SDG 8 - Decent work and economic growth (statistical annex)


Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all (statistical annex)

Data extracted in October 2017. Most recent data: Further Eurostat information, Main tables. Planned article update: September 2018.

This article provides an overview of statistical data on SDG 8 ‘decent work and economic growth’ in the European Union (EU). It is based on the set of EU SDG indicators for monitoring of progress towards the UN Sustainable Development Goals (SDGs) in an EU context.

This article is part of a set of statistical articles, which are based on the Eurostat publication ’ Sustainable development in the European Union — Monitoring report on progress towards the SDGs in an EU context (2017 edition)’. This report is the first edition of Eurostat’s future series of monitoring reports on sustainable development, which provide a quantitative assessment of progress of the EU towards the SDGs in an EU context.

Real gross domestic product (GDP) per capita

SDG 08 10 2001-2016.PNG

Although weakened by the effects of the economic crisis, real GDP per capita has been following an overall upward trend in the long and short term.

Figure 1: Real GDP per capita, EU-28, 1995–2016
(EUR per inhabitant)
Source: Eurostat online data code (sdg_08_10)
Figure 2: Real GDP per capita, growth rate, by country, 2001–2016 and 2011–2016
(percentage change on previous year)
Source: Eurostat online data code (sdg_08_10)

Gross domestic product (GDP) is a measure of economic activity and is commonly used as a proxy for developments in a country’s material living standards. It refers to the value of total final output of goods and services produced by an economy within a certain period of time. Figure 1 shows that based on GDP per capita Europeans have continued to enjoy rising living standards over recent decades, despite the effects of the economic crisis.

Although per capita GDP rebounded in the years after the severe economic slump (+ 1.1 % per year on average between 2009 and 2016), the economic recovery still seems to be fragile. In 2016, the EU had to cope with numerous challenges, including the lowest pace of global and trade growth since 2009, geopolitical tensions, terrorist attacks in several Member States, stressed banking sectors, the UK’s vote to leave the EU and a mounting backlash against globalisation [1].

Nevertheless, real GDP grew by 1.5 % in 2016 and is expected to grow continuously at a similar pace in 2017 and 2018. However, for a lasting economic upswing wages and investment need to rise more strongly. Over the past few years, private consumption has been the main growth driver. Yet, the temporary rise in consumer inflation is set to eat into the purchasing power of households. In addition, investment growth is not expected to rise as policy uncertainty, the modest medium to long-term demand outlook, and remaining deleveraging needs, continue to weigh on investment decisions [2].

In comparison, world’s GDP growth is projected to increase, from 3.0 % in 2016 to 3.7 % in 2018. In most major advanced economies, growth is projected to continue along its current modest path. In the United States GDP growth is projected to pick from 1.6 % in 2016 to 2.5 % in 2018, supported by an expected fiscal expansion, especially in 2018, despite higher long-term interest rates and continued headwinds from the stronger US dollar. In contrast, growth in China is expected to shrink from 6.7 % in 2016 to 6.3 % in 2018 as its economy undergoes necessary transitions, including shifting towards consumption and services, adjustment in several heavy industries, working off excess housing supply and ensuring credit developments are sustainable. Higher commodity prices and easing inflation are supporting a recovery from deep recessions in Brazil, Russia and some other commodity producers, although short-term supply restrictions will limit the positive impact of higher oil prices on production in some countries. Strong growth should continue in India over the next two years, helped by the implementation of key structural reforms and strong public sector wage growth [3].

Growth in per capita output has not been uniform among Member States and over the short term (2011 to 2016) it has ranged from 7.3 % per year in Ireland to – 1.6 % per year in Greece. These disparities result from different general economic conditions and production capacities as well as asymmetries in the size and nature of the economic shock. Some economies, particularly those that had accumulated large macroeconomic imbalances before 2008, have been more exposed to the effects of the crisis and experienced larger dips in 2008 and 2009 as well as in 2012 and 2013.

Total employment rate

SDG 08 30 2001-2016.PNG

The EU’s employment has risen in both the long and short terms but remains at a distance from the 75 % target set in the Europe 2020 strategy. But the target may still be met if the recovery in employment rates recorded from 2013 onwards can be maintained.

Figure 3: Total employment rate, EU-28, 2001–2016
(% of population aged 20 to 64)
Source: Eurostat online data code (sdg_08_30)
Figure 4: Total employment rate, by country, 2011 and 2016
(% of population aged 20 to 64)
Source: Eurostat online data code (sdg_08_30)

The employment rate is defined as the share of the population in employment. The data analysed here focus on the population aged 20 to 64 in order to monitor the Europe 2020 strategy target of raising employment rates among this age group to 75 % by 2020 [4]. Data presented in this section stem from the EU Labour Force Survey (EU-LFS).

