social cohesion paper

8/6/2019 Social Cohesion Paper

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Evaluating welfare states in Europeon social cohesion

Maastricht University

Faculty of Economics and Business Administration

Maastricht, 1 June 2007

NGotho, Philip (i428442)

Groenestijn, Martin-Hugo, van (i179388)

1039M Social Europe(s)

Tutor: Dr. T. van Veen

Paper


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Table of Content

Table of Content ______________________________________________________2

1.INTRODUCTION_____________________________________________________3

2.METHODOLOGY_____________________________________________________42.1 Weighting sub-indicators ______________________________________________ 5

2.2 Quantifiying sub-indicators_____________________________________________ 52.2.1SOCIAL INCLUSION_________________________________________________________5 2.2.2INEQUALITY______________________________________________________________6 2.2.3POVERTY ________________________________________________________________7

2.3 Aggregating towards Social Cohesion ____________________________________ 7

3.DATA DESCRIPTION__________________________________________________8

4.EMPIRICALANALYSIS________________________________________________9

4.1 Indicator outcome_____________________________________________________ 94.2 Social Cohesion with respect to Public Social Expenditures _________________ 11

4.3 Equity and Efficiency_________________________________________________ 13

5.CONCLUSION______________________________________________________15

REFERENCES: _______________________________________________________16

APPENDIXA_________________________________________________________17

APPENDIXB_________________________________________________________19

APPENDIXC_________________________________________________________24


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1.INTRODUCTION

The European welfare state is under attack. Opponents suggest causality

between Europes modest economic performance compared to the US and the size of

transfer programs (Atkinson, 1999). Supporters of the welfare state claim that the

European welfare system can be regarded as the jewel on the crown. (Giddens,

2007, p. 1).

When arguing against the welfare state, authors often come up with poor or

even wrong arguments see De Neubourg and Castonguay (2006). Even the concept

of welfare state is often misused, when is argued against the Europes welfare state in

general. It is a misconception that there is just one European Social Model.

Sapir (2005) argues that there are four types of welfare states; the Nordic,

Continental, Mediterranean and the Anglo-Saxon. This paper will develop an

indicator which can be used to identify these four systems and compare the

performance of the different types of welfare states. The created indicator will reflect

social cohesion. The welfare state is created to achieve broad social cohesion and is

therefore the most important evaluator of success. We quantify social cohesion (our

indicator) by data on social inclusion, inequality and poverty.

The subsequent step to take, is investigating whether social spending has a

(positive) influence on social cohesion. This is done on a cross-section basis within

Europe. This relation is indeed positive (more social spending is associated with

higher social cohesion).

The last opportunity for opponents of the welfare state left, is the so-called

equity-efficiency trade-off. This is often mentioned as an endogenous welfare state

characteristic: generating equity can only be achieved at the cost of efficiency. We

investigate the change in real GDP per capita as a proxy for efficiency along with theGini-coefficient as estimator for equity. If there exists a positive relation, then that

suggests that an equity-efficiency trade-off exists. We cannot provide any convincing

evidence in favour or against the trade-off.

This paper continues with a section on the methodology. Section III gives a

short overview of the data we collected; section IV presents the empirical findings.

The paper is concluded with section V where we summarise our findings and

formulate our view on the welfare state. This view is accompanied by

recommendations for future policy.


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2.METHODOLOGY

We follow the methodology as proposed by Efferink, Kool and Van Veen

(2003) for their analysis of country risk. Their starting point is the development of

data categories and grouping the corresponding data. A weighting scheme gives one

indicator per category. The category indicators (sub-indicators) are also given a

certain weight to finally arrive at the final indicator. According to Efferink et. al., it is

important to [n]ote that this formula or weighting scheme is not derived from a set of

equations. Nor is there any prescription about how to construct such a scheme. (...)

[T]his highly subjective view on the relevance of various variables (...) is the secret.

(Efferink, Kool & Van Veen, 2003, p.45).

This methodology is applied as following. The data categories relevant for this

paper are social inclusion, inequality and poverty. The weights given to each of these

sub-indicators are 40%, 20% and 40%, respectively.

