Commission staff working document - Joint Report on Social Protection and Social Inclusion accompanying document to the Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions - Proposal for the Joint Report on Social Protection and Social Inclusion 2010 - Supporting document COM(2010)25 final SEC(2010)99
Date: 2010-02-05
Institutions: European Commission
Subjects: European social policy, housing, impact study, marginalisation, pension scheme, poverty, public health, report, social integration, social security, unemployment

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COMMISSION OF THE EUROPEAN COMMUNITIES 

Brussels, 5.2.2010 
SEC(2010) 98 final 

COMMISSION STAFF WORKING DOCUMENT 

Joint Report on Social Protection and Social Inclusion 

accompanying document to the 

COMMUNICATION FROM THE COMMISSION TO THE COUNCIL, THE 
EUROPEAN PARLIAMENT, THE EUROPEAN ECONOMIC AND SOCIAL 
COMMITTEE AND THE COMMITTEE OF THE REGIONS 

Proposal for the Joint Report on Social Protection and Social Inclusion 2010  

Supporting document 

COM(2010)25 final 
 SEC(2010)99 

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TABLE OF CONTENTS 

1. 

2. 

2.1. 

2.2. 

2.3. 

2.4. 

2.5. 

2.6. 

Scope and Outline of the Report .................................................................................. 4 

The social situation in the EU-27................................................................................. 5 

The social impact of the crisis...................................................................................... 5 

Poverty and the crisis in public perception: main results from EU wide opinion polls9 

Situation of the Member States' before the crisis: the role of social protection in 
addressing inequalities and poverty ........................................................................... 10 

Employment growth doesn't automatically lead to a reduction of poverty................ 21 

The adequacy and sustainability of pension systems................................................. 24 

Health care and long-term care: ensuring sustainability and access to quality services 
for all .......................................................................................................................... 29 

2.7. 

Social protection over the economic cycle................................................................. 31 

3. 

3.1. 

3.2. 

3.3. 

3.4. 

Responding to the crisis and preparing for recovery ................................................. 35 

First evaluation of policy responses........................................................................... 35 

Overview of main policy measures taken in response to the crisis............................ 37 

The need for effective and efficient social inclusion policies during and after the 
crisis ........................................................................................................................... 40 

Supporting the integration of the most excluded in the labour market and in society 
as whole: the role of activation and access to services .............................................. 41 

3.5. 

Income support: the specific role of minimum income schemes............................... 42 

4. 

4.1. 

4.2. 

4.3. 

5. 

5.1. 

5.2. 

5.3. 

5.4. 

5.5. 

The use of the European Social Funds to support social objectives during the crisis 
and in the long term.................................................................................................... 53 

ESF support for social protection and inclusion: actions responding to the crisis..... 55 

ESF support for social protection and inclusion: long-term actions .......................... 59 

The European Globalisation Adjustment Fund (EGF)............................................... 61 

The importance and extent of homelessness and housing exclusion ......................... 62 

Housing vulnerability: the importance of housing in the context of the current 
economic crisis........................................................................................................... 62 

Housing exclusion –- an important challenge for the EU population at large and 
particularly for those at risk of poverty...................................................................... 63 

The overall policy response — comprehensive strategies and better governance..... 70 

Causes of homelessness and housing exclusion and instruments .............................. 71 

Monitoring and evaluation ......................................................................................... 75 

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6. 

Effectiveness and efficiency in the health sector: some considerations at a time of 
economic crisis........................................................................................................... 77 

6.1.  Why more effectiveness and efficiency 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 .............................................................................................................. 105 

7. 

7.1. 

7.2. 

7.3. 

7.4. 

8. 

9. 

9.1. 

9.2. 

9.3. 

9.4. 

Long-term implications of the crisis for the sustainability and adequacy of pensions
.................................................................................................................................. 107 

Outcomes of pension reforms prior to the crisis ...................................................... 108 

First effects of the crisis ........................................................................................... 115 

Long-term implications of the crisis ........................................................................ 124 

Policy implications................................................................................................... 126 

Governance .............................................................................................................. 129 

Annexes.................................................................................................................... 131 

Indicators.................................................................................................................. 131 

Data sources ............................................................................................................. 137 

Annex to part 6 on Health ........................................................................................ 141 

Statistical tables........................................................................................................ 157 

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1. 

SCOPE AND OUTLINE OF THE REPORT  

This supporting document was prepared by the Commission services to accompany the 2010 
Joint  Report  on  Social  Protection  and  Social  Inclusion  [Commission  proposal:  COM(2010) 
xx].  It  provides  an  assessment  of  the  social  situation  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 explored; the sustainability and 
adequacy  of  pensions;  homelessness  and  housing  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 document 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 reforms 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 also points to the long-term challenges that will 
accompany  recovery.  Member  States’  specific  reporting  on  their  strategies  to  fight 
homelessness  and  housing  exclusion  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  report  is  organised  as  follows. 
Section  2  contains  an  overview  of  the  social  situation  in  the  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 incomes both during and beyond the crisis. Section 4 
covers  the  role  of  the  European  Social  Fund  and  the  European  Globalisation  Adjustment 
Fund. Section 5 considers homelessness and housing exclusion in more depth. Finally, section 
6 looks at healthcare expenditure, section 7 the sustainability and adequacy of pensions; and 
section 8 matters of governance.  

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2. 

THE 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  automatic  stabilisers  playing  a  major  role  in 
absorbing  the  shock  and  in  mitigating  the  economic  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  recovery,  the  full  impact  of  the  crisis  on  labour  markets  and  public 
finances is still unfolding and there 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, employment 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 creation 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 projected 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 working 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 countries. Among the five largest EU economies, 
real GDP is expected to contract 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  contracted  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. 

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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 against 5.2%), in Estonia (15.2% as against 4%), 
Lithuania (14.6% as against 4.3%) and Latvia (22.3% as against 6.1%). 

Some categories of workers have been particularly hit by the crisis, 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  Member  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  drop  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  time  work  arrangements  may  have  contained  the 
growth in unemployment rates observed 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  apparent  in  the  growing  number  of  unemployment 
benefit recipients during 2008 and into the third quarter of 2009. The crisis has had no clear 
impact  on  the  percentage  of  older  workers  claiming  early  retirement  benefits,  apart  from 
upward trends reported in May 2009 in LT, PL and EL.  

Table 2.1a: Countries that have reported significant increases in unemployment benefits 
claimant since the outset 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 the social impact of the crisis 

The  impact  in  terms  of  social  assistance  claimants  became  clear  in  the  second  and  third 
quarters of 2009 (See Table 2.1b). The pressure on last-resort schemes depends both on how 

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early  the  crisis  hit  the  different  countries,  and  on  the  varying  coverage  and  duration  of 
unemployment schemes. Claimant numbers continued 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  five  countries.  In  Denmark  and  Slovakia,  this 
surge  followed  a  period  of  strong  decline.  In  Hungary,  Poland1,  and  the  UK  the  percentage 
dropped slightly. 

Table 2.1b: Countries that have reported significant increases in the claimants of social 
assistance since the outset of the crisis 

Countries already reporting a surge in social assistance claimants in spring 2009 

IE

45000

35000

25000

15000

IE Emergency
Social
Assistance
i
R i

t

1

2

3

4

5

6

7

8

9

10

11

12

1

2

3

4

5

6

7

8

9

10

11

12

2 0 0 8

2 0 0 9

LT

LT Recipients of social
benefit (x1000)

85

60

35

10

1

2

3

4

5

6

7

8

9

10

11

12

1

2

3

4

5

6

7

8

9

10

11

12

2 0 0 8

2 0 0 9

AT: +10.6% between Q3-08 and Q3-09, 

PT

400000

350000

300000

250000

PT beneficiaries of Social
assistance

1

2

3

4

5

6

7

8

9

10

11 12

1

2

3

4

5

6

7

8

9

10

11 12

2 0 0 8

2 0 0 9

Countries reporting a surge in social assistance claimants in the autumn 2009 

80000

75000

70000

65000

60000

DK

CZ: +11% between February 08 and February 09 

CY: +15% between 2008 and September 2009 

DK Recipients of cash benefits

1

2

3

4

5

6

7

8

9

10

11 12

1

2

3

4

5

6

7

8

9

10

11 12

2 0 0 8

2 0 0 9

1 

The reason of social benefits dropping in Poland can be unchanged income criteria for social benefits 
since  2006  while  during  last  few  years  the  income  of  Polish  households  have  been  noticeably  risen 
(there is particularly observed earnings increase). 

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20000

17500

15000

12500

10000

LV

LV persons with
guaranteed minimum
income (GMI) benefit

SK

SK recipients of
assistance in material
need

190000

170000

150000

130000

1

2

3

4

5

6

7

8

9

10

11 12

1

2

3

4

5

6

7

8

9

10

11

12

1

2

3

4

5

6

7

8

9

10

11 12

1

2

3

4

5

6

7

8

9

10

11 12

2 0 0 8

2 0 0 9

2 0 0 8

2 0 0 9

Source: SPC/ISG questionnaire on the 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) and FI (-1.5% between Q2-08 and Q2-09). In 
the  United  Kingdom,  prices  have  started  recovering  after  the  initial  fall  observed  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% between 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  potential  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 specific support schemes to renters has increased 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 support 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  administrative  data  on  applications  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,  Luxembourg,  Austria  and  (to  a  minor  extent)  Portugal. 
These increases also partly reflect long-term trends in the consumption pattern of households. 

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According to the spring report, debts linked to utility bills have also increased 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 Latvia 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  some  of  the  southern  and  eastern  European 
countries,  the  crisis  has  also  made  a  deep  impression  in  previously  economically  sound 
countries,  such  as  Ireland.  Overall,  about  one  fifth  of  Europeans  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 months. A quarter of EU citizens 
expect the situation to get worse in the coming 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  optimistic  about  both  the  present  situation  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 extent of poverty within the European Union, 
the perceived personal and societal reasons behind poverty, who is thought to be most at risk, 
if  people  feel  somehow  threatened  by  the  possible  prospect  of  poverty,  how  poverty  may 
prevent  people  from  taking  full  advantage  of  society,  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, together with the level of administration felt to be 
mainly responsible for taking action. 

EU citizens are strongly aware of the problem of poverty and social exclusion in today’s 
society: three out of four Europeans (73 %) feel that poverty in  their country  is widespread. 
However,  the  extent  to  which  poverty  is  seen  as  widespread  differs  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’ reasons 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 precarious employment, people with disabilities, and 
those suffering from some form of long-term illness. 

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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 decent 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, compared 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 national governments are 
primarily responsible for combating poverty. Even if Europeans do not regard the European 
Union  as  primarily  responsible  for  combating  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 crisis: the role of social protection in 
addressing inequalities and poverty 

2.3.1.  At the outset of the crisis the situation of Member States varied greatly 

As highlighted above, not all Member States were in the same situation 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  their  GDP  on  social  protection,  and 
periods  of  economic  growth  had  allowed  many  governments  in  the  EU  to  devote  more 
resources to  social  policy intervention. The structure of social protection expenditure shows 
that old-age pensions and sickness and healthcare 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 over the life-cycle, insuring people against social 
risks and helping reduce poverty. 

EN 

10 

   EN 

 
Figure 2.1 Expenditure on social protection benefits - gross, by function, in % of GDP — 
2007 

Old age and survivors

Sickness/Health care

Disability

Unemployment

Family/Children

Housing and Social exclusion n.e.c.

35

30

25

20

15

10

5

0

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 se

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  Republic,  the  Netherlands,  Slovakia,  Denmark, 
Hungary, , Austria, , Slovenia and 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 corrected for differences in the cost 
of  living,  poverty  thresholds  are  five  times  higher  in  the  UK  at  the  top  of  the  ranking  after 
Luxembourg  (which  is  clearly  an  outlier)  than  in  the  two  countries  at  the  bottom  (Romania 
and Bulgaria).  

EN 

11 

   EN 

 
 
Figure 2.2: At-risk-of-poverty rate and illustrative value of the at-risk-of-poverty 
thresholds (single adult household); 2008 

At-risk-of-poverty rate (left axis)
Value of thresholds for a single household (right axis)

n
o
i
t
a
l
u
p
o
p

l
a
t
o
t

f
o
%

30

25

20

15

10

5

0

18000

15000

12000

9000

6000

3000

0

s
d
r
a
d
n
a
t
S

i

r
e
w
o
P
g
n
s
a
h
c
r
u
P
n
I

EU
27

EU
15

NMS
10

cz nl sk dk* dk hu at si se fr

lu

fi be de mt

ie cy pl pt ee it uk el es

lt bg ro lv

Source: EU-SILC (2008). dk*: values including imputed rent2 

Over the last decades a shift in poverty risks was observed from the elderly towards younger 
people.  Child  poverty  remained  stable  or  increased  in  many  EU  countries  with  some 
exceptions (CZ, EE, IE, LT, PL - see figure 2.4), while poverty risks generally decreased for 
the  elderly  as  a  consequence  of  the  maturing  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. However, age patterns of poverty differ  across 
countries. 

2 

3 

Two  values  are  presented  for  Denmark,  with  and  without  imputed  rent.  See  footnote  below  and 
methodological note in annex. 
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), 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 

12 

   EN 

 
 
 
 
 
 
 
 
                                                 
Figure 2.3: At-risk of poverty rate by age group, 2008 

Children (aged 0-17)

Working age
population (aged 18-
64)

Elderly (aged 65+)

Cyprus 
elderly 
poverty: 
49%

Latvia 
elderly 
poverty: 
51%

40

35

30

25

20

15

10

5

0

eu27 cz

nl

si

sk

dk

cy

at

se

be dk* hu m t

fi

fr

lu

ie

de

ee

uk

es

it

pl

pt

bg

lt

el

lv

ro

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  evolution  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 available starting from 2007. It has to be kept in 
mind that at-risk-of-poverty rates figures are subject to confidence intervals of 1 percentage 
point at the most aggregated level, and therefore changes over time are only meaningful for 
changes of more than 2 to 3 percentage points (depending on the 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  experienced  risks  of  poverty  by  3  percentage  points 
higher than the overall population, with child poverty increasing slightly from 19% to 20% in 
2008.  

This  overall  stability  at  EU  level  hides  great  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 elderly (65+) are at higher risk of poverty than both children and 
working  age  population  (20%  against  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  partly  the  age  orientation  of  social  protection  in  these  countries 
where pensions used to appear relatively generous compared to weak support to families with 
children. During the period, the relative situation of children and the elderly evolves rapidly, 
with the child at-risk-of-poverty rate dropping by 5 percentage points and the elderly risk of 
poverty rate increasing by 4 percentage points.  

EN 

13 

   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  increased  for  children  while  it  was  decreasing  the 
elderly. Ireland, and to lesser degree Portugal are the only countries to have reduced 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 from the National Strategy Reports 2008-2010 and 
the SPC report on minimum income provision for the elderly4 that could support this analysis, 
but would need further elaboration. It lists new measures taken in the area of child poverty, 
and  it  provides  information  on  the  recent  evolution  of  pension  systems  that  could  help 
explaining the strong trends observed 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  strong  economic  growth, 
accompanied  by  a  strong  increase  in  wages  in  the  years  before  the  crisis.  Further  analysis 
would be needed to fully understand the deterioration of the relative situation of the elderly in 
these  countries.  However,  there  are  indications  that  where  pensions  were  indexed  to  prices 
and not to wages, at-risk-of poverty rates for the elderly have increased dramatically. In some 
MS,  however,  some  of  the  impacts  of  reforms  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  have  resulted  from  a  strengthening  of  pension 
benefits  (e.g.  IE).  This  illustrates  that  the  type  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  specifically  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 

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

eu25 All
eu25 18-64

2008
eu25 0-17
eu25 65+

2005

2006

2007

eu15 All
eu15 18-64

2008
eu15 0-17
eu15 65+

4 

Minimum  income  provision  for  older  people  and  their  contribution  to  adequacy  in  retirement,  SPC 
study 2006 

EN 

14 

   EN 

 
 
 
                                                 
Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 

2005

2006

2007

2008

nms10 All
nms10 18-64

nms10 0-17
nms10 65+

2005

2006

2007

2008

cz All
cz 18-64

cz 0-17
cz 65+

2005

2006

2007

2008

de All
de 18-64

de 0-17
de 65+

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

40

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

be All
be 18-64

2008
be 0-17
be 65+

2005

2006

2007

2008

dk All
dk 18-64

dk 0-17
dk 65+

2005

2006

2007

2008

ee All
ee 18-64

ee 0-17
ee 65+

2005

2006

2007

2008

ie All
ie 18-64

ie 0-17
ie 65+

2005

2006

2007

2008

el All
el 18-64

el 0-17
el 65+

EN 

15 

   EN 

 
 
 
 
 
 
 
 
 
Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 

35

30

25

20

15

10

5

35

30

25

20

15

10

5

55

45

35

25

15

5

35

30

25

20

15

10

5

2005

2006

2007

2008

es All
es 18-64

es 0-17
es 65+

2005

2006

2007

2008

it All
it 18-64

it 0-17
it 65+

2005

2006

2007

2008

fr All
fr 18-64

fr 0-17
fr 65+

2005

2006

2007

2008

cy All
cy 18-64

cy 0-17
cy 65+

35

30

25

20

15

10

5

55

45

35

25

15

5

35

30

25

20

15

10

5

2005

2006

2007

2008

2005

2006

2007

2008

lv All
lv 18-64

lv 0-17
lv 65+

lt All
lt 18-64

lt 0-17
lt 65+

35

30

25

20

15

10

5

2005

2006

2007

2008

2005

2006

2007

2008

lu All
lu 18-64

lu 0-17
lu 65+

hu All
hu 18-64

hu 0-17
hu 65+

EN 

16 

   EN 

 
 
 
 
 
 
 
 
 
Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

2008

mt All
mt 18-64

mt 0-17
mt 65+

2005

2006

2007

2008

nl All
nl 18-64

nl 0-17
nl 65+

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

2008

2005

2006

2007

2008

at All
at 18-64

at 0-17
at 65+

pl All
pl 18-64

pl 0-17
pl 65+

2005

2006

2007

2008

pt All
pt 18-64

pt 0-17
pt 65+

2005

2006

2007

2008

si All
si 18-64

si 0-17
si 65+

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

2008

2005

2006

2007

2008

sk All
sk 18-64

sk 0-17
sk 65+

fi All
fi 18-64

fi 0-17
fi 65+

EN 

17 

   EN 

 
 
 
 
 
 
 
 
 
Figure 2.4: At-risk-of-poverty rate, total and by broad age groups, by country; 2005-08 

35

30

25

20

15

10

5

35

30

25

20

15

10

5

2005

2006

2007

2008

2005

2006

2007

2008

se All
se 18-64

se 0-17
se 65+

uk All
uk 18-64

uk 0-17
uk 65+

2.3.4.  Living standards vary greatly across the EU 

Source: EU-SILC 

Material deprivation rates complement the picture 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  provides  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  expenses,  eat  meat  or  proteins  regularly,  go  on 
holiday, or cannot afford to buy a television, a washing machine, a car or a telephone5.  

17% of Europeans live in these difficult conditions. However, in Bulgaria, Latvia, Hungary, 
Poland  and  Romania  more  than  30%  of  people  are  affected.  The  material  deprivation  rate 
complements the at-risk of poverty rate by reflecting 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  disparities  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  measures  the  percentage  of  the 
population that cannot afford at least 3 of the 9 items quoted above. 

EN 

18 

   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 

n
o
i
t
a
l

u
p
o
p

l
a
t
o
t

f
o
%

60

50

40

30

20

10

0

At-risk-of-poverty rate (left axis)

Material deprivation rate (left axis)

Value of thresholds for a single household (right axis)

15000

18000

s
d
r
a
d
n
a
t
S
r
e
w
o
P
g
n
i
s
a
h
c
r
u
P
n

I

12000

9000

6000

3000

0

EU
27

EU
15

NMS
10

lu 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

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 system 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  disincentive  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 pensions effectively reduce poverty 
risks but the degree to which they do so varies 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 the size of expenditure, which varies from 12% to 
30%  of  GDP,  but  the  composition  of  expenditure,  the  quality  of  interventions,  and,  more 
broadly, the efficiency and effectiveness of social protection also play an important role.  

EN 

19 

   EN 

 
 
 
 
 
 
 
 
Figure  2.6  –  Impact  of  social  transfers  (excluding  pensions)  on  the  at-risk-of-poverty 
rate for the total population (percentage reduction), 2007 

70

60

50

40

30

20

10

0

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,  inequalities  have  often  increased 
and poverty and social exclusion remain a major issue in most EU countries. Most increases 
in inequalities happened between the mid-1980s and the mid-1990s. Over the last 10 years 
inequalities have remained stable in most countries, 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  than  middle  incomes.  In 
some  countries,  low  incomes  caught  up  with  median  incomes,  while  in  other  countries 
inequalities also widened at the bottom of the distribution. 

According  to  national  sources  gathered  by  the  OECD,  relative  poverty  risks  increased  in 
most Member States between the mid-1980s and the mid-1990s and in most cases they either 
increased or remained stable between the mid-1990s and the mid-2000s. Fully comparable EU 
data available for the last three years confirm the stability of relative poverty, 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 contribution to the evaluation of the social 
dimension of the Lisbon Strategy", 2009 

EN 

20 

   EN 

 
 
                                                 
Figure 2.7: Trends in poverty rates and material deprivation, Total population - 2005-
2008 

EU27

EU15

NMS10

n
o
i
t
a
l

u
p
o
p

l
a
t
o
t

f
o
%

50

45

40

35

30

25

20

15

10

5

0

2005

2006

2007

2008

2005

2006

2007

2008

Risk of poverty

Material Deprivation

Source: EU-SILC (2008, 2007, 2006, 2005); Without BG and RO 

2.4. 

Employment growth doesn't automatically 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  increased  participation  of  older  workers  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  faced  by  unemployed  working  age 
adults is more than five times higher than those in work (44% against 8%), and the inactive 
(other than retired) face a risk-of-poverty that is three times higher than that of the employed 
(27% against 8%).  

EN 

21 

   EN 

 
 
 
 
 
Figure  2.8:  At-risk-of-poverty  rate  of  the  unemployed  and  of  the  inactive  (not  retired) 
vs. people employed, people aged 18+, 2008 

Employed

Unemployed

Inactive (not retired)

70

60

50

40

30

20

10

0

eu27cz 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 lv

Source: EU-SILC 2008 

However, having a job is not always a guarantee against the risk of poverty and the working 
poor  represent  one  third  of  the  working  age  adults  at-risk-of-poverty.  In  2008,  8%  of  the 
people in employment were living under the poverty threshold. This figure has not improved 
since 2005. In-work poverty is linked to employment 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 

Working poor: total 18+

Permanent contract

Temporary contract

25

20

15

10

5

0

eu27cz 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 ro

EN 

22 

   EN 

 
 
 
Source: EU-SILC 2008 

Since  2000,  the  rise  in  temporary  work  (see  Figure  2.10),  part-time  work  (including 
involuntary  part-time  working)  along  with  sometimes  stagnating  wages  has  increased  the 
number  of  individuals  with  low  yearly  earnings.  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 

45

40

35

30

25

20

15

10

5

0

Young 
workers: +14%

Total: +15%

Prime age 
workers: +24%

Older 
workers: +9%

2000

2001

2002

2003

2004

2005

2006

2007

2008

Total

15 to 24

25 to 49

50+

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,  single  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,  disability  and  other  discriminatory 
factors, etc.). The worst-off are those households in which nobody works. In 20082008 in the 
EU27, 9.2% of adults of working age and 9.2% of children were living 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  significantly  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 

23 

   EN 

 
 
Figure  2.11  EU-27  -  Employment  and  unemployment  rates  and  shares  of  children  and 
adults (aged 18-59 and not students) living in jobless households; 2001-0808 — % 

14

12

10

8

6

66

64

62

60

58

2001

2002

2003

2004

2005

2006

2007

2008

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  has  set  in.  In  some  countries,  increasing  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  return  to  the  labour  market.  Some  short-term 
responses  to  sudden  increases  in  unemployment  can  exacerbate  these  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 population? Currently, pension 
systems have significantly reduced poverty among 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 for younger people, ranging from 54% in Latvia 
to more than 100% in Hungary. However, single elderly women still face a much higher risk 
of poverty than single men. 

EN 

24 

   EN 

 
 
Figure 2.12: Relative income of the elderly: median income of people aged 65+  
as a ratio of the income of people aged 0-64, 2008 

1,20

1,00

0,80

0,60

0,40

0,20

0,00

v
l

y
c

e
e

g
b

k
d

t
1 l
k
d

i
f

k
u

e
i

e
b

t

m

e
s

s
e

z
c

t

k p
s

l

n

i
s

m ale 

fem ale

o e

l

r

t
e i
d

t
a

r
f

u p

l

l

u
h

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 income distribution of pensioners, are not taken into account, 
nor are other non-monetary benefits (free healthcare, transport, 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 sustainability 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  rate  for  older  workers  by  2010.  In  2007,  the 
employment rate for older workers in the 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 developments 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 pensions. 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  maturation  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 

25 

   EN 

 
 
 
reflects of reforms that have lowered future benefit 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  incentives  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 line 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 replacement 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 

26 

   EN 

 
 
                                                 
Table 2.2: Change in theoretical replacement rates for a worker with average earnings retiring at 65 after 40 years, 2006-2046 

Change in Theoretical replacement rates in percentage points (2006-2046)

NET

GROSS Replacement Rate

Coverage rate (%)

Assumptions

Contribution rates**

Total

Total

Statutory 
pension

Type of 
Statutory 
Scheme (DB, 
NDC or DC), 
2046

Occupational 
and 
supplementary 
pensions

Type of 
Occupational or 
Supplementary 
Scheme (DB or 
DC), 2046

Statutory 
pensions, 
2006

Occupational 
and Voluntary 
pensions, 2006

Statutory 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)

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

4
15
-21
7
1
11
-7
-12
-17
-11
3
14
-12
-3
0
5
-9
6
5
-19
-20
52
2
2
-11
-13
-4

5
15
-16
20
2
9
-12
-9
-16
-10
-3
11
-11
1
-1
13
-8
11
1
-16
-20
39
-4
1
-12
-13
-2

0
15
-16
-10
-9
9
-12
-9
-16
-2
-17
11
-11
1
-1
13
-8
2
1
-16
-20
39
-4
1
-12
-11
-3

DB
DB and DC
DB
DB
DB
DB and DC
DB
DB
DB
DB
DB and NDC
DB
NDC and DC
DB and DC
DB
DB and DC
DB
DB
DB
NDC and DC
DB
DB and DC
DB
DB and DC
DB
NDC and DC
DB

5
/
/
30
11
/
/
/
/
-9
14
/
/
/
/
/
/
10
/
/
/
/
/
/
/
-2
0

DC

DC
DC

DC
DC

DB

DC
DC

100
NA
100
100
90
100
NA
89
100
100
100
100
100
89
92
100
100
100
100
77
81
NA
100
100
100
100
100

55
/
/
78
70
/
/
/
/
55
22(M)/17(F)*
/
/
/
/
/
/
91
/
/
/
/
/
/
/
90
53 (M)/56(F)

16.36
NA
28
0.9 
19.5
22
20
28.3
20
9.5
33
16.6 
20
26
24
26.5
30
7
22.8
19.52
33
29
24.35
28.75
21.6
17.2
19.85% (17.25%)

NA
/
/
8.8
NA
/
/
/
/
10-15
5.7
/
/
/
/
/
/
9.8
/
/
/
/
/
/
/
4.5
9

4.25

12.7
4

10
6.91

11.5 -12.5

4.5
8

Evolution of 
statutory 
pensions 
expenditures 
between 2007 
and 2045 
(source 
EPC/AWG)***
4,8
2,9
1,8
0,8
1,7
0,8
8,6
5,9
1,3
3,1
1,6
6,2
2,8
4,3
11,1
3,9
4,7
4,3
1,6
-0,7
1,3
7,7
6,9
2,2
4,2
1,8
1,8

Source: ISG calculations done using the OECD APEX model or national models, EPC/AWG projections 
*Note: Figures as of June 2008  
**Note: Contribution rates used for statutory schemes and also any occupational or private schemes included in the base case, thus 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 calculation 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 recalled 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 the 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 overall contributions and aggregate wages declared to social security). In Portugal the TRR 
will fall partly due to the introduction of the sustainability factor related to life expectancy. It should be noted that the actual pension cuts resulting from the sustainability factor have been lower than previously 
expected in the 2006 projections. ***Note: AWG projections figures include funded tiers of statutory schemes and statutory early retirement schemes 

EN 

27 

EN 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
However, as the work histories required for a full pension are being extended it is important to 
protect vulnerable groups and cater for career breaks which should not be unduly penalised in 
the  pension  system.  While  the  most  vulnerable  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 equalise pension eligibility ages for men and women to 
help  ensure  that  women  can  have  a  decent  retirement  income.  Furthermore,  care  burdens, 
which  still  mainly  fall  on  women,  and  the  way  they  result  in  lower  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 theoretical 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 

4

2

0

-2

-4

-6

-8

R
F

Z
C

S
E

U
L

I

T F
M

T
A

E
B

L
E

E
S

E
E

K
S

E

I

E
D

K
D

T
L

T

I

K
U

L
P

Y
C

U
H

T
P

L
N

G
B

I

V S
L

O
R

 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 increasing 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 risk of unemployment is well covered by public 
pension  schemes  in  many  Member  States.  Nevertheless,  it  is  definitely  less  true  for  funded 
pensions and the preservation of pension entitlements 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  effects  on  work  incentives  in  order  to  prevent 
becoming a new dependency traps. 

EN 

28 

   EN 

 
 
Figure 2.14. Accumulated difference in net theoretical 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 unemployment compared with no break* 

2

1

0

-1

-2

-3

-4

-5

-6

-7

T
M

T
P

R
F

Z
C

S
E

U
H

G
B

L
E

K
D

E

I

L
N

T
A

T
L

E
E

I

S

K
U

E
B

E
S

U
L

Y
C

E
D

L
P

V
L

 1 year

2 years

3 years

I

T F

I

K
S

O
R

Source: SPC/ISG* The unemployment 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:  ensuring  sustainability  and  access  to  quality 
services for all 

The availability, affordability and quality of health and long-term care systems can strongly 
contribute to ensuring healthy, independent living and improving labour market participation 
and  productivity.  However,  there  are  inequalities  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  Member  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  represents  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,  growing  patient  expectations  and  increased  risky  behaviour  (for 
example,  alcohol  abuse  or  obesity  in  children  and  young  adults).  This  trend  is  yet  more 
marked,  if  combined  with  low  economic  growth,  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 priority setting have been 
deemed an urgent task. 

Member  States  are  in  very  different  positions  to  face  these  challenges.  In  fact,  there  are 
substantial  differences  in  health  outcomes  and  health  expenditure  across  the  EU,  with  those 
reporting lower life expectancy (Bulgaria, Romania, the Baltic states, Hungary) also reporting 

8 

Communication  from  the  Commission:  Solidarity  in  Health.  Reducing  health  inequalities  in  the  EU, 
COM(2009)567/4.  

EN 

29 

   EN 

 
 
                                                 
the  lowest  total  health  expenditure  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 

7
0
0
2
,
y
c
n
a
t
c
e
p
x
e
e
f
i
L

82

80

78

76

74

72

70

5

IT

ES

SE

NL

LU

IE

FI

MT

UK

SI

EU 27

EL

PT

DK

FR

AT

BE

DE

CY

CZ

PL

SK

HU

EE

RO

BG

LV LT

6

7

8

9

10

11

12

Total healthcare expenditure as a % of GDP, 2007

Source: Life expectancy - EUROSTAT 2006 for FR and IT, 2007 for the rest of the 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  expenditure  on  healthcare  and  life  expectancy  in  the  EU 
Member States 

7
0
0
2
,
y
c
n
a
t
c
e
p
x
e
e
f
i
L

82

80

78

76

74

72

70

5

NL

FR

DE

UK

LU

IE

SE

AT

IT

ES

MT

BE
FI

PT

SI

DK

CZ

EU 27

EL

CY

PL

SK

EE

HU

RO

BG

LV

LT

10

15

20

25

30

35

40

45

50

Out-of-pocket paym ents  as  a % of total healthcare  expenditure, 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 

30 

   EN 

 
 
 
 
 
 
 
The current crisis can place an additional economic constraint in countries where the health 
and social care sector is already under-resourced, social protection 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  where  the  financial  situation  of  households  is 
reduced (Hungary). 

The  impact  of  the  economic  crisis  was  felt  strongly  in  some  new  Member-States  (Estonia, 
Latvia, Lithuania, Romania, Hungary), as well as in older and richer 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 adjusting for public health funding deficits remains a 
particular concern especially in the newer Member-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  role  as  automatic  stabilisers  and  sustain  the 
productive  capacity  of  the  economy.  In  some  countries,  however,  there  are  significant 
weaknesses and gaps in social safety nets. In others with mature social protection systems to 
cushion  the  impact  of  the  crisis,  financial  sustainability  is  questioned  in  the  long  run. 
Countries faced with major public finance deficits are left with little room for manoeuvre to 
address the social consequences of the crisis. This is of particular concern for those who also 
have  weaker  levels  of  protection  (e.g.  Lithuania,  Latvia,  Romania).  Mapping  the  at-risk-of-
poverty rate of the total population against total social protection expenditure as a percentage 
of GDP gives  a first  indication  of the importance 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 

31 

   EN 

 
Figure 2.17: Total social protection expenditure and at-risk-of-poverty rate of the total 
population in EU Member States 

35

30

25

20

15

7
0
0
2

,

P
D
G

f
o
%
n

i

e
r
u
t
i

d
n
e
p
x
e

n
o
i
t
c
e
t
o
r
p

l
a
i
c
o
S

10

5

BE

DE

FI

NL

SE
DK
AT

HU
SI

FR

LU

MT

CY

IE

PL

IT

UK

PT

EL

ES

CZ

SK

10

15

BG

LT

EE

20

RO

25

At-risk-of-poverty rate total population, 2008

Note: The horizontal and perpendicular lines depict the EU averages of the variables 

Source: ESSPROS 2007, EU-SILC 2008 

An analysis of the evolution of social spending and public deficits against the economic cycle 
can illustrate to what extent social spending is counter-cyclical, both in good times and bad. 
Ideally,  increases  in  social  protection  expenditure  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,  after  having  increased  sharply  in  the  early  1990s 
when growth rates were very low. In recent years, a trend can be observed towards increased 
resources  devoted  to  social  protection  from  general  government  budgets.  Promoting  labour 
market  participation  in  addition  to  improving  the  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 

32 

   EN 

 
 
 
 
 
 
 
 
 
 
 
Figure 2.18: Expenditure on social protection benefits since 1994 in the EU in relation to 
the fiscal situation, % of GDP 

EU-27

%

11,0

10,0

9,0

8,0

7,0

6,0

5,0

4,0

3,0

2,0

1,0

0,0

-1,0

-2,0

-3,0

-4,0

33,0

30,0

27,0

24,0

21,0

18,0

15,0

12,0

9,0

6,0

3,0

0,0

-3,0

-6,0

-9,0

-12,0

P
D
G

f
o
%

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

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. However, it is also clear that for social protection 
systems to function well, their modernisation needs to be accompanied by effective strategies 
for growth and more and better jobs. 

The AMECO database is based on National Accounts.  

9 
In this extract from AMECO the sum of "Social transfers in kind" and "Social benefits other than social transfers 
in  kind"  in  accordance  with  European  System  of  Accounts  1995  (ESA95)  has  been  used.  Generally 
speaking the results for total expenditure on social protection is somewhat lower than in ESSPROS. For 
details  on  the  main  differences  compared  with  the  European  System  of  Integrated  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.europa.eu/cache/ITY_OFFPUB/KS-RA-07-022/EN/KS-RA-07-022-EN.PDF  

EN 

33 

   EN 

 
 
 
 
                                                 
‘Growth,  Jobs  and  Social  Progress’:  a  contribution  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 modernisation 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 undergone 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 vulnerable 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  markets  and  quality  of  work, 
notably  in  relation  to  its  impact  on  the  gender  dimension.  As  a  consequence,  while  the 
emphasis  should  still  be  on  promoting  growth  and  jobs,  fighting  child  poverty,  engaging 
closely  in  active  inclusion  and  more  generally  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  pursued  and  fully  articulated  with  growth  and 
employment  strategies.  The  consolidation  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 health and safety at work. 

EN 

34 

   EN 

 
3. 

RESPONDING 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 rises 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 Member States have major gaps in their safety 
nets,  and  not  all  governments  have  the  financial  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 Commission estimate (Figure 
2.1) shows that spending on overall recovery 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  investing  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, Hungary 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 

Meas ures  aim ed at hous eholds

Increas ed s pending on labour m arket 

Meas ures  aim ed at bus ines s

Increas ed inves tm ent expenditure

P
D
G
f
o
% 

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S FI
E

E
D

T
A

E
S

L
P

K
U

Z SI
C

E
B

Y
C

L
N

E
K I
D

T
P

T

I

T
M

K
S

R
F

E
V E
L

L
E

O
R

G L
T
B

U
H

Source: Commission services – European Economy Occasional papers N°51 July 09 "The EU's response to 
support the real economy during the economic 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 

35 

   EN 

 
 
 
                                                 
Figure 3.2: Expected increase in social expenditure between 2007 and 2010, pp of GDP 

9%

8%

7%

6%

5%

4%

3%

2%

1%

0%

7
2
-
U
E

expected increase in social expenditure between 2007 and 2010 (in GDP percentage points) - left axis

2007 level of social expenditure (% of GDP) - right axis

45%

40%

35%

30%

25%

20%

15%

10%

5%

0%

i

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L

Source: EC Economic Forecast Autumn 2009 (AMECO database) 

3.1.1.  First evaluation of the impact 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  highlighted  in  the  SPC  report  on  "Growth,  Jobs  and 
Social  Progress"  a  number  of  estimates  for  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  estimates  15%  to  35%  of  economic  fluctuations 
are  smoothed  by  automatic  stabilizers,  depending  on  Member  State11.  In  general,  most 
components of social protection expenditures increase more quickly than GDP in periods of 
economic  downturn,  and  more  slowly  than  GDP  in  economic  recovery.  But,  while 
unemployment expenditures are clearly among the most sensitive to changes in the economic 
conditions, the variability of social protection expenditures also reflects changes in other types 
of expenditures (with significant 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 

12 

13 

Sources:  Creel  J.  and  Saraceno  F.  Automatic  Stabilisation,  Discretionary  Policy  and  the  Stability  Pact,  OFCE, 
working  paper  n°  2008-15;  Van  den  Noord  P.  (2000),The  Size  and  Role  of  Automatic  Fiscal  Stabilizers  in  the 
1990s and Beyond., OECD Economics Department Working Paper, n° 230.  
Dolls  et  al  (2009),  Automatic  Stabilizers  and  Economic  Crisis:  US  vs.  Europe,  IZA  Discussion  Papers  4310, 
Institute for the Study of Labor (IZA). 
One  should  note  that  these  estimates  are  based  on  microsimulation  models  (often  for  different  years)  while  the 
former  are  based  on  macroeconomic  economic  regressions  (for  the  same  years).  Thus  microsimulation  estimates 
are  theoretical  (and  rely  notably  on  sometimes  strong  assumptions  on  take  up  of  benefits  and  employment 
behaviours of households), macroeconomic regression rely on actual figures reflecting past experience. 

