Rising Economic Prosperity and Social Quality the Case of New Member States of the European Union

Rising Economic Prosperity and Social Quality the Caseof New Member States of the European Union

Pamela Abbott • Claire Wallace

Accepted: 2 January 2012� Springer Science+Business Media B.V. 2012

Abstract This paper considers whether rising economic prosperity in the New Member

States of the European Union since joining the EU is also reflected in better a quality of life

and what constitutes a better quality of society for the citizens of these countries. The paper

contributes to the debate about the relationship between economic conditions and sub-

jective well-being by showing that the factors that contribute to the latter have not only

changed with economic growth but that subjective life satisfaction has also improved. Here

we consider how this relationship can be explained by using the Social Quality model to

measure the quality of society. We look specifically at the New Member States of the

European Union (Latvia, Lithuania, Estonia, Poland, Czech Republic, Slovakia, Slovenia,

Hungary, Romania and Bulgaria) using the European Quality of Life Surveys for 2003 and

2007. This covers a period during which the economic conditions of these societies

improved and they modernised. The social quality model explains a great deal of the

variance in life satisfaction and helps us to show that as well as economic factors, other

aspects of the quality of society, such as social integration and empowerment, are also

important. We argue that economic and social factors have to be understood as interacting

with other aspects of society if we seek to understand the quality of society.

Keywords Social quality � Life satisfaction � New member states � Economic change

1 Introduction

Eight of the ten new member states of the European Union which joined in 2004 (Lith-

uania, Latvia, Estonia, Poland, Hungary, Czech Republic, Slovakia and Slovenia), as well

as those that joined in 2007 (Bulgaria and Romania), were post-communist countries which

had suffered economic hardships since the introduction of market capitalism from 1989

onwards. They have also experienced the disintegration of the previous social and political

system that had been held in place by the old regime, with consequent disruption and

P. Abbott � C. Wallace (&)Aberdeen, UKe-mail: [email protected]

123

Soc Indic ResDOI 10.1007/s11205-012-9992-0

anomie (Genov 1998; Abbott and Sapsford 2006). The subsequent absorption of these

societies into the economic and political orbit of the European Union, culminating in their

accession, has helped to modernise and improve their economies although this was not a

uniform process (Delhey 2001; Rose et al. 2009). Our first question is whether this is

reflected in higher levels of life satisfaction? Our second question is if this is the case, then

what aspects of the social context have made a difference? In order to ascertain this we

need to look at a range of different indicators of societal quality and these have been

theoretically developed as the ‘‘Social Quality Model’’ (Abbott and Wallace forthcoming).

Rather than simply adding a list of various indicators (as is often the case in studies of

subjective well-being) the indicators we have chosen reflect four different dimensions of

societal quality: economic security; social inclusion; social cohesion; and social empow-

erment (Beck et al. 1997, 2001).

Whilst it is often claimed that the idea of quality of life should be measured as

something beyond economic progress (Hagerty et al. 2001; Layard 2005), there is nev-

ertheless substantial debate about the relationship between economic progress and other

indicators of social progress. More specifically, economic growth and happiness or life

satisfaction are not linked in a linear way. For example, Richard Easterlin has argued that

as the economies of countries grow overall, life satisfaction does not increase corre-

spondingly once a certain level of prosperity has been reached. Even within societies,

income differences become less important in explaining life satisfaction over time as levels

of affluence increase (Easterlin 1974, 2000). Nevertheless, most agree that economic well-

being, both in the form of individual income and economic prosperity of the society as

measured by GDP per capita, remains important (Headey et al. 2008; Stanca 2010).

Therefore it is necessary to taken into account a range of drivers for explaining happiness

or satisfaction in addition to economic prosperity as measures of the quality of life (Diener

and Suh 1997; Stiglitz et al. 2009).

Studies of the transforming societies of Eastern Europe have shown that there is a

close relationship between rising affluence and rising satisfaction (Guriev and Zhu-

ravskaya 2009; Namazie and Sandfrey 2001; Sablonniere et al. 2009). Furthermore, those

that have compared new member states with the more prosperous EU countries have

found that economic factors are more important in the former countries (Bohnke 2008;

Fahey and Smyth 2004). In these cross-sectional studies it seems that economic factors

are relatively more important in determining life satisfaction in the less prosperous

countries, such as those of East-Central Europe. Indeed, research has pointed to the fact

that not only are the economic levels of the countries in question lower than those in

Western Europe, but they score lower on almost all measures of societal quality (Alber

et al. 2008). However, evidence suggests that there may have been some ‘‘catching up’’

taking place in recent years, due to European Union investment and with the moderni-

sation of the social and political systems (Rose et al. 2009). The question is therefore, if

we look at differences over time rather than cross-sectionally, how have these societies

changed?