Subsequently, these three categories need to be quantified this is done by

using the following variables. For social inclusion, we use (very) long-term

unemployment rate, suicide rate and self-perceived health. Inequality is measured by

the Gini-coefficient and the gender pay gap. The last category (poverty) is using data

on (persistent) at risk of poverty rate. This methodology is summarised in table 1.

Parameter Value Weight Sub-indicator Weight Indicator

1.1 Long-Termunemployment 15%1.2 Very Long-Termunemployment 35%

1.3 Suicide rate 30%1.4 Self-perceived health(bad) 10%

1. SocialInclusion

1.5 Self-perceived health(very bad) 10%

40%

2.1 Gini coefficient 70%2Inequality 2.2 Gender pay gap 30%

20%

3.1 At-risk of poverty rate 30%3 Poverty 3.2 Persistent at-risk of

poverty rate 70%

40%

Table 1

As mentioned by Efferink et al., the weights on each sub-indicator and their

underlying variables are rather subjective. Therefore, unfortunately, the justificationof our (sub-)indicator weights is not extremely robust, nor analytically invulnerable.


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Practically, the scheme has been created by logical reasoning. Besides, it

represents our view on the relative importance of the different components of social

inclusion.

2.1 Weighing sub-indicators

As poverty and social inclusion are highly related (poverty can result in a lack

of social inclusion), these variables should be given equal weight1 to reflect the

relative importance of these variables. Inequality is a phenomenon that is, outside

Europe, often observed in societies with lower income per capita. This is a

correlation, not a causality and therefore it only sideways contributes to a lack of

social cohesion. Another reason to give inequality a lower importance than the other

two sub-indicators is the fact that inequality deviates less between European countries

than other data (e.g. income per capita). This roughly evenly distributed variable

carries therefore less information in it than a very scattered variable would do (see for

example Bertola (2006), figure 2). These two types of arguments (analytical and

empirical) give enough support to assign only half the importance to inequality as

compared to social inclusion and poverty.

2.2 Quantifying sub-indicators

The following subsection section elaborates on the construction of the sub-

indicators on social inclusion, inequality and poverty. Prior to producing these sub-

indicators it is essential to provide a definition of these concepts, as it enlarges our

understanding of these social conditions. This in turn enables us to select the most

appropriate variables which can capture the development of the social conditions over

time and can allow cross-section analysis. For the underlying variables, the general

rule long-term/persistence is worse than short-term applies. This is applicable for

unemployment and poverty rates.

2.2.1SOCIAL INCLUSION

Several definitions are offered for social and economic inclusion and

exclusion (see The Roeher Institute p.43 (2003)). We intend to use the definition as

1This is a good example of the subjectiveness; one could argue that poverty facilitates social exclusion

and should therefore have a higher (relative) importance [1:1.5 instead of 1:1]


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suggested by Guildford (2002), where he defines social inclusion as being

accepted and able to participate fully within our families, our communities and our

society. Those who are excluded (...) do not have the opportunity for full participation

in the economic and social benefits of society. For measurement purposes it is

important to find indicators which capture the development of the social conditions

over time.

Bearing in mind the definition for social inclusion, we believe that long-term

unemployment, suicide rate and self-perceived health are the most suitable indicators

for the level of social inclusion. The weighing scheme gives the highest weight (50%)

to long-term unemployment as it is considered to be the highest risk factor of social

exclusion (European Commission DJR, 2001).

Suicide rate, used as a proxy for societys physiological exclusion (social

attachment), is given the second highest weight (30%). Suicide may be a surprising

choice, but it is the second most common cause of death among young men

(Rahman et al., 2000). Rahman et al. provide evidence about the connection between

suicide and socio-economic conditions. This is enough for enclosure of this variable.

Amongst others, OHara (2006) discusses the link between social inclusion

and health status. He observes that social inclusion has been widely recognized as a

key social determinant of health. Obviously, this is the reverse relation as we use it,

but the correlation still holds. The reason for equal importance of bad and very bad

self-perceived health is due to subjective measurement of this data; self-reporting

makes an objective distinction between bad and very bad difficult.

