Quality of life indicators - productive or main activity

Data from October 2013. Most recent data: Further Eurostat information, Main tables and Database. Planned update: July 2018

This article is part of the Eurostat online publication Quality of life indicators, providing recent statistics on the quality of life in the European Union (EU). The publication presents a detailed analysis of many different dimensions of quality of life, complementing the indicator traditionally used as the measure of economic and social development, gross domestic product (GDP).

The present article focuses on the second dimension of the '8+1' quality of life indicators framework, productive or main activity. This refers to both paid and unpaid work and to other types of main activity status, but at the moment data is available only for the former thus not covering the whole population. Paid work usually takes up a significant part of people's time and it can have a significant impact on the quality of life, either positively or negatively. On the positive side, work generates an income, but it also can provide identity and opportunities to socialise with others, to be creative, to learn new things and to engage in activities that give a sense of fulfilment and enjoyment. Conversely, people's quality of life deteriorates when they experience discrimination, insecurity, fear of physical injury, or have to work long hours for inadequate pay. Lack of work or unemployment may even threaten people’s psychological health.

Assessing the effect of paid work on quality of life is a complex matter, because many complementary aspects of people’s main activity have to be taken into account. Broadly speaking, the quantity as well as the quality of employment need to be measured.

Figure 1: Employment rate, 2007 and 2012 (% of active population aged 15 to 64)
Source: Eurostat, EU-LFS (lfsi_emp_a)
Figure 2: Long-term unemployment (12 months or more) rate and unemployment rate, 2012 (% of active population)
Source: Eurostat, EU-LFS (lfsa_urgaed) and (une_ltu_a)
Figure 3: Unemployment rate by educational level, 2012 (% of active population aged 15 to 74)
Source: Eurostat, EU-LFS (lfsa_urgaed)
Figure 4: Youth unemployment ratio, 2012 (% of the total population aged 15 to 24)
Source: Eurostat, EU-LFS (lfsi_act_a)
Figure 5: Percentage of population aged 15 to 74 in involuntary part-time employment by sex, 2012 (%)
Source: Eurostat, EU-LFS (lfsa_eppgai)
Figure 6: Proportion of low-wage earners (excluding apprentices), 2006 and 2010 (1) (%)
Source: Eurostat (earn_ses_pub1a)
Figure 7: Proportion of low-wage earners (excluding apprentices) by age group, 2010 (1) (%), Source: Eurostat (earn_ses_pub1a)
Figure 8: Proportion of low-wage earners (excluding apprentices) by educational level, 2010 (1) (%)
Source: Eurostat (earn_ses_pub1i)
Table 1: Average number of actual weekly hours of full-time work, 2012 (1) (hours)
Source: Eurostat, EU-LFS (lfsa_ewhun2) and (lfsa_ewh2n2)
Figure 9: Population aged 15-74 usually working at nights, 2012 (% of the total population in employment)
Source: Eurostat, EU-LFS (lfsa_ewpnig)
Figure 10: Number of fatal accidents at work, 2008 and 2010 (1) (incidence rates per 100 000 persons employed)
Source: Eurostat (hsw_mi01)
Figure 11: Satisfaction with current job, 2011 (mean scale 1-10)
Source: Eurofound (Third European Quality of Life Survey Quality of life in Europe: Impacts of the crisis)

Main statistical findings

Productive or main activity in the context of quality of life

‘Productive or main activity’ refers to both paid and unpaid work. However, data is available only concerning various aspects of the former (including the lack thereof) and do not cover the latter. Hence, the indicators analysed in this article refer only to gainful employment. However, work affects quality of life not only because of the income it generates but also because of the role it plays in giving people their identity and opportunities to socialise with others. People’s paid work consumes a significant part of their time and shapes their sense of fulfilment and happiness. If work provides individuals with an opportunity to be creative, learn new things, engage in activities that produce a sense of achievement and reward, and gain an income sufficient to enhance their capabilities[1], then their quality of life can improve. Conversely, if they experience discrimination, insecurity, fear of physical injury, or have to work long hours for inadequate pay, they may feel that their quality of life is deteriorating. In addition, a lack of work and unemployment have been shown to have a negative impact on psychological health[1][2]. Assessing the effect of paid work on quality of life is a complex task which requires us to take into account several factors covering various complementary aspects of people’s main activity.