EN 

36 

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The results suggest that in the event of a large unemployment shock (e.g. a 5 pp increase in 
the unemployment rate), automatic stabilisers 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  considerable  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  stabilisation  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  stabilisers  is  such  that,  for  the  OECD  countries  as  a 
whole,  the  net  fiscal  stimulus  they  provide  in  2009  is  estimated  to  exceed  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* 

income stabilization (% of shock absorption)
FEDTax

Benefits

SIC

SE
DK
FR
PT
AT
LU
BE
DE
FI
NL
EURO
EU
UK
IE
EL
ES
IT
US
SI
HU
PL
EE

19.7
24.3
7.6
22.5
20
14.7
25.7
23.1
22.4
10.3
16.6
17.2
19.4
20.7
12.6
12.7
18.3
21.5
17.5
22.7
15.1
17.8

2.9
8.3
19
9.4
16.7
9
12.4
14.5
5
13.1
12.9
12.1
6.1
3.6
13.7
6.4
10.1
5.1
21.6
19
17
2.2

45.8
38.2
31.7
30.6
30.3
29.6
27.6
26.8
26.7
23.9
21
18.9
18.6
18.2
11.9
9.1
7.6
7.1
5.4
4.7
-2.7
-3.2

Tax and benefits
68.5
70.7
58.2
62.5
67
53.3
65.7
64.5
54.1
47.2
50.4
48.2
44.1
42.5
38.3
28.3
35.9
33.7
42.5
46.4
29.5
16.8

* 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  the  National  Strategy  Reports.  As 
labour market conditions have continued to worsen 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.  New  or  reinforced  measures  focus  on  flexible  working 

EN 

37 

   EN 

 
 
time arrangements, which are seen as effective means to maintain people in employment in 
response to short term shocks, as well as a way 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  work.  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 support provided to groups at risk, notably youth, 
families  with  children  and  the  disabled.  Some  Member  States  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. renegotiation 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 crisis may have a severe impact on the healthcare sector 
in several EU Member States, on both the supply and demand sides. On the supply side, the 
economic  and  financial  crisis  may  lead  to  reduced  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  result  of  a  combination  of  factors  contributing  to 
worsening health among the general population. 

The health impact of the rapid deterioration in public 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  financed  through  general  tax  revenues,  decreases  in 
GDP and economic outputs may result in significant reductions in public revenue for health. 
Alternatively,  for  countries  that  rely  predominantly  on  wage-related  contributions  to  health 
insurance  funds,  increases  in  unemployment  are  likely  to  constrain  revenues  earmarked  for 
health. 

Several Member States have included measures within their recovery packages to mitigate the 
impact  of  the  economic  crisis  on  health  care,  in  the  following  areas  i)  investing  in  health 
iii) 
infrastructure, 
restructuring and reorganising the healthcare system. 

ii)  providing  additional  funding  to  the  healthcare  sector, 

Some Member States have allocated funding to the construction of new healthcare centres or 
the  upgrading  of  the  existing  health  infrastructure  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 

38 

   EN 

 
Furthermore,  many  Member  States  have  adopted  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 resources 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  productive  and  efficient  way,  re-
defining  priorities  (so  as  to  reallocate  funds  and  distribute  any  surpluses  to  other  fields  that 
appear  to  have  higher  deficits),  and  reorienting  and  reorganising  healthcare  services,  in  an 
attempt to respond effectively to the increased demand for healthcare services in the context 
of the economic crisis. 

However, a few Member States have not introduced 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  crisis  are  still  hard  to 
predict. At present, the bulk of pensions in payment are delivered by public PAYG schemes 
on which the crisis in financial markets has no direct effect. By contrast, the book values of 
the  assets  held  by  pension  funds  have  fallen  significantly  and  real  issues  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 pensioners 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 systems will be affected as unemployment and 
lower  growth  reduce  revenues  from  taxes  and  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 participated in activation measures) or the impact of measures to 
preserve or create jobs. A few countries have commissioned independent ex-post or ex-ante 
evaluations of their overall recovery packages. 

The  preparation  of  their  2010  budgets  is  the  occasion  for  Member  States  to  review  the 
measures  originally  taken  in  the  light  of  constraints  on  public  finances.  This  review  should 
also highlight the need to balance the burden of the policy responses across different levels of 
government.  

One  year  into  the  crisis,  more  Member  States  report  a  stronger  emphasis  on  provisions  to 
ensure  budgetary  discipline.  This  is  because  of  very  high  constraints  on  public  finances, 
and/or  the  need  to  preserve  the  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  others  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. 

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39 

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As  welfare  systems  continue  to  play  their  role  of  automatic  stabilisers,  social  protection 
expenditure  is  projected  to  rise.  However,  their  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 have led some Member States to adopt fiscal 
consolidation packages that may weaken the effects of previous recovery measures aimed at 
preserving  employment  and/or  sustaining  demand.  In  the  long  run,  however,  their  aim  is  to 
ensure sound public finances and thereby support macroeconomic stability and future growth. 

3.3. 

The need for effective and efficient social inclusion policies during and after the 
crisis 

While the economy is expected to return to a 0.7% growth in 2010, labour demand is likely to 
remain  weak  for  a  while  and  past  experience  suggests  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 unemployment 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 both by the drop in their parents income, on which 
they often depend and by the lack of job opportunities. The maturing of pensions systems in 
recent  decades  has  helped  reducing  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 risks 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 — particularly 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 their employability and learning capacity. 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,  conditionality  and  replacement  rates.  Some  workers 
are better covered than others. Young workers with short contributory records and some of the 
self-employed may not be entitled to unemployment benefits, while workers on part-time or 
temporary contracts often benefit from a lower level of protection than other workers.  

Reforms  to  strengthen  incentives  to  work  have  tightened  eligibility  criteria,  or  reduced  the 
level  or  duration  of  benefit  entitlements.  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 durations and relaxed eligibility rules 

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40 

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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 Social 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  unemployment  and  periods  of  inactivity  also  affect 
people’s employability through skill depreciation, discouragement, and in some cases a lack 
of integration in society as a whole.  

3.4. 

Supporting  the  integration  of  the  most  excluded  in  the  labour  market  and  in 
society as whole: the role of activation 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  complemented  with  policies  aimed  at  helping  them  back  on  the  labour 
market and participate fully in society. Active labour market policies and ambitious life long 
learning strategies have an important role to play in fighting poverty and social exclusion.  

The SPC report on "Growth, Jobs and Social Progress" reviews recent 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 the unemployed and help low wage workers to 
get  better  jobs.  It  shows  that  both  spending  and  participation  in  active  labour  market 
measures, including training, have improved overall in the last years. 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  participation  rates  of  the  unemployed  have 
increased  but  were  still  only  around  8.5 %  in  2008.  After  an  increase  in  early  2000,  the 
participation  rates  of  the  inactive  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  hides  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  during  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 increased 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)  and  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 

41 

   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  spending)  remained  the 
same. Further analysis would be needed to identify the factors behind the relative decrease in 
income maintenance spending (changes in the design 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 large 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  declaring  that  they  are  inactive  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 barriers to participation in the labour market and in society as 
a whole. Labour market policies alone are not sufficient to support the integration of the most 
vulnerable in society and into the labour market: the personal, family and social hurdles they 
face should also be addressed by quality social and health services. 

3.5. 

Income support: the specific role of minimum income schemes 

3.5.1.  Minimum income schemes in the context of Active Inclusion 

The  Active  Inclusion  Strategy15  provides  an  integrated  framework  within  which  the 
multidimensional nature of poverty and social exclusion 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 those – 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  1992  Council  Recommendation16  that  called  on  Member  States  to 
recognise such a basic right.  

In  the  context  of  the  adequate  income  support  strand  of  the  strategy,  the  focus  here  is  on 
minimum  income  (MI)  schemes  for  working-age  people  across  EU  Member  States.17 

15 

16 
17 

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 practical 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 Parliament in its Resolution of 6 May 2009. 
Council Recommendation 92/441/EEC. 
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.  Marlier  (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 

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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, Matsaganis and Sutherland (2009),19 the level of income provided to a 
person through a MI scheme is the minimum level 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 insurance 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  experts  part  of  the  EU  Network  on  social 
inclusion20 note that the rise in unemployment brought 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 conceived as a short-term form of assistance (though 
formally not time-limited in most Member States). They are means-tested and funded through 
the  tax  system  (i.e.  non-contributory).  They  mainly  target  people  out  of  work  but  some 
Member  States  have  extended  their  scope  to  provide  in-work  income  support.  The 
institutional features of MI schemes across EU countries are considered 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  States  in  the  way  MI  schemes  are  designed.  In 
terms  of  comprehensiveness  of  the  schemes  (i.e.  the  extent  to  which  MI  schemes  are  non-
categorical,  thus  generally  applying  to  the  low-income  population  and  not  only  to  specific 

18 

19 

20 

21 

http://www.peer-review-social-inclusion.eu/network-of-independent-experts/2009/minimum-

from: 
income-schemes. 
The  work  on  MI  presented  in  this  document  is  meant  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. 
Figari F., T. Haux, M. Matsaganis and H. Sutherland (2009) "The effects of Minimum Income schemes 
on the working-age population in the European Union",SSO Research Note 5(2009). 
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 the Member States and candidate Member States. Twice a 
year,  the  experts  produce  a  report  on  their  respective  countries  concerning  a  specific  subject  that  is 
being examined in the context of the EU social inclusion 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 official 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 countries. For more information on the network and its 
work, see: http://www.peer-review-social-inclusion.eu/network-of-independent-experts. 
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). 

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subgroups),  the  work  of  the  EU  Network  experts  pinpoints  to  the  existence  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  countries  (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 the 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  related  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  incomes  that  still  have  no  access  to  MI  schemes. 
Some groups, like the homeless, refugees and asylum seekers, are often left uncovered even in 
the countries with the more comprehensive schemes.  

22 
23 

24 

25 

26 

This has improved with the introduction of the RSA in 2009 
People  are  considered  as  "covered"  by  one  or  more  MI  schemes  if  they  meet  all  the  eligibility 
conditions and are therefore entitled to receive benefits. 
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  the  different  countries.  Market  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, disposable income. Baseline results from EUROMOD rely on 
the assumption of full take up (i.e. all eligible individuals or households receive the benefits they are 
entitled  to)  (see  Paulus  A.,  F.  Figari  and  H.  Sutherland  (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.  
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 the analysis with updated policy rules. The new version 
of the model using 2008 policy rules for 9 EU countries 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 Partnership Agreement between DG EMPL and the University 
of Essex). 
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  the  UK).  Among  the  other  conditions  of  entitlement, 
information on availability for work and citizenship is not always available (Figari et al., 2009). 

EN 

44 

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Figure  3.3  –  Working-age  (16-64)  individuals  below  the  poverty  line  (at  60%  of  the 
median) by minimum income entitlement status (policy years 2001, 2003, 2005) 

e
l
p
o
e
p
e
g
a
g
n
i
k
r
o
w

f
o
%

18%

16%

14%

12%

10%

8%

6%

4%

2%

0%

BE DK DE

EE

EL

ES

FR

IT

LU HU

NL

AT

PL

PT

SI

FI

SE UK

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 2003 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 simulated for IT and ES, where the schemes are administered at 
the regional level and variation across regions is too large. 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. Results for these three countries should be treated with 
caution.  
Source: Figari, Haux, Matsaganis and Sutherland (2009) 

In  terms  of  trends,  many  Member  States 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 with 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 

28 

29 

The  specific  MI  schemes  considered  are  “droit  à  l’integration  sociale”  for  BE;  “kontanthjælp  and 
starthjælp”  for  DK;  “Sozialhilfe”  for  DE;  “toimetulekutoetus”  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;  “rendimento  social  de  insercao”  for  PT;  “denarna 
socialna pomoč” for SI; “toimeentulotuki” for FI; “ekonomiskt bistand” for SE; “income support” for 
the UK; no general MI scheme for EL and HU (EUROMOD cannot represent the discretion left to the 
local level in some systems). 
For each country the main characteristics of the MI scheme, as from MISSOC, are summarised in Table 
A2, Appendix 1, in Figari et al. (2009). 
Though modelled in the current version 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 

45 

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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 schemes, 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 additional 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  income  of  households  with  working-age 
individuals in the poorest 10% of the population (policy years 2001, 2003, 2005) 

Market income
Social insurance contributions
Unemployment benef its
Old age benef its

Personal taxes
Other benef its
Family benef its
MI schemes

e
m
o
c
n

i
e
l
b
a
s
o
p
s
i
d
f
o
% 

200

180

160

140

120

100

80

60

40

20

0

-20

-40

-60

BE DK DE EE EL ES FR IT

LU HU NL AT PL

PT

SI

FI

SE UK

Source: EUROMOD

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: Figari, Haux, Matsaganis and Sutherland (2009) 

In  most  Member  States  MI  schemes  are  designed  as  schemes  applying  to  the  country  as  a 
whole, while delivery is delegated to the local authorities. But there are 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 

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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  that  people  entitled  to 
benefits  might  actually  not  receive  them  due  to  the  following  reasons  (Hernanz,  Malherbet 
and Pellizzari, 2004):31 

(1) 

(2) 

(3) 

(4) 

(5) 

relatively  high  "information  costs"  for  potential  claimants  (i.e.  efforts  required  to 
obtain  and  understand  information)  with  regard  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; 

"administrative  costs"  related  to  the  duration  of  the  administrative  process  and  to 
uncertainties  with  regard  to  the  outcome  of  the  application,  which  may  discourage 
potential claimants from applying; 

pecuniary determinants affecting the (rational) cost-benefit calculation to  claim  for 
benefits, related to benefit levels 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 situations of less extreme need); 

social and psychological costs related to the perception of SA support and the fear of 
stigmatisation refraining people from claiming; 

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  factors  might  be  exacerbated  by  the  insufficient  number  of 
social workers processing the applications). 

Evidence on take up is currently very fragmented, limited in terms of country coverage and 
referred  to  different  (mostly  not  recent)  years  and  different  benefit  schemes  for  different 
countries. In the EU, the UK is the only country where official estimates 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 quoted OECD paper by Hernanz et al. (2004) reports estimates of take up for 
SA and housing benefits ranging between 40% and 80%. A recently completed EUROMOD 

30 

31 

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. 
Hernanz V., F. Malherbet and M. Pellizzari (2004) "Take-up of welfare benefits in OECD countries: a 
review  of 
the  evidence"  OECD  Social,  Employment  and  Migration  Working  Papers 
DELSA/ELSA/WD/SEM(2004)2. 

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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  claimed)  for  SA  ("Hilfe  zur  Sicherung  des 
Lebensunterhalts") in 2003 (Fuchs, 2007);34 

–  Finland:  between  50%  and  60%  for  SA  ("Toimeentulotuki")  by  working-age  families 
between 1996 and 2003 (with a declining rate over the period) (Bargain et al., 2007);35 

–  Germany: 33% by caseload and 43% by expenditure 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  Social  Integration  Income  (RSI)  in  2009 

(Rodrigues, 2009);38 

–  UK:  between  78%  and  88%  by  caseload  and  between  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 therefore 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 Belgium non-take up is 
estimated to be greater for women, couples, individuals with educational attainment below the 
second stage of secondary studies and the 16-24 age cohort. In the UK, people that do not take 
up Income Support tend to be slightly older than those that take it up (with a larger share of 
people  aged  50-59)  and  more  likely  to  be  owner-occupiers  in  terms  of  tenure  type,  to  have 

32 

33 

34 

35 

36 

37 

38 

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).  
Matsaganis  M.,  A.  Paulus  and  H.  Sutherland  (2008)  "The  take  up  of  social  benefits"  SSO  Research 
Note 6(2008). 
Fuchs M. (2007) "Social assistance – No, thanks? Empirical analysis of non-take up in Austria 2003" 
EUROMOD Working Paper No. EM4/07.  
Bargain  O.,  H.  Immervoll  and  H.Viitamäki  (2007)  "How  tight  are  safety  nets  in  Nordic  countries? 
Evidence from Finnish register data" IZA Discussion Paper 3004. 
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. 
Vrooman  J.C.  and  K.T.M.  Asselberghs  (1994)  "De  gemiste  bescherming,  niet-gebruik  van  sociale 
zekerheid door bestaansonzekere huishoudens" COSZ/Sociaal en Cultureel Planbureau, Rijswijk. 
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. 

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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 instance, 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 and 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 welfare programme are reached, this clearly reduces 
the chance for the programme to achieve its objectives (Hernanz et al., 2004). Secondly, when 
not claiming a benefit is (at least partly) involuntary, due, for instance, 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).  Moreover,  if  information  on  benefit  programmes  is  not 
"randomly  distributed"  but  rather  more  available  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 relatively 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 effects of non-take up of SA schemes in some 
EU countries.40 Simulation results pinpoint to the following effects (see Table 3.2):41 

(1) 

(2) 

non-take up lowers the capacity of SA benefits to reduce the aggregate poverty gap.42 
Incomplete take up reduces poverty gap efficiency by over a half in PL, by around one 
third in SE and PT, and by a tenth in the UK. 

non-take up has a significant negative effect on SA effectiveness 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  effects 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  entitlement  and 

39 
40 

41 
42 

The difference becomes negligible after including housing costs (DWP, 2009).  
The  schemes  considered  in  the  four  countries  for  which  results  are  reported  here  below  are:  Pomoc 
Społeczna  in  PL,  Rendimento  Mínimo  Garantido/Rendimento  Social  de  Inserção  in  PT,  Ekonomiskt 
Bistånd/Socialbidrag in SE, and Income Support in the UK. 
The policy year considered is 2001 for all countries but Poland, for which 2005 is used. 
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 

49 

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application  procedures.  For  instance,  the  EU  Network  expert  for  Ireland  highlights  that 
strategies  to  increase  take  up  have  focussed  especially  on  information  campaigns  through  a 
variety  of  media  and  formats.  For  the  Netherlands,  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  facilities,  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  means  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 entitlement 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 disposable income - unless stated 
otherwise - under complete take up; all values in %) 
(policy years 2001, 2005) 

Poland 

Portugal  Sweden  UK 

49.9 
23.5 
-53 

13.0 
15.8 
22 

15.4 
15.4 
0 

22.4 
16.1 
-28 

A. Poverty gap efficiency 
Complete take up 
Incomplete take up 
Proportional change 
B. At-risk-of-poverty rate at 60% of median 
Complete take up 
Incomplete take up 
Proportional change 
C. At-risk-of-poverty rate at 50% of median 
Complete take up 
Incomplete take up 
Proportional change 
D. At-risk-of-poverty rate at 40% of median 
Complete take up 
Incomplete take up 
Proportional change 
E. Poverty gap 
Complete take up 
Incomplete take up 
Proportional change 

10.1 
10.1 
0 

2.6 
5.4 
107 

2.9 
4.8 
64 

3.7 
4.0 
9 

4.2 
4.6 
9 

5.4 
9.2 
69 

48.7 
33.3 
-32 

8.8 
9.5 
8 

4.3 
5.7 
31 

2.5 
3.7 
47 

2.2 
2.9 
34 

59.9 
54.0 
-10 

14.6 
15.1 
4 

7.2 
8.0 
10 

2.8 
3.7 
30 

3.2 
3.7 
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 external 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. 

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50 

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3.5.4.  Minimum income schemes: the issues 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 Member 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 reported 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  beyond  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 Protection 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 results 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  poverty  line  (at  60%  of  the  median) 
before and after receiving MI benefits. The median poverty gap for people entitled to benefits 
is indeed reduced through MI benefits in all countries, though with a substantial cross-country 
variation. The effect is stronger in BE, the NL and SE and smaller in ES, EE, AT, PL and FI. 
Figure 3.5 also shows that in all countries the median poverty gap is larger for working-age 
individuals entitled to MI (before receiving it) than for individuals that are not entitled to it. 
This suggests that MI schemes are indeed targeting the poorest working-age individuals in all 
countries, despite the fact that, as mentioned above, 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  deterioration  of  benefit  adequacy 
with  respect  to  general  living  standards,  with  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 standardised 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 Marlier, 2009, and the country reports produced by the 
EU Network of independent experts for the country-specific institutional details on this).  

44 
45 

46 

47 

COM(2008) 639 final. 
European  Commission  (2008)  “Social  protection  and  social  inclusion  2008:  EU  indicators” 
Commission Staff Working Document. 
The poverty gap is expressed as the distance between the household equivalised income and the poverty 
line as a proportion of the poverty line. 
Nelson  K.  (2009)  "Social  assistance  and  minimum  income  protection  in  the  EU:  vulnerability, 
adequacy, and convergence" Luxembourg Income Study Working Paper No. 511. 

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51 

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Figure 3.5 – Median poverty gap of working-age individuals below the poverty line (at 
60% of the median) by MI entitlement status (before and after receiving MI benefits) 
(policy years 2001, 2003, 2005) 

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

BE

DE

EE

ES

FR

IT

LU

NL

AT

PL

PT

SI

FI

SE

UK

Not entitled to MI Entitled to MI (before receiving MI) Entitled to MI (after receving 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, where the schemes are administered at the regional level 
and variation across regions is too large. For these two countries MI receipt information 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 schemes 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, increases 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  Commission  study  shows  that  between  2001  and  2007  the 
largest improvements in terms of reducing unemployment traps were achieved by FR, SK, FI, 
SE, BE and DK for all household types. The introduction of in-work benefits contributed to 
reducing  unemployment  traps  in  FR,  SK,  IE  and  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 reducing the financial disincentives to work in FR and FI. 

48 

European  Commission  (2009)  “Recent  reforms  of  the  tax  and  benefit  systems  in  the  framework  of 
flexicurity” European Economy Occasional Papers 43, Feb 2009. 

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Inactivity  traps  were  also  considerably  reduced  between  2001  and  2007  in  a  number  of 
countries. In particular, this was the case for one-earner couples with children at a low wage 
level in FR, SE, AT, ES, FI, CZ and SK. The reduction was mainly due to changes in social 
assistance schemes, followed, for instance, by the 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 children), the UK (for one-earner couples), IT 
(for  two-earner  couples  with  and  without  children)  and  IE  (for  two-earner  couples  without 
children  and  single  parents  with  children).  Based  on  recent  data  (2007),  reductions  in 
inactivity  traps  have  been  recorded  in  particular  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  design  of  MI  schemes  that  might  bring  about 
disincentives to take up work are identified by the EU Network experts (Frazer and Marlier, 
2009). These include: 

(4) 

(5) 

high  benefit  withdrawal  rates  (also  with  regard  to  secondary  benefits  providing 
access to key services like medical care and childcare); 

lack  of  systematic  mechanisms  to  adjust  the  value  of  earnings  disregards49  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  detailed  review  of  the  existing 
evidence and further analytical work on the relationship between minimum income protection 
and  incentives  to  take  up  work  will  be  conducted  with  the  Social  Protection  Committee 
Indicators Sub-Group. 

4. 

THE  USE  OF  THE  EUROPEAN  SOCIAL  FUNDS  TO  SUPPORT  SOCIAL  OBJECTIVES 
DURING THE CRISIS AND IN THE LONG TERM 

The  European  Union  mobilises  significant  financial  resources  to  fight  poverty  and  social 
exclusion and to promote the policy objectives agreed in the Social OMC. Here, the European 
Social Fund (ESF) is the single most important financial instrument at the disposal of the EU. 
The ESF accounts for almost 10 % of the € 120 billion annual EU budget, 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  social  inclusion,  fighting  discrimination  and 
strengthening institutional capacity. 

As  described  in  greater  depth  in  the  2008  Joint  Report  on  Social  Protection  and  Social 
Inclusion,  Member  States  have  designed  strategies  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 

53 

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Fighting poverty and social exclusion through ESF interventions primarily takes two forms. 
Firstly,  the  ESF  can  target  social  exclusion  explicitly.  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  intervention  is  used,  however,  the  bulk  of  ESF 
spending helps prevent or reduce social exclusion.  

The two approaches outlined above involve a broad range of target groups and policy areas. 
In  the  period  2007–2013,  the  European  Social  Fund  will  focus  on  the  social  inclusion  of 
disadvantaged  people,  in  particular  by  improving  their  opportunities  for  integration  in  the 
labour  market.  In  addition,  the  ESF  also  supports  employability  measures,  the  social 
economy,  access  to  vocational  training,  and  life-long  learning.  Gender  mainstreaming,  the 
promotion of equal opportunities and anti-discrimination measures 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 contribution to health and long-term care by focusing on 
key personnel employed in this labour-intensive sector.  

The  operational  programmes  for  the  2007–2013  programming  period  were  developed  in  a 
period  of  increasing  employment  and  stable  growth,  but  the  overall  economic  context  in 
which  they  now  operate  has  changed  fundamentally.  Economic  growth  plummeted  in  2009 
and the situation in the labour market has deteriorated significantly. For many disadvantaged 
persons,  the  result  is  further  vulnerability  and  isolation  from  the  labour  market.  Social 
protection and inclusion systems now face the enormous challenge of ensuring that the crisis 
does not disproportionately affect those citizens most in need.  

The unemployed are the group requiring most urgent 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  urgent  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 increasing scarcity of resources, the 
ESF  can  provide  stable,  predictable  and  available  financial  support.  In  their  response  to  the 
crisis, Member States and the European Union have made use of the financial instruments at 
their  disposal,  such  as  the  ESF,  by  re-adjusting  their  operational  programmes,  where 
necessary, and fine-tuning them to their emerging needs.  

Member  States’  responses  to  the  crisis  also  reflect  the  will  not  to  lose  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-consuming,  the  way  operational  programmes  are 
implemented  shows  that  combating  the  crisis  in  the  short  term  and  addressing  long-term 

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54 

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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  actions  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 instruments 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 social inclusion of workers losing their jobs. 

4.1. 

ESF support for social protection and inclusion: 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  ESF  to  enhance  support  for  the  unemployed,  to 
prevent  further  rises  in  unemployment  and  to  strengthen  the  social  inclusion  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 arrangements to better respond to the crisis 

4.1.1. 

Support for the unemployed 

As  mentioned  earlier,  the  current  economic  crisis  has  had  a  significant  impact  on 
unemployment. Given the well-known link between poverty and unemployment, a key policy 
objective  is  to  ensure  that  unemployed  people  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  exclusion.  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  priorities  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 costs of transport and settling down in other places, funds for 
retraining  qualified  redundant  employees  (for  instance  from  the  service  sector),  or  financial 
support for business start-ups by employees losing their jobs as a result of lay-offs. Similarly, 
additional ESF funds have been allocated to support self-employment for the unemployed in 
Slovenia. 

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55 

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Ireland has introduced a number of new active measures that may receive ESF co-funding, 
such  as  a  work  experience  scheme  (including  for  graduates),  an  increase  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 increased number of short-term training places.  

In  the  UK,  the  devaluation  of  the  sterling  against  the  euro  since  2008  has  resulted  in 
additional  ESF  funding  in  England  amounting  to  £ 179  million.  This  additional  funding  is 
being used to help those most affected by the economic downturn. Of this, £ 79 million has 
been allocated to provide extra help for the unemployed 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 centres (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  posts’,  ‘work  experience’,  ‘promotion  of  new 
employers’ and so forth, targeting particular groups and different sectors. 

Portugal has strengthened measures to address the unemployed, such as qualification actions, 
professional  training,  professional  internships  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 self-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 people 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 poverty, it is important that rising unemployment 
is tackled — especially the drift towards long-term unemployment. Many ESF actions taken 
by  Member  States  have  been  designed  with  a  view  to  preventing  further  rises  in 
unemployment and people falling into social exclusion and poverty. 

Germany  has  responded  to  the  crisis  by  adapting  its  short-term  allowance  scheme 
(Kurzarbeitergeld) to the new situation on the labour market. The principle is ‘better retrained 
than  redundant’  (‘Qualifizieren  statt  entlassen’).  In  particular,  the  maximum  duration  for 
receiving the short-term allowance has been extended 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  courses.  If  such  a  course  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 training 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 and training costs of employees whose companies 
are  forced  to  reduce  their  working  hours.  The  two  short-term  working  schemes,  ‘Train 

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yourself!’  and  ‘Training  is  a  chance’,  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  and  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-financed  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  market.  Since  the  financial  crisis,  however, 
funding  has  also  targeted  the  increasing  number  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 national resources and ESF regional operational 
programmes have been allocated to such unemployment benefits and to active labour market 
policies (ALMPs) for the period 2009-2010, focusing 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  employment  services  and 
employment  agencies  and  the  target  groups  benefit  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  traineeships  and  stimulating  regional  cooperation 
between  all  actors  (municipalities,  social  partners,  schools,  PES)  able  to  contribute  to 
participation possibilities for young people up to the age of 27. The activities qualifying for 
support  are  those  covered  by  the  national  Action  Plan,  and  include  education,  training, 
guidance, working/learning combinations, traineeships, apprenticeships, etc. 

In  Spain,  the  ESF  contributes  to  a  number  of  actions,  focusing  both  on  the  short  term 
(responding to lay-offs) and on the long term (supporting sustainable economic growth), such 
as  reinforced  personalised  guidance  and  support,  skills  development  and  local  needs,  the 
promotion of occupational and geographical mobility, and the concentration of support on the 
most  vulnerable.  Over  a  long-term  perspective,  the  ESF  provides  reinforced  support  to 
emerging sectors (identification of future occupational and skills requirements) and to human 
capital and education actions (combating 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  most  vulnerable  (general  introduction  of  the 
‘active solidarity income’ — Revenu de Solidarité Active (RSA)). In addition, it was decided 
to extend temporarily the ESF support for training activities by crisis-affected companies with 
more than 250 employees (whereas the OP targets mainly SMEs).  

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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  ESF 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 crisis. Most ESF OPs try to ensure a coordinated response to the 
needs  of  those  furthest  from  the  labour  market,  including  actions  to  promote  access  to 
employment  and  sustainability,  the  social  inclusion  of  disadvantaged  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 women and young people) and strengthen the social inclusion of 
vulnerable  groups,  while  also  supporting  the  development  of  human  resources  and  the 
adaptability of workers and enterprises. As a result, there is a high degree 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  interventions  under  the  Prevention 
Action Plan (such as promoting new employment opportunities for vulnerable persons, skills 
upgrading,  vocational  training,  work  experience  and  subsidised  job  placements,  along  with 
upgrading and expanding the activities of the public 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  the  devaluation  of  sterling 
against the euro) has been allocated to increasing the support that Jobcentre Plus provides to 
disadvantaged  groups  such  as  ex-offenders,  refugees,  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 system for programmes co-financed by the ESF. 
This system gives greater support to social inclusion projects, for  which  40 % pre-financing 
(instead of 30 %) has been set aside. 

In  Greece,  an  important  objective  is  to  further  restructure  the  public  employment  centres 
(KPA) by converting them into ‘one-stop shops’ able 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  attendance  of  vulnerable  groups  in  secondary 
education  (Roma,  migrants,  minorities)  and  to  reduce  early  school-leaving  and  promote 
achievement  through  all-day  schools,  learning  support  programmes  for  immigrants,  the 
establishment  of  intercultural  schools,  ‘second  chance’  schools  and  adult  education  centres, 
and the use of new technologies in the learning process.  

4.1.4. 

Simplifying ESF implementation arrangements to respond to the crisis  

In their response to the crisis, Member States have 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 

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supported by the ESF and the fine-tuning of programmes, it is worth noting that a number of 
changes  to  OPs  and  implementing  arrangements  have  been  made.  Member  States  have 
amended the selection criteria, modified the strategic indicators to take account of emerging 
needs and, in some cases, reallocated funding 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  envisaged  by  the  authorities,  including  fast-
tracking for project selection — especially for labour market 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  substantially  in  response  to 
the challenges faced by Latvia due to the financial and economic crisis. The main change is 
the  re-allocation  of  resources  to  Priority  3  ‘Promotion  of  Employment  and  Health  at  Work’ 
(€ 22  million)  and  Priority  4  ‘Promotion  of  Social  Inclusion’  (€ 16  million).  New  measures 
include  a  local  employment  emergency  programme,  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.  Similarly,  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 ‘Increasing Participation and Reducing Inequality 
in the Labour Force’ to Priority I ‘Increasing Activation of the Labour Force’.  

In  Portugal,  the  ESF  programme  has  been  modified  to  mitigate  the  impact  of  the  crisis. 
Under priority 5 ‘Support for entrepreneurship 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 unemployed people and social welfare beneficiaries 
by supporting their participation in useful social activities. Priority 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  programmes  will  continue  with  long-term  social 
inclusion  actions  to  strengthen  social  cohesion.  In  the  current  programming  period,  some 
Member States are using the ESF to implement multidisciplinary actions to respond to more 
complex  social  challenges.  These  actions  cover  different  fields  such  as  education, 
employment or social inclusion in a holistic manner. The experiences to date show that ESF 
support mobilises and triggers effects from different policy fields which would otherwise not 
have  come  about.  The  catalytic  effect  generated  by  the  ESF  on  the  ground  leads  to  the 
streamlining  of  multidisciplinary  actions,  thus  overcoming  fragmented  policy-making  and 
combining different interventions into a single comprehensive approach. 

•  In  Slovakia,  the  ESF  co-finances  the  complex  (comprehensive)  local  development 
strategies  for  marginalised  Roma  communities.  These  strategies  have  been  allocated 
almost  € 179  million  for  the  programming  period  2007-2013.  They  require  at  least  one 

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investment project (ERDF) and 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  infrastructure  (educational, 
social and tourist, plus settlement regeneration), 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 that economic and social deficiencies are usually concentrated 
in  specific  neighbourhoods  where  structural  deficiencies  in  buildings  and  dwellings, 
inadequate  infrastructures,  high  unemployment  rates,  low  incomes,  lack  of  skills  or 
education  and,  as  a  result,  poor  employment  opportunities  are  creating  tensions  in  these 
communities, including tensions between different 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 action. Under the BIWAQ programme, 
public  bodies,  private  entities  and  partnerships  (such  as  businesses,  education  or  training 
providers, schools, clubs or associations) may receive 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 following its integrated approach. BIWAQ projects 
target both the mainstream segments of society and persons with an immigrant background 
and  aim  to  promote  social  inclusion  and  community  life  in  neighbourhoods.  BIWAQ 
focuses  on  (1)  helping  the  long-term  unemployed  back  to  work;  (2)  providing  young 
people  with  training  and  integrating  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 regional government has singled out 
80  particularly  deprived  neighbourhoods  in  the  region  for  intervention  under  the  ESF 
Programme ‘Employment in the 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.  The  success  of  the  project  prompted  its 
mainstreaming in the OP 2007-2013. The project comprises an ad hoc consortium bringing 
together  all  relevant  actors  to  jointly  manage  actions  (urban  planning,  social  inclusion, 
training,  etc.).  Main  ‘innovative’  features:  strengthening  and  recognition  of  local 
governments as main actors in employment and 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  implementation  of  policies  to  territorial 
implementation; and strengthened cooperation between regional/local administrations.  

•  In  Ireland,  the  ESF  helps  promote  equality  in  tertiary  education  by  increasing  the 
participation rates of students with disabilities, students from disadvantaged backgrounds, 
including  from  the  Roma  community,  ethnic  minorities  and  mature  ‘second-chance’ 
students,  through  the  ‘Third  Level  Access’  measure.  The  Fund  for  Students  with  a 

50 

51 

BIWAQ  stands  for  ‘Bildung,  Wirtschaft,  Arbeit  im  Quartier‘  (education,  economy,  work  in  the 
neighbourhood). 
This programme is an urban development programme which targets neighbourhoods with development 
priority. The Social City (Soziale Stadt) was launched in 1999 to counteract the increasing social and 
spatial segregation of urban communities. 

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Disability,  part  of  the  Third  Level  Access  fund,  provides  grants  for  the  provision  of 
services  and  purchase  of  equipment  for  students  with  serious  sensory,  physical  and/or 
communicative disabilities. ESF co-financing is also used to provide targeted aids such as 
transport,  sign-language  assistance/interpreters  and  personal  assistants.  The  Student 
Assistance Fund, which aims to assist students 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.  Assistance  under  the  Student  Assistance  Fund 
covers rent, books/course materials and living expenses. Expenses financed under the Fund 
for Students with Disabilities include transport, personal assistance, and equipment.  

•  In  the  UK,  the  ESF-funded  project  Seeing  the  Potential,  which  is  run  by  the  Royal 
National  Institute  of  Blind  People  (RNIB),  assists  blind  and  partially-sighted  people  to 
prepare for work — through training or work placements — and secure and sustain paid or 
voluntary  employment.  The  project  operates  by  regularly  meeting  with  clients  to  assist 
with  exploring  employment  options  and  identifying  vacancies,  creating  a  CV,  and 
providing assistance with application forms and cover letters. 

4.3. 

The European Globalisation Adjustment Fund (EGF) 

The  EU  Structural  Funds,  in  particular  the  European  Social  Fund  (ESF),  support  the 
anticipation  and  management  of  change  through  activities  with  a  strategic  and  long-term 
perspective,  such  as  life-long  learning.  In  contrast,  the  European  Globalisation  Adjustment 
Fund (EGF) provides one-off, time-limited individual support geared to helping workers who 
have become redundant as a result of globalisation. 

The  EGF  exists  to  support  workers  who  lose  their  jobs  as  a  result  of  changing  global  trade 
patterns or the current economic and financial crisis. When a large enterprise shuts down or a 
factory is relocated to a country outside the EU, or a whole sector loses many jobs in a region, 
the EGF can help the redundant workers to find new jobs as quickly as possible. A maximum 
amount of € 500 million per year is available to the 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  modified  in  2009  to  enable  it  to  respond  more 
flexibly to the requirements of redundant workers. Some aspects of the EGF were modified 
specifically for the expected duration of the crisis, including: 

–  The  addition  of  the  crisis  itself  as  a  qualifying  condition.  Where  previously  evidence  of 
changing  world  trade  patterns  had  to  be  provided,  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 from the moment of redundancy, which may occur 
several  months  before  the  decision  on  such  funding  has  been  taken  by  the  EU’s  budgetary 
authority. 

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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 specifically 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  levels.  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  that  the  EGF  tackles  is  geographical  remoteness.  The  case  of 
Perlos in Eastern Finland showed that the collapse of the biggest employer in the region may 
threaten  the  whole  area  with  depopulation.  By  helping  the  workers  to  acquire  new  skills 
locally and to find new jobs or start their own businesses, the EGF helped to ensure a brighter 
outlook for the region, and to keep the younger population there. 

5. 

THE 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 economic crisis differs between 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 situation of EU citizens. This complex picture is at 
least  partly  due  to  the  different  structure  of  housing  markets  and  their  legal  and  policy 
frameworks. The labour and credit markets constitute the most obvious connection between 
housing and the broader economy.  

Employment  in  the  construction  sector,  which  increased  in  the  vast  majority  of  Member 
States between 2000 and 2007 with the housing boom, 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  increased  the  risks  of  becoming  homeless. 
Concerning  the  credit  market,  the  vulnerability  of  households  to  fluctuating  and  often  over-
inflated  house  prices  and  to  uncertain  financial  markets  has  increased  in  the  last  ten  years: 
mortgage  debt  as  a  percentage  of  household  income  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 impact on the housing situation of EU citizens are 
illustrated  by  the  following  examples  based  on  national  data52.  Significant  increases  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).  

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and  +46.3 %  in  2009),  Spain  (+126 %  in  2008),  Greece  (+17 %  in  2008),  Ireland  (+30 % 
between  June  2008  and  June  2009),  and  the  United  Kingdom  (from  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 schemes 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, Member States have reacted with measures to protect 
mortgage holders,  such  as  housing  loan  subsidies  (EL,  IT,  NL,  PL53, IE,  SK  and the UK), 
state guarantees for mortgage loans and tax reforms (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 efficiency (DE, ES, FR, IE, LV, LU, MT, AT, 
PT and the UK). More general measures introduced to strengthen income support are also 
important to help people cope with the worsening conditions in the labour market.  

5.2. 

Housing exclusion –- an important challenge 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 are poor. This is why the Charter 
of  Fundamental  Rights  provides  for  the  right  to  housing  assistance  so  as  to  ensure  a  decent 
existence for all who lack sufficient resources. Housing  support  and social  housing are also 
recognised as essential services in supporting active inclusion policies55.  

Housing  affordability  is  an  important  challenge  considering  that  housing  costs  represent  a 
significant proportion of people’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  for  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 

54 

55 

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. 
For further analysis on homelessness and housing exclusion, see also the 2009 Social Situation Report 
at: http://ec.europa.eu/social/main.jsp?catId=675&langId=en  
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).  

