee (SPC) on 14 September 2009. It is a contribution to discussions on the future 
shape of the EU’s Growth and Jobs Strategy and looks at the way economic, employment and 
social policies interact. It was prepared by the SPC, which brings  together experts 
representing each Member State together  with the European Commission. The report 
investigates the extent to which past economic  and employment growth has contributed to 
greater social cohesion, as well as the extent to which the modernisati on of social protection 
systems has supported this growth. 
The report shows that Europeans can count on sound social protection systems. Not only has 
social protection greatly contributed to mitigating the worst social consequences of the 
economic and financial crisis, it has also underg one profound modernisation, in line with the 
overall Lisbon strategy. 
However, social protection is not enough to limit or prevent poverty and exclusion. Having a 
job remains the best safeguard against poverty and exclusion, thus confirming and important 
stance of the Lisbon Strategy. Yet, this report  clearly shows that the virtuous circle of 
participation in employment and living out of poverty has not always functioned in the last 
decade. Serious obstacles still face the most vul nerable groups, such as the low-skilled, lone-
parent families, or migrants. In addition, recent developments have shown that more attention 
needs to be paid to the interaction between flexible labour market s and quality of work, 
notably in relation to its impact on the ge nder dimension. As a consequence, while the 
emphasis should still be on promoting growth  and jobs, fighting ch ild poverty, engaging 
closely in active inclusion and more genera lly fighting labour market segmentation and 
encouraging job quality will have crucial importance. 
The task of modernising social protection is not  over: quite the contrary. Building on previous 
achievements, reforms should be further purs ued and fully articulated with growth and 
employment strategies. The cons olidation of pension reforms will require further efforts to 
promote longer working lives, which in turn  makes a strong case for fighting health 
inequalities and improving h ealth and safety at work. 
 
EN 35   EN 3. R ESPONDING TO THE CRISIS AND PREPARING FOR RECOVERY  
The crisis has highlighted great diversity within  the EU. Its scope, magnitude and effects vary. 
Large drops in GDP have triggered dramatic ri ses in unemployment in some countries, while 
it has been contained in others. The capacity of  EU welfare systems to address the rising 
demand for social security also varies. Some Me mber States have major gaps in their safety 
nets, and not all governments have the fina ncial room for manoeuvre to let automatic 
stabilisers operate fully.  
3.1. First evaluation of policy responses 
Members State policy responses vary in scale and emphasis. A Commiss ion estimate (Figure 
2.1) shows that spending on overall recove ry measures ranges from less than 1  % of GDP in 
Hungary, Lithuania, Bulgaria and Greece to more than 3.5  % in Spain, Finland and Germany. 
Figure 1 also illustrates the different emphases placed by Member States on the various types 
of measures: some countries predominantly i nvesting in support for households, others in 
labour market measures, and yet others devoting large shares of their spending to investment 
expenditure.  
According to the Commission’s autumn forecast,  as a result of automatic stabilisers and 
discretionary measures to reinforce social benefits , social expenditure in the EU is expected to 
increase by 3.2 percentage points of GDP between 2007 and 2010 (Figure 2). The forecast 
rise ranges from less than 1 pp in Bulgaria, Hunga ry and Slovakia to 6 pp or more in Estonia, 
Ireland, Latvia and Lithuania.  
Figure 3.1: Overview of the composition of recovery measures in EU Member States' 
recovery plans – Discretionary stimulus (aggregate over 2009-10)10 
0.00.51.01.52.02.53.03.54.04.5
ES
FI
DE
AT
SE
PL
UKCZ
SI
BE
CY
NL
DK
IE
PT
IT
MT
SK
FR
LV
EEEL
ROBG
LT
HU% of GD PMeasures aimed at households Increased spending on labour market 
Measures aimed at business Increased investment expenditure
 
Source: Commission services – European Economy Occasi onal papers N°51 July 09 "The EU's response to 
support the real economy during the ec onomic crisis: an overview of Member States' recovery measure". – Table 
2 on page 16. 
                                                 
10 The figure for Poland might be overestimated , e.g. including the impact of the announced Social 
Solidarity Fund  which was rejected later on. 
 
EN 36   EN Figure 3.2: Expected increase in social  expenditure between 2007 and 2010, pp of GDP 
0%1%2%3%4%5%6%7%8%9%
EU-27
Slovakia
Bulgaria
Hungary
Poland
Czech Republic
France
Malta
Sweden
Greece
Netherlands
Austria
Italy
Germany
Belgium
Slovenia
Cyprus
Romania
Portugal
Luxembourg
Denmark
United Kingdom
Spain
Finland
Lithuania
Latvia
Ireland
Estonia0%5%10%15%20%25%30%35%40%45%expected increase in social expenditure between 2007 and 2010 (in GDP percentage points) - left axis
2007 level of social expenditure (% of GDP) - right axis
 
Source: EC Economic Forecast Autumn 2009 (AMECO database)  
3.1.1. First evaluation of the impac t of automatic stabilisers 
The last year has illustrated the key role played in Europe by automatic stabilizers in 
cushioning the impact of the crisis. As highl ighted in the SPC repor t on "Growth, Jobs and 
Social Progress" a number of estimates fo r large European countries based on past 
experiences have shown that the capacity for stabilization of public finances in European 
countries varies. According to these macro es timates 15% to 35% of economic fluctuations 
are smoothed by automatic stabilizers, depending on Member State11. In general, most 
components of social protection expenditures in crease more quickly than GDP in periods of 
economic downturn, and more slowly than  GDP in economic recovery. But, while 
unemployment expenditures are clearly among th e most sensitive to changes in the economic 
conditions, the variability of social protection ex penditures also reflects changes in other types 
of expenditures (with signif icant variations between Member States covered). 
More recently, a working paper by the Institute of Labour (IZA)12 provides an illustration of 
the various impacts of automatic  stabilizers across EU countries13. The model estimates the 
relative contribution of taxes and benefits to  disposable income stabilization and demand 
stabilization. It points to the limited role of unemployment benefits stabilization in some EU 
Member States (see Table 1).  
                                                 
11 Sources: Creel J. and Saraceno F. Automatic Stabilisatio n, Discretionary Policy and the Stability Pact, OFCE, 
working paper n° 2008-15; Van den Noord P. (2000),The Size and Role of Au tomatic Fiscal Stabilizers in the 
1990s and Beyond., OECD Economics De partment Working Paper, n° 230.  
12 Dolls et al (2009), Automatic Stabilizers and Economic  Crisis: US vs. Europe, IZA Discussion Papers 4310, 
Institute for the Study of Labor (IZA).  
13 One should note that these estimates are based on microsim ulation models (often for different years) while the 
former are based on macroeconomic ec onomic regressions (for the same year s). Thus microsim ulation estimates 
are theoretical (and rely notably on sometimes strong a ssumptions on take up of benefits and employment 
behaviours of households), macroec onomic regression rely on actual figures reflecting past experience.  
 
EN 37   EN The results suggest that in th e event of a large unemployment shock (e .g. a 5 pp increase in 
the unemployment rate), automatic stab ilisers in the EU would absorb 48  % of the shock (only 
34 % in the US), with benefits  having an important income  stabilisation effect (19  % in the EU 
and only 7  % in the US). However, there is consid erable heterogeneity within the EU, as 
illustrated in Table 3.1. These results suggest that social transfers, in particular on the revenue 
side and also on unemployment insurance, play a key role in the stab ilisation of disposable 
incomes and household demand. According to the OECD Economic Outlook (2009), when 
seen in relation to the impact of discretionary fiscal measures implemented during the crisis, 
the scale of the operation of automatic stabiliser s is such that, for the OECD countries as a 
whole, the net fiscal stimulus they provide in 2009 is estimated to ex ceed the discretionary 
fiscal action currently planned by governments by a factor of 2½. 
Table 3.1 - income and demand stabilization in case of unemployment shock* 
FEDTax SIC Benefits Tax and benefits
SE 19.7 2.9 45.8 68.5
DK 24.3 8.3 38.2 70.7
FR 7.6 19 31.7 58.2PT 22.5 9.4 30.6 62.5AT 20 16.7 30.3 67
LU 14.7 9 29.6 53.3
BE 25.7 12.4 27.6 65.7DE 23.1 14.5 26.8 64.5
FI 22.4 5 26.7 54.1
NL 10.3 13.1 23.9 47.2EURO 16.6 12.9 21 50.4
EU 17.2 12.1 18.9 48.2
UK 19.4 6.1 18.6 44.1IE 20.7 3.6 18.2 42.5
EL 12.6 13.7 11.9 38.3
ES 12.7 6.4 9.1 28.3IT 18.3 10.1 7.6 35.9US 21.5 5.1 7.1 33.7
SI 17.5 21.6 5.4 42.5
HU 22.7 19 4.7 46.4PL 15.1 17 -2.7 29.5
EE 17.8 2.2 -3.2 16.8income stabilization (% of shock absorption)
 
* Unemployment shock refers to an increase in the unemployment rate by five percentage points. 
** FEDTax: taxes, SIC: Social Insurance Contributions. 
Source: Dolls et al (2009), Automatic  Stabilizers and Economic Crisis: US vs. Europe, IZA Discussion Papers 
4310, Institute for the Study of Labor (IZA) based on the micro-simulation model EUROMOD 
3.2. Overview of main policy measures  taken in response to the crisis 
Most Member States continue to strengthen their policy responses  to the economic 
slowdown, in line with national reform programmes and th e National Strategy Reports. As 
labour market conditions have continued to wo rsen in the second and third quarters of 2009, 
many Member States have strengthened and consolidated the set of labour market measures  
they had adopted at an early stage. These measures aim to preserve employment, support 
activation and promote re-integration in the labour market, while anticipating and managing 
the adverse impact of restructuring. Ne w or reinforced measures focus on flexible working 
 
EN 38   EN time arrangements , which are seen as effective means to maintain people in employment in 
response to short term shocks, as well as a wa y to further enhance active labour markets and 
ease labour taxation. 
Member States have also further enhanced their measures to support people's income . Two 
countries have adopted comprehensive packages to reinforce their safety nets. New measures 
have especially been taken to strengthen unemployment benefits  while paying attention to 
avoiding disincentives to get back to wor k. Member States have also reinforced minimum 
income schemes  especially in countries where they  appeared weak under the increased 
pressure created by the crisis. 
Member States also report on the specific s upport provided to groups at risk, notably youth , 
families with children  and the disabled. Some Member St ates also report on measures to 
ensure equal opportunities between women  and men. 
A few Member States have taken further measures to avoid and stem the direct consequences 
of the financial crisis for individuals and families. These include measures to protect 
mortgage holders  against repossession (e.g. renegotiati on of mortgages for the unemployed), 
to address over-indebtedness, or to create incentives for banks to give access to credit  to 
individuals, including people on low income.  
The current economic and financial cris is may have a severe impact on the healthcare sector  
in several EU Member States, on both the supp ly and demand sides. On the supply side, the 
economic and financial crisis may lead to re duced funding for health and long-term care 
services as a result of  budget cuts and lower tax revenues,  while the demand for health and 
long-term care services may increase as a resu lt of a combination of factors contributing to 
worsening health among  the general population. 
The health impact of the rapid deterioration in pub lic finances is likely to be fully felt only at 
the end of this year, when budgets for 2010 will be  discussed. In view of  the levels of public 
debt, it is more than likely that the fiscal  ‘room to manoeuvre’ will further reduce. The 
deterioration in public finances  and consequent shrinking of fiscal resources could force 
governments to adopt drastic adjustment and austerity measures. 
For countries whose health system is finan ced through general tax revenues, decreases in 
GDP and economic outputs may result in signifi cant reductions in public revenue for health. 
Alternatively, for countries that  rely predominantly on wage-rela ted contributions to health 
insurance funds, increases in unemployment ar e likely to constrain revenues earmarked for 
health. 
Several Member States have included measures w ithin their recovery packages to mitigate the 
impact of the economic crisis on he alth care, in the following areas i) investing in health 
infrastructure, ii) providing addition al funding to the healthcare sector, iii) 
restructuring and reorganising the healthcare system . 
Some Member States have allocated funding to the construction of new healthcare centres or 
the upgrading of the existing health infrastruc ture as a means to boost employment in the 
construction sector, although these measures were not initially considered  as a part of an 
economic recovery plan. 
 
EN 39   EN Furthermore, many Member States have adop ted measures to reduce the impact of the 
economic crisis on health care by securing sufficient funds for the healthcare sector during the crisis, improving the utilisation of existing reso urces within the healthcare sector and ensuring 
the protection of patients’ rights and entitlements.  
The measures taken by some Member States in order to restructure and reorganise the 
healthcare sector are aimed at using resources in the most pr oductive and efficient way, re-
defining priorities (so as to reallocate funds a nd distribute any surpluses to other fields that 
appear to have higher deficits), and reorien ting and reorganising healthcare services, in an 
attempt to respond effectively to  the increased demand for health care services in the context 
of the economic crisis. 
However, a few Member States have not introd uced specific health-related measures to cope 
with the economic crisis, either because their health systems have not  yet been directly 
affected by the crisis or because health care is not regarded as a key element in re-launching 
economic growth.  
Regarding the longer-term impact of the crisis on pension schemes , and social security 
schemes in general, many countries observe that the effects of the cris is are still hard to 
predict. At present, the bulk of pensions in payment are de livered by public PAYG schemes 
on which the crisis in financia l markets has no direct effect. By contrast, the book values of 
the assets held by pension funds have fallen sign ificantly and real issu es of solvency could 
emerge if markets take long to recover. But, apart from in a few Member States, this would 
primarily affect the incomes of future pensione rs in the medium to long term. Most Member 
States therefore regard their pension systems as quite resilient. However, if the crisis deepens 
and continues for several years, even PAYG sy stems will be affected as unemployment and 
lower growth reduce revenues from taxes a nd social contributions  and weaken public 
finances.  
In their replies to the October 2009 questionnaire, most countries indicate that it is still too 
early to fully evaluate the social impact of the measures they have  taken in response to 
the crisis . However, some countries report on stock-taking exercises performed by 
government to evaluate the take-up of specific measures (e.g. number of benefit recipients, 
number of workers having partic ipated in activation measures) or the impact of measures to 
preserve or create jobs. A fe w countries have commissioned i ndependent ex-post or ex-ante 
evaluations of their ove rall recovery packages. 
The preparation of their 2010 budge ts is the occasion for Memb er States to review the 
measures originally taken in th e light of constraints on public  finances. This review should 
also highlight the need to bala nce the burden of the policy responses across different levels of 
government.  
One year into the crisis, more  Member States report a stronge r emphasis on provisions to 
ensure budgetary discipline . This is because of very high  constraints on public finances, 
and/or the need to preserve th e long-term sustainability of public finances in general and 
social protection in particular. In addition to the two countries  who had already reported on 
this aspect in spring 2009, a number of othe rs are planning or have recently adopted 
‘austerity’ packages  of different sorts. These packages include reforms of the public sector 
(e.g. redundancies and reduced wages for state employees), tax increases (especially VAT), 
etc. 
 
EN 40   EN As welfare systems continue to play their ro le of automatic stabilisers, social protection 
expenditure is projected to rise. However, th eir capacity to address the rising demand for 
social security varies greatly across Member  states, and not all Member States have the 
financial room for manoeuvre to let automatic stabilisers operate fully. The review of public 
finances and the preparation of the 2010 budgets ha ve led some Member States to adopt fiscal 
consolidation packages that may weaken the eff ects of previous recove ry measures aimed at 
preserving employment and/or sustaining demand. In the long r un, however, their aim is to 
ensure sound public finances and thereby suppor t macroeconomic stability  and future growth. 
3.3. The need for effective and efficient soci al inclusion policies during and after the 
crisis 
While the economy is expected to return to a 0.7% growth in 2010, labou r demand is likely to 
remain weak for a while and past experience s uggests that the social consequences of the 
downturn will persist.  Unemployment in the EU reached 9.5% in November 09, and could 
reach 10.3% in 2010. The rate is more than double for young workers  (21.4%) and migrants  
(18.18.9%).  
The loss of family income caused by unemploym ent deeply affects all those who depend on 
it. Clearly this includes children and other dependants . Cuts in the provision of social 
services may also affect families with children. Young people  still in education or seeking to 
enter the labour market may also affected bot h by the drop in their parents income, on which 
they often depend and by the lack of job opport unities. The maturing of pensions systems in 
recent decades has helped re ducing poverty risks for the elderly  in many parts of the EU. 
However, the crisis threatens the development of adequate pensions where elderly poverty 
remains very high and has highlighted ri sks in privately managed schemes.  
The crisis is also likely to affect those furthest from the labour market , whether inactive or 
long-term unemployed. Even before the crisis, the low-skilled, people with disabilities or 
mental health problems, and migrants — partic ularly women — had limited access to training 
and other enabling services. Recent efforts to boost employability for all may be undermined 
by the lack of jobs and increased pressure on  training and employment  services. Maintaining 
decent living standards for all is not only crucial to ensure that people can live in dignity, but 
is also necessary to sustain th eir employability and learning cap acity. Overall, the crisis has 
shown that most Europeans can rely on some of the most effective safety nets  in the world. 
However, there are gaps across countries and population groups. 
The effectiveness of unemployment benefits  varies greatly across and within countries 
depending on their coverage, duration, condition ality and replacement rates. Some workers 
are better covered than others. Young workers w ith short contributory records and some of the 
self-employed may not be entitled to unemplo yment benefits, while workers on part-time or 
temporary contracts often benefit from a lowe r level of protection th an other workers.  
Reforms to strengthen incentives to work have tightened eligibility criteria, or reduced the 
level or duration of benefit en titlements. Together with a greater emphasis on activation 
measures, these reforms have contributed to an  overall reduction in long-term unemployment. 
However, they have not always managed to reduce long-term welfare dependency . Even 
though several Member  States have prolonged benefit durati ons and relaxed eligibility rules 
 
EN 41   EN in response to the crisis, the pressure on last-resort schemes  is likely to increase, as 
unemployment benefits run out for more and more people. 
The report ‘Growth, Jobs and Soci al Progress’ warns that past crises have shown that long-
term unemployment or inactivity tend to persist long after recovery has set in. This partly 
reflects increasing numbers of people moving into  long-term sickness and disability benefits 
or early retirement schemes. Long-term unemplo yment and periods of inactivity also affect 
people’s employability through skill depreciation, discouragement, and in some cases a lack 
of integration in so ciety as a whole.  
3.4. Supporting the integration of the most excluded in the labour market and in 
society as whole: the role of ac tivation and access to services 
Adequate income support is crucial for people's ability to live in dignity (see section 3.5), but 
it should also be complement ed with policies aimed at he lping them back on the labour 
market and participate fully in society. Activ e labour market policies and ambitious life long 
learning strategies have an impor tant role to play in fighting poverty and social exclusion.  
The SPC report on "Growth, Jobs and Social Progress" reviews re cent trends in  a number of 
policy fields that promoted in the context of the Lisbon Strategy to  support greater labour 
market participation among the inactive and th e unemployed and help low wage workers to 
get better jobs. It shows that both spending and participat ion in active labour market 
measures, including training, have improved overall in the last year s. However, more needs to 
be done to ensure that such policies reach all categories of workers , including the low 
skilled, the young and the elderly, migrants and the disabled. 
Participation in life-long learning  has improved overall in the EU-27 from 7.1  % of people 
aged 25-64 in 2000 to 9.6  % in 2008. However, great disparities remain across countries, with 
participation rates among the 25-64 age group varying from 3  % or less in RO, BG, HU and 
EL to more than 30  % in DK and SE. The participatio n rates of the unemployed have 
increased but were still only around 8.5  % in 2008. After an incr ease in early 2000, the 
participation rates of the inac tive stagnated and stood at 6.9  % in 2008. The main issue of 
concern is the very low rates and slow progress in the participation of low-skilled 
workers , which stood at 3.8  % in 2008 (as against 2.8  % in 2000). Furthermore, the 
percentage of early school -leavers was still high at 15.2  % in the EU in 2007, as against 
17.2  % in 2000. Moreover, the overall progress hide s the poor performance of a number of 
countries like BE, DK, DE, EE, ES, FR, AT and SK, where no or very little progress was 
made. 
Labour market policy (LMP) expenditure  decreased from 0.51  % of GDP to 0.47  % 
between 2005 and 2007, partly reflecting declining unemployment rates. LMP expenditure 
per person wanting to work also stagnated duri ng that period. There was also a slight shift 
from spending on passive measures  to spending on active measures14. Spending on active 
measures per person wanting to work in creased from 1472 PPS in 2005 to 1739 PPS in 2007, 
while spending on ‘passive’ measures per person wanting to work declined from 3931 PPS to 
                                                 
14 ‘Passive measures’ include income support (8) an d early retirement schemes (9); ‘active measures’ 
include training (2), job rotation and job sharing (3), employment incentives (4), supported employment 
and rehabilitation (5), direct job creation (6), and start-up incentives (7). 
 
EN 42   EN 3770 PPS in 2007. The decline was mainly driven  by the decline in income replacement 
spending, while spending on early retirement (8  % of total passive sp ending) remained the 
same. Further analysis would be needed to iden tify the factors behind th e relative decrease in 
income maintenance spending (changes in the desi gn of benefits, reduced benefits, etc). (See 
point 3.6) 
The lack of enabling services has also been identified as an obstacle to participation in the 
labour market, especially for women with care responsibilities.  It is also a compounding 
factor in child poverty.  Member States’ efforts to increase child care provision  have helped 
to increase the number of children in formal care arrangements from 25  % in 2005 to 30  % in 
2007 for children below the age of 2. Very larg e differences persist between Member States, 
with rates ranging from 2  % in CZ, PL and SK to more than 40  % in BE, DK, NL and SE. In 
many countries the provision of child care is mainly on a part- time basis, which can hamper 
labour market participation for lone parents in particular. Furthermore, in the same period the 
share of persons with care responsibilities declar ing that they are inac tive or working part-
time due to the lack of care  services increased from 26.7  % in 2006 to 29.8  % in 2008.  
More generally, adequate and individualised social and employment services play a key 
role in addressing the structural ba rriers to participati on in the labour market and in society as 
a whole. Labour market policies alone are not su fficient to support the integration of the most 
vulnerable in society and into th e labour market: the personal, fa mily and social hurdles they 
face should also be addressed by quality social and health services. 
3.5. Income support: the specific ro le of minimum income schemes 
3.5.1. Minimum income schemes in th e context of Active Inclusion 
The Active Inclusion Strategy15 provides an integrated fr amework within which the 
multidimensional nature of poverty and social ex clusion can appropriately be tackled, and as 
such it is fully supported by the Member States. Adequate income support is a key pillar of 
the strategy . Its aim is to ensure a dignified life to t hose – either fit or unfit to work – that are 
not endowed with sufficient resources to live in a manner compatible with human dignity, 
consistently with the 1 992 Council Recommendation16 that called on Member States to 
recognise such a basic right.  
In the context of the adequate in come support strand of the strategy, the focus here is on 
minimum income (MI) schemes for working-age people  across EU Member States.17 
                                                 
15 The European Commission adopted on 3 October 2008 a Recommendation on the active inclusion of 
people excluded from the labour market providing common principles and prac tical guidelines for the 
Active Inclusion Strategy – a comprehensive integrated strategy linking together adequate income 
support, inclusive labour markets and access to quality services. It was endorsed by the Council on 17 
December 2008, and by the European Parlia ment in its Resolution of 6 May 2009. 
16 Council Recommendation 92/441/EEC. 
17 The analysis presented in Sections 3.4.1 and 3.4.2 relies heavily on the work conducted by the EU 
Network of national independent experts on social inclusion, and particularly on the Synthesis Report 
drawn from their work (Frazer H. and E. Mar lier (2009) "Minimum income schemes across EU 
Member States. Synthesis Report"). The Synthesis Report covers 26 out of the 27 Member States as a final report for LU was not available when the report was finalised. However, LU is included in the 
Tables in the Synthesis Report’s Annex on “Main characteristics of MI schemes and their relationship 
with national social protection systems”. The national experts' reports and their overview are available 
 
EN 43   EN 18These are schemes that provide cash benefits aimed at ensuring a minimum standard of 
living to individuals and their dependants having  no, or insufficient, other means of financial 
support (including contributory cash benefits and support from other family members). As 
stated by Figari, Haux, Matsag anis and Sutherland (2009),19 the level of income provided to a 
person through a MI scheme is the minimum leve l of income deemed acceptable for that type 
of person by the social protection system in the country concerned.  
MI schemes are to be considered as "schemes of last resort". They provide a safety net, aimed 
at preventing destitution to people that are not eligible for social insu rance benefits or whose 
entitlement to such benefits has expired. In this sense, they play an even more important 
role in a context of crisis , and the more so, the more long-lasting the economic downturn. 
Indeed, many of the national independent e xperts part of the EU Network on social 
inclusion20 note that the rise in unemployment br ought about by the financial and economic 
crisis has already had an impact on social assistance (SA) schemes.21  
Almost all EU countries have some form of MI scheme  at the national level , while those 
Member States that do not have one, like Italy, have some sort of schemes at the regional or 
local level. The schemes are generally conceive d as a short-term form of assistance (though 
formally not time-limited in most Member Stat es). They are means-tested and funded through 
the tax system (i.e. non-contri butory). They mainly target pe ople out of work but some 
Member States have extende d their scope to provide in -work income support. The 
institutional features of MI sc hemes across EU countries are cons idered in the next Section. 
The following two Sections focus respectively on  non-take up and benefit adequacy and work 
incentives. 
3.5.2. Institutional features  of minimum income schemes in EU countries 
Substantial differences exist across Member St ates in the way MI schemes are designed. In 
terms of comprehensiveness of the schemes (i .e. the extent to whic h MI schemes are non-
categorical, thus generally a pplying to the low-income popula tion and not only to specific 
                                                                                                                                                         
from: http://www.peer-review-social-inclusion.eu/ne twork-of-independent-experts/2009/minimum-
income-schemes . 
18 The work on MI presented in this document is mean t to be as the first step in the direction of more 
detailed analytical work on Active Inclusion. As such, it only touches upon a specific issue mainly 
linked to adequate income support, but also partly to inclusive labour markets. The third pillar of active 
inclusion (access to quality services) is of course as  important as the other two but is left to future 
investigation. 
19 Figari F., T. Haux, M. Matsaganis and H. Suther land (2009) "The effects of Minimum Income schemes 
on the working-age population in the European Union",SSO Research Note 5(2009). 
20 The EU Network of National Independent Experts on Social Inclusion assists the European 
Commission in monitoring and evaluating the situation with regard to poverty and social exclusion and 
the policies that are relevant in this respect in th e Member States and candidate Member States. Twice a 
year, the experts produce a report on their respectiv e countries concerning a specific subject that is 
being examined in the context of the EU social in clusion process. Once a year, the experts produce an 
independent (non-governmental) assessment of an official policy document (social inclusion strand of the National Strategy Report on Social Protection and Social Inclusion or an of ficial reply to an SPC 
questionnaire on a specific topic). The Network Core Team produces synthesis reports, bringing 
together the main results of the analysis across c ountries. For more information on the network and its 
work, see: http://www.peer-review-social-inclusion .eu/network-of-independent-experts
. 
21 SA schemes represent the broader category including MI benefits together with other types of benefits 
like housing benefits, child benefits and unemployment assistance benefits. In what follows we will 
make it explicit whether considerations and findings apply to SA schemes more generally rather than 
specifically to MI schemes (to which we refer whenever not differently specified). 
 
EN 44   EN subgroups), the work of the EU Network expert s pinpoints to the existe nce of four "broad" 
groups of countries with different institutional features. A first group of Member States (AT, 
BE, CY, CZ, DE, DK, FI, NL, PT, RO, SI, SE) is characterised by relatively simple and 
comprehensive MI schemes , generally open to those lacking sufficient resources to live in 
dignity. A smaller group of countri es (EE, HU, LT, LV, PL, SK) has simple and non-
categorical MI schemes accompanied by  more restricted eligibility conditions . A third 
group (ES, FR22, IE, MT, UK) is characterised by a complex set of different and often 
categorical schemes  that sometimes overlap one with th e other but generally cover most of 
those with insufficient resources. Finally, there is a small group of countries having limited, 
partial or piecemeal arrangements  only covering narrow categories of people. 
In general, eligibility conditions (commonly rela ted to age, nationality , residence, lack of 
financial resources and availability for work) vary significantly. Consistently, large cross-
country variation in coverage23 of MI schemes is observed  – as evident also from Figure 
3.3 reporting EUROMOD24 simulations on the poor working-age individuals (not in full-time 
education) living in assessment units entitled and not entitled to MI.25 26 In some Member 
States there are people on very low income s that still have no access to MI schemes.  
Some groups, like the homeless, refugees and asyl um seekers, are often left uncovered even in 
the countries with the more comprehensive schemes.  
                                                 
22 This has improved with the introduction of the RSA in 2009 
23 People are considered as "covered" by one or mo re MI schemes if they meet all the eligibility 
conditions and are therefore entitled to receive benefits. 
24 EUROMOD is a tax-benefit micro-simulation model currently covering 19 EU countries (EU-15 plus 
EE, HU, PL and SL). Cash benefits, direct taxes and social contributions are calculated by the model on 
the basis of tax-benefit policy rules in place in th e different countries. Mark et incomes, as well as 
instruments that are not simulated, are taken from the data. Results derived from the model are therefore based on simulated, rather than recorded, disposab le income. Baseline results from EUROMOD rely on 
the assumption of full take up (i.e. all eligible indi viduals or households receive the benefits they are 
entitled to) (see Paulus A., F. Figari and H. Suther land (2008) "The effects of taxes and benefits on 
income distribution in the EU" Chapter 7 in SSO Monitoring Report 2008). The assumption of full take 
up allows focusing the analysis here on the issue of non-entitlement among poor households.  
25 EUROMOD simulations presented here are run with the version of the model currently available, which 
uses 2001, 2003 and 2005 tax-benefit policy rules depending on the country. This of course means that 
changes in national tax-benefit policy rules intervened  after the reference year are not reflected in the 
results. It will be possible in the future to repeat th e analysis with updated policy rules. The new version 
of the model using 2008 policy rules for 9 EU countr ies will be available as from February 2010. By 
February 2012 EUROMOD will be upgraded to use 2010 policy rules for all 27 Member States (project 
financed under a three-year Framework Partnershi p Agreement between DG EMPL and the University 
of Essex). 
26 When interpreting EUROMOD results, one should also keep in mind that asset tests affecting eligibility 
to some MI schemes are not considered (except in  cases where information on assets is relatively 
reliable and asset tests are critical, like for th e UK). Among the other conditions of entitlement, 
information on availability for work and citizenship is not always available (Figari et al., 2009). 
 
EN 45   EN Figure 3.3 – Working-age (16-64 ) individuals below the poverty line (at 60% of the 
median) by minimum income entitlem ent status (policy years 2001, 2003, 2005)  
0%2%4%6%8%10%12%14%16%18%
BE DK DE EE EL ES FR IT LU HU NL A T PL PT SI FI SE UK% of working age people
Poor and not on MI Poor and on MI 
Note: MI schemes are defined here as to include the benefits listed as “Minimum resources: general non-
contributory minimum” in the Mutual Information System on Social Protection (MISSOC) database.27 28 Tax-
benefit policy rules refer to 2001 for DK, FR, SE; to 200 3 for BE, DE, IT, LU, NL, AT, PT, FI, UK; to 2005 for 
EE, EL, ES, HU, PL, SI.29 Figures for FR do not take into account the (time-limited) earnings disregards linked 
to the MI scheme (RMI). MI schemes cannot be simulate d for IT and ES, where the schemes are administered at 
the regional level and variation across regions is too larg e. For these two countries MI receipt information from 
national surveys is therefore used. The sample size of poor working-age individuals living in assessment units 
entitled to MI benefits is small in DK, ES and AT. Resu lts for these three countries should be treated with 
caution.  
Source: Figari, Haux, Matsaganis and Sutherland (2009) 
In terms of trends, many Member St ates display a clear move towards tightened eligibility 
conditions . Conditionality has been generally increased and availability for work  has 
commonly become a more stringent  requirement for people who are fit to work. Sanctions are 
often associated with the failure to comply w ith the requirement of availability for work, and 
might lead to reductions in benefit amounts and to the loss of the right to  SA benefits in more 
                                                 
27 The specific MI schemes considered are “droit à l’integration sociale” for BE; “kontanthjælp and 
starthjælp” for DK; “Sozialhilfe” for DE; “toimetule kutoetus” for EE; “renta minima de inserción” 
(regional scheme) for ES; “revenu minimum d’insertion” for FR; “minimo vitale/reddito minimo” 
(regional scheme) for IT; “revenu minimum garanti” for LU; “algemene bijstand” for the NL; “Sozialhilfe” for AT; “poloc spoleczna” for PL; “ren dimento social de insercao” for PT; “denarna 
socialna pomo č” for SI; “toimeentulotuki” for FI; “ekonomiskt bistand” for SE; “income support” for 
the UK; no general  MI scheme for EL and HU (EUROMOD ca nnot represent the discretion left to the 
local level in some systems). 
28 For each country the main charact eristics of the MI scheme, as fro m MISSOC, are summarised in Table 
A2, Appendix 1, in Figari et al. (2009). 
29 Though modelled in the current ve rsion of EUROMOD, IE is excluded  from this analysis. The decision 
is linked to the assumption of full take-up used in EUROMOD, which applies also to those other benefits to which MI operates as a top-up. This generates an over-estimation of such other benefits 
leading to an under-estimation of MI entitlement. This applies particularly to IE that has therefore been 
excluded from the analysis  (Figari et al., 2009). 
 
EN 46   EN extreme cases. There is also a trend towards a stronger link between income support through 
MI schemes and activation measures .  
While the focus of the analysis here is on MI sc hemes, it is anyway important to highlight that 
in many Member States MI benefit recipients receive additional assistance for specific 
needs , like housing benefits, contributions for fuel costs and child benefits  (this can be seen, 
for instance, from Figure 3.4 on the composition of disposable income for households with 
working-age individuals in the poorest decile  of the population obtained using EUROMOD). 
Though not formally classified as "guaranteed MI benefits", these additio nal benefits in fact 
contribute to the level of income that is actually guaranteed to people supported by MI 
schemes.  
Figure 3.4 – Components of disposable in come of households with working-age 
individuals in the poorest 10% of the population (policy years 2001, 2003, 2005)  
 
Note: Tax-benefit policy rules refer to 2001 for DK, FR, SE; to 2003 for BE, DE, IT, LU, NL, AT, PT, FI, UK; 
to 2005 for EE, EL, ES, HU, PL, SI. Source: Fi gari, Haux, Matsaganis and Sutherland (2009) 
In most Member States MI schemes are design ed as schemes applying  to the country as a 
whole, while delivery is delegated to the local authorities. But there ar e a few Member States, 
like Austria and Hungary, where responsibility for policy decisions on SA benefit levels and eligibility conditions is partly delegated to regional/local governments. At the local level the 
EU Network experts note that the introduction of "one-stop-shop"  type of arrangements in a 
number of Member States has represented an  important innovation to ensure effective 
coordination in the delivery of various schemes.  
3.5.3. The non-take up of benefits: estimated  extent, causes and policy-relevant 
consequences 
While coverage of MI schemes is defined on the basis of eligibility criteria, the take up of 
benefits refers to the share of people entitled to  benefits (i.e. covered by the schemes) that Source: EUROMOD-60-40-20020406080100120140160180200
BE DK DE EE EL ES FR IT LU HU NL A T PL PT SI FI SE UK% of disposable incom eMarket inc ome Personal taxes
Social insurance contributions Other benefits
Unemployment benefits Family benefits
Old age benefits M I  schem es
 
EN 47   EN actually are  in receipt of benefits. Coverage and take-up rates do not necessarily 
coincide ,30 and indeed the limited and fragmented available evidence shows a large to very 
large gap between the two. Contributions in the literature highlight th at people entitled to 
benefits might actually not r eceive them due to the following reasons (Hernanz, Malherbet 
and Pellizzari, 2004):31 
(1) relatively high " information costs " for potential claimants (i.e. efforts required to 
obtain and understand information) with rega rd to benefit regulations (including the 
existence of the benefit itself and the eligibility criteria) and the related application procedures, with "information costs" being higher, the more complex the design of the 
scheme and the procedures; 
(2) "administrative costs " related to the duration of th e administrative process and to 
uncertainties with regard to the outcome of the application, which may discourage potential claimants from applying; 
(3) pecuniary determinants  affecting the (rational) cost-b enefit calculation to claim for 
benefits, related to benefit le vels being too low and/or the expected duration of benefit 
receipt to be too short to offset the costs of claiming in terms of time and efforts (this 
might explain non-take up in situ ations of less extreme need); 
(4) social and psychological costs  related to the perception of  SA support and the fear of 
stigmatisation refraining people from claiming; 
(5) errors in evaluation procedures and discretionary assessment  of applications (not 
based on objective clearly established criteria) leading to the rejection of applications by eligible people (these f actors might be exacerbated by the insufficient number of 
social workers processing the applications). 
Evidence on take up is currently very fragment ed, limited in terms of country coverage and 
referred to different (mostly not recent) year s and different benefit schemes for different 
countries. In the EU, the UK is th e only country where official es timates of take-up rates have 
been published (by the Department for Work and Pensions) for various benefits, including 
Income Support, since 1997 (the last estimates being referred to 2007-08). The message to be 
drawn from the available (though not recent) evidence is anyway clear: non-take up is 
indeed substantial and requires research efforts  on the side of the academic community 
and attention on the side of policy-makers , though over the last years measures to tackle 
this key issue have been put in place at  national level, as explained below. 
The traditionally quot ed OECD paper by Hernanz et al. (2004) reports es timates of take up for 
SA and housing benefits ranging between 40%  and 80%. A recently completed EUROMOD 
                                                
 
30 In an "'ideal world" where all people entitled to benefits actually receive them, coverage and take-up 
rates would of course be identical. In the real world "frictions" of different nature (see the rest of the 
Section) characterising both the stage of delivery of  the schemes and the stage of claiming for benefits 
generate incomplete take-up so that take-up rates end up being smaller, or much smaller, than coverage 
rates. 
31 Hernanz V., F. Malherbet and M. Pellizzari (2004) "Take-up of welfar e benefits in OECD countries: a 
review of the evidence" OECD Social, Employment and Migration Working Papers 
DELSA/ELSA/WD/SEM(2004)2. 
 
EN 48   EN project (AIM-AP)32 has provided additional evidence on take up for some EU countries and 
different types of social benefits. With regard to countries for which SA  more generally or MI 
schemes more specifically were analysed, the project led to the following take-up estimates (Matsaganis, Paulus and Sutherland, 2008):
33  
– Austria: 44% by caseload (i.e. numbers of individuals/households claiming benefits) and 
52% by expenditure (i.e. amount of benefit cl aimed) for SA ("Hilf e zur Sicherung des 
Lebensunterhalts") in 2003 (Fuchs, 2007);34 
– Finland: between 50% and 60% for SA ("To imeentulotuki") by working-age families 
between 1996 and 2003 (with a declining rate over the period) (B argain et al., 2007);35 
– Germany: 33% by caseload and 43% by expend iture for SA in 2002 (Frick et al., 2007);36 
– Netherlands: between 72% and 81% for SA (ABW) (Vrooman et al., 1994);37  
– Portugal: between 70% and 75% for the So cial Integration Income (RSI) in 2009 
(Rodrigues, 2009);38 
– UK: between 78% and 88% by caseload and be tween 85% and 93% by expenditure for 
Income Support in 2007-08 with a decrease in  caseload take up by about 1% since 2006-07 
and by at least 4% since 1997-98, though the latter piece of evidence is not certain due to high and increasing modelling bias (DWP, 2009). 
The available evidence th erefore suggests that take up of SA benefits is far from complete 
and even significantly low in many EU countries . Moreover, compared to the past take up 
seems to have declined, at least in some EU countries for which data are available. The risk 
of non-take up might also be greater for some groups than for others , as highlighted by 
the EU Network experts (Frazer and Marlier, 2009). For instance, in Be lgium non-take up is 
estimated to be greater for wo men, couples, individuals with e ducational attainment below the 
second stage of secondary studies and the 16-24 ag e cohort. In the UK, people that do not take 
up Income Support tend to be slig htly older than those that take  it up (with a larger share of 
people aged 50-59) and more likely to be owne r-occupiers in terms of tenure type, to have 
                                                
 
32 The Accurate Income Measurement for the Assessment of Public Policies was a programme (started in 
2006 and finished in 2009) funded by the European Commission under the Sixth Framework Programme. The programme aimed at improving the comparability, scope and applicability of tools, 
methods and data for the measurement of income and the analysis of the effects of policies on 
inequality, poverty and social inclusion. It involved 11 universities and research institutes in various EU countries (http://www.iser.essex.ac.uk/research /euromod/research-and-policy-analysis-using-
euromod/aim-ap).  
33 Matsaganis M., A. Paulus and H. Sutherland (2008) "The take up of social benefits" SSO Research 
Note 6(2008). 
34 Fuchs M. (2007) "Social assistance – No, thanks? Empi rical analysis of non-take up in Austria 2003" 
EUROMOD Working Paper No. EM4/07.  
35 Bargain O., H. Immervoll and H.Viitamäki (2007) "H ow tight are safety nets in Nordic countries? 
Evidence from Finnish register data" IZA Discussion Paper 3004. 
36 Frick J.R. and O. Groh-Samberg (2007) "Estimating the size and determinants of benefit non-take up in 
Germany" Deutsches Institut für Wirtschaftsforschung, Berlin. 
37 Vrooman J.C. and K.T.M. Asselberghs (1994) "De gemiste bescherming, niet-gebruik van sociale 
zekerheid door bestaansonzekere huishoudens" CO SZ/Sociaal en Cultureel Planbureau, Rijswijk. 
38 Rodrigues C.F. (2009) "Impacto do RSI na distribução do rendimento e exclusão" European Seminar 
"Social Integration Income – RSI a right to social integration", Lisbon March 2009. 
 
EN 49   EN other incomes, to share their household with other benefit units and to live in a household 
below 60% of median income before housing costs39 (DWP, 2009). Some of the EU Network 
experts, the Austrian for inst ance, underline the fact that non-take up can vary significantly 
by region within a country  (Frazer and Marlier, 2009).  
There are several reasons why it is important for policy-makers to better understand the extent 
and causes of non-take up a nd to identify appropriate policy responses. Firstly, low take up 
distorts the intended effects of social benefits  (Matsaganis et al., 2008) . If only a fraction of 
those that are supposed to benefit from a welf are programme are reached , this clearly reduces 
the chance for the programme to achieve its obj ectives (Hernanz et al., 2004). Secondly, when 
not claiming a benefit is (at leas t partly) involuntary, due, for inst ance, to lack of information, 
non-take up generates disparities of treatment between individuals (those that are 
informed and those that are not) that were supposed to be treated equally by the welfare 
programme  (Hernanz et al., 2004). Mo reover, if information on benefit programmes is not 
"randomly distributed" but rather more availa ble to certain groups within the eligible 
population, the disparities  of treatment implied by non-take  up end up being particularly 
harmful to those people that are relati vely more in need for assistance.  
The policy-relevant consequences of non-take up clearly emerge also in Matsaganis et al. 
(2008), where EUROMOD is used to study the eff ects of non-take up of SA schemes in some 
EU countries.40 Simulation results pinpoint to th e following effects (see Table 3.2):41 
(1) non-take up lowers the capaci ty of SA benefits to reduce the aggregate poverty gap.42 
Incomplete take up reduces poverty gap effi ciency by over a half in PL, by around one 
third in SE and PT, and by a tenth in the UK. 
(2) non-take up has a significant negative e ffect on SA effectiv eness at reducing the 
at-risk-of-poverty rate . Simulation results show that incomplete take up leads to an 
increase in the poverty rate by 0.5 points  in the UK, by 0.7 points in SE and by 2.8 
points in PL. Moreover, the negative eff ects on poverty rates are stronger, the lower 
the poverty line considered, thus the more we move towards the bottom of the income 
distribution (see estimates for the 60%, 50% and 40% thresholds in Table 3.2). 
(3) non-take up increases the poverty gap  (expressed as the average gap between poor 
households’ incomes and the poverty line as a proportion of disposable income) by 9-16% in PT and the UK, by 34% in SE and by 64% in PL.  
Again these findings show that non-take up is to  be considered a matter of concern and its 
monitoring is particularly relevant. As anticipated, the relevance of the issue has been recognised by the Member  States that have  generally put in place  measures to increase take 
up. These have mainly consisted of simplification of procedures  to apply for benefits, as 
well as measures to better inform potential beneficiaries  about their en titlement and 
                                                
 
39 The difference becomes neg ligible after including housing costs (DWP, 2009).  
40 The schemes considered in the four countries for which results are reported here below are: Pomoc 
Społeczna in PL, Rendimento Mínimo Garantido/Rendim ento Social de Inserção in PT, Ekonomiskt 
Bistånd/Socialbidrag in SE, an d Income Support in the UK. 
41 The policy year considered is 2001 for all countries but Poland, for which 2005 is used. 
42 The aggregate poverty gap is given by the sum, over the whole sample of poor households, of the 
differences between the poverty threshold (at 60% of median equivalised household disposable income) 
and the pre-transfer household disposable income. 
 
EN 50   EN application procedures. For instance, the EU Network expert for Ir eland highlights that 
strategies to increase take up have focussed especially on information campaigns through a 
variety of media and formats. For the Nether lands, the experts note that “municipalities 
promote the use of existing income facilities. This is for instance done by writing directly to 
people entitled to these facili ties, by publishing articles in local newspapers and by giving 
information at locations such as playgrounds and schools. Furthermore, the procedures to 
apply for support will be simplified and by mean s of data-linking non-applicants will be 
identified..”. The already mentioned “ one-stop shops ” introduced in a number of Member 
States have also contributed to increasing take up by informing people applying for one 
benefit about their eventual en titlement to other benefits.  
Table 3.2 – The effects of non-take up of SA  benefits among working-age individuals43 
(poverty line at 60% of median  equivalised household disposab le income - unless stated 
otherwise - under complete take up ; all values in %) 
(policy years 2001, 2005)  
 Poland Portugal Sweden UK 
A. Poverty gap efficiency 
Complete take up 49.9 22.4 48.7 59.9 
Incomplete take up 23.5 16.1 33.3 54.0 
Proportional change -53 -28 -32 -10 
B. At-risk-of-poverty rate  at 60% of median 
Complete take up 13.0 15.4 8.8 14.6 
Incomplete take up 15.8 15.4 9.5 15.1 
Proportional change 22 0 8 4 
C. At-risk-of-poverty rate  at 50% of median 
Complete take up 5.4 10.1 4.3 7.2 
Incomplete take up 9.2 10.1 5.7 8.0 
Proportional change 69 0 31 10 
D. At-risk-of-poverty rate  at 40% of median 
Complete take up 2.6 4.2 2.5 2.8 
Incomplete take up 5.4 4.6 3.7 3.7 
Proportional change 107 9 47 30 
E. Poverty gap 
Complete take up 2.9 3.7 2.2 3.2 
Incomplete take up 4.8 4.0 2.9 3.7 
Proportional change 64 9 34 16 
Source: Matsaganis, Paulus and Sutherland (2008) 
                                                 
43 As already said, baseline results from EUROMOD rely on the assumption of full take up. In Matsaganis 
et al. (2008) a methodology is applied to simulate also the case with incomplete take up. The take-up 
rate is set equal to an estimate derived from extern al sources and the number of  beneficiaries within the 
eligible population is set to match the estimated take -up rate. Eligible people not claiming their benefits 
are selected randomly. Random draws are repeated 1000 times (100 times for Poland) and average 
values are calculated and presented as simulation results. 
 
EN 51   EN 3.5.4. Minimum income schemes: the i ssues of adequacy and work incentives 
The 2008 European Commission Communication on the active inclusion of people excluded 
from the labour market 44 already underlined that in most Me mber States and with regard to 
most family types SA benefits alone are not sufficient to lift people out of poverty risk . 
This emerged from OECD calculations on net income of social assistance recipients using tax-benefit models (as repor ted in European Commission, 2008)
45 and has been confirmed by 
the EU Network of national independent experts.  A review and discussion of differences in 
methodologies and measures of adequacy is be yond the scope of this brief analysis but is 
already scheduled in the context of the work  on Active Inclusion, and included in the 2010 
work-programme of the Social Prot ection Committee Indicators Sub-Group. 
The EU Network experts also  highlight the fact that MI schemes play an important role in 
reducing poverty intensity, though the extent  to which they do so varies greatly across 
Member States . This shows up also in simulation resu lts obtained for 15 EU countries using 
EUROMOD (Figari et al., 2009).Figure 3.5  represents the median poverty gaps46 for working-
age individuals (not in  full-time education) below the pove rty line (at 60% of the median) 
before and after receiving MI benefits. The me dian poverty gap for peopl e entitled to benefits 
is indeed reduced through MI benefits in all co untries, though with a substantial cross-country 
variation. The effect is stronge r in BE, the NL and SE and sma ller in ES, EE, AT, PL and FI. 
Figure 3.5 also shows that in al l countries the median poverty gap is larger for working-age 
individuals entitled to MI (befor e receiving it) than for individuals  that are not entitled to it. 
This suggests that MI schemes are indeed targ eting the poorest working-age individuals in all 
countries, despite the fact that, as mentioned ab ove, in some Member States people with very 
low incomes are still left with no access to the schemes due to low coverage. 
Mechanisms for up-rating MI benefits over time  are also important to ensure adequacy. Many 
of the EU Network experts note a tendency towards deteriorat ion of benefit adequacy 
with respect to general living standards, wi th the benefits “losing ground” relative to 
wage increases  over time  (which reflects the more general downward trend – observed by 
Nelson, 200947 – for social assistance benefits standa rdised for wage increases between 1990 
and 2005). This is often linked to the lack of clear systems and procedures for regular up-
rating of the MI level  (see Frazer and Marlie r, 2009, and the country reports produced by the 
EU Network of independent experts for the country-specific institutional details on this).  
                                                 
44 COM(2008) 639 final. 
45 European Commission (2008) “Social protection and social inclusion 2008: EU indicators” 
Commission Staff Working Document. 
46 The poverty gap is expressed as the distance betw een the household equivalised income and the poverty 
line as a proportion of the poverty line. 
47 Nelson K. (2009) "Social assistance and minimum income protection in the EU: vulnerability, 
adequacy, and convergence" Luxembourg Income Study Working Paper No. 511. 
 
EN 52   EN Figure 3.5 – Median poverty gap of working-age  individuals below the poverty line (at 
60% of the median) by MI entitlement stat us (before and after receiving MI benefits) 
(policy years 2001, 2003, 2005)  
0.00.10.20.30.40.50.60.70.80.91.0
BE DE EE ES FR IT LU NL AT PL PT SI FI SE UKNot entitled to MI Entitled to MI (before receiving MI) Entitled to MI (after recev ing MI) 
Note: MI schemes are defined here as to include the benefits listed as “Minimum resources: general non-
contributory minimum” in the Mutual Information System on Social Protection (MISSOC) database. Tax-benefit 
policy rules refer to 2001 for FR, SE; to 2003 for BE, DE, IT, LU, NL, AT, PT, FI, UK; to 2005 for EE, ES, PL, 
SI. Figures for FR do not take into account the (time- limited) earnings disregards linked to the MI scheme 
(RMI). MI schemes cannot be simulated for IT and ES, wh ere the schemes are administered at the regional level 
and variation across regions is too la rge. For these two countries MI receipt informa tion from national surveys is 
therefore used. The sample size of working-age individuals below the poverty line entitled to MI benefits is 
small in DK, ES and AT. DK has been dropped while the results for the remaining countries should be treated 
with caution.  
Source: Figari, Haux, Matsaganis and Sutherland (2009) 
For many Member States designing MI scheme s in such a way not to negatively impact 
on incentives to take up work represents a key concern . Attention has been increasingly 
devoted to designing the schemes so as to avoid creating unemployment and inactivity 
traps, as well as low wage traps  for people in work and in receipt of MI benefits. In this 
sense, based on the assessment of the tax- benefit reforms aimed at making work pay 
conducted by the European Commission in February 2009,48 policy interventions adopted by 
the Member States include reductions in the tax wedge (direct labour taxation plus social 
security contributions) on lower wages, increa ses in minimum wages, the introduction of in-
work benefits and the review of the design of out -of-work benefits including social assistance.  
The above mentioned European Commissi on study shows that between 2001 and 2007 the 
largest improvements in terms of reducing unemp loyment traps were achieved by FR, SK, FI, 
SE, BE and DK for all household types. The in troduction of in-work benefits contributed to 
reducing unemployment traps in FR, SK, IE an d FI, while a contribution in this sense was 
provided by measures to reduce the tax wedge on low wages in FR, FI, BE and PL. Increased 
earnings disregards helped re ducing the financial disincentiv es to work in FR and FI. 
                                                 
48 European Commission (2009) “Recen t reforms of the tax and benefi t systems in the framework of 
flexicurity” European Economy O ccasional Papers 43, Feb 2009. 
 