Most studies have concluded that societal, institutional and cultural factors are

important mediators between subjective well-being and the macroeconomic level, whether

it be the quality of governance of a society, the welfare state or regional cultural variations

(Fahey and Smyth 2004; Grasso and Canova 2008; Haller and Hadler 2006), leading some

to question the usefulness of universal indicators such as GDP or the Human Development

Index (HDI) as adequate measures of societal well-being per se (Bonini 2008), especially

since they do not contain any subjective indicators.

P. Abbott, C. Wallace

123

The question is therefore: what aspects of social life in the former communist countries

are relevant for improving life satisfaction? This can help us to understand the role of

economic growth in a social context. We argue that this relationship can be explained

by using the Social Quality Model. Whilst subjective well-being is mainly concerned

with individual perceptions (for example the role of ‘having’, ‘loving’ and ‘being’

defined by Allardt and others (Allardt 1993), we argue that it is the social contextwhich is important for determining individual well-being and this is shaped both by the

structure of society and by macroeconomic conditions. For this purpose a more

sociological explanation is required (Haller and Hadler 2006). Whilst a number of

authors have noted the increase in happiness or life satisfaction in Eastern Europe, the

relationship to other societal dimensions still remains under-explored (Lelkes 2006;

Hayo 2007; Baltescu 2010; Selezneva 2011). It is this dimension that we will explore

here, linking it to changes in macroeconomic performance as measured by GDP per

capita (PPP US$).

This paper is based upon data from the 2003 and 2007 European Quality of Life

surveys in the former communist countries of Central and Eastern Europe that are now

members of the European Union. The aim is to consider the influence of both economic

and societal quality factors on subjective life satisfaction. We recognise that the period

between 2003 and 2007 is relatively short and a measurement of two points in time does

not demonstrate a trend. Nevertheless, at least until the economic crisis of 2008, the

countries under consideration had been experiencing significant growth in their formal

economies, so these countries are good ones on which to test the changing relationship

between rising economic prosperity and life satisfaction. We therefore proceed in four

stages. First, we look at economic growth and how it has affected these countries.

Secondly we look at the life satisfaction and whether this has increased correspondingly.

Thirdly, we look at whether indicators of societal quality have increased over the same

period. Finally, we consider what aspects of social and economic life contribute to life

satisfaction and how these may have changed as the societies in question developed

between the two time periods.

2 GDP and Subjective Well-Being: Are They Both Rising?

Following the decline in the economies of the former communist countries in the 1990s

there has been economic growth in the first decade of the twenty-first century. Between

2003 and 2007 the economies of all ten countries grew, with GDP per capita (PPPUS$)

growing between 19% (Hungary) and 61.5% (Romania) (see Table 1). Despite the

uneven growth between the countries their relative ranking changed little between the

2 years with Slovenia remaining the wealthiest and Bulgaria slipping one place with

Romania moving up one place as the poorest. Differences in GDP between the countries

are also relatively large with that for Slovenia (the wealthiest country) being over twice

that for Bulgaria and Romania. Although there have been significant growth rates, the

gap between the new member states and the EU 15 is nevertheless wide in 2003 and

2007 (Rose et al. 2009).

Life satisfaction also rose in all new member states except Hungary between 2003 and

2007 from a mean value of 5.77 to one of 6.31 (see Table 2). The change in the mean

values varied from ?0.97 in Lithuania and Romania to -0.38 in Hungary. Bulgaria,

despite an increase of 0.48, in general satisfaction remained the least satisfied country and

Slovenia with an increase of 0.15 remained the most satisfied (see Table 2).

Rising Economic Prosperity

123

In 2003 there was a reasonably good fit between life satisfaction and GDP PPPUS$

although Romania and Poland were generally more satisfied than would be predicted from

GDP and Lithuania and Slovakia less so. In 2007 Poland and Romania were again gen-

erally more satisfied than would be predicted from GDP with Hungary and the Czech

Republic being less satisfied. We should note that this was following an economic crisis in

Hungary.

3 Quality of Society

It is important to distinguish between societal well-being and individual well-being,

although the two are inextricably linked (Bohnke 2008; Fahey and Smyth 2004; Fahey and

Smyth 2004; Watson et al. 2009). The former provides the context in which individuals are

Table 1 Gross domestic product per capital (PPPUS$) by country 2003–2008

2003 2004 2005 2006 2007 Difference2003–2007 (%)

Bulgaria 6,700 7,300 7,800 8,600 9,300 ?38.8

Czech Republic 15,200 16,300 17,100 18,300 20,000 ?31.5

Estonia 11,300 12,400 13,700 15,400 16,900 ?49.6

Hungary 13,100 13,700 14,200 15,000 15,600 ?19

Latvia 9,000 9,900 10,900 12,400 14,400 ?60

Lithuania 10,200 10,900 11,900 13,100 14,800 ?45.1

Poland 10,100 11,000 11,500 12,400 13,400 ?32.7

Romania 6,500 7,400 7,900 9,100 10,500 ?61.5

Slovakia 11,500 12,400 13,500 15,000 16,700 ?45.2

Slovenia 17,300 18,700 19,600 20,700 22,200 ?28.3

Sources Eurostat, Nominal GDP per capial purchasing power standards. Annual data. http://epp.eurostat.eu.europa.eu/portal/page/portal//national_accounts/data/database