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Fig. 5.1: Share of housing costs in total household income net of housing allowances — 
2007 

60

50

40

30

20

10

0

poor

non-poor

Total

EU25 SIMTESLU IEPTCY FI

FRAT

EE ITLTLVSEBEHUCZPL

SKELUKDKNL

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  income  is  also  particularly  important  for 
households in  more densely urbanised areas, for 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  population  housing  costs  account  for  over  40 %  of  disposable 
income, which can significantly reduce the capacity of the household to adequately cope with 
all the other needs besides accommodation, even if the relevance of a relatively high housing 
cost  burden  on  household  welfare  obviously  depends  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 such as SK, DK, NL, EL and BG over 50 % of the at-risk-of-
poverty  population  faces  an  excessive  housing  cost  burden.  This  represents  an  important 
challenge  in  terms  of  increased  risks  for  social  and  housing  exclusion.  It  also  points  to  the 
importance  of  housing  affordability  as  a  fundamental  element  in  improving  the  living 
standards of people at risk of poverty.  

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Fig. 5.2: Housing costs overburden rate — 2007 

70

60

50

40

30

20

10

0

Poor

Non-poor

Total

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 BG

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 population. 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 
- one room for the household; 

The dwelling is considered overcrowded if one the criteria mentioned below is not fulfilled:  

57 

- 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 different sex between 12 and 17 years of age;  
- one extra room - for two people under 12 years of age. 
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 living-room can have different impacts on the capacity 
of the individual to invite people and socialize at his or her place according to the different social and 
cultural  norms.  For  these  reasons,  data  on  overcrowding  is  published  with  and  without  single-person 
households.  

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Fig. 5.3: Overcrowding rate by poverty status — 2007 

70

60

50

40

30

20

10

0

Non-poor

Poor

Total

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 LV

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-poverty 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  

90

80

70

60

50

40

30

20

10

0

poor

non-poor

total

EU MTSK FI

SEDK ATDE LUCZ IEFRBE NLUKEL ITES SLHU PTCYEEBG LTPLLVRO

Note: housing deprivation factors 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. 
Source: EUROSTAT; EU-SILC 2007.  

EN 

66 

   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 
18
14
15
16
11
13
22
15
19
18
14
21
30
26
25
15
19
5
18
9
37
20
29
17
6
5
6
15

eu27
be
bg
cz
dk
de
ee
ie
gr
es
fr
it
cy
lv
lt
lu
hu
mt
nl
at
pl
pt
ro
si
sk
fi
se
uk

Total

Lack of bath or 
shower in 
dwelling

Lack of indoor 
flushing toilet 
for sole use of 
household

Dwelling too 
dark

Lacking no 
item

4
1
20
1
1
1
18
1
1
0
1
0
1
22
18
0
5
0
0
1
7
4
42
1
1
1
1
0

4
1
34
1
0
1
15
1
3
0
1
0
1
20
20
1
6
0
0
2
6
3
44
1
3
1
0
1

8
9
10
4
5
4
7
9
8
10
8
8
6
12
11
5
10
4
5
6
9
17
8
10
4
5
7
11

75
79
60
82
86
83
65
80
76
75
80
76
67
58
60
83
73
91
78
86
59
68
43
75
90
89
88
77

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  insecure  accommodation.  Being  without  a  roof  or 
without a house and having to live in emergency shelters or in temporary accommodation is 
of  course  the  most  extreme  form  of  homelessness  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  common  "language"  for  transnational  exchanges  on 
homelessness. This typology was launched in 2005 and is used for different purposes - as a framework 
for debate, for data collection purposes, for policy purposes, monitoring purposes, and in the media. 

EN 

67 

   EN 

 
 
                                                 
proper assessment of this problem. Definitions of homelessness and housing 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  have  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  very  narrow  definitions  can  make  it  difficult  to 
establish a definitive picture of those experiencing homelessness and housing exclusion and 
its causes. The national data available on rough 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  population  and  the  shortage  of  affordable  flats 
following privatisation of the public housing stock. 

EN 

68 

   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 

69 

   EN 

 
 
5.3. 

The  overall  policy  response  —  comprehensive  strategies  and  better 
governance59 

5.3.1.  Comprehensive strategies are key to fighting homelessness and housing exclusion.  

Homelessness and housing exclusion have been identified 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 years by the Social OMC. Transnational studies and 
exchanges  have  helped  to  enhance  mutual  learning  and  encourage  increased  efforts  in  a 
number of countries60. 

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 has helped to push the agenda forward, improve 
coordination  in  policy  design  and  implementation  and  identify  more  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  duration  of  homelessness  (in 
particular the time spent in emergency and temporary accommodation); improving the quality 
of services and accommodation for homeless people; and 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,  initiatives  to  reduce  the 
number of evictions and, secondly, increased efforts to help people leaving 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 emphasis on providing temporary accommodation than 
on actual prevention. There is also a trend towards building other support services around the 
provision  of  temporary  accommodation.  However,  some  Member  States  have  successfully 
moved  beyond 
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).  

temporary/crisis  accommodation 

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 

60 

61 

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).  
For a wealth of information on homelessness and housing exclusion, see the website of FEANTSA (the 
European  Federation  of  National  Organisations  Working  with  the  Homeless)  which  is  supported  by 
PROGRESS (http://www.feantsa.org/code/en/hp.asp). 
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 

70 

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‘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,  homeless  people  often  require  support  beyond  housing.  This  has 
prompted several Member States to introduce socially supported accommodation, combining 
independent living with health and social support62.  

5.3.2. 

Improved governance as an important tool to make strategies more effective 

Policies  to  fight  homelessness  and  housing  exclusion  are  the  responsibility  of  different 
ministries at national level and different levels of government. Typically, national government 
is  responsible  for  planning  and  overall  policy  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  comprehensive  strategy,  where  steering  committees 
have  also  been  established  to  coordinate  the  efforts  of  all  actors  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  participation  is  not  promoted 
enough in some Member States and, in most, the direct involvement of people experiencing 
homelessness and housing exclusion remains quite limited.  

Three  elements  prove  to  be  particularly  useful  in  improving  governance  in  the  area  of 
homelessness  and  housing  exclusion  where  responsibilities  are  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 housing exclusion and instruments  

5.4.1. 

Several factors causing homelessness and housing exclusion – need for a joint policy 
response to tackle them. 

Homelessness  and  housing  exclusion  are  particularly  complex  phenomena.  They  are  caused 
by a number of different factors and in turn affect several socio-economic outcomes, such as 
people’s  health  and  well-being,  social  participation,  employability,  and  consequently 
income63.  Broadly  speaking,  the  causes  of  homelessness  and  housing  exclusion  can  be 

62 

63 

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.  
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 

71 

   EN 

 
                                                 
grouped into three broad categories, even though 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  breakdown,  violent  and  abusive  relationships, 
disabilities and mental illness, substance dependency.  

- Institutional, such as discharge from institutions (foster and state care, prison, armed forces, 
hospitals). Housing exclusion can also be brought about by discrimination and lack of legal 
status, affecting some ethnic minorities and migrants.  

The  changing  profile  of  the  homeless  population  also  points  to  new  categories  of  people 
becoming  more  vulnerable  due  to  the  current  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-quality jobs who find it difficult to find adequate and affordable 
housing,  or  those  in  precarious,  short-term  employment,  who  move  in  and  out  of  the  lower 
end  of  the  labour  market  and  thus  find  it  difficult  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  unemployment  rate  being  on  average  in  the  EU 
more than double that of the overall population, 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 population65, which impacts a person's possibility to own or rent a 
home. 

The second group consists of migrant and mobile workers who find themselves 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 tackled with two sets of measures: 

–  Support for individuals, where social policy instruments such as social assistance benefits 

and quality social services play a key role 

64 

65 

66 

the 

EU 

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.  
See 
34-35 
Youth 
(http://ec.europa.eu/youth/news/doc/new_strategy/youth_report_final.pdf).  See  also  the  PROGRESS 
funded 
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/). 
On the issue of housing and migration, see the results of the mutual learning project "Building inclusion 
–  access 
the  PROGRESS  programme 
(http://buildinginclusion.oberaxe.es/en/home/index).  

in  Europe"  supported  by 

to  housing  and 

"European 

inclusion 

learning 

against 

project 

mutual 

Report 

2009, 

cities 

child 

pp 

EN 

72 

   EN 

 
                                                 
Despite the weight of housing costs in total disposable income, especially 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 benefits have remained almost unchanged since 
the beginning of the decade, with the only exceptions 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) 

1,6

1,4

1,2

1,0

0,8

0,6

0,4

0,2

0,0

EU BGEE ITLTPTSIAT

BECZLVPL

ESLUMT FI

2000

2006

IENLCYELHUSESKDEDKFRUK

Source: EUROSTAT; ESSPROS  

Homeless people often face multiple disadvantages. There is a growing  emphasis  in several 
Member  States  on  developing  integrated  approaches  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 sufficient, 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 
68 

In Estonia, housing costs are taken into account in the calculation of the subsistence benefit. 
See  the  Commission  Recommendation  on  active  inclusion  [2008/867/EC]  published  in  the  Official 
Journal of 18.11.2008 (L. 307/11).  

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73 

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Improving  the  supply  of  adequate  and  affordable  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 economic and social support. A very widespread 
problem  is  that  there  is  excess  demand  for  public  housing  and  relatively  long  waiting  lists. 
Tenant  purchasing  polices  have  reduced  the  existing  stock  of  housing  in  some  cases  (UK), 
while deregulation and priority for private housing 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 the 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,  advantageous  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;  setting  minimum  standard 
requirements  for  the  quality  of  housing  (e.g.  safety,  health,  usefulness,  energy  saving);  and 
setting  minimum  space  standards.  Some  countries  have  introduced  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  several  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 intervention to help marginalised communities should 
be eligible for ERDF support can open the way for 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  include:  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  tax  reliefs  (BE),  and  the  sale  of  houses  under 
market value (NL). 

Housing  and  urban  regeneration  programmes,  together  with  planning  instruments,  can 
directly improve the living standards of local communities and help people to access adequate 
housing. Urban regeneration programmes are a common feature in many cities across the EU, 

69 

See  also  the  website  of  CECODHAS,  the  European  Liaison  Committee  for  Social  Housing 
(http://www.cecodhas.org/). 

EN 

74 

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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 social diversification and relocation of economic activities, 
these  polices  are  particularly  important  for  increasing  the  functional  and  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 exclusion 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  for  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  States  to  enhance  data  collection  and  develop 
corresponding monitoring systems71.  

The 2011 Census represents a unique opportunity to produce invaluable baseline figures in the 
field  of  homelessness.  At  EU  level,  steps  forward  in  the  measurement  of  homelessness  and 
housing  exclusion  have  been  achieved  with  the  adoption  by  Member  States  of  the  common 
indicators  on  housing  costs  and  overcrowding  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 these 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 systematic 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 systematic monitoring or evaluation, and the overall 
understanding of the issue is sketchy (AT, CZ, IT, RO, SK). NGOs have also carried out more 
or  less  coordinated  research  on  monitoring  and  evaluation  in  an  attempt  to  fill  the  current 
knowledge gaps. 

70 

71 
72 

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. 
See the Peer Review programme website: http://www.peer-review-social-inclusion.eu/peer-reviews. 
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 

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Some  projects  have  also  been  launched  in  a  number  of  Member  States  to  establish  formal 
monitoring of the situation of the homeless, and thus a countrywide 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 countrywide 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  Brussels.  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  system  for  monitoring  homelessness,  but  national 
surveys are carried out approximately every five years. Some government agencies have been 
tasked with developing statistics, and to improve knowledge of different 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 ultimate 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  instance,  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 efforts 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 questionnaire 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 homelessness is collated by central government in all 
four jurisdictions. 

EN 

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6. 

EFFECTIVENESS 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  care.  The  crisis  may  impact  the  health  sector 
negatively on both the demand and supply sides. The demand for health and long-term care 
may increase as a result of a deterioration in health determinants (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  expenditure  on  health  also  reporting  lower  health  status  (e.g.  lower 
life expectancy).  

The crisis places budget constraints on all countries, which will be particularly felt in those 
where  the  health  sector  is  already  under-resourced,  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 has worked as an automatic stabiliser and a recovery tool in 
many  countries,  though  not  all.  If,  as  forecast,  this  economic  crisis  is  to  continue  for  some 
time, and given the large government deficits observed, the near future will bring a period of 
budgetary  constraints.  This  may  translate  into  stronger  prioritisation  and  even  budget  cuts 
across the public sector, including the health sector.  

In  addition,  large  socio-economic  gaps  in  health  (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  crisis,  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  policies  to  achieve  these  goals,  Member  States  can 
benefit from pooling their knowledge and exchanging their experiences and information. 

Indeed, the effectiveness and efficiency 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  expenditure  in  public  budgets. 
Furthermore, the ratio of total health expenditure to gross domestic product has increased over 
time  and  continues  to  grow.  Data  show  a  recent  slowdown  in  expenditure  growth,  but 
pressures on health spending are likely to continue given the emerging challenges of ageing, 
technology development and growing expectations. 

A  rising  share  of  resources  devoted  to  healthcare  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  likelihood  of  detecting  and  treating  diseases, 
avoiding mortality, ensuring independent living and reducing health inequalities between and 
within  Member  States).  Good  health  contributes  to  economic  prosperity  through  improving 

EN 

77 

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labour  market  participation  and  productivity  and  increasing  participation  in  other  societal 
activities. High levels of population health and an increase in Healthy Life Years73 are crucial 
in  the  context  of  an  ageing  population,  to  allow  for  longer  working  lives  and  secure  higher 
employment,  productivity  and  competitiveness.  Nonetheless,  increasing  health-related 
expenditure  and  strong  expenditure  pressures  have  also  given  rise  to  general  apprehension, 
increased efficiency concerns, and calls for improving 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 healthy ageing and health workforce related work, 
as well as work by the OECD (including the 2008 Joint EC/OECD conference on improving 
health systems efficiency) and the WHO. It also draws on recent CZ presidency conferences 
on this topic and the 2007 LU seminar on the rational use of resources in the health sector. 

6.1.  Why more effectiveness and efficiency 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) following suit. At the other extreme, RO, LT, CY, 
PL, and LV spend less than 6.5 % of GDP. On average (population-weighted), EU Member 
States spend about 9 % of GDP on health, including both public 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 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  available,  over  the  past  50  years  (Table  A1  in  the  Annex).  Also,  total 
expenditure on health per capita (PPP) has consistently increased over time (Figure 3). 

73 
74 

http://ec.europa.eu/health/ph_information/indicators/lifeyears_en.htm  
The  figures  based  on  time  series  of  health  expenditure  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 

78 

   EN 

 
                                                 
Figure 6.1 

Total expenditure on health as %  of GDP (breakdown between 
private and public expenditure).  2007 or latest available

t

of
% 
s
a
e 
ur
di
n
e
p
x
e
h 
al
e
H

t

P 
D
G

12,0

10,0

8,0

6,0

4,0

2,0

0,0

EU27*

BEBGCZDK DE EE IEEL ES FR ITCYLV LT LUHUMT NLAT PL PTROSK SI FISEUK

Private expenditure as %of GDP

Public expenditure % GDP

Public expenditure as % of total expenditure on health 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

of
% 
e 
r
u
t
di
n
e
p
x
e
c 
bl
u
P

i

h
t
al
e
h
n 
o
e 
r
u
t
di
n
e
p
x
e
al
ot

t

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  expenditure  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 available, over the past 50 years (Table 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

12,0

10,0

8,0

6,0

4,0

2,0

0,0

0
7
9
1

5
7
9
1

0
8
9
1

5
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

EU15 pop weighted average

EU27 pop weighted average

Source: Eurostat, OECD Health data, WHO Health for All databases and EC computations. 

EN 

79 

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Total expenditure on health per capita PPS, 1970-2007

Figure 6.3 

S
P
P
a
t
i
p
a
c
r
e
p

3000

2500

2000

1500

1000

500

0

0
7
9
1

5
7
9
1

0
8
9
1

5
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

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 expenditure still grew faster than GDP throughout 
the 1990s and early 2000s, but has remained a roughly constant share of GDP in recent years.  

The  reason  for  these  results,  looking  at  the  time  series  available  for  individual  countries 
(Figures A3 in the Annex), is that the growth rates for total 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  expenditure  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  which  longer  time  series  are  available,  some 
convergence between GDP growth and health expenditure growth is observed in recent years, 
after very high health expenditure 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 expenditure growth and 
GDP growth have been converging during recent years, with some countries even showing a 
reduction in total expenditure on health as a percentage of GDP.  

Figures A3 also provide interesting information on what can happen to health expenditure and 
its  growth  in  periods  of  economic  downturn.  Looking  at  SE  and  FI  for  example,  the 
downturns in the early 2000s saw health expenditure growth increase and peak compared to 
the  general  trend  of  decreasing  expenditure  growth,  while  the  economic  crisis  of  the  early 
1990s  resulted  in  negative  health  expenditure  growth  rates  in  line  with  the  negative  GDP 
growth rates. In times of economic crisis, therefore, 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 

80 

   EN 

 
 
 
 
 
                                                 
Total expenditure on health as % of GDP, 1997-2007

Figure 6.4 

12,0

11,0

10,0

9,0

8,0

7,0

6,0

5,0

4,0

3,0

BE

BG CZ

DK

DE

EE

IE

EL

ES

FR

IT

CY

LV

LT

LU

HU MT

NL

AT

PL

PT

RO

SI

SK

FI

SE UK

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 percentage of GDP (Figure 5 compared to Figure 2, and 
Figures  A4  and  A5  and  Table  A2  in  the  Annex).  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 the Annex), it can be seen that in some countries 
(DK, FR, LU, AT) the share of public expenditure has been fairly 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  also  explains  the  emphasis  on 
improving effectiveness and efficiency 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 

81 

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Public expenditure on health as a % of GDP, 1970-2007

Figure 6.5 

8,0

7,0

6,0

5,0

4,0

3,0

2,0

1,0

0,0

0
7
9
1

5
7
9
1

0
8
9
1

5
8
9
1

0
9
9
1

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

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  percentage  of  GDP)  have 
similar outcomes and that countries with similar expenditure levels have different outcomes, 
at least in terms of life expectancy.  

Figure 6.6 

82.0

80.0

78.0

76.0

74.0

72.0

h
t
r
i
b

t
a

y
c
n
a
t
c
e
p
x
e

e
f
i
L

70.0

0

Life expectancy at birth vs total expenditure on health per capita PPS, 
2007 or latest value

R2 = 0,6308

MT
MT

CY
CY

IT
IT

ES
ES

FI
FI
EL
EL

UK
UK

SE
SE

FR
FR
DE
DE
IE
IE
BE
BE

NLAT
NLAT

DK
DK

PT
PT

SI
SI

LU
LU

CZ
CZ

SK
SK

HU
HU

PL
PL

EE
EE

BG
BG

RO
RO

LVLT
LVLT

1000

2000

3000

4000

5000

Total expenditure on health per capita PPS

Source: Eurostat, OECD Health data and EC computations 

76 

For a short review, see the Joint Report on Social Protection and Social Inclusion 2007. 

EN 

82 

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It may be noted that countries with lower life expectancy at birth and lower health expenditure 
(as a percentage of GDP or per capita) are also those with higher 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 health, it is as important for them to ensure that what is spent 
and any additional amounts spent make an effective 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 factors: a) factors affecting demand for care, 
such  as  general  health  status  of  the  population  and  thus  the  need  for  care,  population  age 
structure and income levels, plus organisational (e.g. cost-sharing) and cultural (e.g. self-care) 
factors,  and  b)  supply-side  factors  such  as  the  availability  and  distribution  of  services,  the 
physician/nurse  mix,  cultural,  organisational  and  institutional  factors  including  wages  and 
remuneration methods, gate-keeping, market regulation, diffusion of high-cost technology, or 
administrative costs. These are summarised in Figure 6.7.  

Figure 6.7 

Population

size, age-structure

Life
expectancy Morbidity/

Acut 
health status

Use of 
health
care 
services

Health
expenditure

Prices,
costs

Health 
insurance
schemes

Supply/
access

Medical/
technological
progress

Socio-economic
determinants/
healthy behavior/
genetic conditions

General framework
conditions
(policies, rules,
assets, economy)

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 effectiveness 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 Annex), notably a higher proportion of people aged 
65+  and  especially  those  aged  80+.  Between  2008  and  2060  the  EU-27  population  aged  65 
and over is projected to increase 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  Communication  ‘Solidarity  in  Health:  Reducing  health 
inequalities in the EU’ SEC(2009) 1396. 

EN 

83 

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it  new  patterns  of  morbidity  including  multi-morbidity  (multiple  chronic  diseases,  disability 
and dependency) presenting themselves over a long period of time. Evidence shows that the 
need  and  demand  for  health  care  is  strongly  and  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  structure.  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 AHEAD) 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 crucial 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 affected by the cultural and institutional factors of 
each  country,  helping  explaining  the  gaps  in  per  capita  spending  at  older  ages  between  EU 
Member States. 

Figure 6.8. Projected changes in population structure in % for selected years, EU27 

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

2010

2020

2030

2040

2050

2060

0-14

15-64

65-79

80+

Source: Eurostat, EUROPOP2008 (EUROstat POpulation Projections 2008-based) convergence scenario; 2009 
EPC/EC Ageing report 

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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

p
u
o
r
g
e
g
a
h
c
a
e
n

i
s
t
n
e
d
n
o
p
s
e
r
f
o
% 

70

60

50

40

30

20

10

0

Long-standing illness

Severily limited

Bad 

Very bad

15-24

25-34

35-44

45-54

55-64

65-74

75-84

85+

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 negative implications, such as reducing the supply 
of staff and increasing staff wages, thus resulting in higher production costs. Across Europe, 
between 1995 and 2000, the number of physicians 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 predicted 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  approach  retirement  age,  sufficient 
new  and  younger  recruits  are  needed  to  replace  them.  In  addition  to  staff  ageing,  health-
related jobs may not be attractive to new generations, and several countries are faced with the 
migration of their health professionals to richer countries. As increased numbers of staff may 
take  time  to  materialise,  in  view  of  the  duration  of  medical  and  other  training,  we  need  to 
ensure an effective and efficient workforce in the meantime79.  

78 
79 

See http://ec.europa.eu/health/ph_systems/docs/workforce_gp_en.pdf. 
The development of robust human resource strategies to improve recruitment and retention will be one 
of the most important issues for employers in the health and care sectors. 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 

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Table 6.1 The projected costs of ageing: pure demography scenario 

Source: 2009 EPC/EC, Ageing Report 

In addition to potentially increasing demand, ageing reduces the relative size of the working 
population  (Figure  10)  and  thus  poses  a  challenge  to  governments  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 

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Another pressure on healthcare expenditure comes from technological development80. While 
this  can  bring  about  less  intrusive  and  cheaper  treatments  (day  case  instead  of  in-patient 
surgery),  it  contributes  to  raising  expenditure  by  providing  ways  to  cure  or  control  hitherto 
untreatable  diseases  through  new  and  often  expensive  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  access,  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 seems to be lagging behind expectations and 
potential, this area should be given adequate attention in the future.  

In what relates to health professionals, ICT have the potential to reliably free the doctors and 
nurses  from  most  of  the  administrative  burden,  saving  their  valuable  time  for  health-
enhancing activities, something especially 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 significant 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  pharmaceutical  expenditure  accounts  on  average  for  a 
relatively  minor  share  of  national  spending  on  health  (less  than  a  fifth  of  total  health 
expenditure),  it  increased  faster  than  total  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),  although  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  Nordic  countries  and  a  number  of  new  Member  States,  show  a 
growing  share.  There  are  also  wide  differences  in  pharmaceutical  expenditure  per  capita 
(Figure  A11  in  the  Annex)  between  Member  States.  These  reflect  different  practices  in 
relation to market regulation, pricing, reimbursement, coverage, distribution, prescribing and 
dispensing  of  pharmaceuticals,  thus  constituting  a  suitable  area  for  information  and  best 
practice exchange. 

80 

81 

Technology here stands for more than just equipment or ICT as it includes pharmaceuticals and other 
types of medical interventions. 
http://www.oecd.org/document/42/0,3343,en_2649_33929_38311850_1_1_1_1,00.html 

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Figure 6.11. Pharmaceutical expenditure as % of total expenditure on health 

45

40

35

30

25

20

15

10

5

0

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 *

45

40

35

30

25

20

15

10

5

0

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

LU

IE

MT

FR

NL

IT

PL

PT

SK

ES

UK

BE

CZ

DE

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  demand  exceeds  unity  (1.1 
converging to 1 by the end of the projection period). The desire for greater choice of provider 
and care setting, tailor-made treatment, access to a new and wider 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, contributions 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 / unhealthy 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  associated  with  a  higher  incidence  and  prevalence  of 
cardiovascular  and  respiratory  diseases,  diabetes,  etc.  In  addition,  there  continue  to  be 

EN 

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significant outbreaks of communicable diseases such as TB, and the prevalence of HIV/AIDS 
is  of  strong  concern.  These  result  in  an  unnecessary  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

S
P
P
a
t
i
p
a
c
r
e
p
h
t
l
a
e
h
n
o
e
r
u
t
i
d
n
e
p
x
e

l

a
t
o
T

4500

4000

3500

3000

2500

2000

1500

1000

500

0

0

R2=0,8853

LU

FR

NLAT

DKDE
BE
SE
UK

IE

EL

IT
ES

FI

PT

CZ

CY

HU
SK

EE

LT
PL

LV

BG
ROSI

10000

20000

30000

40000

50000

60000

70000

80000

GDP per capita PPS

Source: Eurostat, OECD Health data and EC computations 

Large and widening health inequalities 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 expectancy at birth between 
the lowest and highest socio-economic groups) indicate that not everyone has benefited in the 
same way from the increase in health expenditure and the greater availability of medical care 
as well as the economic progress 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, geographical disparities in provision, waiting times, 
lack  of  information,  discrimination,  language  barriers,  health  literacy  and  socio-cultural 
expectations in relation to life and care use. Premature and avoidable 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.  Reducing  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, public health prevention and a rethinking of 
priorities in this sector. 

EN 

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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 may 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 changes in mortality to periods 
of economic recession are scarce and somewhat contradictory. Some perhaps counterintuitive 
findings come from the US and Europe, where recession has been accompanied by falling all-
causes  mortality  rates,  although  an  increase  in  suicide  rates  is  generally  observed  (Brenner, 
2007). Those findings have been observed for recent, 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 morbidity, and especially mental ill health, when 
searching for the health consequences of an economic crisis. In addition, while rapid and deep 
social  and  economic  changes  will  have  consequences  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 resilience and robustness of the health sector, as well as 
policy responses in the fields of social 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 birth for men (Figure 13) remained 
stable or improved slightly among the adult population while infant mortality 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  social  safety  nets  and  a  health  care  system 
offering  universal  coverage  provided  comprehensive  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 crisis in the early-1990s or mid-1990s during the 
transition  to  democracy  and  to  a  market  economy:  high  unemployment  and  inflation  and  a 
drop  in  GDP  were  observed,  albeit  to  different  extents.  It  can  be  observed  that  the  rise  in 
unemployment  and  the  drop  in  GDP  during  that  transition  period  could  be  associated  with 
increased mortality and reduced life expectancy, in particular for men. For some countries life 
expectancy  did not increase during transition, while for others it actually  decreased  and has 
taken some time to return to pre-transition levels.  

EN 

90 

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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 

80

78

76

74

72

70

68

66

64

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

76

74

72

70

68

66

64

62

60

FI 

SE 

BG 

CZ 

EE 

LV 

LT 

HU 

PL 

RO 

SK 

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

Source: Eurostat 

Fluctuations in the unemployment rate are more closely associated with short-term changes 
in  health  than  any  other  economic  indicator.  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  the  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 significant risk factor for morbidity. In addition 
to increasing alcohol or substance abuse and malnutrition, unemployment (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 protection 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  (Sverke  et  al.,  2002)  has  revealed  a  significant 
negative  correlation  between  job  insecurity  and  poorer  mental  health.  The  relationship  has 
been confirmed by longitudinal studies (Ferrie et al., 2003) showing that job insecurity should 
be treated as a cause of worsening mental health. 

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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  protection  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  care  may  fall  as  a  result  of  the  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 currency 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  payments  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 decline, if public services are not 
adequately  equipped  to  cope.  This  problem  will  affect  all  countries  where  publicly  funded 
services are under pressure.  

Some  governments  choose  to  increase  cost-sharing.  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 the 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  the  costs  of  care  for  patients  through  generic  substitution  or 
public subsidies. 

Where  recession  is  accompanied  by  inflation  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 effectiveness and efficiency gains 
to  be  made  within  the  sector  and  in  addressing  the  social  determinants  of  health.  Different 
financing  and  organisational  arrangements  may  be  more  or  less  able  to  control  such 
expenditure pressures (2007 Joint 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 prevention and rehabilitation versus treatment). The 
search for ways to raise effectiveness and efficiency is therefore ongoing.  

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6.2. 

Improving effectiveness and efficiency in the health sector: 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 efficiency and what they entail.  

6.2.1.  Encouraging the use of primary care  

Encouraging  the  use  of  primary  care  instead  of  direct  use  of  specialist  care  while 
strengthening referral systems from primary to other 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 compulsory referral system with a gate-keeping role 
for primary care physicians and via financial incentives (i.e. higher reimbursement if a patient 
follows a referral system from primary to other types of care). 

In  the  last  decade,  policy  makers  in  many  Member  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  others  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 and using specialist and hospital 
care directly through overuse or unnecessary use of emergency departments. In more recent 
times, the growing focus on addressing observed healthcare delivery deficiencies (improving 
access  and  quality)  and  improving  value  for  money  in  the  health  sector  (efficiency)  has 
shifted attention to primary care 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 the 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. Stronger primary care aims 
to avoid patients organising or having to organise their care path through the system, leading 
to  disparities  in  access,  lack  of  coordination  and  continuity  of  care  (quality),  duplication  of 
procedures and use of unnecessary and more expensive diagnostic and curative hospital care, 
resulting in health and financial costs for both the patient and the system. A focus on primary 
care will also improve access to health promotion and disease prevention to avoid or postpone 
the onset of disease and ensure its early diagnosis, thus bringing about savings in the sector.  

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Figure 6.14. General practitioners per 100 000 inhabitants 

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

1997
168.9

48.3
61.5
109.6
56.3

1998
170.8

48.3
63.5
108.0
64.5

1999
173.7

49.0
64.1
106.4
80.8

2000
175.1

51.2 (b)
71.9
106.6
88.2

2001
177.2

52.5
72.1
106.2
85.4

2002
176.2
67.5
52.2
72.2
105.1
92.7

2003
176.4
68.6
51.4
71.5
104.2
95.5

27.8

27.9

29.8

27.7

26.5

28.5

31.9

2004
175.9
69.1
51.3
75.3
102.4
100.2
62.2
33.9

2005
173.3
67.8
51.2
74.6
97.4
99.8
68.3
35.5

2006
170.3
66.8

74.4
99.2

69.9

161.6

161.3

159.6

16.0
7.5
71.2
65.3

44.7
131.0

43.0

16.7
8.5
33.2
49.8

20.2
8.3
72.5
66.1

45.0
134.4

43.4

20.3
36.5
34.5
51.4

33.4
15.6
73.9
65.9

45.5
132.8

43.7

19.8
41.5
36.3
52.0

161.1
37.4
40.6
21.3
74.3
66.0

45.5
134.6

44.2

19.7
43.2
37.7
52.8
71.1

162.0

162.8

163.8

164.5

164.6

164.1

41.0
27.9
77.2
66.0

45.5
137.4

44.5

19.4
44.0
38.7
54.6
71.8

43.8
36.0
75.2
66.1

45.6
139.9

44.7

19.0
43.6
39.7
56.0
72.5

45.0
43.0
74.7
66.1

45.6
141.1
11.9
44.9

19.2
43.2
40.6
57.0
74.8

Source: Eurostat 

52.9
48.2
76.6
65.6

46.1
143.3
13.3
45.6

26.7
43.2

57.7
76.9

54.7
50.5

65.4

46.4
146.0
14.3

65.8
26.2
36.9

58.9
79.0

55.7
52.6

65.2

150.5
15.2

80.9
26.0
36.3

60.2

2007
170.9

105.3

54.7

77.7

153.3

However, reforms to improve health system efficiency (as well as accessibility and quality of 
care)  through  greater  use  of  primary  care  imply  a  change  in  its  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 encouraging group rather than individual practices, and 
sometimes a common budget, so that primary care 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 appears to bring satisfaction to both patients 
and primary care providers. For patients, the expansion of primary care services, especially if 
this  translates  into  a  better  geographic  distribution  of  services,  may  mean  easier  access  to  a 
wider range of services provided in a more personal 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 more 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 incentives for primary care providers, 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 

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attentive to the needs of individual patients and ensuring they get access to appropriate care 
but at less cost (EC/OECD conference, 2008). By ensuring a coherent care path, coordination 
can  be  of  great  importance  to  the  most  disadvantaged  groups,  who  often  lack  continuous 
follow-up in terms of preventive or early care and end up relying on late or emergency care 
instead. Care coordination is particularly pertinent in the context of ageing and the attendant 
multi-morbidity and chronic diseases, which result in greater use of many different types of 
both medical and support care at the same time. Care coordination is thus about ensuring that 
patients access care that is appropriate 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  settings  and  budgets,  specialisation  of  medical  knowledge,  lack 
of  communication  and  mutual  professional  esteem,  and  even  rivalry  between  professionals 
have led to fragmentation of care (between primary 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. Further, there can be high levels 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 health status and their income) and the system 
(e.g. increased costs/expenditure). Good coordination of care can reduce the need for hospital 
stays, the unnecessary use of emergency care and the duplication of procedures (in particular 
expensive and invasive diagnostic 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 track of patients once they move 
to hospital or institutional settings due to lack of referral back to the family doctor.  

Policies conducive to coordination include: a) improved use of ICT as a key tool to link the 
healthcare  "silos"  and  allow  information  to  follow  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,  communication  with  patients  and  networking;  d) 
implementation  of  targeted  disease  programmes;  and  e)  addressing  administrative  barriers 
(e.g. through pooling resources from health and social sectors and addressing lack of mutual 
esteem  and  recognition  between  different  medical  professions).  Communication  across  the 
various parts of the health sector is fundamental to avoid fragmentation 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  areas.  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  shorten  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  case  surgery  is  an  appealing  solution  to  reduce 

EN 

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overall costs in the health sector 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  across  EU  countries  in  terms  of  hospital  activity,  measured  by 
hospital  inpatient  average  length  of  stay  (ALOS),  can  be  observed.  In  addition  to  data 
comparability  issues,  variations  can  be  due  to  various  factors  associated  with  quality  and 
financial  considerations.  They  include  patient  registration  practices  as  hospital  cases, 
historical  medical  practices,  absence  of  clinical  guidelines,  lack  of  referral  back  to  primary 
care, lack of alternative follow-up care at home, lack of long-term 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 overcapacity or remuneration/budgetary systems that 
make  in-patient  procedures  more  financially  attractive  to  providers.  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 stay (in days), all causes excluding births 

BE
BG

CZ

DK

DE

EE

IE

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE 

UK

2000
7.7

6.3

10.1

6.4

8.8

6.0

6.4

7.5

2001
7.5

6.2

9.8

6.4

7.7

6.0

6.5

10.6

7.4

9.9

6.8

10.8

9.5

6.7

10.6

2002
7.4

10.3

6.1

9.7

6.4

7.7

6.1

6.4

10.3

7.5

8.0

9.0

12.9

6.7

10.0

2003
7.7

10.2

5.9

6.4

7.7

6.0

7.6

6.0

10.0

7.2

7.6

10.0

7.2

8.8

12.7

6.5

9.3

2004
7.6

10.2

6.4

7.2

5.9

7.6

6.3

2005
7.5
8.3

10.9

6.5

7.1

5.9

7.6

6.0

9.6

10.1

10.1

7.3

8.1

5.4

7.2

9.5

6.8

7.9

8.7

12.5

6.4

7.3

8.0

5.4

6.9

9.0

8.4

6.7

7.9

8.4

12.5

6.4

8.7

2006
7.4
7.5

10.7

5.4

10.2

6.3

7.0

5.8

7.7

5.9

10.0

7.4

7.9

6.7

8.9

8.1

7.7

8.3

12.7

6.4

8.8

2007
7.3
7.2

10.6

5.3

10.2

6.2

5.8

6.2

9.9

7.3

7.9

4.8

6.4

9.0

8.0

7.8

7.7

8.1

2008

8.8

4.9

Source: Eurostat. Please note that caution is needed in interpreting the table results as it includes all causes 
(including psychiatric care) rather than just acute care, fact that can increase the figures 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 concentration of tasks between 
hospitals  in  a  defined  health  region.  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  may  go  as  far  as  having  a  very  few  centres  of 
excellence  serving  the  entire  population.  Division  and  concentration  of  tasks  does  require 
good  coordination  and  communication  structures  between  primary  and  secondary  care  and 
between the various hospitals. 

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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 health care, in GDP terms as well (2008 EC/OECD 
conference).  The  public  sector  is  the  primary  source  of  financing  for  pharmaceuticals, 
accounting on average for 60 % of total pharmaceutical expenditure in OECD countries, while 
another large part comes directly from households. Moreover, there are also large differences 
in  pharmaceutical  expenditure  per  capita  (Figure  A10  in  the  Annex),  which  may  reflect 
different  practices  in  market  regulation,  pricing,  reimbursement,  coverage,  distribution, 
prescribing  and  dispensing  of  pharmaceuticals,  and  different  objectives  (affordable  access, 
cost-containment,  encouraging  of  industry  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)  promoting  future  innovation  (long-run  perspective), 
which  involves  high  costs  for  the  development  of  new  drugs.  Innovation  creates  new  care 
opportunities, some of which may replace old, more invasive and 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 price regulation to set maximum prices for patented drugs and/or 
reference pricing (the maximum price reimbursed by public insurance for non-patented drugs, 
typically  an  average  of  the  prices  of  drugs  in  each  therapeutic  group  with  perhaps  a  certain 
percentage  margin  below  that  average).  The  patient  then  pays  the  difference  in  price.  Price 
regulation  can  induce  the  desired  patient  behaviour  and  control  expenditure,  but  some 
drawbacks need to be taken into account. Indeed, producers can use the reference price for all 
drugs or slightly adjust the definitions of drugs to obtain a higher 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  manufacturers  to  launch  products  first  in  countries  with  no 
regulation  at  the  entry  point  in  order  to  set  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 (higher reimbursement for 
generic  drugs).  Prescribing  guidelines  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 opportunities for efficiency gains in the distribution chain 
(looking  at  existing  practices  in  reimbursing  pharmacies,  the  number  and  location  of 

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pharmacies, the number of pharmacists, opening hours, etc.) and see if these encourage higher 
prices and higher sales.  

Yet  another  is  to  use  economic  evaluation  and  thus  information  on  the  relative  cost-
effectiveness  and  cost-utility  of  products  in  the  definition  of  prices  and  reimbursement 
schemes  (and  cost-sharing)  for  pharmaceuticals,  while  ensuring  that  the  rewards  for 
innovation  are  consistent  with  the  value  of  the  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 established, as pharmaceutical firms may be more 
willing to negotiate an overall budget for a large set of medicines than to negotiate the unit 
price  of  each  medicine.  They  can  also  explore  the  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  effect  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 health 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 regulation 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  Communication  Technologies  (ICTs)  /  e-Health82 

solutions but also more economic assessment of technology 

Technological  development  can  bring  about  less  intrusive  and  cheaper  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  identified  as  an  obstacle  to  healthcare  access  and 
associated  with  quality  deficits.  The  resulting  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  sufficiently  employing  ICTs  or  are  doing  so  without 
sufficient  concern  for  interoperability,  thus  fragmenting  health  information  flows.  This 
reduces the ability to systematically 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. 