EN 53   EN Inactivity traps were also considerably reduced between 2001 and 2007 in a number of 
countries. In particular, this was the case for one-earner couple s with children at a low wage 
level in FR, SE, AT, ES, FI, CZ and SK. The re duction was mainly due to changes in social 
assistance schemes, followed, for instance, by th e introduction of in-work benefits as in SK 
and SE. Targeted reductions in inactivity traps for certain family types were achieved also in HU (for two-earner couples with and without ch ildren), the UK (for one-earner couples), IT 
(for two-earner couples with and without chil dren) and IE (for two- earner couples without 
children and single parents w ith children). Based on recent data (2007), re ductions in 
inactivity traps have been recorded in partic ular for FR, LV and SE . This was driven by 
changes in social assistance schemes in FR  and LV and by the introduction of in-work 
benefits in SE.  
Specific factors  characterising the de sign of MI schemes that might bring about 
disincentives to take up work  are identified by the EU Networ k experts (Frazer and Marlier, 
2009). These include: 
(4) high benefit withdrawal rates  (also with regard to secondary benefits providing 
access to key services like medical care and childcare); 
(5) lack of systematic mechanisms to ad just the value of earnings disregards
49 over 
time so as to avoid their erosion; 
(6) regulations on refund of benefits  on the part of former beneficiaries. 
In the context of the work on Active Inclusion, a more deta iled review of the existing 
evidence and further analytical work on the re lationship between mini mum income protection 
and incentives to take up work will be co nducted with the Social Protection Committee 
Indicators Sub-Group. 
4. T HE USE OF THE EUROPEAN SOCIAL FUNDS TO SUPPORT SOCIAL OBJECTIVES 
DURING THE CRISIS AND IN THE LONG TERM  
The European Union mobilises significant fina ncial resources to fight poverty and social 
exclusion and to promote the po licy objectives agreed in the So cial OMC. Here, the European 
Social Fund (ESF) is the single mo st important financial instrument  at the disposal of the EU. 
The ESF accounts for almost 10  % of the €  120 billion annual EU budge t, and will spend over 
€ 75 billion in total between  2007 and 2013. In the period 2007–2013, the ESF will invest 
over €  75 billion in creating jobs, promoting soci al inclusion, fighting discrimination and 
strengthening institutional capacity. 
As described in greater depth in the 2008 Jo int Report on Social Protection and Social 
Inclusion, Member States have designed strate gies to create more and better jobs and to 
promote social inclusion and cohesion in  the 117 ‘operational programmes’ planned 
according to their specific situations and needs.  
                                                 
49 Earnings disregards are the part of income that is not taken into account when assessing whether 
eligibility conditions are met by the applicants. 
 
EN 54   EN Fighting poverty and social ex clusion through ESF interventions  primarily takes two forms. 
Firstly, the ESF can target social exclusion ex plicitly. Such actions tend to be curative in 
nature and are aimed at people already suffering from social exclusion. Some €  10 billion 
(12.4  % of the total funding over 2007-2013) can be spent on this type of action.  
Secondly, ESF actions aim to prevent or reduce poverty and exclusion through early 
intervention. In particular, measures to help invest in skills and knowledge, but also to 
improve workers’ adaptability or fight early school-leaving, belong to this second type of 
intervention. No matter which form of inte rvention is used, however, the bulk of ESF 
spending helps prevent or reduce social exclusion.  
The two approaches outlined above involve a broa d range of target groups and policy areas. 
In the period 2007–2013, the European Social F und will focus on the social inclusion of 
disadvantaged people, in particular by improvi ng their opportunities fo r integration in the 
labour market. In addition, the ESF also s upports employability measures, the social 
economy, access to vocational training, and life-long learning. Gender mainstreaming, the promotion of equal opportunities and anti-discrimination measur es are also supported. As far 
as pensions are concerned, the ESF aims to promote longer working lives by keeping older 
workers in employment. Finally, throughout  the programming period, many operational 
programmes will make a significant contributio n to health and long-term care by focusing on 
key personnel employed in this  labour-intensive sector.  
The operational programmes for the 2007–2013 pr ogramming period were developed in a 
period of increasing employment and stable gr owth, but the overall economic context in 
which they now operate has changed fundame ntally. Economic growth  plummeted in 2009 
and the situation in the labour market has dete riorated significantly. For many disadvantaged 
persons, the result is further vulnerability and isolation from the labour market. Social 
protection and inclusion systems now face the enor mous challenge of ensuring that the crisis 
does not disproportionately affect those citizens mo st in need.  
The unemployed are the group requiring most ur gent action. Many Member  States focus their 
ESF interventions on this group in order to help  them maintain their employability and find a 
new job as quickly as possible. In  addition, the number of persons at risk of losing their jobs 
has also increased. Therefore, an equally ur gent issue is to prevent unemployment. Many 
measures supported by the ESF therefore seek to keep people in employment, albeit often 
with shorter working hours, and prepare for the upcoming recovery by investing in their skills 
and qualifications.  
In a context of rising unemployment, falling revenues and in creasing scarcity of resources, the 
ESF can provide stable, predicta ble and available financial suppor t. In their response to the 
crisis, Member States and the European Union ha ve made use of the financial instruments at 
their disposal, such as the ESF, by re-a djusting their operational programmes, where 
necessary, and fine-tuning them to their emerging needs.  
Member States’ responses to the crisis also re flect the will not to lo se sight of the most 
vulnerable. While efforts to give  people furthest from the labour market a realistic chance of 
finding a job are by nature more time-cons uming, the way operational programmes are 
implemented shows that combating the crisis in the short term and addressing long-term 
 
EN 55   EN priorities and actions in support of vulnerable groups are not mutually exclusive, with many 
Member States maintaining their efforts to help  those facing structural barriers in accessing 
the labour market.  
The following chapter looks at ESF-supported ac tions responding to the most urgent needs 
prompted by the crisis and at the longer-term aim of cushioning the impact of the crisis on the 
most vulnerable. The chapter also sets out how  the Commission and the Member States have 
adjusted their instrume nts to respond to the crisis, by modifying, simplifying or making them 
more effective. Finally, the chapter describes some recent actions supported by the European 
Globalisation Fund to help maintain the soci al inclusion of workers losing their jobs. 
4.1. ESF support for social protection and incl usion: actions responding to the crisis 
As part of their immediate responses to the crisis in the areas of social inclusion and 
protection, Member States have used the ES F to enhance support for the unemployed, to 
prevent further rises in unemployment and to st rengthen the social in clusion of vulnerable 
groups.  
Member States have used four main approaches to mobilise ESF resources to counter the 
effects of the crisis, which can  be described as follows:  
• Support for the unemployed 
• Preventing the risk of unemployment 
• Social inclusion of vulnerable groups 
• Simplifying ESF implementation arrangement s to better respond to the crisis 
4.1.1. Support for the unemployed 
As mentioned earlier, the cu rrent economic crisis has had a significant impact on 
unemployment. Given the well-known link betw een poverty and unemployment, a key policy 
objective is to ensure that unemployed peopl e benefit from active measures as soon as 
possible, in terms of new employment where it exists, the updating of old skills or the 
acquisition of new ones. The objective is to ensure  that people do not lose their link with the 
labour market and become long-term unemployed, thereby increasing their chances of financial and social exclusi on. The following section details some of the ways in which 
Member States have used the ESF to support the unemployed.  
To better focus ESF spending on certain areas, Poland  has introduced anti-crisis measures 
mainly under the Adaptability and ALMP prio rities of the operational programme (OP), 
which play the principal role in mitigating the impact of the crisis. Some specific measures (amounting to €
 156.5 million in 2009) include subsidies to increase the geographical mobility 
of employees by covering the co sts of transport and settling dow n in other places, funds for 
retraining qualified redundant employees (for in stance from the service sector), or financial 
support for business start-ups by employees losing th eir jobs as a result of  lay-offs. Similarly, 
additional ESF funds have been allocated to support self-employment for the unemployed in 
Slovenia . 
 
EN 56   EN Ireland  has introduced a number of new active measures that may receive ESF co-funding, 
such as a work experience scheme (including fo r graduates), an increa se in the number of 
tertiary education places for the unemployed, a doubling of the monthly capacity of the public 
employment service (PES), and a significantly in creased number of short-term training places.  
In the UK , the devaluation of the sterling agains t the euro since 20 08 has resulted in 
additional ESF funding in England amounting to £  179 million. This additional funding is 
being used to help those most affect ed by the economic downturn. Of this, £  79 million has 
been allocated to provide extra help for the une mployed to make a successful return to work, 
focusing on people who have been on jobseekers allowance for 6 months (and therefore at 
risk of long-term unemployment) and other disadvantage unemployed people from day 1 of 
unemployment at Jobcentre Plus. In addition, the introduction of the ‘Training for Success’ 
programme in Northern Ireland will assist young people in acquiring the required skills and 
qualifications to get work. 
In Greece , the creation of 12 new employment cen tres (KPA) and the renovation of another 
38 will help address the needs of those recently made unemployed. 122  350 unemployed had 
benefited from active employment measures up to March 2008, through participation in co-
financed projects such as ‘new employment pos ts’, ‘work experience’, ‘promotion of new 
employers’ and so forth, targeting part icular groups and different sectors. 
Portugal  has strengthened measures to address th e unemployed, such as qualification actions, 
professional training, professional internsh ips for young people with high qualifications, 
double certification training, and consulting schemes for enterprises. Special attention is given 
to measures to help create jobs, including se lf-employment, entrepreneurship and professional 
internships, and an effort has been made to increase the implementation rate of these 
measures. Participation by unemployed people in useful social activities is promoted by the 
OP, aiming to help unemployed pe ople retain contact with the labour market, avoid long-term 
unemployment, and increase their purchasing power.  
4.1.2. Preventing the risk of unemployment 
Since unemployment is so strongly linked to pove rty, it is important that rising unemployment 
is tackled — especially the drift towards l ong-term unemployment. Many ESF actions taken 
by Member States have been designed with  a view to preventing further rises in 
unemployment and people falling in to social exclusion and poverty. 
Germany  has responded to the crisis by adap ting its short-term allowance scheme 
(Kurzarbeitergeld) to the new situation on the la bour market. The principle is ‘better retrained 
than redundant’ (‘Qualifizieren  statt entlassen’). In particular, the maximum duration for 
receiving the short-term allowance has been ex tended from 6 to 24 months. Furthermore, the 
government seeks to encourage employers and employees to use the period of short-time 
work to organise training cour ses. If such a cour se is organised, the public employment 
service pays, as a financial incentive, 100  % of the social security costs. The ESF can be used 
as a source for co-financing the traini ng courses and the short-term allowance.  
Similarly, in the Czech Republic , an ESF co-financed budget of €  125 million has been 
allocated to schemes subsidising the wages a nd training costs of employees whose companies 
are forced to reduce their working hours. The two short-term working schemes, ‘Train 
 
EN 57   EN yourself!’ and ‘Training is a ch ance’, enable companies to obtain reimbursement of the 
training costs and salaries for their employees  for the time they spend on training. Their 
implementation is managed by the labour offices or directly by the Ministry of Labour.  
The Hungarian  OP co-funded by the ESF supports a similar scheme, combining reduced 
working time with training, for micro, small a nd medium-sized enterprises. A scheme for 
larger companies is also envisaged. In Slovenia , the obligatory training of employees 
temporarily waiting for work is also co-fin anced by the ESF. Another example of this 
approach is Austria  which has changed its OP to extend the group of potential beneficiaries 
to employees in short-time working ("Kurzarbeit")  (before the change training for older 
workers was eligible). Similarly, the initial focus of Finland’s  OPs  was mainly on employed 
people and the weakest groups in the labour ma rket. Since the financial crisis, however, 
funding has also targeted the increasing nu mber of workers who have just become 
unemployed.  
The Italian  government has widened the scope of some  unemployment benefits (indennità di 
disoccupazione in deroga). Extra funds from na tional resources and ESF regional operational 
programmes have been allocated to such unemp loyment benefits and to  active labour market 
policies (ALMPs) for the period 2009-2010, focusi ng on the needs of redundant workers or on 
those temporarily laid off due  to demand fluctuations or firm restructuring. These new 
provisions complement national unemployment benefit programmes: the workers are involved 
in labour market reactivation programmes run by public employ ment services and 
employment agencies and the target groups be nefit from personalised training paths or are 
given training vouchers.  
The Netherlands  has modified its OP with a view  to combating youth unemployment. A 
national Action Plan on Youth Unemployment  was presented in May 2009. The measures 
include creating extra apprenticeships and trai neeships and stimulati ng regional cooperation 
between all actors (municipalities, social part ners, schools, PES) able to contribute to 
participation possibilities fo r young people up to the age of 27. The activities qualifying for 
support are those covered by th e national Action Plan, and in clude education, training, 
guidance, working/learning combinations , traineeships, apprenticeships, etc. 
In Spain, the ESF contributes to a number of ac tions, focusing both on the short term 
(responding to lay-offs) and on the long term (supporting sustai nable economic growth), such 
as reinforced personalised guidance and support , skills development and local needs, the 
promotion of occupational and geographical mob ility, and the concentration of support on the 
most vulnerable. Over a long-term perspectiv e, the ESF provides re inforced support to 
emerging sectors (identification of future occu pational and skills requirements) and to human 
capital and education actions (c ombating early school drop-out). 
France has reinforced the priorities for strengthening the ability of workers and companies to 
adapt to economic change, ensuring access to employment for job seekers through training for qualifications, and providing support for the mo st vulnerable (general  introduction of the 
‘active solidarity income’ — Revenu de Solidar ité Active (RSA)). In addition, it was decided 
to extend temporarily the ESF support for traini ng activities by crisis-a ffected companies with 
more than 250 employees (whereas the OP targets mainly SMEs).  
 
EN 58   EN 4.1.3. Social inclusion of vulnerable groups  
In the current global economic downturn, the role of the ESF in supporting the most 
vulnerable has never been more critical. The E SF is contributing to the efforts made by the 
Member States in a number of actions aimed at ensuring that vulnerable groups are not disproportionately hit by the cris is. Most ESF OPs try to ensure a coordinated response to the 
needs of those furthest from the labour ma rket, including actions to promote access to 
employment and sustainabilit y, the social inclusion of di sadvantaged persons, and human 
capital development.  
In Cyprus,  the OP co-financed by the ESF provides for a series of interventions to increase 
labour supply (especially of wome n and young people) and strength en the social inclusion of 
vulnerable groups, while also supporting the development of human resources and the 
adaptability of workers and enterprises. As a re sult, there is a high de gree of complementarity 
between the actions planned under the ESF and the Prevention Action Plan put in place by the 
government in response to the crisis. A large number of interventi ons under the Prevention 
Action Plan (such as promoting new employment opportunities fo r vulnerable persons, skills 
upgrading, vocational training, work experience and subsidised job placements, along with upgrading and expanding the activities of the pu blic employment services to better respond to 
the needs of the unemployed and the vulnerable)  are expected to be supported by the ESF. 
In the  UK,  part of the additional ESF funding (resulting from th e devaluation of sterling 
against the euro) has been allocated to increasi ng the support that Jobcentre Plus provides to 
disadvantaged groups such as ex-offenders, re fugees, homeless people, people with drug or 
alcohol problems, people leaving residential care, lone parents, people with disabilities, etc., 
thus strengthening activation and prevention. 
Romania  has set up a national pre-financing syst em for programmes co-financed by the ESF. 
This system gives greater support to so cial inclusion projects, for which 40
 % pre-financing 
(instead of 30  %) has been set aside. 
In Greece , an important objective is to further re structure the public employment centres 
(KPA) by converting them into ‘one-stop shops’ ab le to implement stronger active policies for 
disadvantaged groups. More precisely, support for strengthening the social inclusion of at-risk 
groups includes actions to improve the atte ndance of vulnerable groups in secondary 
education (Roma, migrants, minorities) and to reduce early school-leaving and promote 
achievement through all-day schools, learni ng support programmes for immigrants, the 
establishment of intercultural schools, ‘sec ond chance’ schools and adult education centres, 
and the use of new technologies  in the learning process.  
4.1.4. Simplifying ESF implementation arrange ments to respond to the crisis  
In their response to the crisis, Member States ha ve also made use of the flexibility offered by 
the ESF to cushion the impact of the crisis on the most vulnerable by adjusting their operational programmes, modifying them where necessary and using the simplification tools 
proposed by the Commission to improve  the effectiveness of the ESF.  
Many Member States have used the opportunity  to review their operational programmes to 
adapt them to the changing economic context.  Concerning the refocusing of strategies 
 
EN 59   EN supported by the ESF and the fine-tuning of prog rammes, it is worth noting that a number of 
changes to OPs and implementing arrangement s have been made. Member States have 
amended the selection criteria, modified the st rategic indicators to ta ke account of emerging 
needs and, in some cases, reallocated f unding between categories and priorities. 
In Poland , some changes have been made to the selection criteria — such as ensuring 
participation in ESF projects for those employed in  sectors particularly affected by the crisis. 
Simplified implementation arrangements are envi saged by the authori ties, including fast-
tracking for project sele ction — especially for labour mark et and adaptability measures.  
In order to better respond to the crisis, Latvia  has reviewed the priorities set in the ESF OP. 
The OP ‘Human Resources and Employment’ has been revised substan tially in response to 
the challenges faced by Latvia due to the financ ial and economic crisis. The main change is 
the re-allocation of resources to Priority 3 ‘P romotion of Employment and Health at Work’ 
(€ 22 million) and Priority 4 ‘Promotion of Social Inclusion’ (€  16 million). New measures 
include a local employment emergency progr amme, short-term working combined with 
training, and retraining of teachers in the context of education reform.  
In the UK, the Wales/Convergence OP  has transferred €  41 million from priority 1 ‘For young 
people’ to the ‘Employability’ priority. Sim ilarly, the Irish ESF OP was revised in 2009 to 
better respond to the crisis by focusing more on support for the unemployed. This involves 
transferring some resources from Priority II ‘In creasing Participation and Reducing Inequality 
in the Labour Force’ to Pr iority I ‘Increasing Activati on of the Labour Force’.  
In Portugal , the ESF programme has been modified to mitigate the impact of the crisis. 
Under priority 5 ‘Support for en trepreneurship and transition into active life’, new measures 
have been introduced to support the maintenance of jobs in enterprises in a sound financial 
situation but facing falling world demand, mainly  by training workers. Another modification 
involves promoting the employability of unempl oyed people and social welfare beneficiaries 
by supporting their participation in  useful social activities. Pr iority 6 ‘Citizenship, Inclusion 
and Social Development’ has received an additional €  37.1 million from the Portuguese 
government in order to boost public investment in the social sector. 
4.2. ESF support for social protection and inclusion: long-term actions 
Despite the crisis, the ESF co-funded progra mmes will continue with long-term social 
inclusion actions to strengthe n social cohesion. In the cu rrent programming period, some 
Member States are using the ESF to implement multidisciplinary actions to respond to more 
complex social challenges. These actions c over different fields such as education, 
employment or social inclusion in a holistic ma nner. The experiences to date show that ESF 
support mobilises and triggers effects from diff erent policy fields which would otherwise not 
have come about. The catalytic effect ge nerated by the ESF on the ground leads to the 
streamlining of multidisciplinary actions, t hus overcoming fragmented policy-making and 
combining different interventions in to a single comprehensive approach. 
• In Slovakia , the ESF co-finances the complex (comprehensive) local development 
strategies for marginalised Roma communiti es. These strategies have been allocated 
almost € 179 million for the programming pe riod 2007-2013. They require at least one 
 
EN 60   EN investment project (ERDF) a nd one non-investment project (ESF). The call for proposals 
has already been published and will remain open until the end of January 2010. Eligible 
activities under six operational programmes include building in frastructure (educational, 
social and tourist, plus settlement regenera tion), supporting employment  growth and social 
inclusion, raising the educational level of communities, innovation and technology 
transfers, health promotion, and waste management. 
• In Germany  an ESF co-funded programme (BIWAQ50) has been launched to address the 
multiple problems arising in deprived neighbourhoods due to social and economic change. 
Its starting point is the fact th at economic and social deficiencies are usually concentrated 
in specific neighbourhoods where structural deficiencies in buildings and dwellings, 
inadequate infrastructures, hi gh unemployment rates, low in comes, lack of skills or 
education and, as a result, poor employment opportunities are creating tensions in these 
communities, including tensions between diffe rent ethnic groups. BIWAQ is closely linked 
to a more comprehensive policy initiative called the ‘Social City’51, which is based on an 
integrated approach cutting across various fields of acti on. Under the BIWAQ programme, 
public bodies, private entities and partnerships (such as businesses, education or training 
providers, schools, clubs or associations) may r eceive funding for projects within the areas 
covered by the ‘Social City’ programme. The content of the BIWAQ projects must have a 
connection with the development strategies adopted by urban and local authorities under 
the ‘Social City’ programme, thereby followi ng its integrated approach. BIWAQ projects 
target both the mainstream segments of soci ety and persons with an  immigrant background 
and aim to promote social inclusion a nd community life in neighbourhoods. BIWAQ 
focuses on (1) helping the long-term unemp loyed back to work ; (2) providing young 
people with training and integr ating them into the labour market; (3) facilitating the 
transition from school to work; and (4) strengthening the local economy.  
• As part of the Spanish  regional OP for Cataluña, the re gional government has singled out 
80 particularly deprived neighbourhoods in  the region for intervention under the ESF 
Programme ‘Employment in th e Neighbourhoods’. One of them is the Barrio de La Mina 
(a particularly deprived area in Barcelona). This area received ESF co-financing under the 
Catalonia OP Objective 3 in 2000-2006. Th e success of the project prompted its 
mainstreaming in the OP 2007-2013. The projec t comprises an ad hoc consortium bringing 
together all relevant actors to jointly mana ge actions (urban pla nning, social inclusion, 
training, etc.). Main ‘innovativ e’ features: strengthenin g and recognition of local 
governments as main actors in employment a nd local development policies; a ‘Charter of 
Services’ for local governments, integrating all active employment policies into a single 
project; a change of approach  from sectoral implementati on of policies to territorial 
implementation; and strengthened cooperation between regional/local administrations.  
• In Ireland , the ESF helps promote equality in tertiary educati on by increasing the 
participation rates of students with disabili ties, students from disa dvantaged backgrounds, 
including from the Roma community, ethni c minorities and mature ‘second-chance’ 
students, through the ‘Third Level Access’  measure. The Fund for Students with a 
                                                 
50 BIWAQ stands for ‘ Bildung, Wirtschaft, Arbeit im Quartier ‘ (education, economy, work in the 
neighbourhood). 
51 This programme is an urban development programme which targets neighbourhoods with development 
priority. The Social City ( Soziale Stadt ) was launched in 1999 to count eract the increasing social and 
spatial segregation of urban communities. 
 
EN 61   EN Disability, part of the Third Level Acce ss fund, provides grants for the provision of 
services and purchase of equipment for stude nts with serious sensory, physical and/or 
communicative disabilities. ESF co-financing is al so used to provide targeted aids such as 
transport, sign-language assistance/interpre ters and personal assistants. The Student 
Assistance Fund, which aims to assist student s who might otherwise, because of financial 
reasons, suffer severe hardship or be unable to continue their tertiary studies, is also an 
integral part of tertiary access funding. A ssistance under the Student Assistance Fund 
covers rent, books/course materials and living expenses. Expenses financed under the Fund 
for Students with Disabilities include transp ort, personal assistance, and equipment.  
• In the UK, the ESF-funded project Seeing the Po tential, which is run by the Royal 
National Institute of Blind People (RNIB), assi sts blind and partially-sighted people to 
prepare for work — through training or work placements — and secure and sustain paid or 
voluntary employment. The projec t operates by regularly meeting with clients to assist 
with exploring employment options and identifying vacancies, creating a CV, and 
providing assistance with applica tion forms and cover letters. 
4.3. The European Globalisation Adjustment Fund (EGF) 
The EU Structural Funds, in particular th e European Social Fund (ESF), support the 
anticipation and management of change throu gh activities with a st rategic and long-term 
perspective, such as life-long learning. In cont rast, the European Globalisation Adjustment 
Fund (EGF) provides one-off, time-limited indivi dual support geared to helping workers who 
have become redundant as a result of globalisation. 
The EGF exists to support workers who lose thei r jobs as a result of  changing global trade 
patterns or the current economic and financial cr isis. When a large enterprise shuts down or a 
factory is relocated to a country  outside the EU, or a whole sect or loses many jobs in a region, 
the EGF can help the redundant workers to find new jobs as qu ickly as possible. A maximum 
amount of €  500 million per year is available to th e EGF to finance such interventions. 
The advent of the current recession, with its  greater demands and challenges, called for a 
strengthened response, and the EGF was modifi ed in 2009 to enable  it to respond more 
flexibly to the requirements of redundant worker s. Some aspects of the EGF were modified 
specifically for the expected dura tion of the crisis, including: 
– The addition of the crisis itself as a qua lifying condition. Where pr eviously evidence of 
changing world trade patterns had to be provi ded, applications made by the end of 2011 
can be justified by redundancies caused by the crisis. 
– For applications introduced before the end of 2011 the intervention rate has been increased 
to 65  %, rather than the normal 50  %. This means less strain on national budgets, so more 
workers can be assisted. 
One of the key principles of the EGF is that  assistance should be provided as quickly as 
possible in order to keep the workers in the labour market. Active labour market policy 
measures can be eligible for EGF funding fr om the moment of redundancy, which may occur 
several months before the decision on such f unding has been taken by  the EU’s budgetary 
authority. 
 
EN 62   EN The EGF specifically encourages measures aimed at disadvantaged or older workers to help 
them reintegrate into the labour market, in order to make up for the disadvantage that their age 
may constitute in the eyes of potential employers or the extra training they may require after many years in the same job or the same sector . In several EGF cases Member States have 
proposed actions specifi cally for workers over 45 or over 50, aiming to keep them in active 
employment. Where necessary, this assistance can include wage subsidies and public works 
employment. 
Other EGF cases have targeted workers with low basic education leve ls. Both Portugal and 
Ireland have proposed measures to help redundant  workers overcome obstacles resulting from 
low basic education levels, through provision of targeted education and the recognition and certification of experience gained. 
Another area of disadvantage th at the EGF tackles is geogra phical remoteness. The case of 
Perlos in Eastern Finland showed that the coll apse of the biggest employer in the region may 
threaten the whole area with depopulation. By helping the wo rkers to acquire new skills 
locally and to find new jobs or start their own bu sinesses, the EGF helped to ensure a brighter 
outlook for the region, and to keep the younger population there. 
5. T
HE IMPORTANCE AND EXTENT OF HOMELESSNESS AND HOUSING EXCLUSION  
5.1. Housing vulnerability: the importance of  housing in the context of the current 
economic crisis 
The link between the housing market and the ec onomic crisis differs be tween Member States, 
both in terms of the role of housing as a factor behind the economic crisis and the consequences of the crisis for the housing situati on of EU citizens. This complex picture is at 
least partly due to the diffe rent structure of housing mark ets and their legal and policy 
frameworks. The labour and credit markets c onstitute the most obvious connection between 
housing and the broader economy.  
Employment in the construction sector, which increased in th e vast majority of Member 
States between 2000 and 2007 with the housing boo m, was one of the worst affected by the 
economic crisis. In turn, employment losses in the economy at large have had a further 
negative impact on housing markets and incr eased the risks of becoming homeless. 
Concerning the credit market, the vulnerability  of households to fluc tuating and often over-
inflated house prices and to un certain financial markets has increased in the last ten years: 
mortgage debt as a percentage of household in come has increased in most Member States, 
reaching over 100
 % in PT, ES, SE, the UK and IE and over 200  % in DK and NL.  
The potential severity of the crisis and its im pact on the housing situat ion of EU citizens are 
illustrated by the following examples based on national data52. Significant in creases in the 
number of non-performing housing loans have been recorded in Belgium, Estonia (+ 215  % 
in 2008 and a further 40  % increase in the first quarter of 2009), Greece, Ireland, Lithuania 
and Latvia. The number of repossessions  has also increased  in Denmark (+100  % in 2008 
                                                 
52 See the Joint assessment by the SPC and the European  Commission of the social impact of the crisis 
and of policy responses (doc. SPC/0911/1).  
 
EN 63   EN and +46.3  % in 2009), Spain (+126  % in 2008), Greece (+17  % in 2008), Ireland (+30  % 
between June 2008 and June 2009), and th e United Kingdom (fro m 10000 in Q2-2008 to 
11400 in Q2-2009). The number of beneficiaries of specific support schemes for tenants has 
increased in IE (+41  % between Q2-2008 and Q2-2009) and HU (+5  % between 04-2008 and 
04-2009), while the number of beneficiaries of sc hemes to support mortgage holders also rose 
in IE: +144  % between Q2-2008 and Q2-2009. Finally, the applications and waiting times 
for social housing  have increased  in Ireland, Luxembourg and the UK.  
The consequences of the economic  crisis on households vary greatly across Member States, 
depending on the support mechanisms in place and the policies introduced to counteract the effects of the downturn. In particular, Memb er States have reacted with measures to protect 
mortgage holders , such as housing loan subsidies (EL, IT, NL, PL
53, IE, SK and the UK), 
state guarantees for mortgage loans and tax refo rms (ES, HU, PT and LU ), the possibility to 
renegotiate and postpone mortgage payments and making repossessions more difficult (EL, 
ES, IT and LT); and investment in housing and regeneration , including accommodation for 
the homeless and measures to improve energy e fficiency (DE, ES, FR, IE, LV, LU, MT, AT, 
PT and the UK). More genera l measures introduced to strengthen income support  are also 
important to help people cope with the wo rsening conditions in the labour market.  
5.2. Housing exclusion –- an important cha llenge for the EU population at large and 
particularly for those at risk of poverty54 
A decent home is an essential need and access to affordable  and quality  housing is one of the 
main determinants of people’s well-being and social  participation. Indeed, according to a 
recent Eurobarometer survey, for 26  % of EU citizens the fact that decent housing is too 
expensive is the social factor that best explains why people ar e poor. This is why the Charter 
of Fundamental Rights provides for the right to housing assistan ce so as to ensure a decent 
existence for all who lack sufficient resource s. Housing support and social housing are also 
recognised as essential services in  supporting active inclusion policies55.  
Housing affordability is an important challe nge considering that housing costs represent a 
significant proportion of pe ople’s income. On average in the EU the share of housing costs in 
total disposable income , net of housing allowances, is 19  %, reaching over 20  % in CZ, PL, 
SK, EL and the UK and over 25  % in DK and NL. The issue of affordability is particularly 
problematic for the at-risk-of- poverty population: in the EU as a whole, the impact of housing 
costs is more than twice as important fo r the poor as for the non-poor population (33  % vs 
17 %) and this ratio is over 2.5 in FI, AT, FR, CY, SI, LU and SE, where poor people spend 
three times more on housing, relatively to their income, than non-poor people. 
                                                 
53 The public support for mortgage holders is created  as interest-free loan and it is offered only to 
unemployed persons whose have lost their jobs after 1st July 2008. During one year the state covers the 
mortgage rate of registered unemployed person (who applies for such support) up to a. 300 EUR 
monthly. After 2-years the support is finished and the mortgage holders have to, during 8 years, pay 
back (monthly) amount of this support. 
54 For further analysis on homelessness and housing exclusion, see also the 2009 Social Situation Report 
at: http://ec.europa.eu/social/m ain.jsp?catId=675&langId=en   
55 See the Commission Recommendation on active inclusion [2008/867/EC] paragraph 4(c), Council 
Conclusions of 17.12.2008 paragraph 29 and the European Parliament resolution of 6.05.2009 (A6-
0263/2009).  
 
EN 64   EN Fig. 5.1: Share of housing costs in total household income net of housing allowances — 
2007 
0102030405060
EU25SIMTESLUIEPTCYFIFRATEEITLTLVSEBEHUCZPLSKELUKDKNLpoor
non-poor
Total
 
Source: EUROSTAT; EU-SILC 2007 
Notes: data on DE omitted because key components of the housing cost variable are missing. 
The impact of housing costs on household inco me is also particul arly important for 
households in more densely urbanised areas, fo r single households with or without children 
(around 28  %) and for tenants (27  %). 
Housing costs are on average the most important single expenditure item relative to income. 
For a significant part of the popula tion housing costs account for over 40  % of disposable 
income, which can significantly reduce the capacity of the household to ad equately cope with 
all the other needs besides accommodation, even if the relevance of a relatively high housing 
cost burden on household welfare obviously de pends on the level of household income. 
Approximately 13% of the EU population is affected by housing costs overburden , but the 
figure is 39  % for the at-risk-poverty population as against 7  % for the non-poor — more than 
a five-fold difference. Indeed, the difference is  over 10 times in CY, SE, LT, AT and EL and 
over 20 times in LU.  
Furthermore, in Member States su ch as SK, DK, NL, EL and BG over 50  % of the at-risk-of-
poverty population faces an excessive housing co st burden. This represents an important 
challenge in terms of increased  risks for social and housing ex clusion. It also points to the 
importance of housing affordability as a fu ndamental element in improving the living 
standards of people at risk of poverty.  
 
EN 65   EN Fig. 5.2: Housing costs overburden rate — 2007 
010203040506070
EU CY MT IE LU FI LT SI EE AT FR ES HU PT IT SE LV BE CZ PL DK EL UK RO NL SK BGPoor
Non-poor
Total
 
Note: share of the population living in a household where housing costs (net of housing allowances) represent 
more than 40 % in the total household income (net of housing allowances). Data on DE omitted because key 
components of the housing cost variable are missing. 
Source: EUROSTAT; EU-SILC 2007 
Despite the fact that those at risk of poverty tend to spend more, in relative terms, on housing, 
they live in worse housing conditions. Over 27  % of low-income people lives in overcrowded 
accommodation56, as opposed to 15  % of the rest of the populati on. The overcrowding rate for 
the at-risk-of-poverty population is over 50  % in SK, LV, LT, RO, BG, CZ, HU and over 68  % 
in PL. If single households are excluded57, the overcrowding rate is reduced by 2 percentage 
points in SE and 3 in FI, but it increases by 2 in EE, IT, LV, PL, SK and 3 in BG, HU, LT and 
RO.  
                                                 
56 The dwelling is considered over crowded if one the criteria mentioned below is not fulfilled:  
- one room for the household; 
- one extra room for each couple; - one extra room for each single person aged 18+; 
- one extra room - for two single people of the same sex between 12 and 17 years of age;  
- one extra room - for each single person of diffe rent sex between 12 and 17 years of age;  
- one extra room - for two people under 12 years of age. 
57 According to the definition of overcrowding, single-people households living in one-room flats are 
classified as overcrowded. However, this type of  accommodation can range from  large inner city lofts 
to small, inadequate bed-sits; without information on the size of the dwelling it is difficult to properly 
assess the situation. Also, the lack of a separate liv ing-room can have differen t impacts on the capacity 
of the individual to invite people and socialize at his or her place acc ording to the different social and 
cultural norms. For these reasons, data on overcrowding is published with and without single-person 
households.  
 
EN 66   EN Fig. 5.3: Overcrowding rate by poverty status — 2007 
010203040506070
EU CY NL DE ES BE MT IE UK FI DK LU FR SE AT PT IT EL CZ SI SK EE HU BG PL LT RO LVNon-poor
Poor
Total
 
Source: EUROSTAT; EU-SILC 2007 
Apart from overcrowding, low-income households also tend to live in poorer quality 
accommodation. The share of the at-risk-of-povert y population affected by at least one of the 
housing deprivation factors is 38  % in the EU as a whole, and over 50  % in EE, LV, PL, LT, 
BG and RO. This compares with 22  % for the non-poor population. 
Fig. 5.4a: Share of the population affected by at least one housing deprivation factor — 
2007  
0102030405060708090
EUMTSKFISEDKATDELUCZIEFRBENLUKELITESSLHUPTCYEEBGLTPLLVROpoor
non-poor
total
 
Note: housing deprivation factors are: damp walls, leakin g roof or rot in windows; no bath or shower in the 
dwelling; no indoor flushing toilet for the sole use of the household; dwelling too dark. 
Source: EUROSTAT; EU-SILC 2007.  
 
EN 67   EN Figure 5.4b: Material deprivation for the 'Housing' dimension, by item - 2007 
Leaking roof, 
damp walls, 
floors or 
foundation, or 
rot in window 
frames of floor Lack of bath or 
shower in 
dwellingLack of indoor 
flushing toilet 
for sole use of 
householdDwelling too 
darkLacking no 
item
eu27 18 4 4 8 75
be 14 1 1 9 79
bg 15 20 34 10 60
cz 16 1 1 4 82
dk 11 1 0 5 86
de 13 1 1 4 83
ee 22 18 15 7 65
ie 15 1 1 9 80
gr 19 1 3 8 76
es 18 0 0 10 75
fr 14 1 1 8 80
it 21 0 0 8 76
cy 30 1 1 6 67
lv 26 22 20 12 58
lt 25 18 20 11 60
lu 15 0 1 5 83
hu 19 5 6 10 73
mt 5004 9 1
nl 18 0 0 5 78
at 9126 8 6
pl 37 7 6 9 59
pt 20 4 3 17 68
ro 29 42 44 8 43
si 17 1 1 10 75
sk 6134 9 0
fi 5115 8 9
se 6107 8 8
uk 15 0 1 11 77Total
 
Source: EUROSTAT; EU-SILC 2007 
Note: housing deprivation items are: damp walls, leaking roof or rot in windows; no bath or shower in the 
dwelling; no indoor flushing toilet for the sole use of the household; dwelling too dark. 
The indicators presented above mainly concern two aspects of housing exclusion that lead to 
homelessness, namely inadequate and insecu re accommodation. Being without a roof or 
without a house and having to live in emergenc y shelters or in temporary accommodation is 
of course the most extreme form of homelessn ess and indeed poverty and social exclusion. 
The lack of a commonly agreed framework  at EU level to define and quantify homelessness, 
along the lines of the ETHOS definition58, for example, remains one of the main obstacles to a 
                                                 
58 The European Typology of Homelessness and housing exclusion (ETHOS) was developed by 
FEANTSA (the European Federation of National Organisations Working with the Homeless - 
http://www.feantsa.org/code/en/hp.asp ) as a means of improving understanding and measurement of 
homelessness in Europe, and to provide a comm on "language" for transnational exchanges on 
homelessness. This typology was launched in 2005 an d is used for different purposes - as a framework 
for debate, for data collection purposes, for policy purposes, monitoring purposes, and in the media. 
 
EN 68   EN proper assessment of this problem. Definitions  of homelessness and ho using exclusion (HHE) 
vary widely across Member States. There are a small number of Member States that have 
broad definitions of HHE that either correspond directly to the ETHOS definition or cover very similar categories (DE, DK, LU, NL, SE, UK), while some have partial coverage of 
ETHOS categories (BE, FR, HU, PT), some ha ve a narrow definition (CZ, ES, FI, IE, PL, 
SK) and others have no standardised definition at all (AT, BG, CY, EE, EL, IT, LT, LV, MT, 
RO, SI).  
The lack of clear definitions or the use of ve ry narrow definitions can  make it difficult to 
establish a definitive picture of those expe riencing homelessness and housing exclusion and 
its causes. The national data available on r ough sleepers and houseless people show a mixed 
picture, with the situation improving in certain  Member States (UK, IE, NL and DE), but 
deteriorating in others (RO, LT, CZ, HU and SK ). In particular, homelessness has emerged as 
an issue after transition in post-communist countries due to limited public budget support for 
housing developments for the low-income popula tion and the shortage of affordable flats 
following privatisation of the public housing stock. 
 
EN 69   EN ETHOS – European typology on homelessness and housing exclusion 
 
Source: FEANTSA – the European Federation of National Organisations Working with the Homeless 
(http://www.feantsa.org/ code/en/pg.asp?Page=484 )  
 
EN 70   EN 5.3. The overall policy response — comprehensive strategies and better 
governance59 
5.3.1. Comprehensive strategies are key to fi ghting homelessness and housing exclusion.  
Homelessness and housing exclusion have been iden tified as an issue of concern by almost all 
Member States. This greater awareness amongst Member States is also due to the increasing focus given to the issue of HHE in recent year s by the Social OMC. Transnational studies and 
exchanges have helped to enhance mutual le arning and encourage increased efforts in a 
number of countries
60. 
A growing number of Member  States have adopted comprehensive strategies  to fight 
homelessness and housing exclusion, either at national (IE, PT, UK, DK, FI, NL and FR) or 
regional/local level (SE, DE and ES). This ha s helped to push the agenda forward, improve 
coordination in policy design a nd implementation and identify mo re financial resources. In 
general, strategies are more effective with specific targets,  including: prevention  (both in 
terms of preventing evictions and follow-up of individuals discharged from public 
institutions); ending the most severe forms of homelessness  (such as rough sleeping, in line 
with the European Parliament Resolution61); reducing the durat ion of homelessness  (in 
particular the time spent in emergency and temporary accommodation) ; improving the quality 
of services  and accommodation for homeless people; a nd improving the supply of affordable 
housing .  
In several countries (e.g. DE, ES , IE, LU, NL, PL, PT and CY), there is a high and/or growing 
emphasis on prevention , which has proved to be the most effective and least costly way of 
combating homelessness. It has also received renewed attention as Member States respond to the economic crisis. Prevention tends to be of two types: firstly, init iatives to reduce the 
number of evictions and, secondly, increased effo rts to help people leav ing institutions gain 
access to suitable housing. There are examples of comprehensive strategies  targeting specific 
risk groups, such as people released from prison (BE, DK, NL, UK and FI) or children leaving care (PL, MT). 
In many Member States, there is more empha sis on providing temporary accommodation than 
on actual prevention. There is also a trend to wards building other support services around the 
provision of temporary accommodation. However, some Member States have successfully moved beyond temporary/crisis accommodati on to developing more comprehensive 
progression policies to help people move from temporary accommodation to supported 
accommodation and/or into more permanent housing such as social housing (e.g. FI).  
For people already affected by homelessness and housing exclusion, two broad approaches 
can be identified in the EU: the ‘staircase approach’ , leading the homeless step-by-step up 
the housing ladder from emergency accommodation to  permanent, independent living; and the 
                                                
 
59 The next two sections are also based on the analysis of the Member States' contributions by the network 
of Independent Experts on Social Inclusion ( http://www.peer-review-social-inclusion.eu/network-of-
independent-experts ).  
60 For a wealth of information on homelessness and housing exclusion, see the website of FEANTSA (the 
European Federation of National Organisations Work ing with the Homeless) which is supported by 
PROGRESS ( http://www.feantsa.org/code/en/hp.asp ). 
61 Declaration of the European Parliament on ending street homelessness (2009/C 259 E/04) published on 
the Official Journal of 29.10.2009, C 259 E/19. 
 
EN 71   EN ‘housing first’  approach, offering individuals stable housing as a first priority. The latter 
approach has often proved to be  more effective where there is  an adequate housing supply for 
low-income people. However, ‘housing first’ does not mean ‘housing only’, and to ensure 
sustainable integration, home less people often require su pport beyond housing. This has 
prompted several Member States to introdu ce socially supported accommodation, combining 
independent living with h ealth and social support62.  
5.3.2. Improved governance as an important tool  to make strategi es more effective 
Policies to fight homelessness and housing exclusion are the re sponsibility of different 
ministries at national level and different leve ls of government. Typica lly, national government 
is responsible for planning and overall polic y design, while responsibility for delivery is 
devolved to local and/or regional authorities.  
For this reason, inter-ministerial coordination is  essential, and is being improved in several 
Member States, especially those with a co mprehensive strategy, where steering committees 
have also been established to coordinate the efforts of all acto rs involved. However, 
fragmented responsibilities often represent one of  the main challenges for the effective design 
of integrated policies. At the same time, the lack  of capacity and resources at local level is one 
of the main problems in implementing such policies.  
In several Member States (BE, DE, DK, ES , FI, HU, IE, MT, PL, PT and the UK) there 
appears to be a strong or increasing tendency to involve key stakeholders in the planning, 
delivery and monitoring of services. However,  stakeholder participat ion is not promoted 
enough in some Member States and, in most, the direct involvement of people experiencing 
homelessness and housing exclus ion remains quite limited.  
Three elements prove to be particularly useful in impr oving governance in the area of 
homelessness and housing exclus ion where responsibilities ar e shared between different 
levels of government and NGOs: leadership  by the main public authority in charge of 
homelessness and housing exclusion policies; participation  and consultation of relevant 
stakeholders in policy design and implementation; and consensus  on the agreed strategy.  
5.4. Causes of homelessness and ho using exclusion and instruments  
5.4.1. Several factors causing hom elessness and housing exclusion – need for a joint policy 
response to tackle them. 
Homelessness and housing exclusion are particul arly complex phenomena. They are caused 
by a number of different factors and in turn a ffect several socio-economic outcomes, such as 
people’s health and well-being, social pa rticipation, employabilit y, and consequently 
income63. Broadly speaking, the causes of home lessness and housing exclusion can be 
                                                 
62 On social and supported housing-related services, see the study by the Network of Local Authority 
Observatories on active inclusion ( http://www.eurocities-nlao.eu/ ) supported by PROGRESS.  
63 See also the study for the European Commission coordinated by the University of York on "Housing 
exclusion: welfare policies, housing provision and labour markets".  
 
EN 72   EN grouped into three broad categories, even thoug h multiple reasons often coexist and reinforce 
each other64.  
- Structural , such as low income, debt, worklessness and shortages of adequate and affordable 
housing. 
- Personal , such as relationships and family br eakdown, violent and abusive relationships, 
disabilities and mental illn ess, substance dependency.  
- Institutional , such as discharge from institutions (f oster and state care, prison, armed forces, 
hospitals). Housing exclusion can also be brou ght about by discrimination and lack of legal 
status, affecting some ethnic minorities and migrants.  
The changing profile of the homeless populati on also points to new categories of people 
becoming more vulnerable due to the curr ent social and economic environment and 
institutional settings. The first group consists of those at the margins of the labour market : 
either those in low-paid, poor-qua lity jobs who find it difficult to  find adequate and affordable 
housing, or those in precarious, short-term em ployment, who move in and out of the lower 
end of the labour market and thus find it difficu lt to afford relatively high housing costs or 
even access the rental market. In particular, many young people face specific challenges  in 
finding adequate housing. With the youth unemplo yment rate being on average in the EU 
more than double that of the overall populati on, a disproportionate number of young people 
face challenges when establishing their family and set up their own households. There are also higher numbers of young people on a temporary contract or in part-time employment 
compared to the rest of the population
65, which impacts a person's possibility to own or rent a 
home. 
The second group consists of migrant and mobile workers  who find themselv es in precarious 
employment, on low incomes and often without a supportive social network. Several Member 
States have found this group to be growing in the population affected by HHE, including 
vulnerable migrants, refused asylum seekers,  illegal immigrants, economic migrants and 
ethnic minorities, especially the Roma (CZ, IE, CY, MT, PL, PT, and the UK)66. 
5.4.2. Measures to tackle homelessness 
The causes of HHE are being tackle d with two sets of measures: 
– Support for individuals , where social policy instruments su ch as social assistance benefits 
and quality social services play a key role 
                                                 
64 On the complexities of multiple deprivation, see the PROGRESS funded mutual learning project 
"CONNECTIONS – social inclusion at city level" ( http://www.connectionsprogress.eu/home ) and in 
particular the Vienna and Oslo peer reviews.  
65 See the EU Youth Report 2009, pp 34-35 
(http://ec.europa.eu/youth/news/doc/new_strategy/youth_report_final.pdf ). See also the PROGRESS 
funded mutual learning project "European cities against child poverty" 
(http://www.againstchildpoverty.com/index.php ) and the FP7 CSEYHP project: "Combating Social 
Exclusion among Young Homeless Populations " (http://www.movisie.nl/118836/eng/ ). 
66 On the issue of housing and migration, see the results of the mutual learning project "Building inclusion 
– access to housing and inclus ion in Europe" supported by the PROGRESS programme 
(http://buildinginclusion.oberaxe.es/en/home/index ).  
 
EN 73   EN Despite the weight of housing costs in total di sposable income, especi ally for the population 
at risk of poverty, expenditure on housing-related benefits  remains very limited in most 
Member States: only in DE, DK, FR and the UK does it exceed 0.5  % of GDP. In countries 
such as BG, EE67, IT, LT, PT and SI, expenditure on housing-related benefits is almost 
insignificant relative to GDP. Housing-related be nefits have remained almost unchanged since 
the beginning of the decade, with the only excep tions being a fairly significant reduction in 
EL and a marked increase in DE and SK. 
Fig. 5.5: Social protection expenditure as % of  GDP: housing function (cash benefits) 
0,00,20,40,60,81,01,21,41,6
EU BGEEITLTPTSIATBECZLVPLESLUMTFIIENLCYELHUSESKDEDKFRUK2000
2006
 
Source: EUROSTAT; ESSPROS  
Homeless people often face multiple disadvantage s. There is a growing emphasis in several 
Member States on developing integrated appr oaches to homelessness which go beyond just 
issues of accommodation and look at access to  employment, income support and access to 
services such as health and social services  — in other words, approaches that adopt an active 
inclusion  approach68. In several countries, however, there appears to be a complete absence of 
any integrated approach. 
Likewise, several Member States emphasise that the homeless can benefit from social services 
such as employment, health, care, and social assistance services on the same basis as other 
vulnerable groups. However, this is often not su fficient, as several obstacles may in practice 
impede actual access. Also, in a significant minority of Member States homeless people 
appear to have very limited access to such services.  
                                                 
67 In Estonia, housing costs are taken into account  in the calculation of the subsistence benefit. 
68 See the Commission Recommendation on active inclus ion [2008/867/EC] published in the Official 
Journal of 18.11.2008 (L. 307/11).  
 
EN 74   EN Improving the supply of adequate and afford able housing, in particular social and 
public housing  
Social and public housing69 emerges as a key element in HHE strategies and is often the 
most important solution for homelessness, especially for persons and families who can manage their housing situation with normal econo mic and social support. A very widespread 
problem is that there is excess demand for pub lic housing and relative ly long waiting lists. 
Tenant purchasing polices have reduced the ex isting stock of housing in some cases (UK), 
while deregulation and priority for private housi ng have been factors in  other cases. Several 
Member States are increasing the volume of housing with a specific focus on social housing 
(IE, BE, UK, FI, FR, IT, MT, EE), although this does not always meet demand. In some countries, private housing has been prioritised and the construction of social and/or public 
housing has been decreasing. The deregulation of  the housing market has also reduced the 
supply in some countries. 
The quality  of housing stock varies widely across th e EU. Inadequate housing standards are 
an issue for a significant number of Member States, especially for several of the newer 
Member States where the housing stock was in great part built during the communist period. Several countries have introduced policies to  set standards and improve the quality of 
housing. These include offering financial incentives and support  to property owners to 
provide high-quality accommodation, such as  financial bonuses, adva ntageous loans or 
advances for modernisation and renovation and tax deductions. Regulation and the setting of 
minimum standards  is another approach used to ensure the quality of housing. Measures used 
by Member States to improve the stock of  permanent accommodation include: increased 
monitoring and regulation of the privately rented sector; settin g minimum standard 
requirements for the quality of housing (e.g. sa fety, health, usefulness, energy saving); and 
setting minimum space standards.  Some countries have introdu ced regulations to define 
overcrowding or inadequate housing at  national, regional and local levels in legal and 
regulatory frameworks (UK, IT, RO, LU, FI).  However, in some countries with highly 
devolved systems, the setting and enforcement of  standards varies from region to region (DE, 
ES). There is also a growing emphasis in se veral Member States (e.g. IE, IT, LU, PT, RO, 
UK) on improving the regulation and oversight  of temporary accommodation and related 
services with a view to increasing standards.  
The Commission proposal that housing interventi on to help marginalised communities should 
be eligible for ERDF support can open the way fo r the structural funds to make an important 
contribution towards such objectives  in the convergence regions. 
There are efforts in a number of Member States to develop or extend instruments to improve 
the affordability  of housing. These in clude: housing benefit / means-tested housing 
allowances (BE, DE, FI, LU, PL, UK, IE); rent  allowance guarantees (NL); and regulations 
governing rents (AT, BE and IE), mortgage ta x reliefs (BE), and the sale of houses under 
market value (NL). 
Housing and urban rege neration programmes , together with pla nning instruments, can 
directly improve the living standards of local communities and help people to access adequate housing. Urban regeneration progra mmes are a common feature in many cities across the EU, 
                                                
 
69 See also the website of CECODHAS, the Eu ropean Liaison Committee for Social Housing 
(http://www.cecodhas.org/ ). 
 
EN 75   EN and focus investment on areas with  a high concentration of socially vulnerable groups in order 
to improve the quality of housing, tackle social  problems and ensure lower rents in local 
areas70. In a context of increased so cial diversification and relo cation of economic  activities, 
these polices are particularly important for in creasing the functional an d social mix of EU 
cities. There are several interesting examples of countries where policies to increase the social 
mix to avoid developing high concentrations of disadvantaged residents are part of 
mainstream planning and housing policy (DK, DE , FI, LU and the UK). As well as other 
specific areas, some programmes focus on the social excluded communities, such as the 
Roma. 
5.5. Monitoring and evaluation 
The need to develop or improve ways of collecting statistical data to improve the 
understanding of homelessness and housing exclusi on in the various Member States is widely 
recognised. The lack of data is at least partly responsible for the lack of a consistent and 
robust information and evaluation strategy  in most Member States. The Peer Review on 
"Counting the homeless – improving the basis fo r planning assistance" that took place in 
Vienna, Austria in November 2009 concluded that the EU must reinforce cooperation in this 
field and encourage political will in Member St ates to enhance data collection and develop 
corresponding monitoring systems71.  
The 2011 Census represents a unique opportunity to  produce invaluable base line figures in the 
field of homelessness. At EU level, steps fo rward in the measurement of homelessness and 
housing exclusion have been achieved with th e adoption by Member States of the common 
indicators on housing costs and overcrowdin g presented in section 5.2 and with the 
PROGRESS supported project MPHASIS72.  
Some Member States report the absence, at all administrative levels, of  statistical data on 
homelessness and housing exclusion (BG, CY, EL and SI). In thes e countries, such gaps are 
filled to some extent by the work of NGOs or other players (e.g. the Council of  Europe in 
BG). Censuses carried out every decade or so also  play a role in this respect, which is all the 
more important in the absence of any other syst ematic and scientific data collection process. 
The absence of any monitoring of homelessness also means that any policies in place to 
address the issue are impossible to assess using agreed, quantified and measurable standards. 
In Germany, some individual Länder have been  collecting data on homelessness, sometimes 
for many decades, but this has not resulted in any global overview, and there are no nationwide statistics on the issue. 
In a few other Member States, there is no syst ematic monitoring or evaluation, and the overall 
understanding of the issue is sk etchy (AT, CZ, IT, RO, SK). NGOs  have also carried out more 
or less coordinated research on monitoring and ev aluation in an attempt to fill the current 
knowledge gaps. 
                                                
 
70 On HHE in cities and urban regeneration, see also the website of EUROCITIES, the network of major 
European cities ( http://www.eurocities.eu/main.php ) and in particular the 'Inclusive Cities' programme 
supported by PROGRESS. 
71 See the Peer Review programme website: http://www.peer-review-social-inclusion.eu/peer-reviews . 
72 For detailed results of MPHASIS ("Mutual Progress on Homelessness Through Advancing and 
Strengthening Information Systems") see: http://www.trp.dundee.ac.uk/research/mphasis/index.html . 
 
