Good Job, Good Life? Working Conditions and Quality of Life in Europe

Abstract

Cross-national comparisons generally show large differences in life satisfaction of individuals within and between European
countries. This paper addresses the question of whether and how job quality and working conditions contribute to the quality
of life of employed populations in nine strategically selected EU countries: Finland, Sweden, the UK, the Netherlands, Germany,
Portugal, Spain, Hungary, and Bulgaria. Using data from the European Quality of Life Survey 2003, we examine relationships
between working conditions and satisfaction with life, as well as whether spillover or segmentation mechanisms better explain
the link between work domain and overall life satisfaction. Results show that the level of life satisfaction varies significantly
across countries, with higher quality of life in more affluent societies. However, the impact of working conditions on life
satisfaction is stronger in Southern and Eastern European countries. Our study suggests that the issue of security, such as
security of employment and pay which provides economic security, is the key element that in a straightforward manner affects
people’s quality of life. Other working conditions, such as autonomy at work, good career prospects and an interesting job
seem to translate into high job satisfaction, which in turn increases life satisfaction indirectly. In general, bad-quality
jobs tend to be more ‘effective’ in worsening workers’ perception of their life conditions than good jobs are in improving
their quality of life. We discuss the differences in job-related determinants of life satisfaction between the countries and
consider theoretical and practical implications of these findings.

KeywordsJob quality-Life satisfaction-Quality of life-Europe-Cross-national comparison

Full text

Good Job, Good Life? Working Conditions and Quality
of Life in Europe
Sonja Drobnic
ˇ•Barbara Beham •Patrick Pra
¨g
Accepted: 8 February 2010 / Published online: 4 March 2010
ÓSpringer Science+Business Media B.V. 2010
Abstract Cross-national comparisons generally show large differences in life satisfaction
of individuals within and between European countries. This paper addresses the question of
whether and how job quality and working conditions contribute to the quality of life of
employed populations in nine strategically selected EU countries: Finland, Sweden, the
UK, the Netherlands, Germany, Portugal, Spain, Hungary, and Bulgaria. Using data from
the European Quality of Life Survey 2003, we examine relationships between working
conditions and satisfaction with life, as well as whether spillover or segmentation mech-
anisms better explain the link between work domain and overall life satisfaction. Results
show that the level of life satisfaction varies significantly across countries, with higher
quality of life in more affluent societies. However, the impact of working conditions on life
satisfaction is stronger in Southern and Eastern European countries. Our study suggests
that the issue of security, such as security of employment and pay which provides eco-
nomic security, is the key element that in a straightforward manner affects people’s quality
of life. Other working conditions, such as autonomy at work, good career prospects and an
interesting job seem to translate into high job satisfaction, which in turn increases life
satisfaction indirectly. In general, bad-quality jobs tend to be more ‘effective’ in worsening
workers’ perception of their life conditions than good jobs are in improving their quality of
life. We discuss the differences in job-related determinants of life satisfaction between the
countries and consider theoretical and practical implications of these findings.
Keywords Job quality Life satisfaction Quality of life Europe 
Cross-national comparison
S. Drobnic
ˇ(&)
University of Hamburg, Allende-Platz 1, Hamburg 20146, Germany
e-mail: sonja.drobnic@uni-hamburg.de
B. Beham
Humboldt-Universita
¨t zu Berlin, Spandauer Str. 1, Berlin 10178, Germany
e-mail: barbara.beham@wiwi.hu-berlin.de
P. Pra
¨g
University of Groningen, Grote Rozenstraat 31, Groningen 9712 TG, The Netherlands
e-mail: p.praeg@rug.nl
123
Soc Indic Res (2010) 99:205–225
DOI 10.1007/s11205-010-9586-7

1 Introduction
Being in paid employment is consistently ranked as one of the most important determinants
of a high quality of life in Europe (Clark 2001,2005; Haller and Hadler 2006). Work not
only provides people with an adequate amount of money to make ends meet, it also
provides individuals with a clear time structure, a sense of identity, social status and
integration, and opportunities for personal development (Gallie 2002). However, although
we know that having a job is important for quality of life of individuals, we still know very
little empirically about how employment characteristics and key aspects of the quality of
work affect quality of life and general life satisfaction in particular. This limited knowl-
edge is rather surprising given the widely spread awareness that work is such a core
activity in society and ‘‘perhaps only kin relationships are as influential in people’s
everyday lives’’ as work (Kalleberg 2009). The objective of this paper is to investigate how
work characteristics, such as working hours, job insecurity, or physical and psychological
work demands, influence the quality of life of European citizens, and which aspects of
work are particularly important for individual well-being.
How to conceptualize and measure ‘‘quality of life’’ has long been debated in social
sciences. Historically, quality of life research stems from two rather opposing approaches
(Noll 2004): the Scandinavian ‘level of living’ approach (Erikson 1974,1993) and the
American ‘quality of life’ approach (Campbell et al. 1976). The ‘level of living’ approach
drew on the tradition of Swedish welfare research and thus had a strong focus on objective
living conditions. According to this approach, quality of life depends crucially on ‘‘the
individual’s command over—under given determinants—mobilizable resources, with
whose help he/she can control and consciously direct his/her living conditions’’ (Erikson
1974: 275). Resources can be both economic (such as income or wealth) and non-economic
(such as education or social relations). For research in the ‘level of living’ tradition, the
subjective evaluation of living conditions was not of interest and was even suspected to be
biased: For instance, individuals who have experienced downward social mobility may
express a substantially decreased satisfaction with their only slightly worsened living
conditions, whereas individuals who spent years living under menial conditions might have
adapted to these and express contentment with their situation (Erikson 1993).
Contrary to the ‘level of living’ approach, the American ‘quality of life’ approach drew
on individuals’ subjective evaluations to assess quality of life (Campbell et al. 1976;
Diener et al. 1999). Individual resources were not considered to be relevant for individual
welfare; instead, the focus of this approach was on individuals’ needs. Living conditions as
perceived by individuals and their subjective positive evaluations make up the core of
quality of life, regardless of how others would evaluate the individual’s living conditions.
Scales drawing on subjective well-being, positive affect, or satisfaction with important life
domains (such as work, family, and health), have been used by the proponents of the
subjective approach (Veenhoven 1996).
Between these two extreme positions, attempts to integrate both subjective and
objective indicators have emerged (e.g. Allardt 1976; Zapf 1984), as none of the two
informational sources can be dismissed easily. Most influential contemporary approaches
acknowledge the existence of a subjective–objective duality in quality of life research,
and the consensus that both objective and subjective indicators complement each other
and should be used jointly has become widely accepted. In recent years, even the
distinction between subjective and objective measures of quality of life has come under
scrutiny (Oswald and Wu 2010; Pra
¨g et al. 2010b; Veenhoven 2000). Both types of
measurement aim at the same qualities, and the terminology may be misleading. Neither
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are ‘objective’ measures undisputable, nor can ‘subjective’ measures be taken as mere
matters of taste.
Also, there has been much discussion on which dimensions comprise the life component
of quality of life. Most scholars regard quality of life as a construct of discrete life domains
(Cummins 1996; Lance et al. 1995; van Praag et al. 2003). Cummins (1996) gathered no
less than 173 terms that had been used to describe domains of life satisfaction. His analysis
revealed that 83% of life facets used in the literature could be classified within his proposed
scheme of seven life domains comprising material well-being, health, productivity, inti-
macy, safety, community, and emotional well-being. Allardt (1993) even suggested that all
relevant life domains could be summarized with the triad ‘having, loving, being’.
As with ‘‘quality of life’’, there have been diverse attempts to determine what consti-
tutes a ‘‘good’’ job. Whereas labour economists define the quality of work mainly in terms
of wages and hours of work, sociologists and organizational psychologists perceive work
through a broader lens including employee’s well-being, satisfaction, work-life balance,
job autonomy and personal development. Gallie (2007), for instance, discusses five dif-
ferent dimensions of quality of work: skills, training, task discretion, work-life balance,
and job insecurity. The issue of job quality and quality of working life has become an
important policy issue at the European level through the inclusion of ‘‘quality of work’’
indicators in the European Employment Strategy in 2001 (European Commission 2001).
The EU definition of job quality relies on a multi-dimensional approach, including
objective characteristics of the job, subjective evaluation of workers, worker characteris-
tics, and the match between the worker and the job. Within the framework of the European
Employment Strategy, ten groups of indicators have been defined to monitor employment
quality: intrinsic job quality; skills, life-long learning and career development; gender
equality; health and safety at work; flexibility and security; inclusion and access to the
labour market; work organization and work-life balance; social dialogue and worker
involvement; diversity and non-discrimination; overall economic performance and pro-
ductivity (Davoine et al. 2008; Royuela et al. 2008: 404).
1
While some approaches to quality of work, such as the European indicators, focus
mainly on objective macro indicators, sociological and psychological approaches stipulate
that people themselves can evaluate different aspects of their work situation and can judge
for themselves what is important about their work. This ‘‘subjective’’ approach has focused
on factors that affect the degree of satisfaction or dissatisfaction that people feel in their
job, such as satisfaction with various working conditions, competence development, and
the possibility of reconciling work and non-work life. Sirgy et al. (2001) contend that the
focus of quality of working life is beyond the concept of work satisfaction and that job
satisfaction is more of a possible outcome of the quality of work rather than one of its
dimensions. The relationship between objective and subjective indicators is not a simple
issue. For example, a demanding job offering high autonomy and good career prospects but
requiring long working hours can be evaluated very differently by a young professional
with career aspirations and no family obligations than by an employee with family
responsibilities. Pichler and Wallace (2009) examined job satisfaction across Europe and
identified several determinants of job satisfaction. After controlling for institutional factors
and country-level compositional effects, they found significant association in the expected
direction between overall job satisfaction and objective indicators of working conditions of
1
Davoine et al.(2008), however, contend that because of lack of political consensus the indicators exclude
some fundamental dimensions of employment quality, such as wages. Also, Green (2006) points at defi-
ciencies in the European definition in neglecting dimensions such as wages and work intensity.
Good Job, Good Life? 207
123