2.2.2INEQUALITY

The second sub-indicator to be quantified is inequality. The two variables to

quantify inequality are the Gini-coefficient and the gender pay gap. The Gini-

coefficient measures the inequality of distribution of income. The value lies between 0

and 1, where 0 corresponds to perfect income equality and 1 to perfect income

inequality. The gender pay gap measures the difference between mens and womens

average gross hourly earnings as a percentage of mens average gross hourly earnings.

These two variables are given weights of 70% (societal income inequality) and

30% (gender inequality) respectively. This weighting scheme does in principle just

represent a matter of taste we think inequality is best described by income inequality

across the entire population; though, much gender inequality is certainly undesirable.


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It must be recognised that changing this relative importance has only moderate

aggregate effects (inequality as sub-indicator only contributes to one-fifth of the total

indicator).

2.2.3POVERTY

The final sub-indicator is poverty. We follow the definition proposed by

Hansen (1994, cited in Golding 1995, p.213), which states that people are in poverty

when their resources are so limited as to exclude them from the minimum acceptable

way of life in the state in which they live.

Persistent poverty is worse than short-term poverty (general rule). The

relative importance is set at 70% and 30% respectively and is justified by mentioning

that this proposal reflects our view that long term poverty and is much worse than

short term poverty.

2.3 Aggregating towards Social Cohesion

In the literature many different definitions of social cohesion are used; some

authors emphasise shared values and sense of belonging as being critical, other base

their definition on the ability to work together. We propose to use the definition

employed by the European Committee for Social Cohesion, which defines social

cohesion as:

Societys ability to secure the long-term well-being of all its members,

including equitable access to available resources, respect for human dignity

with due regard for diversity, personal and collective autonomy and

responsible participation.

According to the committee this definition presupposes social commitment to

reduce disparities to a minimum and avoid polarisation (Council of Europe, 2005,

p.23). Using this description one can group social inclusion, inequality and poverty to

the broader definition of social cohesion. Our indicator will thus aim to measure the

degree of social cohesion within a country, where a lower indicator corresponds to a

higher degree of social cohesion.

.


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3.DATA DESCRIPTION

Our research on the indicators is for the largest part based on data provided by

Eurostat. This database is an institution from the European Union to enhance public

access to information about [European Union] initiatives and European Union policies

in general (http://ec.europa.eu). Some caution about objectivity is therefore

demanded, but severe concerns about this issue are highly unlikely to be realistic.

We have created a panel of yearly data ranging in the time-dimension mostly

from 1995 to 2005. This enables both a cross-section analysis to discuss differences

within the European Union as well as an analysis over time of certain countries.

Appendix A shortly summarises time-span for the data and how the data is measured

for each variable.

Regarding the analysis on equity-efficiency trade-off we consulted three

datasets from the OECD; economic outlook, national accounts and the social

expenditure database. Data on real GDP, output gap and public social expenditure was

retrieved from these datasets. Locating information on the gini-coefficient proved to

be a greater challenge, as there was no one single source available with a data

collection covering a long time span. Through the World Institute for Development

Economics Research (WIDER) we retrieved a dataset on the Gini-coefficient,

composed from a range of sources. The main disadvantage such a dataset has, is the

fact that the sources also employ different methodologies, making it hard to compare

data. Although we have taken the greatest care in ensuring that the final data is as

reliable and comparable as possible one has to remain cautious on the results.


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4.EMPIRICAL ANALYSIS

4.1 Indicator outcome

After gathering all necessary data from the sources as described in the

previous section, the methodology can be carried out. The results of this are presented

in Table 2 (appendix B presents the detailed tables per country and for the EU-15 as a

whole).

Sub-indicators

System

(final indicator

average)

Country Social Inclusion Inequality Poverty

Final

indicator

Denmark 5.33 19.78 7.34 9.02Finland 8.58 22.18 7.14 10.73

Nordic

(9.40)Sweden

25.16 20.89 5.50 8.44

Austria 7.02 23.74 8.69 11.03

Belgium 8.49 22.55 9.53 11.72

France 7.42 23.44 10.41 11.82

Germany 7.48 24.55 8.44 11.27

Luxemburg 5.62 23.85 9.47 10.81

Continental

(11.02)

NL 3.92 25.20 7.23 9.50

Ireland 4.96 27.36 14.63 13.31Anglo-Saxon

(12.94) UK 3.86 30.03 12.58 12.58

Greece 3.80 27.88 15.46 13.28

Italy 5.69 23.83 14.01 12.65

Portugal 5.37 28.23 16.33 14.32

Mediterranean

(13.31)

Spain 5.51 27.41 13.26 12.99

EU-15 6.05 25.55 11.02 11.94

Table 2

The first observation to be made is that the Nordic system (the average of

Denmark, Finland and Sweden) has the best final indicator. The second-best

performer is the Continental model (also when Luxemburg is excluded), followed by

the Anglo-Saxon model and the worst performance comes from the Mediterranean

model.