Broadly speaking, the aspects that need to be measured are the quantity and the quality of employment. Indicators used for assessing the quantity or lack of employment are unemployment (including long-term unemplyment) and involuntary part-time employment and low work intensity, the last two being used as proxies of underemployment (working less than one is able) within the context of quality of life. A slightly different measurement concept is used for defining Underemployed_part-time_worker within the labour market context, due to the fact that there is less focus on individual choices and capabilities. As noted in the Joseph E. Stiglitz, Amartya Sen and Jean-Paul Fitoussi's Report, ‘people who become unemployed report lower life-evaluations, even after controlling for their lower income, and with little adaptation over time; unemployed people also report a higher prevalence of various negative effects (sadness, stress and pain) and lower levels of positive ones (joy). These subjective measures suggest that the costs of unemployment exceed the income-loss suffered by those who lose their jobs, reflecting the existence of non-pecuniary effects among the unemployed and of fears and anxieties generated by unemployment in the rest of society’.

The quality of employment is measured by various sub-dimensions, in line with a framework developed by a joint UNECE/Eurostat/OECD Task Force, including income and benefits (the incidence of low earnings), work-life balance (based on the average number of hours worked, at the moment) and health and safety at work (the incidence of work-related accidents).

It should be noted that employment quantity and quality are complementary and, therefore, not to be substituted when it comes to measuring improvements in the quality of life. Improvements in quantity affect most the un- and the under-employed, whereas improvements in quality affect most those in employment. The complementarity between employment quantity and quality as regards well-being has been reflected for some time in the European Commission’s European Employment Strategy for ‘more and better jobs’.

All of these indicators (which we examine further below) are objective, i.e. they measure observed characteristics of employment. However, it is also important to use subjective indicators, such as individuals’ satisfaction both overall and with various aspects of their work. One such indicator is currently under development in the 2013 Ad-hoc Module of EU-SILC. Due to its importance for quality of life (see, for example, Van Praag and Ferrer-i-Carbonell, 2011), a ‘placeholder’ measuring satisfaction with work (taken from the EQLS) is currently included in the framework.

Quantitative aspects of employment

Unemployment is strongly associated with low levels of life satisfaction and happiness. The link between unemployment and underemployment and lower subjective well-being has been documented in several studies (see Abdalallah, Stoll and Eiffe, 2013 for a review). Importantly, research has shown that this link cannot be explained purely on the basis of characteristics (e.g. bad health) that may make individuals less likely to be employed. In other words, being unemployed has an impact on well-being regardless of other characteristics that may be associated with it (ibid.).

In 2012, the employment rate (i.e. the number of employed people as a proportion of the population aged 15 to 64) in the EU-28 was 64.1 %, as compared with 65.3 % in 2007 (see Figure 1). The Member States with the highest employment rates in 2012 were (in descending order) the Netherlands, Sweden, Germany, Denmark, Austria and the United Kingdom, all of which had rates of 70.0 % or more (75.1 % in case of the Netherlands). At the lower end of the scale were Croatia, Greece, Spain, Italy, Hungary, Bulgaria, Ireland, Malta, Romania, Poland and Slovakia, which all had rates of below 60.0 %, with Croatia’s as low as 50.7 %. Between 2007 and 2012, the trend was one of falling employment rates across Member States, with only a few exceptions (e.g. Germany, Austria, Poland, Romania, Malta, the Czech Republic and Luxembourg).

Unemployment and long-term unemployment

Some studies have suggested that people’s subjective well-being tends to adapt to prolonged unemployment, i.e. the negative effect of unemployment on well-being is reduced. Others have shown that people who have been unemployed for over a year experience a greater adverse effect on their well-being than those unemployed for a shorter period (see, for example, Abdallah, Stoll and Eiffe, 2013).

The unemployment rate, which measures the rate of those actively looking for employment as a proportion of the total economically active population aged 15-74, was 10.5 % in the EU-28 in 2012 (see Figure 2). Within the economically active population, 4.7 % were ‘long-term unemployed’, i.e. had been in this situation for at least a year.