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98 

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ICT  and  e-Health  solutions  have  the  potential  to  improve  the  collection  and  storage  of 
multiple  sources  of  data  (electronic  records,  registries,  and  administrative  data)  and  the 
linkages  between  them  as  well  as  enhance  information  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  control  costs.  E-prescribing  can 
support  compliance  with  protocols,  avoid  interaction  between  drugs  or  confusion  between 
patients,  dosages  or  times  of  application,  and  support  generic  prescription  (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 administrative burden on staff and to free the valuable 
time  of  health  professionals  for  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 reimbursement 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 systems 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  professionals  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 the (cross-border) interoperability of e-Health 
systems. 

6.2.6.  Health Technology Assessment 

Technological development can increase expenditure 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 new technology at an affordable price has led to 
calls  for  greater  use  of  economic  assessment  and  evaluation  of  technology  (Health 
Technology  Assessment  —  HTA83),  including  a  cost-effective  and  cost-utility  analysis  to 
decide  if  a  certain  care  intervention  or  drug  should  be  included  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 patients, the public purse, service providers and innovators. HTA is 
thus being more and more debated but there is a wide variation across 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 summarises information about the medical, social, economic and ethical 
issues  related  to  the  use  of  a  health  technology  in  a  systematic,  transparent,  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. 

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yield  different  results  that  may  not  be  totally  generalisable  or  transferable.  It  is  a 
multidisciplinary  field  and  requires  skilled  scientists  and  the  creation  of  committees.  In 
addition, there may be societal and ethical issues involved. Building on a number of previous 
actions  and  projects,  the  Commission  and  Member  States  are  currently  working  on  a  joint 
initiative aimed at increasing cooperation, sharing 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  sustainability,  user  charges  have 
two roles: 1) to raise revenues for the sector and 2) send signals to patients 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 small 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 counteracting moral hazard). In most cases the revenue is not large, 
and in some cases is outweighed by the collection costs. Hence, user charges have not been 
very  successful  in  raising  additional  financing,  and  mostly  function  to  encourage  the  better 
use  of  services  as  in  2),  although  their  impact  is  limited  when  complementary  insurance  is 
available. 

Charges  have  been  accompanied  by  intense  political  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 vulnerable and less well-off. Consequently, a practice 
of small charges combined with a number of payment exemptions (based on age, income and 
chronic disease) has developed. Existing evidence does indeed suggest that charging can and 
does reduce utilisation84. While this may not have major health consequences for most of the 
population, it has important negative consequences for the health of those with low incomes 
and  poor  health  (who  need  health  services  more  often).  Hence,  if  not  properly  designed, 
charges  can  have  financial  and  health  consequences  for  some  groups  of  the  population  and 
thus contribute to the socio-economic health inequalities 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 maximising efficiency gains.  

One  suggestion  is  that  authorities  should  define  a  minimum  care  package  of  a  sufficiently 
high quality so that all citizens are willing to contribute to its financing, thus ensuring broad, 
publicly  funded  provision.  This  package  will  be  fully  covered  by  public  financing  and 
determined,  where  possible,  using  cost-effectiveness  criteria.  Building  on  this  initial  high-
quality package, charges (co-payments, co-insurance and deductibles) will be introduced to an 
increasing  extent  to  encourage  appropriate  behaviour  (e.g.  generics  rather  than  branded 
products, primary care rather than direct visits to specialists and hospitals, preventive rather 

84 

"Achieving better value for money in health care", OECD 2009.  

EN 

100 

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than  curative  care).  Some  charges  should  not  be  covered  by  complementary  insurance  to 
ensure that they encourage desirable behaviour. At the same time 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 users: patient choice and involvement 

on 

also 

seen 

have 

years 

emphasis 

increased 

Recent 
patient 
an 
empowerment/involvement/choice  and  satisfaction.  When  introducing  choice,  one  needs  to 
think  about  its  design  (at  which  stage,  how  choice  is  allowed)  and  its  objective.  Patients’ 
ability to choose providers can lead to increased patient satisfaction, and fits in with the goal 
of improved well-being and the notion 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  restricted  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 following referral by a primary care physician.  

Choice  is  nevertheless  constrained  by  the  level  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  number  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  countries  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), capitation (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 services provided). Each system provides different 
incentives  for  physicians.  A  fee-for-service  system  may  be  associated  with  supply-induced 
demand  and  the  lack  of  care  coordination,  especially  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 Member 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  and  disease  prevention  services.  In  others,  the  fee-for-service 
system is regulated and a list 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 attempt to establish a comparable structure of hospital costs. In 
addition,  there  is  greater  use  of  prospective  budgeting  for  hospitals  (payments  fixed  in 
advance of the provision of services), often based on potential patient case-mix and a set of 
healthcare need criteria. Some countries use global prospective budgets. 

Some  Member  States  are  supplementing  the  above  mechanisms  with  the  measurement  of 
hospital  efficiency,  hospital  benchmarking  and  ranking  (measuring  performance  of 
organisations according to specified standards and comparing them using the results) on the 

EN 

101 

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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 performance measurement 
and  benchmarking  have  induced  changes  in  hospital  care  delivery  to  achieve  cost  savings. 
The overall results appear to be positive, especially if the 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 benchmarking have to be adjusted 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 technology assessment of their new drugs. 

6.2.7.4.  Non-financial incentives for physicians: training and motivation 

The  development  of  robust  human  resource  strategies  to  improve  recruitment  and  retention 
will be one of the most important issues for policy makers in the health sector. 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 providing opportunities to 
work  flexibly,  and  schemes  to  attract  and  retrain  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 insurers/purchasers and 
providers about health status and the care needed 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  care  is  financed  and 
delivered,  thus  raising  issues  of  possible  excess  demand  and  consumption.  There  are  also 
practical and regulatory constraints on the entry and exit of providers such as restrictions on 
access to training for staff, economies of scale and scope in the provision of many services, 
and the fact that, from society’s point of view, providers and purchasers cannot just fail and 
vanish  from  the  market  leaving  a  gap  in  the  provision  of  needed,  life-saving  services.  In 
addition,  health-related  education  and  training  have  the  characteristics  of  public  goods  and 
there  is  substantial  R&D  in  the  sector.  Moreover,  the  objectives  associated  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  healthcare  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 complex mechanisms that need to be in place to 
obtain the required information to attain the other objectives associated with health care. 

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On  the  other  hand,  policy  makers  and  researchers  in  recent  times  have  expressed  their 
concerns that sole reliance on non-market mechanisms may also be undesirable, as it can give 
rise  to  opportunistic  behaviour  and  inefficiency.  Hence,  several  countries  are  looking  at  the 
scope for promoting more rational use of resources by using market-type mechanisms such as 
increased competition, notably in certain sub-markets, 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  benefit  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  sometimes  regulations  for  high-risk  patients,  to 
avoid cream-skimming and ensure a level playing field. 

The second is competition between providers, or competition for collective health services, a 
more common mechanism,  whereby  a  purchaser concludes a block contract with a provider 
for  the  delivery  of  a  set  of  specified  services.  The  separation  between  purchasers  and 
providers  in  various  national  health  systems  in  the  EU  is  intended  to  create  strategic 
reductions. 
purchasers  who  would  choose  between  providers 
Negotiation/bargaining  and  contracting  have  often  been  based  on  benchmarking.  Research 
indicates that contracting has delegated responsibility in previously 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  purchasers  and  national  health 
strategies. It has induced changes in provision patterns (from in-patient to out-patient care and 
the adoption of cost-effective interventions) and cost reductions have been observed.  

to  achieve  cost 

In  conclusion,  there  may  be  room  for  greater  competition  among  insurers/purchasers  and 
providers and greater use of market-type mechanisms in sub-markets or for certain procedures 
that  may  encourage  greater  cost  efficiency  in  the  health  sector.  However,  one  must  not 
underestimate  the  regulatory  challenge  and  the  considerable  costs  of  the  administrative 
machinery  needed  to  create  and  sustain  competition  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 status, to allow for risk-adjustment mechanisms, as well as in 
terms  of  care  costs,  prices,  and  market  structure.  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  quality  of  care  for  those  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-competition 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 contract process used, the duration 
of  the  contract,  the  population  covered,  and  the  definition  of  price  and  quality  criteria.  In 
some sub-markets this competition may not be realistic if there are economies of scope and 

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scale and few providers. Moreover, if a purchaser wishes to ensure integrated care then it may 
wish to contract with a larger provider offering a wider range of services, therefore strongly 
limiting  its  choice.  Contracting  requires  information  and  data  collection  on  many  variables 
such as unit costs, prices, length of stay, etc. Imperfect information may have negative effects 
on unmeasured dimensions of the care provided. Finally, the contract type (global budgets vs. 
case-based DRG payments) provides different incentives to providers.  

EU  Member  States  differ  in  their  institutional  and  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 engaged in these policies.  

6.2.8.  Encouraging effective health promotion and disease prevention 

As  highlighted,  if  people  are  healthier  for  longer  the  pressure  on  expenditure  and  public 
expenditure  in  particular  is  lower.  A  range  of  health  promotion  and  disease  prevention 
activities (e.g. vaccination, screening for certain types of cancer) are considered effective and 
cost-effective in improving population health outcomes by avoiding disease and mortality and 
through  early  diagnosis  and  treatment  (often  less  costly)  and  thus  higher  survival  chances. 
However, expenditure on health promotion and disease 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 prevention, some countries have introduced direct 
personal  financial  incentives  for  people  to  prevent  illness  and  promote  their  health.  These 
include  financial  disincentives  to  smoke  or  drink  alcohol  (especially  spirits)  through  high 
taxation  of  these  products.  Other  mechanisms  include  age  regulation  for  the  sale  of  alcohol 
and smoking bans in public places. These are often coupled with publicly reimbursed support 
schemes  for  quitting  smoking.  Some  countries  are  considering  higher  taxes  on  soft  drinks. 
Others  prescribe  physical  exercise  as  a  treatment  or  give  financial  incentives  to  do  so 
(vouchers).  Financial  incentives  are  also  given  to  pregnant  women  to  eat  a  healthy  diet  and 
follow  pre-natal  care  or  for  patients  to  comply  with  their  medication.  As  mentioned  above, 
some  countries  provide  additional  fee-for-service  remuneration  to  physicians  to  perform 
health promotion and disease prevention activities. In addition, many national authorities have 
implemented  projects  to  improve  healthy  eating  and  exercise  in  schools.  More  research  is 
needed to understand the cost-effectiveness of several of these schemes.  

Figure 6.16. Public expenditure on health promotion and disease prevention as a share 
of total current expenditure on health 

Belgium 
Bulgaria 
CzechRepublic 
Denmark 
Germany 
Estonia 
Ireland 
Greece 
Spain 

: 

2003 
1,34 
3,5 
1,75 
2,44 
2,84 
2,16 
2,5 

2004 
1,72 
3,6 
1,75 
2,51 
2,86 
1,51 

2005 
3,62 
2,84 
1,46 
2,29 
2,86 
1,83 

2006 
3,53 
3,13 
1,84 
2,32 
2,95 
1,94 

: 
: 

: 
: 

: 
: 

2,2 

2,21 

2,21 

2,25 

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France 
Italy 
Cyprus 
Latvia 
Lithuania 
Luxembourg 
Hungary 
Malta 
Netherlands 
Austria 
Poland 
Portugal 
Romania 
Slovenia 
Slovakia 
Finland 
Sweden 
UnitedKingdom 

: 
: 

: 

: 

: 

1,45 
0,7 
0,5 

0,72 
3,32 

2,73 
1,66 
3,24 
1,3 
5,28 
2,86 
1,7 
3,05 
2,46 

: 

1,41 
0,6 
0,44 

1,78 
0,75 
2,97 

2,43 
1,78 
1,54 
1,22 
6,92 
2,94 
1,9 
3,11 
2,4 

: 

: 

: 

1,47 
0,6 
0,46 
0,24 
1,74 
1,09 
2,89 

2,37 
1,67 
1,78 
1,18 
6,63 
2,83 
1,3 
3,29 
1,56 

1,58 
0,6 
0,51 

1,26 

2,76 

2,54 
1,66 
1,79 
1,16 
5,9 
2,8 
1,9 
3,24 
2,66 

: 

: 

: 

: 

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 through increased effectiveness and efficiency. This may imply 
restructuring of the way health care is organised and delivered. A number of paths have been 
suggested, including a restructuring of primary and secondary care, greater care coordination, 
more intensive and interoperable  use of ICT and e-Health solutions, a proper assessment of 
current pharmaceutical policies, greater use of health technology assessment, a re-engineering 
of  remuneration  systems  and  financial  incentives  for  both  providers  and  users  of  care  more 
generally,  the  development  of  non-financial  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  efficiency  should  aim  to  promote  health,  prevent 
morbidity  and  ensure  access  for  all  to  high-quality  care  that  is  sustainable.  Short-term 
strategies must be well-linked to long-term strategies. 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,  income,  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  effectiveness  and  efficiency,  more  information  and 
assessment is needed regarding many of these tools. 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 information. In this context, there is 
a  need  to  investigate  the  various  aspects  of  the  functioning  of  national  health  systems.  The 

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Commission will work with Member States to identify areas where a potential for improving 
health performance exists and support the development of national strategies to reduce health 
inequalities. 

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7. 

LONG-TERM  IMPLICATIONS  OF  THE  CRISIS  FOR  THE  SUSTAINABILITY  AND 
ADEQUACY OF PENSIONS  

Over  the  last  15  years  consecutive  waves  of  Member  State  reforms  in  response  to  the 
challenge  of  ageing  have  markedly  altered  pension  systems  and  pension  scheme  designs 
across the Union. For almost 10 of these years, the EU has sought to underpin this process by 
providing  a  framework  for  policy  learning  with  common  objectives  conducive  to  the 
planning, implementation and assessment of such reforms through the Lisbon process and the 
Social OMC. With the introduction of the euro, the fiscal framework in the EU – the Stability 
and Growth Pact – has been strengthened, 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  downturn,  Member  States  also  have  to  revisit 
achievements and re-assess core responses in the light of the short- and longer-term impacts 
on the various elements in their pension systems.  

This  chapter  presents  a  first  explorative  analysis  of  the  outcome  of  reforms,  the  immediate 
impacts of the crisis, and the longer-term implications 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  the  Social  Protection  and  the  Economic  Policy 
Committees in 2010.  

Key findings and messages can be summarised as follows:  

A first examination of crisis impacts shows that while budgetary restrictions 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 rapidly approaching ageing challenge into sharper 
focus and put the adequacy/sustainability balance sought over a decade of reforms under new 
pressure.  

Strong  trends  in  reforms  towards  a  greater  role  for  pre-funding  and  defined-contribution 
formulas  will  increase  sensitivities  to  volatilities  in  financial  markets,  including  the  present 
downturn.  The  wide  variation  in  the  losses  and  capacities  of  funded  schemes  to  absorb  the 
shock demonstrates that differences in design, regulation and investment strategies matter. To 
achieve  longer-term  adequacy  and  sustainability,  lessons  need  to  be  learned  and  greater 
security for pension savers achieved. 

The  closer  links  introduced  between  benefits  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. 

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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  ECFIN)  and  Economic  Policy  Committee  (Ageing 
Working Group) 2009 Ageing Report from the spring 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  costs)  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 eventually 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 reforms 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 among the population aged 15-64 from 65.5% in 2007 
to  69.9%  in  2060,85  public  pension  expenditure  is  forecast  to  reach  only  12.5%  of  GDP  in 
2060.86 

In response to the longevity challenge, we see that due to many pension reforms, the relative 
level of annual pensions will decrease over the next forty years, given a forty year career.87 
That  said,  in  many  cases  policymakers  have  tightened  eligibility  rules  for  full  pensions  and 
extended pensionable ages to encourage longer working lives as people live longer. There has 
also been a move toward greater pre-funding of pensions as a method for moving some of the 
payment  burden  forward  to  current  working  generations,  but  also  as  a  method  of  reaping 
eventual gains from growing financial markets, 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)  encouraging/enabling  more  people  to  work  more  and 
longer, (2) greater pre-funding of pensions, and (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 

86 
87 

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. 
Ageing Report 2009 
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  currently  much  lower  than  40  years  in  many  EU 
countries. 

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significant  improvement  has  been  seen  in  increasing  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  group  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 improvement in the employment rate for older 
workers has been markedly better than that for both people of prime working age (25-54) and 
youth  (15-24).  In  addition,  most  Member  States  experienced  a  higher  increase  in  the 
employment rate for older women than 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) 

eu27

eu27 (male)

eu27 (female)

eu15

eu15 (male)

eu15 (female)

60

55

50

45

40

35

30

25

20

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Source: Eurostat 

Recent improvements in the employment rates of older workers should not hide the fact that 
the  employment  rates  of  older  men  have  declined  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  contrast,  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  and  boosting  of  the  trend  towards  increasing 
female employment. 

88 

89 

More detailed analysis can be found in the chapter 2 "Active ageing and labour market trends for older 
workers", Employment in Europe 2007 Report. 
Ibidem 

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Figure 7.2 Employment rates by gender in the EU-15, 1970 and 2008 

l

n
o
i
t
a
u
p
o
p
p
u
o
r
g
e
g
a
f
o
%

100

90

80

70

60

50

40

30

20

10

0

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+

Men 1970

Men 2008

Women 1970

Women 2008

80%

Source: OECD Stat base 

General policies fostering economic growth and jobs together with societal changes (such as 
structural changes in the skill, gender and sectoral 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  underpinned  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 examining 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 supplementing to pensions for people who choose to defer 
taking them.  

Increasing  the  link  between  actual  contributions  (number  of  contributions,  period  they  are 
made over and their level) and eventual pension income. Due to their nature, funded pensions 
—  both  defined-benefit  (DB)  and  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  public  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  pension  reforms  (e.g.  SE,  IT,  PL,  DE,  FI,  FR,  AT)  have  already 
introduced  such  mechanisms.  While  these  measures  may  have  little  impact  on  retirement 
decisions, they can (if allowed to operate as intended) reduce pension benefits in relation to 
earnings and contribute to better alignment of expenditures with revenue. 
Outlawing and reducing age discrimination in work places and labour markets at both EU and 
national levels. 

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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  challenge.  However,  it  is  important  to  note  that  pay-as-you-go 
(PAYG) is and will remain the most important element in overall pension provision for most 
European citizens. 

In  macro-economic  terms,  pre-funding  is  about  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  various  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  schemes  (on  a  compulsory,  quasi-compulsory  or 
voluntary basis) 
setting  up  a  national  reserve  fund  (more  or  less  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. Whether 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  better  features  that  used  to  distinguish  public  from 
private and PAYG from funding schemes. Through transformative NDC designs (e.g. SE, IT, PL) or 
simply  by  significantly  strengthening  the  links  between  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  private,  fully  funded  schemes.  The  aim  is  to  provide 
similarly strong and transparent incentives 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 PAYG schemes, expanding existing or introducing 
new occupational and voluntary schemes, or — most importantly — shifting part of former 
PAYG contributions to mandatory funded 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-contribution  (DC)  schemes  and  the  vast  majority  form 
part  of  the  compulsory  social  security  system  (BG,  EE,  LT,  LV,  HU,  PL,  SE,  SK,  RO).  In 
some  countries,  however,  reforms  currently  under  way  (e.g.  DK  and  most  recently  the  UK) 

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involve  a  national  quasi-compulsory  occupational  pension  scheme  set  up  with  employer 
involvement. It is important to note that occupational pensions are not  compulsory  in  many 
Member  States,  which  raises  concerns  of  coverage  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  rates  of  occupational  and  statutory  funded  pensions  in 
2006 and 2046 in selected Member States 

2046

2006

70%

60%

50%

40%

30%

20%

10%

0%

IT RO BG BE DE HU SE EE

LT UK

PL SK

IE

LV DK NL

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 

1,2

1,0

0,8

0,6

0,4

0,2

0,0

2060

2007

PT

ES

RO

BG

HU

LT

PL

SK

IE

EE

SE

LV

DK

NL

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  comparing  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). 

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Similarly,  a  number  of  Member  States  have  set  up  reserve  funds  more  or  less  explicitly 
intended to help smooth the impact of the demographic 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 reserve 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  States  the  funds  may  not  be  purely  pension 
funds but social protection or demographic 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 have 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 undergoing 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  story  of  how  pension  systems  are  changing  as  a 
result of reforms is one of increased 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 period. Moreover, the drop in the value of annual pension will be 
reduced as more people will be getting pensions in the future (e.g. more women).  

Given  the  projected  reduction  in  working  age  population,  the  same  level  of  contributions 
cannot  continue  to  fund  these  increased  pensions,  and  to  avoid  constant  increases  Member 
States have sought other ways to rebalance their systems. Reducing the replacement rates at a 
given  age  of  retirement  is  one  way  to  return  to  a  more  sustainable  balance  between 
contributions  and  total  pension  paid  over  (longer  average)  retirements.  Another  way  is  to 
continue to pay the same annual pension but to increase the age at which it is first payable in 
line with longevity increases. Most countries combine these approaches. 

In funded defined-contribution (DC) schemes actuarial adjustments occur automatically. The 
pension fund accumulated will have to cover more or less years of retirement depending on 
when a person retires and how long they can expect 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 schemes 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  pensionable  age  with  a  fixed  annual  pension,  to  give  people 
choices  based  on  actuarial  fairness.  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 

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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  designed  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 negative) 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 adjustments 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 pension benefits at a given retirement age emerging 
from reforms has given rise to questions whether 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 concept, it would be safe to say 
that greater sustainability has been secured by introducing a greater element 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 contributions to voluntary pension 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 ensure 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  relative  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, just 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 systems enable workers to preserve their previous living 
standards  when  moving  from  employment  to  retirement  and  the  relative  income  of  the  elderly.  The  main 
indicator  is  the  aggregate  replacement  ratio.  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  possibility  to  look  at  the  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. 

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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 for more complicated pension systems 

Implicit  in  the  greater  role  for  pre-funded  components  is  the  move  towards  multi-tier 
systems,  whether  by  expanding  existing  rudimentary  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  their  working  lives  to  obtain  sufficient  pension  rights  for  an 
adequate pension package.  

Despite these caveats, the many innovative features in pension systems 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 halt in 2008 as the world entered one of the 
direst financial and economic crises in years. EU-27 GDP is projected to fall by 4.1% in 2009, 
even if the economy started to grow again in the third quarter of the year.  

Current  pensioners  have  so  far  been  among  those  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 minimum 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 pensioners across the Union.  

The main reason for this is that current pensioners overwhelmingly draw their pensions from 
public  (pre-reform)  PAYG  systems  and  established  most  of  their  pension  rights  before 
reforms  began  to  take  effect.  Notwithstanding  the  trend  towards  a  larger  role  for  funded 
schemes,  benefits  from  such  schemes  still  generally  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 type 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  reductions  in  contribution  revenues  immediately 
weaken  public  pension  scheme  finances  in  most  countries,  it  would  still  take  a  longer 
weakening of overall public finances before pensioners could conceivably 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)  occupational  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 

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seek  to  restore  their  funding  balance.  The  crisis  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 authorities 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 the 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-specific 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 ensure market stability and prevent the forced 
sale  of  mortgage  bonds  owned  by  pension  funds  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 calculated 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 over time but also between different interests. 
A  greater  sharing  of  risks  between  scheme  members  and  employers  may  be  needed  if  the 
decline in DB provision is to be halted and such schemes are to have a viable future. In the 
Netherlands,  the  existing  risk-sharing  mechanisms  have  been  used  to  lower  or  freeze 
indexation of benefits and/or increases in contribution 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)  pension  schemes  leave  the  investment  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 investment out-performance, unlike DB members.  

DC-funded pensions can be statutory, occupational and voluntary, and all three are expected 
to see some growth in at least some Member States. Currently, statutory DC-funded schemes 
are found in the majority of new Member States (BG, EE, HU, LT, LV, PL, RO, SK — see 
table  below)  together  with  SE  and  IT.  A  number  of  Member  States  have  DC  occupational 
pension schemes, notably UK, IE, SE and DK, although others including NL, BE and CY also 

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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 incentivised Riester pensions.91 

Statutory  DC  schemes  will  grow  as  transitional  arrangements  switch  some  elements  of 
provision  from  PAYG  to  funded  statutory  DC  schemes.  For  occupational  DC  schemes, 
growth will stem largely from a switch from DB to DC provision.  Individual 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. For those close to retirement the impact can be 
real, leading to less affluent, or possibly delayed, retirement. 

For those countries that have opted for an important role for funded 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  career  profiles  these  schemes  are  an  appropriate 

solution; and 

–  how  to  ensure  the  payout  phase  matches  the  original  purpose  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  could  be  very  costly  and 
possibly  create  incentives  for  excessive  risk-taking  if  the  guarantee  carries  no  price  to  the 
scheme operators. Another more likely solution consists 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  contain  such  options  at  the  moment.  Attempts  to 
reduce the reliance of pension funds on more volatile assets by setting limits on the value of 
shares in portfolios can be also observed, but the timing of such reforms (low value of more 
risky assets when the crisis hit) is questionable.  

The choice between investment strategies with different potential rates of return and levels of 
risk leads to questions as to the accuracy of information. In statutory schemes where there was 
a choice between continuing in PAYG schemes or moving part of the contributions 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 regarding the choice of 
pension funds and investment strategies, evidence suggests that many people went for riskier 
options  than  would  have  been  justified  given  their  earning  capacity  and  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  expectations  for  central  and  eastern 

91 

It is important to remind that Riester pensions are not pure DC schemes because they do not leave the 
investment  risk  entirely  with  scheme  members.  Financial  institutions  are  obliged  to  offer  to  their 
customers a guarantee of maintenance of nominal value of capital. 

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European countries obviously played a role. But so did the fact that nobody told people that a 
sudden decline in asset values could occur. Hence, 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 people make the right choices. 
Introducing  limited-risk  default  options  designed  to  be  a  reasonable  choice  for  most  people 
would likewise help. 

The 2009 Joint Report on Social Inclusion and Social Protection stressed that Member States 
should  give  careful  consideration  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 the population. This is often not the case for less well-off people 
and  for  those  with  shorter  or  atypical  employment  careers.  People  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 afterthought when it should be 
central to the scheme, especially where it will form an important element of overall pension 
provision.  A  poorly  designed  payout  phase  means  money  supposedly  saved  to  provide 
retirement  income  leaks  out  of  the  pension  system  to  be  used  for  other  purposes  such  as 
bequests. This is a problem unique to DC pensions. PAYG and DB schemes and their inherent 
cross-subsidies between those who live for longer or shorter periods in retirement 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 match 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  explained  before  people  join  schemes  reduces  the  likelihood  of 
difficulties later. 

An important advantage of DC schemes over DB plans 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  situation  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),  relative  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 (contributions ranging from 5% of gross wages in BG 
to  9%  in  SK),  existence  of  phasing-in  arrangements  (e.g.  gradual  increase  in  contribution 
levels in LV and RO, and transitional arrangements in LT, PL, or SK), and the character of 
the scheme (mandatory for cohorts under a certain 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. 

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Table 7.1 Pension systems in selected Member States92  

Country  

Bulgaria  

Estonia  

Hungary  

Latvia  

% Wage 
to funded 
scheme 

Proportion of 
total 
contribution 
to funded 
scheme  

Year 
funded 
scheme 
started 

5% 

6% 

8% 

21.7% 

20.0% 

23.9% 

2002 

2002 

1998 

Participation in funded scheme 

Year funded participants retire 

Mandatory <42 

Full cohorts in 2023 

Voluntary 

Partial cohorts by 2012 

Mandatory for new entrants; 
voluntary for all others 

Partial cohorts by 2013;  
full cohorts by 2045 

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 

Romania  

2%, 
increasing 
to 6% 

6.7% 

2008 

Mandatory <35; voluntary 36-45 

Partial cohorts of women by 2009 
and men by 2014; 

full cohorts of women by 2029 and 
men by 2034 

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 States 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, using revenues from privatising state enterprises, 
or  shifting  part  of  the  cost  to  current  pensioners,  e.g.  through  the  introduction  of  less 
favourable indexation rules, or to future beneficiaries of the PAYG schemes93. 

The  reforms  usually  made  participation  in  the  funded  scheme  mandatory  for  younger 
generations, while people nearing retirement were excluded, and intermediate cohorts had the 
choice  to  join  or  not.  In  some  Member  States  (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 considerably exceeded official estimates. 

Bringing forward costs by increasing pre-funding has placed strains on Members States' fiscal 
positions, and the current economic situation provides a serious stress test of the viability of 

92 

93 

Relevant EU countries extracted from World Bank Human Development Network paper "The Financial 
Crisis and Mandatory Pension Systems in Developing Countries Short- and medium-term responses for 
retirement 
income  systems"  http://siteresources.worldbank.org/INTPENSIONS/Resources/395443-
1121194657824/PRPNote-Financial_Crisis_12-10-2008.pdf 
According to the 2008 SPC study "Privately Managed Funded Pension Provision and their Contribution 
to Adequate and Sustainable Pensions", pp.18-19. 

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such arrangements. Facing a growing fiscal gap, 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 mandatory 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% member share) and will reach their 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. Contribution 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 employees’ 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 all new entrants to the labour market. In Poland, the 
government is discussing a reduction in contributions 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 transfers 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 treated as an anti-cyclical measure. However, there are also 
arguments against decreasing the 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  adjust  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, transparency and long-term planning are important. 

7.2.4.  Distribution  of  the  burden  of  the  crisis  in  PAYG  systems  between  different 

generations 

PAYG schemes also have not been immune to the 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  States,  most  retired  cohorts  today  obtain  their 
pensions under pre-reform rules providing for guaranteed pension levels. Younger cohorts in 
reformed schemes may be affected to some extent depending on the design of the scheme.  

Member States in the majority of cases are keeping 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 working age population. LV and LT are exceptions here as they 
are  recording  the  deepest  fall  in  GDP  in  the  EU  in  2009  (both  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 Forecast of Autumn 2009. 

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Pension benefits for current pensioners in Latvia have seen an overall 10% reduction (70% 
for  working  pensioners)  since  the  1st  of  July  2009.  According  to  the  judgment  of  the 
Constitutional  Court  (21  December  2009),  these  deductions  will  be  removed  from  1st 
February 2010 and deductions 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 stabilize an increase of the deficit of the State 
and the State Social Insurance Fund budgets and to ensure 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%. Pensions for working old age pensioners will be 
reduced proportionally to their insured income 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 sustainability 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 schemes. 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 ballooning general government deficits and 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  increase  in  public  debt  some  countries  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 security 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  resources  in  times  of  constraint,  it  is  important  to 
consider  the  long-term  demographic  pressures  on  the  pension  system.  The  use  of  funds 
earmarked  for  pensions  can  also  lead  to  a  loss  of  social  confidence  and  acceptance  for  the 
pension system. 

95 

European Economic Forecast, Autumn 2009, European Commission, p. 208. 

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7.2.6.  The effects of the crisis on automatic mechanisms in PAYG systems 

While automatic mechanisms enhance the transparency of a pension system, 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 triggers are allowed to function.  

Most automatic mechanisms have not yet been applied in practice, and experience from 2006-
2008 shows that it is critical to monitor the functioning of these mechanisms, some of which 
are  close  to  activation  given  the  financial  and  economic  pressures  on  pension  systems  as  a 
result of the crisis. Prior to the crisis a few countries had already taken political decisions to 
postpone  automatic  adjustments.  Changing  the  regulations  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 pension 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 the 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 mechanism in DE would require contribution rates 
to be raised. Whiles there is a cap of 20% on contribution rates, this can be balanced with a 
decrease  in  pension  indexation.  In  2002  to  2005,  contribution  rates  would  have  had  to  be 
increased to over 20% or pension indexation would 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 increase in total contributions outside the statutory system.  

In  Sweden,  the  fall  in  financial  markets  has  triggered  the  adjustment  mechanism.  The 
activation  of  the  mechanism  reduces  the  indexation  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 government has recently decided to re-evaluate 
the calculation performed for the balancing mechanism and the proposal that has been decided 
by  the  Swedish  parliament  is  one  that  smoothens  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  value  of  the  funds.  This  will  have  the  effect  of  sharing  the 
burden of the financial downturn over more years. 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 expenditure 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.  

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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  pension  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 sense, Member States are in very different positions to face the crisis. Countries 
with  more  balanced  budgets  can  afford  to  apply  a  higher  degree  of  counter-cyclicality  at  a  time  of  crisis  as 
compared with countries where the consolidation 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 most vulnerable and those most affected by a downturn. 
In  contrast,  countries  faced  with  major  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 immediately and directly impacted by the financial 
crisis. Falls in the value of investments feed through into deficits in definend-benefit pension 
schemes and into lower individual pension fund 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.  Ultimately,  the  economy  determines 
what is affordable for PAYG pensions. Lower growth, 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 mechanisms 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 crisis has added to this challenge. Indeed, 
the financial crisis may have put into sharper focus underlying structural issues regarding the 
sustainability  of  pension  systems.  These  issues  may  previously  have  been  masked  by 
expectations of returns on funded pension schemes or anticipated 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  financing  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  pensions  in  defined-contribution  schemes  has  also 
been brought into sharper focus. In PAYG schemes, 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 highlighted. At the same time, as eligibility rules are 
tightened  in  reforms,  the  effect  of  long  career  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.  However,  pension  reforms  and  resulting  pension 
promises  have  been  predicated  on  scenarios  of  steady  economic  growth  and  continued 
increases in employment. 

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Adjustments to all kinds of pension schemes may 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 particular 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  economic  growth  over  the  medium  and  long  term. 
The  recession  could  have  implications  for  the  growth  potential  of  the  EU  economy.  On  the 
demand  side,  deteriorating  labour  market  conditions  could  constrain  consumption  in  the 
medium term. The supply side of the economy could be also affected.96  

Trend growth in the next few years could be lower 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 economic 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 close to retirement today. However, the length of 
the shock and the financial situation of the system when the shock hits crucially affect how 
the system can handle the payment burden in the short and long term. Pension reforms have 
been  based  on  certain  assumptions  of  growth  and  returns  on  paid  contributions.  If  pension 
systems  are  unable  to  handle  the  effects  of  lower  than  expected  returns  or  a  narrower 
contribution base due to unemployment, this could ultimately affect the adequacy of benefits. 
However, a system that cannot pay 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 the role of automatic stabilisers in the current 
crisis.  However,  anti-cyclicality  should  be  maintained  when  recovery  sets  in,  so  that  social 
protection  systems  are  sustainable  in  the  long  run.  This  often  implies  politically  difficult 
decisions. Meanwhile, automatic adjustment mechanisms in pension schemes may tend to be 
activated in a pro-cyclical rather than anti-cyclical  manner,  which  needs  to  be  monitored  or 
adjusted. 

In the event of protracted low growth Member States 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. According 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 increase to 13.6% of GDP instead of 12.5%.97 

7.3.2.  Long-term adequacy of pensions in light of the crisis 

Over the coming decades the sensitivity 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 pensions in the income packages of future pensioners is set to 
increase  markedly.  At  the  same  time,  the  bulk  of  funded  schemes  will  be  of  the  defined-
contribution  type  where  investment  risks  are  moved  to  pension  savers.  In  addition,  the 

96 
97 

For further discussion see Sustainability Report 2009, p. 48. 
Ageing Report 2009, pp. 185-187. 

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reduced  pensions  from  public  PAYG  schemes  will  increasingly  be  calculated  on  life-time 
earnings-related  contributions.  On  present  trends,  only  those  with  very  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  systems.  It  will  also  be  contingent  on  the  ability  of  labour 
markets to deliver sufficient opportunities 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 unemployment 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  negatively  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 the 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, being 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,  early  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  that,  in  addition  to  the  need  to  ease  future 
expenditure  pressures  due  to  population  ageing,  they  will  have  to  increase  efforts  to  reduce 
the swollen public debts due to the current crisis. Discussions on increasing the pensionable 
age are under way in a number of Member States.  

In Latvia, the government intends to increase the retirement age from 62 to 65 by 2021. In 
Hungary,  the  retirement  age  will  be  gradually  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. There would be special provision 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 pensions 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  opportunity  to  return  to  the 
labour market, e.g. offering flexible retirement options, monitoring whether wage differentials 

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between  younger  and  older  workers  do  not  push  out  older  workers  from  the  labour  market, 
changing the habits of employers, or outlawing discrimination on the grounds of age.  

7.3.4. 

Increases in pensionable age for DB schemes 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  comparatively  young  pension  eligibility  ages  look 
increasingly  unaffordable.  Increases  in  pensionable  age  would  require  more  or  less  formal 
agreements with social partners, usually at company or sector level.  

7.3.5.  Risks linked to the exposure of future 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-performance. Nevertheless, the possibility of 
obtaining high replacement rates has to be considered 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 funded schemes to volatility in financial markets 
and  highlighted  the  need  for  policymakers,  regulators  and  supervisors  to  promote  more 
prudent management of people’s retirement savings. With losses ranging from 15% to 35%, 
and with an even greater variation in the capacity to absorb the shock, differences in pension 
fund designs and investment strategies 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  achieved.  Accordingly  a  new  agenda  is  emerging  for 
necessary changes to funded designs and for speedy completion of the unfinished parts of the 
new  mandatory  schemes  (e.g.  concerning  more  secure  default  options,  life-styling,  charge 
capping,  and  rules  for  annuitisation  and  the  pay-out  phase).  Achieving  this  will  be  an 
important part of rebuilding public confidence in funded, privately managed pensions. 

7.4. 

Policy implications 

The  longer-term  challenge  of  ageing  is  no  longer  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 sharper focus. The balance between 
adequacy and sustainability — the object of a decade of pension reforms — is under pressure 
from  the  financial  and  economic  crisis.  Increases  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  public  finance  improvements  intended  to  provide 
room for extra expenditure to address ageing and this lost ground will have to be regained.  

7.4.1. 

Shorter-term implications 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  schemes  and  the  mechanisms  designed  to  protect 

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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 realistic 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 recovery plans, to smooth impacts. Adjustment mechanisms 
designed to share risk (e.g. potential changes to the indexation 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/employee  negotiations  to  agree  burden  sharing,  where  necessary,  to  keep  DB 
schemes  open.  In  Member  States  with  insurance-style  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  pressures  need  to  remain  credible.  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 and needs to be carefully explained. Similarly, where 
public  pension  schemes  have  automatic  adjustment  mechanisms  in  place  to  support  sustainability,  any 
interference  with  the  automatic  outcome  can  reduce  their  credibility  and  social  acceptance  and  needs  careful 
explanation.  

7.4.2.  Medium/long-term implications of the crisis 

In the future an increasing share of pension income is expected to be provided by DC pension 
systems. This is due to two factors. One is the 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 new DC pension schemes often partly replacing PAYG pensions, 
as  in  many  new  Member  States.  Box  Y  below  raises  a  few  specific  longer  term  policy 
questions that Member States may want to consider, 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 all Member States and a long-term implication of the crisis 
is to increase overall employment rates and employment rates of older workers. 

Box Y. Longer-term policy questions for specific types of pensions 

There  are  a  number  of  longer-term  policy  questions  Member  States  may  wish  to  consider,  depending  on  the 
type(s) of pension schemes in their particular system: 

DC pensions 

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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 introducing 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 approach that benefits all stakeholders. There may also be a 
need to examine whether there are underlying structural issues in some DB schemes, which may need addressing 
via  specific  changes,  for  instance  to  retirement  ages.  There  may  also  be  merit  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  long-term  sustainability  of  PAYG  pension  systems  and  its 
impact will need to be closely monitored. Where underlying 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 employment 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 therefore important to consider developing this anti-cyclical 
behaviour in social spending even as the economy enters a boom.  

Current pension systems for those retiring today have so far stood up reasonably well to the 
major  stress  test  of  the  financial  crisis.  However,  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 solvency and social adequacy. 
Pension  systems  were  of  course  already  under  pressure  from  the  demographic  ageing  in 
Europe.  The  crisis  has  added  to  this  pressure,  and  brought  into  sharper  focus  underlying 
structural  issues  that  pension  systems  are  facing.  With  different  expectations  for  economic 
growth and investment performance, these issues are now surfacing and the crisis may offer 
the impetus and political opportunity to see through difficult reforms. 