Table 2 Life satisfaction by country 2003 and 2007

Country Satisfaction 2003 Satisfaction 2007 Difference 2003and 2007

Mean SD Mean SD

Bulgaria 4.42 2.315 4.90 2.013 ?0.48

Czech Republic 6.41 2.103 6.52 2.121 ?0.11

Estonia 5.81 2.023 6.65 1.950 ?0.84

Hungary 5.89 2.187 5.51 2.250 -0.38

Latvia 5.48 2.125 6.03 2.154 ?0.55

Lithuania 5.33 2.154 6.20 2.124 ?0.97

Poland 6.18 2.290 6.79 2.079 ?0.61

Romania 6.11 2.281 6.46 2.058 ?0.35

Slovakia 5.59 2.363 6.56 2.041 ?0.97

Slovenia 7.01 1.964 7.15 1.952 ?0.14

Mean FCC 5.77 2.290 6.31 2.164 ?0.61


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http://epp.eurostat.eu.europa.eu/portal/page/portal//national_accounts/data/database

http://epp.eurostat.eu.europa.eu/portal/page/portal//national_accounts/data/database

able to flourish and grow—the capability structure (Nussbaum and Sen 1993; Sen 1999). In

this context we need to consider the opportunities that society provides for individuals to

build their capabilities and the resources that are available for individuals to utilize in

securing their own and their families’ welfare. In the latter sense, well-being is sub-

jective—it is our understanding of our condition—but it is constituted through social

interactions and cultural meanings and is therefore socially embedded. The quality of

society influences social engagement and the higher the quality of a society the more

options people have to plan and make arrangements for the future (Abbott and Wallace

forthcoming). There is a strong relationship between economic performance and the

quality of governance in a society and individuals perception of the quality of their society

(Bohnke 2008; Haller and Hadler 2006). Therefore, agency and the ability to build

capabilities is dependent on social and geographical location as well as individuals per-

ceptions of the opportunities available to them, which are in turn influenced by their

position in the societal opportunity structures (Fahey and Smyth 2004).

The Social Quality Model specifies both the conditions for individual well-being and the

conditions for building and sustaining societies that are able to ensure the well-being of

their members. It measures the quality of the social context of everyday life, and differs

from other approaches to subjective well-being in that it is grounded in a theory of ‘‘the

social’’ and in sociological understandings of society, which are the outcome of the dia-

lectical relationship between the formation of social collectivities and the self-realisation of

the human subject. It is concerned with the recursive relationship between system and

community or system integration and social integration (Lockwood 1992) and between

agency and structure (Giddens 1984). It measures the extent to which the quality of daily

life provides for an acceptable standard of living, taking account of the structural features

of societies and their institutions as assessed by reference to their impact on citizens (Beck

et al. 1997). The Social Quality Model is essentially a normative one, arguing for what

conditions citizens should expect in a good society, but one which enables us to measure

social progress (Phillips 2006).

The Social Quality model is seen as a holistic construct which measures four com-

plementary aspects: that influence quality of life. The first dimension, economic securitymeans having available the necessary material resources for a decent life; the second

dimension social inclusion, having access to the necessary institutional and infrastructural

context; the third dimension social cohesion, that the necessary social structures, with

collectively accepted values and norms are in place; and the fourth dimension, empow-erment, that people feel that they have the capacity to take control over their own lives and

have the necessary knowledge, skills and conditions to do so. The model is based on the

assumption that the welfare of citizens is influenced by all four quadrants so that they form

the conditions for each other and influence the outcome and economic security is inade-

quate on its own. It enables us to theoretically derive indicators to correlate with subjective

life satisfaction and test the extent to which life satisfaction is influenced by the four

constituent elements of the model. The indicators are measures of the underlying conceptsof economic security, social cohesion, social integration and empowerment rather than

only measures in themselves, as we have argued elsewhere (Abbott and Sapsford 2006;

Abbott and Wallace forthcoming). We use life satisfaction as the dependent variable

because it is the test of the ability of the social system to deliver satisfaction to its citizens.

Our main hypothesis is therefore that subjective life satisfaction will have improved during

the two periods (in tandem with macroeconomic growth) but that this can be explained by

the increasing importance of non-economic factors in the composition of social quality.