The Member States with the highest unemployment rates in 2012 were Spain at 25.0 %, followed by Greece (24.3 %), Croatia and Portugal (15.9 %), Latvia (15.0 %), Ireland (14.7 %) and Slovakia (14.0 %). Austria, the Netherlands and Luxembourg had the lowest unemployment rates, between 4.3 % and 5.3 %. The Member States with the highest overall unemployment rates also recorded the highest long-term unemployment, with some differences in the ranking: Greece was highest at 14.4 %, followed by Spain (11.1 %), Croatia (10.3 %), Slovakia (9.4 %) and Ireland (9.1 %). Similarly, the countries with the lowest long-term unemployment rates (ranging between 1.1 % and 1.8 %) were those with the lowest overall rates, together with Sweden and Finland.

Unemployment by educational attainment

In all countries, higher levels of educational qualification were associated with lower unemployment rates. From a quality-of-life perspective, this is a positive development, as research has shown that, other things being equal, unemployment has a larger negative effect on the well-being of people with higher education (see, for example, Abdallah, Stoll and Eiffe, 2013). In 2012, the unemployment rate in the EU-28 was 10.5 % overall (see Figure 3), but 18.2 % for those with only basic education, 9.6 % for those with upper-secondary/post-secondary (non-tertiary) education, and only 6.1 % for those with tertiary education and above.

In 2012, unemployment among those with low educational qualifications was highest in Slovakia (44.6 %) and Lithuania (34.7 %) and lowest in Romania (6.9 %), Luxembourg, the Netherlands (both 8.4 %) and Austria (8.9 %). Greece and Spain had by far the highest unemployment rates among those with secondary education – 27.4 % and 24.4 % respectively, as compared with only 3.9 % in Austria and 4.8 % in Malta. Greeks and Spaniards with higher education qualifications (or similar) also faced quite high rates (18.1 % and 15.0 % respectively). At the other end of the scale, the jobless rate among those with a higher education in Austria, Malta, Germany and the Czech Republic was between 2.1 % and 2.9 %. This range, which may be due to differing labour market structures, shows how unemployment can be distributed differently across educational categories from country to country.

The greatest variations in unemployment rates according to level of educational qualification were recorded in the Czech Republic, Slovakia, Lithuania, Hungary, Germany and Bulgaria, where rates among the most educated were one-tenth to one-fifth of those among the least educated. On the other hand, in countries like Romania, Cyprus and Portugal, the degree of variation was much smaller, with the former around 70-80 % of the latter.

It is also worth noting (see Figure 3), however, that although the relative gap in Spain (15.0 % vs 33.8 %) was very similar to that in Luxembourg (3.6 % vs 8.4 %), the Netherlands (3.2 % vs 8.4 %) and Finland (3.9 % vs 16.0 %), the actual rates were much higher: the unemployment rate of those with high qualifications in Spain (15.0 %) was almost five times that in the Netherlands (3.2 %) and almost double that among those with low qualifications in Luxembourg and the Netherlands (both 8.4 %). Similarly, people with high qualifications in Greece, Portugal and Cyprus recorded higher unemployment rates (18.1 %, 11.9 % and 10.3 % respectively) than those with basic qualifications in Luxembourg, the Netherlands (both 8.4 %) and Austria (8.9 %).

Unemployment by age

As to whether unemployment has a relatively greater adverse effect on younger people’s well-being, the evidence is mixed[3][4][5].

The average ‘youth unemployment ratio’ (i.e. the number of unemployed expressed as a proportion of the population aged between 15 and 24) in the EU-28 in 2012 was 9.7 % (see Figure 4). Spain (20.6 %), Greece (16.1 %) and Portugal (14.3 %) had levels well above this average. The Member States with the lowest youth unemployment ratios were Germany (4.1 %), Luxembourg (5.0%) and Austria (5.2 %).

The youth unemployment ratio is different from the youth unemployment rate, which measures the share of the unemployed as a proportion of the active population aged between 15 and 24. High youth unemployment rates do reflect problems faced by young people in finding employment, but the alarming figures do not refer to the whole population in that age category, as many are studying full-time and are therefore neither employed nor looking for a job and available for work. As such, they are not part of the labour force, on the basis of which the unemployment rate is calculated. More information on measuring youth unemployment is available.

