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

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Mar 4, 2010 - of life. Other working conditions, such as autonomy at work, good career ... Keywords Job quality 4 Life satisfaction 4 Quality of life 4 Europe 4.
Soc Indic Res (2010) 99:205–225 DOI 10.1007/s11205-010-9586-7

Good Job, Good Life? Working Conditions and Quality of Life in Europe Sonja Drobnicˇ • Barbara Beham • Patrick Pra¨g

Accepted: 8 February 2010 / Published online: 4 March 2010 Ó Springer 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 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. Keywords Job quality  Life satisfaction  Quality of life  Europe  Cross-national comparison S. Drobnicˇ (&) University of Hamburg, Allende-Platz 1, Hamburg 20146, Germany e-mail: [email protected] B. Beham Humboldt-Universita¨t zu Berlin, Spandauer Str. 1, Berlin 10178, Germany e-mail: [email protected] P. Pra¨g University of Groningen, Grote Rozenstraat 31, Groningen 9712 TG, The Netherlands e-mail: [email protected]

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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 knowledge 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, intimacy, 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 constitutes 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 different 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 characteristics, 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 productivity (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 deficiencies in the European definition in neglecting dimensions such as wages and work intensity.

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individuals, such as occupational class, type of contract, or supervision responsibilities, as well as between job satisfaction and subjective evaluations, such as job demands, autonomy, 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 measuring 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 different 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 samelevel 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 conceptual 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 satisfaction 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 conceptualized 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 workhome 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

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greatly among European countries but it is not clear whether the determinants of life satisfaction 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 countrylevel 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 temporary 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 workhome 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

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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 interested 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 supervising 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. Furthermore, 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 compartmentalization 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).

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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 quadratic 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, distinguishing 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, Bulgarians 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

123

2.45a

3.10c

2.11bc

1.60ab

2.47a

3.92ef

2.64bc

1.90b

2.40ab

7.95a

3.01bc

3.08c

2.09bc

1.53ab

2.89b

3.94f

2.49ab

1.60a

2.53bc

7.59ab

Job demanding/stressful

Time pressure

Job dangerous/unhealthy

Job insecurity

Well-paid

Job autonomy

Career prospects

Job dull/boring

Work-home interference

Job satisfaction

7.44bc

2.30a

1.66a

2.96de

3.81def

3.38c

1.48a

1.88ab

2.94bc

2.49a

.73b

33.36

a

7.64cd

NL

7.92a

2.43ab

1.63a

2.78cd

3.66cde

3.46c

1.72bc

1.81a

3.15cd

3.27cd

.61ab

38.11

bc

7.47c

DE

7.31bc

2.73cd

2.22cd

3.14e

3.45bc

3.05b

1.60ab

1.92ab

3.43d

2.94b

.62ab

35.98

b

7.50c

UK

6.82de

2.88d

2.40d

2.83cd

3.27ab

2.62a

1.88c

2.13bc

2.75ab

3.44d

.59a

41.59

de

6.30b

PT

7.14cd

2.71cd

2.09bc

3.14e

3.63cd

2.98b

1.85c

1.97ab

2.95bc

2.97b

.61ab

39.91

cd

7.57cd

E

7.11cd

2.84d

2.17c

2.29a

3.02a

2.36a

1.93c

2.35cd

2.99bc

3.14bc

.67ab

43.14

e

6.10b

HU

6.42e

2.88d

2.13c

2.40ab

3.27ab

2.41a

3.21d

2.47d

2.54a

3.75e

.57a

42.93e

4.69a

BG

1–10

1–5

1–5

1–5

1–5

1–5

1–5

1–5

1–5

1–5

0–6

2–110

1–10

Range

23.28 (8, 3345)

20.05 (8, 3345)

36.93 (8, 3345)

23.64 (8, 3345)

29.62 (8, 3345)

48.65 (8, 3345)

69.51 (8, 3345)

11.11 (8, 3345)

12.51 (8, 3345)

43.89 (8, 3345)

3.36 (8, 3345)

30.46 (8, 3345)

151.89 (8, 3345)

F (df)

.053

.046

.081

.054

.066

.104

.143

.026

.029

.095

.008

.068

.266

R2

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

Note: All F-tests are statistically significant at p \ .001 Means with different superscripts are significantly different from one another using Tukey HSD test

.62ab

38.36

.57a

39.46

bc

8.23e

cd

7.90de

Commuting time

Working hours

Life satisfaction

FI

SE

Table 1 Comparison of variable means by Country

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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 2 examines 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 satisfaction. 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).