123

4 Methods

The 2003 and 2007 European Quality of Life Surveys serve as the data bases for the

empirical analysis. In the 2003 a 28 country survey was carried out covering the then EU

and candidate countries—at that time the new member states of Central Europe were not

yet EU members. In 2007 the survey covered 31 countries, the 27 EU member states, three

candidate countries and Norway. By that time, eight post-communist states had joined in

2004 (Lithuania, Estonia, Latvia, Poland, Czech Republic, Slovakia, Slovenia and

Hungary) and two more had just joined in 2007 (Romania and Bulgaria). Prior to joining

the EU, these countries had been subject to EU harmonisation strategies as part of the

accession process. In 2003 the questionnaire was fielded by Infomart GFK and in 2007 by

TNS Opinion, these organisations having responsibility for assigning national institutes to

draw random samples of around 1,000 respondents (but with 600 in Slovenia and Estonia

in 2003 and 1,500 in Poland in 2007) and conduct the interviews in each country. In both

years the survey collected comparable information on household and family composition,

working conditions, social position, income and standard of living, time use and work-life

balance, housing conditions, political participation, social support and social networks,

health and subjective well-being. Some changes were made to the questionnaire between

waves, with additional questions being asked in 2007 but the key elements for measuring

quality of society and subjective well-being were retained (Anderson et al. 2009).

In this paper we use the data for the 10 former communist countries of Eastern and

Central Europe that are now members of the EU, a total of 9,301 in respondents in 2003

and 10,949 in 2007. We first consider the extent to which people’s overall evaluation of

their quality of life had changed between 2003 and 2007. We then construct a model, based

on Social Quality, and test the extent to which it measurers the quality of life in the

countries under consideration by carrying out an OLS regression with life satisfaction as

the dependent variable. This has already been validated in both surveys for the whole of the

EU and found to be stable across time and across countries (Abbott and Wallace forth-

coming). Although we cannot measure a trend using only two cross national surveys at

different time points, it does enable us to look at whether the quality of society was

different in 2007, after there had been substantial economic growth, when compared with

2003.

In constructing the model we have selected as indicators variables from a rich data set as

indicative of the underlying constructs we are measuring using ‘‘realist’’ social theory

(Craib 1984). Undoubtedly we could have explained more of the variance if we had

included additional indicators but this would have made the model more difficult to

interpret and was not necessary for our purpose here as we are testing the four underlying

constructs rather than variations in individual indicators.

In order to test our main hypothesis that social quality improved in the region between

2003 and 2007 we carried out a series of OLS regressions with life satisfaction as the

dependent variable, controlling for age and gender for 2003 and 2007. We entered the

variables in four blocks: economic security; social cohesion; social integration, and;

empowerment. Finally, using Slovenia as the reference, we tested our models to see if they

held for all the countries. We tested the model for multicollinearity and found it to be

satisfactory as the tolerance of no variable was below 0.4. The levels of single order

correlations between the dependent and independent variable were also tested and found to

be acceptable.

We should note that there were a number of changes in the questionnaire between 2003

and 2007 and this makes the comparison of some individual variables impossible but does


123

not impact on our ability to construct comparable models. In 2003 there was not a question

in trust in government but we were able to compute a scale from two questions: trust in the

government to deliver state pensions and trust in the government to deliver social benefits

(for details on the construction of scales and the exact wording of questions, see

Appendix).

To construct our model we use a number of variables as indicators of the underlying

constructs of Social Quality in which we were interested. The main variables are shown in

Fig. 1 in terms of the quadrants of the Social Quality Model. The precise coding and

question wording are shown in the Appendix. Each scale was constructed after carrying out

a Factor Analysis with varimax rotation and calculating the Cronbach’s Alpha to ensure

internal reliability. We use scales because they even out random variability and are more

stable.

5 Life Satisfaction and Economic Development

The generally accepted measure of economic growth is changes in GDP. This grew

between 2003 and 2007 in all 10 countries as we noted above (Table 1). However, mac-

roeconomic indicators are not necessarily reflected in the experiences of individual

households, because GDP is an overall average measure. If we turn to the variables that

constitute our first dimension, economic security, a more mixed picture emerges. Whilst

there was an overall increase in economic security, with only 23.8% having difficulty in

making ends meet in 2007 as compared with 37.8% in 2003, people in the Bulgaria,

Hungary, Slovakia and Slovenia reported having more difficulties in 2007 than in 2003.

However, the mean scores on the deprivation index, which indicates if households can

afford to buy a range of different goods, suggest that economic situation was improving

with the exception of Hungary and Slovenia where it remained stable (Tables 3, 4).

Therefore, the consumption potential of households increased or stabilised over the period,

even if many households continued to feel poor. We can conclude that, in line with the

increase in GDP, there is evidence of economic growth across the region and a decline in

deprivation and absolute poverty, although many households were still struggling to make

ends meet.