2We had to estimate the variables on self-perceived health and persistent at-risk of poverty rate for

every period, since this data was missing. It is estimated between Danish and Finnish values for thefirst variable and about about half of the at-risk of poverty rate for the second variable (see Appendix B

for data).


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These observations are in line with the expectations: a very equitable North

and a less equitable South. It is worth paying attention to important factors that

contribute to this indicator.

The sub-indicator on social inclusion is the best for Greece (3.80) and worst

for Finland (8.58). This is quite surprising, as the overall indicator has the reverse

order. The value for social inclusion means that amongst European citizens, the

Finnish feel most excluded from society. The suicide rate causes the high value on

social inclusion for Finland it has the highest suicide rate within the EU-15.

The distribution of social inclusion across different countries is mixed. Some

Continental countries, for example, perform well on social inclusion, whilst others

perform even worse than every single Mediterranean country. Apparently, the distinct

ranking of the four systems comes from the indicator on inequality or poverty, or

both.

Inequality shows a picture that is more in line with the final indicator. The

Nordic countries experience the lowest inequality; least inequality is experienced by

Denmark, then Sweden and Finland. The Anglo-Saxon model does worst as a group.

For poverty, the performance is exactly as the final indicator; the Scandinavian

countries perform best, where the Mediterranean experience most poverty. A division

can be made into two groups here; Nordic-Continental (average value of poverty-

indicator: 7.8) and Anglo-Saxon-Mediterranean (14.2), since those rates lie relatively

close to each other.

Where social inclusion is rather spread across the sample, inequality and

poverty both contribute to a pretty robust distinction between the models. Poverty

distinguishes the Nordic and Continental countries from the Anglo-Saxon and

Mediterranean ones. Inequality emphasises the difference between the Nordic and

Continental system. The cause for Mediterranean underperformance compared to the

Anglo-Saxon model is ascribed to worse performance on both social inclusion and

poverty. It does better on inequality; assigning different weights to inequality could

therefore change the picture. This investigative part is summarised in table 3.


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Averages on sub-indicators

SystemSocial inclusion Inequality Poverty

Average onfinal indicator

Nordic 6.36 20.95 6.66 9.40

Continental 6.66 23.89 8.96 11.02

Anglo-Saxon 4.41 28.69 13.60 12.94

Mediterranean 5.09 26.83 14.76 13.31

Table 3

Not only does this analysis give evidence that social cohesion is rather diverse

within the European Union, it also provides convincing evidence that it is plausible to

divide Europe (in this respect) into four regions. The region where the Netherlands

should be placed, is a controversial issue, as it scores satisfactory on social cohesion

(


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y = -0,315x + 19,244

R2 = 0,5374

6,0

7,0

8,0

9,0

10,0

11,0

12,0

13,014,0

15,0

15,0 20,0 25,0 30,0 35,0X

Y

Public social exp. vs. Social cohesion

FIN

SW

A

B F

L

NL

IRL EL

IT

PT

ES

DK

D

UK

6,0

7,0

8,0

9,0

10,0

11,0

12,0

13,0

14,0

15,0

14,0 19,0 24,0 29,0 34,0

FIN

SW

A

B

F

D

L

NL

IRL

UK

EL

IT

PT

ES

DK

Fig. 1: Public social expenditures and indicator performance

Figure 2 depicts the regression line which seems to have a good fit. However,

we observe several outliers, both below the regression line and above. These are all

outliers in terms of level, not slope. The outliers below the regression line are (from

top left to bottom right) Ireland, Luxemburg, the Netherlands, Denmark and Sweden.

The largest outliers above the regression line are France, Greece, Italy and Portugal.