Involuntary part-time employment 

Involuntary part-time employment (as a proportion of total part-time employment) measures one aspect of underemployment which is important in the context of Quality of life. If people work fewer hours than they would like to, this has implications for their opportunities to earn income, interact socially and shape their identity, all of which impinge on their quality of life. People sometimes accept part-time work for lack of full-time alternatives. However, in some Member States without favourable legislation or collective agreements for this type of contract, part-time work may involve inferior conditions as regards access to benefits and opportunities for training and career advancement.

In 2012 26.3 % (over one in four) of employees working part-time in the EU 28 did so involuntarily (see Figure 5). Among female part-time employees, the proportion was 23.7 %. In 2012, Greece and Bulgaria were the countries with the highest proportions of overall (63.6 % and 62.3 %) and female (61.4 % and 62.7 %) involuntary part-timers. The Netherlands, where part-time employees enjoy similar conditions to those working full-time, registered the lowest rate of female involuntary part-time employment (7.7 %) and the second lowest overall rate (8.8 %). Slovenia recorded the lowest overall rate (8.1 %).

In the majority of Member States, the proportion of involuntary part-time workers is higher among men than among women. This is not surprising, given that women are more likely to have to combine work and family obligations, and thus to ‘prefer’ working part-time. However, this is not the case in all Member States. Involuntary part-time employment is also more prevalent amongst those aged 15-24 and 25-49 than among older employees (aged 50-74). Detailed data by Member State are not provided, as the proportion of the population working part-time is so small in some countries that the figures are unreliable.

Quality of employment

Income and benefits

‘Low-wage earners’ are employees earning two thirds or less of the ‘national median earnings’ (an hourly rate that one half of a country’s population earn less than and the other half more than). Hence, the low-wage threshold is different in each country.

In 2010, 16.9 % of all employees (excluding apprentices) in the EU-27 were low wage earners, a slight increase from 16.8 % in 2006 (see Figure 6). The Member States with the highest proportions of low wage earners were Latvia (27.8 %) and Lithuania (27.2 %), followed by Romania (25.6 %). In all three countries, these levels are lower than in 2006 by one or two percentage points. At the other end of the scale, in Sweden, only 2.5 % of employees (excluding apprentices) were low wage earners, up from 1.8 % in 2006.

Low earnings by age

On average (see Figure 7), employees aged 30 or less were more than twice as likely (30.7 % in the EU-27) to be low wage earners than those aged 30-49 (13.5 %) or older (14.3 %).

There were some notable exceptions to these trends in the Baltic States, the Czech Republic and Slovakia. In all these countries apart from Estonia, the proportions of low wage earners among those aged 50 or more and among the under 30s were similar. In Estonia, the proportion in the older age-group was even higher.

In all Member States, the proportion of employees aged below 30 who were low wage earners is always greater than among those aged 30-49. In other words, the passage from a young working age to an age of 30-49 is associated everywhere with a lower likelihood of low earnings. However, in no fewer than 12 Member States (most of them situated in Eastern Europe), those aged 50 or over are more likely than those aged 30 to 49 to be low-wage earners.

Low earnings by educational attainment

In 2010, the proportion of employees in the EU-27 with a high level of education (tertiary and above) who were low-wage earners was 5.8 %, while the proportion among those with medium (secondary/post-secondary) qualifications was 19.2 % and among those with low qualifications 29.0 % (see Figure 8). In Germany and Slovakia, over half of employees with low qualifications are low earners (54.6 % and 51.5 % respectively), while in Sweden only four in 100 employees with low qualifications are low-wage earners. In Lithuania, almost four in 10 employees with medium educational attainment earn low wages, whereas in Sweden this applies to fewer than three in 100 employees in that category. The countries where employees with high educational attainment are most likely to be low-wage earners are Lithuania (13.3 %), Ireland (12.9 %), Latvia (12.0 %) and the United Kingdom (11.4 %), while in Belgium there are virtually no employees with high qualifications earning low salaries (0.2  %).

Work-life balance

The number of hours worked per week influences work-life balance, which in turn has an effect on subjective well-being. However, this effect is not linear. Research has shown that subjective well being increases with the number of hours an individual works per week but only up to a certain point, beyond which it starts to deteriorate, possibly because excessive (over 48 per week) working hours reduce job satisfaction which in turn reduces overall fulfilment (Abdallah, Stoll and Eiffe, 2013).