Other aspects of societal quality did not necessarily improve. For example, there was an

overall decline in general trust (Table 5) everywhere except Poland and Romania, and this

Economic Security Income of the household Deprivation index Ability to afford basic food (absolute poverty) Ability to afford to make ends meet

Social Cohesion General trust Trust in government Perception of social conflict

Social Inclusion Social support Frequency of contact with friends and relatives Marital status Vote in elections Membership of political party/trade union Feeling left out of society

Social Empowerment Education Self evaluation of health Extent of control of one’s life

Fig. 1 Variables used for social quality


123

was one element of social cohesion. If we turn to social inclusion, feeling left out of society

has declined sharply from 24.0 to 13.2%, except in Hungary, where it increased (Table 6).

In terms of social empowerment, Table 7 shows a general increase in social control. The

number of people feeling that life was too complicated had dropped from 47.3 to 27.4%

and this trend was true for all countries except for Romania.

Therefore it is not the case that indicators of societal quality all show a positive

trend—in fact only some of them do. Therefore the effects of economic improvement

were not evenly distributed across the region, perhaps due to the rising levels of income

inequality1. In order to look at this more systematically, we now turn to multiple

regression analysis.

Table 3 Difficulty/greatdifficulty in making ends meet(points 5 and 6)

2003 2007

Bulgaria 34.2 45.9

Czech Republic 17.6 14.8

Estonia 28.4 13.9

Hungary 28.6 35.6

Latvia 40.3 26.4

Lithuania 35.3 14.2

Poland 53.4 25.7

Romania 42.3 31.5

Slovakia 16.1 19.0

Slovenia 12.1 13.8

Average 37.8 23.8

Table 4 Deprivation index(6 can afford all,12 afford none)

Social cohesion

2003 2007

Mean SD Mean SD

Bulgaria 10.22 1.7 9.10 2.0

Czech Republic 7.6 1.7 7.24 1.6

Estonia 8.8 2.0 7.49 1.7

Hungary 8.4 1.9 8.42 1.9

Latvia 9.1 1.9 8.15 1.9

Lithuania 9.5 2.0 8.36 1.94

Poland 8.7 1.9 7.99 1.9

Romania 9.6 1.9 8.66 2.1

Slovakia 8.5 2.0 8.04 2.0

Slovenia 6.8 1.4 6.89 1.4

Average

1 http://data.worldbank.org/.


123

http://data.worldbank.org/

Table 5 General trust—cannottrust people (1 lowest 10 highest)

2003 2007

Mean SD Mean SD

Bulgaria 4.50 2.5 4.04 2.1

Czech Republic 4.78 2.2 4.51 2.40

Estonia 5.47 2.1 5.23 2.39

Hungary 4.96 2.2 4.63 2.83

Latvia 4.96 2.4 4.13 2.45

Lithuania 4.95 2.3 4.42 2.46

Poland 4.71 2.3 4.77 2.24

Romania 5.42 2.4 5.54 2.10

Slovenia 4.43 2.2 4.98 2.35

Slovakia 5.49 2.1 5.18 2.47

Average 4.93 2.3 4.74 2.37

Table 6 Feel left out (percentagree/somewhat agree)

2003 2007

Bulgaria 29.2 23.3


Estonia 21.2 9.2

Hungary 8.7 9.0

Latvia 27.5 10.5

Lithuania 25.3 12.8

Poland 22.4 13.9

Romania 20.1 10.9

Slovakia 29.1 6.4

Slovenia 26.6 5.7

Average 24.0 13.2

Table 7 Social control (percentagree somewhat agree lifebecome too complicated)

2003 2007

Bulgaria 65.0 44.0


Estonia 42.9 19.6

Hungary 34.0 26.0

Latvia 45.9 23.3

Lithuania 58.2 28.6

Poland 48.8 24.4

Romania 21.9 24.4

Slovakia 54.2 24.3

Slovenia 39.2 25.4

Average 47.3 27.4


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6 Multiple Regression Analysis

The multiple regression analysis showed that all four elements of the Social Quality Model

contributed to explaining the variation in life satisfaction and that the model is stable

across the two waves (Tables 8, 9). In 2003 the model explained 41.8% of the variance and

in 2007 39.6%. When we entered the countries as dummies with Slovenia as the reference

country the variance explained increased marginally to 43.8% in 2003 but did not increase

significantly in 2007 (Tables 10, 11). The country Betas were very low even when sig-

nificant and suggest that in 2003 Poles, Hungarians, Bulgarians and Slovaks were mar-

ginally less satisfied than would be predicted by the model and Romanians more satisfied.

In 2007 the Hungarians were more dissatisfied than would be predicted by the model and

the Bulgarians marginally more satisfied.