Fig. 2: Regression line indicator performance on public expenditures

Although more refined research would be needed to explain the position of

these countries, we hypothesise that this could be due to characteristics of more

dynamic labour markets in the high performing countries, whereas the less performing

countries are generally known to have more rigid labour markets. One could argue

that more social cohesion can be achieved with the same amount of expenditures by

labour market reforms which would lead to an inward shift of the curve.


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Social Europe(s) 13

4.3 Equity and Efficiency

Okun is generally credited for popularising the notion that an equity-efficiency

trade-off exists, as such that when governments provide more income supports to its

citizens economic efficiency suffers. Neubourg and Castonguay (2006) argue that

such a trade-off exists only under specific assumptions. Indeed, they demonstrate that

higher equity could both raise and decrease productivity.

In this section we investigate whether there is evidence of an equity-efficiency

trade-off within the countries. For the efficiency variable we use the real GDP per

capita and for the equity variable we use the Gini-coefficient, which is generally

recognised as the foremost indicator of equity. Table 4displays the results from

regressing the change in real GDP per capita on the value of the Gini-coefficient. The

choice of countries is solely due to limited data availability on the gini-coefficient.

The time span varies across country with starting years between 1975 and 1985. They

all run until 2004. We include a dummy for the years 1990-1993, as during this period

most investigated countries experienced heavy recessions. The improved results

indicate that this is warranted.

Real GDP per capita (dependent variable)

Country Gini-coefficient(independent variable)

Dummy R-squared

Sweden (Nordic)0.15

(1.66)-3.94***(-5.00)

0.52

Germany (Continental)-0.74*(-2.04)

-0.80(-1.32)

0.36

UK (Anglo-Saxon)0.13

(1.30)-2.89***(-2.44)

0.18

US (Anglo-Saxon)0.18

(1.08)-2.08*(-1.80)

0.12

Table 4: Significance level: * 10%, ** 5%, *** 1%.

Although 3 out of 4 countries have a positive coefficient on the Gini value,

indicating that an equity-trade off exists, none of them are significant. Germany in

contrast is significant at the 10% level and indicates that more equity actually

increases efficiency. These results prove to be nonconclusive.


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Having found no clear-cut evidence on a equity-efficiency trade-off, we

further investigate if one can find a relationship between change in public social

expenditure (as percentage of GDP) and the change in real GDP per capita (table 5).

We again include a dummy to control for the recession years during 1990-93. In this

case, the data covers the time span from 1980-2000.

Also these results prove to be non-significant, except for Ireland where the

coefficient is significant at the 10% level. At best, we can conclude that more often

than not the coefficients are positive, indicating that additional public social

expenditures increase growth. However, as these results are conceptual insignificant

one cannot draw strong inferences from it.

Real GDP per capita (dependent variable)

CountryChange in public social

expenditure(independent variable)

Dummy R-squared

Denmark (Nordic)0.97

(1.44)-0.83

(-0.60)0.11

Sweden (Nordic)0.16

(0.36)-0.27

(-0.20)0.01

Germany (continental)0.81

(1.22)-1.97*(-1.74)

0.15

France (continental) 0.54(1.53)

-1.68**(-2.15)

0.23

UK (Anglo-Saxon)-0.05

(-0.06)-0.43

(-0.23)0.01

Ireland (Anglo-Saxon)-0.75*(-1.93)

-1.61(-1.21)

0.28

Italy (Mediterranean)1.01

(1.45)-2.28*(-2.07)

0.22

Spain (Mediterranean)0.87

(0.77)-3.05*(-1.79)

0.17

Table 5: Significance level: * 10%, ** 5%, *** 1%.


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5.CONCLUSION

This paper has evaluated the European welfare systems in two ways. The first

was by following a weighting scheme as proposed by Efferink, Kool and Van Veen

(2003). The second method was by performing an equity-efficiency analysis; is there

a trade-off between these concepts?

The first technique enables us to make cross-section comparisons based on

averages for every country. This showed a superior performance for the Nordic

system; the Mediterranean countries did worst. It further confirmed the general belief

that there are indeed four different social models.