individuals, such as occupational class, type of contract, or supervision responsibilities, as
well as between job satisfaction and subjective evaluations, such as job demands, auton-
omy, career prospects, or job security.
In this paper, we follow this recent approach and incorporate both objective indicators and
subjective evaluations of job characteristics and working conditions in our study to better
understand life satisfaction in European societies. We take subjective overall life satisfaction
as an indicator of people’s quality of life. Life satisfaction is an overall cognitive assessment
of feelings and attitudes about one’s life at a particular point in time and is considered a
desirable goal in and of itself. Life satisfaction differs a great deal among individuals and
between European countries (Fahey and Smyth 2004; Pra
¨g et al. 2010a; Szu
¨cs et al. 2010)
and is to a large extent affected by societal contexts in which individuals live (Bo
¨hnke 2008).
Due to different levels of economic development, differences in sectoral composition, and
the extent of public policies, working conditions vary significantly across countries and can
be expected to influence life satisfaction in a variety of ways. To capture the variability in
country contexts but nevertheless understand the underlying patterns of relationships
between working conditions and life satisfaction, we will focus on nine strategically selected
EU countries from Northern, Western, Southern and Eastern Europe, which can also be
considered representatives of different welfare and employment regimes: Finland, Sweden,
the UK, the Netherlands, Germany, Portugal, Spain, Hungary, and Bulgaria. Through
identifying the work-related factors that contribute to individuals’ quality of life, we perceive
our analysis as a contribution to the identification and development of indicators for mea-
suring quality of employment and quality of jobs in Europe.
2 Working Conditions and Life Satisfaction
How important is having a good job for overall life satisfaction? In the literature, this
question has been addressed using the concepts of domain hierarchy and domain salience
(Sirgy 2002). Domain hierarchy refers to the idea that life domains are cognitively structured
in a hierarchical pyramid: feelings about life overall are located at the top of this pyramid, the
level below is reserved for satisfaction with the different life domains, and the bottom level
pertains to life events within different life domains. Domain salience is the assumption that
different life domains, such as work, family, health, or leisure vary in salience, i.e. some
domains can be more important than others (Sirgy 2002). Theory distinguishes three dif-
ferent types of mechanisms across a variety of life domains: spillover, segmentation, and
compensation (Wilensky 1960; Staines 1980). Spillover refers to both the process and the
outcome by which affective experiences in one life domain (e.g. work) influence experiences
in another domain (e.g. family) and overall life. Compensation describes a mechanism by
which individuals try to balance their affect across domains. For example, an individual may
seek to compensate for a lack of satisfaction in one domain by trying to find more satisfaction
in another one (e.g. employees become more involved in their work when experiencing
family problems at home) (Lambert 1990). Segmentation refers to a mechanism by which
individuals strictly separate life domains in order to prevent experiences being transferred
between life domains and overall life attitudes (e.g. trying to leave work-related troubles in
the office and not bring those home) (Sirgy 2002). In our study, we address two mechanisms:
spillover and segmentation. Since we are not examining the relationships between same-
level domains, we cannot address the compensation mechanisms.
The relationship between the work domain and general life satisfaction from a spillover
perspective has been examined in a number of studies which have focused on the
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relationship between job satisfaction and life satisfaction (cf. Delhey 2004). However, the
focus in this paper is not on the relationship between work domain satisfaction and overall
life satisfaction but on the link between job characteristics/working conditions and overall
level of life satisfaction. A similar approach has been taken by Wallace et al. (2007) who
examined this relationship but concluded that it is mediated by job satisfaction. A con-
ceptual model that emerged from their study is one in which working conditions on the one
hand and work-life balance indicators on the other contribute to satisfaction with one’s job,
and job satisfaction affects overall subjective life satisfaction. Job satisfaction is thus an
intervening variable or missing link between working conditions and life satisfaction. In
this way, Wallace et al. (2007) corroborate spillover theories, according to which satis-
faction with a lower domain (work) influences or spills over into overall life satisfaction.
Some scholars challenge the spillover approach and conventional wisdom that attitudes
towards work influence overall life satisfaction. For example, Rode and Near (2005)
contend that it is not job satisfaction that impacts on overall life satisfaction; rather, the
relationship will appear when constraints, opportunities and activities associated with the
work domain influence the constraints, opportunities and activities experienced in other life
domains. One such crucial linkage between the domains is that between the work and the
family/home, which has been amply demonstrated in the literature on work-life balance.
Work-family balance is a term frequently used in popular as well as academic writings,
although explicit definitions of the construct can hardly be found in the scholarly discourse
(Frone 2003). According to the scarcity argument in role theory (Goode 1960), a person
has a limited amount of resources and energy to spend. Multiple life roles (e.g., work,
family) compete for those scarce resources which may lead to the experience of role stress
and conflict. Negative work-to-home interference or work-family conflict is defined as ‘‘a
type of inter-role conflict that occurs when the role demands stemming from one domain
(work or family) interfere or are incompatible with role demands stemming from the other
domain (family or work)’’ (Greenhaus and Beutell 1985: 77). While early studies con-
ceptualized conflict between work and family/home as a uni-dimensional construct
(Bedeian et al. 1988), later research distinguished two directions of interference: work
interfering with family/home and family/home interfering with work (Carlson et al. 2000;
Frone et al. 1997). The work-family/home interface was found to be asymmetric permeable
(Pleck 1977). Work as the stronger system interferes more often with home life than vice
versa for both men and women (Aycan and Eskin, 2005; Frone et al. 1992). In line with
these findings, we include an indicator of interference between work and home or work-
home conflict in our analysis to examine whether a successful management of the interface
between these domains contributes to the overall life satisfaction.
2.1 Analytic Strategy and Hypotheses
As outlined above, previous research on the relationship between work characteristics,
working conditions and life satisfaction is inconclusive (cf. Diener et al. 1999; Rode and
Near 2005; Wallace et al. 2007), as are the explanations of the mechanisms that generate the
link between working conditions and life satisfaction. We therefore take a stepwise approach
to the question. After presenting the descriptive statistics and testing for the differences
between the countries, we pool the data for the nine countries and regress life satisfaction on a
series of measures: individuals’ job characteristics, GDP per capita, country dummies, job
satisfaction, and work-home interference. In the next step, we estimate the effects of working
conditions on life satisfaction in each country separately in order to examine whether the
relationships differ among the countries. We know that the levels of life satisfaction differ
Good Job, Good Life? 209
123