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8. 

GOVERNANCE 

The  crisis  has  emphasised  the  value  of  policy  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 information on emerging social problems and 
on new policy measures. This information has been 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  awareness  and  understanding  of  common 
challenges.  

The need to react swiftly to the crisis has led many Member States to reinforce 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  administrative  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. assessment of the likely impact of proposed measures before they are 
decided). Given that pressure aimed at limiting public 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 impact 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 States and between the Member States and 
the  European  Commission.  The  latter  has  recently  taken  initiatives  to  strengthen  its  own 
capacity to assess social impacts.  

Countries  that  can  rely  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 crisis. 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 have had to meet increased demand for social 
benefits  and  services  while  often  seeing  their  own  revenues  squeezed.  Cooperation  and 
coordination among all these actors has been an invaluable asset.  

In preparation for the EU strategy post-2010, the Social Protection Committee has established 
a Task Force to review the experience 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 exclusion remain a major issue in most EU countries, 
although with substantial differences across Europe. 

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Drawing on the lessons of the crisis and of ten 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  outcomes,  including  gender  equality.  To  this  end, 
reinforcing the Social OMC and increasing its effectiveness 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  economy  entails  continued  modernisation  of  social  protection  to 
deliver the dual objectives of adequacy and sustainability. This will be crucial for improving 
the functioning and social outcomes of labour markets, thus ensuring the optimal use of our 
human  resources  through  opportunities  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  strategy  coincides  with  the  European  Year  for  combating 
poverty  and  social  exclusion.  Raising  awareness,  reinforcing  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 eradication of poverty and social exclusion. 

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9. 

ANNEXES 

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 income98. Source: EU-SILC. 

+  Illustrative  threshold  value:  Value  of  the  at-risk-of-poverty  threshold  (60%  median 
national  equivalised  income)  in  PPS  for  an  illustrative  household  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 poverty threshold and the threshold 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  called  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  Education  —  ISCED  97)  and  have  not  received 
education or training in the four weeks 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,  healthcare,  long-term  care,  education  and  unemployment 
transfers),  current  level  (%  of  GDP)  and  projected  change  in  share  of  GDP  (in  percentage 
points) (2007-2020; 2007-2060). 

http://ec.europa.eu/economy_finance/publications/publication14994_en.pdf  (Table  A  134  – 
The cost of ageing overview) 

98 

99 

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. 

Students aged 18-24 who live in households composed solely of students are not counted in either the 
numerator or denominator. 

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7a.  Median  relative  income  of  elderly  people: Median equivalised income  of  people  aged 
65+ as a ratio of income of people 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  the  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  income  below  the  at-risk-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 population in the same age group. Source: LFS. 

11.  In-work  poverty  risk:  Individuals  who  are  classified  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 household characteristics. 
It should also be analysed in comparison with 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 per capita in PPP. Source: 
EUROSTAT based on system of health accounts (SHA) data. 

100 

101 

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. 
Standard deviation measures how, on average, the situation in regions differs from the national average. 
As a complement to the indicator, a graph showing 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 population/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 unemployment, respectively. (An extra column with 
the national employment and unemployment rates would be included). 

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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  information  that  would  be  most  relevant  to 
frame and understand better the national 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 households by household type, 2008 (percentage 
of total population). Source: EU-SILC. 

Context 6a: General government debt - General 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  debt  levels  up  to  2050  (in  %  of  GDP).  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). Source: Eurostat ESPROSS. 

Context 7b: Social protection benefits by group 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. 

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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 - Inactivity Trap at 67% of Average Wage, 9c - 
Inactivity traps. Source: Joint Commission -OECD project using tax-benefit Models. 

Context 10: Net income of social assistance recipients as % of the at-risk of poverty rate 
threshold for 3 jobless households types. This indicator refers to the 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-of-poverty threshold. This 
indicator is calculated on the basis of the tax-benefit models developed jointly by the OECD 
and  the  European  Commission.  It  is  only  calculated  for  Countries  where  non-categorical 
social benefits are in place and for 3 jobless household types: single, lone parent, 2 children 
and  couple  with  2  children.  This  indicator  is  especially  relevant  when  analysing  MWP 
indicators. 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. This indicator is meant to compare the observed risk of poverty with a hypothetical 
measure of a risk of poverty in absence of all social transfers (other than pensions) all things 
being  kept  equal.  In  particular,  household  and  labour  market  structure  are  kept  unchanged. 
This  measure  does  not  take  into  account  other  types  of  transfers  that  have  an  impact  on 
household disposable income such as transfers in kind and tax rebates.Source: EU-SILC. 

Context 12: Change in Theoretical replacement 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 retirement 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 accompanied by information on representativeness and 
assumptions (contribution rates and coverage rate, public and private). Specific assumptions 
agreed in the ISG. For further details, see 2006 report on Replacement Rates. Source: ISG and 
AWG 

9.1.3.  New indicators adopted in the field of social inclusion: 

In 2009, the Social Protection Committee adopted new 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  household  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 adequately warm, or could not afford (even if wanted to): vi) a 
washing machine, vii) a colour TV, viii) a telephone, ix) a personal car. 

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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 (see above, indicator SI-P8). 

In July 2009, 2 secondary indicators and 2 context information were adopted in the field of 
housing, but further work, including further improvement of the quality of the data is needed 
before a primary indicator can be identified. 

3.  Housing  costs:  Percentage  of  the  population  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  renters,  housing  benefits  for  rent  free  households. 
They  also  include  structural  insurance,  mandatory  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 include capital repayment for mortgage holders.  

Housing allowances include rent benefits102 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 overcrowded 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 same 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  items  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 sole use of the household; - Dwelling too dark.

Breakdowns: sex, age (0-17; 18-64; 65+); for the 4 items only: poor/non-poor. 

102 

103 

104 

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. 
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. 
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. 

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6. Share of housing costs in total disposable household income: Median of the distribution 
among  individuals  of  the  share  of  housing  costs  (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 

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9.2. 

Data sources 

9.2.1. 

Indicators of income and living conditions: EU-SILC 

EU-SILC  data  are  available  for  25  EU  countries  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  systematic  production  of  Community  statistics  on 
income  and  living  conditions.  In  addition  to  those  regulations  mentioned  above  there  are 
various  other  implementing  regulations,  concerning  e.g.  definitions  and  updates,  fieldwork 
aspects  and  imputation  procedures  and  quality  reports  as  well  as  annual  regulations  setting 
down  lists  of  secondary  target  variables.  In  June  2006,  the  Social  Protection  Committee 
adopted a new set of common indicators for the social protection and social inclusion process. 

The  EU-SILC  definitions  of  total  household  gross  and  disposable  income  and  the  different 
income components keep as close as possible to the international recommendations of the UN 
‘Canberra Manual’. A key objective of EU-SILC is to deliver timely, robust and comparable 
data  on  total  disposable  household  income,  total  disposable  household  income  before 
transfers, total gross income and gross income at component level (in the ECHP, the income 
components were recorded net). This objective will be reached in two steps, 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  definition  underlying  the  calculation  of  indicators 
currently excludes imputed rent. This could have a distorting effect in comparisons between 
countries, or between population sub-groups, when accommodation tenure status varies. This 
effect  may  be  particularly  apparent  for  the  elderly  who  may  have  been  able  to  accumulate 
wealth in the form of housing assets. In the statistical 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 taken 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 value of goods produced for own consumption105 and non-
cash employee income. These components, together with imputed rent data are available for 
all  countries  from  the  SILC  (2007)  exercise  onwards;  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  the  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 

137 

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Social  Protection  Committee  will  discuss  the  possible  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 income situation of the population in 2005, even 
if the information was collected in 2006. EU aggregates are computed as population-weighted 
averages of available national values.  

Limitations 

The limited sample size for certain data sources used for the collection of income data and the 
specific  difficulties  of  collecting  accurate  information  on  disposable  income  directly  from 
households  or  through  administrative  records  raise  certain  concerns  as  regards  data  quality. 
This  is  particularly  the  case  for  information  on  income  at  the  two  ends  of  the  income 
distribution. 

Furthermore,  household  surveys  do  not  cover  persons  living  in  collective  households, 
homeless persons or other difficult-to-reach groups.  

It  must  also  be  acknowledged  that  self-employment  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 income 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  community  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 interpreted as being the bottom 10% in terms 
of living standards. This is why reference is made to the ‘at-risk-of-poverty’ rate rather than 
simply the poverty rate.  

Confidence intervals 

Indicators are estimated values based on a sample drawn from the target population and thus 
are  affected  by  sampling  error.  Statistical  theory  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  estimated  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 Regulation provides for national 
samples to be designed so as to achieve a confidence interval of +/-1% around the estimated 
value of the total at-risk-of-poverty rate. Eurostat is computing these intervals for a number of 
indicators  and  exact  values  will  be  reported  in  EU  quality  reports.  First  computations  show 
that  the  confidence  intervals  around  the  total  at-risk-of-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 

138 

   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 carried out since 1983 in the EU Members States, 
with some states providing quarterly results from a continuous labour force survey, and others 
conducting  a  single  annual  survey  in  the  spring.  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  quarter'  in  all  countries  except  for  France  and 
Austria, which is 'first quarter') of each year. It also provides data for Bulgaria, Croatia and 
Romania. 

The Annual Averages of Labour Force Data series is a harmonised, 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  and  Candidate  Countries  (since  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  economic  activity  and  employment  status.  The  first 
series is based mainly on the EU LFS. Data covers the population living in private households 
only  (collective  households  are  excluded)  and  refers  to  the  place  of  residence  (household 
residence concept). They are broken down by gender and aggregate 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  living  in  collective  households.  They  are  broken 
down 
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 relevant breakdowns, the original LFS data has been used for this 
report. 

sex,  working-time 

(full-time/part-time) 

contract 

status 

and 

by 

9.2.3.  Age-related expenditure projections 

Long-term budgetary projections were prepared 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 States (2008-2060)', European Economy 2/2009  

The  projections  are  made  on  the  basis  of  a  common  population  projection  and  agreed 
common  underlying  economic  assumptions  that  have  been  endorsed  by  the  EPC.  The 
projections are made on the basis of ‘no policy change’, i.e. only reflecting enacted legislation 
but  not  possible  future  policy  changes  (although  account  is  taken  of  provisions  in  enacted 
legislation that enter into force over time). The pension projections are 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 changes in behaviour over time: for example, 
this  is  reflected  in  the  assumptions  for  participation  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  uniformly  to  all  Member  States,  for  several 
countries adjustments have been made to avoid an overly mechanical approach that leads to 
economically  unsound  outcomes  and  to  take  due  account  of  significant  country-specific 

EN 

139 

   EN 

 
circumstances.  The  pension  projections  were  made  using  the  models  of national authorities, 
and thus reflect the current institutional features of national pension systems. In contrast, the 
projections for healthcare, long-term care, education and unemployment transfers were made 
using common models developed by the European Commission in close cooperation with the 
EPC  and  its  Working  Group  on  Ageing  Populations.  The  projection  results  show  the 
combined  impact  of  expected  changes  in  the  size  and  demographic  structure  of  the 
population,  projected  macroeconomic  developments  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  according  to  the  ESSPROS  definition,  goes  beyond 
public  expenditure  and  also  includes  expenditure  by  private  social  protection  schemes. 
‘Pension  expenditure’  is  the  sum  of  seven  different  categories  of  benefits,  as  defined  in  the 
1996 ESSPROS Manual: disability pension, early retirement benefit due to reduced capacity 
to work, old-age pension, anticipated old-age pension, partial pension, survivors’ pension and 
early  retirement  benefit  for  labour  market  reasons.  Some  of  these  benefits  (for  example, 
disability pensions) may be paid to people who have not reached the standard retirement age. 

Replacement rates 

The  figures  for  current  and  prospective  pension  replacement  rates  are  based  on  the 
methodology developed by the Indicators Sub-Group of the Social Protection Committee. The 
results  are  based  on  the  baseline  assumption  of  a  hypothetical  person  (male  where  gender 
matters) retiring at the age of 65 after a 40-year full-time working career with a flat earnings 
profile at average earnings with contributions to the most general public pension scheme as 
well as to occupational and private pension schemes for some Member States.  

The  replacement  rate  represents  the  individual  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 Health for All database (www.who.int\nha) 

This  information  is  based  on  national  health  accounts  (NHAs)  collected  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 OECD 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.  Standard  accounting  estimation  and  extrapolation  techniques  have 
been used to provide time series (1998-2004). Ministries of Health have responded to the draft 
updates  sent  for  their  inputs  and  comments.  The  principal  international  references  used  are: 
the  International  Monetary  Fund  (IMF),  Government  Finance  Statistics  and  International 
Financial Statistics; OECD health data; and the United Nations National Accounts Statistics. 
National  sources  include:  national  health  accounts  reports,  public  expenditure  reports, 
statistical  yearbooks  and  other  periodicals,  budgetary  documents,  national  accounts  reports, 
central  bank  reports,  non-governmental  organisation  reports,  academic  studies,  reports  and 
data  provided  by  central  statistical  offices  and  ministries,  and  statistical  data  on  official 
websites. 

EN 

140 

   EN 

 
9.3. 

Annex to part 6 on Health 

Figure A1 

Total expenditure on health per capita PPS, 2007 or latest available

S
P
P
a
t
i

p
a
c

r
e
P

5000

4500

4000

3500

3000

2500

2000

1500

1000

500

0

Bulgaria
Romania

Latvia
Slovenia
Hungary
Slovakia
UnitedKingdom
Lithuania
Portugal
Spain
Poland
Cyprus
Sweden
Denmark
CzechRepublic
Greece
Finland
Estonia
Italy

Ireland

Luxembourg
Germany
Netherlands
France
Belgium
Austria

Source: Eurostat for all, except Ireland, Greece, Italy and UK. Source for these four Member States: 
OECD Health data. Malta: non available. 

EN 

141 

   EN 

 
 
 
 
Figure A2 

Total expenditure on health as a % of GDP

P
D
G

f
o
%

12,0

11,0

10,0

9,0

8,0

7,0

6,0

5,0

4,0

3,0

2,0

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

1980

1985

1990

1995

2000

2005

2006

2007

Source: OECD Health data and WHO Health for All databases 

EN 

142 

EN 

 
  
 
 
 
 
Table A1: Total expenditure on health as a percentage of GDP, 1960-2007 

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

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
10,2

10,0

3,9

5,6

6,3

7,6

7,7

8,4

8,3

7,3

7,2

7,0

7,1

7,3

7,7

8,2

7,9

8,7
8,4

7,3

4,6
6,4

8,9
8,4

8,3
5,9
5,3
7,0

8,5
8,8

8,2
8,7

7,5

7,4

5,3

5,4
8,0

6,0

5,1
5,4
3,5
5,4

8,5
8,8

7,1
6,6
5,4

3,7

4,0

1,5
3,8

2,5
4,7

8,6
8,9

6,7
5,9
6,0

8,5
8,3

6,3
6,5
6,2

7,3

7,3

3,1

4,3

5,2

5,2

5,0

5,5

5,3

5,2

4,3

4,6

5,2

7,0
6,9

7,4
7,4

7,3
6,4

7,4
6,7

7,6
6,8

7,6
6,8

7,9
7,0

2,5

5,1

5,3

5,7

6,3

6,2

6,4

5,9

3,8

4,8

3,9

4,1

5,5
6,8
4,5

6,2
7,5
5,4

6,3
8,9
5,6

7,1
8,5
5,8

7,2
8,3
5,8

7,3
8,3
5,9

7,1
8,2
5,8

7,1
8,2
5,8

7,2
5,2
4,7
8,3
8,3

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

8,0
8,3
4,8
5,9
2,9
5,6

7,7
8,2
5,9

4,9
8,2

6,5
6,4
6,7
8,6
7,9

5,1
7,0

8,2
8,4
6,0
6,4

8,8
8,0
6,3

5,1
8,3
9,6

7,0
7,0
7,1
8,9
8,0

5,4
7,5

8,4
8,7
6,1
6,6

9,0
8,2
6,8

6,7
8,6
9,6

6,9
7,9
7,4
9,3
7,9

5,5
7,6

8,5
9,3
5,8
6,9

8,2
8,4
6,8

6,9
8,4
9,8

6,9
8,6
7,3
9,3
7,6

5,3
8,1

8,3
9,6
5,5
7,0

7,7
8,0
6,9

7,0
8,1
10,1

6,7
8,6
7,4
10,4
7,3

6,7
8,2
10,4

6,5
8,6
7,5
10,4
7,4

6,7
8,2
10,2

6,4
8,4
7,3
10,2
7,7

5,6
7,3

8,3
9,5
5,5
7,8

7,9
8,0
6,8

5,7
7,0

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

8,0
8,2
6,8

5,6
6,8

7,9
9,8
5,6
8,0

5,8
7,6
8,1
6,6

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

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

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

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

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

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

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

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

6,9
9,6
10,5

7,1
9,5
8,4
11,0
9,0

7,3
8,1

9,7
10,2
6,2
9,9

7,3
8,3
9,1
8,5

6,8
9,8
10,4

7,6
9,6
8,5
11,0
8,7

7,4

9,8
10,1
6,4

7,7
8,2
9,1
8,4  

Source: OECD Health data and WHO Health for All databases 

EN 

143 

EN 

 
  
Figures A3: GDP growth rates versus growth rates of total expenditure on health 106 

Austria

Belgium

Germany

40,0

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

-5,0

-10,0

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

-5,0

106 

EN 

45,0
40,0
35,0
30,0
25,0
20,0
15,0
10,0
5,0
0,0

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

1971

1974

1977

1980

1983

1986

1989

1992

1995

1998

2001

2004

2007

GDP grow th

THE grow th

GDP grow th

THE grow th

Greece

Hungary

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

-5,0

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

1
7
9
1

3
7
9
1

5
7
9
1

7
7
9
1

9
7
9
1

1
8
9
1

3
8
9
1

5
8
9
1

7
8
9
1

9
8
9
1

1
9
9
1

3
9
9
1

5
9
9
1

7
9
9
1

9
9
9
1

1
0
0
2

3
0
0
2

5
0
0
2

7
0
0
2

GDP grow th

THE grow th

Ireland

25,0

20,0

15,0

10,0

5,0

0,0

-5,0

45,0

40,0

35,0

30,0

25,0
20,0

15,0

10,0

5,0

0,0

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

GDP grow th

THE grow th

GDP grow th

THE grow th

GDP grow th

THE grow th

The relevant information (i.e. total health expenditure in absolute values) is not readily available for the eight Member States missing in these graphs, or is just available for 
very short time series. 

144 

EN 

 
  
 
 
 
                                                 
Italy

Luxembourg

The Netherlands

30,0

25,0

20,0

15,0

10,0

5,0

0,0

90,0

80,0

70,0

60,0

50,0

40,0

30,0

20,0

10,0

0,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

1
7
9
1

3
7
9
1

5
7
9
1

7
7
9
1

9
7
9
1

1
8
9
1

3
8
9
1

5
8
9
1

7
8
9
1

9
8
9
1

1
9
9
1

3
9
9
1

5
9
9
1

7
9
9
1

9
9
9
1

1
0
0
2

3
0
0
2

5
0
0
2

7
0
0
2

-5,0

1971

1974

1977

1980

1983

1986

1989

1992

1995

1998

2001

2004

2007

-10,0

GDP grow th

THE grow th

GDP grow th

THE grow th

Poland

Portugal

60,0

50,0

40,0

30,0

20,0

10,0

0,0

1
9
9
1

2
9
9
1

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

1
7
9
1

3
7
9
1

5
7
9
1

7
7
9
1

9
7
9
1

1
8
9
1

3
8
9
1

5
8
9
1

7
8
9
1

9
8
9
1

1
9
9
1

3
9
9
1

5
9
9
1

7
9
9
1

9
9
9
1

1
0
0
2

3
0
0
2

5
0
0
2

7
0
0
2

18,0

16,0

14,0

12,0

10,0

8,0

6,0

4,0

2,0

0,0

40,0

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

GDP grow th

THE grow th

Slovakia

3
9
9
1

4
9
9
1

5
9
9
1

6
9
9
1

7
9
9
1

8
9
9
1

9
9
9
1

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

GDP grow th

THE grow th

GDP grow th

THE grow th

GDP grow th

THE grow th

EN 

145 

EN 

 
  
 
 
Spain

Sw eden

UK 

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

25,0

20,0

15,0

10,0

5,0

0,0

-5,0

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

35,0

30,0

25,0

20,0

15,0

10,0

5,0

0,0

GDP grow th

THE grow th

GDP grow th

THE grow th

Source: OECD Health data, WHO Health for All databases and EC computations 

1
6
9
1

4
6
9
1

7
6
9
1

0
7
9
1

3
7
9
1

6
7
9
1

9
7
9
1

2
8
9
1

5
8
9
1

8
8
9
1

1
9
9
1

4
9
9
1

7
9
9
1

0
0
0
2

3
0
0
2

6
0
0
2

GDP grow th

THE grow th

EN 

146 

EN 

 
  
 
Figure A4 

Public expenditure on health as % of GDP, 1997-2007

1998

1999
2000
2001
2002

2003
2004
2005
2006

2007

10

9

8

7

6

5

4

3

2

1

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

Source: OECD Health data and WHO Health for All databases 

EN 

147 

EN 

 
  
 
Figure A5 

Public expenditure on health as % of GDP, 1980-2007

10

9

8

7

6

5

4

3

2

1

0

E
B

G
B

Z
C

K
D

E
D

E
E

E

I

L
E

S
E

T
R I
F

Y
C

V
L

T
L

U
L

U
H

T
M

L
N

T
A

L
P

T
P

I

O S
R

I

K F
S

E
S

K
U

1980

1985

1990

1995

2000

2005

2006

2007

Source: OECD Health data and WHO Health for All databases 

EN 

148 

EN 

 
  
 
Table A2: Public expenditure on health as a % of GDP, 1960-2007 

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

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

7,5
6,6

5,8

3,6
5

7,9
6,6

6,8
3,3
4,2
5,6

7,3
6,8

6,9
6,7

5,7

5,6

4,2

4,3
6,3

7,1
6,8

5,2
4
4,3

4,4

4,1
2,3
2,3
4,1

2,8

3,1

0,9
2,4

1,3
3,4

7,3
6,9

4,8
3,2
4,7

7,1
6,3

4,6
3,6
4,8

5,7

5,7

4,6
6,9
6,3

4,4
3,5
5,1
6,4
6,1

2,8

4

4,8

4,6

4,5

5,1

4,9

4,8

5

3

3,2

3,3

4,8
4,8

5,1
5,1

5,2
4,9

5,1
5,1

5,2
5,2

5,1
5,2

5,3
5,2

1,5

3

3,4

3,1

3,3

3,2

3,4

3,1

5,4
6,1
4,4
3,8

4,8
6,9

4,7
3,4
5,2
6,6
6,3

4,8
6,3

5,6
6,1
4,5
4

4,9
6,9
7,8

5
3,8
5,5
6,8
6,2

5
6,6

6,1
6,4
4,6
3,9

6,4
7,1
7,7

5,1
4,3
5,7
7,1
5,9

5,1
6,6

6,2
6,9
4,3
4,4

6,5

6,7

6,5
6,9
7,9

5
4,3
5,5
7,1
5,6

4,9
7,1

6,1
7,2
4
4,4

6,4
6,7
8,2

4,8
4,5
5,4
8,3
5,1

5,1
6,1

5,9
7
4
4,9

6,1
6,8
8,5

4,7
4,5
5,4
8,3
5,2

5,2
5,7

5,4
7
4,3
5,2

2,1

3,2

3,3

3,5

4,1
5,8
3,9

4,8
6,8
4,9

5
8,2
5

5,6
7,7
4,9

5,7
7,4
4,9

5,8
7,4
4,9

5,6
7,3
4,8

5,7
7,3
4,8

6,2
7,4
4,9

7,1
7,1
5,3

7,2
7,1
5,7

6,3
7,4
5,8

5,8
7
5,8

5,7
6,9
5,7

5,8
7,1
5,7

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

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

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

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

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

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

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

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

6
6,7
8,3

4,7
4,5
5,3
8,1
5,4

5,2
5,5

5,4
7,4
4
5,3

5,3
5,5
6,9
5,3

6,1
8,1
8,1

5,5
5,9
6
8,7
6,9

6,6
5,9

7,8
4,3
7,1

5
6,2
7,4
6,9

5,8
8,2
8

6,1
5,8
6,1
8,7
6,7

5,2

7,7
4,6

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

Source: OECD Health data and WHO Health for All databases 

EN 

149 

EN 

 
  
Figures A6: Public expenditure as % of total expenditure on health, 1960-2007  

100

90

80

70

60

50

40

1960

1970

1980

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

BE

BG

CZ

DK

DE

EE

IE

100

90

80

70

60

50

40

1960

1970

1980

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

EL

ES

FR

IT

CY

LV

LT

100

90

80

70

60

50

40

100

90

80

70

60

50

40

1960

1970

1980

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

1960

1970

1980

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

EL

ES

FR

IT

CY

LV

LT

RO

SI

SK

FI

SE

UK

Source: OECD Health data and WHO Health for All databases 

EN 

150 

EN 

 
  
 
 
 
 
Figure A7 

Life expectancy at birth vs total expenditure on health as % of GDP, 
2007 or latest available

h

t
r
i
b

t

a

y
c
n
a

t
c
e
p
x
e
e

f
i

L

82.0

80.0

78.0

76.0

74.0

72.0

70.0

4.0

FR

AT

DE

BE

ES

IT

SE

MT
UK

FI

SI

EL

NL

PT
DK

y = 1,5045x + 65,266
R2 = 0,5439

IE

LU

CY

CZ

PL

HU

SK

BG

EE

RO

LT

LV

6.0

8.0

10.0

12.0

total expenditure on health as % of GDP

Source: Eurostat data, OECD Health data, WHO Health for All database and EC computations 

EN 

151 

   EN 

 
 
 
 
 
Figures A8a 

Projected life expectancy at birth, males 

Projected life expectancy at 65, males  

Source: Eurostat, EUROPOP2008 convergence scenario; 2009 EPC/EC Ageing Report 

EN 

152 

   EN 

 
 
 
Figures A8a 

Projected life expectancy at birth, female (in years) 

Projected life expectancy at 65, women (in years) 

Source: Eurostat, EUROPOP2008 convergence scenario; 2009 EPC/EC Ageing Report 

EN 

153 

   EN 

 
 
 
Figures A9: Population pyramids 2008 and 2060, EU27 

Men

Women

Men

Women

90+

85-89

80-84

75-79

70-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

90+

85-89

80-84

75-79

70-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

4,00

3,00

2,00

1,00

0,00

1,00

2,00

3,00

4,00

4,00

3,00

2,00

1,00

0,00

1,00

2,00

3,00

4,00

Per cent

Per cent

Source: Eurostat, EUROPOP 2008 convergence scenario 

Figure A10 Age-related expenditure profiles 

Source: EPC/EC 2009 Ageing Report  

EN 

154 

   EN 

 
 
 
Figure A11. Pharmaceutical expenditure per capita PPS, 2007 or latest available 

Total pharmaceutical expenditure per capita PPS

S
P
P
a
t
i

p
a
c

r
e
P

600

500

400

300

200

100

0

Bulgaria
Germany
Spain
France
Cyprus
Denmark
Belgium
CzechRepublic
Greece
Italy
Estonia

Latvia
Hungary
Netherlands
Lithuania
Austria

Slovenia
Romania
Slovakia
Portugal
Poland
Sweden
Finland

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)

30

25

20

15

10

5

0

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

AT

SK

BE

ES

CZ

SE

DK

UK

FI

FR

DE

EL

HU

IE

IT

LU

NL

PL

PT

EN 

Source: OECD Health data 

155 

   EN 

 
 
 
 
 
Figure A13. Sleeping and anxiety problems in SE (% of the population) in the early 2000s 

Source: Ministry of Health and Social Affairs, Sweden. See at 
http://ec.europa.eu/health/ph_determinants/life_style/mental/docs/ev_20090427_co06_en.pdf 

EN 

156 

   EN 

 
 
9.4. 

Statistical tables 

1a. At-risk-of-poverty rate by age and gender, 2008

Total population

Total
Men
Women

Children aged 0-17 Total
People aged 18-64 Total
Men
Women
Total
Men
Women

People aged 65+ 

EU27
17p
16p
17p
20p
15p
14p
15p
19p
16p
22p

EU25
16p
15p
17p
19p
15p
14p
15p
19p
16p
21p

BE
15
14
16
17
12
11
13
21
20
22

BG
21
20
23
26
17
16
18
34
27
39

CZ 
9
8
10
13
8
7
9
7
3
10

DK
12
12
12
9
11
11
11
18
17
19

DK(1)
11
11
12
10
12
13
12
10
8
11

DE
15
14
16
15
15
15
16
15
12
18

EE
19
16
22
17
15
15
15
39
25
46

IE
16
15
16
18
14
13
14
21
19
23

EL
20
20
21
23
19
18
19
22
21
24

ES
20
18
21
24
16
15
17
28
25
30

FR
13b
13b
14b
17b
13b
12b
13b
11b
10b
12b

IT
19
17
20
25
16
15
18
21
17
24

CY
16
14
18
14
11
9
13
49
43
54

LV
26
23
28
25
20
19
20
51
45
54

LT
20
18
22
23
17
16
17
29
17
36

LU
13
13
14
20
13
12
14
5
5
6

HU
12
12
12
20
12
12
12
4
3
5

MT
15
14
15
20
12
10
13
22
24
20

NL
11
11
11
13
10
10
10
10
10
9

AT
12
11
13
15
11
10
12
15
12
17

PL
17
17
17
22
16
17
16
12
9
13

PT
18
18
19
23
16
15
17
22
19
24

1a. At-risk-of-poverty threshold (illustrative values), EUR and PPS, 2008
CZ 
3638
7640
5828
12239

EUR '- One-person household
       '- Two adults with two dep. ch
PPS '- One-person household
       '- Two adults with two dep. ch

BE
10788
22654
10146
21307

EU27
:
:
:
:

EU25
:
:
:
:

BG
1303
2736
2801
5881

DK
14497
30443
10529
22110

DK(1)

15917
33426
11561
24277

DE
10953
23001
10627
22317

EE
3328
6989
4652
9770

IE
13760
28896
10949
22993

EL
6480
13608
7249
15223

ES
7753
16282
8391
17622

FR
10538b
22130b
9734b
20441b

IT
9382
19702
9033
18969

CY
10022
21046
11335
23804

LV
2899
6088
4403
9245

LT
2502
5253
4196
8811

LU
18550
38955
16505
34660

HU
2639
5542
3993
8385

MT
5743
12061
7831
16446

NL
11694
24557
11314
23760

AT
11406
23953
11248
23620

PL
2493
5235
3915
8221

PT
4878
10243
5768
12113

Source: SILC 2008, Income data 2007; except for UK, income year 2008 and for IE moving income reference period (2007-2008)
(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

Total population

1b. Relative median at-risk-of-poverty gap by age and gender, 2008
EU27
22p
23p
21p

Total
Men
Women

EU25
21p
22p
21p

BG
27
27
27

BE
17
18
17

Total

Children aged 0-17
People aged 18-64 Total
Men
Women
Total
Men
Women

People aged 65+ 

22p
24p
25p
23p
18p
17p
18p

21p
23p
24p
23p
17p
17p
18p

18
19
20
19
14
15
13

40
30
29
30
18
14
20

CZ 
18
21
15

21
19
22
17
8
7
8

DK
18
19
17

19
25
30
20
8
7
8

DK(1)
22
25
19

22
26
30
23
8
9
8

DE
23
24
21

19
25
27
24
17
18
17

EE
20
24
19

24
27
29
25
15
13
16

IE
19
20
18

20
21
21
21
8
12
6

EL
25
24
25

26
26
26
26
21
20
23

ES
24
25
23

26
26
27
26
19
21
17

FR
18b
19b
17b

15b
21b
23b
20b
12b
11b
13b

IT
23
23
23

24
26
25
26
19
16
20

CY
17
16
17

14
15
14
16
19
18
20

LV
29
27
30

29
30
29
30
27
21
30

LT
26
29
25

28
31
31
29
17
12
18

LU
17
15
18

17
17
14
20
15
15u
15u

HU
17
18
17

17
18
18
18
10
10u
10

MT
18
19
18

17
18
20
17
20
19
20

NL
15
14
17

13
17
17
18
14
12
16

AT
15
16
15

16
17
20
16
14
14
14

PL
21
21
20

22
21
22
21
14
13
14

PT
23
22
23

26
24
23
24
18
17
18

RO(1)
23
22
24
33
20
20
20
26
21
30

RO(1)
1173
2462
1907
4005

RO
32
33
32

39
32
33
31
23
23
23

SI
12
11
14
12
10
11
10
21
12
28

SK
11
10
12
17
10
9
10
10
4
13

FI
14
13
14
12
12
13
11
23
16
28

SE
12
11
13
13
11
11
11
16
10
21

UK
19p
18p
20p
23p
15p
14p
16p
30p
28p
33p

SI
6535
13724
8395
17629

SK
2875
6038
4040
8484

FI
11800
24779
9632
20228

SE
12178
25573
10377
21792

UK
13119p
27550p
11609p
24380p

SI
19
21
19

16
20
22
18
20
18
21

SK
18
21
17

24
19
22
18
9
8u
10

FI
16
17
14

16
19
20
18
11
10
12

SE
18
20
17

18
23
24
23
11
13
11

UK
21p
21p
21p

19p
22p
24p
21p
21p
18p
21p

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).
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
CZ 
3.4

EU27
5p

EU25
4,8p

BG
6.5

S80/S20

BE
4.1

Total

DK
3.6

DK(1)
3.6

DE
4.8

EE
5

IE
4.5

EL
5.9

ES
5.4

FR
4,2b

IT
5.1

CY
4.1

LV
7.3

LT
5.9

LU
4.1

HU
3.6

MT
4

NL
4

AT
3.7

PL
5.1

PT
6.1

RO
7

SI
3.4

SK
3.4

FI
3.8

SE
3.5

UK
5,6p

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).
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.