In the regression analysis we entered age 2 and gender as controls on Step 1 (Tables 8,

9). In both years the variance explained was trivial and non significant. We then went on to

add variables from each component of the Social Quality Model in turn in order to look at

their contribution to explained variance. In Step 2 we entered the economic security

variables and the variance explained increased to 28.6% in 2003 and 25.2% in 2007 with

self assessed ability to make ends meet making the greatest contribution to the variance

explained closely followed by the deprivation scale in both years. Inability to afford basic

food also made a significant contribution but income did not.3 In step 3 we added the social

cohesion indicators and the variance explained increased to 36.6% in 2003 and 30.6 in

2007. The economic variables continued to make a strong but reduced contribution to the

variance explained and general trust and trust in government also made strong contribu-

tions with the conflict scale making a relatively small but significant contribution. In Step 4

we added in the indicators of social integration and the variance explained increased to

39.2% in 2003 and 34.9% in 2007. The economic variables remained strong although their

contribution declined as did the trust variables. The conflict scale no longer made a

significant contribution in 2003 although it continued to make a small but significant

contribution in 2007. In terms of social integration the only indicator that made a strong

significant contribution in both years is feeling left out with some indication that social

support/contact with friends and relatives may make a relatively small contribution. On

Step 5 we added the empowerment indicators and the variance explained increased to

41.8% in 2003 and 38.8% in 2007. In both years economic variables continued to make a

strong contribution as did the trust variables and feeling left out. In both years health status

and feeling that life is too complicated made strong contributions to the variance explained.

If we look at the significant indicators in the model for 2003 and 2007 (Tables 8, 9) we

can see a consistency in them. In terms of economic variables the two that make a

significant contribution to the variance explained are the deprivation scale and the ability to

make ends meet. In terms of social cohesion it is general trust and trust in government that

is important, for social integration it is the feeling of being integrated (or not) that makes a

noticeable contribution whilst for empowerment it is health status and feeling in control

that are important.

We can conclude that all steps added to the model but that economic security was still

the more important in 2003 and 2007. The model had slightly more explanatory power

2 We did not use the square of age because previous research indicates that life satisfaction declines withage in these countries and does not follow the U-shape found elsewhere Bohnke (2008).3 Household income was equivalised between countries and we used the pre-coded variable in the data setin each case.


123

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123

in 2003, but in both years around 40% of the variance can be explained using only a few

indicators. This is because the indicators are themselves indicative of underlying constructs

which are posited in the model, as we have argued above.

Table 10 Country differencesin subjective satisfaction(OLS regression) 2003 formercommunist NMS andcandidate countries

* p \ 0.001 ** p \ 0.001Reference country is Slovenia

Variables B Beta SE

Constant 5.436 0.675

Age 0.001 0.010 0.002

Gender 0.216 0.047** 0.055

Economic

HH Income 0.000 0.012 0.000

Deprivation scale -0.135 -0.121** 0.020

Make ends meet -0.391 -0.214** 0.031

Food 0.283 0.054** 0.075

Social cohesion

General trust 0.000 0.189** 0.012

Trust government -0.145 -0.097** 0.018

Conflict scale 0.023 0.021 0.013

Social integration

Support ill 0.018 0.001 0.220

Support advice 0.270 0.020 0.172

Support depressed 0.141 0.011 0.166

Support money 0.111 0.020 0.073

Married 0.174 0.037* 0.059

Contact parents 0.014 0.012 0.018

Contact children 0.007 0.007 0.015

Contact friends 0.056 0.028 0.024

Relatives/friends letter etc 0.091 0.018 0.065

Feel left out 0.205 0.085** 0.033

Vote -0.081 -0.014 0.069

Meeting TU etc 0.046 0.006 0.093

Empowerment

Life complicated 0.348 0.159** 0.030

Health -0.232 -0.111** 0.030

Education -0.089 -0.024 0.048

Countries

Czech Republic -0.135 -0.017 0.131

Estonia -0.015 -0.022 0.146

Hungary -0.330 -0.046* 0.129

Latvia -0.095 -0.012 0.137

Lithuania -0.109 -0.013 0.138

Poland 0.599 0.074** 0.140

Slovakia -0.394 -0.057* 0.125

Bulgaria -0.642 -0.084** 0.141

Romania 0.393 0.064** 0.131

Adjusted R2 0.438


123

Table 11 Country differencesin subjective satisfaction(OLS regression) 2007 formercommunist NMS