greatly among European countries but it is not clear whether the determinants of life satis-
faction themselves also differ among the countries. Wallace et al. (2007), who performed a
similar analysis, analyzed regional sub-clusters and performed multilevel modelling to
distinguish variations in life satisfaction due to individual characteristics and due to country-
level factors. However, with this type of modelling it is not possible to draw conclusions on
specific differences between the countries or to determine whether the individual-level
factors in specific countries differ in their effects on life satisfaction.
We first test the hypotheses that there is a direct link between working conditions and
overall life satisfaction. We expect that positive evaluations of working conditions (work
not too demanding and stressful, not dangerous or unhealthy, no time pressure, interesting
job, good pay and good career prospects, job autonomy, job security) increase overall life
satisfaction. In line with the importance of employment for high quality of life, we
hypothesize that life satisfaction increases with working hours. However, it has also been
shown that there are gains in quality of life from reducing working hours (Verbakel and
DiPrete 2008), leading to the hypothesis that there is a non-linear relationship between
working hours and life satisfaction. Life satisfaction first increases with working hours but
decreases again with very long hours. This non-linear effect will be tested by including a
linear and a quadratic term for working hours in the analysis. Commuting time is as a rule
time without direct income compensation and without benefits of leisure time; the effect on
life satisfaction is expected to be negative. In addition to subjectively evaluated working
conditions, we include two objective job characteristics: supervision responsibility and
contract type. Supervision is an indication of a higher occupational class and is assumed to
increase life satisfaction. A permanent contract is assumed to be preferred over a tem-
porary job contract and to contribute to quality of life.
In our analytic strategy, we will examine predictions derived from the spillover and the
segmentation theories. Thus, we next include job satisfaction in the analysis. In accordance
with the spillover thesis, we hypothesize that job satisfaction has a positive effect on overall
life satisfaction and that the direct effects of working conditions will disappear (diminish)
when job satisfaction is included in the analysis. Alternatively, if segmentation rather than
spillover is the prevailing mechanism, job satisfaction will not translate into general life
satisfaction because attitudes towards work are those that people can compartmentalize.
Rather, a successful managing of the work-home interface will be an important aspect of life
quality. We include an indicator of work-home interference and hypothesize that high work-
home interference will be negatively associated with high life satisfaction.
There are a growing number of studies that show how important the societal context and
country-level variables are in understanding the differences in quality of life. Fahey and
Smyth (2004) attribute the wide differences in the mean level of life satisfaction and
striking regularities in variability across European countries to their level of economic
development as measured by GDP per capita. We will include GDP per capita to test the
hypothesis about the positive effect of economic development on life satisfaction. Country
dummies will be included next to capture other possible idiosyncrasies between countries.
3 Data and Variables
Data for this analysis come from the European Quality of Life Survey (EQLS 2003),
conducted on behalf of the European Foundation for the Improvement of Living and
Working Conditions. The survey covers the EU-15 states, the new Member Countries that
joined the European Union in 2004 and 2007, and Turkey. This study focuses on the
210 S. Drobnic
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following countries: Bulgaria (BG), Hungary (HU), Portugal (PT), Spain (E), Germany
(DE), the Netherlands (NL), Finland (FI), Sweden (SE) and the UK. Since we are inter-
ested in the impact of work on the quality of life, the analyses draw on a sub-sample of
working respondents in each country, ranging from 255 in Bulgaria to 489 in Sweden.
To asses the overall life satisfaction, which is the dependent variable in this analysis,
respondents were asked ‘‘All things considered, how satisfied would you say you are with
your life these days?’’ Responses were given on a ten-point scale, with 1 indicating very
dissatisfied and 10 very satisfied.
2
Independent variables are weekly hours normally worked
in the main job, including any paid or unpaid overtime. This variable is included in the
analysis in a linear and quadratic form. Respondents were asked about their commuting
time using their usual mode of transport, whether they have any responsibility for super-
vising the work of other employees, and about the type of contract they held. We
dichotomized the responses on the type of contract to distinguish between the indefinite
permanent contract and all other types of contract or no contract (see also Gash et al.
2007).
Further, the respondents were asked using a five-point scale (strongly agree, agree,
neither agree/nor disagree, disagree or strongly disagree) whether their work is too
demanding and stressful; whether they are well-paid; whether they have a great deal of
influence in deciding how to do their work (job autonomy); whether their work is dull and
boring; whether their job offers good prospects for career advancement; whether they
constantly work to tight deadlines (time pressure); and whether they work in dangerous or
unhealthy conditions.
3
For the regression analyses, these subjective evaluations of job
characteristics have been dichotomized in such a way that the responses ‘‘agree’’ and
‘‘strongly agree’’ are assigned the value one and all other responses the value zero. Fur-
thermore, respondents were asked to assess their job security: ‘‘How likely do you think it
is that you might lose your job in the next 6 months?’’ Possible answers were ‘very likely,
quite likely, neither likely/nor unlikely, quite unlikely or very unlikely’. A dummy variable
job insecurity indicates that a person estimates that it is very or quite likely to lose his/her
job in the following 6 months.
Two variables were included in the analysis to verify the spillover and the compart-
mentalization theses. Respondents rated their job satisfaction on a scale of 1–10 where 1
meant ‘very dissatisfied’ and 10 ‘very satisfied’. Work-home interference is an index
composed of the following three items: ‘‘I have come home from work too tired to do some
of the household jobs which need to be done’’; ‘‘It has been difficult for me to fulfil my
family responsibilities because of the amount of time I spend on the job’’; ‘‘I have found it
difficult to concentrate at work because of my family responsibilities’’. Although the
interference between work and home can be thought of as having two separate directions
(from work to home and vice versa), exploratory factor analysis reveals that the three items
load on a single factor. Cronbach’s alpha for the index is .72, thus indicating that the three
2
The methodological question of whether such a ten-point scale can be used as a cardinal variable in an
OLS regression has been addressed by Ferrer-i-Carbonell and Frijters (2004) in a study on happiness scores.
They assert that assuming ordinality (as usually done by economists) or cardinality of happiness scores
makes little difference for the results.
3
A potential problem with measuring working conditions is the reliance on self-reported attitudinal data
that may have several biases. One such bias is habituation, where respondents get used to bad jobs, for
example, and stop reporting their working conditions as poor. However, there are no other standardized
methods of assessing job quality other than using surveys to ask workers about their jobs. With such caveats
in mind, we nevertheless adhere to the view that subjective reports are valid and reasonably credible (see
also Fahey and Smyth 2004).
Good Job, Good Life? 211
123