EN 76   EN Some projects have also been launched in a nu mber of Member States to establish formal 
monitoring of the situati on of the homeless, and thus a coun trywide database, but are still at 
the preliminary or teething stage (EE, MT, PT). 
In BE, the situation varies depending on the region, but the federal authorities are making 
efforts to improve statistical knowledge at count rywide level, backed by a federal department, 
set up in 1998, to fight poverty. Data  collection is still incomplete, but is being assisted by the 
work of agencies such as Strada in Brusse ls. In Flanders, the CAW is obliged to submit 
registration data on homeless people to the administration every year. 
In Sweden, there is no regular reporting syst em for monitoring homelessness, but national 
surveys are carried out approximately every five  years. Some government agencies have been 
tasked with developing statisti cs, and to improve knowledge of di fferent methods to facilitate 
access by homeless people to the regular housing market. 
However, the most common pattern is a multi-level or multi-party system for documenting 
the situation of homeless people, for example in  Hungary, Ireland, Lithuania, the Netherlands, 
Poland, Spain, Finland and the UK. The role played by social services is not negligible in this 
respect, as they tend to be the ul timate source of data on homelessness. 
The nature and operation of these multi-level or multi-party documentation systems varies 
among the Member States. In Hungary, for instan ce, there is a network of regional bureaus 
that collect data daily on the available capacities of  the institutions concerned. However, no 
countrywide up-to-date data are available on the topic, though e fforts are being made to put 
this information into one comprehensive database. 
In Finland, the Housing Finance and Development Centre is responsible at national level for 
gathering monitoring data on homelessness.  Quantitative trends in homelessness are 
monitored and assessed annually by means of a que stionnaire that is sent out to every local 
authority in the country. 
Ireland’s new homeless strategy has set specific performance indicators for each of its six 
strategic aims, in an attempt to improve data  availability and comparability. In the UK, 
national reporting is based on returns from  local authorities under the homelessness 
legislation. The information on statutory homelessn ess is collated by central government in all 
four jurisdictions. 
 
EN 77   EN 6. E FFECTIVENESS AND EFFICIENCY IN THE HEALTH SECTOR : SOME CONSIDERATIONS 
AT A TIME OF ECONOMIC CRISIS  
The current economic and financial crisis makes more evident and urgent the need to improve 
the effectiveness and efficiency of health ca re. The crisis may impact the health sector 
negatively on both the demand a nd supply sides. The demand for health and long-term care 
may increase as a result  of a deterioration in health de terminants (e.g. higher unemployment, 
reduced income) and thus health status. On the supply side, the economic crisis may lead to a 
reduction in the funding available for health and long-term care as  a result of rising deficits 
and lower contributions and tax revenues. Member  States are in very different positions to 
face these challenges: there are large differences  in health outcomes and health expenditure 
across the EU, with in general those countries reporting lower expenditure on health and especially lower public expenditu re on health also reporting lo wer health status (e.g. lower 
life expectancy).  
The crisis places budget constraints on all countr ies, which will be particularly felt in those 
where the health sector is already under-resour ced, social protection is least developed and 
households are poorer. In previous short and small recessions, and so far in the current 
downturn, expenditure on health ha s worked as an automatic stabiliser and a recovery tool in 
many countries, though not all. If, as forecast, this economic cris is is to continue for some 
time, and given the large government deficits ob served, the near future will bring a period of 
budgetary constraints. This may translate into  stronger prioritisation and even budget cuts 
across the public sector, incl uding the health sector.  
In addition, large socio-economic gaps in heal th (translating into premature and avoidable 
mortality and disease), which persist despite the large increases in expenditure, and which 
may increase as a result of the economic cris is, call for greater effectiveness in healthcare 
delivery.  
Thus, increasing the effectiveness and efficiency  of health care will likely be common goals 
in the years to come. In searching for policie s to achieve these goals, Member States can 
benefit from pooling their know ledge and exchanging their ex periences and information. 
Indeed, the effectiveness and effi ciency of health spending is a long-standing concern in many 
Member States. Spending on healthcare and the provision of services absorbs a large share of 
total resources in the economy, in particular public expenditure. Health -related expenditure is 
the second biggest component of social  protection expenditu re in public budgets. 
Furthermore, the ratio of total health expenditu re to gross domestic pr oduct has increased over 
time and continues to grow. Data show a r ecent slowdown in expenditure growth, but 
pressures on health spending are likely to cont inue given the emerging challenges of ageing, 
technology development and growing expectations. 
A rising share of resources devoted to healthca re systems, together with a more equitable 
distribution of these resources, i. e. more widely available, affordable, higher-quality health 
care, has been associated with a considerable improvement in the health status of the EU 
population in recent decades (increasing like lihood of detecting and treating diseases, 
avoiding mortality, ensuring independent living and reducing health inequalities between and 
within Member States). Good health contribut es to economic prosperi ty through improving 
 
EN 78   EN labour market participation and productivity and increasing participatio n in other societal 
activities. High levels of popul ation health and an increa se in Healthy Life Years73 are crucial 
in the context of an ageing population, to allo w for longer working lives and secure higher 
employment, productivity and competitiveness. Nonetheless, increasing health-related 
expenditure and strong expenditure  pressures have also given ri se to general apprehension, 
increased efficiency concerns, and calls for im proving the value for money of funds allocated 
to the health sector. 
This chapter is based on previous Joint Reports  on social protection and social inclusion and 
on EU level Ageing-related and EU level health y ageing and health workforce related work, 
as well as work by the OECD  (including the 2008 Joint EC/O ECD conference on improving 
health systems efficiency) and the WHO. It al so draws on recent CZ presidency conferences 
on this topic and the 2007 LU seminar on the rati onal use of resources in the health sector. 
6.1. Why more effectiveness and effici ency in health care is needed 
6.1.1. Health expenditure analysed74 
In general, total expenditure on health represents a significant share of EU Member 
States’ financial resources  (Figure 6.1), as measured by GDP, although it varies across EU 
Member States from 5  % in EE to 11  % in FR. BE, DE and AT also spend more than 10  % of 
GDP on health, with PT (9.9) and DK (9.8) follo wing suit. At the other extreme, RO, LT, CY, 
PL, and LV spend less than 6.5  % of GDP. On average (populat ion-weighted), EU Member 
States spend about 9  % of GDP on health, including both publ ic and private expenditure (with 
the EU-15 population-weighted average reaching 9.5  % of GDP). A large part of this 
expenditure is from public  sources (EU average of 75  %): more than 60  % in all Member 
States, except for CY (43  % in 2005), more than 70  % in 19 Member States and more than 
80 % in 6 Member States, including LU with 90  % (Figure 6.1). Total expenditure on health 
per capita is also sizeable, though it varies across Member States, from around less than  500 
Purchasing Power Standard (PPS) unit in RO to  more than 4000 PPS in LU (Figure A1 in the 
Annex). 
Time series data (Figure 2) show that over the past decade total expenditure on health has 
increased by about 1 pp of GDP in the EU-27 (population-weighted average). The same 
trend (increasing share of health  expenditure as % of GDP) has b een seen in the vast majority 
of individual Member States since 1980 (Figure A2 in the Annex) and, for those countries for 
which data are available, over the past 50 y ears (Table A1 in the Annex). Also, total 
expenditure on health per capita (PPP) has c onsistently increased over time (Figure 3). 
                                                 
73 http://ec.europa.eu/health/ph_information/indicators/lifeyears_en.htm   
74 The figures based on time series of health expenditu re used here should be considered with caution, 
since there have been methodological breaks in the computation of the relevant underlying data at 
certain points of time, notably the introduction of  the System of Health Accounts (SHA) in many 
countries. 
 
EN 79   EN Figure 6.1 
Total expenditure on health as % of GDP (breakdown between 
private and public expenditure).  2007 or latest available
0,02,04,06,08,010,012,0
EU27*BEBGCZDKDEEEIEELESFRITCYLVLTLUHUMTNLATPLPTROSKSIFISEUKHealth expenditure as %  of 
GDP 
0%10%20%30%40%50%60%70%80%90%100%
Public expenditure %  of 
total expenditure on healt h
Private expenditure as %of GDP
Public expenditure % GDP
Public expenditure as % of total expenditure on health  
Source: OECD Health data and WHO Health for All databases, EU-27* standing for the population-weighted 
average of the latest values available: BG, EE, CY, LV , LT, MT, RO and SI for 2005 and PT and LU for 2006, 
others for 2007 — EC computations. 
Time series data (Figure 6.2) show that over the past decade total expenditure on health 
has increased by about 1 pp of GDP in the EU-27 (population-weighted average). The 
same trend (increasing share of health expenditu re as % of GDP) has been seen in the vast 
majority of individual Member States since 1980 (Figure A2 in the Annex) and, for those 
countries for which data are ava ilable, over the past 50 years (T able A1 in the Annex). Also, 
total expenditure on health per capita (PPP) has consistently increased over time (Figure 6.3). 
Figure 6.2 and 6.3 
Total expenditure on health as a % of GDP, 1970-2007
0,02,04,06,08,010,012,0
1970
19751980
1985
19901991199219931994
1995
1996
1997
199819992000
2001
20022003200420052006
2007EU15 pop weighted average EU27 pop weighted average 
Source: Eurostat, OECD Health data, WHO Health for All databases and EC computations. 
 
EN 80   EN Figure 6.3 
Total expenditure on health per capita PPS, 1970-2007
050010001500200025003000
1970
19751980
1985
19901991
1992
1993
1994
1995
1996
19971998
1999
20002001
2002
20032004
2005
20062007per capita PPS 
EU15 pop weighted average EU27 pop weighted average 
Source: Eurostat, OECD Health data and EC computations. 
The data in Figure 6.2 suggest, however, different  periods of health expenditure growth. The 
fastest health expenditure growth (compared to GDP growth) was observed — on average for 
the EU-15 — up to the early 90s. Health expend iture still grew faster than GDP throughout 
the 1990s and early 2000s, but has remained a roughl y constant share of GDP in recent years.  
The reason for these results, looking at the ti me series available for individual countries 
(Figures A3 in the Anne x), is that the growth rates for tota l health expenditure are in general 
higher than GDP growth rates for most countries  and years. They are significantly higher the 
further back in time one goes. Total expenditu re on health increased fast in the 1960s and 
1970s (annual growth rates higher than 15  %). Then from the 1990s onwards, growth rates in 
the EU-15 countries decreased to become more similar to GDP growth rates, though still 
higher. In the new Member States for whic h longer time series are available, some 
convergence between GDP growth and health expend iture growth is observe d in recent years, 
after very high health expend iture growth during the 1990s and in the early 2000s. A look at 
the last 10 years of data shows that while total expenditure on health is in general higher in 
2008 than in 1998 (Figure 6.4 and Figures A3 in the Annex), health ex penditure growth and 
GDP growth have been converging during recent years, with some countries even showing a 
reduction in total expenditure on heal th as a percentage of GDP.  
Figures A3 also provide intere sting information on what can ha ppen to health expenditure and 
its growth in periods of economic downtur n. Looking at SE and FI for example, the 
downturns in the early 2000s saw health expend iture growth increase and peak compared to 
the general trend of decreasing expenditure gr owth, while the economic crisis of the early 
1990s resulted in negative health expenditure gr owth rates in line with the negative GDP 
growth rates. In times of economic crisis, th erefore, health spending has reacted in opposing 
ways: either following the downward trend in the whole economy or working counter-
cyclically75. 
                                                 
75 The Research Note ‘ Recession and health in Europe: what to expect?’  (European Observatory on the 
Social Situation and Demography) finds that economic downturns in the 27 EU countries from 1970 to 
 
EN 81   EN Figure 6.4 
Total expenditure on health as % of GDP, 1997-2007
3,04,05,06,07,08,09,010,011,012,0
BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL A T PL PT RO SI SK FI SE UK
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 
Source: OECD Health data and WHO Health for All databases 
Given that public expenditure is the main driver of total health expenditure, public 
expenditure on health as a percentage of GDP has followed a similar overall pattern  to 
that of total health expenditure as a percenta ge of GDP (Figure 5 compared to Figure 2, and 
Figures A4 and A5 and Table A2 in the A nnex). Over the last four decades, public 
expenditure on health as a percentage of GDP appears to have increased fast until the early 1990s, increased less fast throughout the 1990s, and remained more or less constant in more 
recent years. 
Looking at the evolution of public expenditure as a percentage of total expenditure on health 
in individual Member States (Figures A6 in th e Annex), it can be seen that in some countries 
(DK, FR, LU, AT) the share of public expenditure has been fair ly constant over the last two 
decades, while in others it has increased (PT,  IE) or conversely fallen initially before 
increasing again in the past decade. In all, public expenditure accounts for a significant 
share of total expenditure on health (75
 % on average for the EU) . It thus competes with 
other areas (e.g. education) for public  resources, which al so explains the emphasis on 
improving effectiveness and effi ciency in the health sector . 
                                                                                                                                                         
2007 had no significant effect on healthcare spending (in per capita terms and as a percentage of GDP), 
based on a variety of indicators for recession (including fluctuations in GDP and unemployment and 
taking account of time lags). 
 
EN 82   EN Figure 6.5 
Public expenditure on health as a % of GDP, 1970-2007
0,01,02,03,04,05,06,07,08,0
1970
1975
1980
1985
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
EU15 pop weighted average EU27 pop weighted average 
Source: OECD Health data and WHO Health for All databases and EC computations 
Importantly, there is considerable evidence76 that higher total health  expenditure per capita 
leads to lower mortality, lower infant mortality and higher life expectancy, as shown in simple 
form by Figure 6. Furthermore, Figure A7 in the Annex also shows that countries with 
different levels of health expenditure (in per capita terms or as a pe rcentage of GDP) have 
similar outcomes and that countries with simila r expenditure levels have different outcomes, 
at least in terms of  life expectancy.  
Figure 6.6 
Life expectancy at birth vs total ex penditure on health per capita PPS, 
2007 or latest value
BE
BGCZDKDE
EEIEELES FRIT
CY
LVLTLU
HUMTNLAT
PLPT
ROSI
SKFISE
UK BE
BGCZDKDE
EEIEELES FRIT
CY
LVLTLU
HUMTNLAT
PLPT
ROSI
SKFISE
UK
70.072.074.076.078.080.082.0
0 1000 2000 3000 4000 5000Total expenditure on health per capita PPSLife expectancy at birthR2 = 0,6308
 
Source: Eurostat, OECD Health data and EC computations 
                                                 
76 For a short review, see the Joint Report on Social Protection and So cial Inclusion 2007. 
 
EN 83   EN It may be noted that countries with lower life ex pectancy at birth and lo wer health expenditure 
(as a percentage of GDP or per capita) are also those with highe r inequities in access to care 
and health status.77 Hence, some countries may be investing too little in this sector. While 
they may have to spend more on he alth, it is as important for them  to ensure that what is spent 
and any additional amounts spent make an effect ive and efficient contribution to health .  
In sum , the consistent increase in total expenditure on health, the fact that a significant part of 
that expenditure is public, and indications that there may be scope for improvement give rise 
to some uneasiness about the size and growth  of health expenditure and thus prompt calls for 
health systems to obtain good value for money (through greater effectiveness and 
efficiency) . 
6.1.2. Pressures on healthcare spending 
Levels of spending depend on a combination of f actors: a) factors aff ecting demand for care, 
such as general health status of the popula tion and thus the need for care, population age 
structure and income levels, plus organisationa l (e.g. cost-sharing) and cultural (e.g. self-care) 
factors, and b) supply-side fact ors such as the availability a nd distribution of services, the 
physician/nurse mix, cultural, organisational and institutional factors including wages and 
remuneration methods, gate-keepin g, market regulation, diffusi on of high-cost technology, or 
administrative costs. These are summarised in Figure 6.7.  
Figure 6.7 
 
Source: 2007 AHEAD — Ageing, health status and determinants of health expenditure project 
In this context, it is worth describing in more detail some important challenges to the 
system that emphasise the need to look more closely at the ef fectiveness and efficiency of 
resources allocated to health .  
One of these challenges is population ageing . This translates into more people living longer 
(Figure 8 and Figures A8 and A9 in the Anne x), notably a higher proportion of people aged 
65+ and especially those aged 80+. Betw een 2008 and 2060 the EU-27 population aged 65 
and over is projected to in crease from less than 20  % to about 30  % of the population, and the 
‘very old’ (80+) will be the fastest growing segment of the population. Ageing can bring with 
                                                 
77 Impact assessment accompanying the Communica tion ‘Solidarity in Health: Reducing health 
inequalities in the EU’ SEC(2009) 1396. Population Health 
size, age-structure Use of insurance
Life health Health Prices, schemesexpectancy Morbidity/ care expenditure costs
Acut services Supply/health status access
Medical/ Socio-economic General framework
technological determinants/ conditionsprogress healthy behavior/ (policies, rules,
genetic conditions assets, economy)
 
EN 84   EN it new patterns of morbidity including multi-morbidity  (multiple chronic diseases, disability 
and dependency) presenting themse lves over a long period of time . Evidence shows that the 
need and demand for health care is strongly a nd positively correlated with age: health 
deteriorates with age (Figure 9) and correspondingly, expenditure  profiles increase with age 
(Figure A10 in the Annex). This means that there will be higher pressure to provide more and 
substantially different care  than with a younger population st ructure. Moreover, while the 
demand for formal auxiliary medical and support care is likely to increase as a result of 
ageing, the number of informal carers (family and relatives) may fall as a result of changing 
family structures, mobility, and work patterns. Consequently, as expenditure rises with old age, if age-disease patterns remain unchanged, expenditure levels will increase. According to 
the 2009 EPC/EC projections, EU public health  expenditure will increase by 1.7 percentage 
points of GDP by 2060 due to population ageing, i.e. a 25
 % increase with respect to current 
spending (Table 1).  
However, research (e.g. 2009 EPC/EC Ageing Report, 2007 AHE AD) shows that the impact 
of ageing on expenditure can be mitigated by improving the health status of the elderly. 
Hence, a healthier ageing population is cruci al to control expenditure growth . Indeed, the 
age-related projections estimate that the impact  of demographic change (costs increasing by 
1.7 % of GDP) is more than halved if people live longer but the onset of disease is also later. 
Moreover, age-utilisation relationships are aff ected by the cultural and institutional factors of 
each country, helping explaining the gaps in pe r capita spending at older ages between EU 
Member States. 
Figure 6.8. Projected changes in population st ructure in % for selected years, EU27 
0%10%20%30%40%50%60%70%80%90%100%
2010 2020 2030 2040 2050 20600-14 15-64 65-79 80+
 
Source: Eurostat, EUROPOP2008 (EUROstat POpulation Projections 2008-based) convergence scenario; 2009 
EPC/EC Ageing report 
 
EN 85   EN Figure 6.9. Health status by age, 2007 
Self-reported general health, limitations in daily activities, and long-
standing illness in the EU, by age group
010203040506070
15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+% of respondents in each age groupBad Severily limitedLong-standing illness
Very bad
 
Source: Eurostat  
A related challenge is to ensure the availability of a health workforce  able to respond to 
future needs. Thus, ageing can have other nega tive implications, such as reducing the supply 
of staff  and increasing staff wages, thus resultin g in higher production costs. Across Europe, 
between 1995 and 2000, the number of physicia ns under the age of 45 dropped by 20  %, while 
the number aged 45 and over went up by over 50  % (European Commission Green Paper on 
the health workforce78). For nurses, average ages are rising: in five Member States nearly half 
the nurses are aged 45 and over. It is predicte d that the retirement of the baby boomers will 
affect the health sector by reducing staff numbers at such a rate that there will be insufficient numbers of younger people coming into the system to replace them. The health sector, a labour-intensive sector, currently provides employment for about 10
 % of the EU workforce, 
and approximately 70  % of healthcare budgets is spent on salaries and other charges related 
directly to employment (Green Paper). As current staff appro ach retirement age, sufficient 
new and younger recruits are needed to replace them. In addition to staff ageing, health-related jobs may not be attractiv e to new generations, and severa l countries are faced with the 
migration of their health profe ssionals to richer countries. As increased numbers of staff may 
take time to materialise, in view of the dur ation of medical and other training, we need to 
ensure an effective and efficient workforce in the meantime
79.  
                                                 
78 See http://ec.europa.eu/health/ph_systems/docs/workforce_gp_en.pdf . 
79 The development of robust human resource strategi es to improve recruitment and retention will be one 
of the most important issues for em ployers in the health and care sect ors. Such strategies could range 
from raising awareness of careers among school and university leavers, running return-to-practice 
campaigns with support for updating of skills and opportunities to work flexibly, and introducing 
schemes to attract and retain older workers or those needing to change careers after redundancy. 
 
EN 86   EN Table 6.1 The projected costs of ageing: pure demography scenario 
 
Source: 2009 EPC/EC, Ageing Report 
In addition to potentially incr easing demand, ageing reduces the relative size of the working 
population (Figure 10) and thus  poses a challenge to govern ments to ensure sufficient 
revenues for the health sector from  shrinking tax bases/contributions.  
Figure 6.10. Labour force projections, 2007-2060, percentage change in population aged 
15-64 
 
Source: EPC/EC 2009 Ageing Report 
 
EN 87   EN Another pressure on healthca re expenditure comes from technological development80. While 
this can bring about less intrusive and cheaper tr eatments (day case instead of in-patient 
surgery), it contributes to rais ing expenditure by providing ways  to cure or control hitherto 
untreatable diseases through new and often expe nsive interventions, albeit also often less 
intrusive and with fewer side-effects. Thus , technology creates a supply-induced demand for 
services (diagnosis, prevention and treatment). In addition, health staff need to be trained to 
use it. The 2009 EPC/EC age-related projections  (2009 EPC/EC Ageing Report) suggest that 
between 2  % and 3  % of yearly growth in  healthcare spending can  be ascribed to non-
demographic and non-income factors such as technology. Nevertheless, the potential for ICT 
technology and process innovation to improve acce ss, quality and coordination of care, as 
well as cost predictability and control should be  kept in mind. There is growing evidence of 
this potential81 and even if field implementation seem s to be lagging behind expectations and 
potential, this area should be given adequate attention in the future.  
In what relates to health prof essionals, ICT have the potential to reliably free the doctors and 
nurses from most of the administrative burde n, saving their valuab le time for health-
enhancing activities, something es pecially important in the present and coming times of health 
personnel shortages (as mentioned above). 
Part of the progress in medical technology is the development of new pharmaceuticals. 
Member States point to a significan t growth in pharmaceutical expenditure  and the diffusion 
of new medicines as one of the financial pressures they face. There is evidence (2008 
EC/OECD conference) that, although pharmaceu tical expenditure accounts on average for a 
relatively minor share of national spending on h ealth (less than a fifth of total health 
expenditure), it increased faster than tota l health expenditure and GDP between 1980 and 
2005. Also, the public sector is the primary source of financing (60  % of total pharmaceutical 
expenditure on average in the OECD), a lthough private expenditure is greater for 
pharmaceuticals than for other types of care.  On average, pharmaceutical expenditure 
constitutes a growing share of total health expenditure (Figure 11). However, there are 
important differences across Member States: some  show a constant share over recent decades 
while others, notably the Nord ic countries and a number of new Member States, show a 
growing share. There are also wide differe nces in pharmaceutical expenditure per capita 
(Figure A11 in the Annex) between Member St ates. These reflect different practices in 
relation to market regulation, pricing, reimbursement, coverage , distribution, prescribing and 
dispensing of pharmaceuticals, thus constituti ng a suitable area for information and best 
practice exchange. 
                                                 
80 Technology here stands for more than just equipment or ICT as it includes pharmaceuticals and other 
types of medical interventions. 
81 http://www.oecd.org/document/42/0,3343,en_2649_33929_38311850_1_1_1_1,00.html  
 
EN 88   EN Figure 6.11. Pharmaceutical expenditure as  % of total expenditure on health 
051015202530354045
1970
1972 1974
1976 1978 1980 1982 1984 1986 1988 1990
1992
1994
1996
1998
2000 2002 2004 2006
AT DK EE FI EL HU RO SI SE EU average * 
051015202530354045
19701972
19741976 1978
19801982
19841986 19881990 19921994199619982000 200220042006
LU MT NL PL PT SK ES UK BE CZ DE
IE FR IT 
Source: WHO Health for All database 
Growing expectations , broadly related to education, income , family structures and/or access 
to information, also play an important role in increasing demand for and supply of care. In 
general, countries with a higher GDP per capita tend to spend more on health (Figure 12). The 
2009 EPC/EC Ageing Report projects significantly higher public health spending (additional 
0.6 percentage points of GDP) once income  elasticity of dema nd exceeds unity (1.1 
converging to 1 by the end of the projection peri od). The desire for greater choice of provider 
and care setting, tailor-mad e treatment, access to a new and wi der range of technologies, and 
the enforcement of patient rights are some of the pressures policy-makers have to balance 
against existing resources. Indeed, while people  want more and modern care and free choice 
as patients, often as contributors they wish to pay lower taxes, contribu tions or user charges. 
As for public health and patient empowerment , ICT allows web 2.0 tools to harness the 
potential of social marketing and networks for public health, health promotion and lifestyle 
changes. 
In addition, there are emerging risks to health  from risk behaviour / unh ealthy life-styles that 
can lead to a higher incidence and prevalence of chronic diseases. Lack of exercise, unhealthy 
diet, obesity (see Figure A12 in the Annex), excessive drinking and high rates of smoking, 
notably in young age groups, are a ssociated with a higher in cidence and prevalence of 
cardiovascular and respiratory di seases, diabetes, etc. In a ddition, there continue to be 
 
EN 89   EN significant outbreaks of communicable diseases su ch as TB, and the prevalence of HIV/AIDS 
is of strong concern. These result in an unn ecessary burden of disease on societies and on 
health budgets.  
Figure 6.12 
Total expenditure on health per capita vs GDP per capita, 2007 or latest year available
BE
BGCZDKDE
EEIE
EL
ESFR
IT
CY
LVLTLU
HUNLAT
PLPT
ROSISKFISEUK
050010001500200025003000350040004500
0 10000 20000 30000 40000 50000 60000 70000 80000
GDP per capita PPSTotal expenditure on health per capita PPSR2=0,8853
 
Source: Eurostat, OECD Health data and EC computations  
Large and widening health inequalitie s between and within Member states (e.g. a 14-year 
gap in life expectancy at birth for men and an  8-year gap for women between Member States 
and differences of 10 years for men and 6 years for women in life expect ancy at birth between 
the lowest and highest socio-economic groups) indi cate that not everyone has benefited in the 
same way from the increase in health expenditu re and the greater availability of medical care 
as well as the economic progres s that delivers better health through more and better jobs and 
better living conditions. Barriers to accessing care (including health promotion, disease 
prevention, treatment and rehabilitation) have been identified, including lack of health 
insurance, direct financial costs of care, ge ographical disparities in provision, waiting times, 
lack of information, discrimination, language ba rriers, health literacy and socio-cultural 
expectations in relation to life and care use. Premature and av oidable mortality and morbidity 
are an economic burden to society as they are detrimental to employment, productivity and 
growth. Avoidable ill-health places an economic burden on health care systems and 
unnecessary pressure on public budgets. Re ducing unnecessary and premature death and 
disease can make a contribution to meeting the Lisbon goals of employment and growth and achieving Europe’s full potential for prosperity. Hence, such large gaps in health call for 
greater effectiveness of healthcare delivery, pub lic health prevention and a rethinking of 
priorities in this sector . 
 
EN 90   EN 6.1.3. The current economic and social situation 
The current downturn will impact on the demand for health care and on available resources. 
Hence it is crucial to understand where potential effectiveness and efficiency gains can be made and where greater value for money ma y be attained in the health sector.  
6.1.3.1. Potential effects of the economic crisis on health status 
Research shows that higher public expenditure on health is related to lower mortality 
(Brenner, 2009; figures above), so significant reductions in spending on life-saving 
interventions will increase mortality. However, data relating change s in mortality to periods 
of economic recession are scarce and somewhat c ontradictory. Some perhaps counterintuitive 
findings come from the US and Europe, wher e recession has been accompanied by falling all-
causes mortality rates, although an increase in suicide rates is genera lly observed (Brenner, 
2007). Those findings have been observed for recen t, relatively short periods of recession and 
may be unlikely in a more sustained and deeper  downturn. Moreover, mortality is an extreme 
event and often depends on a complex matrix of determinants acting over a long time. It would perhaps be more intuitive to look at morb idity, and especially mental ill health, when 
searching for the health consequences of an ec onomic crisis. In additi on, while rapid and deep 
social and economic changes will have conseq uences for the health of the population, the 
extent and distribution of these consequences are likely to vary depending on the development 
and coverage of social safety nets, the resilienc e and robustness of the health sector, as well as 
policy responses in the fields of so cial security and health care.  
For example, in the early 1990s, FI experienced a severe economic recession, during which 
the unemployment rate increased from 3.4
 % in 1990 to 18.4  % in 1994 and long-term 
unemployment rose to 27  %. However, life expectancy at bi rth for men (Figure 13) remained 
stable or improved slightly among the adult popul ation while infant mort ality declined from 
6.3 deaths per 1  000 live births in 1986 to 4 in 1994. This  may be explained by the fact that a 
developed welfare system comprising wide soci al safety nets and a health care system 
offering universal coverage provided comprehens ive protection. Nevertheless, the crisis did 
have a health impact especially in terms of mental health, with an increase in sleeping and 
anxiety problems (see e.g. Figure A13 in the Annex for SE). 
Several new Member States experienced a cris is in the early-1990s or mid-1990s during the 
transition to democracy and to a market ec onomy: high unemployment  and inflation and a 
drop in GDP were observed, albeit to different ex tents. It can be observed that the rise in 
unemployment and the drop in GDP during that tr ansition period could be associated with 
increased mortality and reduced life expectancy, in  particular for men. For some countries life 
expectancy did not increase duri ng transition, while for others it actually decreased and has 
taken some time to return to pre-transition levels.  
 
EN 91   EN Figures 6.13. Life expectancy at birth for men, 1985-2007, for FI and SE and for those 
countries that have undergone the economic and political transition from a planned to a 
market economy 
646668707274767880
19851987 19891991 1993
19951997
19992001200320052007FI 
SE 
 
606264666870727476
1985 1987
1989 1991
1993 1995
1997
19992001
2003
2005 2007BG 
CZ 
EE 
LV 
LT 
HU 
PL 
RO 
SK 
 
Source: Eurostat 
Fluctuations in the unemployment rate  are more closely associated  with short-term changes 
in health than any other economic indi cator. A study has shown that every 1  % rise in 
unemployment rates is associated with a 0.79  % rise in suicides of those aged 65 and less and 
a 0.79  % rise in homicides (Stuckler, D. et al., 2009). A study of th e correlation between 
unemployment  and mortality  in Britain during the recession period in the 1970s and 1980s 
showed that the unemployed had a mortality rate 20  %-25  % higher than the average for their 
respective socioeconomic group (Marmot, 2009).  
The unemployment rate is also found to be a si gnificant risk factor for morbidity. In addition 
to increasing alcohol or substa nce abuse and malnutrition, unempl oyment (and the associated 
lower income and financial distress) is also  found to be an important risk factor in 
cardiovascular disease and mental health  (distress, depression, anxiety, psychosomatic 
symptoms, etc.). Moreover, the negative effect  of unemployment on mental health is stronger 
in countries with a weak level of social pr otection and unequal income distributions. Not only 
unemployment is detrimental to health. Even job insecurity  has a negative impact on health 
(Bilbao Agency, 2007). A meta analysis (Sverk e et al., 2002) has revealed a significant 
negative correlation between j ob insecurity and poorer mental  health. The relationship has 
been confirmed by longitudinal st udies (Ferrie et al., 2003) showing that j ob insecurity should 
be treated as a cause of worsening mental health. 
 
EN 92   EN 6.1.3.2. Potential effects of the economic crisis on the healthcare sector 
Reductions in public expenditure  on health may also affect the composition of health  
spending . Where governments report cuts, they suggest that salaries will be maintained, but 
that savings will be made in infrastructure and equipment. However, some governments may 
choose to increase the health and social prot ection budget, as has actually happened in 
previous instances of recession. As a result, health spending  in some of the countries affected 
by economic downturns has fallen, while in other countries it has been maintained or even 
increased. 
Private expenditure on health ca re may fall as a result of th e drop in household disposable 
income. In contrast to public spending, private out-of-pocket expenditure  usually tends to 
decline in a recession, particularly  if services are available at lower cost in the public sector. 
The reduction in household income caused by cu rrency devaluation, inflation, unemployment, 
wage reduction or other factors can affect the ability of families to pay for health care. Recourse to cost-sharing and out-of-pocket pa yments for health care may be avoided or 
reduced by turning to government-subsidised and not-for-profit health care providers in times 
of crisis. As a result of the lower demand for private care and the consequent transfer of 
demand to the public sector the overall quality of care may dec line, if public se rvices are not 
adequately equipped to cope. This problem w ill affect all countries  where publicly funded 
services are under pressure.  
Some governments choose to increase cost-s haring. Decreasing public health spending, 
increased costs of treatment, and reduced family income and/or insurance coverage will affect 
the use of health services . For patients, price increases (in th e form of official user charges 
and co-payments, payment for medicines or informal payments) may deter less well-off 
patients from seeking the necessary care as it becomes unaffordable. However, it may be possible to control the rise in th e costs of care for patients through  generic substitution  or 
public subsidies. 
Where recession is accompanied by inflati on and devaluation of  domestic currencies , the 
prices of imported  medicines, raw materials and medical equipment can increase.  
In sum: EU health systems have to balance increasing demands on services, and the need to 
respond to people’s health needs, with restricted  or even diminishing financial resources. The 
fact that similar health expenditure levels may be associated with different outcomes has 
raised some political discussion on whether there could be eff ectiveness and efficiency gains 
to be made within the sector and in addressi ng the social determinants of health. Different 
financing and organisational ar rangements may be more or less able to control such 
expenditure pressures (2007 Join t Report; OECD 2005). Differences  in expenditure  levels and 
price structures raise questions in relation to  financing and delivery  structures and policy 
priorities (e.g. health promotion, disease prev ention and rehabilitation versus treatment). The 
search for ways to raise effectivenes s and efficiency is therefore ongoing.  
 
EN 93   EN 6.2. Improving effectiveness and efficiency in the health se ctor: a look at a number 
of areas  
The last decade has seen increasing debate on ways to improve health system performance 
and value for money and thus enhance longer- term sustainability. The following sections 
review some possible strategies to improve effectiveness and effi ciency and what they entail.  
6.2.1. Encouraging the use of primary care  
Encouraging the use of primary care instead of direct use of sp ecialist care while 
strengthening referral systems from primary to ot her types of care is one of the health policy 
reforms that are being implemented or planned by EU Member States to improve resource use in this sector. This is done by enforcing a comp ulsory referral system with a gate-keeping role 
for primary care physicians and vi a financial incentives (i.e. hi gher reimbursement if a patient 
follows a referral system from pr imary to other types of care). 
In the last decade, policy makers in many Me mber States have changed the way they see 
primary care. While some Member States had a primary care-led system with patients first 
visiting a primary care physician who would then  refer the patient to specialist services 
(referral and gate-keeping role), in many othe rs free choice and direct access to specialists, 
with a strong emphasis on curative hospital-based care, were part of normal service delivery. 
Primary care remained peripheral, sometimes seen  as a synonym for lower-quality care with 
patients failing to register or  visit a primary care physician a nd using specialist and hospital 
care directly through overuse or unnecessary us e of emergency departments. In more recent 
times, the growing focus on addressing observed h ealthcare delivery deficiencies (improving 
access and quality) and improving value for mone y in the health sector (efficiency) has 
shifted attention to primary ca re and its potential role in achieving these improvements (2008 
WHO World Health Report; 2007 PROGRESS workshop on ‘Policy options for promoting 
rational resource use in th e areas of health care and long-term care’).  
Primary care is to be the first point of access to the health system under normal circumstances. 
The primary care physician (also called ‘general practitioner’ or ‘family doctor’) examines the 
patient and decides whether he/she should then visit a specialist. Str onger primary care aims 
to avoid patients organising or having to organi se their care path thr ough the system, leading 
to disparities in access, lack of coordination and continuity of care (quality), duplication of 
procedures and use of unnecessary and more e xpensive diagnostic and curative hospital care, 
resulting in health and financia l costs for both the patient and the system. A focus on primary 
care will also improve access to health promoti on and disease prevention to avoid or postpone 
the onset of disease and ensure its early diagnos is, thus bringing about sa vings in the sector.  
 
EN 94   EN Figure 6.14. General practitioners per 100  000 inhabitants  
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
BE 168.9 170.8 173.7 175.1 177.2 176.2 176.4 175.9 173.3 170.3 170.9
BG 67.5 68.6 69.1 67.8 66.8
CZ 48.3 48.3 49.0 51.2 (b) 52.5 52.2 51.4 51.3 51.2
DK 61.5 63.5 64.1 71.9 72.1 72.2 71.5 75.3 74.6 74.4
DE 109.6 108.0 106.4 106.6 106.2 105.1 104.2 102.4 97.4 99.2
EE 56.3 64.5 80.8 88.2 85.4 92.7 95.5 100.2 99.8 105.3
IE 62.2 68.3 69.9
EL 27.8 27.9 29.8 27.7 26.5 28.5 31.9 33.9 35.5
ES
FR 161.6 161.3 159.6 161.1 162.0 162.8 163.8 164.5 164.6 164.1
CY 37.4
LV 16.0 20.2 33.4 40.6 41.0 43.8 45.0 52.9 54.7 55.7 54.7
LT 7.5 8.3 15.6 21.3 27.9 36.0 43.0 48.2 50.5 52.6
LU 71.2 72.5 73.9 74.3 77.2 75.2 74.7 76.6
HU 65.3 66.1 65.9 66.0 66.0 66.1 66.1 65.6 65.4 65.2
MT 77.7
NL 44.7 45.0 45.5 45.5 45.5 45.6 45.6 46.1 46.4
AT 131.0 134.4 132.8 134.6 137.4 139.9 141.1 143.3 146.0 150.5 153.3
PL 11.9 13.3 14.3 15.2
PT 43.0 43.4 43.7 44.2 44.5 44.7 44.9 45.6
RO 65.8 80.9
SI 16.7 20.3 19.8 19.7 19.4 19.0 19.2 26.7 26.2 26.0
SK 8.5 36.5 41.5 43.2 44.0 43.6 43.2 43.2 36.9 36.3
FI 33.2 34.5 36.3 37.7 38.7 39.7 40.6
SE 49.8 51.4 52.0 52.8 54.6 56.0 57.0 57.7 58.9 60.2
England 71.1 71.8 72.5 74.8 76.9 79.0  
Source: Eurostat 
However, reforms to improve health system effi ciency (as well as accessibility and quality of 
care) through greater use of pr imary care imply a change in it s scope, its delivery and its 
financing. While greater use of primary care is indeed a more efficient option for care 
delivery because it ensures more adequate care, avoids unnecessary care (as primary care doctors compared to patients acting alone have  more and better information on the type of 
care needed following a referral) and postpones the need for care, this entails a wider range of 
tasks for primary care physicians and nurses,  including health promotion and disease 
prevention activities. Reforms are also encourag ing group rather than individual practices, and 
sometimes a common budget, so that primary car e centres act as purchasers of other types of 
care for their patients. Primary care providers will also act as the care guide or coordinator for 
their patients.  
Expanding the scale and scope of primary care a ppears to bring satisfaction to both patients 
and primary care providers. For patients, the expa nsion of primary care services, especially if 
this translates into a better geographic distri bution of services, may mean easier access to a 
wider range of services provided in a more pers onal and continuous basis over a lifetime, with 
more time given to the patient. For primary care physicians, a wider range of responsibilities 
and tasks renders primary care mo re interesting and rewarding. 
For primary care to improve value for money in the system, one nevertheless has to look at 
the number of primary care physicians available (Figure 14), the set of services included in 
primary care and the financial in centives for primary care provide rs, much like in other parts 
of the health sector, so that these factors do not run counter to  referral and gate -keeping goals.  
6.2.2. Care coordination 
Care coordination can be defined as policies that help ensure care is more coherent both 
within and across care settings and over time. It is about making health care systems more 
 
EN 95   EN attentive to the needs of indi vidual patients and ensuring they get access to appropriate care 
but at less cost (EC/OECD conf erence, 2008). By ensuring a co herent care path , coordination 
can be of great importance to the most disa dvantaged groups, who often lack continuous 
follow-up in terms of preventive or early care a nd end up relying on late  or emergency care 
instead. Care coordination is particularly pertin ent in the context of ageing and the attendant 
multi-morbidity and chronic diseases, which resu lt in greater use of many different types of 
both medical and support care at the same time. Ca re coordination is thus about ensuring that 
patients access care that is appropr iate and of a high quality (i.e . safe, effective and responsive 
to the needs and preferences of patients), and is provided in the most cost-efficient or cost-
effective manner (effectiveness, efficiency and thus sustainability).  
Currently, independent care sett ings and budgets, specialisation of medical knowledge, lack 
of communication and mutual pr ofessional esteem, and even ri valry between professionals 
have led to fragmentation of care (between pr imary and secondary or tertiary care, between 
medical and support/social care). Patients may not always receive  the care they  should, when 
they should, or where it is best provided. Furt her, there can be high le vels of medical error. 
Belated care, often in emergency departments,  as well as overuse or unnecessary care, 
duplication of procedures, and conflicting medical recommendations represent a double 
burden for patients (negative impact on their hea lth status and their income) and the system 
(e.g. increased costs/expenditure). Good coordina tion of care can reduce the need for hospital 
stays, the unnecessary use of emergency care and the duplica tion of procedures (in particular 
expensive and invasive di agnostic procedures).  
Primary care providers are often seen as best placed to be the guide or coordinator, although 
at present referral systems from primary to other types of care do not function perfectly: 
patients do not register with or visit family doctors, who lose tr ack of patients once they move 
to hospital or institutional settings due to la ck of referral back to the family doctor.  
Policies conducive to coordinati on include: a) improved use of IC T as a key tool to link the 
healthcare "silos" and allow information to foll ow the patient, including electronic health 
records or software that follows the patient’s path through several episodes of care; b) reconfiguring provider structures, in particular to include more elements of multi-disciplinarity (multi-disciplinary teams in care practices); c) incentives to care providers (e.g. elements of remuneration explicitly linked to care coordination) and skills development in chronic disease management, communicati on with patients a nd networking; d) 
implementation of targeted disease programmes;  and e) addressing ad ministrative barriers 
(e.g. through pooling resources from health and so cial sectors and addre ssing lack of mutual 
esteem and recognition between different me dical professions). Communication across the 
various parts of the health sector is fundament al to avoid fragmenta tion and rivalry between 
medical professions and types of care.  
6.2.3. Reforming in-patient care and enhancing outpatient care 
Health policy reforms to improve value for money in the health system also encompass 
reforms in the specialist and hospital care area s. These often call for changes in medical 
knowledge and medical technology to enable, for example, less invasive medical (diagnostic, 
surgical) interventions. This can in turn shorte n stays in in-patient care or render them 
unnecessary through the use of day case surgery, thus allowing for more intensive use of 
existing beds and staff. More use of day cas e surgery is an appealing solution to reduce 
 
EN 96   EN overall costs in the health sect or by cutting hospital costs (which often make up a large part of 
total expenditure in the sector ), and many countries have been  encouraging it. Looking at 
Figure 15, a wide variation acro ss EU countries in terms of hospital activity, measured by 
hospital inpatient average length of stay (A LOS), can be observed. In addition to data 
comparability issues, variations can be due to  various factors associated with quality and 
financial considerations. They include pati ent registration practices as hospital cases, 
historical medical practices, abse nce of clinical guidelines, lack  of referral back to primary 
care, lack of alternative follow- up care at home, lack of long-te rm care at home or community 
so that long-term care patients are treated in hospital, but also disincentives to reduce in-
patient care and length of stay, such as overc apacity or remuneration/budgetary systems that 
make in-patient procedures more financially  attractive to provid ers. In addition, the 
implementation of day case surgery and a general reduction of ALOS should be accompanied by monitoring mechanisms to follow up its impact including adverse effects on health 
outcomes. 
Figure 6.15. Average length of in-patient st ay (in days), all causes excluding births 
2000 2001 2002 2003 2004 2005 2006 2007 2008
BE 7.7 7.5 7.4 7.7 7.6 7.5 7.4 7.3
BG 8.3 7.5 7.2
CZ 10.3 10.2 10.2 10.9 10.7 10.6
DK 6.3 6.2 6.1 5.9 5.4 5.3
DE 10.1 9.8 9.7 10.2 10.2
EE
IE 6.4 6.4 6.4 6.4 6.4 6.5 6.3 6.2
ES 8.8 7.7 7.7 7.7 7.2 7.1 7.0
FR 6.0 6.0 6.1 6.0 5.9 5.9 5.8 5.8
IT 7.6 7.6 7.6 7.7
CY 6.4 6.5 6.4 6.0 6.3 6.0 5.9 6.2
LV 9.6 8.8
LT 1 0 . 61 0 . 31 0 . 01 0 . 11 0 . 11 0 . 0 9 . 9
LU 7.5 7.4 7.5 7.2 7.3 7.3 7.4 7.3
HU 8.1 8.0 7.9 7.9
MT 5 . 45 . 4 4 . 84 . 9
NL 8.0 7.6 7.2 6.9 6.7 6.4
AT 10.0 9.5 9.0 8.9 9.0
PL 7.2 6.8 8.4 8.1 8.0
PT 6.7
RO 7.8
SI 7.9 7.9 7.7 7.7
SK 9.9 9.5 9.0 8.8 8.7 8.4 8.3
FI 12.9 12.7 12.5 12.5 12.7
SE 6.8 6.7 6.7 6.5 6.4 6.4 6.4
UK 10.8 10.6 10.0 9.3 8.7 8.8 8.1 
Source: Eurostat. Please note that caution is needed in in terpreting the table results as it includes all causes 
(including psychiatric care) rather than just acute care, fact that can increase the fi gures for ALOS. In addition, 
there are differences across countries in  the way they report on ALOS for different types / functions of care 
considered. 
Measures to increase efficiency also include the division and concentr ation of tasks between 
hospitals in a defined health re gion. The idea is to concentrate certain types of services in 
fewer hospitals to improve capacity use, while  often also improving the quality of those 
services. For certain services, concentration ma y go as far as having a very few centres of 
excellence serving the entire population. Divisi on and concentration of tasks does require 
good coordination and communication structures  between primary and secondary care and 
between the various hospitals. 
 
EN 97   EN 6.2.4. Pharmaceuticals  
Spending on pharmaceuticals has risen rapidly in  the last two decades. Pharmaceutical 
expenditure accounts  for about 1.5  % of GDP, and although a relatively minor share of 
spending by OECD countries on health — on average less than a fifth of total health 
expenditure — the share has been increasing over  the past 20 years, at an average rate of 
5.7 % per year, faster than other types of hea lth care, in GDP terms as well (2008 EC/OECD 
conference). The public sector is the primar y source of financing for pharmaceuticals, 
accounting on average for 60  % of total pharmaceutical expenditu re in OECD countries, while 
another large part comes directly from households . Moreover, there are also large differences 
in pharmaceutical expenditure per capita (Fig ure A10 in the Annex), which may reflect 
different practices in market regulation, pr icing, reimbursement, coverage, distribution, 
prescribing and dispensing of pharmaceuticals, and different objectives (affordable access, 
cost-containment, encouraging of industr y production and R&D). Hence the growing 
concerns expressed.  
In this sector, a trade-off is often identified between: a) obtaining greater value for money 
given a limited public budget; and b) promoti ng future innovation (lo ng-run perspective), 
which involves high costs for the developmen t of new drugs. Innovation creates new care 
opportunities, some of which may replace old, more invasive a nd expensive practices in the 
long run but will require considerable funding in the short run, which will have to come from 
the sale of current branded and patented drugs. Therefore, policy makers need to identify policies that can induce savings in the short run without hindering innovation.  
Countries have been using pri ce regulation to set maximum pri ces for patented drugs and/or 
reference pricing (the maximum price reimbur sed by public insurance for non-patented drugs, 
typically an average of the prices of drugs in each ther apeutic group with perhaps a certain 
percentage margin below that average). The patie nt then pays the difference in price. Price 
regulation can induce the desired patient be haviour and control expenditure, but some 
drawbacks need to be taken into account. Indeed , producers can use the re ference price for all 
drugs or slightly adjust the de finitions of drugs to obtain a hi gher price premium. Price limits 
are also based on a set of other factors, including the importance and leverage of the 
pharmaceutical sector in the country. Price regulation based on external benchmarking 
(looking at the price of a same  drug in other countries with similar economic and geographic 
characteristics) can induce manuf acturers to launch products first in countries with no 
regulation at the entry point in order to se t the industry price as an example. As a 
consequence, such measures should be coupled with other policies. 
One way to increase the cost-efficiency of pharmaceuticals is to encourage generic 
substitution. A number of Member  States have been doing this for some time, but for others 
there is a large scope for improvement. The use of generics can be encouraged through 
prescribing guidelines (defining positive or negative lists of publicly reimbursed drugs, 
encouraging doctors to prescribe by active element and pharmacists to sell the cheapest 
medicine that matches the prescription) and through user charges (hi gher reimbursement for 
generic drugs). Prescribing guide lines and financial incentives can  be used to influence the 
demand for pharmaceuticals overall. They can be coupled with information campaigns. 
Another policy is to see if there are opportunitie s for efficiency gains in the distribution chain 
(looking at existing practices in reimbursi ng pharmacies, the number and location of 
 
EN 98   EN pharmacies, the number of pharmacists, opening hour s, etc.) and see if these encourage higher 
prices and higher sales.  
Yet another is to use economic evaluation a nd thus information on the relative cost-
effectiveness and cost-utility of products in the definition of prices and reimbursement 
schemes (and cost-sharing) for pharmaceutical s, while ensuring that the rewards for 
innovation are consistent with the value of th e benefits offered. Economic evaluation is not 
commonly used for health policy decisions in many countries, and there is large room for 
improvement. 
In addition, governments can seek to establish price-volume agreements or even confidential 
rebates when value-based prices cannot be esta blished, as pharmaceutical firms may be more 
willing to negotiate an overall budget for a larg e set of medicines than to negotiate the unit 
price of each medicine. They can also explore th e possibility for risk sharing in the case of 
new medicines, to reduce the financial risk presented by new medicines when information on 
their cost and their expected e ffect on health outcomes is insufficient. This can involve the 
pharmaceutical company and the purchaser authority agreeing on the expected benefits of the drug, with the company then paying part of the h ealth service costs if the drug fails to fulfil 
expectations. Such agreements can allow new, expensive drugs to be covered. 
Some countries (UK and ES) are experimenting with profit re gulation to control the amount 
of profit drug companies may keep on their sales to  the National Health Service so as to keep 
the public costs of purchasing drugs  down to a reasonable level.  
6.2.5. Greater use of Information and Communi cation Technologies (ICTs) / e-Health
82 
solutions but also more econom ic assessment of technology 
Technological development can bring about le ss intrusive and cheape r treatments, thus 
facilitating the above changes in the primary and secondary care sectors (e.g. greater use of 
day case surgery). In addition, the lack of communication among different care providers and 
between providers and patients has been identi fied as an obstacle to healthcare access and 
associated with quality deficits. The resulti ng lack of care coordination translates into 
additional financial costs.  
Both better information and better systems for information transfer are needed to improve 
health monitoring, access to health care and the quality and sustainability of health systems. 
eHealth can also allow for additional access points to health information and to the health system (health portals; online health services, e.g.: NHS direct ), providing more information 
to patients. This support to health literacy can encourage health promotion and lifestyle 
changes, as well as patient empowerment. 
Currently, health systems are not sufficien tly employing ICTs or are doing so without 
sufficient concern for interoperability, thus fragmenting health information flows. This 
reduces the ability to sy stematically record and report inputs,  processes, outputs and outcomes 
as well as the ability to develop and use evidence-based guidelines.  
                                                
 
82 e-Health  is the generic name given to a group of powerful ICT-based tools used for the benefit of 
patients and/or health systems. 
 