EN 

157 

EN 

 
  
 
3. Healthy life years : Disability free life expectancy (+ life expectancy at 0, 45, 65) 1997-2008

life expectancy at birth - males
life expectancy at 45 - males
life expectancy at 65 - males
Healthy Life Years at birth - males

life expectancy at birth - females
life expectancy at 45 - females
life expectancy at 65 - females
Healthy Life Years at birth - females

life expectancy at birth - males
life expectancy at 45 - males
life expectancy at 65 - males
Healthy Life Years at birth - males

life expectancy at birth - females
life expectancy at 45 - females
life expectancy at 65 - females
Healthy Life Years at birth - females

eu27
eu27
eu27
eu27

eu27
eu27
eu27
eu27

eu25
eu25
eu25

eu25
eu25
eu25
eu25

Disability free life expectancy at birth - males

eu15

Disability free life expectancy at birth - females
Source: Eurostat - Demography; e: estimate

eu15

1997
:
:
:
:

1998
:
:
:
:

1999
:
:
:
:

2000
:
:
:
:

2001
:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

80.2
:
:
:

80.2
:
:
:

80.4
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

79.7
:
:
:

:

:

79.9
:
:
:

:

:

2002
74.5
31.9
15.9
:

80.9
37.3
19.5
:

75.0
32.3
16.1
:

80.8
37.2
19.4
:

2003
74.6
31.9
15.9
:

80.8
37.2
19.4
:

75.1
32.3
16.1
:

81.1
37.4
19.6
:

2004
75.2
32.5
16.4
:

81.5
37.8
19.9
:

75.7
32.8
16.6
:

81.3
37.6
19.7
:

:

:

2005
75.4
32.6
16.5
:

81.5
37.8
20.0
:

75.9
32.9
16.7
60.8

81.2
37.5
19.6
62.1

:

:

2006
75.8
32.9
16.8
:

82.0
38.2
20.4
:

76.3
33.3
17.1
61.6

81.9
38.1
20.2
62.1

:

:

2007
:
:
:
61,60e

:
:
:
62,30e

:
:
:
:

81.9
:
:
:

:

:

2008
:
:
:
:

:
:
:
:

:
:
:
:

:
:
:
:

:

:

63,2e

63,5e

63,6e

64,3e

64,5e

63,9e

64,4e

65,0e

65,8e

66,0e

EN 

158 

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

1997

74.2
31.6
15.2
66.5

80.7
37.2
19.5
68.3

1997

67.0
26.3
12.3
:

73.8

31.7
14.7
:

1997

70.5

28.1

13.2

:

77.6
34.1

16.7

:

1998

74.4
31.7
15.3
63.3

80.7
37.3
19.6
65,4(e)

1998

67.4
26.4
12.5
:

74.6

32.2
15.1
:

1998

71.2

28.6

13.5

:

78.2
34.5

17.1

:

1999

74.4
31.8
15.5
66.0

81.0
37.4
19.7
68.4

1999

68.3
27.2
12.9
:

75.0

32.5
15.4
:

1999

71.5

28.8

13.7

:

78.3
34.5

17.1

:

BE
BE
BE
BE

BE
BE
BE
BE

BG
BG
BG
BG

BG
BG
BG
BG

CZ
CZ
CZ
CZ

CZ
CZ
CZ
CZ

2001

75.0
32.3
15.9
66.6

81.2
37.7
19.9
68.8

2001

68.6
27.2
13.0
:

75.4

32.8
15.6
:

2001

72.1

29.3

14.0

:

78.6
34.8

17.3

:

2000

74.6
32.0
15.6
65.7

81.0
37.5
19.8
69.1

2000

68.4
27.0
12.7
:

75.0

32.4
15.3
:

2000

71.7

29.0

13.8

:

78.5
34.8

17.3

:

159 

2002

75.1
32.3
15.8
66,9(e)

81.2
37.5
19.7
69,0(e)

2002

68.8
27.3
13.0
:

75.5

32.9
15.7
:

2002

72.1

29.3

13.9

62,8(p)

78.7
34.9

17.3

63,3(p)

2003

75.3
32.5
16.0
67,4(e)

81.1
37.3
19.6
69,2(e)

2004

76.0
33.0
16.4
58,4(bi)

81.8
38.0
20.2
58,10(bi)

2003

68.9
27.3
13.0
:

75.9

33.1
15.9
:

2003

72.0

29.2

13.8

:

78.6
34.7

17.2

:

2004

69.0
27.5
13.2
:

76.2

33.4
16.2
:

2004

72.6

29.7

14.2

:

79.2
35.3

17.6

:

2005

76.2
33.1
16.6
61.7

81.9
38.0
20.2
61.9

2005

69.0
27.2
13.1
:

76.2

33.3
16.1
:

2005

72.9

29.9

14.4

57,9(bi)

79.3
35.3

17.7

59,90(bi)

2006

76.6
33.6
17.0
62.8

82.3
38.5
20.7
62.8

2006

69.2
27.3
13.2
:

76.3

33.5
16.3
:

2006

73.5

30.4

14.8

57.8

79.9
36.0

18.3

59.8

2007

77.1
34.0
17.3
63.3

82.6
38.8
21.0
63.7

2007

69.5
27.5
13.3
:

76.7

33.7
16.4
:

2007

73.8

30.7

15.1

61.3

80.2
36.2

18.5

63.2

2008

:
:
:

:
:
:

2008

69.8
27.9
13.5
:

77.0

34.0
16.7
:

2008

74.1

30.9

15.3

80.5
36.5

18.8

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

DK
DK
DK
DK

DK
DK
DK
DK

DE
DE
DE
DE

DE
DE
DE
DE

EE
EE
EE
EE

EE
EE
EE
EE

1997

73.6

30.9

14.6

61.6

78.6
35.0

18.0

1998

74.0

31.1

14.9

62.4

79.0
35.4

18.3

60,7(e)

61,3(e)

1997

74.1

31.4

15.2

1998

74.6

31.7

15.4

1999

74.2

31.3

15.0

62.5

79.0
35.2

18.1

60.8

1999

74.8

32.0

15.6

2000

74.5

31.6

15.2

62.9

79.2
35.5

18.3

61.9

2000

75.1

32.2

15.8

2001

74.7

31.7

15.2

62.2

79.3
35.6

18.3

60.4

2001

75.6

32.5

16.1

2002

74.8

31.8

15.4

2003

75.0

32.0

15.6

2004

75.4

32.4

15.9

62,8(e)

63,0(e)

68,3(bi)

79.4
35.6

18.2

79.8
35.9

18.5

80.2
36.4

19.0

61,0(e)

60,9(e)

68,80(bi)

2002

75.7

32.6

16.2

2003

75.8

32.7

16.2

61,9(e)

62,1(e)

62,3(e)

63,2(e)

64,1(e)

64,4(e)

65,0(e)

80.5
36.9

19.1

80.8
37.1

19.3

81.0
37.3

19.4

81.2
37.5

19.6

81.5
37.6

19.8

81.3
37.5

19.6

81.3
37.5

19.6

64,3(e)

64,3(e)

64,3(e)

64,6(e)

64,5(e)

64,5(e)

64,7(e)

1997

64.2

24.9

12.5

:

75.9

33.3

16.8

:

1998

63.9

24.2

12.2

:

75.4

32.9

16.5

:

1999

64.7

25.0

12.5

:

76.0

33.5

17.0

:

2000

65.2

25.1

12.6

:

76.2

33.5

17.0

:

2001

64.8

24.8

12.6

:

76.4

33.7

17.3

:

2002

65.2

25.2

12.7

:

77.0

33.9

17.3

:

2003

66.1

25.6

12.7

:

77.1

34.1

17.4

:

2005

76.0

32.8

16.1

68.4

80.5
36.6

19.1

68.2

2005

76.7

33.4

16.9

55(bi)

82.0
38.1

20.1

55,10(bi)

2005

67.3

26.2

13.1

48.0

78.1

35.0

18.0

52.2

2006

76.1

32.8

16.2

67.7

80.7
36.8

19.2

67.1

2006

77.2

33.8

17.2

58.5

82.4
38.5

20.5

58.0

2006

67.4

26.2

13.2

49.4

78.6

35.1

18.3

53.7

2007

76.2

33.0

16.5

67.4

80.6
36.6

19.2

67.4

2007

77.4

34.0

17.4

58.8

82.7
38.7

20.7

58.4

2007

67.2

26.2

13.1

49.5

78.8

35.5

18.5

54.6

2008

76.5

33.3

16.6

81.0
37.1

19.5

2008

77.6

34.2

17.6

82.7
38.6

20.7

2008

68.7

27.2

13.6

79.5

36.0

18.9

2004

76.5

33.3

16.7

:

81.9
38.0

20.1

:

2004

66.4

25.7

13.0

49,8(bi)

77.8

34.6

17.8

53,30(bi)

EN 

160 

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

1997

73.4

30.7

14.0

63.2

78.7

35.2

17.6

:

1997

75.4

32.9

16.2

66.4

80.4

36.8

18.4

68.7

1997

75.2

32.8

16.4

65.5

82.3

38.8

20.5

68.2

IE
IE
IE
IE

IE
IE
IE
IE

EL
EL
EL
EL

EL
EL
EL
EL

ES
ES
ES
ES

ES
ES
ES
ES

1998

73.4

30.9

14.2

64.0

79.1

35.5

17.8

:

1998

75.4

32.8

16.2

66.5

80.3

36.7

18.3

68.3

1998

75.3

32.8

16.2

65.2

82.4

38.7

20.4

68.2

1999

73.4

30.8

14.1

63.9

78.9

35.3

17.6

67.6

1999

75.5

32.9

16.2

66.7

80.5

36.8

18.4

69.4

1999

75.3

32.7

16.2

65.6

82.4

38.7

20.3

69.5

2000

74.0

31.5

14.6

63.3

79.2

35.7

18.0

66.9

2000

75.5

32.8

16.1

66.3

80.6

36.8

18.4

68.2

2000

75.8

33.2

16.7

66.5

82.9

39.2

20.8

69.3

161 

2001

74.5

31.9

15.0

63.3

79.9

36.4

18.5

66.5

2001

76.0

33.2

16.5

66.7

81.0

37.2

18.7

68.8

2001

76.2

33.4

16.9

66.0

83.2

39.4

21.0

2002

75.2

32.4

15.4

2003

75.9

33.0

15.9

2004

76.4

33.4

16.2

63,5(e)

63,4(e)

62,5(bi)

80.5

36.9

18.9

80.8

37.0

19.2

81.4

37.6

19.6

65,9(e)

65,4(e)

64,30(bi)

2002

76.2

33.4

16.6

2003

76.5

33.5

16.7

2004

76.6

33.7

16.9

66,7(e)

66,7(e)

63,7(bi)

81.1

37.2

18.8

81.2

37.2

18.7

81.3

37.5

19.0

68,5(e)

68,4(e)

65,20(bi)

2002

76.3

33.5

16.9

2003

76.3

33.5

16.8

2004

76.9

34.0

17.3

66,6(e)

66,8(e)

62,5(bi)

83.2

39.4

21.0

83.0

39.2

20.8

83.7

39.9

21.5

69,2(e)

69,9(e)

70,2(e)

62,50(bi)

2005

77.3

34.1

16.8

62.9

81.7

37.9

19.9

64.1

2005

76.8

34.0

17.1

65.7

81.6

37.8

19.2

67.2

2005

77.0

34.0

17.3

63.2

83.7

39.7

21.3

63.1

2006

77.4

34.2

16.8

63.2

82.2

38.2

20.3

65.0

2006

77.2

34.3

17.5

66.3

81.9

37.9

19.4

67.9

2006

77.7

34.6

17.9

63.7

84.4

40.4

22.0

63.3

2007

77.4

34.3

17.1

62.7

82.1

38.1

20.1

65.3

2007

77.1

34.2

17.4

65.9

81.8

37.9

19.4

67.1

2007

77.8

34.6

17.8

63.2

84.3

40.4

22.0

62.9

2008

77.5

34.5

17.2

82.3

38.4

20.4

2008

77.7

34.6

17.8

82.4

38.3

19.8

2008

78.0

34.7

18.0

84.3

40.4

21.9

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

2001

75.5

33.0

17.0

60.5

83.0

39.4

21.5

63.3

2001

77.1

34.0

16.9

69.8

83.1

39.2

21.0

2002

75.7

33.1

17.0

2003

75.8

33.1

17.0

2004

76.7

33.9

17.7

60,4(e)

60,6(e)

61,2(bi)

83.0

39.3

21.4

82.7

39.0

21.1

83.8

40.1

22.1

63,7(e)

63,9(e)

64,10(bi)

2002

77.4

34.2

17.0

2003

77.1

34.0

16.8

2004

77.9

34.7

17.5

70,4(e)

70,9(e)

68,4(bi)

83.2

39.3

21.0

82.8

38.8

20.6

83.8

39.9

21.6

73,0(e)

73,9(e)

74,4(e)

70,70(bi)

2001

76.6

33.9
16.8

:

81.4

37.6

19.2

:

2002

76.4

33.7
16.3

:

81.0

37.4

19.0

:

2003

76.9

33.8
16.5

68.4

81.3

37.4

19.1

69.6

2004

76.6

33.7
16.6

:

81.9

37.8

19.4

:

2005

76.7

33.9

17.7

62.0

83.8

40.0

22.0

64.3

2005

78.0

34.8

17.4

65.7

83.6

39.6

21.3

66.5

2005

76.8

34.2
16.8

59,5(bi)

80.9

37.6

19.1

57,90(bi)

2006

77.3

34.4

18.2

62.7

84.5

40.7

22.7

64.1

2006

78.5

35.2

17.9

64.7

84.2

40.1

21.8

64.1

2006

78.4

35.1
17.4

64.3

82.2

38.1

19.5

63.2

2007

77.6

34.6

18.4

63.1

84.8

41.0

23.0

64.2

2008

:

:

:

:

:

:

2007

2008

:

:

:

62,8(e)

:

:

:

62(e)

2007

77.9

34.9
17.4

63.0

82.2

38.4

19.6

62.7

:

:

:

:

:

:

2008

78.5

35.4
17.9

83.1

38.9

20.4

1997

:

:

:

60.2

:

:

:

63.1

1997

75.8

33.0

16.2

68.0

82.0

38.4

20.2

71.3

1997

74.9

32.8
15.7

:

80.0

36.5

18.2

:

FR
FR
FR
FR

FR
FR
FR
FR

IT
IT
IT
IT

IT
IT
IT
IT

CY
CY
CY
CY

CY
CY
CY
CY

1998

74.8

32.4

16.5

59.2

82.6

39.1

21.2

62.8

1998

76.0

33.1

16.2

67.9

82.1

38.4

20.3

71.3

1998

74.7

32.4
15.3

:

79.8

36.2

18.0

:

1999

75.0

32.6

16.6

60.1

82.7

39.2

21.2

63.3

1999

76.5

33.5

16.5

68.7

82.6

38.8

20.5

72.1

1999

76.0

33.5
16.5

:

79.9

36.6

18.3

:

2000

75.3

32.9

16.8

60.1

83.0

39.4

21.4

63,2(e)

2000

76.9

33.8

16.7

69.7

82.8

39.0

20.7

72.9

2000

75.4

32.8
15.9

:

80.1

36.6

18.3

:

162 

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

1997

1998

1999

2000

2001

LV
LV
LV
LV

LV
LV
LV
LV

LT
LT
LT
LT

LT
LT
LT
LT

LU
LU
LU
LU

LU
LU
LU
LU

:

:
:

:

:

:

:

:

1997

65.5

26.0
13.2

:

76.6

34.1

17.3

:

1997

74.0

31.2
14.8

:

80.0

36.7

19.2

:

:

:
:

:

:

:

:

:

1998

66.0

26.2
13.3

:

76.7

34.1

17.4

:

1998

73.7

31.2
15.2

:

80.8

37.3

19.5

:

:

:
:

:

:

:

:

:

1999

66.3

26.4
13.4

:

77.0

34.5

17.6

:

1999

74.4

31.8
15.3

:

81.4

37.5

19.9

:

:

:
:

:

:

:

:

:

2001

65.9

26.2
13.5

:

77.6

34.7

17.9

:

2001

75.1

32.5
16.0

:

80.7

37.4

19.7

:

:

:
:

:

:

:

:

:

2000

66.8

26.7
13.7

:

77.5

34.8

17.9

:

2000

74.6

32.0
15.5

:

81.3

37.7

20.1

:

163 

2002

64.7

24.9
12.5

:

76.0

33.5

17.0

:

2002

66.2

26.1
13.3

:

77.5

34.6

17.8

:

2002

74.7

32.3
15.9

:

81.5

37.7

20.1

:

2003

65.6

25.3
12.6

:

75.9

33.2

16.8

:

2003

66.4

26.2
13.3

:

77.8

34.8

18.1

:

2003

74.8

31.9
15.3

:

80.9

37.0

18.9

:

2004

65.9

25.4
12.6

:

76.2

33.7

17.1

:

2004

66.3

26.1
13.4

:

77.7

34.7

17.9

:

2004

76.0

33.1
16.5

59,1(bi)

82.4

38.5

20.5

60,20(bi)

2005

65.4

25.0
12.5

50,6(bi)

76.5

33.8

17.2

53,10(bi)

2005

65.3

25.3
13.0

51,2(bi)

77.3

34.3

17.6

54,30(bi)

2005

76.7

33.4
16.7

62.2

82.3

38.4

20.4

62.1

2006

65.4

24.9
12.7

50.5

76.3

33.5

17.3

52.2

2006

65.3

25.1
13.0

52.4

77.0

34.2

17.6

56.1

2006

76.8

33.5
17.0

61.0

81.9

38.0

20.3

61.8

2007

65.8

25.2
12.8

50.9

76.5

33.7

17.2

53.7

2007

64.9

24.8
12.9

53.4

77.2

34.4

17.9

57.7

2007

76.7

33.3
16.4

62.2

82.2

38.1

20.3

64.6

2008

67.0

26.1
13.0

77.8

34.6

17.9

2008

66.3

25.8
13.4

77.6

34.6

18.1

2008

78.1

34.6
17.4

83.1

39.0

21.0

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

HU
HU
HU
HU

HU
HU
HU
HU

MT
MT
MT
MT

MT
MT
MT
MT

NL
NL
NL
NL

NL
NL
NL
NL

1997
66.7

25.4

12.5

:

75.5

32.7

16.3

:

1997
75.2

32.1

14.6

:

80.1

36.6

18.4

:

1997
75.2

32.0

15.1

62.5

80.7

37.0

19.3

61.4

1998
66.5

25.3

12.6

:

75.6

32.8

16.4

:

1998
74.9

32.0

14.6

:

80.0

36.3

18.1

:

1998
75.2

32.0

15.1

61.9

80.8

37.1

19.4

61,1(e)

1999
66.7

25.3

12.5

:

75.6

32.6

16.2

:

1999
75.3

32.1

15.0

:

79.4

35.9

17.8

:

1999
75.4

32.1

15.2

61.6

80.5

36.9

19.2

61.4

2001
68.2

26.4

13.2

:

76.7

33.5

17.0

:

2001
76.6

33.4

15.7

:

81.2

37.0

18.7

:

2001
75.8

32.6

15.6

61.9

80.8

37.1

19.4

59.4

2000
67.6

26.0

13.0

:

76.2

33.2

16.8

:

2000
76.2

32.7

15.1

:

80.3

36.5

18.5

:

2000
75.6

32.3

15.4

61.4

80.7

37.0

19.3

60.2

164 

2002
68.3

26.4

13.2

:

76.7

33.6

17.0

:

2002
76.3

33.0

15.3

65,1(p)

81.3

37.3

19.1

65,7(p)

2002
76.0

32.7

15.6

2003
68.4

26.3

13.0

53,5(p)

76.7

33.5

16.9

57,8(p)

2003
76.4

33.2

15.6

:

80.8

36.9

18.7

:

2003
76.3

32.9

15.8

61,7(e)

61,7(e)

80.7

37.0

19.4

81.0

37.2

19.5

59,3(e)

58,8(e)

2004
68.7

26.6

13.4

:

77.2

33.8

17.3

:

2004
77.4

34.1

16.3

:

81.2

37.4

19.1

:

2004
76.9

33.5

16.3

:

81.5

37.7

19.9

:

2005
68.7

26.4

13.3

52(bi)

77.2

33.8

17.2

53,90(bi)

2005
77.3

33.8

16.2

68,5(bi)

81.4

37.5

19.4

70,10(bi)

2005
77.3

33.8

16.4

65(bi)

81.7

37.9

20.1

63,10(bi)

2006
69.2

26.8

13.7

54.2

77.8

34.3

17.7

57.0

2006
77.0

33.6

16.1

68.1

81.9

37.7

19.5

69.2

2006
77.7

34.2

16.8

65.0

82.0

38.1

20.3

63.2

2007
69.4

26.9

13.7

55.0

77.8

34.3

17.8

57.6

2007
77.5

34.4

16.7

69.0

82.2

38.5

20.3

70.8

2007
78.1

34.5

17.1

65.7

82.5

38.6

20.7

63.7

2008
70.0

27.3

14.0

78.3

34.7

18.1

2008
77.1

34.3

17.0

82.3

38.4

20.1

2008
78.4

34.8

17.4

82.5

38.5

20.7

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

AT
AT
AT
AT

AT
AT
AT
AT

PL
PL
PL
PL

PL
PL
PL
PL

PT
PT
PT
PT

PT
PT
PT
PT

1997
74.1

31.4

15.2

62.2

80.7

37.0

19.1

:

1997

68.5

27.1

13.2

:

77.0

33.9

16.8

:

1997

72.2

31.0

14.9

59.3

79.3

36.3

18.4

60.4

1998
74.5

31.7

15.4

63.4

81.0

37.3

19.4

:

1998

68.9

27.4

13.4

:

77.4

34.2

17.1

:

1998

72.4

31.1

15.0

59.1

79.6

36.4

18.5

61.1

1999
74.9

32.0

15.7

63.6

81.0

37.3

19.4

:

1999

68.8

27.3

13.3

:

77.5

34.3

17.1

:

1999

72.6

31.3

15.0

58.8

79.7

36.5

18.5

60.7

2001
75.7

32.8

16.3

64.2

81.7

37.9

20.0

68.5

2001

70.0

28.1

13.7

:

78.4

35.0

17.7

:

2001

73.5

31.9

15.7

59.5

80.5

37.1

19.1

62.7

2000
75.2

32.4

16.0

64.6

81.2

37.5

19.6

68.0

2000

69.6

27.9

13.6

:

78.0

34.7

17.5

:

2000

73.2

31.6

15.4

60.2

80.2

36.9

18.9

62.2

165 

2002
75.8

32.8

16.3

2003
75.9

32.9

16.4

2004
76.4

33.4

16.8

65,6(e)

66,2(e)

58,1(bi)

81.7

37.8

19.8

81.5

37.7

19.7

82.1

38.2

20.2

69,0(e)

69,6(e)

60,20(bi)

2002

70.3

28.4

13.9

62.5

78.8

35.3

18.0

68.9

2002

73.8

31.9

15.7

2003

70.5

28.4

13.9

:

78.8

35.3

18.0

:

2003

74.2

32.0

15.7

2004

70.6

28.5

14.2

:

79.2

35.6

18.4

:

2004

75.0

32.6

16.3

59,7(e)

59,8(e)

55,1(bi)

80.6

37.2

19.2

80.6

37.0

19.0

81.5

37.9

19.7

61,8(e)

61,8(e)

52,00(bi)

2005
76.7

33.6

17.0

57.8

82.2

38.4

20.3

59.6

2005

70.8

28.7

14.3

61(bi)

79.3

35.8

18.5

66,60(bi)

2005

74.9

32.5

16.1

58.4

81.3

37.6

19.4

56.7

2006
77.2

34.0

17.3

58.4

82.8

38.8

20.7

60.8

2006

70.9

28.8

14.5

58.2

79.7

36.1

18.8

62.5

2006

75.5

32.9

16.6

59.6

82.3

38.5

20.2

57.6

2007
77.4

34.2

17.5

58.4

83.1

39.0

21.0

61.1

2007

71.0

28.8

14.6

57.4

79.8

36.2

19.0

61.3

2007

75.9

33.1

16.8

58.3

82.2

38.4

20.2

57.3

2008
77.8

34.5

17.7

83.3

39.3

21.1

2008

71.3

29.1

14.8

80.0

36.4

19.1

2008

76.2

33.3

16.9

82.4

38.6

20.3

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

1997

65.2

25.8

12.7

:

73.3

31.8

15.3

:

1997

71.1

29.0
14.0

:

79.1

35.5

18.0

:

1997
68.9

27.0

12.9

:

76.9

33.7

16.5

:

RO
RO
RO
RO

RO
RO
RO
RO

SI
SI
SI
SI

SI
SI
SI
SI

SK
SK
SK
SK

SK
SK
SK
SK

1998

66.3

26.4

13.0

:

73.8

32.1

15.5

:

1998

71.3

29.1
13.9

:

79.2

35.6

18.1

:

1998
68.6

26.9

12.8

:

77.0

33.8

16.6

:

1999

67.1

26.9

13.0

:

74.2

32.3

15.5

:

1999

71.8

29.3
14.1

:

79.5

35.8

18.3

:

1999
69.0

27.1

13.0

:

77.4

34.0

16.8

:

2001

67.5

27.0

13.3

:

74.9

32.7

16.0

:

2001

72.3

29.8
14.5

:

80.4

36.5

19.0

:

2001
69.5

27.3

13.0

:

77.7

34.1

16.8

:

2000

67.7

27.3

13.4

:

74.8

32.7

15.9

:

2000

72.2

29.7
14.2

:

79.9

36.2

18.7

:

2000
69.2

27.2

12.9

:

77.5

34.1

16.7

:

166 

2002

67.4

26.7

12.9

:

74.7

32.4

15.7

:

2002

72.6

30.0
14.5

:

80.5

36.6

19.0

:

2002
69.8

27.5

13.2

:

77.7

34.3

16.9

:

2003

67.7

26.8

13.1

:

75.0

32.7

15.8

:

2003

72.5

29.8
14.3

:

80.3

36.5

18.8

:

2003
69.8

27.6

13.2

:

77.7

34.3

16.9

:

2004

68.3

27.3

13.3

:

75.5

33.1

16.2

:

2004

73.5

30.7
15.0

:

80.8

37.0

19.4

:

2004
70.3

28.0

13.3

:

78.0

34.5

17.1

:

2005

68.7

27.4

13.4

:

75.7

33.1

16.2

:

2005

73.9

31.1
15.2

56,3(bi)

80.9

37.1

19.3

59,90(bi)

2005
70.2

27.8

13.3

54,9(bi)

78.1

34.5

17.1

56,40(bi)

2006

69.2

27.7

13.6

:

76.2

33.5

16.5

:

2006

74.5

31.6
15.9

57.6

82.0

38.0

20.1

61.0

2006
70.4

28.0

13.3

54.3

78.4

34.8

17.3

54.4

2007

69.7

28.1

13.9

60.4

76.9

33.9

16.9

62.4

2007

74.7

31.8
15.9

58.7

82.0

38.1

20.2

62.3

2007
70.6

28.1

13.6

55.4

78.4

34.9

17.5

55.9

2008

69.7

28.0

14.0

77.2

34.2

17.2

2008

75.5

32.4
16.4

82.6

38.5

20.5

2008
70.8

28.5

13.8

79.0

35.3

17.8

EN 

 
  
 
3. Disability free Life expectancy (+ Life expectancy at 0, 45, 65) by country, 1995-2008 Source: Eurostat – Demography database 

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

Life expectancy at birth - males
Life expectancy at 45 - males
Life expectancy at 65 - males
Healthy Life Years at birth - males

Life expectancy at birth - females
Life expectancy at 45 - females
Life expectancy at 65 - females
Healthy Life Years at birth - females

EN 

1997
73.5

31.0

15.0

55.5

80.7

37.0

19.1

57.6

1997
76.8
33.4
16.3
62.1

82.0
38.1
20.1
60.0

1997
74.7
31.8
15.1
60,9(e)

79.7
36.1
18.5
61,2(e)

1998
73.6

31.0

15.0

55.9

81.0

37.3

19.3

58.3

1998
76.9
33.6
16.4
61.7

82.1
38.2
20.2
61,3(e)

1998
74.8
32.0
15.3
60,8(e)

79.8
36.2
18.6
62,2(e)

1999
73.8

31.2

15.2

55.8

81.2

37.5

19.5

57.4

1999
77.1
33.8
16.5
62.0

82.0
38.0
20.1
61.8

1999
75.0
32.1
15.4
61,2(e)

79.9
36.2
18.6
61,3(e)

FI
FI
FI
FI

FI
FI
FI
FI

SE
SE
SE
SE

SE
SE
SE
SE

UK
UK
UK
UK

UK
UK
UK
UK

2001
74.6

32.0

15.7

56.7

81.7

37.8

19.8

56.9

2001
77.6
34.2
16.9
61.9

82.2
38.2
20.2
61.0

2001
75.8
32.9
16.1
61,1(e)

80.5
36.9
19.2
60,8(e)

2000
74.2

31.7

15.5

56.3

81.2

37.5

19.5

56,8(e)

2000
77.4
34.1
16.8
63.1

82.0
38.0
20.2
61.9

2000
75.5
32.6
15.8
61,3(e)

80.3
36.7
19.0
61,2(e)

167 

2005
75.6

32.8

16.8

51.7

82.5

38.8

21.0

52.4

2005
78.5
34.9
17.4
64.2

82.9
38.8
20.7
63.1

2002
74.9

32.1

15.8

2003
75.2

32.3

16.2

2004
75.4

32.6

16.5

57,0(e)

57,3(e)

53,1(bi)

81.6

37.8

19.8

81.9

38.0

20.0

82.5

38.6

20.7

56,8(e)

56,5(e)

52,90(bi)

2002
77.8
34.3
16.9
62,4(e)

82.2
38.1
20.1
61,9(e)

2002
76.0
33.1
16.2
61,4(e)

80.6
36.9
19.2
60,9(e)

2003
78.0
34.5
17.1
62,5(e)

82.5
38.5
20.4
62,2(e)

2003
76.2
33.2
16.3
61,5(e)

80.5
36.8
19.1
60,9(e)

2004
78.4
34.9
17.5
62(bi)

82.8
38.8
20.7
60,90(bi)

2004
76.8
33.8
16.8
:

81.0
37.3
19.4
:

2005
77.1
34.0
17.0
63,2(bi)

81.2
37.4
19.6
65,00(bi)

2006
75.9

33.1

16.9

52.9

83.1

39.2

21.2

52.7

2006
78.8
35.2
17.7
67.1

83.1
39.0
20.9
67.1

2006
77.3
34.3
17.4
65.0

81.7
38.0
20.1
65.1

2007
76.0

33.2

17.0

56.7

83.1

39.2

21.3

58.0

2007
79.0
35.4
17.9
67.5

83.1
39.0
20.8
66.6

2007
77.6
34.6
17.6
64,8(e)

81.8
38.0
20.2
66,2(e)

2008
76.5

33.7

17.5

83.3

39.3

21.4

2008
:
:
:

:
:
:

2008
:
:
:

:
:
:

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)

2000 total

female
male

2004 total

female
male

2005 total

female
male

2006 total

female
male

2007 total

female
male

EU27

17,6e
15,5e
19,6e

EU25
17,2e
15,0e
19,3e

16.1
13.8
18.4

15.8
13.7
17.8

15.5
13.4
17.6

15.1
13
17.1

15.7
13.3
18.1

15.5
13.3
17.6

15.4
13.1
17.6

14.9
12.7
17.1

BE
13.8
11
16.4

13,1b
10,8b
15,4b

12.9
10.5
15.3

12.6
10
15.1

12.1
10.3
13.9

BG
:
:
:

21.4
20.6
22.2

20.4
20.3
20.6

17.3
17
17.7

14.9
14.7
15.2

CZ

:
:
:

6.3
6.6
6.1

6.2
6.3
6.1

5.1
4.9
5.4

5.2
4.7
5.7

DK

11.7
10.4
12.8

8.8
7.1
10.5

8.7
6.9
10.5

9.1
7.7
10.5

12,5b
9,1b
15,7b

DE

14.6
14.9
14.4

12.1
11.9
12.2

13,5b
13,7b
13,3b

13.6
13.3
13.9

12.5
11.8
13.1

EE

15.1
11,0u
19.4

13.1
7,8u
18.6

13.4
:u
17,1u

13.5
:u
19,8u

14.4
:u
21.7

IE
:
:
:

13.1
10
16

12.5
9.5
15.4

12.1
9
15.3

11.6
8.4
14.7

EL
18.2
13.6
22.9

14.7
11.3
18.1

13.6
9.7
17.6

15.5
10.8
20.2

14.6
10.6
18.6

ES
29.1
23.2
35

32
25.1
38.7

30,8b
24,9b
36,6b

30.5
24
36.7

31
25.2
36.6

FR
13.3
11.9
14.8

12.8
10.8
14.7

12.2
10.3
14.1

12.4
10.6
14.4

12.6
10.3
15.1

IT
25.1
21.7
28.5

22.3
18.3
26.5

22
18.2
25.8

20.6
17.1
23.9

19.7
16.4
22.9

CY
18.5
13.9
25

20.6
14.9
27.2

18,2b
10,4b
27,2b

14.9
8.2
22.5

12.5
6.8
19.5

LV
:
:
:

14.7
9.5
19.8

14.4
10.4
18.2

14.8
10.4
18.9

15.1
10.1
20

LT
16.5
12.8
20

10,5b
8,6u
12,4u

8.1
5,6u
10,7u

8.2
5,8u
10,5u

7.4
5,1u
9,6u

2008 total

female
male

14.9
12.9
16.9

5.6
5.4
5.8
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 the 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)

7.4
4,7u
10,0u

31.9
25.7
38

15.5
10.7
20.2

19.7
16.7
22.6

11.8
11.2
12.4

11.8
9.8
13.8

11.3
8
14.6

14.8
10.9
18.5

11.5
9.2
13.7

14.8
15.5
14.1

12
10.6
13.4

14
8,2u
19.8

14.8
12.6
17

13.7
9.5
19

LU
16.8
17.6
15.9

12.7
12.7
12.6

13.3
9.6
17

14
10.4
17.6

12.5
8,4u
16.6

13.4
10,9u
15.8

HU
13.9
13.4
14.4

12.6
11.5
13.6

12.5
11.3
13.7

12.6
11.4
13.8

11.4
10.1
12.6

11.7
10.9
12.5

MT
54.2
56.1
52.5

42,1b
39,8b
44,3b

38.9
35.5
42.1

39.9
36.8
42.8

38.3
34.9
41.3

39
36.1
41.7

NL
15.4
14.1
16.6

14.1
11.7
16.4

13.5
11.1
15.9

12.6
10.1
15.1

11.7
9.3
14

11.4
8.8
14

AT
10.2
10.7
9.6

9,5i
8,8i
10,2i

9.1
8.7
9.6

9.8
9.7
10

10.7
10.1
11.4

10.1
9.8
10.4

PL
:
:
:

5,6b
3,9b
7,3b

5.3
3.7
6.8

5.4
3.9
6.9

5
3.8
6.2

5
3.9
6.1

PT
43,6p
36,3p
50,9p

39,4p
31,0p
47,7p

38,8p
30,7p
46,7p

39,1p
31,3p
46,6p

36,9p
30,4p
43,1p

35,4p
28,6p
41,9p

RO
22.9
22
23.8

22,4b
21,1b
23,7b

19.6
19.1
20.1

17.9
18
17.8

17.3
17.4
17.1

15.9
16
15.9

SL
:
:
:

4,3u
2,5u
6,0u

4,9u
3,2u
6,5u

5.6
4,0u
7,1u

4,1u
2,2u
5,8u

5,1u
2,6u
7,2u

SK
:
:
:

6.8
6.3
7.3

6.3
5.9
6.7

6.6
5.8
7.3

6.5
5.8
7.2

6
4.9
7.1

FI
9,0i
6,5i
11,5i

10,0i
7,5i
12,5i

10,3i
8,2i
12,4i

9,7i
7,8i
11,8i

9,1i
7,2i
11,2i

9,8i
7,7i
12,1i

SE
7.3
5.8
8.7

9.2
7.8
10.6

10,8b
9,7b
11,9b

12,4p
11,3p
13,5p

11,4p
10,0p
12,6p

11,1p
9,9p
12,3p

UK
18.2
17.5
18.8

12,1i
11,2i
13,0i

11.6
10.6
12.6

11.3
10.2
12.3

16,6b
15,6b
17,6b

17
15.6
18.3

EN 

168 

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)

2001 Children

EU27

10,1e

EU25

10,0e

Adults (18-59)
Total

10,2e

Men

Women

8,9e

11,5e

10,1e

8,8e

11,4e

2002 Children

10,2e

10,0e

Adults (18-59)
Total

10,4e

Men

Women

2003 Children

9,1e

11,6e

10,2e

Adults (18-59)
Total

10,4e

Men

Women

2004 Children

9,2e

11,5e

10,1e

Adults (18-59)
Total

10,4e

Men

Women

9,3e

11,4e

2005 Children

9,9e

Adults (18-59)
Total

10,3e

Men

Women

9,2e

11,3e

2006 Children

9.8

Adults (18-59)
Total

Men

Women

2007 Children

Adults (18-59)
Total

Men

Women

2008 Children

Adults (18-59)
Total

Men

Women

9.8

8.8

10.9

9.4

9.3

8.2

10.3

9.2

9.2

8.2

10.1

10,2e

8,9e

11,4e

10,1e

10,2e

9,0e

11,4e

9,9e

10,2e

9,2e

11,3e

9,7e

10,1e

9,1e

11,2e

9.7

9.7

8.7

10.8

9.3

9.2

8.1

10.3

9.2

9.1

8.1

10.1

BE

11.9

13.3

11.1

15.5

13.1

14

11.7

16.4

13.2

14.4

12.4

16.3

13

13.8

11.6

16

12.8

13.7

11.7

15.7

12.7

13.6

11.8

15.4

12

12.3

10.6

13.9

11.3

12

10.4

13.6

BG

19.6

17.7

17.1

18.3

19.4

17.1

16.8

17.5

17.9

15.9

15.5

16.2

16.5

14.4

14

14.8

15.7

13.7

13.3

14.1

15

12.1

11.6

12.6

12.8

10.2

10.1

10.3

11

9

8.7

9.4

CZ

7.8

7.8

6.2

9.4

7.7

7.3

5.5

9.1

8.6

7.7

5.8

9.7

9.1

8

6.3

9.7

8.2

7.4

5.9

8.9

8.1

7.2

5.7

8.6

8

6.5

4.9

8.1

7.4

6

4.5

7.6

DK

:

:

:

:

5.7

8.4

7.9

8.8

5.7

9.4

8.8

10

6

9.4

9.2

9.5

5.7

8.6

8.4

8.7

5

7.7

7.1

8.3

5.3

8.1

7.6

8.5

3.3

6.8

6.4

7.2

DE

9.6

9.8

9

10.7

10.3

10.3

9.7

10.9

11.1

10.9

10.3

11.5

11.4

11.1

10.8

11.4

11,0b

11,0b

10,7b

11,2b

10.6

10.5

10.2

10.8

9.6

9.5

9.1

9.9

9.3

9

8.6

9.4

EE

11.5

11.3

11.4

11.2

11

10.5

10.7

10.3

8.4

10.2

10.8

9.7

8.7

9.7

10.3

9.1

8.8

8.6

9.7

7.5

6.9

6.6

6.5

6.6

7.2

6

6.1

5.9

6.8

6.2

6.6

5.8

IE

32.1

13.4

9.6

17.2

11.1

8.8

7.5

10

11.8

9.1

7.7

10.4

11.8

8.6

7.2

10

11.9

8.3

6.9

9.8

11.2

7.8

6.5

9.2

11.5

7.9

6.7

9.3

13.1

9.2

8.1

10.3

EL

5.5

9.4

7

11.7

5.3

9.4

7.1

11.7

4.6

9

6.8

11.3

4.7

9.1

6.8

11.3

4.2

8.9

6.7

11.1

3.9

8.1

6

10.3

3.9

8

6

10

3.6

7.5

5.7

9.3

ES

6.6

7.5

6.7

8.3

6.5

7.5

6.8

8.2

6.2

7.3

6.7

8

6.2

7.2

6.6

7.9

5,6b

6,6b

6,1b

7,1b

5.3

6.3

5.8

6.8

5.3

6.2

5.8

6.7

6.5

7.4

7.2

7.7

FR

9.5

10.2

8.8

11.5

9.1

10.1

8.8

11.4

9

10.1

8.9

11.3

8.9

10.2

9

11.3

8.8

10.3

9.2

11.5

9.3

10.5

9.4

11.6

8.8

10

9

11.1

8.5

9.8

8.8

10.8

IT

6.9

10.4

8.7

12.1

7

10

8.4

11.6

6.9

9.6

8.1

11.2

5,9b

9,4b

8,1b

10,8b

5.9

9.8

8.4

11.1

5.7

9.5

8.1

10.9

5.8

9.2

7.9

10.6

6.7

9.6

8.3

10.9

CY

3.4

5

3.5

6.4

3.2

5.2

3.9

6.4

2.6

5.1

4.1

5.9

2.7

5.1

4

6.2

3.6

5.3

4.3

6.2

3.9

5.2

4.3

6.1

3.9

4.7

4.2

5.2

3.9

4.9

4.7

5.2

LV

11.3

13.1

12.4

13.6

10.1

10.3

10.6

10.1

8.1

8.8

8.6

8.9

8.1

8.1

8

8.2

8

8.5

8.7

8.3

7.1

6.7

6.9

6.6

8.3

6.6

6.7

6.6

7.6

6.4

6.2

6.5

LT

:

11.4

11.5

11.4

8.1

8.9

8.7

9.1

7.5

8.2

8.1

8.3

7.1

7.8

7.9

7.7

6.1

6.8

7.1

6.6

6.8

6.9

7.3

6.6

8.3

7

7.3

6.8

9.9

9

9.1

9

LU

3.3

6.6

5.3

8.1

3.6

7.1

6.3

7.9

3.9

7.5

6

9

3.4

7.1

5.7

8.5

2.7

6.7

5.4

8.1

3.7

7.1

5.4

8.9

3.4

7

6

7.9

3.6

7.9

7.2

8.6

HU

13.7

13.2

12

14.4

14.4

13

12

14

13

11.7

11

12.5

13.1

12

11.2

12.8

14.1

12.3

11.5

13

13.7

11.8

10.8

12.7

13.9

11.9

10.8

12.9

14.6

12.5

11.5

13.4

MT

7.4

NL

5.8

7.6

5.6

9.6

7.8

7.9

6.3

9.6

8.8

8.5

6.7

10.4

9.2

8.8

7

10.8

9.1

8.2

6.3

10.1

9.3

7.9

6

9.8

9.2

7.7

6.2

9.3

8.7

8.1

6.5

9.8

6.9

5.4

8.4

5.8

6.8

5.5

8.2

6.8

7.8

6.5

9.1

7.1

7.9

6.6

9.1

6.7

7.9

6.8

9.1

6.4

7.4

6.1

8.6

5.9

6.5

5.3

7.6

4.8

5.9

4.9

6.9

AT

3.8

7.8

6.1

9.4

3.7

7.3

5.9

8.8

4.1

6.8

5.4

8.1

5,2b

8,2b

6,8b

9,5b

5.9

8.4

7.3

9.4

6

7.6

6.5

8.7

5.3

7.1

5.9

8.4

5.3

7

6

8

PL

:

13.6

12.8

14.4

:

15

14.1

15.9

:

15

14

16

:

15.5

14.5

16.5

:

14.8

13.5

16

11.1

13.2

11.9

14.4

9.5

11.6

10.4

12.7

8.2

10.1

8.7

11.5

PT

3.8

4.4

3.7

5.1

4.3

4.8

4.1

5.4

4.7

5.3

4.7

5.9

4.4

5.3

4.9

5.7

4.6

5.7

5.3

6.1

4.6

5.8

5.2

6.3

5.1

5.7

5.3

6.1

4.7

5.5

5.2

5.8

RO

8

9.4

8.5

10.3

10,7b

11,8b

10,6b

12,9b

10.3

11.5

10.4

12.6

12.2

11.8

11

12.6

11.3

11.3

10.3

12.2

10.3

10.3

9.3

11.2

10

10.4

9.3

11.5

9.9

10.5

9.6

11.5

SI

3.8

8.1

7

9.2

3.6

8.2

7.1

9.2

3.9

8.8

7.9

9.7

3.5

7.7

7

8.5

3.1

7.1

6.4

7.8

3.4

7.4

6.4

8.5

2.2

6.5

5.5

7.5

2.6

6.4

5.7

7.1

SK

9.8

10.1

9.6

10.6

11.6

10.5

10

11.1

11.8

10.3

9.6

11

12.7

10.5

9.8

11.2

13.9

10.3

9.6

11

12.1

9.5

8.8

10.1

10.6

8.9

8.1

9.6

8.6

7.5

7

8.1

FI

SE

:

:

:

:

:

:

:

:

5.7

11

11.6

10.3

5.7

11.1

11.2

10.9

6.6

10.5

11

10

4.9

9.5

10.1

9

4.4

9.1

9.6

8.6

4.1

8.1

8.3

7.8

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

UK

17

11.2

9.1

13.3

17.4

11.2

9

13.3

17.1

11

8.9

13

16.4

11

9

12.9

16.5

10.9

8.9

12.8

16.5

10.8

8.8

12.7

16.7

10.7

8.8

12.7

16.4

10.7

8.9

12.5

u = data lack reliability due to low sample size / : = not available or unreliable data / b = break / p = provisional / e: estimate
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 of the reference quarter).
Source : Eurostat, Labour Force Survey

EN 

169 

EN 

 
  
 
6. Projected total public social expenditures
Total age-related public spending: pension, health care, long-term care, education and unemployment transfers (% of GDP) – baseline scenario
http://ec.europa.eu/economy_finance/publications/publication14994_en.pdf

(Table A 134 – The cost of ageing overview)

EU27
23.1

2007

Change 2007 - 2020

Change 2007 - 2060

0.5

4.7

BE
26.5

1.7

6.9

BG
16.6

CZ
17.9

-0.1

-0.7

3.7

5.5

DK
24.8

2.6

2.6

DE
23.6

0

4.8

EE
14.3

0.2

0.4

IE
17.2

1.4

8.9

EL
22.1

ES
19.3

1.9

1.4

15.9

9

FR
28.4

0.9

2.7

IT
26

0.3

1.6

CY
15.4

LV
13.2

LT
15.8

LU
20

HU
21.6

MT
18.2

NL
20.5

1.3

-0.7

-0.7

1.2

-0.3

2.3

2.1

10.8

0.4

5.4

18

4.1

10.2

9.4

AT
26

0.3

3.1

PL
20.5

-2.7

-2.4

PT
24.5

0.8

3.4

RO
13.1

SI
22.5

SK
15.2

FI

24.2

SE

24.2

2

1.8

-0.7

3

-0.3

10.1

12.1

5.2

6.3

2.6

UK

24.2

0.8

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

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).
 : = 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

Aggregate 
replacement ratio  
(Pensions 65-74 
/Earnings 50-59)

Total

Men

Women

0,49p

0,53p

0,49p

0,5p

0,53p

0,49p

0.45

0.44

0.47

BG

0.34

0.37

0.36

CZ 

0.51

0.48

0.55

DK

0.41

0.38

0.44

DK(1)

0.41

0.38

0.44

DE

0.44

0.47

0.48

EE

0.45

0.37

0.55

IE

0.43

0.4

0.54

EL

0.41

0.48

0.44

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL(2)

AT

PL

PT

RO

SI

SK

FI

SE

0.48

0.53

0.47

0,66b

0,69b

0,58b

0.51

0.58

0.39

0.32

0.37

0.36

0.3

0.25

0.34

0.44

0.45

0.46

0.58

0.54

0.59

0.59

0.6

0.6

0.44

0.47

0.45

0.43

0.48

0.51

0.68

0.65

0.69

0.56

0.65

0.53

0.51

0.65

0.49

0.49

0.54

0.45

0.44

0.5

0.4

0.54

0.54

0.55

0.48

0.47

0.48

0.59

0.62

0.55

UK(2)

0,41p

0,42p

0,44p

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).
 : = 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 waiting time, too far to travel), SILC 2008

1st quintile

2nd quintile

3rd quintile

4th quintile

5th quintile

EU

6.6
4.6

3.2

2.5

1.6

BE
1.4

0

0.3

0

0

BG
41.6

19.6

14.6

10.2

8.1

CZ
1

0.6

1.1

0.5

0.6

DK
0.4

0.2

0.5

0.1

0.1

DE
7.1

4.9

2.8

2.3

1.2

EE
14.2

9.4

7.5

6.8

8

IE
5.3

2.1

2.7

1.4

0.9

EL
10

6.9

5.7

4.1

1.1

ES
0.1

0

0.2

0.2

0.2

FR
3.6

1.8

0.8

0.6

0.2

IT
9.2

6

3.5

3.1

1.9

CY
9.2

4.8

2.4

1.9

0.4

LV
26.2

13.8

11.1

8

4.9

LT
10.2

7.8

6.9

6.6

5

LU
1.4

0.3

0.1

0.5

0.3

HU
5.2

3.7

2.2

1.6

0.9

MT
1.2

1.5

0.7

0.7

0.1

NL
0.4

0.3

0.5

0.1

0.3

AT
1

0.7

0.9

0.3

0.4

PL
10.6

8.7

6.5

5.6

4.8

PT
18.7

11.7

9.6

7.3

2.3

RO
20.7

16.9

13.1

8.4

3.2

SI
0.4

0.2

0.1

0.2

0

SK
3.9

1.2

0.8

0.6

0.5

FI
1

1

0.3

0.2

0.1

SE
4.1

3.7

3.3

2.9

2.1

UK
1.2

1.6

1.4

1.5

1.4

Source: SILC(2008)  
* This data should be interpreted with care when comparing levels of across countries due to a problem in the translation of the questionnaire.