items exhibit sufficient internal consistency. Higher scores on the 5-point scale indicate
higher interference between work and home.
The effects of GDP per capita, which is an aggregate-level variable, and country
dummies are estimated in the models for pooled data. Finally, we include the following
socio-demographic variables as controls in our statistical models: age in linear and qua-
dratic form to capture the non-linear U-shaped effect found in studies on life satisfaction
(Blanchflower and Oswald 2008; see also Anxo and Boulin 2006); marital status, distin-
guishing respondents with (married or cohabiting) partners and respondents without
partners; number of children; and educational level. Due to measurement problems in some
countries, the variable on education is dichotomized and only distinguishes between
respondents with and without college degree.
4 Results
4.1 Cross-Country Differences in Working Conditions
The total size of the sample of the working population with valid data in the nine countries
of interest is 3,354; 47% men and 53% women. The average age is 41 years, ranging from
38 years in Spain to 44 years in Finland. Two-thirds of the participants were married or
living with a partner and 32% indicated that they had no partner. On average, participants
had 1.3 children. 35% of all respondents (41% of men and 29% of women) indicated that
they had a supervisory position in their workplace. Hungary and Bulgaria stand out as
countries with a particularly long working week. With an average of 43 h, the employees
work almost 10 h longer than those in the Netherlands with the shortest average working
time (results not shown, available upon request).
In order to assess the mean values of the variables and test for differences between the
countries, we conducted a series of one-way analysis of variance tests (ANOVA) on the
variables required for the multivariate analysis (Table 1). Differences in physical working
conditions are rather small. East European respondents report the most dangerous and
unhealthy working conditions. In terms of psychological job demands and stress, Bul-
garians report the highest pressure, but time pressure (working under tight deadlines) is
highest for British and German respondents. Perceived job insecurity differs significantly
across countries, with Bulgarians reporting by far the highest level of insecurity among all
respondents. German and Dutch respondents are those most satisfied with their earnings,
while respondents from the post-socialist countries, Portugal, and Finland are significantly
less satisfied with the wages they receive. In terms of job autonomy, respondents from
Nordic countries and the Netherlands report the largest degree of job autonomy. The best
prospects for career advancement are perceived by the British and Spanish, followed by
Dutch and Portuguese respondents, whereas those from the post-socialist countries report
the least opportunities for career advancement. In Portugal and the UK, respondents are
most likely to describe their job as dull and boring, with Sweden, Germany and the
Netherlands being at the lowest end of the scale.
Cross-country differences in work-home interference are relatively small. Perceived
work-life interference is highest in the post-socialist countries, Portugal, the UK and Spain,
and lowest in the Netherlands, Finland and Germany. In contrast to work-life balance,
differences in life satisfaction vary greatly across countries. Life satisfaction is highest in
Finland and Sweden, followed by the Netherlands, Spain, the UK and Germany. These
countries display a very high average level of life satisfaction. The Portuguese and
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Table 1 Comparison of variable means by Country
SE FI NL DE UK PT E HU BG Range F(df)R
2
Life satisfaction 7.90
de
8.23
e
7.64
cd
7.47
c
7.50
c
6.30
b
7.57
cd
6.10
b
4.69
a
1–10 151.89 (8, 3345) .266
Working hours 39.46
cd
38.36
bc
33.36
a
38.11
bc
35.98
b
41.59
de
39.91
cd
43.14
e
42.93
e
2–110 30.46 (8, 3345) .068
Commuting time .57
a
.62
ab
.73
b
.61
ab
.62
ab
.59
a
.61
ab
.67
ab
.57
a
0–6 3.36 (8, 3345) .008
Job demanding/stressful 3.01
bc
2.45
a
2.49
a
3.27
cd
2.94
b
3.44
d
2.97
b
3.14
bc
3.75
e
1–5 43.89 (8, 3345) .095
Time pressure 3.08
c
3.10
c
2.94
bc
3.15
cd
3.43
d
2.75
ab
2.95
bc
2.99
bc
2.54
a
1–5 12.51 (8, 3345) .029
Job dangerous/unhealthy 2.09
bc
2.11
bc
1.88
ab
1.81
a
1.92
ab
2.13
bc
1.97
ab
2.35
cd
2.47
d
1–5 11.11 (8, 3345) .026
Job insecurity 1.53
ab
1.60
ab
1.48
a
1.72
bc
1.60
ab
1.88
c
1.85
c
1.93
c
3.21
d
1–5 69.51 (8, 3345) .143
Well-paid 2.89
b
2.47
a
3.38
c
3.46
c
3.05
b
2.62
a
2.98
b
2.36
a
2.41
a
1–5 48.65 (8, 3345) .104
Job autonomy 3.94
f
3.92
ef
3.81
def
3.66
cde
3.45
bc
3.27
ab
3.63
cd
3.02
a
3.27
ab
1–5 29.62 (8, 3345) .066
Career prospects 2.49
ab
2.64
bc
2.96
de
2.78
cd
3.14
e
2.83
cd
3.14
e
2.29
a
2.40
ab
1–5 23.64 (8, 3345) .054
Job dull/boring 1.60
a
1.90
b
1.66
a
1.63
a
2.22
cd
2.40
d
2.09
bc
2.17
c
2.13
c
1–5 36.93 (8, 3345) .081
Work-home interference 2.53
bc
2.40
ab
2.30
a
2.43
ab
2.73
cd
2.88
d
2.71
cd
2.84
d
2.88
d
1–5 20.05 (8, 3345) .046
Job satisfaction 7.59
ab
7.95
a
7.44
bc
7.92
a
7.31
bc
6.82
de
7.14
cd
7.11
cd
6.42
e
1–10 23.28 (8, 3345) .053
Note: All F-tests are statistically significant at p\.001 Means with different superscripts are significantly different from one another using Tukey HSD test
Superscripts indicate whether the differences between the countries are statistically significant. For example, Bulgaria has an extremely high score for job insecurity which
differs significantly from all other countries (denoted by
d
). Hungary, Portugal, Spain and Germany belong to the next group of countries (denoted by
c
) with relatively high job
insecurity. Lower job insecurity can be found in Sweden, Finland, UK and Germany. Job insecurity is the lowest in the Netherlands. In this example, Germany ‘‘belongs’’ to
two different groups of countries. This simply means that the confidence intervals around the population mean scores overlap. Thus, in terms of job security, Germany differs
significantly only from the Netherlands in one direction and Bulgaria in the other
Good Job, Good Life? 213
123