EN 99   EN ICT and e-Health solutions ha ve the potential to improve th e collection and storage of 
multiple sources of data (electronic records, registries, and administrative data) and the linkages between them as well as enhance info rmation exchange, while abiding with data 
protection and privacy law.  
eHealth can allow for better care coordination by allowing for information to seamlessly 
follow the patient as s/he navigates through the health system. This can directly improve patient safety (for instance, by alerting to possible medicine interactions or avoiding 
unnecessary and harmful procedures ) while also helping to cont rol costs. E-prescribing can 
support compliance with protocols, avoid inte raction between drugs or confusion between 
patients, dosages or times of application, and support generic prescrip tion (and thus control 
costs). ICT and e-Health can also help fight against counterfeiting and mislabelling. They can 
also be key instruments to reduce the administ rative burden on staff and to free the valuable 
time of health professionals fo r core care activities, something of great importance in a 
context of workforce shortages. 
Introducing such system-wide information systems is complex (e.g. cultural barriers, 
resistance to change the legal and reimburseme nt frameworks, etc) and can be expensive in 
the short term, even if the expected gains may outweigh the costs. It requires commitment by 
all stakeholders and staff involvement and a longer-term, system-wide approach. It requires 
training and incentives for staff to use the syst ems implemented. In general, the objectives are 
to promote a coordinated and deeper engagement  in e-Health and to promote mainstreaming, 
acceptance and take-up by involving health prof essionals and patients in national e-Health 
strategies and deployment in a way that reduces  inequality, not adds to it. Moreover, given 
greater patient mobility, the aim is to promote th e (cross-border) interope rability of e-Health 
systems. 
6.2.6. Health Technology Assessment 
Technological development can increase expend iture by creating new treatment opportunities. 
The issue of the health system’s financial ability to pay for these new treatments versus patients’ high expectations of benefiting from ne w technology at an afford able price has led to 
calls for greater use of economic assessm ent and evaluation of technology (Health 
Technology Assessment — HTA
83), including a cost-effective and cost-utility analysis to 
decide if a certain care inte rvention or drug should be incl uded in the publicly funded or 
reimbursed basket of care and to what extent, notably in comparison to other interventions or 
drugs.  
There is growing pressure from stakeholders requesting evidence that public money is spent 
wisely for the benefit of patie nts, the public purse,  service providers and innovators. HTA is 
thus being more and more debated but there is  a wide variation acro ss EU countries and the 
tool is still not commonly used  by policy makers. HTA is in fact a daunting exercise. There 
are different approaches to the definition of costs, outcomes and thresholds. Hence, it may 
                                                 
83 According to EUnetHTA (European network for Health Technology Assessment), 2003, HTA is a 
multidisciplinary process that summ arises information about the medi cal, social, economic and ethical 
issues related to the use of a health technology in a systematic, transparen t, unbiased, and robust 
manner. It therefore helps to inform the formulation of safe, effective health policies that are patient-
focused and seek to achieve best value. 
 
EN 100   EN yield different results that ma y not be totally generalisable  or transferable. It is a 
multidisciplinary field and requires skilled scie ntists and the creation of committees. In 
addition, there may be societal and ethical issues involved. Build ing on a number of previous 
actions and projects, the Comm ission and Member States are currently working on a joint 
initiative aimed at increasing cooperation, shar ing information and developing the same core 
methods in the area of HTA. 
6.2.7. Incentives for users and providers 
6.2.7.1. Financial incentives for patients: user charges 
From the point of view of system efficiency and financial sustainabili ty, user charges have 
two roles: 1) to raise revenues for the sector and 2) send signals to pa tients to combat moral 
hazard (overuse or unnecessary use of care because  it is free at the point of use). Most EU 
countries rely heavily on public funding, so user  charges play only a sm all part in financing 
the system. Moreover, in countries that rely more on user charges, many citizens take out 
complementary insurance to cover those charges (actually rendering citizens less sensitive to charges and their role in counter acting moral hazard). In most cas es the revenue is not large, 
and in some cases is outweighed by the collectio n costs. Hence, user charges have not been 
very successful in raising additional financi ng, and mostly function to encourage the better 
use of services as in 2), al though their impact is limited wh en complementary insurance is 
available. 
Charges have been accompanied by intense po litical discussion because of the potential 
negative impact on the solidarity and equity of the system, i.e.  in reducing care use among 
those who need it, especially the more vulnera ble and less well-off. Consequently, a practice 
of small charges combined with a number of pa yment exemptions (based on age, income and 
chronic disease) has developed. Existing eviden ce does indeed suggest that charging can and 
does reduce utilisation
84. While this may not have major heal th consequences for most of the 
population, it has important negative consequences for the health of th ose with low incomes 
and poor health (who need hea lth services more often). He nce, if not properly designed, 
charges can have financial and health conseq uences for some groups of the population and 
thus contribute to the socio-econom ic health inequa lities observed. 
Therefore, the role of user charges needs to  be carefully rethought. They may be unavoidable 
for financing the system given the already high expenditure and the growing demand and 
expenditure pressures discussed previously. However, if they are to play their two roles 
effectively it is crucial to design them so as to minimise the negative  impact on access to care 
for the most vulnerable while ma ximising efficiency gains.  
One suggestion is that authorities should defi ne a minimum care package of a sufficiently 
high quality so that all citizens are willing to cont ribute to its financing, thus ensuring broad, 
publicly funded provision. This package will be fully cove red by public financing and 
determined, where possible, using cost-effectiv eness criteria. Building on this initial high-
quality package, charges (co-payments, co-insur ance and deductibles) will be introduced to an 
increasing extent to encourag e appropriate behaviour  (e.g. generics ra ther than branded 
products, primary care rather than direct visits to specialists and hosp itals, preventive rather 
                                                 
84 "Achieving better value for mone y in health care", OECD 2009.  
 
EN 101   EN than curative care). Some charges should not be covered by complementary insurance to 
ensure that they encourage desi rable behaviour. At the same tim e a system of exemptions for 
the poor or chronically ill needs to be  in place to avoid under-use of care. 
6.2.7.2. Non-financial incentives for user s: patient choice and involvement 
Recent years have also seen an increased emphasis on patient 
empowerment/involvement/choice and satisfaction. When introduc ing choice, one needs to 
think about its design (at which stage, how c hoice is allowed) and its  objective. Patients’ 
ability to choose providers can l ead to increased patient satisfac tion, and fits in with the goal 
of improved well-being and the noti on that the health sector works for the patient. However, it 
may result in overall increased expenditure with  no general clinical improvements. If properly 
designed, choice at certain stages  in the care delivery process may encourage the development 
of alternative providers  and thus contribute to enhancing efficiency. Some countries where 
provider choice was typically rest ricted have introduced some degree of choice in various 
stages of the process:  choice of the primary care physician,  albeit with some geographic and 
time limitations, or choice of hospital follo wing referral by a primary care physician.  
Choice is nevertheless constrained by the leve l of information patients possess about their 
rights and the quality of care offered, and is thus often influenced by age and social 
background. It is also dependent on the nu mber of alternative providers. Proximity 
considerations also weigh heavily in the decision to search for care elsewhere.  
6.2.7.3. Remuneration of physicians and hospitals and benchmarking 
Labour unit costs vary across count ries in part due to different  remuneration systems. Such 
systems include fee-for-service (income equal to the number of services provided times the 
price of each service), capitati on (income based on the number of patients enrolled with each 
physician, often risk-adjusted to the types of patients enrolled)  and salary (fixed income 
independent of the number of patients and serv ices provided). Each sy stem provides different 
incentives for physicians. A fee-for-service syst em may be associated with supply-induced 
demand and the lack of care coordination, esp ecially if associated  with free choice of 
physician. Capitation or salary systems may, in contrast, result in under-use of services and 
longer waiting times. As a result, several Memb er States are now implementing a combination 
of systems, with, for example in the context of  primary care, a capitation system plus fee-for-
service for health promotion a nd disease prevention services. In others, the fee-for-service 
system is regulated and a lis t of standard tariffs is published by the authorities. 
Many countries have introduced an element of activity-based or case-based remuneration in 
the payment structure of hospital services. These are usually based on diagnosis-related 
groups (DRGs), a way of categorising patients  according to diagnosis and intensity of 
resources required and thus an at tempt to establish a comparable structure of hospi tal costs. In 
addition, there is greater use of prospectiv e budgeting for hospitals (payments fixed in 
advance of the provision of serv ices), often based on potential patient case-mix and a set of 
healthcare need criteria.  Some countries use gl obal prospective budgets. 
Some Member States are supplementing the above mechanisms with the measurement of 
hospital efficiency, hospita l benchmarking and ranking (measuring performance of 
organisations according to specified standards and comparing them using the results) on the 
 
EN 102   EN basis of efficiency and other criteria as a means to induce each hospital to evaluate its 
practices and search for improvements.  
Evidence suggests that changes in hospital budgeting and hospital perfor mance measurement 
and benchmarking have induced changes in hospital care deliv ery to achieve cost savings. 
The overall results appear  to be positive, especially if th e changes are well-communicated to 
providers, if they encourage learning from other providers, and if  approached from a 
rewarding rather than a punishing perspective.  Nevertheless, there are also reports of 
miscoding of patients under more costly DRGs to  obtain greater hospital  revenue or rejecting 
costly patients. Efficiency gains from performance measurement and benchmarking may also not have been as high as expected, while in some cases hospitals may have focused on those 
dimensions of care that are being measured to  the detriment of other important dimensions. 
Moreover, performance measurement and benchmar king have to be adju sted for patient case-
mix and need criteria as well as the availability and quality of equipment (old vs new hospitals).  
Some non-EU countries also use or are planning to use user charges for drug companies to 
raise revenue and pay for the tec hnology assessment of their new drugs. 
6.2.7.4. Non-financial incentives for physicians: training and motivation 
The development of robust human resource stra tegies to improve recruitment and retention 
will be one of the most important issues for polic y makers in the health sector. Such strategies 
could range from raising awareness of career s among school and univers ity leavers, running 
return-to-practice campaigns with support for updating of skills and providing opportunities to 
work flexibly, and schemes to attract and retr ain older workers or those needing to change 
careers after redundancy. 
6.2.7.5. Competition 
The healthcare market is one where several market imperfections are observed. There are 
information asymmetries between patients and providers and between in surers/purchasers and 
providers about health status and the care need ed and provided, allowing for principal-agent 
problems to develop and raising issues of supply-induced demand. There are other 
information gaps, such as patients being cost -unaware as to how ca re is financed and 
delivered, thus raising issues  of possible excess demand a nd consumption. There are also 
practical and regulatory c onstraints on the entry and exit of providers such as restrictions on 
access to training for staff, economies of scale and scope in the provisi on of many services, 
and the fact that, from society’s point of vi ew, providers and purchas ers cannot just fail and 
vanish from the market leavi ng a gap in the provisi on of needed, life-saving services. In 
addition, health-related educati on and training have the charac teristics of public goods and 
there is substantial R&D in the sector. Moreover , the objectives associ ated with healthcare 
provision are not necessarily those of efficiency  but also those of solidarity, universality, and 
equity of access and outcomes.  
In this context, competition in the healthca re market may imply higher costs than a non-
competitive market due to the need to regulate , monitor, audit and control (notably through 
competition and quality authorities) and the comple x mechanisms that need to be in place to 
obtain the required information to attain the ot her objectives associated with health care. 
 
EN 103   EN On the other hand, policy makers and resear chers in recent times have expressed their 
concerns that sole reliance on non-market mechanis ms may also be undesirable, as it can give 
rise to opportunistic behaviour and inefficiency. Hence, severa l countries are looking at the 
scope for promoting more rational use of resour ces by using market-type mechanisms such as 
increased competition, notably in certain sub-mark ets, or procedures to improve efficiency.  
Two types of competition are being explored. The first is competition between healthcare 
insurers,  i.e. competition to provide to each patient a set of services for a specific time period, 
a recent development in some social health insurance systems. What is observed in EU Member States, however, is not the extreme case of an unregulated market where patients pay 
a premium related to their risk  and preferred benef it package. What is found is enhanced 
competition between insurers in a regulated environment (e.g. NL, BE, DE) where insurance 
is mandatory, there is a community-rated premium that all insurers must offer for a minimum 
defined care package, insurers cannot refuse applications, and there is competition on extra 
benefits or side-benefits of the package and along some quality dimensions. There is a risk-adjustment mechanism among insurers, and someti mes regulations for high-risk patients, to 
avoid cream-skimming and ensure a level playing field. 
The second is competition between providers, or  competition for collect ive health services,
 a 
more common mechanism, whereby a purchaser concludes a block cont ract with a provider 
for the delivery of a set of specified se rvices. The separation between purchasers and 
providers in various national health systems in the EU is intended to create strategic 
purchasers who would choose between pr oviders to achieve cost reductions. 
Negotiation/bargaining and contracting have often been based on benchmarking. Research 
indicates that contracting has de legated responsibility in previous ly very hierarchical settings, 
allowing for the involvement of lower-level managers in decision- making. Contracting has 
also made providers more responsive to the priorities of purchaser s and national health 
strategies. It has induced changes in provision pa tterns (from in-patient to out-patient care and 
the adoption of cost-effective interventions) and cost reduc tions have been observed.  
In conclusion, there may be room for greater competition among insurers/purchasers and 
providers and greater use of market-type mechanis ms in sub-markets or for certain procedures 
that may encourage greater cost efficiency in  the health sector. However, one must not 
underestimate the regulatory ch allenge and the considerable costs of the administrative 
machinery needed to create and sustain compe tition in health markets while also ensuring 
coverage and quality of care. The extent of the information  needed is very large in terms of 
population structure and health st atus, to allow for risk-adjustment mechanisms, as well as in 
terms of care costs, prices, and market stru cture. Imprecise information and thus risk-
adjustment leads to cream-skimming of patients.  On the other hand, if many high-risk patients 
seek particular insurers and risk-adjustment is  not properly designed, then a race to the bottom 
ensues, i.e. insurers start offering a lower qua lity of care for thos e patients (e.g. care for 
chronic conditions). This then requires the definition and control of minimum standards. In addition, the efficiency gains may be smaller if  there is under-competi tion between insurers 
and patients are allowed to choose providers.  
The gains associated with greater competition between providers also depend on a number of 
factors: the nature and scope of  the services contracted, the c ontract process used, the duration 
of the contract, the population covered, and th e definition of price and quality criteria. In 
some sub-markets this competition may not be r ealistic if there are economies of scope and 
 
EN 104   EN scale and few providers. Moreover, if a purchaser wishes to ensure integrated care then it may 
wish to contract with a larger provider offeri ng a wider range of serv ices, therefore strongly 
limiting its choice. Contracting requires info rmation and data colle ction on many variables 
such as unit costs, prices, length of stay, etc.  Imperfect information ma y have negative effects 
on unmeasured dimensions of the care provided. Finally, the contract ty pe (global budgets vs. 
case-based DRG payments) provides di fferent incentives to providers.  
EU Member States differ in their institutional a nd market capacity and thus their ability to 
pursue such avenues. As some of these mechanisms have been introduced only recently in some countries, it is important to follow up the results achieved, in terms of efficiency gains, 
by those actively engage d in these policies.  
6.2.8. Encouraging effective health promotion and disease prevention 
As highlighted, if people are healthier for lo nger the pressure on expenditure and public 
expenditure in particular is lower. A range of health pr omotion and disease prevention 
activities (e.g. vaccination, screen ing for certain types of cancer) are considered effective and 
cost-effective in improving population health out comes by avoiding disease and mortality and 
through early diagnosis and treatme nt (often less costly) and t hus higher survival chances. 
However, expenditure on health promotion and di sease prevention is still a minor part of total 
health expenditure (Figure 6.16) . Nevertheless other policy areas may contain prevention 
measures that are not reflected  in health-related budgets. 
To enhance health promotion and disease prev ention, some countries have introduced direct 
personal financial incentives for people to pr event illness and promote their health. These 
include financial disincentives to smoke or dr ink alcohol (especially spirits) through high 
taxation of these products. Other mechanisms in clude age regulation for the sale of alcohol 
and smoking bans in public pl aces. These are often coupled with publicly reimbursed support 
schemes for quitting smoking. Some countries ar e considering higher taxes on soft drinks. 
Others prescribe physical exerci se as a treatment or give financial incentives to do so 
(vouchers). Financial in centives are also given to pregnant  women to eat a healthy diet and 
follow pre-natal care or for patients to comp ly with their medication. As mentioned above, 
some countries provide additi onal fee-for-service remuneration to physicians to perform 
health promotion and disease prevention activitie s. In addition, many national authorities have 
implemented projects to improve healthy eating a nd exercise in schools. More research is 
needed to understand the cost-effectiven ess of several of these schemes.  
Figure 6.16. Public expenditure on health prom otion and disease prevention as a share 
of total current expenditure on health
 
  2003 2004 2005 2006 
Belgium 1,34 1,72 3,62 3,53 
Bulgaria 3,5 3,6 2,84 3,13 
CzechRepublic 1,75 1,75 1,46 1,84 
Denmark 2,44 2,51 2,29 2,32 
Germany 2,84 2,86 2,86 2,95 
Estonia 2,16 1,51 1,83 1,94 
Ireland 2,5 : : : 
Greece : : : : 
Spain 2,2 2,21 2,21 2,25 
 
EN 105   EN France 1,45 1,41 1,47 1,58 
Italy 0,7 0,6 0,6 0,6 
Cyprus 0,5 0,44 0,46 0,51 
Latvia : : 0,24 : 
Lithuania : 1,78 1,74 1,26 
Luxembourg 0,72 0,75 1,09 : 
Hungary 3,32 2,97 2,89 2,76 
Malta : : : : 
Netherlands 2,73 2,43 2,37 2,54 
Austria 1,66 1,78 1,67 1,66 
Poland 3,24 1,54 1,78 1,79 
Portugal 1,3 1,22 1,18 1,16 
Romania 5,28 6,92 6,63 5,9 
Slovenia 2,86 2,94 2,83 2,8 
Slovakia 1,7 1,9 1,3 1,9 
Finland 3,05 3,11 3,29 3,24 
Sweden 2,46 2,4 1,56 2,66 
UnitedKingdom : : : : 
Source: OECD Health data and Eurostat 
6.3. Conclusions 
Health expenditure absorbs an important and growing share of GDP and the public share is 
sizeable. Pressures on health spending are likely to continue. Ageing, technology development and growing expectations, together  with large socio-economic inequalities in 
health and the current economic crisis (causing increased ill-health and budget deficits), call 
for greater value for money thr ough increased effectiveness and efficiency. This may imply 
restructuring of the way health care is organised a nd delivered. A number of paths have been 
suggested, including a restructuri ng of primary and secondary car e, greater care coordination, 
more intensive and interoperable use of ICT an d e-Health solutions, a proper assessment of 
current pharmaceutical policies, greater use of health technology assessm ent, a re-engineering 
of remuneration systems and financial incentives for both providers and users of care more generally, the development of non-financia l incentives, and the use of market-type 
mechanisms. The combination and design may be different across countries, and indeed some 
of the above measures may be more suitable  for some than for others depending on their 
institutional and market capacities.  
Efforts to improve effectiveness and effici ency should aim to promote health, prevent 
morbidity and ensure access for all to high-qua lity care that is sustainable. Short-term 
strategies must be well-linked to long-term st rategies. They should also  be linked to policies 
outside the health sector . Health and consequently the need for care are determined by a wide 
range of factors, including education, in come, working and living conditions, and the 
environment. Hence, attention to health in all policies can improve health and thus the 
sustainability of health systems.  
Despite these first clues to greater effectiv eness and efficiency, more information and 
assessment is needed regarding many of these tool s. Moreover, the list set out above is by no 
means exhaustive. In searching for policies to achieve these goals Member States can benefit 
from pooling knowledge and exchanging experiences and informa tion. In this context, there is 
a need to investigate the various aspects of th e functioning of national health systems. The 
 
EN 106   EN Commission will work with Member States to id entify areas where a potential for improving 
health performance exists and support the develo pment of national strate gies to reduce health 
inequalities. 
 
EN 107   EN 7. L ONG-TERM IMPLICATIONS OF THE CRISIS FOR THE SUSTAINABILITY AND 
ADEQUACY OF PENSIONS  
Over the last 15 years consecu tive waves of Member State reforms in response to the 
challenge of ageing have markedly altered pension systems and pe nsion scheme designs 
across the Union. For almost 10 of these years, the EU has sought to underpin this process by 
providing a framework for po licy learning with common obj ectives conducive to the 
planning, implementation and asse ssment of such reforms through the Lisbon process and the 
Social OMC. With the introduction of the euro, th e fiscal framework in the EU – the Stability 
and Growth Pact – has been st rengthened, including the need for pursuing structural reforms 
e.g. in the field of pensions that contribute to  long-term fiscal sustainability. As the first 
decade of Lisbon is coming to a close, it is time to take stock of the progress made. However, 
with the financial crisis and the economic dow nturn, Member States also have to revisit 
achievements and re-assess core responses in the light  of the short- an d longer-term impacts 
on the various elements in their pension systems.  
This chapter presents a first explorative analys is of the outcome of reforms, the immediate 
impacts of the crisis, and the longer-term implica tions of the crisis for pensions. As an initial 
mapping exercise, it aims to set out some of the main issues that will be subject to a more 
thorough examination in the joint work of th e Social Protection and the Economic Policy 
Committees in 2010.  
Key findings and messages can be summarised as follows :  
A first examination of cr isis impacts shows that while budgetary restricti ons have led to cuts 
in pension payments in a few countries (e.g. LV, LT, HU),  in most Member States current 
pensioners have so far been among those least affected by the crisis. But as schemes are changing, future pensioners will be more exposed. Importantly, crisis setbacks and the likelihood of lower growth have thrown the rapi dly approaching ageing ch allenge into sharper 
focus and put the adequacy/susta inability balance sought over a decade of reforms under new 
pressure.  
Strong trends in reforms towards a greater role for pre-funding a nd defined-contribution 
formulas will increase sensitivi ties to volatilities in financia l markets, including the present 
downturn. The wide variation in the losses a nd capacities of funded sc hemes to absorb the 
shock demonstrates that differences in design, re gulation and investment strategies matter. To 
achieve longer-term adequacy and sustainabilit y, lessons need to be learned and greater 
security for pension savers achieved. 
The closer links introduced between benef its and contributions in many public PAYG 
schemes likewise have made pension entitlements more sensitive to developments in labour markets and benefits will not only depend on the willingness to work but also be contingent 
on opportunities for more complete and longer work careers. 
 
EN 108   EN 7.1. Outcomes of pension reforms prior to the crisis 
7.1.1. The financial resilience of pension schemes and the adequacy of pensions 
In the joint European Commission (DG EC FIN) and Economic Policy Committee (Ageing 
Working Group) 2009 Ageing Report from the sp ring 2009 and the SPC report on Theoretical 
Replacement Rates adopted this summer, Member States provided some major assessments of their success in achieving sustainable and adequate pensions. From scenarios based on trajectories for present and coming reforms to pension systems and assumptions about 
continued growth and increasing employment rates,  it would seem that sustainability (in terms 
of the public budget impact of ageing-induced extra pension co sts) has markedly improved 
over the last decade. In fact, a challenge in some Member State systems in terms of pension policy (i.e. notwithstanding the need to eventual ly implement a fiscal exit strategy and reduce 
the high budget deficits currently  prevailing in a large majority of MS) would be to secure 
sufficient future adequacy. 
The compelling factor behind most pension reform s has been the need to ensure sustainable 
finances in pension systems in the long run as the population ages. Changes in the old-age dependency ratio would result in public pension expenditure in the EU-27 to increase from 
10.1% of GDP in 2007 to 18.8% in 2060. However, Member States have implemented 
reforms that address to a large extent this increase. As a result of these reforms and a 
projected increase in employment rates am ong the population aged 15-64 from 65.5% in 2007 
to 69.9% in 2060,
85 public pension expenditure is for ecast to reach only 12.5% of GDP in 
2060.86 
In response to the longevity chal lenge, we see that due to ma ny pension reforms, the relative 
level of annual pensions will decrease over th e next forty years, given a forty year career.87 
That said, in many cases policymakers have tight ened eligibility rules for full pensions and 
extended pensionable ages to en courage longer working lives as people live longer. There has 
also been a move toward grea ter pre-funding of pensions as a method for moving some of the 
payment burden forward to current working ge nerations, but also as a method of reaping 
eventual gains from growing financial market s, which traditional PAYG systems do not do.  
Pension policy responses by Member States to the ageing challenge have combined three 
broad types of reform measures: (1) encourag ing/enabling more people to work more and 
longer, (2) greater pre-funding of pensions, an d (3) decline in the accrual of annual pension 
rights, all else being equal. 
7.1.2. More people working more and longer 
The first policy response has three elements: more people working; people working more; and 
people working longer. Although all elements have  seen progress to varying degrees, the most 
                                                 
85 In the same time participation rates of older workers (55-64) are projected to increase from 47.5% in 
2007 to 62.5% in 2060. 
86 Ageing Report 2009 
87 Updates of current and prospective theoretical pension replacement rates 2006-2046 , SPC, July 2009. 
One must keep in mind that very few individuals in Member States were ever entitled to the theoretical 
replacement rates, as average career lengths are cu rrently much lower than 40 years in many EU 
countries. 
 
EN 109   EN significant improvement has been seen in incr easing employment rates in general and in 
particular among women and older workers.  
In 2007, the employment rate for older workers in the EU-27 was 45% compared to 37% in 
2001, and 12 countries now exceed  the 50% target (Denmark, Germany, Estonia, Ireland, 
Cyprus, Latvia, Lithuania, the Netherlands , Portugal, Finland, Sweden, and the UK). 
However, the target is still far off for a gr oup of countries where the employment rate for 
older workers is around 30%. The general increase  in employment rates results from two main 
factors: a demographic effect and the increased participation of women. Due to the ageing of 
the baby-boom generation, the relative share of people aged 55-59 — who have a higher employment rate — has grown. Post 2000, the impr ovement in the employment rate for older 
workers has been markedly better than that fo r both people of prime working age (25-54) and 
youth (15-24). In addition, most Member Stat es experienced a higher increase in the 
employment rate for older women th an for older men between 2001 and 2007.
88  
Figure 7.1 Employment rates of older workers ( 55-64) in the EU-15 (1992-2008) and EU-27 
(1997-2008)  
202530354045505560
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008eu27 eu15
eu27 (male) eu15 (male)
eu27 (female) eu15 (female)
 
Source: Eurostat  
Recent improvements in the employment rates of older workers should not hide the fact that 
the employment rates of older men have de clined substantially since 1970, when life 
expectancy was much lower than today. In 1970 there were more employed men aged 55-69 
than today and more women aged 65-69. In c ontrast, the employment rates of women aged 
25-54 increased substantially by at least 25 pp.89 Attracting more people into the labour 
market in the future will thus require reversal  of the decline in the employment of older 
people (especially men) observed after 1970 a nd boosting of the trend towards increasing 
female employment. 
                                                 
88 More detailed analysis can be found in the chapter 2 "Active ageing and labour market trends for older 
workers", Employment in Europe 2007  Report. 
89 Ibidem  
 
EN 110   EN Figure 7.2 Employment rates by gende r in the EU-15, 1970 and 2008  
0102030405060708090100
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+% of age group population
Men 1970 Men 2008 Women 1970 Women 2008 80%
 
Source: OECD Stat base 
General policies fostering economic growth and j obs together with soci etal changes (such as 
structural changes in the skill, gender and sector al composition of older workers) have clearly 
formed the backdrop to much of recent progress particularly in  terms of more people working 
more. But pension reforms have certainly un derpinned developments through changes in 
design and incentives embedded in pension schemes. These include: 
Increasing pensionable ages — i.e. the ages at which retirement benefits can be accessed, or 
accessed without any actuarial reductions (for  instance in the UK, DE, DK before 2030, HU, 
MT, SI and — for women — AT), abolishing or  restricting early retirement options (for 
instance in BE, DK, ES, LV, LT, PL) and examini ng critically other routes out of work prior 
to formal retirement, such as disability and incapacity schemes. 
Improving flexible retirement options, allowing and encouraging people to continue working, 
perhaps in a reduced capacity, and supplementi ng to pensions for people who choose to defer 
taking them.  
Increasing the link between actua l contributions (number of c ontributions, period they are 
made over and their level) and eventual pensi on income. Due to their nature, funded pensions 
— both defined-benefit (DB) a nd defined-contribution (DC) - tend to have such links and 
notional defined-contribution (NDC ) schemes (as in SE, IT, PL, LV ) are also designed in this 
way. But increasingly other publ ic pension designs (e.g. AT, DE, ES, FR, PT) also have 
features where longer working lives feed into higher pensions.  Linking pension benefit calculation and/or indexation of benefits to changes in longevity or 
dependency ratios. Many pensio n reforms (e.g. SE, IT, PL, DE, FI, FR, AT) have already 
introduced such mechanisms. While these meas ures may have little impact on retirement 
decisions, they can (if allowed to operate as in tended) reduce pension be nefits in relation to 
earnings and contribute to better alignm ent of expenditure s with revenue. 
Outlawing and reducing age discrimination in work  places and labour mark ets at both EU and 
national levels.  
 
EN 111   EN 7.1.3. Greater pre-funding of pensions 
Greater pre-funding, in one form or another, has been a popular policy response by Member 
States to the demographic chal lenge. However, it is importa nt to note that pay-as-you-go 
(PAYG) is and will remain the most important el ement in overall pensio n provision for most 
European citizens. 
In macro-economic terms, pre-funding is abou t bringing forward some of the costs of the 
demographic shift to distribute them over a longer period and over different generations. 
Greater pre-funding can have va rious important implications for risk sharing, diversity, 
solidarity, personal responsibility, credibility and efficiency, with these impacts varying 
depending on the pre-funding mechanism chosen. 
The three main approaches to pre-funding are: 
Increasing the role of funded pensions sche mes (on a compulsory, quasi-compulsory or 
voluntary basis) setting up a national reserve fund (more or le ss explicitly ear-marked to help smooth the 
demographic impacts on PAYG schemes) paying down national debt (with a more or less explicit link to smoothing demographic 
impacts) 
Hybrid schemes combining the best features of traditional designs 
A key trend in reforms has been a much larger role  in future pension systems for privately managed, 
fully funded schemes. Yet it would be a gross simplification to say that changes have primarily 
entailed a shift from public to private and PAYG to  funded schemes. In fact, reforms have brought 
several genuine innovations into scheme design. Whet her through big-bang paradigmatic changes or a 
sequence of parametric reforms, Member States have to a large extent developed new hybrid designs . 
Typically, they have sought to incorporate the be tter features that used to distinguish public from 
private and PAYG from funding schemes. Through tran sformative NDC designs (e.g. SE, IT, PL) or 
simply by significantly strengthening the links be tween contributions and benefits, a number of 
statutory, public PAYG systems (e.g. DE, ES, FR, PT) now emulate the individual accounts and 
actuarial connections hitherto only found with priv ate, fully funded schemes. The aim is to provide 
similarly strong and transparent in centives to work and contribute, while avoiding the difficulties of 
funding schemes such as the double payment problem  and investment risks. Likewise, typical 
weaknesses of private funded schemes in terms of social protection, such as low, fragmented and 
discretionary coverage, have been overcome in pioneering Member States through the semi-
compulsory extension of occupational schemes (e.g. NL, SE, DK and recently UK), making private 
scheme coverage mandatory (e.g. BG, EE, LT, LV, HU, PL, SE, SK, RO), or subsidies for lower-
income groups in voluntary private pension savings  schemes (e.g. DE). New occupational schemes 
also tend to be designed so they present far fewer barriers to labour market mobility (e.g. DK, SE & 
UK) than traditional schemes. 
The majority of Member States have expanded the role of pre-funding, by setting up national 
reserve funds to smooth ageing effects on PA YG schemes, expanding existing or introducing 
new occupational and voluntary schemes, or — mo st importantly — shifting part of former 
PAYG contributions to mandatory f unded schemes under private management. 
Over the last ten years, a number of Member States have set up new funded pension schemes 
of the latter kind. These are defined-contributi on (DC) schemes and the vast majority form 
part of the compulsory social security syst em (BG, EE, LT, LV, HU, PL, SE, SK, RO). In 
some countries, however, reforms currently und er way (e.g. DK and most recently the UK) 
 
EN 112   EN involve a national quasi-compulsory occupati onal pension scheme set up with employer 
involvement. It is important to note that occu pational pensions are not  compulsory in many 
Member States, which raises concerns of cove rage when looking at the overall pensions of 
individuals. Another different approach seen in various Member States involves encouraging 
voluntary individual DC pensions. In CZ and DE, on the back of generous targeted incentives, 
a significant increase in the importance of such voluntary schemes is expected.  
Figure 7.3 Gross replacement rate s of occupational and statutory funded pensions in 
2006 and 2046 in selected Member States 
0%10%20%30%40%50%60%70%
IT RO BG BE DE HU SE EE LT UK PL SK IE LV DK NL2046 2006
 
Source: ISG 2009 report on Theoretical Replacement Rates 
Note: Data available only for a number of Member States 
Figure 7.4 Ratio of expenditure on mandatory  occupational and mandatory private 
pensions to expenditure on social security pensions90 
0,00,20,40,60,81,01,2
PT ES RO BG HU LT PL SK IE EE SE LV DK NL2060 2007
 
Source: own calculations on the basis of Ageing Report 2009, data not available for all MS, voluntary private 
pensions are not included 
                                                 
90 Values for Figure 7.4 are calculated by compari ng numbers from tables extracted from the EU 2009 
Ageing Report: A 57 (expenditure on occupational  pensions as percentage of GDP) and A 58 
(expenditure on private  mandatory pensions as percentage of GDP) with numbers in table A53 (gross 
social security pension expenditure as percentage of GDP). 
 
EN 113   EN Similarly, a number of Member States have set up reserve funds mo re or less explicitly 
intended to help smooth the impact of the de mographic challenge on PAYG pension schemes. 
These vary considerably in size, explicit purpose and controls, and their true test will come 
over the long term. In some countries, the rese rve funds have not yet accumulated substantial 
assets (less than 10  % of GDP, e.g. BE, EE, ES, FR, IE, NL), while in others they have 
become quite sizeable (e.g. LU, SE, FI), ranging from just over 20  % of GDP in LU to almost 
30 % of GDP in SE in 2007. In other Member St ates the funds may not be purely pension 
funds but social protection or demogr aphic funds (e.g. UK, LT, CY, PL, PT). 
A final option for moving some of the costs of the demographic change forward is for 
countries to pay down national debt (e.g. BE, DK).  However, few of the countries using this 
route have been able to make explicit links between particular actions to reduce national debt 
and the financing of future pensions.  
Contrary to this increasing role for funded pension schemes, funded occupational defined-
benefit (DB) schemes, which ha ve traditionally been  important in NL, UK, IE, SE and DK are 
in many cases in decline (notably in UK and IE ). Facing the same demographic pressures as 
statutory PAYG schemes, DB schemes are undergoi ng major changes. In particular, they are 
increasing pensionable ages and in many cases  shifting to funded defined-contribution (DC) 
schemes, where the investment and longevity risk  lies to a greater extent  with members rather 
than the scheme. Nonetheless the overall stor y of how pension systems are changing as a 
result of reforms is one of incr eased pre-funding compared to today. 
7.1.4. Changes in the relative level of public pensions 
Strengthening of the link between  contributions and the accrual of benefit rights means that 
the same contributions as in  the past will give people less annual pension. But given 
increasing longevity, this annual reduction does not necessarily imply a lower overall transfer 
paid out over the retirement pe riod. Moreover, the drop in the va lue of annual pe nsion will be 
reduced as more people will be getting pens ions in the future (e.g. more women).  
Given the projected reduction in working ag e population, the same level of contributions 
cannot continue to fund these increased pensio ns, and to avoid constant increases Member 
States have sought other ways to rebalance their systems. Re ducing the replacement rates at a 
given age of retirement is one way to retu rn to a more sustainable balance between 
contributions and total pension paid over (longe r average) retirements. Another way is to 
continue to pay the same annual pension but to in crease the age at which it is first payable in 
line with longevity increases. Most countries combine these approaches. 
In funded defined-contribution (DC) schemes act uarial adjustments occur automatically. The 
pension fund accumulated will have to cover mo re or less years of retirement depending on 
when a person retires and how long they can e xpect to live on average, so the amount they 
will receive annually will vary accordingly. This is made most overt (and individual longevity 
and investment risks are most reduced) when  the payout phase is via annuities. The 
adjustments inherent in individual DC scheme s are no doubt one reason why they have been a 
popular policy response. 
For pay-as-you-go (PAYG) pensions, other options have been considered. One approach is to 
move from having one fixed pe nsionable age with a fixed a nnual pension, to give people 
choices based on actuarial fairne ss. Here, people who choose to  delay taking their pension 
will receive a higher annual amount when they do in fact take it up. Equally, people who opt 
 
EN 114   EN to take their pension earlier will receive a lower pension, reflecting the fact it will on average 
be paid for more years. 
Another approach is to build global (as opposed to individual-choice) adjustment mechanisms 
into public pension schemes. These are de signed to stabilise pension systems through 
automatic adjustments (e.g. SE, FI, PL, DE) or periodically required reviews and adjustments 
(e.g. AT, IT, FR). They intend to reflect changes in  one or more factors such as longevity (e.g. 
in SE, FI, IT, PT), the support ratio (e.g. in  DE), reserve fund performance (e.g. SE) or 
general economic performance (e.g. in FI, SE ). The effects vary from increases in 
contribution rates (e.g. DE), lower (or even nega tive) indexation of benefits (e.g. FI, SE) and 
lower accrual rates (e .g. PT), to increases in pensionable ages (e.g. in DK). 
Such mechanisms at least ensure that the adju stments needed are put on the agenda. But it is 
always easier to set up such mechanisms than to allow them to fully operate when they are triggered. 
The overall decline in the relative level of pens ion benefits at a give n retirement age emerging 
from reforms has given rise to questions whet her key improvements in  the overall financial 
sustainability of systems have been obtained at the cost of adequacy. While this calls for 
further investigation, as adequacy is a multi-level, contextual con cept, it would be safe to say 
that greater sustainability has been secured by introducing a greater el ement of conditionality 
into future pension provision. Obtaining replacement  rates similar to those of the recent past 
will require people to work substantially more  and longer and in many cases people will also 
have to increase their co ntributions to voluntary pe nsion savings schemes.  
Box X. The adequacy of pension systems 
The adequacy  of pension systems and the way it can be measured can be viewed in terms of the two main 
objectives of pensions, as posited by economic thinking: 
1) Pension systems aim to provide all individuals income security in old age. As some people may be poor over a 
lifetime and unable to save enough during working life to en sure income security in old age, one of the stated 
key objectives of public pension systems is precisely to relieve poverty . There should therefore be programmes 
that reduce the risk of poverty in old age, by providing minimum adequate levels of pension income. 
For the OMC, elderly poverty is basically measured rela tive to that of the working age population. The main 
indicators used are at-the-risk-of-poverty rate and the relative income of the elderly. These together give us a 
picture of the efficiency of minimum income pensions in providing adequate income security for the elderly. 
2) Pensions are also a mechanism for consumption smoothing . During their retired lives people have to consume 
real goods and services, ju st as during their working years. Thus 'adequate ' pension income allows for smoothing 
the consumption path over time, through the productive middle years and then the retired years. This also implies 
that 'adequacy' has to take into account the need to retain the value of income over time (i.e. indexation) so as to 
keep constant the real value of a person's pension. 
In order to account for the second dimension in the definition of adequacy, the OMC indicators look at measures 
of replacement income, i.e. the extent to which pension sy stems enable workers to pres erve their previous living 
standards when moving from employment to retirement and the relative income of the elderly. The main 
indicator is the aggregate replacement ra tio. However, this only looks at pensions currently in payment. But 
given the long-term implications of pension reforms, theoretical replacement rates are useful as an additional 
analysis tool. This gives us the po ssibility to look at th e adequacy of the replacement income provided by 
pension systems for theoretical cases. It also allows us to stress-test this adequacy  by assuming macroeconomic 
shocks such as the change in rate of returns for funded pensions or by assuming career-breaks for individuals, for 
example in the case of unemployment. 
 
EN 115   EN These indicators may not be exhaustive in the analysis of pension adequacy, and future work can seek to identify 
new measurements as developments in data sources and modelling tools improve. This can also provide 
possibilities to look at the adequacy and sustainability of pensions more cohesively.  
7.1.5. More interdependent schemes make fo r more complicated pension systems 
Implicit in the greater role for pre-funded components is the move towards multi-tier  
systems, whether by expanding existing rudiment ary tiers or by introducing new statutory, 
occupational or voluntary tiers. This has made systems more complicated  and greatly raised 
the need for transparency, information and even  financial education. Where individuals before 
could rely on single systems to provide for them they will in the future be required to make a 
lot of decisions and adapt thei r working lives to obtain su fficient pension rights for an 
adequate pension package.  
Despite these caveats, the many i nnovative features in pension syst ems as a result of reforms 
have put the majority of Member States on a sound course  towards achieving a better 
balance between financial, labour market and social protection concerns in their pension 
systems. 
7.2. First effects of the crisis 
The European economy is subject to fluctuations  in the economic cycle. It stagnated in 2002-
2003, to rebound again in 2004. Growth came to a ha lt in 2008 as the worl d entered one of the 
direst financial and economic cr ises in years. EU-27 GDP is projected to fall by 4.1% in 2009 , 
even if the economy started to grow agai n in the third quarter of the year.  
Current pensioners have so far been among t hose least affected by the crisis. With steady 
incomes and low inflation they have been fairly well cushioned. Thanks to improvements in recent growth years even pensioners with mini mum pensions have fared somewhat better than 
before. People retiring now or in the near future are also unlikely to be much affected. With a 
few Member States as stark exceptions, this is the situation for pensi oners across the Union.  
The main reason for this is that current pensi oners overwhelmingly draw their pensions from 
public (pre-reform) PAYG system s and established most of their pension rights before 
reforms began to take effect. Notwithstanding  the trend towards a la rger role for funded 
schemes, benefits from such schemes still gene rally play only a marginal role in pensioner 
income. In the few countries where this type  of income is already important, benefits 
furthermore tend to be of the defined-benefit ty pe where the investment risk is borne by the 
scheme. Thus, current pensioner income is not so  sensitive to the short-term ups and downs of 
financial markets. Moreover, even though redu ctions in contribution revenues immediately 
weaken public pension scheme finances in mo st countries, it would still take a longer 
weakening of overall public finances before pens ioners could conceivabl y be affected through 
lower indexing of benefits. Current  pensioners are therefore also  not particularly affected by 
the impact of the crisis on the labour market. 
7.2.1. Occupational pensions schemes in deficit 
Defined-benefit (DB) occupationa l pension schemes take on the investment risk, so in the 
shorter term people in general will get the pension they expect. Going forward some impacts will be felt as funded DB pension schemes that are in deficit as a result of falls in investments 
 
EN 116   EN seek to restore their funding balance. The cris is has caused most DB funds to move into 
deficit, due not only to falls in the value of investments but also to changes in the market 
interest rates used to translate future  liabilities into today's money terms. 
Member State reactions to the problems with funded schemes have in the short term been 
pragmatic. National pension supervisory authorit ies have aimed to allow pension funds more 
flexibility than normal. For instance, Irish  pension funds were given more time to submit 
funding status reports and recovery plans in th e hope that markets would become more stable, 
making the planning process easier and more robust. The normal maximum period allowed 
for recovery from deficits has been extended (e .g. IE, NL) and greater use has been made of 
existing flexibility, as in the UK's scheme-speci fic funding regime. This allows the impacts to 
be spread over a longer period, thus smoothing the impact of the crisis and hopefully allowing 
any recovery in markets to assist  in a return to  full funding. In Denmark , a financial stability 
package for pensions has been implemented to en sure market stability and prevent the forced 
sale of mortgage bonds owned by pension fund s and substantial losses for pension savers. 
Regulators and the insurance and pension industry have agreed to temporary changes in the 
standards by which the solvency of funds is cal culated to avoid funds locking in their losses 
by being forced to sell assets in the currently depressed markets. The double aim is to avoid 
destabilisation of the mortgage bond market and substantial losses for pension savers. 
Dialogue between social partners  is often a key element behind the recovery plans, as they 
involve attempts to share the impacts not only ov er time but also between different interests. 
A greater sharing of risks be tween scheme members and empl oyers may be needed if the 
decline in DB provision is to be halted and such schemes are to have a viab le future. In the 
Netherlands,  the existing risk-sharing mechanisms have been used to lower or freeze 
indexation of benefits and/or increases in cont ribution levels. This shares the impacts between 
employers and pension scheme members, whether still working or retired. These mechanisms 
and the increase in permitted recovery periods aim to avoid the need for any last-resort adjustment of actual benefits. In contrast, the UK , with its legal obligation on employers to 
support their pension schemes, has seen increasing demands on employers to make extra contributions to schemes. In some cases, ad hoc negotiations between employers and 
employees have led to some burden sharing with scheme members (e.g. higher employee 
contributions, lower benefits). 
7.2.2. Market exposure of future pensioners in the DC schemes 
Defined-contribution (DC) pens ion schemes leave the investme nt risk entirely with the 
scheme member,  so the impact of falls in investments is felt directly. On the other hand, DC 
plan members can benefit from any investme nt out-performance, unlike DB members.  
DC-funded pensions  can be statutory, occupational and vol untary, and all three are expected 
to see some growth in at l east some Member States. Curren tly, statutory DC-funded schemes 
are found in the majority of new Member Stat es (BG, EE, HU, LT, LV, PL, RO, SK — see 
table below) together with SE and IT. A numb er of Member States have DC occupational 
pension schemes, notably UK, IE, SE and DK, although others including NL, BE and CY also 
 
EN 117   EN have some provision of this type. Voluntary DC  provision is really only of importance in IE, 
UK, CZ and particularly DE, on the back of  the strongly incentivis ed Riester pensions.91 
Statutory DC schemes will grow  as transitional arrangements switch some elements of 
provision from PAYG to funde d statutory DC schemes. For occupational DC schemes, 
growth will stem largely from a switch from  DB to DC provision. I ndividual voluntary DC 
provision is normally encouraged by tax incentives and typically used to top up other pension 
income. Only modest, if any, growth is expected in this type of provision.  
Fortunately, the crisis came at a time when DC provision was less important than it will be in 
future . People with DC provision who are some way from retirement may have time for 
investment falls to recover at least partially. Fo r those close to retireme nt the impact can be 
real, leading to less affluent, or  possibly delayed, retirement. 
For those countries that have opt ed for an important role for f unded DC provision of whatever 
type, the questions seem to be :  
– how to control the risk for the individual; 
– how to give people a realistic idea  about what can be obtained;  
– how to consider for which income and caree r profiles these schemes are an appropriate 
solution; and 
– how to ensure the payout pha se matches the original pur pose of pension savings as 
efficiently as possible. 
In relation to the capacity to bear risk , the question is also whether mandatory schemes in 
particular should make provision to  protect against too much volatility. This could be done by 
guaranteeing the principal and some minimal rate  of return, but it coul d be very costly and 
possibly create incentives for excessive risk-tak ing if the guarantee carries no price to the 
scheme operators. Another more likely solution c onsists in gradually lowering the investment 
risk as people get closer to retirement age (so- called 'life-styling' or 'life-cycling' investment 
strategies). Not all mandatory schemes contai n such options at the moment. Attempts to 
reduce the reliance of pension funds on more vola tile assets by setting limits on the value of 
shares in portfolios can be also observed, but th e timing of such reforms (low value of more 
risky assets when the crisis  hit) is questionable.  
The choice between investment strategies with di fferent potential rates of return and levels of 
risk leads to questi ons as to the accura cy of information . In statutory sche mes where there was 
a choice between continuing in PAYG schemes or moving part of the cont ributions to the new 
funded scheme, people often opted for a defined-contribution scheme even if it was questionable whether this was indeed the best solution for them. And re garding the choice of 
pension funds and investment strategies, evid ence suggests that many people went for riskier 
options than would have been justified given their earning capacity an d the length of their 
working life. These choices were driven by the information people received at the time. Rates 
of return observed in the past  and the positive growth expect ations for central and eastern 
                                                
 
91 It is important to remind that Riester pensions ar e not pure DC schemes becau se they do not leave the 
investment risk entirely with scheme members. Financial institutions are obliged to offer to their 
customers a guarantee of maintena nce of nominal value of capital. 
 
EN 118   EN European countries obviously played  a role. But so did the fact that nobody told people that a 
sudden decline in asset values could occur. He nce, access to unbiased information is of key 
importance and not only in defined-contribution schemes. Additional information provided by non-partisan organisations such as  consumer NGOs could help pe ople make the right choices. 
Introducing limited-risk default options designe d to be a reasonable choice for most people 
would likewise help. 
The 2009 Joint Report on Social Inclusion and Soci al Protection stressed that Member States 
should give careful considerati on to the proportion of overall pension income expected to 
come from defined-contribution schemes  and whether such schemes would be sufficiently 
appropriate for all groups in th e population. This is often not the case for less well-off people 
and for those with shorter or atypical employment careers. Pe ople in this situation would 
typically be better served by pay- as-you-go schemes, as they would not be able to accumulate 
sufficient benefits or absorb the inherent risks. 
The payout phase in DC pension design often appears to be an afte rthought when it should be 
central to the scheme, especially where it will  form an important element of overall pension 
provision. A poorly designed pa yout phase means money supposedly saved to provide 
retirement income leaks out of the pension sy stem to be used for other purposes such as 
bequests. This is a problem unique to DC pens ions. PAYG and DB schemes and their inherent 
cross-subsidies between t hose who live for longer or shorter periods in retirem ent ensure that 
all resources are used to  provide pensions. DC schemes with  their increased sense of personal 
ownership also bring with them the risk of  money being used for non-pension purposes. 
Allowing this with badly designed payout phases means poorer retirements or greater costs to 
compensate for the leakage. The closest ma tch to the payout outcomes from PAYG and DB 
pensions is provided by annuity-based DC schemes. Ensuring the payout phase is well 
thought out and clearly explaine d before people join schemes reduces the likelihood of 
difficulties later. 
An important advantage of DC schemes over DB pl ans is that they have  a less distortionary 
impact on the labour market. Mobile workers who change their jobs can be often better off in 
terms of their pension outcome with one DC  fund rather than with multiple small DB 
entitlements. DC schemes do not discourage job mobility to extent that DB schemes can do. 
7.2.3. The problem of double payment in mandatory DC schemes 
BG, EE, LT, LV, HU, PL, SE, SK, and RO have  introduced mandatory or quasi-mandatory 
funded pension provision during the last 11 years. The situa tion in these countries is, 
however, diverse.  We can observe differences according to the time of implementation of 
reform (from 1998 in HU to 2008 in RO), rela tive maturity of DC schemes (first partial 
cohorts retired in 2009 in PL, but  will retire only in 2023 in RO), the importance of pension 
contributions feeding into DC schemes (contribu tions ranging from 5% of gross wages in BG 
to 9% in SK), existence of phasing-in arra ngements (e.g. gradual in crease in contribution 
levels in LV and RO, and tran sitional arrangements in LT, PL, or SK), and the character of 
the scheme (mandatory for cohorts under a certa in age in BG, LV, or PL, and mandatory for 
those who decided to opt in on voluntary basis,  e.g. in LT). More detailed information on DC 
schemes in central and eastern Europe  can be found in the table below. 
 
EN 119   EN Table 7.1 Pension systems in selected Member States92  
Country  
 % Wage 
to funded 
scheme  Proportion of 
total 
contribution 
to funded 
scheme  Year 
funded 
scheme 
started  Participation in funded scheme  Year funded participants retire  
Bulgaria  5% 21.7%  2002 Mandatory <42 Full cohorts in 2023  
Estonia  6% 20.0%  2002 Voluntary Partial cohorts by 2012  
Hungary  8% 23.9%  1998 Mandatory for new entrants; 
voluntary for all others Partial cohorts by 2013 ;  
full cohorts by 2045  
Latvia  2% 
increasing 
to 6% 6%  
increasing to 
24.0%  2001 Mandatory <30, voluntary 30-49 Partial cohorts by 2013 ;  
full cohorts by 2033  
Lithuania  5.5% 22.0%  2004 Voluntary Partial cohorts by 2014  
Poland  7.3% 26.1%  1999 Mandatory <30; voluntary 30-50 
 Partial cohorts of women by 2009 
and men by 2014 ; 
full cohorts of women by 2029 and 
men by 2034  
Romania  2%, 
increasing 
to 6% 6.7%  2008 Mandatory <35; voluntary 36-45 Partial cohorts of women by 2023 
and men by 2028 ;  
full cohorts of women by 2033 and 
men by 2038  
Slovak 
Republic 9% 31.3%  2005 Voluntary for all Partial cohorts by 2020  
Source: Regional Bank Staff  
A common feature for Member Stat es that have introduced statutory DC schemes is the need 
to shoulder net transition costs. Often Member States divert part of the contribution for the 
PAYG scheme into the funded scheme while covering the shortfall from the state budget 
though general taxation (e.g. SK, LV , LT, EE, HU). Other strategies  have included increasing 
total contribution rates to pension schemes, usin g revenues from privatising state enterprises, 
or shifting part of the cost to current pe nsioners, e.g. through the introduction of less 
favourable indexation rules, or to futu re beneficiaries of the PAYG schemes93. 
The reforms usually made participation in the funded scheme mandatory for younger 
generations, while people nearing retirement we re excluded, and intermediate cohorts had the 
choice to join or not. In some Member St ates (e.g. LT, HU, PL, SK), however, the net 
transition costs turned out to  be higher than anticipated , as the numbers of workers who 
moved to the mixed PAYG-funded system cons iderably exceeded official estimates. 
Bringing forward costs by increasing pre-funding  has placed strains on Members States' fiscal 
positions, and the current economic situation provide s a serious stress test of the viability of 
                                                 
92 Relevant EU countries extracted from World Ba nk Human Development Networ k paper "The Financial 
Crisis and Mandatory Pension Systems in Developi ng Countries Short- and medium-term responses for 
retirement income systems" http://siteresources .worldbank.org/INTPENS IONS/Resources/395443-
1121194657824/PRPNote-Financial_Crisis_12-10-2008.pdf 
93 According to the 2008 SPC study "Privately Managed Funded Pension Provision and their Contribution 
to Adequate and Sustainable Pensions", pp.18-19. 
 