In 2012, the average number of hours worked by full time employed persons per week in the EU-28 was 41.6 for the main job and 12.2 for the second job (see Table 1). However, the proportions of employed persons with a second job may vary a lot between countries. Greece was ranked highest, at 43.8 hours, for the average hours worked by full-time employed persons in the main job, followed by Austria (43.5), the United Kingdom (42.8), Portugal (42.6), Poland (42.3), the Czech Republic and Cyprus (both 42.1). The lowest figures were reported in Denmark (38.8), with Ireland and Lithuania also recording averages below 40 hours. For second jobs, Hungary came top with 19.1 hours, followed by Greece with 17.8 hours, and Latvia and Ireland with 17.2. At the other end of the scale was Germany, with 8.3 hours per week.

Another indicator reflecting work-life balance and thus potentially impinging on quality of life is the proportion of employees usually working at night. In 2012, an average of 6.5 % of employed people aged 15-74 in the EU-28 usually worked at night (see Figure 9). The distribution across Member States varied widely, between 16.2 % in Slovakia to 1.5 % in Croatia. The proportion was above the EU-28 average in only 10 Member States: Slovakia, Malta, Germany, Ireland, the Netherlands, Finland, Slovenia, Italy, France and Hungary.

Health and safety at work

An important indicator of quality of employment is the rate of accidents at work. This is measured by the number of work accidents recorded per 100 000 employees in the previous 12 months, standardised according to the structure of the economy, and is an indication of the extent to which health and safety standards are upheld in the workplace. The following data refers to fatal accidents, which are better recorded due to the severity, and therefore more easily comparable across Member States.

In 2010, the average EU-27 incidence rate of fatal accidents at work was 2.6, down from 3.2 in 2008 (see Figure 9). Incidence rates were much higher in Cyprus (6.7), Romania and Austria (both 6.4), with trends varying: a slight increase in Cyprus (from 6.6 in 2008), a significant drop in Romania (from 9.8) and a substantial increase in Austria (from 4.7). The Netherlands, Germany and Finland were the Member States with the lowest incidence of work-related accidents in 2010, with rates ranging from 1.6 in the Netherlands and Germany to 1.9 in Finland. As compared with 2008, these rates were slightly higher in Finland (up from 1.5) and lower in Germany and the Netherlands (down from 2.4 and 2.7) respectively.

Job satisfaction

Empirical research suggests that job satisfaction is an important factor in and predictor of overall life satisfaction. For example, [6] showed that job satisfaction was the second most important predictor of overall life satisfaction among British workers (using BHPS data).

Evidence from the Third European Quality of Life Survey (2011), showed that European employees tend to be quite satisfied with their current job, since in nearly all countries average satisfaction is rated between about 7.0 and 8.0 (on a mean scale of 1 to 10), while in Denmark this level is as high as 8.4. Notable exceptions are Greece (6.6) and Bulgaria (6.8), but even there more people than not are satisfied with their current job. While job satisfaction depends on a multitude of factors (from the organisational, such as job content, responsibility, motivation, perception of fairness in the workplace, to remuneration), one can postulate a coexistence of low job satisfaction levels and other adverse factors. For example, most of the countries at the bottom of the job satisfaction scale are also characterised by high or quite high levels of unemployment (e.g. Greece, Spain, Italy and Bulgaria – see Figure 2), high levels of involuntary part-time employment (e.g. Bulgaria, Greece, Spain, Italy – see Figure 5), or higher than average numbers of actual hours of full-time work per week (Greece, Portugal – see Table 1). On the other hand, job satisfaction does not seem to be linked to the proportion of low wage earners. By contrast, Denmark and Finland exhibit very high job satisfaction levels and low ratings for all the adverse factors referred to above.


The quantitative and qualitative aspects of employment are complementary factors as regards quality of life. Detailed 2012 data show wide variation across and within Member States and over time, and both positive and negative developments. Average employment had fallen since 2007, which can be considered a negative development for quality of life. Unemployment is often unevenly distributed across categories of the labour force (age, educational attainment), but also across countries. The younger and less educated are affected more, sometimes with large variations across countries. However, these are also the groups on whose subjective well-being unemployment apparently has the least adverse effect.