Hungarians report rather low levels of life satisfaction, but these are still significantly
higher than the level of life satisfaction experienced by Bulgarians.
Overall, there seems to be a distinctive and systematic pattern in working conditions and
life satisfaction levels across countries. Bulgaria, Hungary and Portugal have in many
respects adverse conditions at work, with Bulgaria being particularly affected by high job
insecurity as well as demanding and stressful jobs. Only when it comes to time pressure
and job intensification (‘‘I constantly work to tight deadlines’’) do respondents from
countries such as the UK and Germany report having difficult working conditions. And
Finnish respondents, who generally share comparably good working conditions with other
Nordic countries, disagree that they are well-paid and in this respect can be grouped with
former socialist countries and Portugal.
4.2 Determinants of Life Satisfaction in the Pooled Data
To examine whether and how working conditions contribute to the level of overall life
satisfaction, we first regress life satisfaction on working conditions for the pooled data for
all countries under study. Coefficients for gender, age in linear and in quadratic form,
marital status, presence of children, and educational attainment are not displayed in the
tables, but are included as control variables in all model equations.
The first model in Table 2examines the effects of both objective working conditions
and subjective evaluations of work on overall life satisfaction. For working hours, the
expected curvilinear effect is not observed but commuting time does have a significant
negative effect on well-being: each daily hour of commuting decreases life satisfaction
measured on a ten-point scale by an average of .13 points. Holding a supervisory position
has a significant positive impact on life satisfaction. Supervisors score on average .26
points higher than non-supervisors. Contrary to frequently discussed issues in research on
the flexibilization of labour markets, no effect of the contract type can be found: holders of
permanent contracts are on average no more satisfied with their lives than employees
holding other types of employment contracts. However, it has to be noted that respondents
who expect to lose their jobs within the next 6 months report on average a 1.22 point lower
score on the 10-point life satisfaction measure than their counterparts who do not perceive
their jobs as insecure.
Turning to the effects of other subjective evaluation measures, effects are mostly as
expected: employees with psychologically demanding and stressful jobs are less satisfied
than workers who perceive their jobs to be less stressful. Likewise, employees who
experience their work as dangerous and unhealthy are on average less satisfied. Being
content with one’s pay and having autonomy over how one’s work is done in turn increases
life satisfaction. As expected, perceiving work as dull and boring decreases life satisfac-
tion. Time pressure and good career prospects appear not to have any significant effect on
overall life satisfaction.
In the second model in Table 2, GDP per capita as a measure of general economic
prosperity is added to the model.
4
Explained variance increases remarkably from 18 to
30%. After adding this variable, working hours exhibit the expected inverted U-shape.
Further analysis reveals that the point of inflection is in fact around 41 h per week: for
employees working less than roughly 41 h per week, the model predicts a positive effect of
4
The highest GDP per capita can be found in The Netherlands (€26,020), followed by Finland (€24,280),
Germany (€24,140), the United Kingdom (€23,160), Sweden (€23,130), Spain (€19,100), Portugal
(€16,920), Hungary (€12,300), and Bulgaria (€5,700).
214 S. Drobnic
ˇet al.
123

Table 2 Life satisfaction regressed on working conditions for pooled data (OLS, standard errors in
parentheses)
(1) (2) (3) (4) (5) (6)
Working hours -0.001 0.022** 0.015* 0.020** 0.019** 0.023***
(0.008) (0.007) (0.007) (0.007) (0.007) (0.007)
Working hours
2
(coeff. 91,000)
-0.181* -0.271** -0.213* -0.277*** -0.229** -0.286***
(0.009) (0.008) (0.008) (0.008) (0.008) (0.008)
Commuting time -0.131** -0.154*** -0.130** -0.113** -0.107* -0.097*
(0.05) (0.047) (0.046) (0.044) (0.046) (0.0437)
Supervisor 0.255*** 0.129* 0.130* 0.0923 0.156* 0.114
(0.066) (0.061) (0.061) (0.059) (0.061) (0.058)
Permanent contract 0.128 0.051 0.064 0.034 0.075 0.044
(0.070) (0.064) (0.063) (0.061) (0.063) (0.060)
Job demanding/stressful -0.346*** -0.146* -0.068 -0.019 0.052 0.070
(0.061) (0.059) (0.059) (0.056) (0.060) (0.058)
Time pressure 0.103 -0.124* -0.157** -0.118* -0.091 -0.070
(0.063) (0.059) (0.058) (0.056) (0.058) (0.056)
Job dangerous/unhealthy -0.201* -0.138 -0.201** -0.145* -0.161* -0.118
(0.083) (0.077) (0.075) (0.072) (0.075) (0.072)
Job insecurity -1.222*** -0.661*** -0.610*** -0.435*** -0.586*** -0.425***
(0.099) (0.094) (0.095) (0.092) (0.094) (0.091)
Well-paid 0.489*** 0.276*** 0.369*** 0.230*** 0.344*** 0.218***
(0.065) (0.061) (0.061) (0.059) (0.060) (0.059)
Job autonomy 0.546*** 0.308*** 0.263*** 0.111 0.247*** 0.106
(0.066) (0.062) (0.062) (0.060) (0.061) (0.059)
Career prospects 0.120 0.108 0.126* -0.056 0.104 -0.064
(0.069) (0.063) (0.063) (0.061) (0.062) (0.061)
Job dull/boring -0.507*** -0.483*** -0.467*** -0.104 -0.388*** -0.061
(0.104) (0.096) (0.095) (0.093) (0.094) (0.093)
Job satisfaction 0.264*** 0.251***
(0.015) (0.015)
Work-home interference -0.256*** -0.196***
(0.030) (0.029)
GDP per capita 0.132*** -0.096 -0.113 -0.109 -0.123
(0.005) (0.109) (0.105) (0.108) (0.104)
Finland 0.540** 0.465** 0.564*** 0.487**
(0.165) (0.158) (0.163) (0.157)
Netherlands -0.070 0.071 -0.015 0.106
(0.334) (0.320) (0.330) (0.318)
Germany -0.294 -0.357* -0.292 -0.353*
(0.156) (0.149) (0.154) (0.148)
United Kingdom -0.358** -0.303** -0.300** -0.261*
(0.113) (0.108) (0.112) (0.108)
Portugal -1.965** -2.009** -1.978** -2.017**
(0.690) (0.661) (0.682) (0.656)
Good Job, Good Life? 215
123