EN 120   EN such arrangements. Facing a growing fiscal ga p, some Member States have decided to limit 
the relative burden of pre-funding  future pension expenditure by reducing the proportion of 
social security contributions diverted to ma ndatory DC schemes (e.g. EE, LT, LV, SK, RO). 
In Estonia,  all compulsory contributions to the DC scheme have been cancelled from 1 June 
2009 until 31 December 2010. Scheme members can restart their contributions on a voluntary 
basis in 2010. The government's intention is that  contributions will be partially resumed in 
2011 (with a 2% state and 1% memb er share) and will reach th eir original level only in 2012 
(4% plus 2%). In Lithuania , social insurance contributions to the DC pension schemes have 
been reduced temporarily from 5.5% to 2% by 2012. They will be increased again to 6% after 2012 for a minimum of 3 years. In Latvia,  part of contributions to  the mandatory funded DC 
scheme has been diverted to feed the PAYG NDC scheme. Contributio n rates to the funded 
pillar are being reduced: in 2009 from 8% to  2%; in 2010 from 9% to  2%; in 2011 from 10% 
to 4%; in 2012 and subsequent years from 10% to 6%.
 In Romania,  the government has 
suspended legal provisions that would have seen  contributions to the mandatory DC scheme 
rise from 2% to 2.5% of empl oyees’ gross salary this year. Slovakia  has allowed workers to 
opt out of the funded scheme and return to  the PAYG scheme for the second time in 2008, 
and the DC scheme will be optional for a ll new entrants to the labour market. In Poland,  the 
government is discussing a reduction in contribu tions to the DC scheme from 7.3% to 3% of 
gross wages and to divert the difference to the PAYG scheme. Another solution under 
consideration of the government is  to revise the way in which public debt is calculated by 
excluding the debt resulting from tran sfers to the funded pension scheme. 
Shifting part of contributions from funded schemes to PAYG schemes helps to reduce the 
aggregate savings rate, so can be tr eated as an anti-cyclical measure . However, there are also 
arguments against decreasing th e pre-funding burden. The inflow  of contributions to funded 
schemes is reduced when prices of assets are low  and offer greater growth prospects. This 
might imply a decline in the expected rates of  return. While it is understandable that public 
authorities see the need to ad just their mandatory private funded schemes, one should not 
forget that pension systems need stability over the long term  if they are to have the necessary 
credibility among citizens. Hence, transpar ency and long-term planning are important. 
7.2.4. Distribution of the burden of the cr isis in PAYG system s between different 
generations 
PAYG schemes also have not been immune to th e crisis. The effect of the crisis on different 
cohorts of pensioners varies  depending on how much future pension systems will differ from 
the current arrangements. In most Member St ates, most retired coho rts today obtain their 
pensions under pre-reform rules providing for guaranteed pension levels. Younger cohorts in 
reformed schemes may be affected to some ex tent depending on the design of the scheme.  
Member States in the majority of cases are k eeping their promises towards current pensioners , 
even at the expense of soaring public debts that  will add to the costs of ageing and increase 
future burdens on the current workin g age population. LV and LT are exceptions  here as they 
are recording the deepest fall in GDP in the EU in 2009 (bot h economies are expected to 
contract by 18%)94 and current pensioner cohorts have also had to bear the burden of 
economic adjustment.  
                                                 
94 European Economic Fo recast of Autumn 2009. 
 
EN 121   EN Pension benefits for current pensioners in Latvia  have seen an overa ll 10% reduction (70% 
for working pensioners) since the 1st of July 2009. According to the judgment of the 
Constitutional Court (21 December 2009), th ese deductions will be removed from 1st 
February 2010 and deducti ons for the time period 1st July 2009 to 1st February 2010 will be 
reimbursed to pensioners. The amount of early  retirement benefit has also been decreased. 
Nevertheless, given the collapse in the labour market, the number of early retirement and 
disability pensions increased considerably in 2008 and especially in 2009. Moreover, there 
will be no indexation of pensions in 2009 and 2010, and from 2011 price indexation will be 
applied (the previous method also considered wages).  
In Lithuania , social security schemes are facing huge  pressures from decreasing income and 
increasing numbers of unemployed. Seeking to stab ilize an increase of the deficit of the State 
and the State Social Insurance F und budgets and to ensu re timely payments of social security 
benefits, a reduction of social security benefits  (social insurance pensions, state pensions and 
other social benefits) was introduced since 1st January (temporarily until 2012). They are 
reduced progressively according to income received (pensions and labour income). On average old age pensions are lowered by 5%. Pens ions for working old age pensioners will be 
reduced proportionally to their insured inco me received, with a maximum reduction of 70%. 
7.2.5. Shrinking contribution base in PAYG schemes 
It is the economic crisis, rather than the financial crisis that precipitated it, that is affecting 
PAYG pensions. The sustainabil ity of PAYG pensions ultimately  depends on the strength of 
the underlying economy,  so fewer people working and paying contributions, lower economic 
growth and higher levels of national debt all weigh down on PAYG scheme s. At least over the 
short term the effects are very limited. Where they  occur, impacts may take the form of lower 
indexation (e.g. EE, LV), higher contributions  (e.g. CY, LV, RO) or delayed reforms. 
The strength of PAYG  pensions is that they are resilient to shocks  in the short term, and these 
impacts can be smoothed and shared over long periods.  
The majority of Member States have preferred to accept increased deficits in their social 
security schemes, so that automatic stabilisers can play their role. Anti-cyclical behaviour in 
social spending  is an important part of supporting an economy in recession. This is one of the 
factors contributing to ballooni ng general government deficits a nd a dramatic increase in the 
level of gross general government debt in the EU, from 58.7% of GDP in 2007 to 83.7% of 
GDP in 2011.95  
In order to limit the in crease in public debt some countri es have decided to deplete their 
reserve funds  (e.g. IE, LV) whereas in others this is being considered (e.g. PL). While in LV 
the reserve fund partially covers the deficit of the social securi ty system, the reserve fund in 
IE was used as a means to help solve the effects of the crisis in the banking sector. While this 
can be considered an effective use of resource s in times of constraint, it is important to 
consider the long-term demographic pressure s on the pension system. The use of funds 
earmarked for pensions can also lead to a lo ss of social confidence and acceptance for the 
pension system. 
                                                 
95 European Economic Forecast, Autumn 2009, European Comm ission, p. 208. 
 
EN 122   EN 7.2.6. The effects of the crisis on aut omatic mechanisms in PAYG systems 
While automatic mechanisms enhance the transpar ency of a pension syst em, they do so only 
if they are allowed to be activated. Automatic adjustment  and indexing rules boost the 
transparency and credibility of  a system only if the trigge rs are allowed to function.  
Most automatic mechanisms have not yet been applied in practice, a nd experience from 2006-
2008 shows that it is critical to monitor the functioning of thes e mechanisms, some of which 
are close to activation given the financial and economic pre ssures on pension systems as a 
result of the crisis. Prior to the crisis a few countries had already take n political decisions to 
postpone automatic adjustments. Changing the re gulations before the adjustments are to be 
activated may damage their credibility. 
In Italy,  the automatic updating of life-expectancy projections for annuity calculations has 
been delayed. In Germany,  pension benefits have been temporarily increased beyond what 
would have been allowed by the automatic adjustment mechanism, which aim to balance contributions and federal subsidies against pens ion expenditure during the year. A part of the 
increase in pension benefits resulted from the so called 'sustainability factor' which takes into account the demographic imbalances between the working population and th e retired. Positive 
change in the relation between the working population and the retired triggers an increase in 
pension benefits. 
The activation of the automatic adjustment mech anism in DE would requi re contribution rates 
to be raised. Whiles there is a cap of 20% on c ontribution rates, this can be balanced with a 
decrease in pension indexation. In 2002 to 2005, contribution rates woul d have had to be 
increased to over 20% or pension indexation woul d have had to be suspended. However, this 
was alleviated by the introduction of the 'Riester  factor' in the adjustment mechanism, which 
takes into account the increas e in total contributions outsi de the statutory system.  
In Sweden , the fall in financial markets has trig gered the adjustment mechanism. The 
activation of the mechanism reduces the in dexation of pensions and earned pension 
entitlements, and depends on the calculation of  a surplus or deficit in the system. This 
calculation is regulated by law. The Swedish gove rnment has recently decided to re-evaluate 
the calculation performed for the balancing mech anism and the proposal that has been decided 
by the Swedish parliament is one that smoothe ns out the volatility of the buffer funds by 
incorporating a three year moving average of their values into the calculation of the balance 
rather than the current annual va lue of the funds. This will ha ve the effect of sharing the 
burden of the financial downturn over more year s. This strategy may increase the anti-cyclical 
nature of the mechanism. 
Box X. The role of pension systems as automatic stabilisers 
Social protection systems can respond in  different ways to the downturn in the economic cycle. On the one hand, 
anti-cyclical behaviour in public spending, especially on social expenditure, is an important part of bringing an 
economy out of recession, since social protection expendi ture constitutes a large part  of total expenditure. The 
role of social protection expenditure as an automatic stabiliser is to attenuate the consequences of economic 
shocks on the level of activity (i.e. by maintaining consumer incomes and thereby promoting demand). In that 
sense, given that pension spending is the biggest item of social protection expenditure, it is evident that it can 
play a crucial role as an anti-cyclical automatic stabiliser to sustain and re-boost the economy. The strength of 
the automatic stabiliser depends on the marginal propensity to consume of the group to which the benefit goes. 
Pensioners, a priori, should tend to consume their income as they have less incentives to save. On the other hand, 
at a time of crisis, as GDP contracts,  government budget balances are often strained, and cutbacks in pensions or 
indexation due to growing budget deficits are also observed.  
 
EN 123   EN Both types of pension policies have been observed in the current crisis. Some countries have held back the 
indexation of pensions (e.g. EE), postponed planned pens ion payments (e.g. HU) or cut pension benefits (e.g. 
LT) to cope with their fiscal consolidation concerns. Other countries have increased pension benefits, typically 
by increasing minimum pensions (e.g. ES, FR, FI, BG) or by increasing the indexation of pension payments 
beyond the normally applied rules (e.g. PT, FI). 
The responsiveness of pension systems to the business cycle is determined by the current capacity of public 
budgets to protect people. In that sens e, Member States are in very different  positions to face th e crisis. Countries 
with more balanced budgets can afford  to apply a higher degree of counter-c yclicality at a time of crisis as 
compared with countries where the cons olidation of fiscal budgets is the major concern. Countries with mature 
pension systems and balanced budgets will thus have more budgetary room for manoeuvre at the onset of a 
recession and will be in a better position to protect the mo st vulnerable and those most affected by a downturn. 
In contrast, countries faced with majo r public finance imbalances are left  with little room for manoeuvre to 
address the social consequences of the crisis.  
7.2.7. Conclusion 
Funded pension schemes have been more immedi ately and directly imp acted by the financial 
crisis. Falls in the value of i nvestments feed through into defici ts in definend-benefit pension 
schemes and into lower individual pension f und accounts. How these then impact on actual 
pension incomes for individuals depends on how  quickly and to what extent investments 
recover and what mechanisms are in place to mitigate and share investment risk. 
Pay-As-You-Go (PAYG) pensions  are also impacted. Ultima tely, the economy determines 
what is affordable for PAYG pensions. Lower gr owth, fewer people in work to pay for those 
already retired and increases in national debt  all weigh down on PAYG pension systems. The 
impact on individual pension income depends on how quickly countries return to growth and 
higher employment rates, what adjustment mech anisms are in place and what further reform 
measures are necessary to ensure PAYG schemes are sustainable in the long term. 
The demographic challenge remains key, and the cr isis has added to this  challenge. Indeed, 
the financial crisis may have put  into sharper focus underlying st ructural issues regarding the 
sustainability of pension systems. These issues may previously have been masked by expectations of returns on f unded pension schemes or anticipa ted levels of economic growth 
and employment rates which may now seem over-optimistic.  
The financial crisis and the economic downturn have outlined  the need for ensuring the 
resilience of reformed systems in terms of ensuring sustainable fi nancing and providing 
adequate pensions, both in the short and long term. Financial losses in pre-funded schemes 
can affect the solvency of these schemes and thus their ability to pay out pensions. The 
inherent risk of lower returns for future pens ions in defined-contribution schemes has also 
been brought into sharper focus. In PAYG scheme s, where the contribution base provided by 
the working population is key, the damage caused by long-term unemployment to the sustainability of these systems has been highlight ed. At the same time, as eligibility rules are 
tightened in reforms, the effect of long car eer breaks on future pensions also becomes 
significant. 
Though none of the present and future pension systems in the Member States have been 
designed to withstand a financial crisis and an  economic downturn of this magnitude, they 
seem to have performed relatively well. Ho wever, pension reforms and resulting pension 
promises have been predicated on scenar ios of steady economic growth and continued 
increases in employment. 
 
EN 124   EN Adjustments to all kinds of pension schemes ma y therefore be necessary to ensure their long-
term health. But one of the few positives that can be taken from the crisis is that it may give the necessary impetus for further reforms, in pa rticular to encourage and enable more people 
to work more and longer. 
7.3. Long-term implications of the crisis 
There is a marked uncertainty regarding econ omic growth over the medium and long term. 
The recession could have implications for th e growth potential of the EU economy. On the 
demand side, deteriorating labour market cond itions could constrain consumption in the 
medium term. The supply side of th e economy could be also affected.
96  
Trend growth in the next few years could be lowe r than projected in the pre-crisis scenarios. 
This would have implications for the future adequacy and sustainability of pensions.  
7.3.1. Will long-term sustainability  of pensions be affected? 
The long-term nature of pensions gives them a certain resilience to ec onomic shocks, as there 
is usually time for the systems to recover. Long  transitional periods in pension reforms also 
tend to protect the pensions of those in or cl ose to retirement today. However, the length of 
the shock and the financial situation of the syst em when the shock hits crucially affect how 
the system can handle the payment burden in th e short and long term. Pension reforms have 
been based on certain assumptions of growth a nd returns on paid cont ributions. If pension 
systems are unable to handle the effects of lower than expected returns or a narrower 
contribution base due to unemployment, this coul d ultimately affect the adequacy of benefits. 
However, a system that cannot pa y out adequate pensions is not sustainable in the long run, as 
its social or even political credibility will decrease. 
Member States have let pension systems play th e role of automatic stabilisers in the current 
crisis. However, anti-cyclicality should be maintained when recovery sets in , so that social 
protection systems are sustainabl e in the long run. This often implies politically difficult 
decisions. Meanwhile, automatic adjustment mech anisms in pension schemes may tend to be 
activated in a pro-cyclical rather than anti-cy clical manner, which needs to be monitored or 
adjusted. 
In the event of protracted low growth Member St ates will be faced with  the difficult task of 
adjusting social security expenditure to levels that reflect the trend growth rate of the economy and are affordable in the long run. Acco rding to an initial assessment by the Ageing 
Working Group, if trend growth is permanently affected, expenditure on public pensions in 
the EU in 2060 is projected to incr ease to 13.6% of GDP instead of 12.5%.
97 
7.3.2. Long-term adequacy of pensi ons in light of the crisis 
Over the coming decades the sens itivity of pensioner incomes to the economic situation will 
change significantly as a consequence of the reforms presented at the beginning of this 
chapter. The share of funded pens ions in the income packages of  future pensioners is set to 
increase markedly. At the same time, the bul k of funded schemes will be of the defined-
contribution type where investment risks ar e moved to pension savers. In addition, the 
                                                 
96 For further discussion see Sustainability Report 2009 , p. 48. 
97 Ageing Report 2009, pp. 185-187. 
 
EN 125   EN reduced pensions from public PAYG schemes w ill increasingly be calc ulated on life-time 
earnings-related contributions. On present tren ds, only those with ve ry long careers and 
largely unbroken contributory records will obtain rights to a full (maximum) pension. Adequacy will therefore not just depend on the ability of workers to respond positively to the 
new work incentives in pension sy stems. It will also be conti ngent on the ability of labour 
markets to deliver sufficient opportun ities for prolonging average careers. 
The effects of the crisis on pensions being paid from statutory PAYG systems are often 
indirect. The EU labour market  is contracting and an unemployment rate of over 10% is 
projected for the EU in 2010 and 2011. The effect of high unem ployment on pensions is two-
fold. Higher unemployment, along with slower productivity and wage growth, affects both the 
tax and contributory base of pension systems,  reducing the revenues that pension systems rely 
on. Furthermore, long-term unemployment can ne gatively affect the accruals of pension 
entitlements , having an adverse affect  on individual pensions. 
The figure 2.12 presents the impact of a career break due to unemployment lasting one, two or 
three years on future pension income, measured in theoretical replacement rates. In a number 
of Member States, pension income can be reduced  by an equivalent of more than 5% of wages 
due to a three-year unemployment break. 
It is thus vital to monitor the length of th e period of unemployment and actively promote a 
return to the labour market. Past crises have often resulted in older workers, a relatively 
vulnerable group on the labour market  in the best of times, be ing prematurely pushed out of 
the labour market. Given the demographic challenges that PAYG systems are yet to face, it is important that Member States reduce the risk of  older workers being forced into early exit 
pathways from the labour market, including, ea rly retirement, unemployment and disability 
schemes. 
7.3.3. Increases in pensionable ages 
Long-term risks for the sustainability and adequacy  of pensions can be limited if more people 
work more and longer. Member States realise th at, in addition to the need to ease future 
expenditure pressures due to popul ation ageing, they will have to  increase efforts to reduce 
the swollen public debts due to the current cr isis. Discussions on increasing the pensionable 
age are under way in a number of Member States.  
In Latvia,  the government intends to increase the re tirement age from 62 to 65 by 2021. In 
Hungary , the retirement age will be gradua lly raised from 62 to 65 by 2022. In the 
Netherlands , the government has proposed that the pensionable age should rise to 66 years in 
2020 and to 67 years in 2025. Ther e would be special provisi on for people who began their 
careers very young and those who worked  in physically demanding jobs. In Slovenia,  the 
government has disclosed a plan to increase the retirement age from the current 61 for women 
and 63 for men to 65 for both by 2020. Early pensi ons would be accessible from the age of 60 
instead of 58. In Romania,  the government is considering an increase in the retirement age 
from 58 to 60 for women and from 63 to 65 for men by 2014. 
The crisis can be used as an opportunity to carry  out necessary reforms and to give an impetus 
to politically difficult decisions. If increases in retirement age are to be successful, they need 
to be coupled with other measures that give older workers the opportun ity to return to the 
labour market, e.g. offering flexible retirement options, monitoring whether wage differentials 
 
EN 126   EN between younger and older workers do not push out older workers from the labour market, 
changing the habits of employers, or outlawi ng discrimination on the grounds of age.  
7.3.4. Increases in pensionable age for DB sche mes in agreement with social partners 
Just as with PAYG schemes, increased longevity is a major challenge to funded DB schemes 
and early retirement schemes, where compar atively young pension eligibility ages look 
increasingly unaffordable. Increases in pensiona ble age would require more or less formal 
agreements with social partners, usua lly at company or sector level.  
7.3.5. Risks linked to the exposure of fu ture pensioners to market outcomes 
It is important to ensure that projected long- term rates of return on DC pension funds are 
reliable and take into account fluctuations in financial markets. The new statutory DC 
schemes have often been introduced in boom  times and on the basis of upbeat economic 
assumptions. 
DC plan members are not only exposed to falls in financial markets, but unlike DB scheme 
members, can benefit from any investment out-p erformance. Nevertheless, the possibility of 
obtaining high replacement rates has to be consider ed in the long term (so there is a question 
of how far financial markets can outperform the real economy) and discussed against risks of 
volatility. 
The crisis has exposed the vulnerability of funde d schemes to volatility in financial markets 
and highlighted the need for policymakers, regulators and supervisors to promote more 
prudent management of people’s retirement sa vings. With losses ranging from 15% to 35%, 
and with an even greater variation in the capac ity to absorb the shock, differences in pension 
fund designs and investment strate gies clearly matter. From the variation in impacts across the 
Union important lessons can be drawn about  how funded schemes can be improved and 
greater security for pension savers achieve d. Accordingly a new ag enda is emerging for 
necessary changes to funded designs and for sp eedy completion of the unfinished parts of the 
new mandatory schemes (e.g. concerning more s ecure default options, life-styling, charge 
capping, and rules for annuitisation and the pay-out phase). Achieving this will be an important part of rebuildi ng public confidence in funded, privately managed pensions. 
7.4. Policy implications 
The longer-term challenge of ageing is no longe r such a distant scenario. Over the next 
decade the working age population will begin to shrink. Indeed, the setbacks from the crisis 
and the likelihood of lower growth  have thrown this into shar per focus. The balance between 
adequacy and sustainability — the object of a decade of pension reforms — is under pressure 
from the financial and economic crisis. Incr eases achieved in employment rates for older 
workers must now be defended against rising  unemployment. Recovery packages have 
secured the ground for a thriving economy to  supply the income that can pay for  pensions. 
But they have also reduced the hard-won publ ic finance improvement s intended to provide 
room for extra expenditure to address ageing and this lost ground will have to be regained.  
7.4.1. Shorter-term implicatio ns for current schemes 
In general, current systems for those retiring  now have coped quite well. A key issue to 
monitor is the resilience of DB pension sche mes and the mechanisms designed to protect 
 
EN 127   EN scheme members when schemes are underfunded. Box x below raises a few specific key 
shorter-term policy questions that Member States  may want to consider depending on the mix 
of pension schemes in their system. 
Box X. Shorter-term policy questions for specific types of pensions 
There are a number of short-term policy questions Member States may wish to consider, depending on the 
type(s) of pension schemes in their particular system: 
Defined-contribution (DC) pensions 
A key issue is providing good information so that individuals have a rea listic understanding of the rates of return 
and the inherent risks of DC provision both in general and to avoid the risk of hasty actions locking in losses 
during downturns. More flexibility in the timing of the start of the payout phase may also need to be considered 
to avoid investment losses being locked in during the transition phase. 
Defined-benefit (DB) pensions 
Short-term flexibility may be necessary, such as on recove ry plans, to smooth impact s. Adjustment mechanisms 
designed to share risk (e.g. potential changes to the in dexation of benefits) may need to be allowed to operate 
fully for the long-term good. In the absence of formal risk-sharing arrangements, there may also be merit in 
encouraging ad hoc employer/employ ee negotiations to agree burden sharin g, where necessary, to keep DB 
schemes open. In Member States with insurance-st yle fall-back arrangements close monitoring of such 
arrangements is important, to ensure they remain robust. Where there are neither adjustment mechanisms nor 
insurance style fall back arrangements,  there is a need to urgently address DB pension security over the long 
term. 
PAYG pensions 
Reserve funds designed to cope with demographic pre ssures need to remain cred ible. Clear ring-fencing 
supported by public and political sentiment, as well as by rules, may help. Drawing on pension reserve funds in 
difficult times for other purposes reduces their credibility an d needs to be carefully explained. Similarly, where 
public pension schemes have automatic adjustment mechanisms in place to su pport sustainability, any 
interference with the automatic outco me can reduce their credibility and social acceptance and needs careful 
explanation.  
7.4.2. Medium/long-term implic ations of the crisis 
In the future an increasing share of pension inco me is expected to be provided by DC pension 
systems. This is due to two factors. One is th e longstanding shift from DB to DC occupational 
pension provision as employers find the costs and risks of DB increasingly unpalatable. The 
other is the introduction of ne w DC pension schemes often pa rtly replacing PAYG pensions, 
as in many new Member States. Box Y belo w raises a few specific longer term policy 
questions that Member States may want to c onsider, depending on the current mix of pension 
schemes in their overall system and how this is  expected to change in the future. What is, 
however, a common challenge for a ll Member States and a long-term  implication of the crisis 
is to increase overall employment rates a nd employment rates of older workers. 
Box Y. Longer-term policy questions  for specific types of pensions 
There are a number of longer-term po licy questions Member States may wish to consider, depending on the 
type(s) of pension schemes in their particular system: 
DC pensions 
 
EN 128   EN Careful consideration should be given to the appropriate maximum proportion of overall pension income 
expected to come from DC pensions, particularly for the less well-off, who may be less able to absorb the 
inherent risks. And the greater the proportion of DC provision the more important it is that the mainstream 
investment choices for DC schemes should mitigate investment risk and volatility close to retirement (such as by 
taking lifestyling/lifecycling approaches or introduci ng minimum guarantee schemes). The payout phase needs 
to be properly worked out and explained from the outset to minimise leakage of pension savings for other 
purposes (e.g. bequests), otherwise the efficiency of DC pension savings can be seriously compromised. Charges 
need to be kept as low as economically viable and consideration has to be given to intervention to achieve this 
where market failure is apparent. Good information for individuals which clearly explains the risks and manages 
expectations is important both for individual decision-making on saving and retirement issues and for long-term 
public support for such schemes. 
DB pensions 
To have a long-term future as an important element of pension provision, some DB schemes may need to 
consider developing more formal risk sharing arrangements. For individuals, DB provision typically offers much 
less risk than DC pensions. But putting too much risk on employers instead encourages them to close schemes, 
so a sharing of risks may be more a viable long term appr oach that benefits all stakeholders. There may also be a 
need to examine whether there are under lying structural issues in some DB schemes, which may need addressing 
via specific changes, for instance to retirement ages. There may also be me rit in considering the role of DB 
pension schemes in the macro economy and whether such schemes could be made more anti-cyclical, while 
recognising that the issues are complex. 
PAYG pensions 
The financial crisis adds to the challenges to the lo ng-term sustainability of PAYG pension systems and its 
impact will need to be closely monitored. Where underlyi ng structural issues are revealed, further action may be 
needed along the lines of a long-term strategy combining working longer, reducing public debt and pension 
reform. In particular, further measures to support empl oyment in general and to provide opportunities for older 
workers pushed out of employment to return to the labour market may be called for. Public spending, of which 
pensions is a key part, has an important role in supporting economic recovery via its anti-cyclical role. 
Government budget balances are often strained, however, which highlights the issue of how to finance this 
expenditure. Although often politically difficult, it is theref ore important to consider developing this anti-cyclical 
behaviour in social spending even  as the economy enters a boom.  
Current pension systems for thos e retiring today have so far stood up reasonably well to the 
major stress test of the financial crisis. Howe ver, there are still some lessons emerging for 
current systems, perhaps especially so for the design of pension systems in future. The crisis 
has demonstrated the interdependence of the various pension pillars within each Member 
State and underlined that pension funds are an important part of the financial system. It has 
also highlighted the importance of common EU approaches to so lvency and social adequacy. 
Pension systems were of course already unde r pressure from the demographic ageing in 
Europe. The crisis has added to this pressu re, and brought into sharper focus underlying 
structural issues that pension systems are f acing. With different expectations for economic 
growth and investment performance, these issu es are now surfacing and the crisis may offer 
the impetus and political opportunity to see through difficult reforms. 
 
EN 129   EN 8. G OVERNANCE  
The crisis has emphasised the value of po licy coordination under the Social OMC and 
provides a further incentive to exploit fully its potential. Since the autumn of 2008, the Social 
Protection Committee has engaged in a joint exercise on monitoring the social impact of 
the crisis . Member States have provided fresh in formation on emerging social problems and 
on new policy measures. This information has b een collected, analysed, and presented to the 
Council. The exercise has also entailed in-depth examination of specific social policy 
challenges in the context of the crisis, such as minimum income schemes and funded 
pensions. Overall, the exercise has provided new opportunities for mutual learning  and 
exchange of best practice . It has increased the awaren ess and understanding of common 
challenges.  
The need to react swiftly to the crisis has led many Member States to re inforce their capacity 
to detect social problems and to intensify cooperation among social and institutional actors. 
Most Member States have endeavoured to enlarge their knowledge base  on the social impact 
of the crisis, using administra tive data or specific monitoring tools, including new surveys. 
Steps have been taken to improve the timeliness of social statistics drawn from EU SILC or 
the LFS. 
As mentioned before, some Member States have  commissioned ex ante impact evaluations of 
recovery packages (i.e. assessmen t of the likely impact of propos ed measures before they are 
decided). Given that pressure aimed at limiting pub lic expenditures is to be expected in most 
of the Member States in the coming years, the development of an adequate ex ante social 
impact assessment capacity in the context of integrated im pact assessment arrangements  
should be encouraged. Strengthening such 'social'  component can contribute to more effective 
and efficient social policy measures. Applied to  non social policy measures, it can contribute 
to avoiding unintended negative  social impacts and to better exploiting possibilities for 
positive synergies (mainstreaming). In this respect, the Social OMC can be used as a forum for exchanging know how between the Member St ates and between the Member States and 
the European Commission. The latter has recen tly taken initiatives to strengthen its own 
capacity to assess social impacts.  
Countries that can re ly on well-established governance arrangements and practices  have 
benefited from the engagement and mobilisation of stakeholders. Local authorities, social 
partners, and NGOs are on the front line of the cris is. Social partners have often played a key 
role in designing and implementing short-term labour market measures to maintain people in 
jobs. Local authorities and NGOs across Europe ha ve had to meet increased demand for social 
benefits and services while often seeing their own revenues squeezed. Cooperation and 
coordination among all these actors ha s been an invaluable asset.  
In preparation for the EU strategy post-2010, th e Social Protection Committee has established 
a Task Force to review the expe rience of the last decade. The Task Force Report  — Growth 
Jobs and Social Progress  — shows that the benefits of growth have not always been evenly 
distributed, and that poverty and social exclusio n remain a major issue in most EU countries, 
although with substantial di fferences across Europe.  
 
EN 130   EN Drawing on the lessons of the crisis and of te n years of the Lisbon strategy, there will be a 
need to foster sustainable growth along with job creation and social cohesion and 
systematically assess progress of social ou tcomes, including gender equality. To this end, 
reinforcing the Social OMC and increasing its e ffectiveness and visibility is essential.  
An integrated vision for an exit strategy from the crisis and a return to long-term growth in an 
inclusive social market econom y entails continued modernisa tion of social protection to 
deliver the dual objectives of adequacy and sust ainability. This will be crucial for improving 
the functioning and social outcome s of labour markets, thus ensuring the optimal use of our 
human resources through opportun ities and access for all. Employment and social policies 
must continue to be central to the growth and employment agenda in the next decade.  
The start of the post-2010 st rategy coincides with the European Year for combating 
poverty and social exclusion . Raising awareness, reinforci ng partnerships between actors 
and reaching out to new actors will help to generate new impetus. The European Year 2010 
should lead the EU and Member States to strongly reaffirm the commitment made ten years 
ago to make a decisive impact on the erad ication of poverty and social exclusion. 
 
EN 131   EN 9. A NNEXES  
9.1. Indicators 
9.1.1. Definition of the 14 overarching indicators 1a. At-risk-of-poverty rate: Share of persons aged 0+ with an  equivalised disposable income 
below 60% of the national equivalised median income
98. Source: EU-SILC. 
+ Illustrative threshold value: Value of the at-risk-of-pove rty threshold (60% median 
national equivalised income) in PPS for an illustrative househol d type (e.g. single person 
household). Source: EU-SILC. 
1b. Relative median poverty risk gap: Difference between the median equivalised income 
of persons aged 0+ below the at-risk-of povert y threshold and the thre shold itself, expressed 
as a percentage of the at-risk-of- poverty threshold. Source: EU-SILC. 
2. S80/S20: Ratio of total income received by the 20%  of the country’s population with the 
highest income (top quintile) to that received by the 20% of the country’s population with the 
lowest income (lowest quintile ). Income must be understood as equivalised disposable 
income. Source: EU-SILC. 
3. Healthy life expectancy Number of years that a person at birth, at 45, and at 65 is still 
expected to live in a healthy condition (also ca lled disability- free life expectancy). To be 
interpreted jointly with life expectancy. Source: EUROSTAT. 
4. Early school-leavers: Share of persons aged 18 to 24 who have only lower secondary 
education (their highest level of education or  training is 0, 1 or 2 according to the 1997 
International Standard Classification of E ducation — ISCED 97) and have not received 
education or training in the four w eeks preceding the survey. Source: LFS. 
5. People living in jobless households: Proportion of people living in jobless households, 
expressed as a share of all people in the same age group99. This indicator should be analysed 
in the light of context indicator  No 8: jobless households by  main household types. Source: 
LFS. 
6. Projected total public  social expenditure: Age-related projections of total public social 
expenditure (e.g. pensions, h ealthcare, long-term care, education and unemployment 
transfers), current level (% of GDP) and project ed change in share of GDP (in percentage 
points) (2007-2020; 2007-2060). 
http://ec.europa.eu/economy_fin ance/publications/publication14994_en.pdf  (Table A 134 – 
The cost of ageing overview) 
                                                 
98 Equivalised median income  is defined as the household’s total disposable income divided by its 
‘equivalent size’, to take account of the size and composition of the household, and is attributed to each household member (including children). Equivalisation is on the basis of the OECD modified scale. 
99 Students aged 18-24 who live in households composed solely of students are not counted in either the 
numerator or denominator. 
 
EN 132   EN 7a. Median relative income of elderly people: Median equivalised in come of people aged 
65+ as a ratio of income of pe ople aged 0-64. Source: EU-SILC. 
7b. Aggregate replacement ratio: Median individual pensions of  65-74 year-olds relative to 
median individual earnings of 50-59 year-olds,  excluding other social benefits. Source: EU-
SILC. 
8. Self-reported unmet need for medical care: Total self-reported unmet need for medical 
care for the following three reasons: financial barriers + waiting times + too far to travel.  
+ Care utilisation: To be analysed together with care utilisation defined as the number of 
visits to a doctor (GP or specialist) during th e last 12 months. Source: EU-SILC subject to 
adjustment in the future. 
9. At-risk-of-poverty rate anchored at a fixed moment in time (2005): Share of persons 
aged 0+ with an equivalised disposable in come below the at-ris k-of-poverty threshold 
calculated in the year 2005 (1st EU-SILC income  reference year for all 25 EU countries), 
adjusted for inflation over the years. Source: EU-SILC. 
10. Employment rate of older workers: Persons in employment in the 55–59 and 60–64 age 
groups as a proportion of the total populat ion in the same age group. Source: LFS. 
11. In-work poverty risk: Individuals who are cl assified as employed100 (distinguishing 
between ‘wage and salary employment plus  self-employment’ and ‘wage and salary 
employment’ only) and who are at risk of poverty. 
This indicator needs to be analysed according to personal, job and hous ehold characteristics. 
It should also be analysed in comparison w ith the poverty risk faced by the unemployed and 
the inactive. Source: EU-SILC. 
12. Activity rate: Share of employed and unemployed people in the total population of 
working age, 15-64. Source: LFS. 
13. Regional disparities — coefficient of variation of employment rates: Standard 
deviation101 of regional employment rates divided by the weighted national average (15-64 
age group). (NUTS II). Source: LFS. 
14. Total health expenditure per capita: Total health expenditure pe r capita in PPP. Source: 
EUROSTAT based on system of health accounts (SHA) data. 
                                                 
100 Individuals classified as employed according to most frequent activity status. The most frequent activity 
status is defined as the status that individuals declare having for more than half the number of months in the calendar year. 
101 Standard deviation measures how, on average, the situation in regions differs from the national average. 
As a complement to the indicator, a graph show ing max/min/average per country is presented. 
Possible alternative measures:   
Regional disparities — underperforming regions . Source LFS 
1. Share of underperforming regions in terms of employment and unemployment (in relation to all 
regions and to the working age popu lation/labour force) (NUTS II).  
2. Differential between average employment/unemployment in underperforming regions and the national average for employment/unemployment (NUTS II).  Thresholds to be applied: 90% and 150% 
of the national average rates for employment and une mployment, respectively. (An extra column with 
the national employment and unemployment rates would be included). 
 
EN 133   EN 9.1.2. Context information 
The overarching indicators have to be assessed in the light of  key context information and by 
referring to past, and where relevant, future  trends. The list of context information is 
indicative and leaves room to other background in formation that would be most relevant to 
frame and understand better the na tional socio-economic context. 
Context 1: Growth rate of GDP volume - percentage change over previous year . Source: 
Eurostat, Annual national accounts; forecast for 2009, 2010, 2011. 
Context 1: GDP per capita in Purchasing Power Standards (PPS) - (EU-27 = 100)  
Source: Eurostat, Annual national accounts; forecast for 2009, 2010, 2011. 
Context 2a: Employment rate (%  of population aged 15-64) - Source: Eurostat - Labour 
Force Survey, Annual averages. 
Context 2b: Unemployment rate (% of labour force aged 15+) - Source: Eurostat - LFS 
adjusted series, Annual average. 
Context 2c: Youth unemployment rate (% of labour force aged 15-24) - Source: Eurostat 
- LFS adjusted series, Annual average. 
Context 2d: Long-term unemployment rate by gender, selected years (% of the labour 
force 15+) - Source: Eurostat - Labour Force Survey, Annual averages.  
Context 4: Old age dependency ratio (current and projected) - ratio between the total 
number of people aged 65 and over and the number of persons  of working age (from 15 to 
64). Source: Eurostat - EUROPOP2008 Trend scenario - baseline variant.  
Context 5a: Distribution of households by age  and household type (private/institutional). 
Source: Eurostat Census data collection 2000-01.  
Context 5b: Population living in private ho useholds by household type, 2008 (percentage 
of total population). Source: EU-SILC.  
Context 6a: General government debt - Gene ral government consolidated gross debt as 
a percentage of GDP. Source: Eurostat - General Government data (2000 to 2009) and 
ECFIN forecasts (2010-2011).  
Context 6b: Projected evolution of de bt levels up to 2050 (in % of GDP). Source: 
Commission services, 2005/06 updated st ability and convergence programmes. 
Context 7a: Social protection benefits by gr oup of functions (as a percentage of total 
benefits). Source: Eurostat ESPROSS.  
Context 7b: Social protection benefits by gr oup of functions (as a percentage of GDP). 
Source: Eurostat ESPROSS.  
Context 8a: Adults aged 18-59 living in jobless households by household types. Source: 
Eurostat - European Labour Force Survey 2008, Annual results.  
 
EN 134   EN Context 8b: Children aged 0-17 living in jobless households by household types. Source: 
Eurostat - European Labour Force Survey 2008, Annual results.  
Context 9a - Unemployment traps, 9b - Inacti vity Trap at 67% of Average Wage, 9c - 
Inactivity traps. Source: Joint Commission -OECD pr oject using tax-benefit Models. 
Context 10: Net income of social assistance rec ipients as % of the at-risk of poverty rate 
threshold for 3 jobless households types. This indicator refers to th e income of people living 
in households that only rely on "last resort" social assistance benefits (including related 
housing benefits) and for which no other income stream is available (from other social 
protection benefits – e.g. unemployment or disability schemes – or from work). The aim of such an indicator is to evaluate if the safety  nets provided to those households most excluded 
from the labour market are sufficient to lift people above the risk-o f-poverty threshold. This 
indicator is calculated on the basis of the ta x-benefit models developed jointly by the OECD 
and the European Commission. It is only calc ulated for Countries where non-categorical 
social benefits are in place and for 3 jobless ho usehold types: single, lone parent, 2 children 
and couple with 2 children. This indicator is  especially relevant when analysing MWP 
indicators. Source: Joint EC-O ECD project using OECD tax-be nefit models, and Eurostat. 
Context 11: At-risk-of-poverty rate before so cial transfers by gender and selected age 
groups. This indicator is meant to compare the observed risk of poverty with a hypothetical 
measure of a risk of poverty in absence of all so cial transfers (other than pensions) all things 
being kept equal. In particul ar, household and labour market structure are kept unchanged. 
This measure does not take into account othe r types of transfers that have an impact on 
household disposable income such as transf ers in kind and tax rebates.Source: EU-SILC.  
Context 12: Change in Theoretical replaceme nt Rates for a worker retiring at 65 after 
40 years. Change in the theoretical level of income from pensions at the moment of take-up 
related to the income from work  in the last year before re tirement for a hypothetical worker 
(base case), percentage points, 2004-2050, with information on the type of pension scheme 
(DB, DC or NDC) and changes in the public pension expenditure as a share of GDP, 2004-
2050. This information can only collectively form the indicator called Projected theoretical 
replacement ratio. Results relate to current and projected, gross (public and private) and total 
net replacement rates, and should be accompan ied by information on representativeness and 
assumptions (contributio n rates and coverage ra te, public and private) . Specific assumptions 
agreed in the ISG. For furthe r details, see 2006 report on Repl acement Rates. Source: ISG and 
AWG 
9.1.3. New indicators adopted in the field of social inclusion: 
In 2009, the Social Protection Committee adopted ne w indicators for the monitoring of social 
inclusion objectives in the field of material deprivation and housing. 
1. Material deprivation rate: Share of population living in households lacking at least 3 
items among the following 9 items: The househol d could not afford: i) to face unexpected 
expenses, ii) one week annual holiday away from  home, iii) to pay for arrears (mortgage or 
rent, utility bills or hire purchase instalments) , iv) a meal with meat, chicken or fish every 
second day, v) to keep home ad equately warm, or could not affo rd (even if want ed to): vi) a 
washing machine, vii) a colour TV, viii) a telephone, ix) a personal car. 
 
EN 135   EN 2. Depth of material deprivation: Unweighted mean of the number of items lacked by the 
population concerned out of the nine items retained for the definition of the “material 
deprivation” indicator (s ee above, indicator SI-P8). 
In July 2009, 2 secondary indicators and 2 contex t information were adopt ed in the field of 
housing, but further work, including further improve ment of the quality of the data is needed 
before a primary indicator can be identified. 
3. Housing costs: Percentage of the popul ation living in a household where total housing 
costs (net of housing allowances) represent more  than 40% of the total disposable household 
income (net of housing allowances). 
Housing costs include mortgage interest payments  (net of any tax relief) for owners and rent 
payments, gross of housing benefits for renter s, housing benefits for rent free households. 
They also include structural insurance, manda tory services and charges (sewage removal, 
refuse removal, etc.), regular maintenance and repairs, taxes, and the cost of utilities (water, electricity, gas and heating). They do not includ e capital repayment for mortgage holders.  
Housing allowances include rent benefits
102 and benefits to owner-occupiers103. 
4. Overcrowding: Percentage of people living in an overcrowded household 
- All households104. 
- excluding single households.  
The person is considered as living in an overc rowded household if the household doesn't have 
at its disposal at least:  
- one room for the household; 
- one room for each couple; - one room for each single person aged 18+; - one room - for two single people of the sa me sex between 12 and 17 years of age;  
- one room - for each single person of different sex between 12 and 17 years of age;  - one room - for two people under 12 years of age.. 
5. Housing deprivation by item:  
Percentage of the population deprived of each  housing deprivation item, and by number of 
items. The following housing deprivation item s are considered: - Leaking roof, damp 
walls/floors/foundations, or rot in window frames  or floors; - no bath or shower in the 
dwelling; - no indoor flushing toilet for the so le use of the household; - Dwelling too dark.
  Breakdowns: sex, age (0-17; 18-64; 65+ ); for the 4 items only: poor/non-poor.  
                                                
 
102 Rent benefit: a current means-tested transfer granted by public authority to tenants, temporarily or on a 
long-term basis, to help them with rent costs. 
103 Benefit to owner occupier: a means- tested transfer by public authority  to owner-occupiers to alleviate 
their current housing costs; in practice, often help with mortgage reimbursements. 
104 The calculation includes single households and considers them as deprived if they live in a studio with a 
bedroom not separated from the living room. This  calculation based on all households should 
systematically be used if the overcrowding criteria is analysed together with other housing quality 
criteria. 
 
EN 136   EN 6. Share of housing costs in total disposable household income: Median of the distribution 
among individuals of the share of housing co sts (net of housing allowances) in total 
disposable income (net of housing allowances)  - median for the total population  
Breakdowns: sex, age (0-17; 18-64; 65+ ); poor/non-poor; degree of urbanisation  
 
EN 137   EN 9.2. Data sources 
9.2.1. Indicators of income and living conditions: EU-SILC EU-SILC data are available for 25 EU countri es since 2005, Bulgaria and Romania have 
launched SILC in 2006. The EU-SILC instrument  has been launched on the basis of the 
Regulation (EC) No 1177/2003 of the European Parliament and of the Council of 16 June 
2003 concerning Community statistics on income and living conditions. Commission Regulation (EC) No 1983/2003 of 7 November  2003, implementing Regulation (EC) No 
1177/2003 of the European Parliament and the Council concerning Community statistics on 
income and living conditions (EU-SILC) as concerns the lists of target primary variables established a common framework for the system atic production of Community statistics on 
income and living conditions. In addition to those regulations mentioned above there are 
various other implementing regulations, concer ning e.g. definitions and updates, fieldwork 
aspects and imputation procedures and quality re ports as well as annua l regulations setting 
down lists of secondary target variables. In June 2006, the Social Protection Committee 
adopted a new set of common indi cators for the social protection and social inclusion process. 
The EU-SILC definitions of total household gro ss and disposable income and the different 
income components keep as clos e as possible to the internati onal recommendations of the UN 
‘Canberra Manual’. A key objectiv e of EU-SILC is to deliver timely, robust and comparable 
data on total disposable hous ehold income, total disposab le household income before 
transfers, total gross income and gross income  at component level (in the ECHP, the income 
components were recorded net). This objective w ill be reached in two st eps, in that Member 
States have been allowed to postpone the delivery of gross income at component level and 
total household gross income data until after the first year of operation.  
Although certain countries (e.g. Denmark) are already able to supply income including 
imputed rent — i.e. the money that one saves on full (market) rent by living in one’s own 
accommodation or in accommodation rented at a price lower than the market rent — for 
reasons of comparability, the income defin ition underlying the calculation of indicators 
currently excludes imputed rent. This could have a distorting e ffect in comparisons between 
countries, or between population sub-groups, when  accommodation tenure status varies. This 
effect may be particularly apparent for the el derly who may have been able to accumulate 
wealth in the form of housing assets. In the st atistical annex, data for Denmark are therefore 
shown both with and without imputed rent, as an  illustration of the impact of this income 
component on the results. Once imputed rent is ta ken into account, the at -risk-of-poverty rate 
falls for people aged 65 and over, the inactive other than pensioners and those living in owner-occupied accommodation.  
It should also be noted that the definition currently used for income excludes other non-
monetary income components: the valu e of goods produced for own consumption
105 and non-
cash employee income. These components, together  with imputed rent data are available for 
all countries from the SILC (2007) exercise on wards; Eurostat is currently assessing the 
quality and comparability of these components.  In 2010, the Indicator's Sub-Group of the 
                                                 
105 Before the introduction of EU-SILC in the new Member States, the value of goods produced for own 
consumption was included in the calculation of th e EU indicators estimated on the basis of national 
sources. This transitional arrangement  was intended to take account of the potentially significant impact 
of this component on income distribution in these countries. 
 
EN 138   EN Social Protection Committee will discuss the po ssible inclusion of each  of them in the 
definition of income underlying the OMC indicators. 
The reference year for the data is the year to  which the income information refers (i.e. the 
‘income year’), which in most cases differs from the survey year in which the data were collected. Accordingly, 2006 data refer to the in come situation of the population in 2005, even 
if the information was collected in 2006. EU a ggregates are computed as population-weighted 
averages of available national values.  
Limitations 
The limited sample size for certain data sources us ed for the collection of income data and the 
specific difficulties of collecting accurate info rmation on disposable income directly from 
households or through administrative records rais e certain concerns as regards data quality. 
This is particularly the case for informati on on income at the two ends of the income 
distribution. 
Furthermore, household surveys do not cove r persons living in collective households, 
homeless persons or other di fficult-to-reach groups.  
It must also be acknowledged that self-employm ent income is difficult to collect, whatever 
the data source. It must also be kept in mind that the difficulty in recording income from the 
informal economy can introduce a bias in in come distribution as measured by surveys. 
Finally, while it is considered to be the best  basis for such analyses, current income is 
acknowledged to be an imperfect measure of consumption capabilities and welfare, as, among 
other things, it does not reflect access to credit, access to accumulated savings or ability to liquidate accumulated assets, informal comm unity support arrangements, aspects of non-
monetary deprivation, differential pricing, etc. These factors may be of  particular relevance 
for persons at the lower end of the income distribution. The bottom 10% of the income 
distribution should not, therefore,  necessarily be inte rpreted as being the bottom 10% in terms 
of living standards. This is why reference is ma de to the ‘at-risk-of-poverty’ rate rather than 
simply the poverty rate.  
Confidence intervals 
Indicators are estimated values based on a samp le drawn from the target population and thus 
are affected by sampling error. Statistical theo ry provides us with tools for calculating 
confidence intervals in which the population value lies with a high probability. The 
confidence intervals are centred around the estim ated values reported and their length is a 
measure of the precision of these estimates. The precision depends on the design of the survey 
and can thus vary between countries. However,  the EU-SILC Regulati on provides for national 
samples to be designed so as to achieve a confidence interval  of +/-1% around  the estimated 
value of the total at-ris k-of-poverty rate. Eurostat  is computing these inte rvals for a number of 
indicators and exact values will be reported in  EU quality reports. First computations show 
that the confidence intervals ar ound the total at-risk-o f-poverty rate are of the order of +/-
0.8%. For the S80/S20 income quintile share ratio, the confidence intervals are of the order of 
+/-0.2. For the relative median at -risk-of-poverty gap, they are of  the order of +/-1.7. For the 
Gini coefficient, they are of the order of +/- 0.9. These indications of precision must be taken 
into account when interpreting the data. 
 
EN 139   EN 9.2.2. LFS: the European Union Labour Force Survey 
The European Union Labour Force Survey (LFS ) is the EU's harmonised survey on labour 
market developments. The survey has been car ried out since 1983 in the EU Members States, 
with some states providing quart erly results from a continuous labour force survey, and others 
conducting a single annual survey in the spri ng. From 2005, all EU Member States have 
conducted a quarterly survey. If not mentioned otherwise, the results based on the LFS refer 
to surveys conducted in the spring ('second quart er' in all countries except for France and 
Austria, which is 'first quarter') of each year. It also provides data fo r Bulgaria, Croatia and 
Romania. 
The Annual Averages of Labour Fo rce Data series is a harmonise d, consistent series of annual 
averages of quarterly results on employment statistics based on the LFS, completed through 
estimates when quarterly data are not available.  It covers all the EU-15 (for the period from 
1991 to present) and all new Member States a nd Candidate Countries (s ince 1996 or later, 
depending on data availability) except the Former Yugoslav Republic of Macedonia. The 
Annual Averages of Labour Force Data consist of two series: 1) population, employment and unemployment, and 2) employment by economi c activity and employment status. The first 
series is based mainly on the EU LFS. Data c overs the population living in private households 
only (collective households are excluded) and refers to the place of residence (household 
residence concept). They ar e broken down by gender and ag gregate age group (15–24, 25–54, 
55–64 and 15–64). Unemployment data  is also broken down by job search duration (less than 
6 months, 6–11, 12–23, 24 months or  more). The second series is based on the ESA 1995 
national accounts employment data. Data covers  all people employed in resident producer 
units (domestic concept), including people liv ing in collective households. They are broken 
down by sex, working-time status (full-tim e/part-time) and contract status 
(permanent/temporary) using LFS distributions . All key employment indicators presented in 
this document are based on the Annual Averages of Labour Force Data series. They represent 
yearly averages unless stated otherwise. Where the Annual Averages of Labour Force Data series does not provide the releva nt breakdowns, the original LFS data has been used for this 
report. 
9.2.3. Age-related expenditure projections 
Long-term budgetary projections were prep ared in 2009 by the Economic Policy Committee 
and the European Commission (DG ECFIN) — see European Policy Committee and 
European Commission (2009) , 'The 2009 Ageing Report: Economic and budgetary 
projections for the EU-27 Member Stat es (2008-2060)', European Economy 2/2009  
The projections are made on the basis of a common population pr ojection and agreed 
common underlying economic a ssumptions that have been endorsed by the EPC. The 
projections are made on the basis of ‘no policy change’, i.e. onl y reflecting enacted legislation 
but not possible future policy changes (althoug h account is taken of provisions in enacted 
legislation that enter into force over time). Th e pension projections ar e made on the basis of 
legislation enacted by mid-2008. They are also made  on the basis of the current behaviour of 
economic agents, without assuming any future ch anges in behaviour over time: for example, 
this is reflected in the assumptions for part icipation rates, which are based on the most 
recently observed trends by age and gender. While the underlying assumptions have been 
made by applying a common methodology uniforml y to all Member States, for several 
countries adjustments have been made to avoid an overly mechanical ap proach that leads to 
economically unsound outcomes and to take due  account of significant country-specific 
 
EN 140   EN circumstances. The pension projections were ma de using the models of  national authorities, 
and thus reflect the current inst itutional features of national pension systems. In contrast, the 
projections for healthcare, long-term care, ed ucation and unemployment transfers were made 
using common models developed by the Europe an Commission in clos e cooperation with the 
EPC and its Working Group on Ageing Populat ions. The projection results show the 
combined impact of expected changes in the size and demographic structure of the 
population, projected macroeconomic developmen ts and assumed neutral evolution in the 
health status of the population in each Member State of the European Union. 
Pension expenditure 
The ‘pension expenditure’ aggregate accordin g to the ESSPROS definition, goes beyond 
public expenditure and also includes expendit ure by private social protection schemes. 
‘Pension expenditure’ is the sum of seven different  categories of benef its, as defined in the 
1996 ESSPROS Manual: disability pe nsion, early retirement bene fit due to re duced capacity 
to work, old-age pension, anticipated old-age pension, partial pension, survivors’ pension and 
early retirement benefit for labour market reas ons. Some of these benefits (for example, 
disability pensions) may be paid to people who have not reached the stan dard retirement age. 
Replacement rates 
The figures for current and prospective pension replacement rates are based on the 
methodology developed by the Indicators Sub-Gr oup of the Social Protection Committee. The 
results are based on the base line assumption of a hypothetical  person (male where gender 
matters) retiring at the age of 65 after a 40-year full-time worki ng career with a flat earnings 
profile at average earnings with  contributions to the most ge neral public pension scheme as 
well as to occupational and private pens ion schemes for some Member States.  
The replacement rate represents the individua l pension income during the first year of 
retirement relative to the individual income  received during the year preceding retirement. 
Calculations are by the Member States. 
Healthcare expenditure — WHO Hea lth for All database (www.who.int\nha) 
This information is based on national hea lth accounts (NHAs) co llected within an 
internationally recognised framework. NHAs depict the financing and spending flows 
recorded in the operation of a health system. In  future, the System of Health Accounts (SHA) 
will contain uniform data for Eurostat, the OE CD and the WHO. In the meantime, the WHO 
database is the only one to cover all Member States.  
About 100 countries have either produced full national health accounts or  report expenditure 
on health to the OECD. Standa rd accounting estimation and ex trapolation techniques have 
been used to provide time series (1998-2004). Mi nistries of Health have responded to the draft 
updates sent for their inputs and comments. The pr incipal international re ferences used are: 
the International Monetary Fund (IMF), Govern ment Finance Statistics and International 
Financial Statistics; OECD health data; and the United Nations Nationa l Accounts Statistics. 
National sources include: national health accounts reports, public expenditure reports, 
statistical yearbooks and other periodicals, budgetary documents, natio nal accounts reports, 
central bank reports, non-governmental organi sation reports, academic studies, reports and 
data provided by central statistical offices and ministries, and statisti cal data on official 
websites. 
 