* p \ 0.001 ** p \ 0.001Reference country is Slovenia

Variables B Beta SE

Constant 1.069 1.409

Age 0.007 0.056** 0.002

Gender 0.117 0.027 0.047

Economic

HH Income 0.000 0.001 0.000

Deprivation scale -0.125 -0.112** 0.017

Make ends meet -0.300 -0.169** 0.025

Food 0.297 0.048** 0.076

Social cohesion

General trust 0.091 0.098** 0.010

Trust government 0.113 0.130** 0.010

Conflict scale 0.024 0.030* 0.009

Social integration

Support ill -0.436 -0.026 0.191

Support advice -0.218 -0.016 0.153

Support depressed -0.133 -0.012 0.125

Support money -0.248 -0.042** 0.067

Married 0.112 0.025 0.049

Contact parents 0.016 0.004 0.055

Contact children 0.003 0.001 0.051

Contact friends 0.008 0.001 0.058

Relatives/friends letter etc 0.117 0.020 0.067

Feel left out 0.304 -0.138** 0.028

Vote -0.050 -0.020 0.027

Meeting TU etc -0.005 -0.001 0.085

Empowerment

Life complicated 0.279 0.144** 0.025

Health -0.284 -0.128** 0.029

Education -0.055 -0.011 0.055

Countries

Czech Republic 0.213 0.032 0.096

Estonia 0.369 0.051** 0.103

Hungary -0.778 -0.112** 0.102

Latvia 0.318 0.039* 0.111

Lithuania 0.163 0.022 0.103

Poland -0.312 -0.047** 0.098

Slovakia 0.259 0.039* 0.099

Bulgaria 0.764 0.091** 0.119

Romania -0.086 -0.012 0.108

Adjusted R2 0.398


123

7 Conclusions

In this paper we have started by looking at overall growth in GDP per capita (PPP US$) in

the ten New Member States of the European Union in the first decade of the twenty-first

century, which has been substantial in all the countries under consideration, although not to

the same extent. When we look more carefully at the experiences of households in terms of

economic security and wellbeing, a more mixed picture emerges. Economic growth at the

macro level was not reflected in all countries by an increase of self reported economic

security at the household level, possibly on account of variations in the population,

including the different positions of ethnic minorities (Siposne Nandori 2011) or because of

feelings of relative deprivation—the feeling that they are not as well off as they expected

to be, or as their neighbours. However, there was a decline in deprivation as measured by

the deprivation index in most countries. Therefore, we should beware of using GDP per

capita alone as a measure of economic improvement since some subjective (micro level)

measures do not correspond entirely with objective (macro level) ones.

We have argued that an increase in well-being is about more than growth in GDP and

that it is necessary to consider social as well as economic indicators. During the same

period, there was a modest but noticeable increase in life satisfaction across the region,

with the exception of Hungary. However, to understand the increase in life satisfaction we

need to take into account other factors in the composition of societal quality.

In order to take a broader perspective and consider societal development we constructed

a model derived from sociological theory, the Social Quality Model, that considers social

and system integration, agency and structure and takes account of subjective indicators.

We tested the model by a carrying out an OLS regression with life satisfaction as the

dependent variable. We demonstrated that our model was stable over time and fitted all the

countries. We show that economic factors are important in societal development but so are

social cohesion, social integration and empowerment.

We have shown that the importance of different variables in explaining life satisfaction

within Social Quality has changed little between 2003 and 2007 (Bohnke 2008; Fahey and

Smyth 2004). This is the case for Central and Eastern European New Member States and

we are able to show which aspects of social development are now more important for

citizens of these countries. It is possible that at least some of these countries have now

reached the level of development where economic well-being is no longer so important for

individual well-being because it is taken as given. However, it is also likely that the

economic recession, which struck the countries of Central and Eastern Europe especially

hard during the period after the last survey was completed, would have had an impact on

these findings, but this will have to be investigated in subsequent research.

This has important implications for public policy. It means that improving economic

performance will not increase the quality of society unless there is also a decline in income

inequality and improvements are reflected in households’ ability to manage their economic

well-being. A general improvement in GDP per capita does not necessarily translate

directly into better well-being for households as we need to take into account the social and

economic structure of the society. So it is insufficient to concentrate on these economic

factors alone. Improving the quality of society also involves improving the cohesion and

governance of the society—the levels of general trust and the trust in government insti-

tutions, for example, the former of which had declined. In addition to these structural

features, the quality of society depends upon levels of social integration, which become

relatively more important as economic prosperity increases, and empowerment—that is the

ability of individuals to feel that they can control their environment. Therefore


123

governments need to focus more upon improving health, education and the participation of

citizens enabling them to take control of their lives and their environment in addition to

economic development.

This paper points to a number of topics for further research which were beyond the

scope of this paper. For example, we have not included objective variables such as the Gini

index of inequality or levels of unemployment, which might have helped to explain the

differences between 2003 and 2007. Furthermore, we have used only one variable as a

dependent variable—life satisfaction—and there should arguably be a more comprehensive

measure of well-being, which is something we will continue to work upon. Other indicators

of the four dimensions could perhaps be found, although the ones selected here explain a

lot of the variation in societies more data points and would be able to show more general

trends.

Acknowledgments We would like to acknowledge the work of the European Foundation for theImprovement of Living and Working Conditions in Dublin who sponsored the survey. Publications from theEuropean Foundation can be found on their website at http://www.eurofound.europa.eu/.