8b. Doctor's consultations

EU-27

EU-25

:

:

BE

7.5

CZ

12.9

DK

7.5

EE

6.9

IE

:

EL

:

ES

8.1

FR

6.4

IT

7.0

CY

2.0

LV

5.2

LT

6.8

LU

6.0

HU

12.9

MT

1.9

NL

5.6

AT

6.7

PL

6.6

PT

3.9

SI

7.2

SK

10.4

FI

4.3

SE

2.8

UK

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 contacts in out-patient wards.

EN 

170 

EN 

 
  
 
9. At-risk of poverty rate anchored at a fixed moment in time (poverty threshold of 2005),  2008

Total population

Children aged 0-17
People aged 18-64

People aged 65+ 

Total
Men
Women
Total
Total
Men
Women
Total
Men
Women

EU27 EU25 BE

12p

12p

13p

15p

11p

11p

12p

14p

12p

13p

13p

14p

16p

12p

12p

13p

15p

13p

15

14

16

17

13

11

14

22

21

BG(1)
:

:

:

:

:

:

:

:

:

CZ  DK DK(2) DE
13
6

11

8

6

6

10

6

5

6

3

1

11

11

9

11

11

11

16

14

9

8

8

10

10

10

3

3

13

14

13

14

13

14

13

11

EE

5

6

5

6

6

6

5

3

1

IE

10

10

10

12

10

9

10

9

10

EL

ES

19

18

19

21

17

17

18

20

19

16

15

17

20

13

13

14

21

20

FR

12b

11b

13b

16b

12b

11b

12b

9b

8b

IT

18

17

20

24

16

15

17

20

17

CY LV LT

LU HU MT NL AT

PL

9

8

11

7

6

5

7

32

27

7

7

7

8

7

6

7

8

4

5

5

5

7

5

6

5

2

2

14

13

15

20

13

13

14

6

5

9

10

9

14

9

9

10

3

2

11

11

12

15

9

8

10

17

18

8

8

8

9

7

7

8

7

7

13

12

14

16

11

11

12

16

12

8

9

8

12

8

9

8

4

3

PT RO(1)
17

:

17

18

21

15

14

16

19

17

:

:

:

:

:

:

:

:

SI

9

8

10

8

8

8

7

17

9

SK

5

5

5

9

4

5

4

2

1

FI

11

11

11

9

10

11

9

17

12

21

SE UK

8

8

9

8

8

9

8

9

6

11

15p

14p

16p

17p

12p

11p

13p

23p

20p

25p

2
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.

15p

16p

10b

36

10

22

17

21

18

22

22

22

23

15

16

2

4

4

9

4

7

4

4

6

:

:

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

2000

2002

2004

2006

2007

2008

total
male
female

total
male

female

total

male
female

total
male

female

total
male

female

total

male

female

total

male

female

36.2
47.0
26.1

36.9
47.1

27.4

38.5

48.4
29.1

40.7
50.4

31.6

43.5
52.7

34.9

44.6

53.9

35.9

45.6

55.0

36.8

35.8
46.6
25.5

36.6
46.9

26.9

38.7

48.8
29.2

41.0
50.8

31.8

43.6
52.8

35.0

44.8

54.1

36.1

45.7

55.0

36.9

22.9
32.1
14.0

26.3
36.4

16.6

26.6

36.0
17.5

30.0
39.1

21.1

32.0
40.9

23.2

34.4

42.9

26.0

34.5

42.8

26.3

:
:
:

37.1 52.0 37.7 50.2 41.7 39.0 35.1 28.3 27.7
53.2 61.3 47.2 62.0 60.2 56.0 52.6 32.5 41.4
22.9 42.0 28.3 41.6 23.1 23.5 18.8 24.4 15.0

:
:
:

36.3 39.5 25.1 17.3
48.1 54.4 35.2 27.0
9.6
27.5 28.3 15.5

:
:
:

33.9 28.4 32.1 49.6b 51.5 23.9 22.8 36.2 63.0 49.0
47.5 40.5 41.5 62.9b 59.5 31.8 39.1 38.4 66.1 59.1
34.1 60.0 39.2
20.3 17.1 24.1 38.0b 44.5 16.1

9.4

20.8 36.3 55.7 37.6 46.3 45.3 39.0 37.0 29.9 27.7 49.4 36.0 40.4 26.7 22.2 28.5 38.2 28.8 28.4 50.7 49.5 22.7 21.3 41.6 64.9 50.7
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

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

27.0 40.8 57.9 38.9 51.6 48.0 39.2 39.6 34.7 28.9 49.4 41.7 41.6 28.1 25.6 30.1 42.3 29.1 26.1 51.4 37.3b 24.5 22.8 47.8 68.0 53.4

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
47.2 65.6 44.5
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

32.5 42.7 60.3 41.8 52.4 49.5 39.4 41.3 37.8 30.5b 49.9 47.9 47.1 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
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

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

39.6 45.2 60.7 48.4 58.5 53.1 42.3 44.1 38.1 32.5 53.6 53.3 49.6 33.2 33.6 29.8 47.7 35.5 28.1 50.1 41.7 32.6 33.1 54.5 69.6 57.3
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

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

42.6 46.0 58.6 51.5 60.0 53.8 42.4 44.6 38.2 33.8 55.9 57.7 53.4 32.0 33.1 28.5 50.9 38.6 29.7 50.9 41.4 33.5 35.6 55.0 70.0 57.4

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

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

46.0 47.6 57.0 53.8 62.4 53.6 42.8 45.6 38.2 34.4 54.8 59.4 53.1 34.1 31.4 29.2 53.0 41.0 31.6 50.8 43.1 32.8 39.2 56.5 70.1 58.0

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

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 

171 

EN 

 
  
 
11. In work at-risk-of-poverty rate after social transfers by gender  (Age 18+), 2008

In work

Total 
Men

Women 

EU27 EU25 BE

BG

8p

9p

8p

8p

8p

8p

5

4

5

7

8

7

CZ  DK DK(1) DE
7
4

5

6

3

4

6

4

6

5

6

7

EE

IE

EL

ES

FR

7

6

9

6

7

6

14

16

12

11

12

9

7b

7b

6b

IT

9

11

6

CY LV LT

LU HU MT NL AT

PL

PT RO SI

SK

FI

SE UK

6

6

7

11

11

11

9

9

9

9

10

10

5

6

4

5

6

2

5

5

5

6

6

6

12

12

10

12

12

11

17

19

15

5

6

4

6

6

5

5

5

5

7

7

6

9p

8p

9p

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).
 : = 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

2000

2002

2004

2006

2007

2008

Total
Male
Female

Total
Male
Female

Total
Male
Female

Total
Male
Female

Total

Male

Female

Total
Male

Female

Total

Male

:
:
:

68.6
77.2
60.1

68.6
76.8
60.5

69.8
77.3
62.4

70.3

77.6

63.0

70.5
77.7

63.3

70.9

78.0

68.0
77.4
58.7

68.7
77.5
60.0

69.0
77.4
60.7

70.3
77.9
62.8

70.7

78.1

63.4

70.9
78.2

63.7

71.4

78.4

64.3
Source : Eurostat - Labour Force Survey, Annual averages.
b= break in data series / : = data not available

Female

63.9

63.5
72.8
54.0

65.1
73.7
56.4

64.8
73.2
56.3

66.7
73.9
59.5

66.5

73.4

59.5

67.1
73.6

60.4

67.1

73.3

60.8

:
:
:

72.0 79.7 70.8 72.2 65.6 63.2 63.0 68.4 59.0
80.0 83.8 79.2 79.0 78.2 77.6 77.3 75.2 73.6
64.0 75.6 62.2 66.4 52.9 49.0 48.9 61.9 44.6

:
:
:

69.8 72.1 62.1 58.7
76.4 78.2 75.9 66.6
63.9 66.5 48.1 51.2

:
:
:

73.0 71.0 65.7 70.6b 68.9 68.2 69.3 72.3 76.2 75.4
82.6 80.3 72.8 79.3b 75.7 72.6 77.2 75.6 79.0 83.2
63.2 61.7 58.8 62.3b 62.3 63.6 61.7 69.1 73.5 67.4

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
66.2 79.1 84.2 78.9 75.6 79.9 77.4 78.8 75.2 74.1 81.4 72.7 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
55.6 63.6 75.6 63.3 65.3 56.3 50.5 52.0 62.4 46.3 57.7 62.1 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

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
66.4 78.6 83.6 78.8 74.6 79.2 77.6 79.1 75.5 74.3 81.3 74.1 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
57.5 62.7 75.5 64.4 64.4 57.8 51.0 53.1 63.0 47.9 61.8 63.9 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

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
67.0 78.4 83.6 80.6b 73.6 80.6 79.2 80.9b 75.3 74.6 82.9 74.4 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
57.3 62.4 75.9 68.0b 66.9 60.8 54.5 58.3b 64.8 50.4 62.5 65.1 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

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

68.8 78.3 84.1 81.3 75.8 81.5 79.1 81.3 75.0 74.6 82.7 76.2 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

60.2 62.3 77.0 69.3 69.3 61.9 55.0 60.2 64.9 50.8 63.8 66.7 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

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
70.6 78.1 83.9 81.8 77.5 81.4 79.1 81.4 74.8 74.4 82.9 77.6 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

62.1 61.5 76.4 70.1 68.7 63.3 54.9 61.4 65.3 50.7 65.4 68.3 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

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

72.5 78.1 84.4 82.1 78.3 80.7 79.1 81.8 74.8 74.4 82.0 78.6 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

63.1 61.0 77.1 70.8 70.1 63.1 55.1 63.2 65.6 51.6 65.7 70.5 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

EN 

172 

EN 

 
  
 
13. Dispersion of regional employment rates*, selected years (%)
EU27
13.0

EU25
:

BG
:

BE
7.9

2000

2004

2005

2006

2007

12.1

11.9

11.4

11.1

:

:

:

:

8.7

8.4

8.7

8.6

6.9

7.2

7.3

7.1

* 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

CZ
5.8

5.6

5.5

5.2

4.6

DK DE
5.4

:

EE
-

IE
:

:

:

:

:

6.0

5.6

5.2

4.8

-

-

-

-

:

:

:

:

EL
5.1

4.1

4.3

3.7

3.5

ES
10.7

8.7

8.3

7.8

7.5

FR
6.9

7.1

7.2

7.4

6.6

IT
17.5

15.6

16.0

16.0

16.3

CY LV LT
-

-

-

LU HU MT NL AT
2.5
-

2.2

9.0

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

9.4

9.9

9.1

9.7

-

-

-

-

2.3

2.0

2.2

2.2

3.5

4.1

3.4

3.8

14. Total health expenditure per capita PPS

EU

BE

BG

CZ

DK DE

EE

FR

IT

CY LV LT

LU HU MT NL AT

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

1219

1353

1442

1454

1485

1553

1628

1683

1748

1883

2071

2133

2295

2663

2786

2832

2877

:

:

:

:

:

:

:

:

:

:

:

:

:

:

526

547

600

624

:

503

492

520

690

733

754

777

788

793

812

854

929

1021

1131

1167

1217

1258

:

1516

1604

1713

1813

1924

1906

1992

2091

2195

2205

Source: OECD health data and Eurostat
AMECO PPS

1387

1588

1447

:

1524

1808

1594

1792

1667

1911

1569

1907

1676

2032

1761

2062

1863

2127

1973

2243

2071

2326

2165

2411

2304

2510

2393

2609

2571

2660

2639

2804

2795

2887

:

:

:

:

:

:

:

:

:

:

:

:

:

566

639

696

786

IE

709

805

922

934

EL

766

794

890

977

1003

1102

ES

783

866

941

976

999

1301

1221

1412

1339

1508

1393

1575

1379

1627

1382

1009

1059

1000

1762

1289

1084

1102

1058

1831

1366

1192

1158

1110

1902

1477

1284

1184

1184

1977

1566

1406

1270

1255

2073

1626

1572

1262

1338

2214

1787

1827

1507

1405

2334

1901

2023

1680

1492

2497

1900

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

623

697

810

:

:

:

:

:

:

1602

1686

1686

1784

2063

2224

2350

2634

:

520

563

565

637

553

558

580

654

701

742

833

952

3853

1099

4229

1116

4377

1205

:

:

1243

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

1272

1453

1380

1562

1468

1677

1505

1786

1543

1923

1508

1858

1578

1932

1638

2065

1759

2202

1884

2336

2035

2459

2194

2468

2421

2613

2607

2707

2773

2860

2876

2894

2990

2975

:

:

2131

1715

1705

2524

1920

1250

2318

1762

1791

2623

2020

1247

2371

1971

1899

2766

2123

1301

694

2500

2122

2052

2849

2227

1363

:

:

:

2844

2265

:

:

2232

:

PL
6.9

6.4

5.6

5.1

4.5

PL

261

314

335

334

337

344

405

425

479

496

507

551

626

633

680

717

767

:

PT RO SL
:
4.6
4.3

3.5

3.3

3.1

3.3

4.9

4.5

3.6

4.6

:

:

:

:

SK
9.1

9.0

9.8

8.6

8.3

FI
6.8

5.5

5.5

5.4

5.6

SE UK
7.1
4.5

4.4

3.0

2.9

2.4

5.9

5.7

5.5

5.4

PT RO SI

SK

FI

SE UK

561

669

735

771

800

868

945

1014

1036

1150

1314

1346

1417

1542

1611

1759

1832

:

:

:

:

:

:

:

:

:

:

:

:

:

:

323

368

405

408

:

:

:

:

:

:

:

:

:

:

:

:

:

:

1497

1565

1647

:

:

:

:

:

:

:

381

381

354

371

397

440

486

670

954

1227

1433

1367

1437

864

955

1379

1483

1057

1252

1493

1087

1233

1496

1165

1242

1463

1131

1315

1577

1216

1373

1612

1272

1426

1697

1335

1513

1843

1452

1614

1989

1596

1689

2154

1720

1833

2305

1873

1867

2400

1964

2030

2494

2153

2127

2487

2255

1719

1101

2213

2635

2404

:

:

:

:

2486

EN 

173 

EN 

 
  
 
Context 1: Growth rate of GDP volume - percentage change over previous year

2000

2006

2007

2008

2009f

2010f

2011f

EU27

EU25

3.9

3.2

2.9

0.8

-4.1

0.7

1.6

3.9

3.2

2.8

0.7

-4.1

0.7

1.6

BE

3.7

2.8

2.9

1.0

-2.9

0.6

1.5

BG

5.4

6.3

6.2

6.0

-5.9

-1.1

3.1

CZ

3.6

6.8

6.1

2.5

-4.8

0.8

2.3

DK

3.5

3.4

1.7

-0.9

-4.5

1.5

1.8

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)

2000
2006
2007
2008
2009f
2010f
2011f

EU27
100
100
100
100
100
100
100

EU25
105.0
103.9
103.7
103.4
:
:
:

BE
126.1
117.7
115.7
115.1
115.6
115.1
114.5

BG
27.8
36.5
37.7
41.3
38.3
38.0
38.8

CZ
68.5
77.0
80.1
80.3
78.0
78.2
78.7

DK
131.6
124.2
121.3
120.1
114.4
115.6
115.9

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

2000

2002

2004

2005

2006

2007

2008

total
male
female

total
male
female

total
male
female

total
male
female

total
male
female

total
male
female

total
male
female

62.2
70.8
53.7

62.4
70.4
54.4

63.0
70.4
55.6

63.5
70.8
56.3

64.5
71.6
57.3

65.4
72.5
58.3

65.9
72.8
59.1

62.4
71.3
53.6

62.8
71.0
54.7

63.4
71.0
55.8

64.0
71.4
56.6

64.8
72.1
57.6

65.8
73.0
58.6

66.3
73.2
59.4

60.5
69.5
51.5

59.9
68.3
51.4

60.3
67.9
52.6

61.1
68.3
53.8

61.0
67.9
54.0

62.0
68.7
55.3

62.4
68.6
56.2

50.4
54.7
46.3

50.6
53.7
47.5

54.2
57.9
50.6

55.8
60.0
51.7

58.6
62.8
54.6

61.7
66.0
57.6

64.0
68.5
59.5

65.0
73.2
56.9

65.4
73.9
57.0

64.2
72.3
56.0

64.8
73.3
56.3

65.3
73.7
56.8

66.1
74.8
57.3

66.6
75.4
57.6

Source : Eurostat - Labour Force Survey, Annual averages.
b= break in data series

DK

76.3
80.8
71.6

75.9
80.0
71.7

75.7
79.7
71.6

75.9
79.8
71.9

77.4
81.2
73.4

77.1
81.0
73.2

78.1
81.9
74.3

DE

3.2

3.2

2.5

1.3

-5.0

1.2

1.7

DE
118.5
116.1
115.8
115.6
112.7
113.8
114.3

EE

10.0

10.0

7.2

-3.6

-13.7

-0.1

4.2

EE
45.0
65.1
68.8
67.4
58.7
58.5
60.1

DE

EE

65.6
72.9
58.1

65.4
71.8
58.9

65.0
70.8
59.2

66,0b
71,3b
60,6b

67.5
72.8
62.2

69.4
74.7
64.0

70.7
75.9
65.4

60.4
64.3
56.9

62.0
66.5
57.9

63.0
66.4
60.0

64.4
67.0
62.1

68.1
71.0
65.3

69.4
73.2
65.9

69.8
73.6
66.3

IE

9.4

5.4

6.0

-3.0

-7.5

-1.4

2.6

IE
130.9
145.5
148.1
135.4
132.7
130.2
131.6

IE

65.2
76.3
53.9

65.5
75.4
55.4

66.3
75.9
56.5

67.6
76.9
58.3

68.6
77.7
59.3

69.1
77.4
60.6

67.6
74.9
60.2

EL

4.5

4,5(p)

4,5(p)

2,0(p)

-1.1

-0.3

0.7

EL
84.1
93,0p
92,8p
94,3p
95.4
94.5
93.4

EL

56.5
71.5
41.7

57.5
72.2
42.9

59.4
73.7
45.2

60.1
74.2
46.1

61.0
74.6
47.4

61.4
74.9
47.9

61.9
75.0
48.7

ES

5.0

4.0

3.6

0.9

-3.7

-0.8

1.0

ES
97.4
104.6
105.0
102.6
101.0
99.0
97.9

ES

56.3
71.2
41.3

58.5
72.6
44.4

61.1
73.8
48.3

63,3b
75,2b
51,2b

64.8
76.1
53.2

65.6
76.2
54.7

64.3
73.5
54.9

FR

3.9

2.2

2.3

0.4

-2.2

1.2

1.5

FR
115.4
108.8
108.5
107.9
107.3
107.7
107.3

IT

3.7

2.0

1.6

-1.0

-4.7

0.7

1.4

IT
116.9
104.2
103.4
102.0
96.0
96.0
95.6

CY

5.0

4.1

5.1

3.6

-0.7

0.1

1.3

CY
88.8
90.7
93.6
95.8
94.3
93.3
92.4

LV

6.9

12.2

10.0

-4.6

-18.0

-4.0

2.0

LV
36.7
51.6
55.7
57.3
46.3
44.6
45.1

LT

3.3

7.8

9.8

2.8

-18.1

-3.9

2.5

LT
39.3
55.3
59.3
61.9
51.6
49.8
50.6

LU

8.4

5.6

6.5

0.0

-3.6

1.1

1.8

LU
243.7
272.2
275.2
276.3
260.5
259.8
257.9

HU

4.9

4.0

1.0

0.6

-6.5

-0.5

3.1

HU
55.3
63.2
62.6
64.4
59.8
59.4
60.4

MT

:

3.5

4.0

2.1

-2.2

0.7

1.6

MT
83.6
76.8
76.4
76.3
77.6
77.3
76.9

NL

3.9

3.4

3.6

2.0

-4.5

0.3

1.6

AT

3.7

3.5

3.5

2.0

-3.7

1.1

1.5

PL

4.3

6.2

6.8

5.0

1.2

1.8

3.2

NL
134.3
131.2
132.2
134.0
128.5
128.0
127.8

AT
131.4
124.4
122.8
123.3
122.4
122.9
122.7

PL
48.3
51.9
54.4
56.4
57.9
58.8
59.8

PT

3.9

1.4

1.9

0.0

-2.9

0.3

1.0

PT
78.0
76.4
75.6
76.0
74.6
74.5
74.1

RO

2.4

7.9

6.3

7.3

-8.0

0.5

2.6

RO
26.1
38.4
41.6
48.0
43.1
43.3
43.9

SL

4.4

5.8

6.8

3.5

-7.4

1.3

2.0

SL
79.8
87.6
88.6
90.9
87.1
87.9
88.2

SK

1.4

8.5

10.6

6.2

-5.8

1.9

2.6

FI

5.1

4.9

4.2

1.0

-6.9

0.9

1.6

SE

4.4

4.2

2.5

-0.2

-4.6

1.4

2.1

UK

3.9

2.9

2.6

0.5

-4.6

0.9

1.9

SK
50.1
63.4
67.7
72,2e
67.8
68.8
68.8

FI
117.2
115.0
118.0
117.2
109.4
109.7
109.7

SE
126.7
121.1
122.8
120.0
116.0
117.0
117.8

UK
119.0
120.3
116.7
116.2
113.7
113.5
113.3

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SL

SK

FI

SE

UK

62.1
69.2
55.2

63.0
69.5
56.7

63.8
69.5
58.3

63.7
69.2
58.4

63.7
68.9
58.6

64.3
69.2
59.7

64.9
69.6
60.4

53.7
68.0
39.6

55.5
69.1
42.0

57,6b
70,1b
45,2b

57.6
69.9
45.3

58.4
70.5
46.3

58.7
70.7
46.6

58.7
70.3
47.2

65.7
78.7
53.5

68.6
78.9
59.1

68.9
79.8
58.7

68.5
79.2
58.4

69.6
79.4
60.3

71.0
80.0
62.4

70.9
79.2
62.9

57.5
61.5
53.8

60.4
64.3
56.8

62.3
66.4
58.5

63.3
67.6
59.3

66.3
70.4
62.4

68.3
72.5
64.4

68.6
72.1
65.4

59.1
60.5
57.7

59.9
62.7
57.2

61.2
64.7
57.8

62.6
66.1
59.4

63.6
66.3
61.0

64.9
67.9
62.2

64.3
67.1
61.8

62.7
75.0
50.1

63.4
75.1
51.6

62.5
72.8
51.9

63.6
73.3
53.7

63.6
72.6
54.6

64.2
72.3
56.1

63.4
71.5
55.1

56.3
63.1
49.7

56.2
62.9
49.8

56.8
63.1
50.7

56.9
63.1
51.0

57.3
63.8
51.1

57.3
64.0
50.9

56.7
63.0
50.6

54.2
75.0
33.1

54.4
74.7
33.9

54.0
75.1
32.7

53.9
73.8
33.7

53.6
73.3
33.4

54.6
72.9
35.7

55.3
72.5
37.4

72.9
82.1
63.5

74.4
82.4
66.2

73.1
80.2
65.8

73.2
79.9
66.4

74.3
80.9
67.7

76.0
82.2
69.6

77.2
83.2
71.1

68.5
77.3
59.6

68.7
76.4
61.3

67,8b
74,9b
60,7b

68.6
75.4
62.0

70.2
76.9
63.5

71.4
78.4
64.4

72.1
78.5
65.8

55.0
61.2
48.9

51.5
56.9
46.2

51.7
57.2
46.2

52.8
58.9
46.8

54.5
60.9
48.2

57.0
63.6
50.6

59.2
66.3
52.4

68.4
76.5
60.5

68.8
76.5
61.4

67.8
74.2
61.7

67.5
73.4
61.7

67.9
73.9
62.0

67.8
73.8
61.9

68.2
74.0
62.5

63.0
68.6
57.5

57,6b
63,6b
51,8b

57.7
63.4
52.1

57.6
63.7
51.5

58.8
64.6
53.0

58.8
64.8
52.8

59.0
65.7
52.5

62.8
67.2
58.4

63.4
68.2
58.6

65.3
70.0
60.5

66.0
70.4
61.3

66.6
71.1
61.8

67.8
72.7
62.6

68.6
72.7
64.2

56.8
62.2
51.5

56.8
62.4
51.4

57.0
63.2
50.9

57.7
64.6
50.9

59.4
67.0
51.9

60.7
68.4
53.0

62.3
70.0
54.6

67.2
70.1
64.2

68.1
70.0
66.2

67.6
69.7
65.6

68.4
70.3
66.5

69.3
71.4
67.3

70.3
72.1
68.5

71.1
73.1
69.0

73.0
75.1
70.9

73.6
74.9
72.2

72.1
73.6
70.5

72,5b
74,4b
70,4b

73.1
75.5
70.7

74.2
76.5
71.8

74.3
76.7
71.8

71.2
77.8
64.7

71.4
77.7
65.2

71.7
77.9
65.6

71.7
77.7
65.8

71.6
77.5
65.8

71.5
77.5
65.5

71.5
77.3
65.8

EN 

174 

EN 

 
  
 
Context 2b: Unemployment rate (% of labour force aged 15+)

EU27

EU25

BE

BG

CZ

DK

2000

2002

2004

2005

2006

2007

2008

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

8.7
7.8
9.8

8.9
8.3
9.7

9.1
8.5
9.8

8.9
8.3
9.6

8.2
7.6
8.9

7.1
6.6
7.8

7.0
6.6
7.5

8.6
7.6
9.9

8.8
8.1
9.7

9.1
8.4
9.9

9.0
8.3
9.8

8.2
7.5
9.0

7.2
6.6
7.9

7.1
6.6
7.6

6.9
5.6
8.5

7.5
6.7
8.6

8.4
7.5
9.5

8.5
7.6
9.5

8.3
7.4
9.3

7.5
6.7
8.5

7.0
6.5
7.6

16.4
16.7
16.2

18.2
18.9
17.3

12.1
12.6
11.5

10.1
10.3
9.8

9.0
8.7
9.3

6.9
6.5
7.3

5.6
5.5
5.8

8.7
7.3
10.3

7.3
6.0
9.0

8.3
7.1
9.9

7.9
6.5
9.8

7.2
5.8
8.9

5.3
4.2
6.7

4.4
3.5
5.6

4.3
3.9
4.8

4.6
4.3
5.0

5.5
5.1
6.0

4.8
4.4
5.3

3.9
3.3
4.5

3.8
3.5
4.2

3.3
3.0
3.7

Source:  Eurostat - LFS adjusted series, Annual average
p = provisional value /  b = break in data series

Context 2c: Youth unemployment rate (% of labour force aged 15-24)

EU27

EU25

BE

BG

CZ

DK

2000

2002

2004

2005

2006

2007

2008

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

17.4
16.6
18.2

18
17.9
18.1

18.5
18.4
18.7

18.3
18.3
18.4

17.1
16.9
17.4

15.3
15.1
15.6

15.4
15.6
15.3

17
16.1
18.1

17.5
17.3
17.8

18.3
18
18.6

18.2
18.1
18.4

16.9
16.7
17.3

15.2
14.9
15.5

15.4
15.5
15.2

16.7
14.5
19.5

17.7
17.2
18.3

21.2
20.2
22.4

21.5
21
22.1

20.5
18.8
22.6

18.8
17.1
20.9

18
17.3
18.7

33.7
36.1
30.7

37
40.1
33.2

25.8
27
24.3

22.3
23.4
21

19.5
18.9
20.3

15.1
14.5
15.9

12.7
13.7
11.4

17.8
18.5
17

16.9
16.6
17.2

21
22.2
19.5

19.2
19.3
19.1

17.5
16.6
18.7

10.7
10.6
11

9.9
9.8
9.9

6.2
6.6
5.7

7.4
7.3
7.5

8.2
8.9
7.4

8.6
8.6
8.6

7.7
7.9
7.5

7.9
8.2
7.5

7.6
6.9
8.4

DE

7.5
7.5
7.5

8.4
8.8
7.9

9.8
10.3
9.1

10.7
11.2
10.1

9.8
10.2
9.5

8.4
8.5
8.3

7.3
7.4
7.2

DE

7.5
8.8
6.2

9.1
11.4
6.7

11.9
13.7
10

14.2
15.8
12.4

12.8
14.2
11.3

11.1
12.2
10

9.9
10.7
9

EE

12.8
13.8
11.7

10.3
10.8
9.7

9.7
10.4
8.9

7.9
8.8
7.1

5.9
6.2
5.6

4.7
5.4
3.9

5.5
5.8
5.3

EE

23.9
23.8
24.1

17.6
14.3
22.5

21.7
21.2
22.4

15.9
16.6
14.9

12
10
14.7

10
12.1
7.1

12
12.6
11.3

IE

4.3
4.4
4.2

4.5
4.7
4.1

4.6
4.9
4.1

4.4
4.6
4.0

4.5
4.6
4.2

4.6
4.9
4.2

6.0
7.1
4.6

IE

6.9
6.8
7.1

8.5
9.2
7.6

8.9
9.3
8.5

8.6
9.1
8

8.6
9.1
8.1

9
9.9
8

12.7
15.3
9.8

EL

11.2
7.4
17.1

10.3
6.8
15.7

10.5
6.6
16.2

9.9
6.1
15.3

8.9
5.6
13.6

8.3
5.2
12.8

7.7
5.1
11.4

EL

29.1
21.5
38.1

26.8
19.9
35.3

26.9
19.1
36.3

26
18.7
34.8

25.2
17.7
34.7

22.9
15.7
32.1

22.1
17
28.9

ES

11.1
7.9
16.0

11.1
8.1
15.7

10.6
8.0
14.3

9.2
7.1
12.2

8.5
6.3
11.6

8.3
6.4
10.9

11.3
10.1
13.0

ES

24.3
18.1
32.5

24.2
19.2
31.1

23.9
19.4
30.1

19.7
16.7
23.4

17.9
15
21.6

18.2
15.2
21.9

24.6
23.7
25.8

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

9.0
7.5
10.8

8.6
7.7
9.7

9.3
8.4
10.3

9.3
8.4
10.3

9.2
8.4
10.1

8.4
7.8
9.0

7.8
7.3
8.4

FR

19.6
17.6
21.9

19.3
17.8
21.1

20.6
19.9
21.5

21.1
20
22.4

22.1
20.9
23.7

19.6
18.9
20.3

19.1
19.2
19

10.1
7.8
13.6

8.6
6.7
11.5

8.0
6.4
10.5

7.7
6.2
10.0

6.8
5.4
8.8

6.1
4.9
7.9

6.7
5.5
8.5

IT

27
23.1
31.9

23.1
19.4
27.8

23.5
20.6
27.2

23.9
21.5
27.4

21.7
19.1
25.3

20.3
18.2
23.3

21.2
18.9
24.7

4.9
3.2
7.2

3.6
2.9
4.5

4.7
3.6
6.0

5.3
4.3
6.5

4.6
4.0
5.4

4.0
3.4
4.6

3.6
3.1
4.2

CY

10.1
6.9
13

8.1
7.9
8.3

10.5
9.4
11.6

13
11.9
14.2

10.5
9.9
11.2

10.1
10.7
9.5

8.8
8.4
9.3

13.7
14.4
12.9

12.2
13.3
10.9

10.4
10.6
10.2

8.9
9.1
8.7

6.8
7.4
6.2

6.0
6.4
5.6

7.5
8.0
6.9

LV

21.4
21.2
21.6

22
20.4
24.2

18.1
16
21.3

13.6
11.8
16.2

12.2
10.5
14.7

10.7
11.2
10

13.1
13.2
13.1

16.4
18.6
14.1

13.5
14.2
12.7

11.4
11.0
11.8

8.3
8.2
8.3

5.6
5.8
5.4

4.3
4.3
4.3

5.8
6.1
5.6

LT

30.6
32.3
28.3

22.4
22.6
22.2

22.7
22.5
22.9

15.7
15.9
15.3

9.8
10
9.6

8.2
7
10

13.4
12.6
14.6

2.2
1.8
2.9

2.6
2.0
3.5

5.0
3.6
6.8

4.6
3.6
6.0

4.6
3.6
6.0

4.2
3.4
5.1

4.9
4.1
5.9

LU

6.6
6
7.2

7
5.8
8.6

16.4
12
21.5

14.3
12.3
16.9

15.8
16.3
15.2

15.6
13.7
18.2

17.3
13.4
21.9

6.4
7.0
5.6

5.8
6.2
5.4

6.1
6.1
6.1

7.2
7.0
7.4

7.5
7.2
7.8

7.4
7.1
7.7

7.8
7.6
8.1

6.7
6.4
7.4

7.5
6.6
9.3

7.4
6.6
9.0

7.2
6.4
8.9

7.1
6.3
8.7

6.4
5.9
7.5

5.9
5.6
6.6

2.8
2.2
3.6

2.8
2.5
3.1

4.6
4.3
4.8

4.7
4.5
5.1

3.9
3.5
4.4

3.2
2.8
3.6

2.8
2.5
3.0

3.6
3.1
4.3

4.2
4.0
4.4

4.9
4.5
5.4

5.2
4.9
5.5

4.8
4.3
5.2

4.4
3.9
5.0

3.8
3.6
4.1

16.1
14.4
18.2

20.0
19.2
21.0

19.0
18.2
20.0

17.8
16.6
19.2

13.9
13.0
14.9

9.6
9.0
10.4

7.1
6.4
8.0

4.0
3.2
5.0

5.1
4.2
6.1

6.7
5.9
7.7

7.7
6.8
8.8

7.8
6.6
9.1

8.1
6.7
9.7

7.7
6.6
9.0

7.3
8.0
6.5

8.6
9.2
7.9

8.1
9.1
6.9

7.2
7.8
6.4

7.3
8.2
6.1

6.4
7.2
5.4

5.8
6.7
4.7

SL

6.7
6.5
7.0

6.3
5.9
6.8

6.3
5.9
6.9

6.5
6.1
7.1

6.0
4.9
7.2

4.9
4.0
5.9

4.4
4.0
4.8

SK

FI

18.8
18.9
18.6

18.7
18.6
18.7

18.2
17.4
19.2

16.3
15.5
17.2

13.4
12.3
14.7

11.1
9.9
12.7

9.5
8.4
10.9

9.8
9.1
10.6

9.1
9.1
9.1

8.8
8.7
8.9

8.4
8.2
8.6

7.7
7.4
8.1

6.9
6.5
7.2

6.4
6.1
6.7

SE

5.6
5.9
5.3

6.1
6.4
5.8

7.7
7.9
7.5

7.7
7.8
7.7

7.1
6.9
7.3

6.2
5.9
6.5

6.2
5.9
6.6

UK

5.4
5.9
4.8

5.1
5.7
4.5

4.7
5.1
4.2

4.8
5.2
4.3

5.4
5.8
4.9

5.3
5.6
5.0

5.6
6.1
5.1

HU

MT

NL

AT

PL

PT

RO

SL

SK

FI

SE

UK

12.4
13.6
10.8

12.7
13.2
11.9

15.5
16.2
14.4

19.4
19.6
19

19.1
18.6
19.8

18
17.6
18.6

19.9
19.1
20.9

13.7
14.9
12.3

17.1
17.6
16.7

16.8
16.3
17.4

16.2
16.6
15.8

16.5
17.8
14.9

13.8
15.7
11.6

11.9
13.6
9.8

5.7
4.9
6.5

5
5.2
4.8

8
7.9
8.1

8.2
8
8.4

6.6
6.1
7.1

5.9
5.6
6.2

5.3
5.4
5.2

5.3
4.7
6

6.7
6.4
7.1

9.7
9.3
10.2

10.3
10.7
9.9

9.1
8.9
9.3

8.7
8.3
9.1

8
7.9
8.2

35.1
33.4
37.1

42.5
41.9
43.3

39.6
37.7
41.9

36.9
35.7
38.3

29.8
28.3
31.6

21.7
20
23.8

17.3
15.2
19.9

8.6
6.2
11.6

11.6
9.8
13.9

15.3
13.5
17.6

16.1
13.6
19.1

16.3
14.5
18.4

16.6
13.5
20.3

16.4
13.3
20.2

20
22.2
17.2

23.2
24.3
21.8

21.9
24.2
18.9

20.2
21.6
18.4

21.4
22.3
20.2

20.1
21.1
18.7

18.6
18.8
18.3

16.3
14.6
18.3

16.5
15
18.6

16.1
13.9
19.2

15.9
14.5
17.8

13.9
11.6
16.8

10.1
9.4
11.2

10.4
9.9
11.3

36.9
39.7
33.8

37.7
39.5
35.5

33.1
34.7
31

30.1
31
28.8

26.6
26.4
27

20.3
20.4
20.2

19
18.5
19.8

21.4
21.1
21.6

21
21.2
20.9

20.7
22
19.4

20.1
20.6
19.5

18.7
19
18.4

16.5
16.4
16.6

16.5
17.1
15.8

10.5
11
9.9

16.6
17.7
15.5

21.5
22.5
20.6

22.9
23
22.8

21.6
21.1
22.1

19.3
18.9
19.8

20.3
19.8
20.8

12.2
13.2
11

12
13.7
10.2

12.1
13.3
10.7

12.8
14.4
11.1

14
15.7
12

14.3
15.8
12.5

15
17
12.7

Source:  Eurostat - LFS adjusted series, Annual average
p = provisional value /  b = break in data series