EN 141   EN 9.3. Annex to part 6 on Health 
Figure A1 
Total expenditure on health per capita PPS, 2007 or latest available
0500100015002000250030003500400045005000
Romania
Bulgaria
Latvia
PolandEstonia
Lithuania
SlovakiaHungary
CzechRepublic
Cyprus
Slovenia
Portugal
Spain
FinlandItaly
Greece
UnitedKingdom
Sweden
DenmarkIreland
France
Belgium
Germany
Austria
Netherlands
LuxembourgPer capita PPS
 
Source: Eurostat for all, except Ireland, Greece, Italy and UK. Source for these four Member States: 
OECD Health data. Malta: non available. 
 
EN 142   EN  
Figure A2 
Total expenditure on health as a % of GDP
2,03,04,05,06,07,08,09,010,011,012,0
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
EU Member States% of GDP
1980 1985 1990 1995 2000 2005 2006 2007
 
Source: OECD Health data and WHO Health for All databases 
 
EN 143   EN Table A1: Total expenditure on health as a percentage of GDP, 1960-2007 
1960 1965 1970 1975 1980 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
BE 3,9 5,6 6,3 7,0 7,1 7,3 7,3 7,2 7,2 7,6 7,7 7,9 7,7 8,2 8,4 8,3 8,4 8,6 8,6 8,7 9,0 10,2 10,5 10,3 10,0 10,2
BG 5,2 5,2 6 6,2 7,2 7,4 7,6 7,5 7,7
CZ 4 , 74 , 95 , 16 , 76 , 97 , 06 , 76 , 76 , 66 , 66 , 56 , 77 , 17 , 47 , 27 , 16 , 96 , 8
DK 8 , 78 , 98 , 58 , 28 , 58 , 68 , 58 , 38 , 28 , 38 , 68 , 48 , 18 , 28 , 28 , 38 , 58 , 38 , 68 , 89 , 39 , 59 , 59 , 69 , 8
DE 6,0 8,4 8,4 8,8 8,7 8,8 8,9 8,3 8,3 9,6 9,6 9,8 10,1 10,4 10,2 10,2 10,3 10,3 10,4 10,6 10,8 10,6 10,7 10,5 10,4
EE 5,5 5,8 5,3 4,9 4,9 5 5,2 5
IE 3 , 74 , 05 , 17 , 38 , 37 , 57 , 47 , 16 , 76 , 36 , 16 , 57 , 06 , 96 , 96 , 76 , 56 , 46 , 26 , 26 , 36 , 97 , 17 , 37 , 57 , 37 , 17 , 6
EL 5 , 4 5 , 9 6 , 65 , 96 , 56 , 66 , 47 , 07 , 98 , 68 , 68 , 68 , 48 , 48 , 67 , 98 , 89 , 19 , 08 , 79 , 49 , 59 , 6
ES 1 , 52 , 53 , 54 , 65 , 35 , 45 , 35 , 46 , 06 , 26 , 56 , 77 , 17 , 47 , 37 , 47 , 57 , 37 , 37 , 37 , 27 , 27 , 38 , 18 , 28 , 38 , 48 , 5
FR 3,8 4,7 5,4 6,4 7,0 8,0 8,4 8,6 8,9 9,3 9,3 10,4 10,4 10,2 10,1 10,1 10,1 10,2 10,5 10,9 11,0 11,1 11,0 11,0
IT 7 , 37 , 37 , 77 , 98 , 07 , 97 , 67 , 37 , 47 , 77 , 77 , 88 , 18 , 28 , 38 , 38 , 78 , 99 , 08 , 7
CY 4,5 5,6 5,6 5,7 5,7 6,1 6,5 6,3 6,1
LV 2,5 6,3 6,4 6 6,1 6,2 6,1 6,8 6,4
LT 3,3 6,1 6,2 6,5 6,3 6,4 6,5 5,7 5,9
LU 3 , 14 , 35 , 25 , 25 , 05 , 55 , 35 , 25 , 45 , 15 , 45 , 55 , 35 , 65 , 75 , 65 , 75 , 85 , 86 , 46 , 87 , 58 , 17 , 77 , 3
HU 7 , 07 , 57 , 68 , 17 , 37 , 06 , 87 , 17 , 26 , 97 , 27 , 68 , 38 , 08 , 38 , 17 , 4
MT 6 , 66 , 66 , 87 , 27 , 88 , 18 , 28 , 4
NL 7 , 07 , 47 , 37 , 47 , 67 , 67 , 98 , 08 , 28 , 48 , 58 , 38 , 38 , 27 , 98 , 18 , 18 , 08 , 38 , 99 , 8 1 0 , 09 , 89 , 79 , 8
AT 4,3 4,6 5,2 6,9 7,4 6,4 6,7 6,8 6,8 7,0 8,3 8,4 8,7 9,3 9,6 9,5 9,5 9,8 10,0 10,1 9,9 10,1 10,1 10,3 10,4 10,4 10,2 10,1
PL 4 , 86 , 06 , 15 , 85 , 55 , 55 , 95 , 65 , 95 , 75 , 55 , 96 , 36 , 26 , 26 , 26 , 26 , 4
PT 2,5 5,1 5,3 5,7 6,3 6,2 6,4 5,9 5,9 6,4 6,6 6,9 7,0 7,8 8,0 8,0 8,0 8,2 8,8 8,8 9,0 9,7 10,0 10,2 9,9
RO 2,9 4,4 4,5 4,6 4,7 5,1 5,4 4,9 5,5
SI 5,6 8 8 8,4 8,7 8,7 8,8 8,5 8,5
SK 5 , 85 , 75 , 85 , 55 , 55 , 65 , 87 , 27 , 07 , 37 , 7
FI 3 , 84 , 85 , 56 , 26 , 37 , 17 , 27 , 37 , 17 , 17 , 78 , 89 , 08 , 27 , 77 , 98 , 07 , 67 , 47 , 47 , 27 , 47 , 88 , 18 , 28 , 58 , 38 , 2
SE 6 , 87 , 58 , 98 , 58 , 38 , 38 , 28 , 28 , 28 , 08 , 28 , 48 , 08 , 08 , 28 , 18 , 28 , 38 , 29 , 09 , 39 , 49 , 29 , 29 , 19 , 1
UK 3 , 94 , 14 , 55 , 45 , 65 , 85 , 85 , 95 , 85 , 85 , 96 , 36 , 86 , 86 , 96 , 86 , 86 , 66 , 76 , 97 , 07 , 37 , 67 , 88 , 18 , 28 , 58 , 4  
Source: OECD Health data and WHO Health for All databases 
 
EN 144   EN Figures A3: GDP growth rates versus growth  rates of total expenditure on health 106 
Austria
-10,0-5,00,05,010,015,020,025,030,035,040,0
1961
1964
1967
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
GDP grow th THE grow thBelgium
0,05,010,015,020,025,030,035,040,045,0
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
2004
2007
GDP grow th THE grow th
 Ge r m a ny
-5,00,05,010,015,020,025,0
1971
19731975197719791981
1983
19851987
1989
1991
1993
199519971999200120032005
2007
GDP grow th THE grow th 
Greece
-5,00,05,010,015,020,025,030,035,0
1961
1964
1967
19701973
1976
1979
1982
19851988
1991
1994
1997
2000
2003
2006
GDP grow th THE grow thHungary
-5,00,05,010,015,020,025,030,035,0
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
GDP grow th THE grow thIreland
0,05,010,015,020,025,030,035,040,045,0
1961
1964
1967
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
GDP grow th THE grow th 
                                                 
106 The relevant information (i.e. total health expenditure in absolute values) is not readily available for the eight Member Stat es missing in these graphs, or is just available for 
very short time series. 
 
EN 145   EN Italy
0,05,010,015,020,025,030,0
1971
19731975197719791981
1983
19851987
1989
1991
1993
199519971999200120032005
2007
GDP grow th THE grow thLuxembourg
-10,0-5,00,05,010,015,020,025,030,0
1971
1974
1977
1980
1983
198
6
1989
1992
1995
1998
2001
2004
2007
GDP grow th THE grow thThe Netherlands
0,02,04,06,08,010,012,014,016,018,0
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
GDP grow th THE grow th 
Poland
0,010,020,030,040,050,060,070,080,090,0
1991
1992199319941995199619971998
1999
20002001200220032004200520062007
GDP grow th THE grow thPortugal
0,010,020,030,040,050,060,0
1971
19731975197719791981
1983
19851987
1989
1991
1993
199519971999200120032005
2007
GDP grow th THE grow thSlovakia
0,05,010,015,020,025,030,035,040,0
1993
1994
1995
19961997199819992000
2001
20022003
2004
200520062007
GDP grow th THE grow th 
 
EN 146   EN Spain
0,05,010,015,020,025,030,035,0
1961
1964
1967
19701973
1976
1979
1982
19851988
1991
1994
1997
2000
2003
2006
GDP grow th THE grow thSweden
-5,00,05,010,015,020,025,0
1961
1964
1967
1970
1973
19761979
1982
1985
1988
1991
1994
19972000
2003
2006
GDP grow th THE grow thUK 
0,05,010,015,020,025,030,035,0
1961
196419671970
1973
19761979198219851988
1991
1994
1997200020032006
GDP grow th THE grow th 
Source: OECD Health data, WHO Health for All databases and EC computations  
 
EN 147   EN Figure A4 
Public expenditure on health as % of GDP, 1997-2007
012345678910
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 UK1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
 
Source: OECD Health data and WHO Health for All databases 
 
EN 148   EN Figure A5 
Public expenditure on health as % of GDP, 1980-2007
012345678910
BE
BG
CZ
DK
DE
EE
IE
EL
ES
FR
IT
CY
LV
LT
LU
HU
MT
NL
AT
PLPT
RO
SI
SK
FI
SE
UK
1980 1985 1990 1995 2000 2005 2006 2007
 
Source: OECD Health data and WHO Health for All databases 
 
EN 149   EN Table A2: Public expenditure on health as a % of GDP, 1960-2007 
1960 1965 1970 1975 1980 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
BE 6,5 6,7 6 , 46 , 56 , 66 , 76 , 76 , 7 76 , 8
BG 3,6 3,9 3,6 4 4,4 4,6 4,6 4,7
CZ 4,6 4,8 4,9 6,4 6,5 6,4 6,1 6 6 5,9 5,9 6 6,4 6,7 6,4 6,3 6,1 5,8
DK 7 , 57 , 97 , 36 , 97 , 17 , 37 , 16 , 96 , 96 , 97 , 16 , 96 , 76 , 86 , 76 , 8 76 , 87 , 17 , 37 , 87 , 97 , 98 , 18 , 2
DE 4,4 6,6 6,6 6,8 6,7 6,8 6,9 6,3 6,3 7,8 7,7 7,9 8,2 8,5 8,3 8,2 8,2 8,2 8,3 8,4 8,5 8,1 8,2 8,1 8
EE 4,7 4,7 4,1 3,8 3,7 3,9 3,9 3,8
IE 2 , 83 , 14 , 15 , 86 , 85 , 75 , 65 , 24 , 84 , 64 , 44 , 7 55 , 1 54 , 84 , 74 , 74 , 64 , 64 , 65 , 15 , 45 , 75 , 95 , 65 , 56 , 1
EL 2,3 3,3 4 3,2 3,6 3,5 3,4 3,8 4,3 4,3 4,5 4,5 4,5 4,4 4,6 4,7 5,3 5,3 5,4 5,1 5,7 5,9 5,8
ES 0 , 91 , 32 , 33 , 64 , 24 , 34 , 24 , 34 , 74 , 85 , 15 , 25 , 55 , 75 , 55 , 45 , 45 , 35 , 35 , 35 , 25 , 25 , 25 , 75 , 85 , 8 66 , 1
FR 2,4 3,4 4,1 5 5,6 6,3 6,4 6,6 6,8 7,1 7,1 8,3 8,3 8,1 8,1 8,1 8 8,1 8,4 8,6 8,7 8,8 8,7 8,7
IT 5,7 5,7 6,1 6,3 6,2 5,9 5,6 5,1 5,2 5,4 5,4 5,5 5,8 6,1 6,2 6,2 6,6 6,8 6,9 6,7
CY 2,3 2,4 2,4 2,4 2,7 3,1 2,8 2,7
LV 3 , 73 , 73 , 33 , 13 , 23 , 2 43 , 8
LT 4,6 4,7 4,5 4,6 4,8 5 3,9 4
LU 2 , 8 44 , 84 , 64 , 55 , 14 , 94 , 8 54 , 8 55 , 14 , 95 , 15 , 25 , 25 , 25 , 25 , 25 , 66 , 16 , 87 , 36 , 96 , 6
HU 6 , 36 , 66 , 67 , 16 , 15 , 75 , 55 , 35 , 24 , 94 , 95 , 3 65 , 8 65 , 95 , 2
MT 4,6 4,6 4,9 5,2 5,8 6,1 6,2 6,5
NL 4,8 5,1 5,2 5,1 5,2 5,1 5,3 5,4 5,6 6,1 6,2 6,1 5,9 5,4 5,4 5,2 5,1 5 5,2 5,5 5,8 5,8 6
AT 3 3,2 3,3 4,8 5,1 4,9 5,1 5,2 5,2 5,2 6,1 6,1 6,4 6,9 7,2 7 7 7,4 7,6 7,8 7,6 7,7 7,7 7,8 7,9 7,9 7,8 7,7
PL 4,4 4,5 4,6 4,3 4 4 4,3 4 3,9 4,1 3,9 4,2 4,5 4,4 4,3 4,3 4,3 4,6
PT 1,5 3 3,4 3,1 3,3 3,2 3,4 3,1 3,8 4 3,9 4,4 4,4 4,9 5,2 5,3 5,4 5,6 6,4 6,3 6,5 7,1 7,2 7,3 7,1
RO 2,7 3,3 3,4 3,5 3,6 3,9 3,5 3,9
SI 6 6 6,2 6,4 6,4 6,3 6,3 6,2
SK 5,3 5,2 5,2 4,9 4,9 5 5,1 5,3 5,2 5 5,2
FI 2 , 13 , 24 , 14 , 8 55 , 65 , 75 , 85 , 65 , 76 , 27 , 17 , 26 , 35 , 85 , 75 , 85 , 55 , 35 , 35 , 15 , 35 , 65 , 9 66 , 26 , 26 , 1
SE 5 , 86 , 88 , 27 , 77 , 47 , 47 , 37 , 37 , 47 , 17 , 17 , 4 76 , 97 , 16 , 9 77 , 1 77 , 37 , 67 , 87 , 57 , 57 , 47 , 4
UK 3 , 33 , 53 , 94 , 9 54 , 94 , 94 , 94 , 84 , 84 , 95 , 35 , 75 , 85 , 85 , 75 , 75 , 35 , 45 , 65 , 65 , 86 , 16 , 26 , 66 , 76 , 96 , 9  
Source: OECD Health data and WHO Health for All databases 
 
EN 150   EN Figures A6: Public expenditure as % of total expenditure on health, 1960-2007   
4050607080901001960
19
70
1980
1986
1988
1990
19
92
1994
1996
1998
2000
2002
20
04
2006
BE BG CZ DK DE EE IE 405060708090100 1960
1970
1980
1986
1988
199
0
1992
1994
1996
1998
2000
2002
2004
2006
EL ES FR IT CY LV LT 
405060708090100 1960
1970
1980
1986
1988
199
0
1992
1994
1996
1998
2000
2002
2004
2006
EL ES FR IT CY LV LT 405060708090100 1960
1970
1980
198
6
198
8
199
0
199
2
1994
1996
1998
200
0
200
2
200
4
200
6
RO SI SK FI SE UK 
Source: OECD Health data and WHO Health for All databases  
 
EN 151   EN Figure A7 
Life expectancy at birth vs total ex penditure on health as % of GDP, 
2007 or latest available
BE
BGCZDKDE
EEIEELES FRIT
CY
LVLTLU
HUMTNLAT
PLPT
ROSI
SKFISE
UK
70.072.074.076.078.080.082.0
4.0 6.0 8.0 10.0 12.0
total expenditure on health as % of GDPLife expectancy at birthy = 1,5045x + 65,266
R2 = 0,5439
 
Source: Eurostat data, OECD Health data, WHO Health for All database and EC computations 
 
EN 152   EN Figures A8a 
Projected life expectancy at birth, males 
 
Projected life expectancy at 65, males  
 
Source: Eurostat, EUROPOP2008 convergen ce scenario; 2009 EP C/EC Ageing Report 
 
EN 153   EN Figures A8a 
Projected life expectancy at birth, female (in years) 
 
Projected life expectancy at 65, women (in years) 
 
Source: Eurostat, EUROPOP2008 convergen ce scenario; 2009 EP C/EC Ageing Report 
 
EN 154   EN Figures A9: Population pyramids 2008 and 2060, EU27 
 
Source: Eurostat, EUROPOP 2008 convergence scenario 
Figure A10 Age-related expenditure profiles 
 
Source: EPC/EC 2009 Ageing Report  4,00 3,00 2,00 1,00 0,00 1,00 2,00 3,00 4,000-45-910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990+
Per  c entMen Women
4,00 3,00 2,00 1,00 0,00 1,00 2,00 3,00 4,000-45-910-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990+
Per centMen Women
 
EN 155   EN Figure A11. Pharmaceutical expenditure pe r capita PPS, 2007 or latest available 
Total pharmaceutical expenditure per capita PPS
0100200300400500600
Belgium
Bulgaria
CzechRepublicDenmarkGermanyEstonia
GreeceSpainFranceItaly
CyprusLatvia
LithuaniaHungary
Netherlands
Austria
Poland
Portugal
Romania
Slovenia
Slovakia
Finland
SwedenPer capita PPS
 
Source: Eurostat and WHO Health for All database 
NB. It should be noted that in some Member States pharmaceutical expenditures in hospitals are not properly 
separated from the total of hospital expenditure.  
Figure A12  
Obesity rates (% of the population that is obese)
051015202530
1980 1981
1982 1983 1984 19851986
19871988 1989
1990 1991 1992 19931994 1995
1996 1997
1998 1999 2000 20012002 2003
2004 2005
2006 20072008
AT BE CZ DK FI FR DE EL HU IE IT LU NL PL PT
SK ES SE UK 
Source: OECD Health data 
 
EN 156   EN Figure A13. Sleeping and anxiety problems in SE (% of the population) in the early 2000s 
 
Source: Ministry of Health and Soci al Affairs, Sweden. See at 
http://ec.europa.eu/health/ph_determinants/life_style/mental/docs/ev_20090427_co06_en.pdf  
 
EN 157   EN 9.4. Statistical tables 
1a. At-risk-of-poverty rate by age and gender, 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO(1)SI SK FI SE UK
Total population Total 17p 16p 15 21 9 12 11 15 19 16 20 20 13b 19 16 26 20 13 12 15 11 12 17 18 23 12 11 14 12 19p
Men 16p 15p 14 20 8 12 11 14 16 15 20 18 13b 17 14 23 18 13 12 14 11 11 17 18 22 11 10 13 11 18p
Women 17p 17p 16 23 10 12 12 16 22 16 21 21 14b 20 18 28 22 14 12 15 11 13 17 19 24 14 12 14 13 20p
Children aged 0-17 Total 20p 19p 17 26 13 9 10 15 17 18 23 24 17b 25 14 25 23 20 20 20 13 15 22 23 33 12 17 12 13 23p
People aged 18-64 Total 15p 15p 12 17 8 11 12 15 15 14 19 16 13b 16 11 20 17 13 12 12 10 11 16 16 20 10 10 12 11 15p
Men 14p 14p 11 16 7 11 13 15 15 13 18 15 12b 15 9 19 16 12 12 10 10 10 17 15 20 11 9 13 11 14p
Women 15p 15p 13 18 9 11 12 16 15 14 19 17 13b 18 13 20 17 14 12 13 10 12 16 17 20 10 10 11 11 16p
People aged 65+ Total 19p 19p 21 34 7 18 10 15 39 21 22 28 11b 21 49 51 29 5 4 22 10 15 12 22 26 21 10 23 16 30p
Men 16p 16p 20 27 3 17 8 12 25 19 21 25 10b 17 43 45 17 5 3 24 10 12 9 19 21 12 4 16 10 28p
Women 22p 21p 22 39 10 19 11 18 46 23 24 30 12b 24 54 54 36 6 5 20 9 17 13 24 30 28 13 28 21 33p
1a. At-risk-of-poverty threshold (illustrative values), EUR and PPS, 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO(1)SI SK FI SE UK
EUR '- One-person household : : 10788 1303 3638 14497 15917 10953 3328 13760 6480 7753 10538 b 9382 10022 2899 2502 18550 2639 5743 11694 11406 2493 4878 1173 6535 2875 11800 12178 13119 p
       '- Two adults with two dep. c h : : 22654 2736 7640 30443 33426 23001 6989 28896 13608 16282 22130 b 19702 21046 6088 5253 38955 5542 12061 24557 23953 5235 10243 2462 13724 6038 24779 25573 27550 p
PPS '- One-person household : : 10146 2801 5828 10529 11561 10627 4652 10949 7249 8391 9734b 9033 11335 4403 4196 16505 3993 7831 11314 11248 3915 5768 1907 8395 4040 9632 10377 11609p
       '- Two adults with two dep. c h : : 21307 5881 12239 22110 24277 22317 9770 22993 15223 17622 20441b 18969 23804 9245 8811 34660 8385 16446 23760 23620 8221 12113 4005 17629 8484 20228 21 792 24380p
(1) Including imputed rent data 2007. See methodological note for an explanation
Notes: i See explanatory text (Eurostat website) p = provisional value  s = Eurostat estimate  u = unreliable or uncertain data   (:) = data not available b= break in data series
1b. Relative median at-risk-of-poverty gap by age and gender, 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
Total population Total 22p 21p 17 27 18 18 22 23 20 19 25 24 18b 23 17 29 26 17 17 18 15 15 21 23 32 19 18 16 18 21p
Men 23p 22p 18 27 21 19 25 24 24 20 24 25 19b 23 16 27 29 15 18 19 14 16 21 22 33 21 21 17 20 21p
Women 21p 21p 17 27 15 17 19 21 19 18 25 23 17b 23 17 30 25 18 17 18 17 15 20 23 32 19 17 14 17 21p
Children aged 0-17Total22p 21p 18 40 21 19 22 19 24 20 26 26 15b 24 14 29 28 17 17 17 13 16 22 26 39 16 24 16 18 19p
People aged 18-64 Total 24p 23p 19 30 19 25 26 25 27 21 26 26 21b 26 15 30 31 17 18 18 17 17 21 24 32 20 19 19 23 22p
Men 25p 24p 20 29 22 30 30 27 29 21 26 27 23b 25 14 29 31 14 18 20 17 20 22 23 33 22 22 20 24 24p
Women 23p 23p 19 30 17 20 23 24 25 21 26 26 20b 26 16 30 29 20 18 17 18 16 21 24 31 18 18 18 23 21p
People aged 65+ Total 18p 17p 14 18 8 8 8 17 15 8 21 19 12b 19 19 27 17 15 10 20 14 14 14 18 23 20 9 11 11 21p
Men 17p 17p 15 14 7 7 9 18 13 12 20 21 11b 16 18 21 12 15u 10u 19 12 14 13 17 23 18 8u 10 13 18p
Women 18p 18p 13 20 8 8 8 17 16 6 23 17 13b 20 20 30 18 15u 10 20 16 14 14 18 23 21 10 12 11 21p
Notes: i See explanatory text (Eurostat website) p = provisional value  s = Eurostat estimate  u = unreliable or uncertain data   (:) = data not available b= break in data series
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
2. Inequality of income distribution: S80/S20 income quintile share ratio
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
S80/S20 Total 5p 4,8p 4.1 6.5 3.4 3.6 3.6 4.8 5 4.5 5.9 5.4 4,2b 5.1 4.1 7.3 5.9 4.1 3.6 4 4 3.7 5.1 6.1 7 3.4 3.4 3.8 3.5 5,6p
Notes: i See explanatory text (Eurostat website) p = provisional value  s = Eurostat estimate  u = unreliable or uncertain data   (:) = data not available  b= break in data series
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008)
Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008) (1) with imputed rent data 2007 (see methodological note).
Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);  (1) with imputed rent data 2007 (see methodological note).
 
 
EN 158   EN 3. Healthy life years : Disability free life expect ancy (+ life expectancy at 0, 45, 65) 1997-2008
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
life expectancy at birth - males eu27 : : : : : 74.5 74.6 75.2 75.4 75.8 : :
life expectancy at 45 - males eu27 : : : : : 31.9 31.9 32.5 32.6 32.9 : :
life expectancy at 65 - males eu27 : : : : : 15.9 15.9 16.4 16.5 16.8 : :
Healthy Life Years at birth - males eu27 :::::::::: 6 1 , 6 0 e :
life expectancy at birth - females eu27 : : : : : 80.9 80.8 81.5 81.5 82.0 : :
life expectancy at 45 - females eu27 : : : : : 37.3 37.2 37.8 37.8 38.2 : :
life expectancy at 65 - females eu27 : : : : : 19.5 19.4 19.9 20.0 20.4 : :
Healthy Life Years at birth - females eu27 :::::::::: 6 2 , 3 0 e :
life expectancy at birth - males eu25 : : : : : 75.0 75.1 75.7 75.9 76.3 : :
life expectancy at 45 - males eu25 : : : : : 32.3 32.3 32.8 32.9 33.3 : :
life expectancy at 65 - males eu25 : : : : : 16.1 16.1 16.6 16.7 17.1 : :
Healthy Life Years at birth - males :::::::: 6 0 . 8 6 1 . 6 ::
life expectancy at birth - females eu25 79.7 79.9 80.2 80.2 80.4 80.8 81.1 81.3 81.2 81.9 81.9 :
life expectancy at 45 - females eu25 : : : : : 37.2 37.4 37.6 37.5 38.1 : :
life expectancy at 65 - females eu25 : : : : : 19.4 19.6 19.7 19.6 20.2 : :
Healthy Life Years at birth - females eu25 :::::::: 6 2 . 1 6 2 . 1 ::
Disability free life expectancy at birth - males eu15 :: 6 3 , 2 e 6 3 , 5 e 6 3 , 6 e 6 4 , 3 e 6 4 , 5 e :::::
Disability free life expectancy at birth - females eu15 :: 6 3 , 9 e 6 4 , 4 e 6 5 , 0 e 6 5 , 8 e 6 6 , 0 e :::::
Source: Eurostat - Demography; e: estimate
 
 
EN 159   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males BE 74.2 74.4 74.4 74.6 75.0 75. 1 75.3 76.0 76.2 76.6 77.1 :
Life expectancy at 45 - males BE 31.6 31.7 31.8 32.0 32.3 32. 3 32.5 33.0 33.1 33.6 34.0 :
Life expectancy at 65 - males BE 15.2 15.3 15.5 15.6 15.9 15. 8 16.0 16.4 16.6 17.0 17.3 :
Healthy Life Years at birth - males BE 66.5 63.3 66.0 65.7 66.6 66,9(e) 67,4(e) 58,4(bi) 61.7 62.8 63.3
Life expectancy at birth - females BE 80.7 80.7 81.0 81.0 81.2 81. 2 81.1 81.8 81.9 82.3 82.6 :
Life expectancy at 45 - females BE 37.2 37.3 37.4 37.5 37.7 37. 5 37.3 38.0 38.0 38.5 38.8 :
Life expectancy at 65 - females BE 19.5 19.6 19.7 19.8 19.9 19. 7 19.6 20.2 20.2 20.7 21.0 :
Healthy Life Years at birth - females BE 68.3 65,4(e) 68.4 69.1 68.8 69,0(e) 69,2(e) 58,10(bi) 61.9 62.8 63.7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males BG 67.0 67.4 68.3 68.4 68.6 68.8 68.9 69.0 69.0 69.2 69.5 69.8
Life expectancy at 45 - males BG 26.3 26.4 27.2 27.0 27.2 27.3 27.3 27.5 27.2 27.3 27.5 27.9
Life expectancy at 65 - males BG 12.3 12.5 12.9 12.7 13.0 13.0 13.0 13.2 13.1 13.2 13.3 13.5
Healthy Life Years at birth - males BG ::::::::::::
Life expectancy at birth - females BG 73.8 74.6 75.0 75.0 75.4 75.5 75.9 76.2 76.2 76.3 76.7 77.0
Life expectancy at 45 - females BG 31.7 32.2 32.5 32.4 32.8 32.9 33.1 33.4 33.3 33.5 33.7 34.0
Life expectancy at 65 - females BG 14.7 15.1 15.4 15.3 15.6 15.7 15.9 16.2 16.1 16.3 16.4 16.7
Healthy Life Years at birth - females BG ::::::::::::
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males CZ 70.5 71.2 71.5 71.7 72.1 72.1 72.0 72.6 72.9 73.5 73.8 74.1
Life expectancy at 45 - males CZ 28.1 28.6 28.8 29.0 29.3 29.3 29.2 29.7 29.9 30.4 30.7 30.9
Life expectancy at 65 - males CZ 13.2 13.5 13.7 13.8 14.0 13.9 13.8 14.2 14.4 14.8 15.1 15.3
Healthy Life Years at birth - males CZ ::::: 6 2 , 8 ( p ) :: 5 7 , 9 ( b i ) 5 7 . 8 6 1 . 3
Life expectancy at birth - females CZ 77.6 78.2 78.3 78.5 78.6 78.7 78.6 79.2 79.3 79.9 80.2 80.5
Life expectancy at 45 - females CZ 34.1 34.5 34.5 34.8 34.8 34.9 34.7 35.3 35.3 36.0 36.2 36.5
Life expectancy at 65 - females CZ 16.7 17.1 17.1 17.3 17.3 17.3 17.2 17.6 17.7 18.3 18.5 18.8
Healthy Life Years at birth - females CZ ::::: 6 3 , 3 ( p ) :: 5 9 , 9 0 ( b i ) 5 9 . 8 6 3 . 2
 
 
EN 160   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males DK 73.6 74.0 74.2 74.5 74.7 74.8 75.0 75.4 76.0 76.1 76.2 76.5
Life expectancy at 45 - males DK 30.9 31.1 31.3 31.6 31.7 31.8 32.0 32.4 32.8 32.8 33.0 33.3
Life expectancy at 65 - males DK 14.6 14.9 15.0 15.2 15.2 15.4 15.6 15.9 16.1 16.2 16.5 16.6
Healthy Life Years at birth - males DK 61.6 62.4 62.5 62.9 62.2 62,8(e) 63,0(e) 68,3(bi) 68.4 67.7 67.4
Life expectancy at birth - females DK 78.6 79.0 79.0 79.2 79.3 79.4 79.8 80.2 80.5 80.7 80.6 81.0
Life expectancy at 45 - females DK 35.0 35.4 35.2 35.5 35.6 35.6 35.9 36.4 36.6 36.8 36.6 37.1
Life expectancy at 65 - females DK 18.0 18.3 18.1 18.3 18.3 18.2 18.5 19.0 19.1 19.2 19.2 19.5
Healthy Life Years at birth - females DK 60,7(e) 61,3(e) 60.8 61.9 60.4 61,0( e) 60,9(e) 68,80(bi) 68.2 67.1 67.4
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males DE 74.1 74.6 74.8 75.1 75.6 75.7 75.8 76.5 76.7 77.2 77.4 77.6
Life expectancy at 45 - males DE 31.4 31.7 32.0 32.2 32.5 32.6 32.7 33.3 33.4 33.8 34.0 34.2
Life expectancy at 65 - males DE 15.2 15.4 15.6 15.8 16.1 16.2 16.2 16.7 16.9 17.2 17.4 17.6
Healthy Life Years at birth - males DE 61,9(e) 62,1(e) 62,3(e) 63,2(e) 64,1(e) 64,4(e) 65,0(e) : 55(bi) 58.5 58.8
Life expectancy at birth - females DE 80.5 80.8 81.0 81.2 81.5 81.3 81.3 81.9 82.0 82.4 82.7 82.7
Life expectancy at 45 - females DE 36.9 37.1 37.3 37.5 37.6 37.5 37.5 38.0 38.1 38.5 38.7 38.6
Life expectancy at 65 - females DE 19.1 19.3 19.4 19.6 19.8 19.6 19.6 20.1 20.1 20.5 20.7 20.7
Healthy Life Years at birth - females DE 64,3(e) 64,3(e) 64,3(e) 64,6(e) 64,5(e) 64,5(e) 64,7(e) : 55,10(bi) 58.0 58.4
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males EE 64.2 63.9 64.7 65.2 64.8 65.2 66.1 66.4 67.3 67.4 67.2 68.7
Life expectancy at 45 - males EE 24.9 24.2 25.0 25.1 24.8 25.2 25.6 25.7 26.2 26.2 26.2 27.2
Life expectancy at 65 - males EE 12.5 12.2 12.5 12.6 12.6 12.7 12.7 13.0 13.1 13.2 13.1 13.6
Healthy Life Years at birth - males EE ::::::: 4 9 , 8 ( b i ) 4 8 . 0 4 9 . 4 4 9 . 5
Life expectancy at birth - females EE 75.9 75.4 76.0 76.2 76.4 77.0 77.1 77.8 78.1 78.6 78.8 79.5
Life expectancy at 45 - females EE 33.3 32.9 33.5 33.5 33.7 33.9 34.1 34.6 35.0 35.1 35.5 36.0
Life expectancy at 65 - females EE 16.8 16.5 17.0 17.0 17.3 17.3 17.4 17.8 18.0 18.3 18.5 18.9
Healthy Life Years at birth - females EE ::::::: 5 3 , 3 0 ( b i ) 5 2 . 2 5 3 . 7 5 4 . 6  
 
EN 161   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males IE 73.4 73.4 73.4 74.0 74.5 75.2 75.9 76.4 77.3 77.4 77.4 77.5
Life expectancy at 45 - males IE 30.7 30.9 30.8 31.5 31.9 32.4 33.0 33.4 34.1 34.2 34.3 34.5
Life expectancy at 65 - males IE 14.0 14.2 14.1 14.6 15.0 15.4 15.9 16.2 16.8 16.8 17.1 17.2
Healthy Life Years at birth - males IE 63.2 64.0 63.9 63.3 63.3 63,5(e) 63,4(e) 62,5(bi) 62.9 63.2 62.7
Life expectancy at birth - females IE 78.7 79.1 78.9 79.2 79.9 80.5 80.8 81.4 81.7 82.2 82.1 82.3
Life expectancy at 45 - females IE 35.2 35.5 35.3 35.7 36.4 36.9 37.0 37.6 37.9 38.2 38.1 38.4
Life expectancy at 65 - females IE 17.6 17.8 17.6 18.0 18.5 18.9 19.2 19.6 19.9 20.3 20.1 20.4
Healthy Life Years at birth - females IE : : 67.6 66.9 66.5 65,9(e) 65,4( e) 64,30(bi) 64.1 65.0 65.3
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males EL 75.4 75.4 75.5 75.5 76.0 76.2 76.5 76.6 76.8 77.2 77.1 77.7
Life expectancy at 45 - males EL 32.9 32.8 32.9 32.8 33.2 33.4 33.5 33.7 34.0 34.3 34.2 34.6
Life expectancy at 65 - males EL 16.2 16.2 16.2 16.1 16.5 16.6 16.7 16.9 17.1 17.5 17.4 17.8
Healthy Life Years at birth - males EL 66.4 66.5 66.7 66.3 66.7 66,7(e) 66,7(e) 63,7(bi) 65.7 66.3 65.9
Life expectancy at birth - females EL 80.4 80.3 80.5 80.6 81.0 81.1 81.2 81.3 81.6 81.9 81.8 82.4
Life expectancy at 45 - females EL 36.8 36.7 36.8 36.8 37.2 37.2 37.2 37.5 37.8 37.9 37.9 38.3
Life expectancy at 65 - females EL 18.4 18.3 18.4 18.4 18.7 18.8 18.7 19.0 19.2 19.4 19.4 19.8
Healthy Life Years at birth - females EL 68.7 68.3 69.4 68.2 68.8 68,5(e) 68,4(e) 65,20(bi) 67.2 67.9 67.1
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males ES 75.2 75.3 75.3 75.8 76.2 76.3 76.3 76.9 77.0 77.7 77.8 78.0
Life expectancy at 45 - males ES 32.8 32.8 32.7 33.2 33.4 33.5 33.5 34.0 34.0 34.6 34.6 34.7
Life expectancy at 65 - males ES 16.4 16.2 16.2 16.7 16.9 16.9 16.8 17.3 17.3 17.9 17.8 18.0
Healthy Life Years at birth - males ES 65.5 65.2 65.6 66.5 66.0 66,6(e) 66,8(e) 62,5(bi) 63.2 63.7 63.2
Life expectancy at birth - females ES 82.3 82.4 82.4 82.9 83.2 83.2 83.0 83.7 83.7 84.4 84.3 84.3
Life expectancy at 45 - females ES 38.8 38.7 38.7 39.2 39.4 39.4 39.2 39.9 39.7 40.4 40.4 40.4
Life expectancy at 65 - females ES 20.5 20.4 20.3 20.8 21.0 21.0 20.8 21.5 21.3 22.0 22.0 21.9
Healthy Life Years at birth - females ES 68.2 68.2 69.5 69.3 69,2(e) 69,9(e) 70,2(e) 62,50(bi) 63.1 63.3 62.9  
 
EN 162   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males FR : 74.8 75.0 75.3 75.5 75.7 75.8 76.7 76.7 77.3 77.6 :
Life expectancy at 45 - males FR : 32.4 32.6 32.9 33.0 33.1 33.1 33.9 33.9 34.4 34.6 :
Life expectancy at 65 - males FR : 16.5 16.6 16.8 17.0 17.0 17.0 17.7 17.7 18.2 18.4 :
Healthy Life Years at birth - males FR 60.2 59.2 60.1 60.1 60.5 60,4(e) 60,6(e) 61,2(bi) 62.0 62.7 63.1
Life expectancy at birth - females FR : 82.6 82.7 83.0 83.0 83.0 82.7 83.8 83.8 84.5 84.8 :
Life expectancy at 45 - females FR : 39.1 39.2 39.4 39.4 39.3 39.0 40.1 40.0 40.7 41.0 :
Life expectancy at 65 - females FR : 21.2 21.2 21.4 21.5 21.4 21.1 22.1 22.0 22.7 23.0 :
Healthy Life Years at birth - females FR 63.1 62.8 63.3 63,2(e) 63.3 63,7(e) 63,9(e) 64,10(bi) 64.3 64.1 64.2
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males IT 75.8 76.0 76.5 76.9 77.1 77. 4 77.1 77.9 78.0 78.5 : :
Life expectancy at 45 - males IT 33.0 33.1 33.5 33.8 34.0 34. 2 34.0 34.7 34.8 35.2 : :
Life expectancy at 65 - males IT 16.2 16.2 16.5 16.7 16.9 17. 0 16.8 17.5 17.4 17.9 : :
Healthy Life Years at birth - males IT 68.0 67.9 68.7 69.7 69.8 70,4(e) 70, 9(e) 68,4(bi) 65.7 64.7 62,8(e)
Life expectancy at birth - females IT 82.0 82.1 82.6 82.8 83.1 83. 2 82.8 83.8 83.6 84.2 : :
Life expectancy at 45 - females IT 38.4 38.4 38.8 39.0 39.2 39. 3 38.8 39.9 39.6 40.1 : :
Life expectancy at 65 - females IT 20.2 20.3 20.5 20.7 21.0 21. 0 20.6 21.6 21.3 21.8 : :
Healthy Life Years at birth - females IT 71.3 71.3 72.1 72.9 73,0(e) 73,9(e) 74,4(e) 70,70(bi) 66.5 64.1 62(e)
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males CY 74.9 74.7 76.0 75.4 76.6 76.4 76.9 76.6 76.8 78.4 77.9 78.5
Life expectancy at 45 - males CY 32.8 32.4 33.5 32.8 33.9 33.7 33.8 33.7 34.2 35.1 34.9 35.4
Life expectancy at 65 - males CY 15.7 15.3 16.5 15.9 16.8 16.3 16.5 16.6 16.8 17.4 17.4 17.9
Healthy Life Years at birth - males CY :::::: 6 8 . 4 : 5 9 , 5 ( b i ) 6 4 . 3 6 3 . 0
Life expectancy at birth - females CY 80.0 79.8 79.9 80.1 81.4 81.0 81.3 81.9 80.9 82.2 82.2 83.1
Life expectancy at 45 - females CY 36.5 36.2 36.6 36.6 37.6 37.4 37.4 37.8 37.6 38.1 38.4 38.9
Life expectancy at 65 - females CY 18.2 18.0 18.3 18.3 19.2 19.0 19.1 19.4 19.1 19.5 19.6 20.4
Healthy Life Years at birth - females CY :::::: 6 9 . 6 : 5 7 , 9 0 ( b i ) 6 3 . 2 6 2 . 7  
 
EN 163   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males LV ::::: 6 4 . 7 6 5 . 6 6 5 . 9 6 5 . 4 6 5 . 4 6 5 . 8 6 7 . 0
Life expectancy at 45 - males LV ::::: 2 4 . 9 2 5 . 3 2 5 . 4 2 5 . 0 2 4 . 9 2 5 . 2 2 6 . 1
Life expectancy at 65 - males LV ::::: 1 2 . 5 1 2 . 6 1 2 . 6 1 2 . 5 1 2 . 7 1 2 . 8 1 3 . 0
Healthy Life Years at birth - males LV :::::::: 5 0 , 6 ( b i ) 5 0 . 5 5 0 . 9
Life expectancy at birth - females LV ::::: 7 6 . 0 7 5 . 9 7 6 . 2 7 6 . 5 7 6 . 3 7 6 . 5 7 7 . 8
Life expectancy at 45 - females LV ::::: 3 3 . 5 3 3 . 2 3 3 . 7 3 3 . 8 3 3 . 5 3 3 . 7 3 4 . 6
Life expectancy at 65 - females LV ::::: 1 7 . 0 1 6 . 8 1 7 . 1 1 7 . 2 1 7 . 3 1 7 . 2 1 7 . 9
Healthy Life Years at birth - females LV :::::::: 5 3 , 1 0 ( b i ) 5 2 . 2 5 3 . 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males LT 65.5 66.0 66.3 66.8 65.9 66.2 66.4 66.3 65.3 65.3 64.9 66.3
Life expectancy at 45 - males LT 26.0 26.2 26.4 26.7 26.2 26.1 26.2 26.1 25.3 25.1 24.8 25.8
Life expectancy at 65 - males LT 13.2 13.3 13.4 13.7 13.5 13.3 13.3 13.4 13.0 13.0 12.9 13.4
Healthy Life Years at birth - males LT :::::::: 5 1 , 2 ( b i ) 5 2 . 4 5 3 . 4
Life expectancy at birth - females LT 76.6 76.7 77.0 77.5 77.6 77.5 77.8 77.7 77.3 77.0 77.2 77.6
Life expectancy at 45 - females LT 34.1 34.1 34.5 34.8 34.7 34.6 34.8 34.7 34.3 34.2 34.4 34.6
Life expectancy at 65 - females LT 17.3 17.4 17.6 17.9 17.9 17.8 18.1 17.9 17.6 17.6 17.9 18.1
Healthy Life Years at birth - females LT :::::::: 5 4 , 3 0 ( b i ) 5 6 . 1 5 7 . 7
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males LU 74.0 73.7 74.4 74.6 75.1 74.7 74.8 76.0 76.7 76.8 76.7 78.1
Life expectancy at 45 - males LU 31.2 31.2 31.8 32.0 32.5 32.3 31.9 33.1 33.4 33.5 33.3 34.6
Life expectancy at 65 - males LU 14.8 15.2 15.3 15.5 16.0 15.9 15.3 16.5 16.7 17.0 16.4 17.4
Healthy Life Years at birth - males LU ::::::: 5 9 , 1 ( b i ) 6 2 . 2 6 1 . 0 6 2 . 2
Life expectancy at birth - females LU 80.0 80.8 81.4 81.3 80.7 81.5 80.9 82.4 82.3 81.9 82.2 83.1
Life expectancy at 45 - females LU 36.7 37.3 37.5 37.7 37.4 37.7 37.0 38.5 38.4 38.0 38.1 39.0
Life expectancy at 65 - females LU 19.2 19.5 19.9 20.1 19.7 20.1 18.9 20.5 20.4 20.3 20.3 21.0
Healthy Life Years at birth - females LU ::::::: 6 0 , 2 0 ( b i ) 6 2 . 1 6 1 . 8 6 4 . 6  
 
EN 164   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males HU 66.7 66.5 66.7 67.6 68.2 68.3 68.4 68.7 68.7 69.2 69.4 70.0
Life expectancy at 45 - males HU 25.4 25.3 25.3 26.0 26.4 26.4 26.3 26.6 26.4 26.8 26.9 27.3
Life expectancy at 65 - males HU 12.5 12.6 12.5 13.0 13.2 13.2 13.0 13.4 13.3 13.7 13.7 14.0
Healthy Life Years at birth - males HU :::::: 5 3 , 5 ( p ) : 5 2 ( b i ) 5 4 . 2 5 5 . 0
Life expectancy at birth - females HU 75.5 75.6 75.6 76.2 76.7 76.7 76.7 77.2 77.2 77.8 77.8 78.3
Life expectancy at 45 - females HU 32.7 32.8 32.6 33.2 33.5 33.6 33.5 33.8 33.8 34.3 34.3 34.7
Life expectancy at 65 - females HU 16.3 16.4 16.2 16.8 17.0 17.0 16.9 17.3 17.2 17.7 17.8 18.1
Healthy Life Years at birth - females HU :::::: 5 7 , 8 ( p ) : 5 3 , 9 0 ( b i ) 5 7 . 0 5 7 . 6
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males MT 75.2 74.9 75.3 76.2 76.6 76.3 76.4 77.4 77.3 77.0 77.5 77.1
Life expectancy at 45 - males MT 32.1 32.0 32.1 32.7 33.4 33.0 33.2 34.1 33.8 33.6 34.4 34.3
Life expectancy at 65 - males MT 14.6 14.6 15.0 15.1 15.7 15.3 15.6 16.3 16.2 16.1 16.7 17.0
Healthy Life Years at birth - males MT ::::: 6 5 , 1 ( p ) :: 6 8 , 5 ( b i ) 6 8 . 1 6 9 . 0
Life expectancy at birth - females MT 80.1 80.0 79.4 80.3 81.2 81.3 80.8 81.2 81.4 81.9 82.2 82.3
Life expectancy at 45 - females MT 36.6 36.3 35.9 36.5 37.0 37.3 36.9 37.4 37.5 37.7 38.5 38.4
Life expectancy at 65 - females MT 18.4 18.1 17.8 18.5 18.7 19.1 18.7 19.1 19.4 19.5 20.3 20.1
Healthy Life Years at birth - females MT ::::: 6 5 , 7 ( p ) :: 7 0 , 1 0 ( b i ) 6 9 . 2 7 0 . 8
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males NL 75.2 75.2 75.4 75.6 75.8 76.0 76.3 76.9 77.3 77.7 78.1 78.4
Life expectancy at 45 - males NL 32.0 32.0 32.1 32.3 32.6 32.7 32.9 33.5 33.8 34.2 34.5 34.8
Life expectancy at 65 - males NL 15.1 15.1 15.2 15.4 15.6 15.6 15.8 16.3 16.4 16.8 17.1 17.4
Healthy Life Years at birth - males NL 62.5 61.9 61.6 61.4 61.9 61,7( e) 61,7(e) : 65(bi) 65.0 65.7
Life expectancy at birth - females NL 80.7 80.8 80.5 80.7 80.8 80.7 81.0 81.5 81.7 82.0 82.5 82.5
Life expectancy at 45 - females NL 37.0 37.1 36.9 37.0 37.1 37.0 37.2 37.7 37.9 38.1 38.6 38.5
Life expectancy at 65 - females NL 19.3 19.4 19.2 19.3 19.4 19.4 19.5 19.9 20.1 20.3 20.7 20.7
Healthy Life Years at birth - females NL 61.4 61,1(e) 61.4 60.2 59.4 59,3( e) 58,8(e) : 63,10(bi) 63.2 63.7  
 
EN 165   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males AT 74.1 74.5 74.9 75.2 75.7 75.8 75.9 76.4 76.7 77.2 77.4 77.8
Life expectancy at 45 - males AT 31.4 31.7 32.0 32.4 32.8 32.8 32.9 33.4 33.6 34.0 34.2 34.5
Life expectancy at 65 - males AT 15.2 15.4 15.7 16.0 16.3 16.3 16.4 16.8 17.0 17.3 17.5 17.7
Healthy Life Years at birth - males AT 62.2 63.4 63.6 64.6 64.2 65,6(e) 66,2(e) 58,1(bi) 57.8 58.4 58.4
Life expectancy at birth - females AT 80.7 81.0 81.0 81.2 81.7 81.7 81.5 82.1 82.2 82.8 83.1 83.3
Life expectancy at 45 - females AT 37.0 37.3 37.3 37.5 37.9 37.8 37.7 38.2 38.4 38.8 39.0 39.3
Life expectancy at 65 - females AT 19.1 19.4 19.4 19.6 20.0 19.8 19.7 20.2 20.3 20.7 21.0 21.1
Healthy Life Years at birth - females AT : : : 68.0 68.5 69,0(e) 69,6(e) 60,20(bi) 59.6 60.8 61.1
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males PL 68.5 68.9 68.8 69.6 70.0 70.3 70.5 70.6 70.8 70.9 71.0 71.3
Life expectancy at 45 - males PL 27.1 27.4 27.3 27.9 28.1 28.4 28.4 28.5 28.7 28.8 28.8 29.1
Life expectancy at 65 - males PL 13.2 13.4 13.3 13.6 13.7 13.9 13.9 14.2 14.3 14.5 14.6 14.8
Healthy Life Years at birth - males PL ::::: 6 2 . 5 :: 6 1 ( b i ) 5 8 . 2 5 7 . 4
Life expectancy at birth - females PL 77.0 77.4 77.5 78.0 78.4 78.8 78.8 79.2 79.3 79.7 79.8 80.0
Life expectancy at 45 - females PL 33.9 34.2 34.3 34.7 35.0 35.3 35.3 35.6 35.8 36.1 36.2 36.4
Life expectancy at 65 - females PL 16.8 17.1 17.1 17.5 17.7 18.0 18.0 18.4 18.5 18.8 19.0 19.1
Healthy Life Years at birth - females PL ::::: 6 8 . 9 :: 6 6 , 6 0 ( b i ) 6 2 . 5 6 1 . 3
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males PT 72.2 72.4 72.6 73.2 73.5 73.8 74.2 75.0 74.9 75.5 75.9 76.2
Life expectancy at 45 - males PT 31.0 31.1 31.3 31.6 31.9 31.9 32.0 32.6 32.5 32.9 33.1 33.3
Life expectancy at 65 - males PT 14.9 15.0 15.0 15.4 15.7 15.7 15.7 16.3 16.1 16.6 16.8 16.9
Healthy Life Years at birth - males PT 59.3 59.1 58.8 60.2 59.5 59,7(e) 59,8(e) 55,1(bi) 58.4 59.6 58.3
Life expectancy at birth - females PT 79.3 79.6 79.7 80.2 80.5 80.6 80.6 81.5 81.3 82.3 82.2 82.4
Life expectancy at 45 - females PT 36.3 36.4 36.5 36.9 37.1 37.2 37.0 37.9 37.6 38.5 38.4 38.6
Life expectancy at 65 - females PT 18.4 18.5 18.5 18.9 19.1 19.2 19.0 19.7 19.4 20.2 20.2 20.3
Healthy Life Years at birth - females PT 60.4 61.1 60.7 62.2 62.7 61,8(e) 61,8(e) 52,00(bi) 56.7 57.6 57.3  
 