On average, the proportion of low-wage earners increased in the EU-27 from 2006. Younger and older people are more likely to belong to that category, as are those with low educational qualifications (though rates vary across Member States). On a positive note, there were on average fewer fatal work accidents than in 2006.

Data sources and availability

In the context of ‘quality of life’, ‘productive or main activity’ covers quantitative and qualitative aspects of employment, and the main activity of those not in employment (for which indicators need to be developed).

  • Data on the quantity (or lack of) employment are provided by indicators on unemployment (unemployment rate and long-term unemployment rate) and underemployment (number of people living in households with very low work intensity, or in involuntary part-time employment). Most of the data on the quantitative aspects of employment come from the European Union Labour force survey (EU LFS), a continuous household survey carried out in all EU Member States, and EFTA (except Liechtenstein) and candidate countries.
  • Quality of employment data relate to income and benefits (percentage of low-wage earners, derived from the Structure of earnings survey (SES)), health and safety at work (work-related accidents, health problems and exposure to hazardous factors; from European statistics on accidents at work (ESAW)), work-life balance (average number of usual hours of work per week in main job or percentage of employees working more than the ILO/OECD threshold level of 49 hours, employees working unsocial hours, and satisfaction with commuting time) and the prevalence of temporary contracts. Assessment of quality of employment is under development and will cover: satisfaction with current work (under development in SILC 2013, currently from the European quality of life survey – EQLS), how possible it is to influence the content and order of tasks (under development in LFS 2015), and assessment of the relationships with colleagues and supervisors.


Paid work, but also unpaid main activities such as domestic work, affect quality of life also besides the income or utility generated, because they are an important determinant of personal identity and provide opportunities for social interaction. Apart from mere access to employment (i.e. the quantitative aspect), the quality of paid work is especially important, since it relates to personal dignity. Hence, ‘addressing the quality of jobs and employment conditions’ and the aspect is covered in the Guidelines for the Employment Policies of the Member States (Council Decision 2010/707/EU).

See also

Further Eurostat information

Main tables

LFS main indicators (t_lfsi)
Employment - LFS adjusted series (t_lfsi_emp)
LFS series - Detailed annual survey results (t_lfsa)
Employment rate, by highest level of education attained (tsdec430)
LFS series -Specific topics (t_lfst)
Employment rate of the age group 15-64 by NUTS 2 regions (tgs00007)
Employment rate of the age group 20-64 by NUTS 2 regions (tgs00102)
Employment rate of the age group 55-64 by NUTS 2 regions (tgs00054)
Average gross annual earnings in industry and services, by sex (tps00175)


LFS main indicators (lfsi)
Population, activity and inactivity - LFS adjusted series (lfsi_act)
Employment - LFS adjusted series (lfsi_emp)
LFS series - Detailed quarterly survey results (from 1998) (lfsq)
Employment - LFS series (lfsq_emp)
Employment rates - LFS series (lfsq_emprt)
LFS series - Detailed annual survey results (lfsa)
Employment - LFS series (lfsa_emp)
Employment rates - LFS series (lfsa_emprt)

Accidents at work (ESAW, 2008 onwards) (hsw_acc_work)
Structure of earnings survey - main indicators (earn_ses_pub)

Dedicated section

Source data for tables, figures and maps (MS Excel)

External links


  1. The effects of low-pay and unemployment on psychological well-being: A logistic regression approach,Theodossiou, I. (1998), Journal of Health Economics, 17, 85–104
  2. Is utility related to employment status? Employment, unemployment, labor market policies and subjective well-being among Swedish youth, Korpi T. (1997), Labour Economics, 4(2), 125–147
  3. Why Are the Unemployed So Unhappy? Evidence from Panel Data. Economica, Winkelmann, L. and Winkelmann, R. (1998, Economica, 65(257), 1–15)
  4. Unhappiness and Unemployment, Clark, A. and Oswald, A. (1994), The Economic Journal, 104 (424), 648–659
  5. Subjective quality of life of young Europeans. Feeling happy but who knows why?, Pichler, F. (2006) Social Indicators Research, 75, 419–444
  6. Happiness Economics: A New Road to Measuring and Comparing Happiness. Foundations and Trends in Microeconomics, Van Praag, B.M.S. and Ferrer-i-Carbonell, A. (2010), 6 (1), 1–97.