Appendix

Variables Used in the Analysis Dependent Variable

Social Satisfaction

All things considered, how satisfied would you say you are with your life these days?Please tell me on a scale of 1 to 10, where 1 means very dissatisfied and 10 means verysatisfied.

To construct our model we use a number of variables as indicators of the underlying

constructs we were interested in. Age—a continuous variable Gender coded 1 = male,

2 = female.

For economic security we used:

1. The income of the household;

Please can you tell me how much your household’s NET income is? If you don’t knowthe exact figure, please give an estimate.

2. A deprivation index constructed from a series of question concerning the ability to buy

essential goods and services as a measure of relative deprivation4.

There are some things that many people cannot afford, even if they would like. For eachof the following —–can your household afford it if you want it?

Keeping your house adequately warmPaying for a week’s annual holiday away from home(not staying with relatives)Replacing any worn-out furniture A meal with meat chicken or fish every second day

Buying new rather than second hand clothes Having friends or family for a drink or a mealat least once a month

Cronbach’s Alpha: 2003 0.86; 2007 0.84.

4 All scales were constructed using factor analysis with varimax rotation and checked for reliability usingCronbach’s Alpha.


123

http://www.eurofound.europa.eu/

3. Inability to afford to buy basic food as a measure of absolute poverty coded 1 = yeas,

2 = no;

Has your household at any time during the last 12 months run out of the money to payfor food?

4. Assessment of adequacy of the income of the household as a more subjective measurer

of relative deprivation, coded from 1 = very easily to 6 with difficulty.

A household may have different sources of income and more than one householdmember may contribute to it. Thinking of your household’s total monthly income: is yourhousehold able to make ends meet—?

For social cohesion we used:

1. General trust;

Generally speaking would you say that most people can be trusted or that you can’t betoo careful in dealing with people? Please tell me on a scale of 1–10, where 1 means thatyou can’t be too careful and 10 means that most people can be trusted.

2. Trust in government

2003 A scale computed from trust in the state pension and social security systems with

1 = a great deal of trust and 4 no trust at all. The coding was reversed to make it

correspond with 2007.

How much trust do you have in the ability of the following two systems to deliver whenyou need it? State pension system, Social benefit system

Chronbach’s Alpha 0.78

2007 Measured on a 10 point scale where 1 = do not trust at all and 10 = trust

completely;

Please tell me how much you personally trust the government?

3. Perception of social conflict—a scale computed from the responses to a series of

questions on the extent of tension between different social groups

In all countries there sometimes exists tension between social groups. In your opinionhow much tension is there between each of the following groups in this country? Poor andrich people Management and workers Men and women Old people and young peopleDifferent racial groups and ethnic groups Different religious groups

Cronbach’s Alpha: 2003 0.7; 2007 0.76

For social integration we used

1. The answers to a series of questions on social support recoded to would not get support

and would get support and entered as dummies—0 = no support, 1 = support;

From whom would you get support in each of the following situations?If you needed help around the house when ill If you needed advice about a serious

personal or family matter If you were feeling bit depressed and wanting to talk tosomeone If you urgently needed to raise a 1,000 Euros to face an emergency(NMS = 500 Euros)

2. The answers to a series of questions on frequency of contact with friends and relatives

dichotomised to frequent contact (once a week or more) other. As we were interested

in social integration we coded those without relatives as other;


123

On average, thinking of the people living outside your household how often do you havedirect (face-to-face contact with any of your children, your mother or father, any of yourfriends and neighbours?

1. Married—coded 0 = not married/living with a partner, 1 = married/living with a

partner;

2. Vote in elections as an indicator of identification with the society, coded 1 Yes, 2 No;

Some people don’t vote nowadays for one reason or another. Did you vote in the last(country) national election?

5. Active in a political party/trade union as the only measure in the data set for formal

social capital available in both years, coded 1 = yes, 2 = no

2003 Over the past year, have you attended a meeting of a trade union, or a politicalparty, a political action group, attended a protest or demonstrated or signed a petition?

2007 Over the past year, have you attended a meeting of a trade union, or a politicalparty or a political action group?

6. The extent to which the respondent felt left out of society measured on a scale from

1 = strongly agree to 5 = strongly disagree as a subjective indicator of social integration.

I feel left out of societyFor social empowerment we used;

1. Education coded from 1 = none to 7 = tertiary education (ISCED)

What is the highest level of education that you completed?

2. Self evaluation of health from 1 very good to 5 very bad;

In general, would you say your health is —

3. The extent to which respondents felt in control of their lives.

Life has become so complicated today that I almost can’t find my wayCoded from 1 strongly agree to 5 strongly disagree

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Rising Economic Prosperity and Social Quality the Case of New Member States of the European Union