EN 166   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males RO 65.2 66.3 67.1 67.7 67.5 67.4 67.7 68.3 68.7 69.2 69.7 69.7
Life expectancy at 45 - males RO 25.8 26.4 26.9 27.3 27.0 26.7 26.8 27.3 27.4 27.7 28.1 28.0
Life expectancy at 65 - males RO 12.7 13.0 13.0 13.4 13.3 12.9 13.1 13.3 13.4 13.6 13.9 14.0
Healthy Life Years at birth - males RO :::::::::: 6 0 . 4
Life expectancy at birth - females RO 73.3 73.8 74.2 74.8 74.9 74.7 75.0 75.5 75.7 76.2 76.9 77.2
Life expectancy at 45 - females RO 31.8 32.1 32.3 32.7 32.7 32.4 32.7 33.1 33.1 33.5 33.9 34.2
Life expectancy at 65 - females RO 15.3 15.5 15.5 15.9 16.0 15.7 15.8 16.2 16.2 16.5 16.9 17.2
Healthy Life Years at birth - females RO :::::::::: 6 2 . 4
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males SI 71.1 71.3 71.8 72.2 72.3 72.6 72.5 73.5 73.9 74.5 74.7 75.5
Life expectancy at 45 - males SI 29.0 29.1 29.3 29.7 29.8 30.0 29.8 30.7 31.1 31.6 31.8 32.4
Life expectancy at 65 - males SI 14.0 13.9 14.1 14.2 14.5 14.5 14.3 15.0 15.2 15.9 15.9 16.4
Healthy Life Years at birth - males SI :::::::: 5 6 , 3 ( b i ) 5 7 . 6 5 8 . 7
Life expectancy at birth - females SI 79.1 79.2 79.5 79.9 80.4 80.5 80.3 80.8 80.9 82.0 82.0 82.6
Life expectancy at 45 - females SI 35.5 35.6 35.8 36.2 36.5 36.6 36.5 37.0 37.1 38.0 38.1 38.5
Life expectancy at 65 - females SI 18.0 18.1 18.3 18.7 19.0 19.0 18.8 19.4 19.3 20.1 20.2 20.5
Healthy Life Years at birth - females SI :::::::: 5 9 , 9 0 ( b i ) 6 1 . 0 6 2 . 3
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males SK 68.9 68.6 69.0 69.2 69.5 69.8 69.8 70.3 70.2 70.4 70.6 70.8
Life expectancy at 45 - males SK 27.0 26.9 27.1 27.2 27.3 27.5 27.6 28.0 27.8 28.0 28.1 28.5
Life expectancy at 65 - males SK 12.9 12.8 13.0 12.9 13.0 13.2 13.2 13.3 13.3 13.3 13.6 13.8
Healthy Life Years at birth - males SK :::::::: 5 4 , 9 ( b i ) 5 4 . 3 5 5 . 4
Life expectancy at birth - females SK 76.9 77.0 77.4 77.5 77.7 77.7 77.7 78.0 78.1 78.4 78.4 79.0
Life expectancy at 45 - females SK 33.7 33.8 34.0 34.1 34.1 34.3 34.3 34.5 34.5 34.8 34.9 35.3
Life expectancy at 65 - females SK 16.5 16.6 16.8 16.7 16.8 16.9 16.9 17.1 17.1 17.3 17.5 17.8
Healthy Life Years at birth - females SK :::::::: 5 6 , 4 0 ( b i ) 5 4 . 4 5 5 . 9  
 
EN 167   EN 3. Disability free Life expectancy (+ Life expectancy at 0, 45 , 65) by country, 1995-20 08 Source: Eurostat – Demography databas e 
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males FI 73.5 73.6 73.8 74.2 74.6 74.9 75.2 75.4 75.6 75.9 76.0 76.5
Life expectancy at 45 - males FI 31.0 31.0 31.2 31.7 32.0 32.1 32.3 32.6 32.8 33.1 33.2 33.7
Life expectancy at 65 - males FI 15.0 15.0 15.2 15.5 15.7 15.8 16.2 16.5 16.8 16.9 17.0 17.5
Healthy Life Years at birth - males FI 55.5 55.9 55.8 56.3 56.7 57,0(e) 57,3(e) 53,1(bi) 51.7 52.9 56.7
Life expectancy at birth - females FI 80.7 81.0 81.2 81.2 81.7 81.6 81.9 82.5 82.5 83.1 83.1 83.3
Life expectancy at 45 - females FI 37.0 37.3 37.5 37.5 37.8 37.8 38.0 38.6 38.8 39.2 39.2 39.3
Life expectancy at 65 - females FI 19.1 19.3 19.5 19.5 19.8 19.8 20.0 20.7 21.0 21.2 21.3 21.4
Healthy Life Years at birth - females FI 57.6 58.3 57.4 56,8(e) 56.9 56,8(e) 56,5(e) 52,90(bi) 52.4 52.7 58.0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males SE 76.8 76.9 77.1 77.4 77.6 77. 8 78.0 78.4 78.5 78.8 79.0 :
Life expectancy at 45 - males SE 33.4 33.6 33.8 34.1 34.2 34. 3 34.5 34.9 34.9 35.2 35.4 :
Life expectancy at 65 - males SE 16.3 16.4 16.5 16.8 16.9 16. 9 17.1 17.5 17.4 17.7 17.9 :
Healthy Life Years at birth - males SE 62.1 61.7 62.0 63.1 61.9 62,4(e) 62,5(e) 62(bi) 64.2 67.1 67.5
Life expectancy at birth - females SE 82.0 82.1 82.0 82.0 82.2 82. 2 82.5 82.8 82.9 83.1 83.1 :
Life expectancy at 45 - females SE 38.1 38.2 38.0 38.0 38.2 38. 1 38.5 38.8 38.8 39.0 39.0 :
Life expectancy at 65 - females SE 20.1 20.2 20.1 20.2 20.2 20. 1 20.4 20.7 20.7 20.9 20.8 :
Healthy Life Years at birth - females SE 60.0 61,3(e) 61.8 61.9 61.0 61,9(e) 62,2(e) 60,90(bi) 63.1 67.1 66.6
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Life expectancy at birth - males UK 74.7 74.8 75.0 75.5 75.8 76. 0 76.2 76.8 77.1 77.3 77.6 :
Life expectancy at 45 - males UK 31.8 32.0 32.1 32.6 32.9 33. 1 33.2 33.8 34.0 34.3 34.6 :
Life expectancy at 65 - males UK 15.1 15.3 15.4 15.8 16.1 16. 2 16.3 16.8 17.0 17.4 17.6 :
Healthy Life Years at birth - males UK 60,9(e) 60,8(e) 61,2(e) 61,3(e) 61,1(e) 61, 4(e) 61,5(e) : 63,2(bi) 65.0 64,8(e)
Life expectancy at birth - females UK 79.7 79.8 79.9 80.3 80.5 80. 6 80.5 81.0 81.2 81.7 81.8 :
Life expectancy at 45 - females UK 36.1 36.2 36.2 36.7 36.9 36. 9 36.8 37.3 37.4 38.0 38.0 :
Life expectancy at 65 - females UK 18.5 18.6 18.6 19.0 19.2 19. 2 19.1 19.4 19.6 20.1 20.2 :
Healthy Life Years at birth - females UK 61,2(e) 62,2(e) 61,3(e) 61,2(e) 60,8(e) 60, 9(e) 60,9(e) : 65,00(bi) 65.1 66,2(e)  
 
EN 168   EN 4. Early school-leavers  (% of the total population aged 18-24 who have at most lower secondary education and not in further education or training)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 total 17,6e 17,2e 13.8 : : 11.7 14.6 15.1 : 18.2 29.1 13.3 25.1 18.5 : 16.5 16.8 13.9 54.2 15.4 10.2 : 43,6p 22.9 : : 9,0i 7.3 18.2
female 15,5e 15,0e 11 : : 10.4 14.9 11,0u : 13.6 23.2 11.9 21.7 13.9 : 12.8 17.6 13.4 56.1 14.1 10.7 : 36,3p 22 : : 6,5i 5.8 17.5
male 19,6e 19,3e 16.4 : : 12.8 14.4 19.4 : 22.9 35 14.8 28.5 25 : 20 15.9 14.4 52.5 16.6 9.6 : 50,9p 23.8 : : 11,5i 8.7 18.8
2004 total 16.1 15.7 13,1b 21.4 6.3 8.8 12.1 13.1 13.1 14.7 32 12.8 22.3 20.6 14.7 10,5b 12.7 12.6 42,1b 14.1 9,5i 5,6b 39,4p 22,4b 4,3u 6.8 10,0i 9.2 12,1i
female 13.8 13.3 10,8b 20.6 6.6 7.1 11.9 7,8u 10 11.3 25.1 10.8 18.3 14.9 9.5 8,6u 12.7 11.5 39,8b 11.7 8,8i 3,9b 31,0p 21,1b 2,5u 6.3 7,5i 7.8 11,2imale 18.4 18.1 15,4b 22.2 6.1 10.5 12.2 18.6 16 18.1 38.7 14.7 26.5 27.2 19.8 12,4u 12.6 13.6 44,3b 16.4 10,2i 7,3b 47,7p 23,7b 6,0u 7.3 12,5i 10.6 13,0i
2005 total 15.8 15.5 12.9 20.4 6.2 8.7 13,5b 13.4 12.5 13.6 30,8b 12.2 22 18,2b 14.4 8.1 13.3 12.5 38.9 13.5 9.1 5.3 38,8p 19.6 4,9u 6.3 10,3i 10,8b 11.6
female 13.7 13.3 10.5 20.3 6.3 6.9 13,7b :u 9.5 9.7 24,9b 10.3 18.2 10,4b 10.4 5,6u 9.6 11.3 35.5 11.1 8.7 3.7 30,7p 19.1 3,2u 5.9 8,2i 9,7b 10.6
male 17.8 17.6 15.3 20.6 6.1 10.5 13,3b 17,1u 15.4 17.6 36,6b 14.1 25.8 27,2b 18.2 10,7u 17 13.7 42.1 15.9 9.6 6.8 46,7p 20.1 6,5u 6.7 12,4i 11,9b 12.6
2006 total 15.5 15.4 12.6 17.3 5.1 9.1 13.6 13.5 12.1 15.5 30.5 12.4 20.6 14.9 14.8 8.2 14 12.6 39.9 12.6 9.8 5.4 39,1p 17.9 5.6 6.6 9,7i 12,4p 11.3
female 13.4 13.1 10 17 4.9 7.7 13.3 :u 9 10.8 24 10.6 17.1 8.2 10.4 5,8u 10.4 11.4 36.8 10.1 9.7 3.9 31,3p 18 4,0u 5.8 7,8i 11,3p 10.2male 17.6 17.6 15.1 17.7 5.4 10.5 13.9 19,8u 15.3 20.2 36.7 14.4 23.9 22.5 18.9 10,5u 17.6 13.8 42.8 15.1 10 6.9 46,6p 17.8 7,1u 7.3 11,8i 13,5p 12.3
2007 total 15.1 14.9 12.1 14.9 5.2 12,5b 12.5 14.4 11.6 14.6 31 12.6 19.7 12.5 15.1 7.4 12.5 11.4 38.3 11.7 10.7 5 36,9p 17.3 4,1u 6.5 9,1i 11,4p 16,6b
female 13 12.7 10.3 14.7 4.7 9,1b 11.8 :u 8.4 10.6 25.2 10.3 16.4 6.8 10.1 5,1u 8,4u 10.1 34.9 9.3 10.1 3.8 30,4p 17.4 2,2u 5.8 7,2i 10,0p 15,6bmale 17.1 17.1 13.9 15.2 5.7 15,7b 13.1 21.7 14.7 18.6 36.6 15.1 22.9 19.5 20 9,6u 16.6 12.6 41.3 14 11.4 6.2 43,1p 17.1 5,8u 7.2 11,2i 12,6p 17,6b
2008 total 14.9 14.8 12 14.8 5.6 11.5 11.8 14 11.3 14.8 31.9 11.8 19.7 13.7 15.5 7.4 13.4 11.7 39 11.4 10.1 5 35,4p 15.9 5,1u 6 9,8i 11,1p 17
female 12.9 12.6 10.6 15.5 5.4 9.2 11.2 8,2u 8 10.9 25.7 9.8 16.7 9.5 10.7 4,7u 10,9u 10.9 36.1 8.8 9.8 3.9 28,6p 16 2,6u 4.9 7,7i 9,9p 15.6male 16.9 17 13.4 14.1 5.8 13.7 12.4 19.8 14.6 18.5 38 13.8 22.6 19 20.2 10,0u 15.8 12.5 41.7 14 10.4 6.1 41,9p 15.9 7,2u 7.1 12,1i 12,3p 18.3
Source: Eurostat, Labour Force Survey u = data lack reliability due to low sample size / : = not available or unreliable data /  b = break / p = provisional
The results for SE are provisional from 2005 as some revisions are foreseen for the variable on educational attainment and on t he variable measuring participation in education and training
Due to changes in the survey characteristics or the transition to annual averages after the year 2000, data lack comparability with former years in DE and CY (from 2005)  
 
EN 169   EN 5. People living in jobless households: children (0-17 years) and prime-age adults (18-59 years), selected years (% of population in the relevant age group)
EU27 EU25 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
2001 Children 10,1e 10,0e 11.9 19.6 7.8 : 9.6 11.5 32.1 5.5 6.6 9.5 6.9 3.4 11.3 : 3.3 13.7 7.4 5.8 3.8 : 3.8 8 3.8 9.8 : : 17
Adults (18-59)
Total 10,2e 10,1e 13.3 17.7 7.8 : 9.8 11.3 13.4 9.4 7.5 10.2 10.4 5 13 .1 11.4 6.6 13.2 7.6 6.9 7.8 13.6 4.4 9.4 8.1 10.1 : : 11.2
Men 8,9e 8,8e 11.1 17.1 6.2 : 9 11.4 9.6 7 6.7 8.8 8.7 3.5 12.4 11.5 5.3 12 5.6 5.4 6.1 12.8 3.7 8.5 7 9.6 : : 9.1
Women 11,5e 11,4e 15.5 18.3 9.4 : 10.7 11.2 17.2 11.7 8.3 11.5 12.1 6.4 1 3.6 11.4 8.1 14.4 9.6 8.4 9.4 14.4 5.1 10.3 9.2 10.6 : : 13.3
2002 Children 10,2e 10,0e 13.1 19.4 7.7 5.7 10.3 11 11.1 5.3 6.5 9.1 7 3.2 10 .1 8.1 3.6 14.4 7.8 5.8 3.7 : 4.3 10,7b 3.6 11.6 : : 17.4
Adults (18-59)
Total 10,4e 10,2e 14 17.1 7.3 8.4 10.3 10.5 8.8 9.4 7.5 10.1 10 5.2 10.3 8.9 7.1 13 7.9 6.8 7.3 15 4.8 11,8b 8.2 10.5 : : 11.2
Men 9,1e 8,9e 11.7 16.8 5.5 7.9 9.7 10.7 7.5 7.1 6.8 8.8 8.4 3.9 10.6 8.7 6.3 12 6.3 5.5 5.9 14.1 4.1 10,6b 7.1 10 : : 9
Women 11,6e 11,4e 16.4 17.5 9.1 8.8 10.9 10.3 10 11.7 8.2 11.4 11.6 6. 4 10.1 9.1 7.9 14 9.6 8.2 8.8 15.9 5.4 12,9b 9.2 11.1 : : 13.3
2003 Children 10,2e 10,1e 13.2 17.9 8.6 5.7 11.1 8.4 11.8 4.6 6.2 9 6.9 2.6 8.1 7.5 3.9 13 8.8 6.8 4.1 : 4.7 10.3 3.9 11.8 5.7 : 17.1
Adults (18-59)
Total 10,4e 10,2e 14.4 15.9 7.7 9.4 10.9 10.2 9.1 9 7.3 10.1 9.6 5.1 8.8 8.2 7.5 11.7 8.5 7.8 6.8 15 5.3 11.5 8.8 10.3 11 : 11
Men 9,2e 9,0e 12.4 15.5 5.8 8.8 10.3 10.8 7.7 6.8 6.7 8.9 8.1 4.1 8.6 8.1 6 11 6.7 6.5 5.4 14 4.7 10.4 7.9 9.6 11.6 : 8.9
Women 11,5e 11,4e 16.3 16.2 9.7 10 11.5 9.7 10.4 11.3 8 11.3 11.2 5.9 8.9 8.3 9 12.5 10.4 9.1 8.1 16 5.9 12.6 9.7 11 10.3 : 13
2004 Children 10,1e 9,9e 13 16.5 9.1 6 11.4 8.7 11.8 4.7 6.2 8.9 5,9b 2.7 8.1 7.1 3.4 13.1 9.2 7.1 5,2b : 4.4 12.2 3.5 12.7 5.7 : 16.4
Adults (18-59)
Total 10,4e 10,2e 13.8 14.4 8 9.4 11.1 9.7 8.6 9.1 7.2 10.2 9,4b 5.1 8.1 7.8 7.1 12 8.8 7.9 8,2b 15.5 5.3 11.8 7.7 10.5 11.1 : 11
Men 9,3e 9,2e 11.6 14 6.3 9.2 10.8 10.3 7.2 6.8 6.6 9 8,1b 4 8 7.9 5.7 11.2 7 6.6 6,8b 14.5 4.9 11 7 9.8 11.2 : 9
Women 11,4e 11,3e 16 14.8 9.7 9.5 11.4 9.1 10 11.3 7.9 11.3 10,8b 6.2 8.2 7.7 8.5 12.8 10.8 9.1 9,5b 16.5 5.7 12.6 8.5 11.2 10.9 : 12.9
2005 Children 9,9e 9,7e 12.8 15.7 8.2 5.7 11,0b 8.8 11.9 4.2 5,6b 8.8 5.9 3.6 8 6.1 2.7 14.1 9.1 6.7 5.9 : 4.6 11.3 3.1 13.9 6.6 : 16.5
Adults (18-59)
Total 10,3e 10,1e 13.7 13.7 7.4 8.6 11,0b 8.6 8.3 8.9 6,6b 10.3 9.8 5.3 8 .5 6.8 6.7 12.3 8.2 7.9 8.4 14.8 5.7 11.3 7.1 10.3 10.5 : 10.9
Men 9,2e 9,1e 11.7 13.3 5.9 8.4 10,7b 9.7 6.9 6.7 6,1b 9.2 8.4 4.3 8.7 7.1 5.4 11.5 6.3 6.8 7.3 13.5 5.3 10.3 6.4 9.6 11 : 8.9
Women 11,3e 11,2e 15.7 14.1 8.9 8.7 11,2b 7.5 9.8 11.1 7,1b 11.5 11.1 6.2 8.3 6.6 8.1 13 10.1 9.1 9.4 16 6.1 12.2 7.8 11 10 : 12.8
2006 Children 9.8 9.7 12.7 15 8.1 5 10.6 6.9 11.2 3.9 5.3 9.3 5.7 3.9 7.1 6.8 3.7 13.7 9.3 6.4 6 11.1 4.6 10.3 3.4 12.1 4.9 : 16.5
Adults (18-59)
Total 9.8 9.7 13.6 12.1 7.2 7.7 10.5 6.6 7.8 8.1 6.3 10.5 9.5 5.2 6 .7 6.9 7.1 11.8 7.9 7.4 7.6 13.2 5.8 10.3 7.4 9.5 9.5 : 10.8
Men 8.8 8.7 11.8 11.6 5.7 7.1 10.2 6.5 6.5 6 5.8 9.4 8.1 4.3 6. 9 7.3 5.4 10.8 6 6.1 6.5 11.9 5.2 9.3 6.4 8.8 10.1 : 8.8
Women 10.9 10.8 15.4 12.6 8.6 8.3 10.8 6.6 9.2 10.3 6.8 11.6 10.9 6.1 6.6 6.6 8.9 12.7 9.8 8.6 8.7 14.4 6.3 11.2 8.5 10.1 9 : 12.7
2007 Children 9.4 9.3 12 12.8 8 5.3 9.6 7.2 11.5 3.9 5.3 8.8 5.8 3.9 8.3 8.3 3.4 13.9 9.2 5.9 5.3 9.5 5.1 10 2.2 10.6 4.4 : 16.7
Adults (18-59)
Total 9.3 9.2 12.3 10.2 6.5 8.1 9.5 6 7.9 8 6.2 10 9.2 4.7 6.6 7 7 11.9 7.7 6.5 7.1 11.6 5.7 10.4 6.5 8.9 9.1 : 10.7
Men 8.2 8.1 10.6 10.1 4.9 7.6 9.1 6.1 6.7 6 5.8 9 7.9 4.2 6.7 7.3 6 10.8 6.2 5.3 5.9 10.4 5.3 9.3 5.5 8.1 9.6 : 8.8
Women 10.3 10.3 13.9 10.3 8.1 8.5 9.9 5.9 9.3 10 6.7 11.1 10.6 5.2 6.6 6.8 7.9 12.9 9.3 7.6 8.4 12.7 6.1 11.5 7.5 9.6 8.6 : 12.7
2008 Children 9.2 9.2 11.3 11 7.4 3.3 9.3 6.8 13.1 3.6 6.5 8.5 6.7 3.9 7.6 9.9 3.6 14.6 8.7 4.8 5.3 8.2 4.7 9.9 2.6 8.6 4.1 : 16.4
Adults (18-59)
Total 9.2 9.1 12 9 6 6.8 9 6.2 9.2 7.5 7.4 9.8 9.6 4.9 6.4 9 7.9 12.5 8.1 5.9 7 10.1 5.5 10.5 6.4 7.5 8.1 : 10.7
Men 8.2 8.1 10.4 8.7 4.5 6.4 8.6 6.6 8.1 5.7 7.2 8.8 8.3 4.7 6.2 9.1 7.2 11.5 6.5 4.9 6 8.7 5.2 9.6 5.7 7 8.3 : 8.9
Women 10.1 10.1 13.6 9.4 7.6 7.2 9.4 5.8 10.3 9.3 7.7 10.8 10.9 5.2 6.5 9 8.6 13.4 9.8 6.9 8 11.5 5.8 11.5 7.1 8.1 7.8 : 12.5
u = data lack reliability due to low sample size / : = not available or unreliable data / b = break / p = provisional / e: esti mate
Due to changes in the survey characteristics, data lack comparability with former years in BG (from 2001), LV and LT (from 2002 ), RO (from 2002), LU (from 2003), HU (from 2003) and AT (from 2004: implementation of a continuous survey covering all weeks o f the reference quarter).
Source : Eurostat, Labour Force Survey  
 
EN 170   EN 6. Projected total public social expenditures
Total age-related public spending: pension, health care, long-term care, education and unemployment transfers (% of GDP) – base line scenario
http://ec.europa.eu/economy_finance/publications/publication14994_en.pdf (Table A 134 – The cost of ageing overview)
EU27 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
2007 23.1 26.5 16.6 17.9 24.8 23.6 14.3 17.2 22.1 19.3 28.4 26 15. 4 13.2 15.8 20 21.6 18.2 20.5 26 20.5 24.5 13.1 22.5 15.2 24.2 24.2 24.2
Change 2007 - 2020 0.5 1.7 -0.1 -0.7 2.6 0 0.2 1.4 1.9 1.4 0.9 0.3 1.3 -0.7 -0.7 1.2 -0.3 2.3 2.1 0.3 -2.7 0.8 2 1.8 -0.7 3- 0 . 30 . 8
Change 2007 - 2060 4.7 6.9 3.7 5.5 2.6 4.8 0.4 8.9 15.9 9 2.7 1.6 10.8 0.4 5.4 18 4.1 10.2 9.4 3.1 -2.4 3.4 10.1 12.1 5.2 6.3 2.6 5.1
7a. Relative median income ratio of people aged 65+ (relative to the complementary age group 0-64) (%), 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
Relative median 
income ratio (65+/0 -
64)Total
0,84p 0,85p 0.74 0.66 0.79 0.7 0.65 0.87 0.62 0.73 0.86 0.78 0,96b 0.88 0. 58 0.54 0.71 0.97 1 0.75 0.84 0.92 0.97 0.83 0.85 0.84 0.79 0.71 0.75 0,71p
 : = not available or unreliable data / b = break / p = provisional / e: estimate
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
7b. Aggregate replacement ratio (%), 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL(2)AT PL PT RO SI SK FI SE UK(2)
Total0,49p 0,5p 0.45 0.34 0.51 0.41 0.41 0.44 0.45 0.43 0.41 0.48 0,66b 0.51 0.32 0.3 0.44 0.58 0.59 0.44 0.43 0.68 0.56 0.51 0.49 0.44 0.54 0.48 0.59 0,41p
Men 0,53p 0,53p 0.44 0.37 0.48 0.38 0.38 0.47 0.37 0.4 0.48 0.53 0,69b 0.58 0.37 0.25 0.45 0.54 0.6 0.47 0.48 0.65 0.65 0.65 0.54 0.5 0.54 0.47 0.62 0,42p
Women 0,49p 0,49p 0.47 0.36 0.55 0.44 0.44 0.48 0.55 0.54 0.44 0.47 0,58b 0.39 0.36 0.34 0.46 0.59 0.6 0.45 0.51 0.69 0.53 0.49 0.45 0.4 0.55 0.48 0.55 0,44p
 : = not available or unreliable data / b = break / p = provisional / e: estimate
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
(2) Pensions from individual insurance private plans are not included, if included ratio for NL and UK would be higher
8a. Inequalities in access to health care (unmet need for care by income quintile for 3 reasons: too expensive, too long waitin g time, too far to travel), SILC 2008
EU 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
1st quintile 6.6 1.4 41.6 1 0.4 7.1 14.2 5.3 10 0.1 3.6 9.2 9.2 26.2 10.2 1.4 5.2 1.2 0.4 1 10.6 18.7 20.7 0.4 3.9 1 4.1 1.2
2nd quintile 4.6 0 19.6 0.6 0.2 4.9 9.4 2.1 6.9 0 1.8 6 4.8 13.8 7.8 0.3 3.7 1.5 0.3 0.7 8.7 11.7 16.9 0.2 1.2 1 3.7 1.6
3rd quintile 3.2 0.3 14.6 1.1 0.5 2.8 7.5 2.7 5.7 0.2 0.8 3.5 2.4 11.1 6.9 0.1 2.2 0.7 0.5 0.9 6.5 9.6 13.1 0.1 0.8 0.3 3.3 1.4
4th quintile 2.5 0 10.2 0.5 0.1 2.3 6.8 1.4 4.1 0.2 0.6 3.1 1.9 8 6.6 0.5 1.6 0.7 0.1 0.3 5.6 7.3 8.4 0.2 0.6 0.2 2.9 1.5
5th quintile 1.6 0 8.1 0.6 0.1 1.2 8 0.9 1.1 0.2 0.2 1.9 0.4 4.9 5 0.3 0.9 0.1 0.3 0.4 4.8 2.3 3.2 0 0.5 0.1 2.1 1.4
* This data should be interpreted with care when comparing levels of across countries due to a problem in the translation of th e questionnaire.
8b. Doctor's consultations
EU-27 EU-25 BE CZ DK EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT SI SK FI SE UK
: : 7.5 12.9 7.5 6.9 : : 8.1 6.4 7.0 2.0 5.2 6.8 6.0 12.9 1.9 5.6 6.7 6.6 3.9 7.2 10.4 4.3 2.8 5.1
Notes:  (:) = data not available
Source:  OECD Health Data. Calculated as the number of contacts with an ambulatory care physician divided by the population. Includes c ontacts in out-patient wards.Source: SILC(2008)  Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);  (1 ) with imputed rent data 2007 (see methodological note).
Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);  (1 ) with imputed rent data 2007 (see methodological note).Aggregate 
replacement ratio  
(Pensions 65-74 
/Earnings 50-59)
 
 
EN 171   EN 9. At-risk of poverty rate anchored at a fixed moment in time (poverty threshold of 2005),  2008
EU27 EU25 BE BG(1)CZ DK DK(2)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO(1)SI SK FI SE UK
Total population Total 1 2 p 1 3 p 1 5 : 61 181 351 0 1 9 1 6 1 2 b 1 89 7 51 491 181 381 7: 9 51 18 1 5 p
Men 12p 13p 14 : 6 11 9 13 6 10 18 15 11b 17 8 7 5 13 10 11 8 12 9 17 : 8 5 11 8 14p
Women 1 3 p 1 4 p 1 6 : 61 181 451 0 1 9 1 7 1 3 b 2 0 1 17 51 591 281 481 8:1 051 19 1 6 p
Children aged 0-17 Total 1 5 p 1 6 p 1 7 : 1 0 98 1 3 6 1 2 2 1 2 0 1 6 b 2 4 787 2 0 1 4 1 5 9 1 6 1 2 2 1 :8998 1 7 p
People aged 18-64 Total 11p 12p 13 : 6 11 10 14 6 10 17 13 12b 16 6 7 5 13 9 9 7 11 8 15 : 8 4 10 8 12p
Men 11p 12p 11 : 5 11 10 13 6 9 17 13 11b 15 5 6 6 13 9 8 7 11 9 14 : 8 5 11 9 11p
Women 1 2 p 1 3 p 1 4 : 6 1 1 1 0 1 4 5 1 0 1 8 1 4 1 2 b 1 7 775 1 4 1 0 1 0 8 1 2 8 1 6 :7498 1 3 p
People aged 65+ Total 1 4 p 1 5 p 2 2 : 3 1 6 3 1 3 39 2 0 2 1 9 b 2 0 3 2 8263 1 7 7 1 6 4 1 9 : 1 7 2 1 7 9 2 3 p
Men 1 2 p 1 3 p 2 1 : 1 1 4 3 1 1 1 1 0 1 9 2 0 8 b 1 7 2 7 4252 1 8 7 1 2 3 1 7 :91 1 2 6 2 0 p
Women 1 5 p 1 6 p 2 2 : 41 741 54 92 2 2 2 1 0 b 2 3 3 6 1 02 6 41 671 842 1:2 222 1 1 1 2 5 p
Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);  (1) BG, RO (:) data not available; (2) with imputed rent (see methodological note).
 : = not available or unreliable data / b = break / p = provisional / e: estimate
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
10. Employment rate of older workers (% of people aged 55-64)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
1998 total 36.2 35.8 22.9 : 37.1 52.0 37.7 50.2 41.7 39.0 35.1 28.3 27.7 : 36.3 39.5 25.1 17.3 : 33.9 28.4 32.1 49.6b 51.5 23.9 22.8 36.2 63.0 49.0
male 47.0 46.6 32.1 : 53.2 61.3 47.2 62.0 60.2 56.0 52.6 32.5 41.4 : 48. 1 54.4 35.2 27.0 : 47.5 40.5 41.5 62.9b 59.5 31.8 39.1 38.4 66.1 59.1
female 26.1 25.5 14.0 : 22.9 42.0 28.3 41.6 23.1 23.5 18.8 24.4 15.0 : 27.5 28.3 15.5 9.6 : 20.3 17.1 24.1 38.0b 44.5 16.1 9.4 34.1 60.0 39.2
2000 total 36.9 36.6 26.3 20.8 36.3 55.7 37.6 46.3 45.3 39.0 37.0 29.9 27.7 49.4 36.0 4 0.4 26.7 22.2 28.5 38.2 28.8 28.4 5 0.7 49.5 22.7 21.3 41.6 64.9 50.7
male 47.1 46.9 36.4 33.2 51.7 64.1 46. 4 55.9 63.2 55.2 54.9 33.6 40.9 67.3 48.4 50.6 37.2 33.2 50.8 50.2 41.2 36. 7 62.1 56.0 32.3 35.4 42.9 67.8 60.1
female 27.4 26.9 16.6 10.3 22.4 46.6 29.0 39.0 27. 2 24.3 20.2 26.3 15.3 32.1 26.7 32.6 16.4 13.3 8.4 26.1 17.2 21.4 40.6 43.8 13.8 9.8 40.4 62.1 41.7
2002 total 38.5 38.7 26.6 27.0 40.8 57.9 38.9 51.6 48.0 39.2 39.6 34.7 28.9 49.4 41.7 4 1.6 28.1 25.6 30.1 42.3 29.1 26.1 5 1.4 37.3b 24.5 22.8 47.8 68.0 53.4
male 48.4 48.8 36.0 37.0 57.2 64.5 47. 3 58.4 65.0 55.9 58.4 38.7 41.3 67.3 50.5 51.5 37.7 35.5 50.8 54.6 39.6 34. 5 61.9 42.7b 35.4 39.1 48.5 70.4 62.6
female 29.1 29.2 17.5 18.2 25.9 50.4 30.6 46.5 30. 8 24.0 21.9 30.8 17.3 32.2 35.2 34.1 18.4 17.6 10. 9 29.9 19.3 18.9 42.2 32.6b 14.2 9.5 47.2 65.6 44.5
2004 total 40.7 41.0 30.0 32.5 42.7 60.3 41.8 52.4 49.5 39.4 41.3 37.8 30.5b 49.9 47.9 4 7.1 30.4 31.1 31.5 45.2 28.8b 26.2 50.3 36.9 29.0 26.8 50.9 69.1 56.2
male 50.4 50.8 39.1 42.2 57.2 67.3 50. 7 56.4 65.0 56.4 58.9 41.7 42.2b 70.8 55.8 57.6 38.3 38.4 53.4 56.9 38.9b 34 .1 59.1 43.1 40.9 43.8 51.4 71.2 65.7
female 31.6 31.8 21.1 24.2 29.4 53.3 33.0 49.4 33.7 24.0 24.6 34.2 19.6b 30.0 41.9 39.3 22.2 25.0 11.5 33.4 19.3b 19.4 42.5 31.4 17.8 12.6 50.4 67.0 47.0
2006 total 43.5 43.6 32.0 39.6 45.2 60.7 48.4 58.5 53.1 42.3 44.1 38.1 32.5 53.6 53.3 4 9.6 33.2 33.6 29.8 47.7 35.5 28.1 5 0.1 41.7 32.6 33.1 54.5 69.6 57.3
male 52.7 52.8 40.9 49.5 59.5 67.1 56. 4 57.5 67.0 59.2 60.4 40.4 43.7 71.6 59.5 55.7 38.7 41.4 49.4 58.0 45.3 38. 4 58.2 50.0 44.5 49.8 54.8 72.3 66.0
female 34.9 35.0 23.2 31.1 32.1 54.3 40.6 59.2 39.1 26.6 28.7 35.8 21.9 36.6 48.7 45.1 27.8 27.1 10.8 37.2 26.3 19.0 42.8 34.5 21.0 18.9 54.3 66.9 49.0
2007 total 44.6 44.8 34.4 42.6 46.0 58.6 51.5 60.0 53.8 42.4 44.6 38.2 33.8 55.9 57.7 5 3.4 32.0 33.1 28.5 50.9 38.6 29.7 5 0.9 41.4 33.5 35.6 55.0 70.0 57.4
male 53.9 54.1 42.9 51.8 59.6 64.9 59. 7 59.4 67.9 59.1 60.0 40.4 45.1 72.5 64.6 60.8 35.6 41.7 45.9 61.5 49.8 41. 4 58.6 50.3 45.3 52.5 55.1 72.9 66.3
female 35.9 36.1 26.0 34.5 33.5 52.4 43.6 60.5 39.6 26.9 30.0 36.0 23.0 40.3 52.4 47.9 28.6 26.2 11.6 40.1 28.0 19.4 44.0 33.6 22.2 21.2 55.0 67.0 48.9
2008 total 45.6 45.7 34.5 46.0 47.6 57.0 53.8 62.4 53.6 42.8 45.6 38.2 34.4 54.8 59.4 5 3.1 34.1 31.4 29.2 53.0 41.0 31.6 5 0.8 43.1 32.8 39.2 56.5 70.1 58.0
male 55.0 55.0 42.8 55.8 61.9 64.3 61. 8 65.2 66.0 59.1 60.9 40.5 45.5 70.9 63.1 60.2 38.7 38.5 46.4 63.7 51.8 44. 1 58.5 53.0 44.7 56.7 57.1 73.4 67.3
female 36.8 36.9 26.3 37.7 34.4 49.8 46.1 60.3 41.0 27.5 31.1 36.0 24.0 39.4 56.7 47.8 29.3 25.7 12.5 42.2 30.8 20.7 43.9 34.4 21.1 24.2 55.8 66.7 49.0
b= break in data series / : = data not available
Source : Eurostat - Labour Force Survey, Annual averages.  
 
EN 172   EN 11. In work at-risk-of-poverty rate after social transfers by gender  (Age 18+), 2008
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
Total 8 p8 p 5 7 456776 1 4 1 1 7 b 96 1 1 995556 1 2 1 2 1 7 5657 9 p
Men 9p 8p 4 8 3 6 6 6 6 7 16 12 7b 11 6 11 9 9 6 6 5 6 12 12 19 6 6 5 7 8p
Women 8 p8 p 5 7 445796 1 2 9 6 b 67 1 1 1 0 1 0 4256 1 0 1 1 1 5 4556 9 p
 : = not available or unreliable data / b = break / p = provisional / e: estimate
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.
12. Activity rates  (% of population aged 15-64)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
1998 Total : 68.0 63.5 : 72.0 79.7 70.8 72.2 65.6 63.2 63.0 68.4 59.0 : 69 .8 72.1 62.1 58.7 : 73.0 71.0 65.7 70.6b 68.9 68.2 69.3 72.3 76.2 75.4
Male : 77.4 72.8 : 80.0 83.8 79.2 79.0 78.2 77.6 77.3 75.2 73.6 : 76.4 78.2 75.9 66.6 : 82.6 80.3 72.8 79.3b 75.7 72.6 77.2 75.6 79.0 83.2
Female : 58.7 54.0 : 64.0 75.6 62.2 66.4 52.9 49.0 48.9 61.9 44.6 : 63 .9 66.5 48.1 51.2 : 63.2 61.7 58.8 62.3b 62.3 63.6 61.7 69.1 73.5 67.4
2000 Total 68.6 68.7 65.1 60.7 71.3 80.0 71.1 70.2 68.2 63.8 65.4 68.7 60.1 69. 1 67.2 70.8 64.1 60.1 58.0 75.2 71.0 65.8 71.4 68.4 67.5 69.9 74.5 77.3 75.5
Male 77.2 77.5 73.7 66.2 79.1 84.2 78.9 75.6 79.9 77.4 78.8 75.2 74.1 81.4 7 2.7 74.5 76.3 67.9 80.5 84.1 80.1 71.7 79.2 75.0 71.9 76.8 77.2 79.8 82.9
Female 60.1 60.0 56.4 55.6 63.6 75.6 63.3 65.3 56.3 50.5 52.0 62.4 46.3 57.7 6 2.1 67.3 51.6 52.7 35.2 66.0 62.0 59.9 63.9 61.9 62.9 63.2 71.9 74.8 68.2
2002 Total 68.6 69.0 64.8 61.9 70.6 79.6 71.7 69.3 68.6 64.2 66.2 69.1 61.1 71. 2 68.8 69.6 65.2 59.7 58.5 76.5 71.6 64.6 72.7 63.4b 67.8 69.9 74.9 77.6 75.3
Male 76.8 77.4 73.2 66.4 78.6 83.6 78.8 74.6 79.2 77.6 79.1 75.5 74.3 81.3 7 4.1 73.6 76.7 67.1 80.1 84.5 79.6 70.6 80.0 70.4b 72.5 76.7 77.0 79.4 82.4
Female 60.5 60.7 56.3 57.5 62.7 75.5 64.4 64.4 57.8 51.0 53.1 63.0 47.9 61.8 6 3.9 65.8 53.6 52.7 36.7 68.3 63.7 58.7 65.6 56.6b 63.0 63.2 72.8 75.8 68.3
2004 Total 69.8 70.3 66.7 62.1 70.4 79.8 74.3b 70.1 70.8 66.8 69.7b 70.0 62.5 72. 4 69.6 68.4 66.6 61.3 58.1 76.9 72.4 64.4 73.4 62.3 70.7 68.9 74.7 78.7b 75. 4
Male 77.3 77.9 73.9 67.0 78.4 83.6 80.6b 73.6 80.6 79.2 80.9b 75.3 74.6 82.9 7 4.4 72.1 76.0 67.9 79.1 83.7 79.3 70.8 79.0 69.4 75.1 76.5 76.6 80.9b 82.0
Female 62.4 62.8 59.5 57.3 62.4 75.9 68.0b 66.9 60.8 54.5 58.3b 64.8 50.4 62.5 6 5.1 64.9 57.0 55.1 36.9 70.0 65.6 58.1 67.9 55.3 66.1 61.5 72.8 76.3b 68.8
2006 Total 70.3 70.7 66.5 64.5 70.3 80.6 75.3 72.4 71.8 67.0 70.8 69.9 62.7 73. 0 71.3 67.4 66.7 62.0 57.6 77.4 73.7 63.4 73.9 63.6 70.9 68.6 75.2 78.8 75.7
Male 77.6 78.1 73.4 68.8 78.3 84.1 81.3 75.8 81.5 79.1 81.3 75.0 74.6 82.7 7 6.2 70.5 75.3 68.7 78.1 83.9 80.5 70.1 79.5 70.7 74.9 76.4 77.1 81.2 82.3
Female 63.0 63.4 59.5 60.2 62.3 77.0 69.3 69.3 61.9 55.0 60.2 64.9 50.8 63.8 6 6.7 64.6 58.2 55.5 36.5 70.7 67.0 56.8 68.4 56.6 66.7 60.9 73.3 76.3 69.2
2007 Total 70.5 70.9 67.1 66.3 69.9 80.2 76.0 72.9 72.4 67.0 71.6 70.0 62.5 73. 9 72.8 67.9 66.9 61.9 58.4 78.5 74.7 63.2 74.1 63.0 71.3 68.3 75.6 79.1 75.5
Male 77.7 78.2 73.6 70.6 78.1 83.9 81.8 77.5 81.4 79.1 81.4 74.8 74.4 82.9 7 7.6 71.0 75.0 69.0 77.6 84.6 81.7 70.0 79.4 70.1 75.8 75.9 77.2 81.4 82.2
Female 63.3 63.7 60.4 62.1 61.5 76.4 70.1 68.7 63.3 54.9 61.4 65.3 50.7 65.4 6 8.3 65.0 58.9 55.1 38.6 72.2 67.8 56.5 68.8 56.0 66.6 60.8 73.8 76.8 69.0
2008 Total 70.9 71.4 67.1 67.8 69.7 80.8 76.5 74.0 72.0 67.1 72.6 70.1 63.0 73. 6 74.4 68.4 66.8 61.5 58.8 79.3 75.0 63.8 74.2 62.9 71.8 68.8 76.0 79.3 75.8
Male 78.0 78.4 73.3 72.5 78.1 84.4 82.1 78.3 80.7 79.1 81.8 74.8 74.4 82.0 7 8.6 71.4 74.7 68.3 76.9 85.3 81.4 70.9 79.5 70.6 75.8 76.4 77.9 81.7 82.4
Female 63.9 64.3 60.8 63.1 61.0 77.1 70.8 70.1 63.1 55.1 63.2 65.6 51.6 65.7 7 0.5 65.5 58.7 55.0 40.2 73.3 68.6 57.0 68.9 55.2 67.5 61.3 73.9 76.9 69.4
Source : Eurostat - Labour Force Survey, Annual averages.
b= break in data series / : = data not availableSource: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);(1) with imputed rent data 2007 (see methodological note).In work
 
 
EN 173   EN 13. Dispersion of regional employment rates*, selected years (%)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 1 3 . 0 : 7 . 9 : 5 . 8 : 5 . 4 -: 5 . 1 1 0 . 7 6 . 9 1 7 . 5 ---- 9 . 0 - 2 . 2 2 . 5 6 . 9 4 . 3 4 . 6 : 9 . 1 6 . 8 4 . 5 7 . 1
2004 1 2 . 1 : 8 . 7 6 . 9 5 . 6 : 6 . 0 -: 4 . 1 8 . 7 7 . 1 1 5 . 6 ---- 9 . 4 - 2 . 3 3 . 5 6 . 4 3 . 5 4 . 9 : 9 . 0 5 . 5 4 . 4 5 . 9
2005 1 1 . 9 : 8 . 4 7 . 2 5 . 5 : 5 . 6 -: 4 . 3 8 . 3 7 . 2 1 6 . 0 ---- 9 . 9 - 2 . 0 4 . 1 5 . 6 3 . 3 4 . 5 : 9 . 8 5 . 5 3 . 0 5 . 7
2006 1 1 . 4 : 8 . 7 7 . 3 5 . 2 : 5 . 2 -: 3 . 7 7 . 8 7 . 4 1 6 . 0 ---- 9 . 1 - 2 . 2 3 . 4 5 . 1 3 . 1 3 . 6 : 8 . 6 5 . 4 2 . 9 5 . 5
2 0 0 7 1 1 . 1 : 8 . 6 7 . 1 4 . 6 : 4 . 8 -: 3 . 5 7 . 5 6 . 6 1 6 . 3 ---- 9 . 7 - 2 . 2 3 . 8 4 . 5 3 . 3 4 . 6 : 8 . 3 5 . 6 2 . 4 5 . 4
* Coefficient of variation of employment rates across regions at NUTS2 level
: not available; - not applicable or real zero or zero by default
Source : Eurostat - Labour Force Survey, Annual averages
14. Total health expenditure per capita PPS
EU 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
1990 1 2 1 9 : 5 0 3 1 3 8 7 1 5 8 8 : 7 0 9 7 6 6 7 8 3 1 3 0 1 1 2 2 1 :::::: 1 2 7 2 1 4 5 3 2 6 1 5 6 1 ::: 1 2 2 7 1 4 3 3 8 6 4
1991 1 3 5 3 : 4 9 2 1 4 4 7 :: 8 0 5 7 9 4 8 6 6 1 4 1 2 1 3 3 9 :::: 5 2 0 : 1 3 8 0 1 5 6 2 3 1 4 6 6 9 ::: 1 3 6 7 1 4 3 7 9 5 5
1992 1 4 4 2 : 5 2 0 1 5 2 4 1 8 0 8 : 9 2 2 8 9 0 9 4 1 1 5 0 8 1 3 9 3 :::: 5 6 3 : 1 4 6 8 1 6 7 7 3 3 5 7 3 5 ::: 1 3 7 9 1 4 8 3 1 0 5 7
1993 1 4 5 4 : 6 9 0 1 5 9 4 1 7 9 2 : 9 3 4 9 7 7 9 7 6 1 5 7 5 1 3 7 9 :::: 5 6 5 : 1 5 0 5 1 7 8 6 3 3 4 7 7 1 ::: 1 2 5 2 1 4 9 3 1 0 8 7
1994 1 4 8 5 : 7 3 3 1 6 6 7 1 9 1 1 : 1 0 0 3 1 1 0 2 9 9 9 1 6 2 7 1 3 8 2 :::: 6 3 7 : 1 5 4 3 1 9 2 3 3 3 7 8 0 0 ::: 1 2 3 3 1 4 9 6 1 1 6 5
1995 1553 : 754 1569 1907 : 1009 1059 1000 1762 1289 : : : 1602 553 : 1508 1858 344 868 : : : 1242 1463 1131
1996 1628 : 777 1676 2032 : 1084 1102 1058 1831 1366 : : : 1686 558 : 1578 1932 405 945 : : : 1315 1577 1216
1997 1683 : 788 1761 2062 : 1192 1158 1110 1902 1477 : : : 1686 580 : 1638 2065 425 1014 : : 381 1373 1612 1272
1998 1516 1748 : 793 1863 2127 : 1284 1184 1184 1977 1566 : : : 1784 654 : 1759 2202 479 1036 : : 381 1426 1697 1335
1999 1604 1883 : 812 1973 2243 : 1406 1270 1255 2073 1626 : : : 2063 701 : 1884 2336 496 1150 : : 354 1513 1843 1452
2000 1713 2071 : 854 2071 2326 : 1572 1262 1338 2214 1787 : : : 2224 742 : 2035 2459 507 1314 : : 371 1614 1989 1596
2001 1813 2133 : 929 2165 2411 : 1827 1507 1405 2334 1901 : : : 2350 833 : 2194 2468 551 1346 : : 397 1689 2154 1720
2002 1924 2295 : 1021 2304 2510 : 2023 1680 1492 2497 1900 : : : 2634 952 : 2421 2613 626 1417 : : 440 1833 2305 1873
2003 1906 2663 526 1131 2393 2609 566 2131 1715 1705 2524 1920 1250 : : 3853 1099 : 2607 2707 633 1542 323 1497 486 1867 2400 1964
2004 1992 2786 547 1167 2571 2660 639 2318 1762 1791 2623 2020 1247 : 623 4229 1116 : 2773 2860 680 1611 368 1565 670 2030 2494 2153
2005 2091 2832 600 1217 2639 2804 696 2371 1971 1899 2766 2123 1301 694 697 4377 1205 : 2876 2894 717 1759 405 1647 954 2127 2487 2255
2006 2195 2877 624 1258 2795 2887 786 2500 2122 2052 2849 2227 1363 : 810 : 1243 : 2990 2975 767 1832 408 1719 1101 2213 2635 2404
2007 2 2 0 5 :: : ::: 2 8 4 4 2 2 6 5 :: 2 2 3 2 ::::::::::::::: 2 4 8 6
Source: OECD health data and Eurostat
AMECO PPS  
 