an additional hour of work on life satisfaction, but when exceeding 41 h, the effect changes
direction and life satisfaction decreases. Furthermore, the model shows that GDP partially
mediates most of the effects which were found in the first model. The coefficient for
supervisory status is cut by half, as is the effect of job insecurity which still remains
significant and substantially large at -.66 points. The negative effect of a demanding and
stressful job becomes weaker; however, time pressure starts having a significantly negative
effect on well-being. The effects of contentment with pay and job autonomy are also
substantially mediated. However, the negative impact of having a dull and boring job on
life satisfaction is largely independent from GDP.
In the third model, we add dummy variables for the countries in the equation. To be able
to simultaneously include both the dummy variables and GDP (which are perfectly cor-
related), the values for GDP for each country have been dispersed in the range plus minus
one percent around the actual value before being randomly assigned to the individuals in
that country.
5
Sweden serves as a reference category for all other countries. By including
country dummies, GDP per capita no longer plays a role in the level of life satisfaction.
However, in addition to economic prosperity which is now captured by country dummies,
there are obviously country differences in life satisfaction that go beyond economic
indicators and working conditions. Finnish employees on average report higher levels of
life satisfaction (.54 points) than Swedish employees when the country’s GDP, the indi-
viduals’ socio-demographic characteristics, and working conditions are controlled for. The
Dutch, Germans, and Spaniards do not differ from Swedish respondents; other countries
have lower life satisfaction. While British workers on average report a .36 lower score in
life satisfaction compared to Swedish workers, Portuguese employees score 1.96 points
lower, Hungarian 2.53 points, and Bulgarian workers 4.43 points—in spite of controlling
for working conditions and GDP.
Models 4 and 5 (Table 2) test the spillover and the segmentation thesis, respectively.
When job satisfaction is added to the equation it becomes obvious that—although a
Table 2 continued
(1) (2) (3) (4) (5) (6)
Spain -0.629 -0.608 -0.616 -0.600
(0.454) (0.434) (0.449) (0.432)
Hungary -2.527* -2.753* -2.609* -2.805*
(1.188) (1.138) (1.175) (1.130)
Bulgaria -4.430* -4.624* -4.624* -4.762**
(1.909) (1.829) (1.888) (1.816)
Intercept 8.551*** 5.450*** 11.05*** 9.568*** 11.63*** 10.08***
(0.398) (0.388) (2.544) (2.438) (2.517) (2.423)
N3354 3354 3354 3354 3354 3354
Adj. R
2
0.180 0.304 0.337 0.391 0.351 0.399
Notes: Gender, age in linear and quadratic form, marital status, number of children, and education are
controlled. Reference for country dummies is Sweden. Coefficients for working hours
2
are multiplied by
1,000
*pB.05, ** pB.01, *** pB.001
5
For example, Dutch respondents were randomly assigned GDP per capita values ranging between €25,760
(Dutch GDP -1%) and €26,280 (Dutch GDP ?1%).
216 S. Drobnic
ˇet al.
123

number of effects are mediated through this variable—having a supervisory position and
an interesting job that offers high autonomy and good career prospects translate into high
job satisfaction. Job satisfaction itself is positively related to the outcome, with each one-
point increase on the job satisfaction measure being accompanied by a .26 point increase in
overall life satisfaction. Nevertheless, a number of aspects of working conditions remain
statistically significant and continue to directly impact the overall life satisfaction. When
the composite index of work-home interference is included in Model 5, not much change in
terms of mediation can be observed, compared to Model 3. However, the negative effect of
time pressure and the positive effect of good career prospects both decrease in size and
become insignificant. In particular, having to work constantly under tight deadlines con-
tributes to the feeling of conflict between work and private life. Work-home interference
reduces life satisfaction as expected.
The sixth model includes both job satisfaction and work-home interference. Both
variables are statistically significant and substantively important. The full model explains
about 40% of variance in life satisfaction. With respect to working conditions, the length of
working and commuting time, job insecurity, and satisfaction with pay remain directly
linked to overall life satisfaction. Workers afraid of losing their job on average report .43
points lower life satisfaction and workers content with their wages on average report .22
points higher satisfaction with their lives. Again, country-level characteristics not
explained by working conditions, socio-demographic characteristics and GDP per capita
determine to a large extent differences in life satisfaction in European countries. Con-
trolling for these factors, Finland has the highest degree of life satisfaction, followed by
Sweden, the Netherlands, and Spain. Life satisfaction is significantly lower in the UK,
Germany, and particularly in Portugal, Hungary and Bulgaria.
4.3 Country Differences in Determinants of Life Satisfaction
In the next step, we analyze each country separately. This is necessary to ascertain whether
the determinants of life satisfaction are similar across countries—albeit at different lev-
els—or the patterns of determinants themselves differ between the countries. In inter-
preting the results, it should be noted that country samples are much smaller than the
pooled sample and statistical power is considerably weaker. Nonetheless, a number of
cross-national similarities and differences in terms of predictors of life satisfaction become
apparent (Table 3). Overall, the variables in the model explain between 16.3% of variance
in life satisfaction in Hungary and up to 23.2% in Portugal. The effects of subjective
evaluation of working conditions show some variation: job insecurity is a particularly
salient issue in the East European countries (Hungary and Bulgaria). Job autonomy is
particularly appreciated in Germany. Unhealthy and dangerous jobs are especially detri-
mental to quality of life in Bulgaria and Portugal, time pressure and its negative effects on
life satisfaction is an important issue in the UK, and satisfaction with pay increases life
satisfaction in Germany and Finland more systematically and to a larger extent than in
other countries. Also, there are some unexpected effects at the country level: both a
demanding and stressful job in Bulgaria and a boring job in Finland appear to increase life
satisfaction. Most likely, other attributes of such jobs generate country-specific constel-
lations. For example, having demanding and stressful work in Bulgaria might be associated
with higher status and other life circumstances that increase quality of life of individuals.
A positive, highly significant effect of job satisfaction on life satisfaction can be found
in all countries, in this way corroborating the spillover thesis. Work–home interference,
however, is not a salient factor for quality of life everywhere in Europe. Experiencing a
Good Job, Good Life? 217
123