After that, we tried to identify what the possible underlying cause is of the

better performances of the Nordic countries, by analysing the cross country evidence

on public social expenditures and indicator performances. We found that a higher

level of public social expenditures generally leads to a better performance on social

cohesion. This shows that social expenditure is done effectively.

After finding support for additional expenditures, we tried to investigate

whether additional expenditures have a negative effect on growth performance (the

renowned equity-efficiency trade-off). To our regret, we did not find any evidence to

be able to bring this debate to a close.

From our analysis we find significant evidence that in order to enhance social

cohesion in a country, higher public social spending could very well be the solution.

However, we believe that the way this is spent matters as we observe that generally

the countries with more dynamic labour markets achieve a better level of social

cohesion with the same expenditure level. It is thus advisable to focus the

expenditures on promoting dynamic labour market, e.g. by spending more on active

labour market policies.


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REFERENCES:

Atkinson, A. (1999), The Economic Consequences of Rolling back the welfare state,

CES, Centre for European Studies/The MIT Press, ch. 1-2.

Bertola, G. (2006), Pensions: Overview of the issues, Oxford Review of Economic

Policy, vol. 22(1), pp. 1-14

Council of Europe (2005), Concerted development of social cohesion indicators:

Methodological guide, Belgium, Council of Europe Publishing

Efferink, L. van, Kool, C. and Veen, T. van. (2003), Country Risk Analysis, Series

Financial and Monetary Studies, 21, 4.

European Commission (2001).Draft Joint Report on Social Inclusion.

Communication from the Commission, 565 final.

Giddens, A. (2007).Europe in the global age, Polity Press, Cambridge.

Golding, P. (1995). Public attitudes to social exclusion: Some problems of

measurement and analysis. In G. Room (ed.),Beyond the threshold, p. 212-232.Bristol: The Policy Press.

Neubourg, Chris de and Castonguay, Julie, (2006) Enhancing Productivity: Social

protection as Investment policy in W. Mitchell, J. Muysken and T. van Veen (ed.),

Growth and Cohesion in the European Union, Edward Elgar

OHara, Philip (2006). Social Inclusion Health Indicators: A Framework for

Addressing the Social Determinants of Health. [online] retrieved 15 May 2007

http://inclusivecities.ca/publication/reports/2006/edmonton-report.pdf

Rahman, M., Palmer, G., Kenway, P. and Howarth, C. (2000). Monitoring povertyand social exclusion [online] retrieved 20 May 2007http://jrf.org.uk/bookshop/eBooks/1859351298.pdf

Sapir, A. (2005). Globalisation and the Reform of European Social Models, BruegelPaper, Bruegel, Brussels, 2005

The Roeher Institute (2003),Policy Approaches to Framing Social InclusionExclusion: An Overview. Toronto, ON: The Roeher Institute
http://inclusivecities.ca/publication/reports/2006/edmonton-report.pdfhttp://jrf.org.uk/bookshop/eBooks/1859351298.pdfhttp://jrf.org.uk/bookshop/eBooks/1859351298.pdfhttp://inclusivecities.ca/publication/reports/2006/edmonton-report.pdf


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17

APPEN

DIX

A

Thefo

llowingtablegivesforeachva

riableuseditstime-span,descr

iptionandsourse

Variable

Time

span

Description

Source

Long-term

unemployment

[%]

1995-

2006

L

ong-termunemployed(12monthsandmore)personsarethoseagedatleast15yearsnot

livingincollectivehouseholdswho

arewithoutworkwithinthenext

twoweeks,areavailable

tostartworkwithinthenexttwo

weeksandwhoareseekingwo

rk(haveactivelysought

e

mploymentatsometimeduringthepreviousfourweeksorareno

tseekingajobbecause

theyhavealreadyfoundajobtos

tartlater).

Thetotalactivepopula

tion(labourforce)isthe

totalnumberoftheemployedand

unemployedpopulation.

Thedurationofunemploymentis

d

efinedasthedurationofasearchforajoborasthelengthofthe

periodsincethelastjob

w

asheld(ifthisperiodisshorterth

anthedurationofthesearchfora

job).