EN 174   EN Context 1: Growth rate of GDP volume - percentage change over previous yea r
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 3.9 3.9 3.7 5.4 3.6 3.5 3.2 10.0 9.4 4.5 5.0 3.9 3.7 5. 0 6.9 3.3 8.4 4.9 : 3.9 3.7 4.3 3.9 2.4 4.4 1.4 5.1 4.4 3.9
2006 3.2 3.2 2.8 6.3 6.8 3.4 3.2 10.0 5.4 4,5(p) 4.0 2.2 2.0 4 .1 12.2 7.8 5.6 4.0 3.5 3.4 3.5 6.2 1.4 7.9 5.8 8.5 4.9 4.2 2.9
2007 2.9 2.8 2.9 6.2 6.1 1.7 2.5 7.2 6.0 4,5(p) 3.6 2.3 1.6 5.1 10.0 9.8 6.5 1.0 4.0 3.6 3.5 6.8 1.9 6.3 6.8 10.6 4.2 2.5 2.6
2008 0.8 0.7 1.0 6.0 2.5 -0.9 1.3 -3.6 -3.0 2,0(p) 0.9 0.4 -1.0 3.6 -4.6 2.8 0.0 0.6 2.1 2.0 2.0 5.0 0.0 7.3 3.5 6.2 1.0 -0.2 0.5
2009f -4.1 -4.1 -2.9 -5.9 -4.8 -4.5 -5.0 -13.7 -7.5 -1.1 -3.7 -2.2 -4.7 -0.7 -18.0 -18.1 -3.6 -6.5 -2.2 -4.5 -3.7 1.2 -2.9 -8.0 -7.4 -5.8 -6.9 -4.6 -4.6
2010f 0.7 0.7 0.6 -1.1 0.8 1.5 1.2 -0.1 -1.4 -0.3 -0.8 1.2 0.7 0.1 -4.0 -3.9 1.1 -0.5 0.7 0.3 1.1 1.8 0.3 0.5 1.3 1.9 0.9 1.4 0.9
2011f 1.6 1.6 1.5 3.1 2.3 1.8 1.7 4.2 2.6 0.7 1.0 1.5 1.4 1.3 2.0 2.5 1.8 3.1 1.6 1.6 1.5 3.2 1.0 2.6 2.0 2.6 1.6 2.1 1.9
Source : Eurostat, Annual national accounts; forecast for 2009, 2010, 2011
f = forecast 
Context 1: GDP per capita in Purchasing Power Standards (PPS),  (EU-27 = 100)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 100 105.0 126.1 27.8 68.5 131.6 118.5 45.0 130. 9 84.1 97.4 115.4 116.9 88.8 36.7 39.3 243.7 55.3 83 .6 134.3 131.4 48.3 78.0 26.1 79.8 50.1 117.2 126.7 119.0
2006 100 103.9 117.7 36.5 77.0 124.2 116.1 65.1 145. 5 93,0p 104.6 108.8 104.2 90.7 51.6 55.3 272.2 63.2 76.8 131.2 124.4 51.9 76.4 38.4 87.6 63.4 115.0 121 .1 120.3
2007 100 103.7 115.7 37.7 80.1 121.3 115.8 68.8 148. 1 92,8p 105.0 108.5 103.4 93.6 55.7 59.3 275.2 62.6 76.4 132.2 122.8 54.4 75.6 41.6 88.6 67.7 118.0 122 .8 116.7
2008 100 103.4 115.1 41.3 80.3 120.1 115.6 67.4 135. 4 94,3p 102.6 107.9 102.0 95.8 57.3 61.9 276.3 64.4 76.3 134.0 123.3 56.4 76.0 48.0 90.9 72,2e 117.2 12 0.0 116.2
2009f 100 : 115.6 38.3 78.0 114.4 112.7 58.7 132.7 95.4 101.0 107.3 96.0 94.3 46.3 51.6 260.5 59.8 77.6 128.5 122.4 57.9 7 4.6 43.1 87.1 67.8 109.4 116.0 113.7
2010f 100 : 115.1 38.0 78.2 115.6 113.8 58.5 130.2 94.5 99.0 107.7 96.0 93.3 44.6 49.8 259.8 59.4 77.3 128.0 122.9 58.8 7 4.5 43.3 87.9 68.8 109.7 117.0 113.5
2011f 100 : 114.5 38.8 78.7 115.9 114.3 60.1 131.6 93.4 97.9 107.3 95.6 92.4 45.1 50.6 257.9 60.4 76.9 127.8 122.7 59.8 7 4.1 43.9 88.2 68.8 109.7 117.8 113.3
Source: Eurostat, Annual national accounts; forecast for 2009, 2010, 2011
f = forecast / : = not available or unreliable data / b = break / p = provisional / e: estimate
Context 2a: Employment rate  (% of population aged 15-64)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 total 62.2 62.4 60.5 50.4 65.0 76.3 65.6 60.4 65.2 56.5 56.3 62.1 53.7 65. 7 57.5 59.1 62.7 56.3 54.2 72.9 68.5 55. 0 68.4 63.0 62.8 56.8 67.2 73.0 71.2
male 70.8 71.3 69.5 54.7 73.2 80.8 72.9 64.3 76.3 71.5 71.2 69.2 68.0 78.7 6 1.5 60.5 75.0 63.1 75.0 82.1 77.3 61. 2 76.5 68.6 67.2 62.2 70.1 75.1 77.8
female 53.7 53.6 51.5 46.3 56.9 71.6 58.1 56.9 53.9 41.7 41.3 55.2 39.6 53.5 5 3.8 57.7 50.1 49.7 33.1 63.5 59.6 48. 9 60.5 57.5 58.4 51.5 64.2 70.9 64.7
2002 total 62.4 62.8 59.9 50.6 65.4 75.9 65.4 62.0 65.5 57.5 58.5 63.0 55.5 68. 6 60.4 59.9 63.4 56.2 54.4 74.4 68.7 51. 5 68.8 57,6b 63.4 56.8 68.1 73.6 71.4
male 70.4 71.0 68.3 53.7 73.9 80.0 71.8 66.5 75.4 72.2 72.6 69.5 69.1 78.9 6 4.3 62.7 75.1 62.9 74.7 82.4 76.4 56. 9 76.5 63,6b 68.2 62.4 70.0 74.9 77.7
female 54.4 54.7 51.4 47.5 57.0 71.7 58.9 57.9 55.4 42.9 44.4 56.7 42.0 59.1 5 6.8 57.2 51.6 49.8 33.9 66.2 61.3 46. 2 61.4 51,8b 58.6 51.4 66.2 72.2 65.2
2004 total 63.0 63.4 60.3 54.2 64.2 75.7 65.0 63.0 66.3 59.4 61.1 63.8 57,6b 68.9 62.3 61.2 62.5 56.8 54.0 73.1 67,8b 51.7 67.8 57.7 65.3 57.0 67.6 72.1 71.7
male 70.4 71.0 67.9 57.9 72.3 79.7 70.8 66.4 75.9 73.7 73.8 69.5 70,1b 79.8 66.4 64.7 72.8 63.1 75.1 80.2 74,9b 57.2 74.2 63.4 70.0 63.2 69.7 73.6 77.9
female 55.6 55.8 52.6 50.6 56.0 71.6 59.2 60.0 56.5 45.2 48.3 58.3 45,2b 58.7 58.5 57.8 51.9 50.7 32.7 65.8 60,7b 46.2 61.7 52.1 60.5 50.9 65.6 70.5 65.6
2005 total 63.5 64.0 61.1 55.8 64.8 75.9 66,0b 64.4 67.6 60.1 63,3b 63.7 57.6 68 .5 63.3 62.6 63.6 56.9 53.9 73.2 68.6 52.8 67.5 57.6 66.0 57.7 68.4 72,5b 71. 7
male 70.8 71.4 68.3 60.0 73.3 79.8 71,3b 67.0 76.9 74.2 75,2b 69.2 69.9 79.2 67.6 66.1 73.3 63.1 73.8 79.9 75.4 58.9 73.4 63.7 70.4 64.6 70.3 74,4b 77.7
female 56.3 56.6 53.8 51.7 56.3 71.9 60,6b 62.1 58.3 46.1 51,2b 58.4 45.3 58 .4 59.3 59.4 53.7 51.0 33.7 66.4 62.0 46.8 61.7 51.5 61.3 50.9 66.5 70,4b 65.8
2006 total 64.5 64.8 61.0 58.6 65.3 77.4 67.5 68.1 68.6 61.0 64.8 63.7 58.4 69. 6 66.3 63.6 63.6 57.3 53.6 74.3 70.2 54. 5 67.9 58.8 66.6 59.4 69.3 73.1 71.6
male 71.6 72.1 67.9 62.8 73.7 81.2 72.8 71.0 77.7 74.6 76.1 68.9 70.5 79.4 7 0.4 66.3 72.6 63.8 73.3 80.9 76.9 60. 9 73.9 64.6 71.1 67.0 71.4 75.5 77.5
female 57.3 57.6 54.0 54.6 56.8 73.4 62.2 65.3 59.3 47.4 53.2 58.6 46.3 60.3 6 2.4 61.0 54.6 51.1 33.4 67.7 63.5 48. 2 62.0 53.0 61.8 51.9 67.3 70.7 65.8
2007 total 65.4 65.8 62.0 61.7 66.1 77.1 69.4 69.4 69.1 61.4 65.6 64.3 58.7 71. 0 68.3 64.9 64.2 57.3 54.6 76.0 71.4 57. 0 67.8 58.8 67.8 60.7 70.3 74.2 71.5
male 72.5 73.0 68.7 66.0 74.8 81.0 74.7 73.2 77.4 74.9 76.2 69.2 70.7 80.0 7 2.5 67.9 72.3 64.0 72.9 82.2 78.4 63. 6 73.8 64.8 72.7 68.4 72.1 76.5 77.5
female 58.3 58.6 55.3 57.6 57.3 73.2 64.0 65.9 60.6 47.9 54.7 59.7 46.6 62.4 6 4.4 62.2 56.1 50.9 35.7 69.6 64.4 50. 6 61.9 52.8 62.6 53.0 68.5 71.8 65.5
2008 total 65.9 66.3 62.4 64.0 66.6 78.1 70.7 69.8 67.6 61.9 64.3 64.9 58.7 70. 9 68.6 64.3 63.4 56.7 55.3 77.2 72.1 59. 2 68.2 59.0 68.6 62.3 71.1 74.3 71.5
male 72.8 73.2 68.6 68.5 75.4 81.9 75.9 73.6 74.9 75.0 73.5 69.6 70.3 79.2 7 2.1 67.1 71.5 63.0 72.5 83.2 78.5 66. 3 74.0 65.7 72.7 70.0 73.1 76.7 77.3
female 59.1 59.4 56.2 59.5 57.6 74.3 65.4 66.3 60.2 48.7 54.9 60.4 47.2 62.9 6 5.4 61.8 55.1 50.6 37.4 71.1 65.8 52. 4 62.5 52.5 64.2 54.6 69.0 71.8 65.8
Source : Eurostat - Labour Force Survey, Annual averages.
b= break in data series  
 
EN 175   EN Context 2b: Unemployment rate (% of labour force aged 15+)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 Total 8.7 8.6 6.9 16.4 8.7 4.3 7.5 12.8 4.3 11.2 11.1 9.0 10.1 4.9 13.7 16.4 2.2 6.4 6.7 2.8 3.6 16.1 4.0 7.3 6.7 18.8 9.8 5.6 5.4
Males 7.8 7.6 5.6 16.7 7.3 3.9 7.5 13.8 4.4 7.4 7.9 7.5 7.8 3.2 14.4 18.6 1.8 7.0 6.4 2.2 3.1 14.4 3.2 8.0 6.5 18.9 9.1 5.9 5.9
Females 9.8 9.9 8.5 16.2 10.3 4.8 7.5 11.7 4.2 17.1 16.0 10.8 13.6 7.2 12.9 14.1 2.9 5.6 7.4 3.6 4.3 18.2 5.0 6.5 7.0 18.6 10.6 5.3 4.8
2002 Total 8.9 8.8 7.5 18.2 7.3 4.6 8.4 10.3 4.5 10.3 11.1 8.6 8.6 3 .6 12.2 13.5 2.6 5.8 7.5 2.8 4.2 20.0 5.1 8.6 6.3 18.7 9.1 6.1 5.1
Males 8.3 8.1 6.7 18.9 6.0 4.3 8.8 10.8 4.7 6.8 8.1 7.7 6.7 2.9 13.3 14.2 2.0 6.2 6.6 2.5 4.0 19.2 4.2 9.2 5.9 18.6 9.1 6.4 5.7
Females 9.7 9.7 8.6 17.3 9.0 5.0 7.9 9.7 4.1 15.7 15.7 9.7 11.5 4.5 10.9 12.7 3.5 5.4 9.3 3.1 4.4 21.0 6.1 7.9 6.8 18.7 9.1 5.8 4.5
2004 Total 9.1 9.1 8.4 12.1 8.3 5.5 9.8 9.7 4.6 10.5 10.6 9.3 8.0 4.7 10.4 11.4 5.0 6.1 7.4 4.6 4.9 19.0 6.7 8.1 6.3 18.2 8.8 7.7 4.7
Males 8.5 8.4 7.5 12.6 7.1 5.1 10.3 10.4 4.9 6.6 8.0 8.4 6.4 3.6 10.6 11.0 3.6 6.1 6.6 4.3 4.5 18.2 5.9 9.1 5.9 17.4 8.7 7.9 5.1
Females 9.8 9.9 9.5 11.5 9.9 6.0 9.1 8.9 4.1 16.2 14.3 10.3 10.5 6 .0 10.2 11.8 6.8 6.1 9.0 4.8 5.4 20.0 7.7 6.9 6.9 19.2 8.9 7.5 4.2
2005 Total 8.9 9.0 8.5 10.1 7.9 4.8 10.7 7.9 4.4 9.9 9.2 9.3 7.7 5.3 8.9 8.3 4.6 7.2 7.2 4.7 5.2 17.8 7.7 7.2 6.5 16.3 8.4 7.7 4.8
Males 8.3 8.3 7.6 10.3 6.5 4.4 11.2 8.8 4.6 6.1 7.1 8.4 6.2 4.3 9.1 8.2 3.6 7.0 6.4 4.5 4.9 16.6 6.8 7.8 6.1 15.5 8.2 7.8 5.2
Females 9.6 9.8 9.5 9.8 9.8 5.3 10.1 7.1 4.0 15.3 12.2 10.3 10.0 6.5 8.7 8.3 6.0 7.4 8.9 5.1 5.5 19.2 8.8 6.4 7.1 17.2 8.6 7.7 4.3
2006 Total 8.2 8.2 8.3 9.0 7.2 3.9 9.8 5.9 4.5 8.9 8.5 9.2 6.8 4.6 6.8 5.6 4.6 7.5 7.1 3.9 4.8 13.9 7.8 7.3 6.0 13.4 7.7 7.1 5.4
Males 7.6 7.5 7.4 8.7 5.8 3.3 10.2 6.2 4.6 5.6 6.3 8.4 5.4 4.0 7.4 5.8 3.6 7.2 6.3 3.5 4.3 13.0 6.6 8.2 4.9 12.3 7.4 6.9 5.8Females 8.9 9.0 9.3 9.3 8.9 4.5 9.5 5.6 4.2 13.6 11.6 10.1 8.8 5.4 6.2 5.4 6.0 7.8 8.7 4.4 5.2 14.9 9.1 6.1 7.2 14.7 8.1 7.3 4.9
2007 Total 7.1 7.2 7.5 6.9 5.3 3.8 8.4 4.7 4.6 8.3 8.3 8.4 6.1 4.0 6.0 4.3 4.2 7.4 6.4 3.2 4.4 9.6 8.1 6.4 4.9 11.1 6.9 6.2 5.3
Males 6.6 6.6 6.7 6.5 4.2 3.5 8.5 5.4 4.9 5.2 6.4 7.8 4.9 3.4 6.4 4.3 3.4 7.1 5.9 2.8 3.9 9.0 6.7 7.2 4.0 9.9 6.5 5.9 5.6
Females 7.8 7.9 8.5 7.3 6.7 4.2 8.3 3.9 4.2 12.8 10.9 9.0 7.9 4.6 5.6 4.3 5.1 7.7 7.5 3.6 5.0 10.4 9.7 5.4 5.9 12.7 7.2 6.5 5.0
2008 Total 7.0 7.1 7.0 5.6 4.4 3.3 7.3 5.5 6.0 7.7 11.3 7.8 6.7 3.6 7.5 5.8 4.9 7.8 5.9 2.8 3.8 7.1 7.7 5.8 4.4 9.5 6.4 6.2 5.6
Males 6.6 6.6 6.5 5.5 3.5 3.0 7.4 5.8 7.1 5.1 10.1 7.3 5.5 3.1 8.0 6.1 4.1 7.6 5.6 2.5 3.6 6.4 6.6 6.7 4.0 8.4 6.1 5.9 6.1
Females 7.5 7.6 7.6 5.8 5.6 3.7 7.2 5.3 4.6 11.4 13.0 8.4 8.5 4.2 6.9 5.6 5.9 8.1 6.6 3.0 4.1 8.0 9.0 4.7 4.8 10.9 6.7 6.6 5.1
Source:  Eurostat - LFS adjusted series, Annual average
p = provisional value /  b = break in data series
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 Total 17.4 17 16.7 33.7 17.8 6.2 7.5 23.9 6.9 29.1 24.3 19.6 27 10.1 21.4 30.6 6.6 12.4 13.7 5.7 5.3 35.1 8.6 20 16.3 36.9 21.4 10.5 12.2
Males 16.6 16.1 14.5 36.1 18.5 6.6 8.8 23.8 6.8 21.5 18.1 17.6 23.1 6 .9 21.2 32.3 6 13.6 14.9 4.9 4.7 33.4 6.2 22.2 14.6 39.7 21.1 11 13.2
Females 18.2 18.1 19.5 30.7 17 5.7 6.2 24.1 7.1 38.1 32.5 21.9 31.9 13 21.6 28.3 7.2 10.8 12.3 6.5 6 37.1 11.6 17.2 18.3 33.8 21.6 9.9 11
2002 Total 18 17.5 17.7 37 16.9 7.4 9.1 17.6 8.5 26.8 24.2 19.3 23. 1 8.1 22 22.4 7 12.7 17.1 5 6.7 42.5 11.6 23.2 16.5 37.7 21 16.6 12
Males 17.9 17.3 17.2 40.1 16.6 7.3 11.4 14.3 9.2 19.9 19.2 17.8 19.4 7 .9 20.4 22.6 5.8 13.2 17.6 5.2 6.4 41.9 9.8 24.3 15 39.5 21.2 17.7 13.7
Females 18.1 17.8 18.3 33.2 17.2 7.5 6.7 22.5 7.6 35.3 31.1 21.1 27.8 8.3 24.2 22.2 8.6 11.9 16.7 4.8 7.1 43.3 13.9 21.8 18.6 35.5 20.9 15.5 10.2
2004 Total 18.5 18.3 21.2 25.8 21 8.2 11.9 21.7 8.9 26.9 23.9 20.6 23.5 10. 5 18.1 22.7 16.4 15.5 16.8 8 9.7 39.6 1 5.3 21.9 16.1 33.1 20.7 21.5 12.1
Males 18.4 18 20.2 27 22.2 8.9 13.7 21.2 9.3 19.1 19.4 19.9 20.6 9.4 16 22.5 12 16.2 16.3 7.9 9.3 37.7 13.5 24.2 13.9 34.7 22 22.5 13.3Females 18.7 18.6 22.4 24.3 19.5 7.4 10 22.4 8.5 36.3 30.1 21.5 27.2 11. 6 21.3 22.9 21.5 14.4 17.4 8.1 10.2 41.9 17.6 18.9 19.2 31 19.4 20.6 10.7
2005 Total 18.3 18.2 21.5 22.3 19.2 8.6 14.2 15.9 8.6 26 19.7 21.1 23.9 13 1 3.6 15.7 14.3 19.4 16.2 8.2 10.3 36.9 16.1 20.2 15.9 30.1 20.1 22.9 12.8
Males 18.3 18.1 21 23.4 19.3 8.6 15.8 16.6 9.1 18.7 16.7 20 21.5 11. 9 11.8 15.9 12.3 19.6 16.6 8 10.7 35.7 13.6 21.6 14.5 31 20.6 23 14.4
Females 18.4 18.4 22.1 21 19.1 8.6 12.4 14.9 8 34.8 23.4 22.4 27.4 14.2 1 6.2 15.3 16.9 19 15.8 8.4 9.9 38.3 19.1 18.4 17.8 28.8 19.5 22.8 11.1
2006 Total 17.1 16.9 20.5 19.5 17.5 7.7 12.8 12 8.6 25.2 17.9 22.1 21.7 10.5 12.2 9.8 15.8 19.1 16.5 6.6 9.1 29.8 16.3 21.4 13.9 26.6 18.7 21.6 14
Males 16.9 16.7 18.8 18.9 16.6 7.9 14.2 10 9.1 17.7 15 20.9 19.1 9.9 10.5 10 16.3 18.6 17.8 6.1 8.9 28.3 14.5 22.3 11.6 26.4 19 21.1 15.7
Females 17.4 17.3 22.6 20.3 18.7 7.5 11.3 14.7 8.1 34.7 21.6 23.7 25.3 11.2 14.7 9.6 15.2 19.8 14.9 7.1 9.3 31.6 18.4 20.2 16.8 27 18.4 22.1 12
2007 Total 15.3 15.2 18.8 15.1 10.7 7.9 11.1 10 9 22.9 18.2 19.6 20.3 10.1 10.7 8.2 15.6 18 13.8 5.9 8.7 21.7 16.6 20.1 10.1 20.3 16.5 19.3 14.3
Males 15.1 14.9 17.1 14.5 10.6 8.2 12.2 12.1 9.9 15.7 15.2 18.9 18.2 10.7 11.2 7 13.7 17.6 15.7 5.6 8.3 20 13.5 21.1 9.4 20.4 16.4 18.9 15.8
Females 15.6 15.5 20.9 15.9 11 7.5 10 7.1 8 32.1 21.9 20.3 23.3 9.5 10 10 18.2 18.6 11.6 6.2 9.1 23.8 20.3 18.7 11.2 20.2 16.6 19.8 12.5
2008 Total 15.4 15.4 18 12.7 9.9 7.6 9.9 12 12.7 22.1 24.6 19.1 21.2 8.8 13.1 13.4 17.3 19.9 11.9 5.3 8 17.3 16.4 18.6 10.4 19 16.5 20.3 15
Males 15.6 15.5 17.3 13.7 9.8 6.9 10.7 12.6 15.3 17 23.7 19.2 18.9 8.4 13.2 12.6 13.4 19.1 13.6 5.4 7.9 15.2 13.3 18.8 9.9 18.5 17.1 19.8 17
Females 15.3 15.2 18.7 11.4 9.9 8.4 9 11.3 9.8 28.9 25.8 19 24.7 9.3 13 .1 14.6 21.9 20.9 9.8 5.2 8.2 19.9 20.2 18.3 11.3 19.8 15.8 20.8 12.7
Source:  Eurostat - LFS adjusted series, Annual average
p = provisional value /  b = break in data seriesContext 2c: Youth unemployment rate (% of labour force aged 15-24)
 
 
EN 176   EN Context 2d: Long-term unemployment rate by gender, selected years (% of the labour force 15+)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
2000 Total 4 3.9 3.7 9.4 4.2 0.9 3.8 5.9 1.6 6.2 4.6 3.5 6.3 1.2 7.9 8 0.5 3.1 4.5 0.8 1 7.4 1.7 3.8 4.1 10.3 2.8 1.4 1.4
Males 3.5 3.4 3.1 9.5 3.5 0.8 3.7 6.7 2.1 3.5 2.8 2.8 4.8 0.5 8.3 9.4 0.5 3.5 4.5 0.6 0.9 6 1.4 4 4.1 10.3 2.8 1.7 1.9
Females 4.6 4.6 4.6 9.2 5.2 1.1 4 5 1 10.1 7.4 4.3 8.4 2.2 7.5 6.5 0.5 2.5 4.5 1 1.2 9.1 2 3.5 4.2 10.2 2.7 1 0.9
2002 Total 4 3.9 3.7 12 3.7 0.9 4 5.4 1.3 5.3 3.7 3 5.1 0.8 5.5 7.2 0.7 2.5 3.2 0.7 1.1 10.9 1.8 4,6b 3.5 12.2 2.3 1 1.1
Males 3.6 3.4 3.2 12.5 3 0.7 4.1 6.3 1.8 3.1 2.3 2.6 4 0.5 6.4 7.6 0.6 2.8 3.5 0.6 1 9.8 1.4 4,8b 3.5 11.9 2.5 1.2 1.4
Females 4.5 4.4 4.3 11.4 4.6 1 4 4.5 0.8 8.6 5.9 3.4 6.9 1 4.6 6.8 0.8 2.2 2.5 0.9 1.2 12.3 2.2 4,4b 3.6 12.5 2 0.8 0.7
2004 Total 4.2 4.1 4.1 7.2 4.2 1.2 5.5 5 1.6 5.6 3.4 3.8 4,0b 1.2 4.6 5.8 1 2.7 3.4 1.6 1,4b 10.3 3 4.8 3.2 11.8 2.1 1.2 1
Males 3.8 3.7 3.7 7.3 3.4 1.1 5.7 5.6 2 3 2.2 3.3 2,9b 0.9 4.8 5.5 0.8 2.8 3.6 1.5 1,3b 9.6 2.6 5.5 3.1 11.3 2.3 1.4 1.2
Females 4.6 4.5 4.7 7.1 5.3 1.3 5.2 4.4 1 9.4 5 4.2 5,5b 1.6 4.3 6.2 1.3 2.6 3 1.6 1,4b 11.1 3.5 3.8 3.4 12.4 2 1 0.6
2005 Total : : 4.4 6 4.2 1.1 5,7b 4.2 1.5 5.1 2,2b 3.8 3.9 1.2 4.1 4.3 1.2 3.2 3.3 1.9 1.3 10.3 3.7 4 3.1 11.7 2.2 : 1
Males : : 3.9 6.1 3.4 1.1 6,0b 4.2 1.9 2.6 1,4b 3.4 2.9 0.8 4.4 4.2 1.2 3.2 3.4 1.9 1.3 9.3 3.2 4.6 2.9 11.2 2.4 : 1.3
Females : : 5 6 5.3 1.2 5,3b 4.2 0.8 8.9 3,4b 4.3 5.2 1.8 3.7 4.5 1.2 3.2 3.4 1.9 1.4 11.4 4.3 3.4 3.3 12.3 2 : 0.7
2006 Total 3.7 3.7 4.2 5 3.9 0.8 5.5 2.9 1.4 4.8 1.8 3.9 3.4 0.9 2.5 2.5 1.4 3.4 2.8 1.7 1.3 7.8 3.9 4.2 2.9 10.2 1.9 1.1 1.2
Males 3.5 3.4 3.7 4.8 3.1 0.7 5.7 3.2 1.8 2.6 1.2 3.6 2.6 0.7 3 2.5 1.3 3.3 3 1.6 1.3 7.1 3.4 4.7 2.5 9.4 2.1 1.2 1.5
Females 4 4 4.9 5.3 4.9 0.9 5.3 2.6 0.9 8.1 2.8 4.2 4.5 1.1 1.9 2.5 1.6 3.4 2.4 1.8 1.3 8.6 4.5 3.6 3.5 11.2 1.8 1 0.8
2007 Total 3.1 3 3.8 4.1 2.8 0.6 4.7 2.3 1.4 4.1 1.7 3.4 2.9 0.7 1.6 1.4 1.2 3.4 2.7 1.3 1.2 4.9 3.8 3.2 2.2 8.3 1.6 0.8 1.3
Males 2.8 2.8 3.3 3.7 2.1 0.5 4.8 2.8 1.7 2.2 1.1 3.2 2.2 0.8 1.9 1.4 1.3 3.3 2.8 1.2 1 4.6 3.2 3.6 1.8 7.5 1.7 0.9 1.6
Females 3.3 3.3 4.3 4.5 3.6 0.7 4.7 1.7 0.9 7 2.5 3.6 3.9 0.7 1.2 1.3 1.1 3.6 2.4 1.4 1.4 5.4 4.5 2.7 2.7 9.3 1.4 0.8 0.9
2008 Total 2.6 2.6 3.3 2.9 2.2 0.5 3.8 1.7 1.6 3.6 2 2.9 3.1 0.5 1.9 1.2 1.6 3.6 2.5 1 0.9 2.4 3.7 2.4 1.9 6.6 1.2 0.8 1.4
Males 2.4 2.4 3 2.7 1.7 0.4 3.9 2 2.2 2.1 1.4 2.8 2.4 0.5 1.9 1 1.2 3.6 2.6 0.9 0.9 2 3.2 2.9 1.6 5.8 1.3 0.8 1.7Females 2.8 2.8 3.7 3.1 2.8 0.5 3.7 1.4 0.9 6 2.9 3 4.1 0.5 1.9 1.4 2.1 3.7 2.5 1 0.9 2.8 4.2 1.8 2.1 7.6 1.1 0.7 0.9
Source : Eurostat - Labour Force Survey, Annual averages
 : = not available or unreliable data / b = break / p = provisional / e: estimate
Context 4: Old age dependency ratio (current and projected) - ratio between the total number of people aged 65 and over and the  number of persons of working age (from 15 to 64)
EU27 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
2010 25.9 26.1 25.3 21.8 25.0 31.2 25.0 16.7 28.2 24.4 25.8 31.0 18.0 25. 2 23.2 21.1 24.2 21.2 22.8 26.0 19.0 2 6.6 21.3 23.9 17.0 25.7 27.8 24.7
2020 31.1 30.6 31.1 31.1 31.9 35.3 29.2 20.2 32.8 27.4 32.8 35.5 22.3 28. 1 26.0 24.2 30.3 31.3 30.7 29.2 27.2 3 0.7 25.7 31.2 23.9 36.8 33.7 28.6
2030 38.0 37.6 36.3 35.7 37.9 46.2 34.4 24.6 38.5 34.3 39.0 42.5 27.4 34. 6 34.7 30.8 34.1 39.1 40.0 38.1 36.0 3 6.6 30.3 40.8 32.3 43.9 37.4 33.2
2040 45.4 42.3 43.6 42.7 42.7 54.7 39.0 30.6 48.3 46.4 44.0 54.1 30.8 40. 7 42.8 36.3 40.1 41.7 46.8 46.0 41.3 4 4.6 40.8 49.4 40.0 45.1 40.8 36.9
2050 50.4 43.9 55.4 54.8 41.3 56.4 47.2 40.4 57.0 58.7 44.7 59.2 37.7 51. 2 51.1 37.8 50.8 49.8 45.6 48.3 55.7 5 3.0 54.0 59.4 55.5 46.6 41.9 38.0
2060 53.5 45.8 63.5 61.4 42.7 59.1 55.6 43.6 57.1 59.1 45.2 59.3 44.5 64. 5 65.7 39.1 57.6 59.1 47.2 50.7 69.0 5 4.8 65.3 62.2 68.5 49.3 46.7 42.1
Source : Eurostat - EUROPOP2008 Trend scenario - baseline variant  
 
EN 177   EN Context 5a: Distribution of households by age and household type (private/institutional)
EU25 BE BG CZ DK DE EE EL ES FR IE IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
Total Total ('000) 441467 10296 7904 10230 5349 82277 1370 10628 40847 58514 3852 56996 690 2377 3484 440 10198 0 15986 8033 38230 10356 21681 1964 5379 5181 0 58789
Private households (%) 98.7       98.6    99.3    99.3       98.7         99.0          98.8         96.6         99.4            97.8         98.4            99.3         99.4       99.0         99.3         98.3       97.5            -         98.6    98.9    98.9    99.0    98.5    99.3    98.4    98.1    -       98.2    
Institutional household ( % 1.3         1.4      0.7      0.7        1.3           1.0            0.9           3.4           0.6              2.2           1.6              0.7           0.6         1.0           0.7           1.7         2.4              -         1.4      1.1      1.1      1.0      1.5      0.7      0.8      0.7      -       1.8      
Total ('000) 90525 2162 1531 2057 1161 15251 312 2011 7341 13426 1009 9833 180 541 846 98 2087 0 3532 1639 8851 2053 4847 376 1277 1135 0 13346
Private households (%) 99.4       99.9    97.9    99.8       99.4         99.7          99.2         97.8         99.9            99.2         99.6            99.9         99.9       99.4         99.3         99.0       96.9            -         99.7    99.7    99.2    99.5    98.3    : 98.3    99.1    -       99.3    
Institutional household ( % 0.6         0.1      2.1      0.2        0.6           : 0.6           2.2           0.1              0.8           0.4              0.1           0.1         0.6           0.7           1.0         3.1              -         0.3      0.3      0.8      0.5      1.7      : 0.4      0.4      -       0.7      
18-64 Total ('000) 279593 6390 5586 6759 3396 52516 852 6824 26547 35788 2420 36517 428 1485 2148 281 6565 0 10279 5152 24522 6610 15420 1299 3444 3269 0 36103
Private households (%) 99.0       99.5    99.4    99.5       98.9         99.6          98.9         96.0         99.7            98.2         98.9            99.5         99.7       99.0         99.4         99.0       97.7            -         99.4    99.4    98.8    99.6    98.0    : 98.7    98.4    -       98.5    
Institutional household ( % 1.0         0.5      0.6      0.5        1.1           : 0.9           4.0           0.3              1.8           1.1              0.5           0.3         1.0           0.6           1.0         2.2              -         0.6      0.6      1.2      0.4      2.0      : 0.6      0.3      -       1.5      
65+ Total ('000) 71306 1744 1322 1411 792 14510 205 1792 6974 9299 423 10646 80 352 489 61 1546 0 2174 1242 4853 1693 3050 289 611 777 0 9341
Private households (%) 96.4       93.9    99.6    97.7       96.7         96.3          98.1         97.5         97.7            94.3         92.8            97.9         96.4       98.7         98.9         93.7       97.5            -         93.5    95.8    98.8    96.4    99.6    : 97.0    95.1    -       95.4    
Institutional household ( % 3.6         6.1      0.4      2.3        3.3           : 1.7           2.5           2.3              5.7           7.2              2.1           3.6         1.3           1.1           6.3         2.5              -         6.5      4.2      1.2      3.6      0.4      : 2.7      3.1      -       4.6      
75+ Total ('000) 30917 774 481 570 379 6191 75 642 3036 4133 184 4762 34 126 178 25 619 0 972 582 1841 701 1063 110 238 340 0 4405
Private households (%) 93.3       88.4    99.3    95.7       94.2         92.5          96.9         96.7         96.1            89.5         87.6            96.5         92.7       98.1         98.3         87.0       95.8            -         87.2    92.4    98.1    93.1    99.4    88.4    95.4    90.8    -       91.5    
Institutional household ( % 6.7         11.5    0.7      4.3        5.8           7.5            2.9           3.3           3.9              10.5         12.4            3.5           7.3         1.9           1.7           13.0       4.2              -         12.8    7.6      1.9      6.9      0.6      5.3      4.2      6.0      -       8.5      
   Hospitals (%) 19.9       5.3      14.0    4.9        : : 3.6           20.4         12.5            13.8         27.8            1.5           5.8         2.0           5.2           9.8         11.8            -         20.8    19.4    18.5    3.3      30.7    : 13.3    27.9    -       44.6    
   Old people's homes (%) 68.0       85.1    83.8    86.3       : : 95.4         34.3         56.6            79.5         56.4            73.2         91.0       97.7         89.1         69.2       83.4            -         75.9    76.3    65.8    85.8    59.4    : 75.1    58.5    -       46.0    
Source: Eurostat Census data collection 2000-01
Context 5b: Population living in private households by household type, 2008 (percentage of total population)
EU27 EU25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
13 13 15 6 10 23 19 15 8 8 7 15 12 6 10 10 12 9 7 16 15 9 6 7 7 9 19 18 13
of which:-  S i n g l e  m e n 6 67 2 4 1 1 9 5 4 3 3 7 5 2 3 3 5 3 37732332886-  S i n g l e  w o m e n 8 88 4 6 1 2 1 0 1 0 4 5 4 9 7 3 7 7 7 6 49965556 1 1 1 0 7
- Under 65 8 8 9 2 5 16 13 9 4 4 3 10 6 3 5 5 8 5 3 11 10 4 2 3 3 4 12 11 7
-  6 5  a n d  o v e r 5 66 4 5 7 6 7 4 4 3 6 6 3 5 5 4 5 45654445776
4 46 2 4 7 5 6 8 1 2 5 3 3 5 5 4 4 34423232577
13 14 15 9 14 18 16 13 11 9 11 16 9 8 9 9 12 12 8 17 13 9 9 8 7 7 20 18 17
11 11 10 9 10 10 14 10 8 12 9 11 12 10 8 9 9 9 9 10 10 7 12 8 9 7 10 11 11
1 2 1 2 8 2 0 1 5 2 7 9 1 2 2 4 2 2 7 1 7 1 4 1 5 1 3 1 0 1 4 2 2 6 1 31 51 91 41 81 8 4 3 912 12 11 11 12 10 12 15 10 10 13 12 13 10 14 15 13 13 11 10 11 12 16 13 10 10 11 11 1117 17 13 10 20 19 15 15 17 25 21 18 18 30 11 18 26 16 16 20 15 15 16 14 22 17 16 18 17
7 7 15 2 5 10 7 6 14 3 3 11 5 7 5 5 7 7 7 13 8 7 4 6 7 7 11 10 9
11 10 7 32 11 2 5 11 14 10 13 6 11 13 24 17 8 16 18 5 12 25 16 27 17 24 4 4 8
EU aggregates based on available country data
Source: SILC 2008
Context 6a: General government debt - General government consolidated gross debt as a percentage of GDP
E U - 2 7 B E B G C Z D KD EE E I E E L E S F R I TC Y L VL T L UH U M T N L A T P L P T R O S I S K F I S E U K
2000 61.8 107.6 74.3 18.5 51.7 59.7 5.1 37.7 101.8 59.2 57.3 109.2 58.8 12 .3 23.7 6.4 55.0 55.9 53.8 66.4 36.8 5 0 . 42 4 . 62 6 . 85 0 . 34 3 . 85 3 . 64 1 . 0
2001 60.9 106.3 67.3 25.1 47.4 58.8 4.8 35.5 102.9 55.5 56.9 108.8 60.7 14 .0 23.1 6.5 52.0 62.1 50.7 67.0 37.6 5 2 . 92 5 . 72 7 . 44 8 . 94 2 . 35 4 . 43 7 . 7
2002 60.3 103.2 53.6 28.5 46.8 60.3 5.6 32.2 101.5 52.5 58.8 105.7 64.6 13 .5 22.3 6.5 55.6 60.1 50.5 66.4 42.2 5 5 . 52 4 . 92 8 . 14 3 . 44 1 . 35 2 . 63 7 . 5
2003 61.7 98.3 45.9 30.1 45.8 63.8 5.5 31.0 97.3 48.7 62.9 104.4 68.9 14 .6 21.1 6.2 58.4 69.3 52.0 65.4 47.1 5 6 . 92 1 . 52 7 . 54 2 . 44 4 . 45 2 . 33 8 . 7
2004 62.1 93.9 37.9 30.4 44.5 65.6 5.0 29.4 98.6 46.2 64.9 103.8 70.2 14 .9 19.4 6.3 59.1 72.5 52.4 64.8 45.7 5 8 . 31 8 . 72 7 . 24 1 . 44 4 . 25 1 . 24 0 . 6
2005 62.7 92.1 29.2 29.7 37.1 68.0 4.6 27.6 100.0 43.0 66.4 105.8 69.1 12 .4 18.4 6.1 61.8 70.2 51.8 63.9 47.1 6 3 . 61 5 . 82 7 . 03 4 . 24 1 . 85 1 . 04 2 . 2
2006 61.3 88.1 22.7 29.4 31.3 67.6 4.5 25.0 97.1 39.6 63.7 106.5 64.6 10 .7 18.0 6.6 65.6 63.6 47.4 62.2 47.7 6 4 . 71 2 . 42 6 . 73 0 . 53 9 . 34 5 . 94 3 . 2
2007 58.7 84.2 18.2 29.0 26.8 65.0 3.8 25.1 95.6 36.1 63.8 103.5 58.3 9. 0 16.9 6.6 65.9 62.0 45.5 59.5 45.0 63.6 12.6 23.3 29.3 35.2 40.5 44.2
2008 61.5 89.8 14.1 30.0 33.5 65.9 4.6 44.1 99.2 39.7 67.4 105.8 48.4 19 .5 15.6 13.5 72.9 63.8 58.2 62.6 47.2 66.3 13.6 22.5 27.7 34.1 38.0 52.0
2009F 73.0 97.2 15.1 36.5 33.7 73.1 7.4 65.8 112.6 54.3 76.1 114.6 53.2 33 .2 29.9 15.0 79.1 68.5 59.8 69.1 51.7 77.4 21.8 35.1 34.6 41.3 42.1 68.6
2010F 79.3 101.2 16.2 40.6 35.3 76.7 10.9 82.9 124.9 66.3 82.5 116.7 58.6 48 .6 40.7 16.4 79.8 70.9 65.6 73.9 57.0 84.6 27.4 42.8 39.2 47.4 43.6 80.3
2011F 83.7 104.0 15.7 44.0 35.2 79.7 13.2 96.2 135.4 74.0 87.6 117.8 63.4 60 .4 49.3 17.7 79.1 72.5 69.7 77.0 61.3 91.1 31.3 48.2 42.7 52.7 44.1 88.2
Source: Eurostat - General Government data and ECFIN forecasts /  F = forecast- Single parents
- 2 adults below 65, no children
- 2 adults, at least one aged 65+, no children
- 3 or more adults, with children- 3 or more adults, no children
- 2 adults, 1 child
- 2 adults, 2 children- 2 adults, 3 or more childrenChildren (0-17)
- Single adults, no children
 
 
EN 178   EN Context 6b: Projected evolution of debt levels up to 2050 (in % of GDP)
Programme scenario
EU-25* *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
2005 63 93.3 : 30.5 35.8 67.7 4.8 27.6 107.5 43.2 66.8 106.4 70.3 11 .9 18.7 6.2 58.4 74.7 52.9 62.9 42.5 63.9 : 29.1 34.5 41.1 50.3 42.8
2010 61 72 : 30 18 64 0 17 90 30 60 97 57 9 16 10 61 65 46 54 45 65 : 27 31 25 34 42
2030 79 31 : 43 23 37 -25 37 18 33 41 32 42 26 22 74 51 16 70 23 -33 64 : 65 16 26 -3 44
2050 180 83 : 188 98 65 -82 157 -56 198 66 1 172 92 76 240 155 -58 176 18 -163 208 : 270 66 96 -1 114
2005 budget scenario
2010 55 74 : 43.2 14.4 73.6 0.9 13.6 96.9 25.7 69.2 108.9 64.3 13 22.4 11.5 76.1 80.2 44.2 58.9 53.2 76.3 : 25.1 38.7 23.7 30.3 47
2030 33 52 : 95.7 -61.2 116.2 -39.3 7.9 165.2 -13.5 132.8 127.6 116. 3 14.9 46.7 56.1 143.6 92.9 67.8 54.9 20 195.4 : 68.5 66.8 7.9 8 90.1
2050 76 129 : 320.3 -135.5 232.4 -117 100.4 451.3 42.6 269.9 208.9 269.9 49. 6 135.7 179.1 247.6 79.6 177.7 67.5 -42.5 517.4 : 287.2 176.9 61.6 58.8 186.7
* Adjusted gross debt.
** aggregates exclude Greece
Source: Commission services, 2005/06 updated stability and convergence programmes.
Context 7a: Social protection benefits by group of functions (as a percentage of total benefits) - 2007
EU-27 EU-25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
Sickness, health care 29,1p 29,2p 26.5 27.1 33.9 23 29,8p 33.4 41.1 28.1 31,2p 29,9p 26,1p 25,2p 29 ,7p 30,7p 26 25.5 29.2 32,5p 26 22.1 28.3 23.8 32,1p 30,8p 26.3 26,1p 30,6p
Disability 8,1p 8p 6.6 8.3 8.1 15 7,7p 9.3 5.5 4.9 7,6p 6,1p 6p 3,7p 7p 10, 4p 12.3 9.6 6.3 9,1p 8 9.6 10 10 7,8p 8,5p 12.6 15,3p 9,8p
Family and children 8p 7,9p 7.1 8.6 9.2 13.1 10,6p 11.6 14.7 6.2 6p 8,5p 4,7p 10,8p 11p 8,7p 16.6 12.8 5.9 6p 10.2 4.5 5.3 13.2 8,7p 10p 11.6 10,2p 6p
Unemployment 5,1p 5,1p 11.7 2 3.5 5.6 5,8p 1.2 7.7 4.5 11,7p 6,1p 1,8p 4,8p 3,3p 1,9p 4.9 3.4 2.8 4,3p 5.3 2.2 5.1 2.2 2,3p 3,6p 7.8 3,8p 2,1p
Old age and survivors benefits 46,2p 46,2p 45.3 51.4 43.9 38.1 43,1p 43.8 27.4 52 41,3p 45,3p 61,1p 46,7p 46 ,8p 47p 37.3 43.9 52.4 40,2p 48.9 60.2 50 47.3 46,7p 43,8p 38.5 41p 44,9p
Housing and social exclusion 3,6p 3,6p 2.8 2.5 1.4 5.1 2,9p 0.8 3.6 4.3 2,2p 4,2p 0,3p 8,7p 2,3 p 1,3p 2.9 4.8 3.3 7,8p 1.5 1.4 1.2 3.5 2,4p 3,3p 3.2 3,8p 6,5p
 e = Eurostat estimate / p =  provisional
Context 7b: Social protection benefits by group of functions (as a percentage of GDP) - 2007
EU-27 EU-25 BE BG CZ DK DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SL SK FI SE UK
Total expenditure* 26.2p 26.4p 29.5 15.1 18.6 28.9 27.7p 12.5 18.9 24.4 21.0p 30.5p 26.7p 18.5p 11 .0p 14.3p 19.3 22.3 18.1 28.4p 28.0 18.1 24.8 12.8 21.4p 16.0p 25.4 29.7p 25 .3p
Social protection benefits 25.2p 25.4p 28.0 14.6 18.0 28.1 26.7p 12.3 17.6 23.8 20.5p 29.0p 25.5p 18.1p 10 .7p 13.9p 19.0 21.9 17.9 26.8p 27.1 17.8 23.4 12.6 20.8p 15.4p 24.6 29.0p 24 .8p
Sickness/Health care 7.4p 7.4p 7.4 3.9 6.1 6.5 8.0p 4.1 7.2 6.7 6.4p 8.7p 6.7p 4.6p 3.2 p 4.3p 4.9 5.6 5.2 8.7p 7.1 3.9 6.6 3.0 6.7p 4.7p 6.5 7.6p 7.6p
Disability 2.0p 2.0p 1.8 1.2 1.5 4.2 2.0p 1.1 1.0 1.2 1.6p 1.8p 1.5p 0.7p 0.7 p 1.4p 2.3 2.1 1.1 2.5p 2.2 1.7 2.3 1.3 1.6p 1.3p 3.1 4.4p 2.4p
Family/Children 2.0p 2.0p 2.0 1.3 1.7 3.7 2.8p 1.4 2.6 1.5 1.2p 2.5p 1.2p 2.0p 1.2 p 1.2p 3.2 2.8 1.1 1.6p 2.8 0.8 1.2 1.7 1.8p 1.5p 2.9 3.0p 1.5p
Unemployment 1.3p 1.3p 3.3 0.3 0.6 1.6 1.5p 0.1 1.4 1.1 2.4p 1.8p 0.5p 0.9p 0.3 p 0.3p 0.9 0.8 0.5 1.2p 1.4 0.4 1.2 0.3 0.5p 0.6p 1.9 1.1p 0.5p
Old age and survivors 11.7p 11.7p 12.7 7.5 7.9 10.7 11.5p 5.4 4.8 12.4 8.5p 13.1p 15.6p 8.5p 5 .0p 6.5p 7.1 9.6 9.4 10.8p 13.3 10.7 11.7 6.0 9.7p 6.8p 9.5 11.9p 11.1p
Housing and Social exclusion n.e.c. 0.9p 0.9p 0.8 0.4 0.3 1.4 0.8p 0.1 0.6 1.0 0.5p 1.2p 0.1p 1.6p 0.2 p 0.2p 0.6 1.1 0.6 2.1p 0.4 0.3 0.3 0.4 0.5p 0.5p 0.8 1.1p 1.6p
Administration costs 0.8p 0.8p 1.0 0.4 0.6 0.8 1.0p 0.1 1.3 0.6 0.5p 1.2p 0.7p 0.3p 0.2 p 0.4p 0.3 0.4 0.2 1.3p 0.5 0.3 0.5 0.2 0.4p 0.6p 0.8 0.6p 0.5p
Other expenditure 0.2p 0.2p 0.5 0.1 0.0 : 0.1p : 0.0 0.0 0.1p 0.2p 0.5p 0.1p 0.1p 0.0p 0.0 : : 0.3p 0.4 0.0 0.9 0.0 0.1p 0.0p : 0.0p 0.0p
* including administrative costs; e = Eurostat estimate / p =  provisional
Context 8a: Adults aged 18-59 living in jobless households by household types , 2008, in % of total number of adults living in jobless households
EU27 EU25 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
Alone without children 26.5 27.5 33.3 17.3 25.7 : 43.0 34.0 19.4 21.5 14.7 31.0 18.2 9.9 24.6 37.3 33.6 14.5 15.7 45.0 37.8 15.8 14.2 10.9 27.3 13.3 51.8 : 27.5
Alone with child(ren) 10.2 10.7 13.7 4.4 14.5 : 10.3 12.4 18.2 3.2 4.8 11.7 4.0 8.0 9.1 11.2 5.5 6.5 7.8 14.1 5.9 7.6 6.8 2.9 4.0 4.6 3.7 : 23.3
Couple without children 19.9 19.9 23.1 19.9 23.3 : 19.1 9.5 11.4 26.9 15.5 26.8 17.3 26.5 12.0 10.9 32.8 21.4 21.0 22.1 23.8 25.2 23.4 20.3 32.4 18.3 22.8 : 14.0
Couple with child(ren) 15.7 15.4 10.7 13.4 11.7 : 14.6 12.1 21.2 11.0 21.3 14.1 17.5 18.3 11.0 11.8 11.7 18.7 18.2 11.5 12.0 13.0 14.1 22.8 6.7 14.5 11.5 : 16.3
Other households without children - total 19.7 19.4 12.5 28.4 19.1 : 9.3 27.4 20.8 32.6 31.9 12.2 33.5 33.0 32.5 21.6 11.6 25.2 28.1 5.9 16.8 26.3 32.0 22.5 25.0 30.2 9.3 : 13.5
    - without elderly (65+) 9.5 9.2 7.6 13.7 7.7 : 4.8 7.8 13.0 13.1 11.4 6.7 16.3 25.4 8.3 8.4 7.1 12.1 12.1 3.4 7.6 11.6 10.4 12.7 12.3 14.5 3.2 : 8.1
    - with at least 1 elderly (65+) 10.3 10.2 4.8 14.7 11.4 : 4.5 19.6 7.8 19.5 20.5 5.4 17.2 7.6 24.2 13.2 4.5 13.1 16.1 2.4 9.3 14.8 21.6 9.8 12.7 15.7 6.0 : 5.5
Other households with child(ren) - total 7.9 7.0 6.8 16.5 5.7 : 3.6 4.7 8.9 4.7 11.7 4.3 9.5 4.3 10.8 7.2 4.8 13.6 9.2 1.5 3.5 12.1 9 . 42 0 . 64 . 71 8 . 90 . 9 : 5.4
    - without elderly (65+) 6.0 5.4 5.8 12.4 4.1 : 3.2 2.0 7.8 3.0 7.9 3.4 7.7 2.7 5.1 4.2 3.9 10.7 6.2 1.2 2.8 8.2 5 . 81 3 . 63 . 51 5 . 50 . 9 : 4.9
    - with at least 1 elderly (65+) 1.9 1.6 1.1 4.2 1.6 : 0.5 2.8 1.1 1.7 3.8 0.9 1.8 1.6 5.7 2.9 0.9 3.0 2.9 0.3 0.7 3.8 3.6 7.0 1.2 3.4 0.0 : 0.5
Source: Eurostat - European Labour Force Survey 2008, Annual results.
 : = not available or unreliable data / b = break / p = provisional / e = estimate  
 
EN 179   EN Context 8b: Children a ged 0-17 livin g in jobless households b y household t ypes, 2008, in % of total number of children living in jobless households
EU27 EU25 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
Alone with child(ren) - no elderly 45.7 47.9 57.7 23.4 57.3 : 46.9 56.1 49.9 27.7 23.5 51.5 22.4 43.1 36.9 50.7 35.1 25.7 39.0 63.0 37.6 37.7 34.5 8.4 32.7 20.1 27.5 : 66.3
Alone with child(ren) - at least 1 elderly 0.4 0.3 0.4 1.1 0.3 : 0.4 0.4 0.1 0.7 0.8 0.2 0.2 0.0 7.8 1.5 1.2 0.3 0.0 0.4 0.8 0.5 1.2 1.2 0.0 0.0 0.0 : 0.1
Couple with child(ren) - total 40.0 39.1 29.6 39.7 30.8 : 45.2 28.6 37.3 53.4 48.7 41.2 59.1 46.1 26.6 29.2 3 7.5 51.0 42.3 34.4 50.9 31.9 44.8 57.3 44.7 39.3 71.0 : 26.8
    - without elderly (65+) 38.9 38.2 28.5 34.7 29.6 : 44.5 27.9 36.9 49.3 47.1 40.2 58.1 43.8 21.0 27.8 35.4 50.5 40.7 33.3 49.9 31.0 40.6 55.5 44.3 39.1 70.0 : 26.1
    - with at least 1 elderly (65+) 1.1 1.0 1.1 5.0 1.3 : 0.7 0.6 0.4 4.0 1.7 1.0 1.0 2.4 5.5 1.4 2.1 0.5 1.6 1.1 1.0 0.9 4.1 1.8 0.4 0.3 1.0 : 0.7
Other households with child(ren) - no elderly 14.0 12.6 12.3 35.9 11.6 : 7.5 14.9 12.7 18.3 27.0 7.1 18.3 10.8 28.7 18.6 26. 1 23.0 18.7 2.2 10.7 30.0 19.5 33.1 22.6 40.5 1.5 : 6.8
    - without elderly (65+) 9.4 8.7 9.8 25.4 8.1 : 5.4 4.3 10.7 8.8 14.7 5.7 13.0 7.4 13.8 10.2 21.4 16.8 11.8 1.5 7.2 16.1 8.9 17.9 14.5 31.4 1.5 : 5.9
    - with at least 1 elderly (65+) 4.6 4.0 2.5 10.4 3.6 : 2.1 10.6 2.0 9.5 12.3 1.4 5.3 3.5 15.0 8.4 4.7 6.1 6.9 0.7 3.5 13.9 10.6 15.2 8.0 9.1 0.0 : 0.9
Source: Eurostat - European Labour Force Survey 2008, Annual results.
 : = not available or unreliable data / b = break / p = provisional / e = estimate
Context 10: Net income of social assistance recipients as % of the at-risk of poverty rate threshold for 3 jobless households t ypes, 2006
LT SK PT MT EE HU ES LV CZ BE PL LU CY FR SI AT DE FI SE DK UK IE NL
single 0.3         0.5      0.5      0.5        0.5           0.5            0.6           0.6           0.6              0.7           0.7              0.8           0.8         0.8           0.8           0.8         0.9              1.0        1.1      1.1      1.2      1.2      1.3      
lone parent, 2 children 0.7         0.6      0.7      0.4        0.6           0.9            0.6           1.3           0.8              0.9           0.9              0.8           0.8         0.8           1.0           0.9         1.2              0.9        0.9      1.0      1.2      1.0      1.1      
couple with two children 0.7         0.5      0.8      0.3        0.5           0.9            0.4           1.1           0.8              0.6           0.7              0.7           0.7         0.7           0.9           0.8         1.1              0.9        0.8      0.9      1.0      1.0      0.9      
Source : Joint EC-OECD project using OECD tax-benefit models, and Eurostat.
Context 11: At-risk-of-poverty rate before social transfers by gender and selected age groups
Before all social transfers except old-age and survivors' benefits
EU27 EU25 BE BG CZ DK DK(1)DE EE IE EL ES FR IT CY LV LT LU HU MT NL AT PL PT RO SI SK FI SE UK
Total population Total 25(p) 25(p) 27 27 20 28 27 24 25 34 23 24 23(b) 23 22 30 27 24 30 23 20 24 25 25 31 23 18 28 29 29(p)
Men 24(p) 24(p) 26 26 19 26 25 23 22 32 22 23 23(b) 22 20 28 25 23 31 22 19 23 25 24 30 21 18 26 27 27(p)
Women 26(p) 26(p) 28 29 21 29 29 25 27 36 24 25 23(b) 25 24 32 29 24 30 24 21 26 25 25 32 25 19 29 30 31(p)
Children aged 0-17 years 33(p) 32(p) 32 31 30 22 22 31 26 40 26 29 34(b) 32 20 32 32 34 47 32 23 36 33 30 43 23 27 30 34 39(p)
People aged 18-64 ye aTotal 23(p) 23(p) 26 22 19 28 28 25 20 31 22 21 22(b) 21 16 24 24 23 30 20 20 23 25 23 27 21 17 26 27 24(p)
Men 22(p) 22(p) 25 22 17 26 26 24 19 30 21 20 21(b) 20 15 23 24 23 30 18 19 22 26 22 27 21 17 26 26 22(p)
Women 24(p) 24(p) 27 23 20 29 29 26 20 33 22 22 23(b) 22 18 25 25 24 30 21 21 24 24 24 27 21 17 26 28 26(p)
People aged 65 years aTotal 23(p) 22(p) 25 41 14 36 31 16 41 38 27 31 13(b) 23 53 53 32 8 10 26 16 17 15 25 30 33 15 31 26 38(p)
Men 20(p) 19(p) 24 35 11 32 27 14 27 32 24 28 12(b) 20 46 47 19 8 7 26 15 13 11 22 23 26 8 23 16 33(p)
Women 26(p) 25(p) 26 46 17 39 34 18 49 42 29 32 14(b) 26 58 56 39 8 11 25 16 20 17 27 35 37 19 36 33 42(p)
 : = not available or unreliable data / b = break / p = provisional / e: estimate
EU Aggregates: Eurostat estimates are obtained as a population size weighted average of national data.Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008);  (1 ) with imputed rent data 2007 (see methodological note).