EN 

175 

EN 

 
  
 
CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SL

SK

FI

SE

UK

Context 2d: Long-term unemployment rate by gender, selected years (% of the labour force 15+)
EU27

EU25

DK

BG

CZ

BE

2000

2002

2004

2005

2006

2007

2008

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

Total
Males
Females

4
3.5
4.6

4
3.6
4.5

4.2
3.8
4.6

:
:
:

3.7
3.5
4

3.1
2.8
3.3

2.6
2.4

2.8

3.9
3.4
4.6

3.9
3.4
4.4

4.1
3.7
4.5

:
:
:

3.7
3.4
4

3
2.8
3.3

2.6
2.4

2.8

3.7
3.1
4.6

3.7
3.2
4.3

4.1
3.7
4.7

4.4
3.9
5

4.2
3.7
4.9

3.8
3.3
4.3

3.3
3

3.7

9.4
9.5
9.2

12
12.5
11.4

7.2
7.3
7.1

6
6.1
6

5
4.8
5.3

4.1
3.7
4.5

2.9
2.7

3.1

4.2
3.5
5.2

3.7
3
4.6

4.2
3.4
5.3

4.2
3.4
5.3

3.9
3.1
4.9

2.8
2.1
3.6

2.2
1.7

2.8

0.9
0.8
1.1

0.9
0.7
1

1.2
1.1
1.3

1.1
1.1
1.2

0.8
0.7
0.9

0.6
0.5
0.7

0.5
0.4

0.5

Source : Eurostat - Labour Force Survey, Annual averages
 : = not available or unreliable data / b = break / p = provisional / e: estimate

DE

EE

3.8
3.7
4

4
4.1
4

5.5
5.7
5.2

5,7b
6,0b
5,3b

5.5
5.7
5.3

4.7
4.8
4.7

3.8
3.9

3.7

5.9
6.7
5

5.4
6.3
4.5

5
5.6
4.4

4.2
4.2
4.2

2.9
3.2
2.6

2.3
2.8
1.7

1.7
2

1.4

IE

1.6
2.1
1

1.3
1.8
0.8

1.6
2
1

1.5
1.9
0.8

1.4
1.8
0.9

1.4
1.7
0.9

1.6
2.2

0.9

EL

6.2
3.5
10.1

5.3
3.1
8.6

5.6
3
9.4

5.1
2.6
8.9

4.8
2.6
8.1

4.1
2.2
7

3.6
2.1

6

ES

4.6
2.8
7.4

3.7
2.3
5.9

3.4
2.2
5

2,2b
1,4b
3,4b

1.8
1.2
2.8

1.7
1.1
2.5

2
1.4

2.9

FR

3.5
2.8
4.3

3
2.6
3.4

3.8
3.3
4.2

3.8
3.4
4.3

3.9
3.6
4.2

3.4
3.2
3.6

2.9
2.8

3

IT

6.3
4.8
8.4

5.1
4
6.9

4,0b
2,9b
5,5b

3.9
2.9
5.2

3.4
2.6
4.5

2.9
2.2
3.9

3.1
2.4

4.1

1.2
0.5
2.2

0.8
0.5
1

1.2
0.9
1.6

1.2
0.8
1.8

0.9
0.7
1.1

0.7
0.8
0.7

0.5
0.5

0.5

7.9
8.3
7.5

5.5
6.4
4.6

4.6
4.8
4.3

4.1
4.4
3.7

2.5
3
1.9

1.6
1.9
1.2

1.9
1.9

1.9

8
9.4
6.5

7.2
7.6
6.8

5.8
5.5
6.2

4.3
4.2
4.5

2.5
2.5
2.5

1.4
1.4
1.3

1.2
1

1.4

0.5
0.5
0.5

0.7
0.6
0.8

1
0.8
1.3

1.2
1.2
1.2

1.4
1.3
1.6

1.2
1.3
1.1

1.6
1.2

2.1

3.1
3.5
2.5

2.5
2.8
2.2

2.7
2.8
2.6

3.2
3.2
3.2

3.4
3.3
3.4

3.4
3.3
3.6

3.6
3.6

3.7

4.5
4.5
4.5

3.2
3.5
2.5

3.4
3.6
3

3.3
3.4
3.4

2.8
3
2.4

2.7
2.8
2.4

2.5
2.6

2.5

0.8
0.6
1

0.7
0.6
0.9

1.6
1.5
1.6

1.9
1.9
1.9

1.7
1.6
1.8

1.3
1.2
1.4

1
0.9

1

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)

2010

2020

2030

2040

2050

EU27 

25.9

31.1

38.0

45.4

50.4

BE

26.1

30.6

37.6

42.3

43.9

BG

25.3

31.1

36.3

43.6

55.4

63.5
Source : Eurostat - EUROPOP2008 Trend scenario - baseline variant

2060

45.8

53.5

CZ

21.8

31.1

35.7

42.7

54.8

61.4

DK

25.0

31.9

37.9

42.7

41.3

42.7

DE

31.2

35.3

46.2

54.7

56.4

59.1

EE

25.0

29.2

34.4

39.0

47.2

55.6

IE

16.7

20.2

24.6

30.6

40.4

43.6

EL

28.2

32.8

38.5

48.3

57.0

57.1

ES

24.4

27.4

34.3

46.4

58.7

59.1

FR

25.8

32.8

39.0

44.0

44.7

45.2

IT

31.0

35.5

42.5

54.1

59.2

59.3

CY

18.0

22.3

27.4

30.8

37.7

44.5

LV

25.2

28.1

34.6

40.7

51.2

64.5

LT

23.2

26.0

34.7

42.8

51.1

65.7

LU

21.1

24.2

30.8

36.3

37.8

39.1

HU

24.2

30.3

34.1

40.1

50.8

57.6

MT

21.2

31.3

39.1

41.7

49.8

59.1

NL

22.8

30.7

40.0

46.8

45.6

47.2

AT

26.0

29.2

38.1

46.0

48.3

50.7

1.4
1.9
0.9

1.1
1.4
0.7

1
1.2
0.6

1
1.3
0.7

1.2
1.5
0.8

1.3
1.6
0.9

1.4
1.7

0.9

1
0.9
1.2

1.1
1
1.2

1,4b
1,3b
1,4b

1.3
1.3
1.4

1.3
1.3
1.3

1.2
1
1.4

0.9
0.9

0.9

PL

19.0

27.2

36.0

41.3

55.7

69.0

7.4
6
9.1

10.9
9.8
12.3

10.3
9.6
11.1

10.3
9.3
11.4

7.8
7.1
8.6

4.9
4.6
5.4

2.4
2

2.8

PT

26.6

30.7

36.6

44.6

53.0

54.8

1.7
1.4
2

1.8
1.4
2.2

3
2.6
3.5

3.7
3.2
4.3

3.9
3.4
4.5

3.8
3.2
4.5

3.7
3.2

4.2

RO

21.3

25.7

30.3

40.8

54.0

65.3

3.8
4
3.5

4,6b
4,8b
4,4b

4.8
5.5
3.8

4
4.6
3.4

4.2
4.7
3.6

3.2
3.6
2.7

2.4
2.9

1.8

SI

23.9

31.2

40.8

49.4

59.4

62.2

4.1
4.1
4.2

3.5
3.5
3.6

3.2
3.1
3.4

3.1
2.9
3.3

2.9
2.5
3.5

2.2
1.8
2.7

1.9
1.6

2.1

SK

17.0

23.9

32.3

40.0

55.5

68.5

10.3
10.3
10.2

12.2
11.9
12.5

11.8
11.3
12.4

11.7
11.2
12.3

10.2
9.4
11.2

8.3
7.5
9.3

6.6
5.8

7.6

FI

25.7

36.8

43.9

45.1

46.6

49.3

2.8
2.8
2.7

2.3
2.5
2

2.1
2.3
2

2.2
2.4
2

1.9
2.1
1.8

1.6
1.7
1.4

1.2
1.3

1.1

1.4
1.7
1

1
1.2
0.8

1.2
1.4
1

:
:
:

1.1
1.2
1

0.8
0.9
0.8

0.8
0.8

0.7

SE

27.8

33.7

37.4

40.8

41.9

46.7

UK

24.7

28.6

33.2

36.9

38.0

42.1

EN 

176 

EN 

 
  
 
Context 5a: Distribution of households by age and household type (private/institutional)

Total

Children (0-17)

18-64

65+

75+

Total ('000)
Private households (%)
Institutional household (%
Total ('000)
Private households (%)
Institutional household (%
Total ('000)
Private households (%)
Institutional household (%
Total ('000)
Private households (%)
Institutional household (%
Total ('000)
Private households (%)
Institutional household (%
   Hospitals (%)
   Old people's homes (%)

EU25 

BE

441467

10296

98.7 

1.3 

90525

99.4 

0.6 

279593

99.0 

1.0 

71306

96.4 

3.6 

30917

93.3 

6.7 

19.9 

68.0 

98.6 

1.4 

2162

99.9 

0.1 

6390

99.5 

0.5 

1744

93.9 

6.1 

774

88.4 

11.5 

5.3 

85.1 

BG

7904

99.3 

0.7 

1531

97.9 

2.1 

5586

99.4 

0.6 

1322

99.6 

0.4 

481

99.3 

0.7 

14.0 

83.8 

CZ

10230

99.3 

0.7 

2057

99.8 

0.2 

6759

99.5 

0.5 

1411

97.7 

2.3 

570

95.7 

4.3 

4.9 

86.3 

DK

5349

98.7 

1.3 

DE

82277

99.0 

1.0 

1161

15251

99.4 

0.6 

99.7 

:

3396

52516

98.9 

1.1 

792

96.7 

3.3 

379

94.2 

5.8 

:

:

99.6 

:

14510

96.3 

:

6191

92.5 

7.5 

:

:

EE

1370

EL

10628

98.8 

0.9 

312

99.2 

0.6 

852

98.9 

0.9 

205

98.1 

1.7 

75

96.9 

2.9 

3.6 

95.4 

96.6 

3.4 

2011

97.8 

2.2 

6824

96.0 

4.0 

1792

97.5 

2.5 

642

96.7 

3.3 

20.4 

34.3 

ES

40847

99.4 

0.6 

FR

58514

97.8 

2.2 

IE

3852

98.4 

1.6 

7341

13426

1009

99.9 

0.1 

99.2 

0.8 

99.6 

0.4 

IT

56996

99.3 

0.7 

9833

99.9 

0.1 

26547

35788

2420

36517

99.7 

0.3 

6974

97.7 

2.3 

3036

96.1 

3.9 

12.5 

56.6 

98.2 

1.8 

9299

94.3 

5.7 

4133

89.5 

10.5 

13.8 

79.5 

98.9 

1.1 

423

92.8 

7.2 

184

87.6 

12.4 

27.8 

56.4 

99.5 

0.5 

10646

97.9 

2.1 

4762

96.5 

3.5 

1.5 

73.2 

Source: Eurostat Census data collection 2000-01

Context 5b: Population living in private households by household type, 2008 (percentage of total population)

- Single adults, no children
of which:
- Single men
- Single women

- Under 65
- 65 and over

- Single parents
- 2 adults below 65, no children

- 2 adults, at least one aged 65+, no children

- 3 or more adults, no children
- 2 adults, 1 child
- 2 adults, 2 children
- 2 adults, 3 or more children
- 3 or more adults, with children

EU aggregates based on available country data
Source: SILC 2008

EU27

EU25

13

13

BE

15

6
8

8
5

4
13

11
12
12
17
7
11

6
8

8
6

4
14

11
12
12
17
7
10

7
8

9
6

6
15

10
8
11
13
15
7

BG

6

2
4

2
4

2
9

9
20
11
10
2
32

CZ

10

DK

23

DE

19

EE

15

4
6

5
5

4
14

10
15
12
20
5
11

11
12

16
7

7
18

10
2
10
19
10
2

9
10

13
6

5
16

14
7
12
15
7
5

5
10

9
7

6
13

10
9
15
15
6
11

Context 6a: General government debt - General government consolidated gross debt as a percentage of GDP

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009F

2010F

2011F

EU-27 BE
107.6

61.8

60.9

60.3

61.7

62.1

62.7

61.3

58.7

61.5

73.0

79.3

83.7

106.3

103.2

98.3

93.9

92.1

88.1

84.2

89.8

97.2

101.2

104.0

BG
74.3

67.3

53.6

45.9

37.9

29.2

22.7

18.2

14.1

15.1

16.2

15.7

CZ
18.5

25.1

28.5

30.1

30.4

29.7

29.4

29.0

30.0

36.5

40.6

44.0

DK
51.7

47.4

46.8

45.8

44.5

37.1

31.3

26.8

33.5

33.7

35.3

35.2

DE
59.7

58.8

60.3

63.8

65.6

68.0

67.6

65.0

65.9

73.1

76.7

79.7

EE
5.1

4.8

5.6

5.5

5.0

4.6

4.5

3.8

4.6

7.4

10.9

13.2

IE
37.7

35.5

32.2

31.0

29.4

27.6

25.0

25.1

44.1

65.8

82.9

96.2

Source:  Eurostat - General Government data and ECFIN forecasts /  F = forecast

EN 

IE

EL

ES

8

4
4

4
4

8
11

8
12
10
17
14
14

EL
101.8

102.9

101.5

97.3

98.6

100.0

97.1

95.6

99.2

112.6

124.9

135.4

8

3
5

4
4

1
9

12
24
10
25
3
10

ES
59.2

55.5

52.5

48.7

46.2

43.0

39.6

36.1

39.7

54.3

66.3

74.0

7

3
4

3
3

2
11

9
22
13
21
3
13

FR
57.3

56.9

58.8

62.9

64.9

66.4

63.7

63.8

67.4

76.1

82.5

87.6

FR

15

7
9

10
6

5
16

11
7
12
18
11
6

IT
109.2

108.8

105.7

104.4

103.8

105.8

106.5

103.5

105.8

114.6

116.7

117.8

177 

CY

690

99.4 

0.6 

180

99.9 

0.1 

428

99.7 

0.3 

80

96.4 

3.6 

34

92.7 

7.3 

5.8 

91.0 

IT

12

5
7

6
6

3
9

12
17
13
18
5
11

CY
58.8

60.7

64.6

68.9

70.2

69.1

64.6

58.3

48.4

53.2

58.6

63.4

PL

PT

RO

38230

10356

21681

LV

2377

99.0 

1.0 

541

99.4 

0.6 

LT

3484

99.3 

0.7 

846

99.3 

0.7 

1485

2148

99.0 

1.0 

352

98.7 

1.3 

126

98.1 

1.9 

2.0 

97.7 

99.4 

0.6 

489

98.9 

1.1 

178

98.3 

1.7 

5.2 

89.1 

LU

440

98.3 

1.7 

98

99.0 

1.0 

281

99.0 

1.0 

61

93.7 

6.3 

25

87.0 

13.0 

9.8 

69.2 

HU

10198

97.5 

2.4 

2087

96.9 

3.1 

6565

97.7 

2.2 

1546

97.5 

2.5 

619

95.8 

4.2 

11.8 

83.4 

MT

0

-

-

0

-

-

0

-

-

0

-

-

0

-

-

-

-

NL

15986

98.6 

1.4 

3532

99.7 

0.3 

10279

99.4 

0.6 

2174

93.5 

6.5 

972

87.2 

12.8 

20.8 

75.9 

AT

8033

98.9 

1.1 

1639

99.7 

0.3 

5152

99.4 

0.6 

1242

95.8 

4.2 

582

92.4 

7.6 

19.4 

76.3 

98.9 

1.1 

8851

99.2 

0.8 

24522

98.8 

1.2 

4853

98.8 

1.2 

1841

98.1 

1.9 

18.5 

65.8 

99.0 

1.0 

2053

99.5 

0.5 

6610

99.6 

0.4 

1693

96.4 

3.6 

701

93.1 

6.9 

3.3 

85.8 

SI

1964

99.3 

0.7 

376

:

:

98.5 

1.5 

4847

98.3 

1.7 

15420

1299

98.0 

2.0 

3050

99.6 

0.4 

1063

99.4 

0.6 

30.7 

59.4 

:

:

289

:

:

110

88.4 

5.3 

:

:

SK

5379

98.4 

0.8 

1277

98.3 

0.4 

3444

98.7 

0.6 

611

97.0 

2.7 

238

95.4 

4.2 

13.3 

75.1 

FI

5181

98.1 

0.7 

1135

99.1 

0.4 

3269

98.4 

0.3 

777

95.1 

3.1 

340

90.8 

6.0 

27.9 

58.5 

CY

6

2
3

3
3

3
8

10
14
10
30
7
13

LV
12.3

14.0

13.5

14.6

14.9

12.4

10.7

9.0

19.5

33.2

48.6

60.4

LV

10

LT

10

LU

12

3
7

5
5

5
9

8
15
14
11
5
24

LT
23.7

23.1

22.3

21.1

19.4

18.4

18.0

16.9

15.6

29.9

40.7

49.3

3
7

5
5

5
9

9
13
15
18
5
17

LU
6.4

6.5

6.5

6.2

6.3

6.1

6.6

6.6

13.5

15.0

16.4

17.7

5
7

8
4

4
12

9
10
13
26
7
8

HU
55.0

52.0

55.6

58.4

59.1

61.8

65.6

65.9

72.9

79.1

79.8

79.1

HU

MT

9

3
6

5
5

4
12

9
14
13
16
7
16

MT
55.9

62.1

60.1

69.3

72.5

70.2

63.6

62.0

63.8

68.5

70.9

72.5

7

3
4

3
4

3
8

9
22
11
16
7
18

NL
53.8

50.7

50.5

52.0

52.4

51.8

47.4

45.5

58.2

59.8

65.6

69.7

NL

16

AT

15

7
9

11
5

4
17

10
6
10
20
13
5

AT
66.4

67.0

66.4

65.4

64.8

63.9

62.2

59.5

62.6

69.1

73.9

77.0

7
9

10
6

4
13

10
13
11
15
8
12

PL
36.8

37.6

42.2

47.1

45.7

47.1

47.7

45.0

47.2

51.7

57.0

61.3

PL

PT

RO

SL

SK

9

3
6

4
5

2
9

7
15
12
15
7
25

6

2
5

2
4

3
9

12
19
16
16
4
16

7

3
5

3
4

2
8

8
14
13
14
6
27

7

3
5

3
4

3
7

9
18
10
22
7
17

9

2
6

4
5

2
7

7
18
10
17
7
24

PT
50.4

52.9

55.5

56.9

58.3

63.6

64.7

63.6

66.3

77.4

84.6

91.1

RO
24.6

25.7

24.9

21.5

18.7

15.8

12.4

12.6

13.6

21.8

27.4

31.3

SI
26.8

27.4

28.1

27.5

27.2

27.0

26.7

23.3

22.5

35.1

42.8

48.2

SK
50.3

48.9

43.4

42.4

41.4

34.2

30.5

29.3

27.7

34.6

39.2

42.7

FI
43.8

42.3

41.3

44.4

44.2

41.8

39.3

35.2

34.1

41.3

47.4

52.7

SE
53.6

54.4

52.6

52.3

51.2

51.0

45.9

40.5

38.0

42.1

43.6

44.1

SE

0

0

0

0

0

-

-

-

-

-

-

-

-

-

-

-

-

FI

19

8
11

12
7

5
20

10
4
11
16
11
4

UK

58789

98.2 

1.8 

13346

99.3 

0.7 

36103

98.5 

1.5 

9341

95.4 

4.6 

4405

91.5 

8.5 

44.6 

46.0 

SE

18

UK

13

6
7

7
6

7
17

11
9
11
17
9
8

8
10

11
7

7
18

11
3
11
18
10
4

UK
41.0

37.7

37.5

38.7

40.6

42.2

43.2

44.2

52.0

68.6

80.3

88.2

EN 

 
  
      
   
   
      
        
         
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
   
 
     
   
        
     
     
       
          
           
          
          
             
          
             
          
        
          
          
        
             
 
       
     
     
     
     
     
     
     
     
 
     
     
      
   
   
      
        
         
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
 
     
   
        
     
     
       
          
          
          
             
          
             
          
        
          
          
        
             
 
       
     
     
     
     
     
     
     
 
     
     
      
   
   
      
        
         
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
 
     
   
        
     
     
       
          
          
          
             
          
             
          
        
          
          
        
             
 
       
     
     
     
     
     
     
     
 
     
     
      
   
   
      
        
         
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
 
     
   
        
     
     
       
          
          
          
             
          
             
          
        
          
          
        
             
 
       
     
     
     
     
     
     
     
 
     
     
      
   
   
      
        
         
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
   
 
     
   
        
   
     
       
          
           
          
          
             
        
           
          
        
          
          
      
             
 
       
   
     
     
     
     
     
     
     
 
     
     
      
     
   
       
          
        
           
        
           
          
        
          
          
        
           
 
       
   
   
   
     
   
   
   
 
     
   
      
   
   
      
        
        
           
        
           
        
      
        
        
      
           
 
       
   
   
   
   
   
   
   
 
     
   
 
Context 6b: Projected evolution of debt levels up to 2050 (in % of GDP)
Programme scenario

2005

2010

2030

2050

2005 budget scenario

2010

2030

2050

* Adjusted gross debt.

EU-25** BE
93.3

63

61

79

180

55

33

76

72

31

83

74

52

129

BG

:

:

:

:

:

:

:

CZ

30.5

30

43

188

43.2

95.7

DK

35.8

18

23

98

14.4

-61.2

320.3

-135.5

DE

67.7

64

37

65

73.6

116.2

232.4

** 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

Sickness, health care
Disability
Family and children
Unemployment 
Old age and survivors benefits
Housing and social exclusion
 e = Eurostat estimate / p =  provisional

EU-27 EU-25
29,2p
29,1p

8,1p

8p

5,1p

8p

7,9p

5,1p

46,2p

46,2p

3,6p

3,6p

BE

26.5

6.6

7.1

11.7

45.3

2.8

BG

27.1

8.3

8.6

2

51.4

2.5

CZ

33.9

8.1

9.2

3.5

43.9

1.4

DK

23

15

13.1

5.6

38.1

5.1

Context 7b: Social protection benefits by group of functions (as a percentage of GDP) - 2007

EU-27 EU-25
26.4p
26.2p

BE

28.0

29.5

7.4p

7.4p

25.2p

25.4p

Total expenditure*
Social protection benefits
Sickness/Health care
Disability
Family/Children
Unemployment
Old age and survivors
Housing and Social exclusion n.e.c.
Administration costs
Other expenditure
* including administrative costs; e = Eurostat estimate / p =  provisional

11.7p

11.7p

2.0p

1.3p

2.0p

0.9p

0.8p

0.2p

1.3p

2.0p

2.0p

0.9p

0.8p

0.2p

12.7

2.0

3.3

7.4

1.8

0.8

1.0

0.5

BG

15.1

14.6

3.9

1.2

1.3

0.3

7.5

0.4

0.4

0.1

CZ

18.6

18.0

6.1

1.5

1.7

0.6

7.9

0.3

0.6

0.0

DK

28.9

28.1

6.5

4.2

3.7

1.6

10.7

11.5p

1.4

0.8

:

0.8p

1.0p

0.1p

EE

4.8

0

-25

-82

0.9

-39.3

-117

DE

29,8p

7,7p

10,6p

5,8p

43,1p

2,9p

DE

27.7p

26.7p

8.0p

2.0p

2.8p

1.5p

IE

27.6

17

37

157

13.6

7.9

100.4

EE

33.4

9.3

11.6

1.2

43.8

0.8

EE

12.5

12.3

4.1

1.1

1.4

0.1

5.4

0.1

0.1

:

EL

107.5

90

18

-56

96.9

165.2

451.3

IE

41.1

5.5

14.7

7.7

27.4

3.6

IE

18.9

17.6

7.2

1.0

2.6

1.4

4.8

0.6

1.3

0.0

ES

43.2

30

33

198

25.7

-13.5

42.6

EL

28.1

4.9

6.2

4.5

52

4.3

EL

24.4

23.8

6.7

1.2

1.5

1.1

12.4

1.0

0.6

0.0

Context 8a: Adults aged 18-59 living in jobless households by household types, 2008, in % of total number of adults living in jobless households

Alone without children
Alone with child(ren)
Couple without children
Couple with child(ren)
Other households without children - total
    - without elderly (65+)
    - with at least 1 elderly (65+)
Other households with child(ren) - total
    - without elderly (65+)
    - with at least 1 elderly (65+)
Source: Eurostat - European Labour Force Survey 2008, Annual results.
 : = not available or unreliable data / b = break / p = provisional / e = estimate

EU25 
27.5
10.7
19.9
15.4
19.4
9.2
10.2
7.0
5.4
1.6

EU27
26.5
10.2
19.9
15.7
19.7
9.5
10.3
7.9
6.0
1.9

BE
33.3
13.7
23.1
10.7
12.5
7.6
4.8
6.8
5.8
1.1

BG
17.3
4.4
19.9
13.4
28.4
13.7
14.7
16.5
12.4
4.2

CZ
25.7
14.5
23.3
11.7
19.1
7.7
11.4
5.7
4.1
1.6

DK
:
:
:
:
:
:
:
:
:
:

DE
43.0
10.3
19.1
14.6
9.3
4.8
4.5
3.6
3.2
0.5

EE
34.0
12.4
9.5
12.1
27.4
7.8
19.6
4.7
2.0
2.8

IE
19.4
18.2
11.4
21.2
20.8
13.0
7.8
8.9
7.8
1.1

EL
21.5
3.2
26.9
11.0
32.6
13.1
19.5
4.7
3.0
1.7

FR

66.8

60

41

66

69.2

132.8

269.9

ES

31,2p

7,6p

6p

11,7p

41,3p

2,2p

ES

21.0p

20.5p

6.4p

1.6p

1.2p

2.4p

8.5p

0.5p

0.5p

0.1p

ES
14.7
4.8
15.5
21.3
31.9
11.4
20.5
11.7
7.9
3.8

IT

106.4

97

32

1

108.9

127.6

208.9

FR

29,9p

6,1p

8,5p

6,1p

45,3p

4,2p

FR

30.5p

29.0p

8.7p

1.8p

2.5p

1.8p

CY

70.3

57

42

172

64.3

116.3

269.9

IT

26,1p

6p

4,7p

1,8p

61,1p

0,3p

IT

26.7p

25.5p

6.7p

1.5p

1.2p

0.5p

13.1p

15.6p

1.2p

1.2p

0.2p

0.1p

0.7p

0.5p

FR
31.0
11.7
26.8
14.1
12.2
6.7
5.4
4.3
3.4
0.9

IT
18.2
4.0
17.3
17.5
33.5
16.3
17.2
9.5
7.7
1.8

LV

11.9

9

26

92

13

14.9

49.6

CY

25,2p

3,7p

10,8p

4,8p

46,7p

8,7p

CY

18.5p

18.1p

4.6p

0.7p

2.0p

0.9p

8.5p

1.6p

0.3p

0.1p

CY
9.9
8.0
26.5
18.3
33.0
25.4
7.6
4.3
2.7
1.6

LT

18.7

16

22

76

22.4

46.7

LU

6.2

10

74

240

11.5

56.1

135.7

179.1

LV

29,7p

7p

11p

3,3p

46,8p

2,3p

LV

11.0p

10.7p

3.2p

0.7p

1.2p

0.3p

5.0p

0.2p

0.2p

0.1p

LV
24.6
9.1
12.0
11.0
32.5
8.3
24.2
10.8
5.1
5.7

LT

30,7p

10,4p

8,7p

1,9p

47p

1,3p

LT

14.3p

13.9p

4.3p

1.4p

1.2p

0.3p

6.5p

0.2p

0.4p

0.0p

LT
37.3
11.2
10.9
11.8
21.6
8.4
13.2
7.2
4.2
2.9

HU

58.4

61

51

155

76.1

143.6

247.6

LU

26

12.3

16.6

4.9

37.3

2.9

LU

19.3

19.0

4.9

2.3

3.2

0.9

7.1

0.6

0.3

0.0

LU
33.6
5.5
32.8
11.7
11.6
7.1
4.5
4.8
3.9
0.9

MT

74.7

65

16

-58

80.2

92.9

79.6

HU

25.5

9.6

12.8

3.4

43.9

4.8

HU

22.3

21.9

5.6

2.1

2.8

0.8

9.6

1.1

0.4

:

HU
14.5
6.5
21.4
18.7
25.2
12.1
13.1
13.6
10.7
3.0

NL

52.9

46

70

176

44.2

67.8

177.7

AT

62.9

54

23

18

58.9

54.9

67.5

PL

42.5

45

-33

PT

63.9

65

64

-163

208

53.2

20

-42.5

76.3

195.4

517.4

MT

29.2

6.3

5.9

2.8

52.4

3.3

MT

18.1

17.9

5.2

1.1

1.1

0.5

9.4

0.6

0.2

:

MT
15.7
7.8
21.0
18.2
28.1
12.1
16.1
9.2
6.2
2.9

NL

32,5p

9,1p

6p

4,3p

40,2p

7,8p

NL

28.4p

26.8p

8.7p

2.5p

1.6p

1.2p

AT

26

8

10.2

5.3

48.9

1.5

AT

28.0

27.1

7.1

2.2

2.8

1.4

PL

22.1

9.6

4.5

2.2

60.2

1.4

PL

18.1

17.8

3.9

1.7

0.8

0.4

10.8p

13.3

10.7

11.7

2.1p

1.3p

0.3p

0.4

0.5

0.4

0.3

0.3

0.0

0.3

0.5

0.9

NL
45.0
14.1
22.1
11.5
5.9
3.4
2.4
1.5
1.2
0.3

AT
37.8
5.9
23.8
12.0
16.8
7.6
9.3
3.5
2.8
0.7

PL
15.8
7.6
25.2
13.0
26.3
11.6
14.8
12.1
8.2
3.8

PT
14.2
6.8
23.4
14.1
32.0
10.4
21.6
9.4
5.8
3.6

RO

:

:

:

:

:

:

:

PT

28.3

10

5.3

5.1

50

1.2

PT

24.8

23.4

6.6

2.3

1.2

1.2

SI

29.1

27

65

270

25.1

68.5

SK

34.5

31

16

66

38.7

66.8

287.2

176.9

FI

41.1

25

26

96

23.7

7.9

61.6

SE

50.3

34

-3

-1

30.3

8

UK

42.8

42

44

114

47

90.1

58.8

186.7

RO

23.8

10

13.2

2.2

47.3

3.5

SL

SK

32,1p

30,8p

7,8p

8,7p

2,3p

8,5p

10p

3,6p

46,7p

43,8p

2,4p

3,3p

FI

26.3

12.6

11.6

7.8

38.5

3.2

SE

26,1p

15,3p

10,2p

3,8p

41p

3,8p

UK

30,6p

9,8p

6p

2,1p

44,9p

6,5p

RO

12.8

12.6

SL

21.4p

20.8p

SK

16.0p

15.4p

FI

25.4

24.6

3.0

1.3

1.7

0.3

6.0

0.4

0.2

0.0

RO
10.9
2.9
20.3
22.8
22.5
12.7
9.8
20.6
13.6
7.0

6.7p

1.6p

1.8p

0.5p

9.7p

0.5p

0.4p

0.1p

SI
27.3
4.0
32.4
6.7
25.0
12.3
12.7
4.7
3.5
1.2

4.7p

1.3p

1.5p

0.6p

6.8p

0.5p

0.6p

0.0p

SK
13.3
4.6
18.3
14.5
30.2
14.5
15.7
18.9
15.5
3.4

6.5

3.1

2.9

1.9

9.5

0.8

0.8

:

FI
51.8
3.7
22.8
11.5
9.3
3.2
6.0
0.9
0.9
0.0

SE

29.7p

29.0p

7.6p

4.4p

3.0p

1.1p

UK

25.3p

24.8p

7.6p

2.4p

1.5p

0.5p

11.9p

11.1p

1.1p

0.6p

0.0p

1.6p

0.5p

0.0p

SE
:
:
:
:
:
:
:
:
:
:

UK
27.5
23.3
14.0
16.3
13.5
8.1
5.5
5.4
4.9
0.5

EN 

178 

EN 

 
  
 
Context 8b: Children aged 0-17 living in jobless households by household types, 2008, in % of total number of children living in jobless households
ES
BG
23.5
23.4
0.8
1.1
48.7
39.7
47.1
34.7
1.7
5.0
27.0
35.9
14.7
25.4
12.3
10.4

Alone with child(ren) - no elderly
Alone with child(ren) - at least 1 elderly
Couple with child(ren) - total
    - without elderly (65+)
    - with at least 1 elderly (65+)
Other households with child(ren) - no elderly
    - without elderly (65+)
    - with at least 1 elderly (65+)
Source: Eurostat - European Labour Force Survey 2008, Annual results.
 : = not available or unreliable data / b = break / p = provisional / e = estimate

EU25 
47.9
0.3
39.1
38.2
1.0
12.6
8.7
4.0

EU27
45.7
0.4
40.0
38.9
1.1
14.0
9.4
4.6

DE
46.9
0.4
45.2
44.5
0.7
7.5
5.4
2.1

CZ
57.3
0.3
30.8
29.6
1.3
11.6
8.1
3.6

EE
56.1
0.4
28.6
27.9
0.6
14.9
4.3
10.6

IE
49.9
0.1
37.3
36.9
0.4
12.7
10.7
2.0

EL
27.7
0.7
53.4
49.3
4.0
18.3
8.8
9.5

BE
57.7
0.4
29.6
28.5
1.1
12.3
9.8
2.5

DK
:
:
:
:
:
:
:
:

FR
51.5
0.2
41.2
40.2
1.0
7.1
5.7
1.4

IT
22.4
0.2
59.1
58.1
1.0
18.3
13.0
5.3

CY
43.1
0.0
46.1
43.8
2.4
10.8
7.4
3.5

LV
36.9
7.8
26.6
21.0
5.5
28.7
13.8
15.0

LT
50.7
1.5
29.2
27.8
1.4
18.6
10.2
8.4

LU
35.1
1.2
37.5
35.4
2.1
26.1
21.4
4.7

HU
25.7
0.3
51.0
50.5
0.5
23.0
16.8
6.1

MT
39.0
0.0
42.3
40.7
1.6
18.7
11.8
6.9

NL
63.0
0.4
34.4
33.3
1.1
2.2
1.5
0.7

AT
37.6
0.8
50.9
49.9
1.0
10.7
7.2
3.5

PL
37.7
0.5
31.9
31.0
0.9
30.0
16.1
13.9

PT
34.5
1.2
44.8
40.6
4.1
19.5
8.9
10.6

RO
8.4
1.2
57.3
55.5
1.8
33.1
17.9
15.2

SI
32.7
0.0
44.7
44.3
0.4
22.6
14.5
8.0

SK
20.1
0.0
39.3
39.1
0.3
40.5
31.4
9.1

FI
27.5
0.0
71.0
70.0
1.0
1.5
1.5
0.0

SE
:
:
:
:
:
:
:
:

UK
66.3
0.1
26.8
26.1
0.7
6.8
5.9
0.9

Context 10: Net income of social assistance recipients as % of the at-risk of poverty rate threshold for 3 jobless households types, 2006
BE

MT

HU

LV

CZ

EE

LT

SK

PT

ES

PL

LU

CY

FR

SI

AT

DE

single
lone parent, 2 children
couple with two children
0.5 
Source : Joint EC-OECD project using OECD tax-benefit models, and Eurostat.

0.7 

0.8 

0.5 

0.4 

0.3 

0.5 

0.7 

0.6 

0.5 

0.7 

0.3 

0.5 

0.6 

0.5 

0.5 

0.9 

0.9 

0.6 

0.6 

0.4 

0.6 

1.3 

1.1 

0.6 

0.8 

0.8 

0.7 

0.9 

0.6 

0.7 

0.9 

0.7 

0.8 

0.8 

0.7 

0.8 

0.8 

0.7 

0.8 

0.8 

0.7 

0.8 

1.0 

0.9 

0.8 

0.9 

0.8 

0.9 

1.2 

1.1 

FI

1.0 

0.9 

0.9 

SE

1.1 

0.9 

0.8 

DK

1.1 

1.0 

0.9 

UK

1.2 

1.2 

1.0 

IE

1.2 

1.0 

1.0 

NL

1.3 

1.1 

0.9 

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

Total population

Total
Men
Women

Children aged 0-17 years
People aged 18-64 yeaTotal
Men
Women

People aged 65 years aTotal
Men
Women

25(p)
24(p)
26(p)
33(p)
23(p)
22(p)
24(p)
23(p)
20(p)
26(p)

25(p)
24(p)
26(p)
32(p)
23(p)
22(p)
24(p)
22(p)
19(p)
25(p)

27
26
28
32
26
25
27
25
24
26

27
26
29
31
22
22
23
41
35
46

20
19
21
30
19
17
20
14
11
17

28
26
29
22
28
26
29
36
32
39

DK(1)
27
25
29
22
28
26
29
31
27
34

DE

EE

24
23
25
31
25
24
26
16
14
18

25
22
27
26
20
19
20
41
27
49

IE

34
32
36
40
31
30
33
38
32
42

EL

ES

23
22
24
26
22
21
22
27
24
29

24
23
25
29
21
20
22
31
28
32

FR

23(b)
23(b)
23(b)
34(b)
22(b)
21(b)
23(b)
13(b)
12(b)
14(b)

IT

23
22
25
32
21
20
22
23
20
26

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

22
20
24
20
16
15
18
53
46
58

30
28
32
32
24
23
25
53
47
56

27
25
29
32
24
24
25
32
19
39

24
23
24
34
23
23
24
8
8
8

30
31
30
47
30
30
30
10
7
11

23
22
24
32
20
18
21
26
26
25

20
19
21
23
20
19
21
16
15
16

24
23
26
36
23
22
24
17
13
20

25
25
25
33
25
26
24
15
11
17

25
24
25
30
23
22
24
25
22
27

31
30
32
43
27
27
27
30
23
35

SI

23
21
25
23
21
21
21
33
26
37

SK

18
18
19
27
17
17
17
15
8
19

FI

28
26
29
30
26
26
26
31
23
36

SE

29
27
30
34
27
26
28
26
16
33

UK

29(p)
27(p)
31(p)
39(p)
24(p)
22(p)
26(p)
38(p)
33(p)
42(p)

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).
 : = 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.

EN 

179 

EN