Table 3 Life satisfaction regressed on working conditions for individual countries (OLS, standard errors in parentheses)
SE FI NL DE UK PT ES HU BG
Working hours -0.009 0.004 -0.000 0.036 0.030 0.017 0.057** 0.037 0.023
(0.030) (0.015) (0.016) (0.023) (0.020) (0.025) (0.020) (0.028) (0.048)
Working hours
2
(coeff. 91,000) 0.164 -0.023 -0.009 -0.539 -0.334 -0.146 -0.594** -0.637* -0.244
(0.003) (0.168) (0.234) (0.274) (0.236) (0.264) (0.220) (0.263) (0.500)
Commuting time -0.279* -0.010 0.072 0.061 -0.054 -0.295 0.057 -0.091 -0.139
(0.122) (0.106) (0.0710) (0.153) (0.133) (0.154) (0.140) (0.152) (0.264)
Supervisor 0.278 -0.005 0.163 0.0112 0.051 0.218 -0.095 0.448 0.039
(0.149) (0.109) (0.104) (0.197) (0.178) (0.210) (0.187) (0.273) (0.299)
Permanent contract 0.280 0.209 0.0314 -0.011 -0.204 -0.043 0.012 -0.110 0.058
(0.171) (0.138) (0.126) (0.190) (0.185) (0.196) (0.160) (0.253) (0.295)
Job demanding/stressful 0.107 -0.160 -0.050 -0.050 0.266 -0.182 0.085 0.181 0.593*
(0.140) (0.140) (0.126) (0.173) (0.180) (0.184) (0.175) (0.242) (0.292)
Time pressure -0.084 0.073 0.024 -0.052 -0.541** -0.132 0.050 -0.140 0.104
(0.143) (0.106) (0.104) (0.183) (0.189) (0.201) (0.162) (0.228) (0.330)
Job dangerous/unhealthy 0.180 0.137 -0.111 0.113 -0.276 -0.841*** -0.089 0.284 -0.787*
(0.160) (0.147) (0.169) (0.249) (0.252) (0.245) (0.228) (0.279) (0.325)
Job insecurity -0.109 -0.261 -0.542 -0.340 -0.408 -0.129 -0.193 -0.751* -0.652*
(0.248) (0.209) (0.295) (0.330) (0.328) (0.284) (0.285) (0.371) (0.269)
Well-paid 0.209 0.279* 0.056 0.490** 0.130 0.207 0.241 -0.191 0.554
(0.136) (0.131) (0.102) (0.181) (0.175) (0.225) (0.166) (0.319) (0.380)
Job autonomy 0.129 0.043 0.012 0.431* 0.140 0.059 0.096 -0.076 0.053
(0.168) (0.134) (0.116) (0.186) (0.189) (0.184) (0.173) (0.242) (0.274)
Career prospects -0.027 0.067 -0.060 0.059 0.012 0.161 -0.259 -0.0544 -0.716
(0.146) (0.125) (0.109) (0.199) (0.185) (0.210) (0.170) (0.320) (0.363)
218 S. Drobnic
ˇet al.
123

Table 3 continued
SE FI NL DE UK PT ES HU BG
Job dull/boring 0.238 0.636* 0.120 0.389 -0.424 0.022 -0.493 -0.095 -0.335
(0.278) (0.246) (0.262) (0.416) (0.248) (0.234) (0.260) (0.322) (0.445)
Job satisfaction 0.179*** 0.285*** 0.267*** 0.298*** 0.172*** 0.314*** 0.317*** 0.298*** 0.191***
(0.038) (0.042) (0.045) (0.048) (0.049) (0.048) (0.049) (0.051) (0.057)
Work-home interference -0.392*** -0.273*** -0.205*** -0.127 -0.309*** -0.125 -0.096 -0.116 -0.142
(0.079) (0.070) (0.056) (0.109) (0.091) (0.088) (0.084) (0.108) (0.139)
Intercept 9.344*** 6.446*** 6.596*** 5.701*** 8.130*** 6.154*** 4.594*** 4.775** 6.753**
(1.091) (0.792) (0.747) (1.200) (1.123) (1.090) (1.085) (1.626) (2.223)
N489 425 463 356 354 361 318 333 255
Adj. R
2
0.181 0.223 0.194 0.225 0.186 0.232 0.207 0.163 0.167
Note: Gender, age in linear and quadratic form, marital status, number of children, and education are controlled. Coefficients for working hours
2
are multiplied by 1,000
*pB.05; ** pB.01; *** pB.001
Good Job, Good Life? 219
123

conflict between work and private life significantly decreases life satisfaction in Sweden,
UK, Finland and the Netherlands. In Southern and Eastern European countries as well as in
Germany, tension between work and home does not significantly affect overall life sat-
isfaction of the working population. A more detailed analysis separately for both sexes (not
shown) reveals the gendered effect of this factor. For men, the effect is only found in
Sweden and the Netherlands. For women, tension between employment and private life is
more wide-spread; a significant negative effect on life satisfaction can be found in Sweden,
Finland, the Netherlands, the UK, and Hungary.
To illustrate the effects of parameter estimates in Table 3on life satisfaction, we calcu-
lated the predicted life satisfaction score for hypothetical workers in the nine countries under
study. We simulated cases under varying working conditions and compared life satisfaction
of these constructed cases with the average life satisfaction score in each country. Predictions
are made for a 40 year-old man with a college degree, married, with one child, working 38 h
per week (Fig. 1). The left-hand bar in Fig. 1displays the predicted overall life satisfaction
of this simulated case under ‘‘bad’’ working conditions: 1.5 h commuting per day, no
supervisory status, no permanent contract, time pressure at work, stressful, insecure, boring,
dangerous and unhealthy job. His job is not well-paid, offers no autonomy and no career
prospects. Job satisfaction is low, two standard deviations below the country mean, and
work-home interference is high, two standard deviations above the mean value for the
country. The right-hand bar for each country in Fig. 1displays the predicted life satisfaction
of the same person working under good working conditions: commuting time is 30 min, the
person has a supervisory position and a permanent contract. His job is interesting, secure,
well-paid, not dangerous or stressful, provides autonomy, and good career prospects. Job
satisfaction is high (two standard deviations above the country mean) and work-home
interference is low (two standard deviations below the mean value for the respective
country). The middle bar for each country shows the observed mean of overall life satis-
faction for employed persons, as derived from Table 1.
The comparison of observed and predicted life satisfaction scores clearly shows that
working conditions can make a large difference in the lives of European workers.
1
2
3
4
5
6
7
8
9
10
SE FI NL DE UK PT E HU BG
Predicted life satisfaction: “bad”, undesirable working conditions
Observed average life satisfaction score
Predicted life satisfaction: “good” working conditions
Fig. 1 Predicted life satisfaction scores for incumbents of ‘‘good’’ and ‘‘bad’’ jobs
220 S. Drobnic
ˇet al.
123