EUR

OSTAT

VeryLong-term

unemployment

[%]

1995-

2006

V

erylong-term

unemploymentratesrepresentverylong-term

unemployedpersonsasa

p

ercentageofthelabourforce.Ve

rylong-termunemployed(24mo

nthsandmore)persons

a

rethoseagedatleast15years

notlivingincollectivehousehold

swhoarewithoutwork

w

ithinthenexttwoweeks,areava

ilabletostartworkwithinthenexttwoweeksandwhoare

seekingwork(haveactivelysoughtemploymentatsometimeduring

thepreviousfourweeks

o

rarenotseekingajobbecausetheyhavealreadyfoundajobtost

artlater).

Thedurationof

u

nemploymentisdefinedasthedurationofasearchforajoboras

thelengthoftheperiod

sincethelastjobwasheld(ifthisperiodisshorterthantheduration

ofthesearchforajob).

T

he

totalactive

population

(labourforce)isthe

totalnumber

ofthe

employed

and

u

nemployedpopulation.

EUR

OSTAT

Suiciderate

[/100,0

00]

1995-

2005

N

umberofpeoplediedbysuicide

EUR

OSTAT

Self-perceived

health(bad)

[%]

1996-

2001

S

elfperceivedhealthbysex,age,educationandactivitystatus(Source:ECHP

UDB,

E

urostat,06/2003)

EUR

OSTAT

Self-perceived

health

(verybad)

1996-

2001

S

elfperceivedhealthbysex,age,educationandactivitystatus(Source:ECHP

UDB,

E

urostat,06/2003)

EUR

OSTAT


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Social

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18

[%]

Ginicoefficient

1995-

2005

T

easurestheinequalityofdistributionofincome.

Thevaluelaysbe

tween0and1,where0

correspondstoperfectincomeequ

alityand1toperfectincomeinequality.

W

IDER

Genderpaygap

[%]

1994-

2005

D

ifferencebetweenmen'sandwo

men'saveragegrosshourlyearn

ingsasapercentageof

m

en'saveragegrosshourlyearningsGenderpaygapisgivenas

thedifferencebetween

a

veragegrosshourlyearningsofmalepaidemployeesandoffemalepaidemployeesasa

p

ercentageofaveragegrosshourlyearningsofmalepaidemployees.

Thepopulation

consistsofallpaidemployeesaged16-64thatare'atwork15+hoursperweek'.

EUR

OSTAT

At-riskofpoverty

rate

[%]

1995-

2005

T

heshareofpersonswithane

quivaliseddisposableincomeb

elow

therisk-of-poverty

threshold,whichissetat60%of

thenationalmedianequivaliseddisposableincome(after

socialtransfers

EUR

OSTAT

Persistentat-riskof

povertyrate

[%]

1995-

2005

T

heshareofpersonswithane

quivaliseddisposableincomeb

elow

therisk-of-poverty

thresholdinthecurrentyearandin

atleasttwooftheprecedingthre

eyears.

Thethresholdis

setat60%ofthenationalmedian

equivaliseddisposableincome.

EUR

OSTAT

Publicsocial

expenditures

1980-

2000

S

ocialexpenditure

isthe

provis

ion

bypublicinstitutionsofbe

nefitsto,andfinancial

contributionstargetedat,householdsandindividualsinorderto

providesupportduring

circumstanceswhichadverselyaffecttheirwelfare,providedthatthe

provisionofthebenefits

a

ndfinancialcontributionsconstitutesneitheradirectpaymentforaparticulargoodor

servicenoranindividualcontracto

rtransfer.Suchbenefitscanbecashtransfers,orcanbe

thedirect(in-kind)provisionofgo

odsandservices.

OEC

DSocial

Exp

enditure

Da

tabase

Changeinreal

GDPpercapita

1971-

2000

OECD

National

Ac

counts


19/27

Social

Europe(s)

19

APPEN

DIX

B

Rawd

ataforeachvariablepersub-in

dicator(socialinclusion,

inequalityandpovertyrespectively)

.


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Europe(s)

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Social

Europe(s)

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22/27


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Europe(s)

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Social Europe(s) 24

APPENDIX C

Values for partial (sub-indicator) and final indicators for each individual country, grouped by social system (Nordic, Contintal, Mediterranean and Anglo-Saxon

respectively); last table represents the aggregate EU-15 data.


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social cohesion paper

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