Employment represents an essential cornerstone of socioeconomic development by fostering economic prosperity, social inclusion and quality of life. The economic recovery in the EU in the past few years has also been reflected in people’s ability to find a productive and paid job. Overall, the EU employment rate has increased in recent years. In 2016, 71.1 % of Europeans where employed which is beyond the pre-crisis level of 70.3 % in 2008. The onset of the economic crisis in 2008 pushed the EU off its path towards its employment target of 75 % by 2020. However, if the employment rate keeps increasing at the same pace recorded since 2013, the 2020 target may still be achieved.

People in their early twenties (age group 20–24) and late career paths (age group 55–64) are underrepresented in the job market. In 2016, 50.6 % of people aged 20 to 24 and 55.3 % of 55 to 64 year olds were employed. For the younger age group, it is plausible that their employment rate is below average as a considerable share is pursuing tertiary education. However, the employment rates for these two age groups have developed quite differently over the past decade. The prospects for young people aged 20 to 24 of finding a job has been most heavily affected by the economic crises, which has meant the employment rate for this group in 2016 was still more than 4 percentage points below their 2008 level of 54.8 % [5]. The reason for this development may be that new entrants into the labour market, who have limited work experience and are often employed through temporary and part-time contracts or pursue a traineeship, are more easily dismissed during weak economic cycles [6]. In contrast, the job situation of people in their late career (age group 55–64) was not affected by the economic slowdown and their employment rate actually increased by 9.7 percentage points between 2008 and 2016 [7]. This favourable trend could be linked to structural factors such as cohorts with higher educational attainment moving up the age pyramid but also to recent pension reforms, such as increasing the pensionable age, the age for early retirement and length of contribution, which had led to longer working lives [8].

In an increasingly knowledge-based economy, such as the EU is today, educational attainment is crucial for securing a job and adequate income. Indeed, in 2016 a person aged 20 to 64 living in Europe with tertiary education was much more successful in landing a job (employment rate of 83.4 %) compared to those with upper secondary or post-secondary non-tertiary education (employment rate of 71.6 %) and with lower secondary or lower education (employment rate of 53.6 %). While the gap between tertiary and upper secondary educational levels was relatively stable with a slight downwards trend over the period from 2002 (13.5 percentage points) to 2016 (11.8 percentage points), the gap between those with a tertiary education and those with lower secondary or less was widening (from 27.9 percentage points in 2002 to 29.8 percentage points in 2016) [9]. And despite the fact that women are increasingly well qualified and even out-performing men in terms of educational attainment (see also SDG 4 ‘Quality education’), the employment rates of women are lower than those for men. However, for all age groups, the gender employment gap (which is analysed in SDG 5 ‘Gender equality’) — the difference in employment rates between men and women — has been decreasing over time.

In 2014, the employment rate of people with disabilities at the European level was 23.8 percentage points lower compared to people without disabilities. About 48.7 % of people with disabilities were employed compared to 72.5 % of those without disabilities. For disabled women the rate was 45.7 %, while for disable men it was 52.3 %. The degree of disability is also an important factor affecting the employment rate. At the EU level, the employment rate of severely disabled people was 28.3 %, while for people with a moderate disability stood at 56.7 % in 2014 [10].

Country of origin can impact the labour market performance of individuals in the EU. Migrant workers from countries outside the EU not only tend to occupy low-skilled and insecure jobs with temporary contracts and poorer working conditions, they also show much lower employment rates than EU citizens [11]. Migrants were particularly affected by the economic crisis, being among the first to lose their jobs, therefore the gap between the average EU employment rates and those of non-EU citizens widened from 7.8 percentage points in 2008 to 14.5 percentage points in 2016 [12]. One explanation for the large variation in employment rates between EU citizens and third-country nationals might be the level of qualifications, with a large proportion of non-EU citizens being less highly educated. However, analysis shows this is not the norm and the share of third-country migrants with at least upper secondary education who work in low-skilled occupations is higher than for the native population. It should be considered that in many Member States a large share of non-EU citizens have migrated not for economic reasons but to join family members, for education and training or to seek international protection [13]. However, migration, especially economic migration, provides an opportunity for dealing with a shrinking labour force and potential skills shortages. Without migration the working-age population will shrink by 7 % in 2030 and by 27 % in 2060 compared with 2016 levels [14].

Employment rates among Member States ranged from 56.2 % to 81.2 % in 2016. Low employment levels were reported by countries from south-eastern Europe. Some of the best performing countries such as Sweden, Germany and the United Kingdom also recorded high regional employment rates [15].

Compared with the world’s other main economies, the EU employment rate of 66.6 % in 2016 for the age group 15 to 64 [16] was mid-range. In most non-EU G20 countries, the employment rate ranged between 74.3 % (Japan) and 61 % (Mexico). Three countries experienced lower levels in 2016, Saudi Arabia (52.5 %), India (49.9 %) and South Africa (43.7 %) [17].

Young people neither in employment nor in education and training

SDG 08 20 2001-2016.PNG

The rate of young people neither in employment nor in education or training has improved slightly since 2002. The trend has however not been continuous and most progress has occurred in recent years.