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Table 2 Life satisfaction regressed on working conditions for pooled data (OLS, standard errors in parentheses)

Working hours

(1)

(2)

(3)

(4)

(5)

(6)

-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 hours2 (coeff. 9 1,000)

-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)

0.255***

0.129*

0.130*

0.0923

0.156*

0.114

(0.066)

(0.061)

(0.061)

(0.059)

(0.061)

(0.058)

0.128

0.051

0.064

0.034

0.075

0.044

(0.070)

(0.064)

(0.063)

(0.061)

(0.063)

(0.060)

Supervisor Permanent contract Job demanding/stressful Time pressure Job dangerous/unhealthy Job insecurity Well-paid Job autonomy Career prospects Job dull/boring

-0.346*** -0.146*

-0.068

-0.019

0.052

0.070

(0.061)

(0.059)

(0.056)

(0.060)

(0.058)

(0.059)

0.103

-0.124*

-0.157**

-0.118*

-0.091

-0.070

(0.063)

(0.059)

(0.058)

(0.056)

(0.058)

(0.056)

-0.201*

-0.138

-0.201**

-0.145*

-0.161*

-0.118

(0.083)

(0.077)

(0.075)

(0.072)

(0.075)

(0.072)

-1.222*** -0.661*** -0.610*** -0.435*** -0.586*** -0.425*** (0.099)

(0.094)

(0.095)

(0.092)

(0.094)

(0.091)

0.489***

0.276***

0.369***

0.230***

0.344***

0.218***

(0.065)

(0.061)

(0.061)

(0.059)

(0.060)

(0.059)

0.546***

0.308***

0.263***

0.111

0.247***

0.106

(0.066)

(0.062)

(0.062)

(0.060)

(0.061)

(0.059)

0.120

0.108

0.126*

-0.056

0.104

-0.064

(0.069)

(0.063)

(0.063)

(0.061)

(0.062)

(0.061)

-0.507*** -0.483*** -0.467*** -0.104

-0.388*** -0.061

(0.104)

(0.094)

(0.096)

(0.095)

Job satisfaction

(0.093)

0.251***

(0.015)

(0.015)

Work-home interference

-0.256*** -0.196*** (0.030)

GDP per capita Finland Netherlands Germany United Kingdom Portugal

(0.093)

0.264***

(0.029)

0.132***

-0.096

-0.113

-0.109

-0.123

(0.005)

(0.109)

(0.105)

(0.108)

(0.104)

0.540**

0.465**

0.564***

0.487**

(0.165)

(0.158)

(0.163)

(0.157)

-0.070

0.071

-0.015

0.106

(0.334)

(0.320)

(0.330)

(0.318)

-0.294

-0.357*

-0.292

-0.353*

(0.156)

(0.149)

(0.154)

(0.148)

-0.358**

-0.303**

-0.300**

-0.261*

(0.113)

(0.108)

(0.112)

(0.108)

-1.965**

-2.009**

-1.978**

-2.017**

(0.690)

(0.661)

(0.682)

(0.656)

123

S. Drobnicˇ et al.

216 Table 2 continued (1)

(2)

Spain Hungary Bulgaria Intercept

(3)

(4)

(5)

(6)

-0.629

-0.608

-0.616

-0.600

(0.454)

(0.434)

(0.449)

(0.432)

-2.527*

-2.753*

-2.609*

-2.805*

(1.188)

(1.138)

(1.175)

(1.130)

-4.430*

-4.624*

-4.624*

-4.762**

(1.909)

(1.829)

(1.888)

(1.816)

8.551***

5.450***

11.05***

9.568***

11.63***

10.08***

(0.398)

(0.388)

(2.544)

(2.438)

(2.517)

(2.423)

N

3354

3354

3354

3354

3354

3354

Adj. R2

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 hours2 are multiplied by 1,000 * p B .05, ** p B .01, *** p B .001

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 correlated), 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 individuals’ 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 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%).

123

Good Job, Good Life?

217

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 onepoint 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 contributes 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. Controlling 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 levels—or the patterns of determinants themselves differ between the countries. In interpreting 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 detrimental 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 constellations. 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

123

123

Career prospects

Job autonomy

Well-paid

Job insecurity

Job dangerous/unhealthy

Time pressure

Job demanding/stressful

Permanent contract

Supervisor

Commuting time

Working hours2 (coeff. 9 1,000)

Working hours

(0.125)

(0.146)

(0.134) 0.067

-0.027

(0.168)

(0.131) 0.043

(0.136)

0.129

0.279*

0.209

(0.209)

(0.248)

(0.147) -0.261

(0.160)

-0.109

0.137

(0.106)

0.180

(0.143)

(0.140) 0.073

-0.084

(0.140)

(0.138) -0.160

(0.171)

0.107

0.209

(0.109)

0.280

(0.149)