A difference in quality of life between those with good and bad jobs can be almost five
points on the ten-point life satisfaction scale, as the simulation for Bulgaria shows. Bad
working conditions are particularly detrimental to life satisfaction in Bulgaria, Hungary and
Portugal, that is in countries with low overall life satisfaction. In other words, the countries
in which undesirable working conditions have the strongest negative effect on life satis-
faction are also the countries in which jobs are of a lesser quality (cf. Table 1) and more
people have low quality jobs, which eventually results in a low country average on the life
satisfaction scale. In these countries, positive working conditions, too, have a considerable
effect and lead to higher gains in life satisfaction than in other countries in the analysis.
5 Conclusions
Our findings make several distinct contributions. First, they provide empirical evidence of
the relationship between working conditions and quality of life of individuals and identify
aspects of work that are particularly salient for individuals’ overall life satisfaction. Sec-
ond, we address the issues of objective and subjective indicators in quality of life and
quality of work and contribute to the academic discussion on the mechanisms that link
these two life domains, such as spillover and segmentation. Third, we contribute to cross-
national comparative research by performing detailed analyses for nine selected EU
member states, including those in Southern and Eastern Europe that are less often included
in comparative studies. Finally, quality of life and well-being of European citizens, as well
as job quality, have been an explicit EU policy objective. Our findings contribute to the
discussion on the decisive dimensions of job quality and bear important policy
implications.
There are substantial differences in terms of working conditions and life satisfaction
among European countries. Life satisfaction outcomes are significantly influenced by the
economic development of countries as measured by GDP per capita, and other country
characteristics that are captured by country dummies in our analysis. Nevertheless, indi-
viduals’ job characteristics and working conditions—or more precisely, individuals’ per-
ceptions of working conditions—also exhibit important effects on life satisfaction
outcomes. The major positive contributions to high quality of life seem to come from
having a well-paid job and autonomy at work. The major negative factors are job insecurity
and having a dull, boring job. Job autonomy and a dull/boring job are work characteristics
that most conspicuously translate into job (dis)satisfaction and through job (dis)satisfaction
indirectly affect overall quality of life. Security of employment and pay, however, exhibit
the most distinct and wide-spread direct effects on life satisfaction across Europe. Since the
perception of being reasonably well-paid is an indicator of economic security, our study
suggests that the issue of security is the key element in employment that in a most
straightforward manner affects people’s quality of life. If a certain basic security level is a
precondition for well-being, the large cross-country differences in average life satisfaction
may to a large extent reflect differences in (perceived) security and the effectiveness of the
welfare safety net across European countries.
Along more general lines, our analysis suggests that the effects of working conditions
on overall life satisfaction are not symmetric. There is a tendency that ‘‘bad jobs’’ are more
effective in lowering life satisfaction than ‘‘good jobs’’ in augmenting it. Having a par-
ticularly good job does not increase individuals’ quality of life much above the baseline
level that is determined by factors not related to work. Perhaps having a good job is highly
associated with other favourable life circumstances which as a whole make individuals
Good Job, Good Life? 221
123

satisfied with their lives. However, a bad job—and especially experiencing cumulative
disadvantages at work—exhibits a considerably stronger negative effect on overall quality
of life.
The second general observation is that the effect of working conditions on overall life
satisfaction is stronger in poorer countries in Eastern and Southern Europe than in Nordic
and Western European societies. Thus, in more affluent societies, job characteristics and
working conditions matter less for individual well-being. Among the countries for which
we performed detailed analyses, Bulgaria, Hungary and Portugal show evidence of
cumulative adverse working conditions and the impact of these on overall life satisfaction
is more pronounced than in other countries. The fact that in these countries working
conditions are less favourable, that the composition of the labour force and an industry
structure with a large manufacturing sector channels many workers into ‘‘bad jobs’’, and
that adverse working conditions have a strong impact on overall life satisfaction, leads us
to conclude that work-related factors have a considerable impact on the very low overall
satisfaction scores observed in these countries in cross-national comparative research.
With economic prosperity and increasing welfare state provision, work dimensions that
most powerfully impact on people’s quality of life seem to change and new determinants of
life satisfaction become salient. Negative aspects of work, such as having a dangerous and
unhealthy job that does not pay satisfactory wages, are supplemented or replaced by other
work characteristics that lead to low job satisfaction and low quality of life, such as a
boring job or lack of autonomy at work. Another emerging issue is intensification of work.
Employees in all countries experience demanding and stressful work but more affluent
societies are confronted with an additional issue: increasing time pressure and intensifi-
cation of work (see also Green 2006). It is in these societies that people increasingly report
that they constantly work to tight deadlines and this has a detrimental effect on their life
quality. Tight deadlines may be more present in affluent societies with an extensive service
sector and less present in manufacturing. Also, the meaning and importance of the work-
home interface is stronger in Nordic and Western European countries than in Southern and
Eastern European countries. Although the reported conflict between work and home is in
effect weaker in Nordic/Western societies, its negative effect on quality of life is stronger.
6
We term this an ‘‘affluence work-home paradox’’: although the tension between work and
home is lesser in richer countries, it has a stronger negative impact on life satisfaction,
perhaps due to increasing awareness and sensitivity towards the issues of work-life balance
or less access to extended family support networks.
In terms of competing mechanisms of domain interaction—spillover or segmentation—
our study suggests that neither mechanism can be ruled out. Certain job characteristics and
working conditions are highly correlated with job satisfaction. An interesting job that
offers good career prospects and allows incumbents to make autonomous decisions on how
to perform their work leads to high satisfaction with work, especially if this job is also
secure and well-paid. When we included job satisfaction in our regression models for the
pooled data, the direct effects of these variables on life satisfaction disappeared or the size
of the coefficients diminished considerably. Also, including job satisfaction significantly
improved the predictive power of the model, supporting the thesis of spillover from the
work domain to overall life attitudes. However, the assumption that people tend to com-
partmentalize life domains and it is the interface between the domains and a successful
6
Differences in the meaning and implications of the work-family conflict is perhaps at the core of the
problem of transferring successful measures for improving the work-life balance from some countries to
others (Leitner and Wroblewski 2006).
222 S. Drobnic
ˇet al.
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partitioning that matters for the quality of life has also been supported. Our analysis
suggests that interference between work and home mediates between life satisfaction and
the following job characteristics and working conditions in particular: time pressure, career
prospects and commuting time. In other words, work intensification and long commuting is
a problem for quality of life particularly if it leads to an unsatisfactory management of the
interface between work and private life. Likewise, the positive effect of career prospects
becomes insignificant when work-home interference is controlled. In broader terms this
indicates that, in their subjective evaluation, a career for which people have to sacrifice
their personal life does not contribute significantly to quality of life.
To conclude, working conditions do have a significant effect on quality of life, mainly
in a sense that bad working conditions lower life satisfaction. From the European per-
spective at large, this study highlights the regional variation in working conditions and the
importance of the societal context in achieving good quality of life. It also highlights the
fact that indicators of high quality jobs that enhance workers’ well-being differ to some
extent between the countries. Policy-makers have to respond to differing needs when
striving to fulfil the Lisbon goal of ‘more and better jobs’ as well as achieving high quality
of life for European citizens. For poorer countries in Eastern and Southern Europe, security
of employment, dangerous and unhealthy working conditions and decent pay are most
crucial issues at present. These issues and the goal of improving them closely follow the
concept of ‘‘decent work’’ (ILO 1999) as a key component of national development
strategies. In several Northern and Western European countries, respondents often report
that a dull and boring job, intensification of work with tight deadlines and balancing work
and private life decisively contribute to their well-being. Together with employment
security and pay (economic security), these are the areas where further research and policy
interventions are most needed.
Acknowledgments This research has been supported in part by the European Commission Sixth
Framework Programme Project ‘‘Quality of Life in a Changing Europe’’ (QUALITY), and the Network of
Excellence ‘‘Reconciling Work and Welfare in Europe’’ (RECWOWE).
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