(0.106) -0.005

0.278

(0.122)

(0.168) -0.010

(0.003)

-0.279*

-0.023

(0.015)

0.164

0.004

(0.030)

FI

-0.009

SE

(0.109)

-0.060

(0.116)

0.012

(0.102)

0.056

(0.295)

-0.542

(0.169)

-0.111

(0.104)

0.024

(0.126)

-0.050

(0.126)

0.0314

(0.104)

0.163

(0.0710)

0.072

(0.234)

-0.009

(0.016)

-0.000

NL

(0.199)

0.059

(0.186)

0.431*

(0.181)

0.490**

(0.330)

-0.340

(0.249)

0.113

(0.183)

-0.052

(0.173)

-0.050

(0.190)

-0.011

(0.197)

0.0112

(0.153)

0.061

(0.274)

-0.539

(0.023)

0.036

DE

(0.185)

0.012

(0.189)

0.140

(0.175)

0.130

(0.328)

-0.408

(0.252)

-0.276

(0.189)

-0.541**

(0.180)

0.266

(0.185)

-0.204

(0.178)

0.051

(0.133)

-0.054

(0.236)

-0.334

(0.020)

0.030

UK

(0.210)

0.161

(0.184)

0.059

(0.225)

0.207

(0.284)

-0.129

(0.245)

-0.841***

(0.201)

-0.132

(0.184)

-0.182

(0.196)

-0.043

(0.210)

0.218

(0.154)

-0.295

(0.264)

-0.146

(0.025)

0.017

PT

Table 3 Life satisfaction regressed on working conditions for individual countries (OLS, standard errors in parentheses)

(0.170)

-0.259

(0.173)

0.096

(0.166)

0.241

(0.285)

-0.193

(0.228)

-0.089

(0.162)

0.050

(0.175)

0.085

(0.160)

0.012

(0.187)

-0.095

(0.140)

0.057

(0.220)

-0.594**

(0.020)

0.057**

ES

(0.320)

-0.0544

(0.242)

-0.076

(0.319)

-0.191

(0.371)

-0.751*

(0.279)

0.284

(0.228)

-0.140

(0.242)

0.181

(0.253)

-0.110

(0.273)

0.448

(0.152)

-0.091

(0.263)

-0.637*

(0.028)

0.037

HU

(0.363)

-0.716

(0.274)

0.053

(0.380)

0.554

(0.269)

-0.652*

(0.325)

-0.787*

(0.330)

0.104

(0.292)

0.593*

(0.295)

0.058

(0.299)

0.039

(0.264)

-0.139

(0.500)

-0.244

(0.048)

0.023

BG

218 S. Drobnicˇ et al.

0.223

0.194

463

(0.747)

6.596***

(0.056)

-0.205***

(0.045)

0.267***

(0.262)

0.120

NL

0.225

356

(1.200)

5.701***

(0.109)

-0.127

(0.048)

0.298***

(0.416)

0.389

DE

0.186

354

(1.123)

8.130***

(0.091)

-0.309***

(0.049)

0.172***

(0.248)

-0.424

UK

0.232

361

(1.090)

6.154***

(0.088)

-0.125

(0.048)

0.314***

(0.234)

0.022

PT

0.207

318

(1.085)

4.594***

(0.084)

-0.096

(0.049)

0.317***

(0.260)

-0.493

ES

2

0.163

333

(1.626)

4.775**

(0.108)

-0.116

(0.051)

0.298***

(0.322)

-0.095

HU

0.167

255

(2.223)

6.753**

(0.139)

-0.142

(0.057)

0.191***

(0.445)

-0.335

BG

* p B .05; ** p B .01; *** p B .001

Note: Gender, age in linear and quadratic form, marital status, number of children, and education are controlled. Coefficients for working hours are multiplied by 1,000

0.181

Adj. R2

425

(0.792)

(1.091)

489

6.446***

9.344***

-0.273*** (0.070)

-0.392***

(0.042)

(0.038)

(0.079)

0.285***

(0.246)

0.179***

0.636*

0.238

FI

(0.278)

SE

N

Intercept

Work-home interference

Job satisfaction

Job dull/boring

Table 3 continued

Good Job, Good Life? 219

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S. Drobnicˇ et al.

220

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 satisfaction 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 3 on life satisfaction, we calculated 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. 1 displays 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. 1 displays 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 satisfaction 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.

10 9 8 7 6 5 4 3 2 1 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

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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 satisfaction 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. Second, 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 crossnational 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, individuals’ job characteristics and working conditions—or more precisely, individuals’ perceptions 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 particularly 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

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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 intensification 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 workhome 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 compartmentalize 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).

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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 perspective 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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