Figure 5: Young people not in employment and not in any education and training, EU-28, 2002–2016
(% of population aged 15 to 29)
Source: Eurostat online data code (sdg_08_20)
Figure 6 Young people not in employment and not in any education and training, by country, 2011 and 2016
(% of population aged 15 to 29)
Source: Eurostat online data code (sdg_08_20)

A considerable proportion of young people aged 15 to 29 in the EU are economically inactive. For some this is due to the pursuit of education and training. Others, however, have withdrawn from the labour market or are not entering it after leaving the education system. Those who struggle with the transition from education to work are captured by the indicator monitoring the rates of young people neither in employment nor in education and training (NEET rate). Data presented in this section stem from the EU Labour Force Survey (EU-LFS).

In 2016, 14.2 % of young people aged 15 to 29 in the EU were not employed and were not receiving further education or training. As shown in Figure 5 the long-term trend was heavily influenced by the economic crisis.

Nowadays, upper secondary education is considered the minimum level Europeans should attain before leaving the education and training system. Therefore, low educational attainment is one of the key determinates of young people entering the NEET category (see also article 4 ‘Quality education’). Other factors include having a disability or coming from a migrant background.

In 2016, 8.0 % of 15 to 29 year olds were inactive and neither in education nor training, which means more than half of NEETs were not looking for a job. Inactive NEETS have been stable around 8 % since 2002. So fluctuations in the NEET rate have been fully triggered by variations in unemployment. However, only a fraction of young people do not want to work (in 2016, only 4.7 % of 15 to 29 year olds were neither in education nor training and did not want to work). This indicates that nearly a quarter of NEETS would have liked to work but were not actively seeking employment or gave up looking for a job.

The EU total conceals very large variations in NEET rates between Member States, ranging from 6.3 % in the Netherlands to 24.3 % in Italy in 2016.

The differences in the NEET rate across Member States are also reflected in the distribution of NEET rates within countries. The highest regional NEET rates were mainly recorded in regions in Mediterranean and eastern European counties. At the other end of the scale, the lowest rates were observed mainly in regions from central and northern Europe [18].

Long-term unemployment rate

SDG 08 40 2001-2016.PNG

The long-term unemployment rate rose considerably after the onset of the economic crisis. However, it started to fall again in 2013 and in 2016 it returned to its 2005 level.

Figure 7: Long-term unemployment rate, EU-28, 2005–2016
(% of active population)
Source: Eurostat online data code (sdg_08_40)
Figure 8: Long-term unemployment rate, by country, 2011 and 2016
(% of active population)
Source: Eurostat online data code (sdg_08_40)

Long-term unemployment refers to people aged 15 to 74 who have been unemployed for 12 months or more. The long-term unemployed in the EU have about half the chance of finding employment compared to the short-term unemployed [19]. Data presented in this section stem from the EU Labour Force Survey (EU-LFS).

In 2016, 9.6 million people or 4 % of the active population in the EU were long-term unemployed. Since 2013, the long-term unemployment rate has dropped by 1.1 percentage points. The differences between men and women have disappeared over the past six years.

Long-term unemployment emerges as the main employment legacy of the crisis as the proportion of long-term unemployed among all unemployed rose from 36.9 % in 2008 to 46.4 % in 2016. Long-term unemployment usually follows strong changes in unemployment, but with some delay. Therefore, slight decreases in long-term unemployment only started being observed in 2014, after the start of the recovery in 2013 [20].

The risk of being long-term unemployed was highest for migrants from outside the EU (48.1 %). The lowest risk faced mobile EU citizens (43.1 %) while the rate for people living in their country of birth was 47.1 % in 2016 [21].

Compared with other main economies in the world the share of long-term unemployed among the EU’s unemployed is rather high. In most non-EU OECD countries, this value was between 0.4 % (Korea) and 57 % (South Africa) in 2015. Japan faced a share of 35.5 %, Australia of 23.5 % the US of 18.7 % and the share in Canada was 11.6 % [22].

In 2016, huge differences in long-term unemployment persisted among Member States, from 1.3 % of the active population in Sweden to 17.0 % in Greece. Roughly the same country patterns shown in Figure 8 were observed for the share of long-term unemployment in total unemployment in 2016. The shares ranged from 18.3 % in Sweden to 72 % in Greece [23].

Involuntary temporary employment

SDG 08 50 2001-2016.PNG

The overall share of employees working involuntarily on fixed-term contracts declined over the past decade but the share has risen again in the short term.

Figure 9: Involuntary temporary employment, EU-28, 2006–2016
(% of total employees)
Source: Eurostat online data code (sdg_08_50)
Figure 10: Involuntary temporary employment, by country, 2011 and 2016
(% of total employees)
Source: Eurostat online data code (sdg_08_50)

Involuntary temporary employment refers to employees working on fixed-term contracts because they were unable to find a permanent job, expressed as a share of total employees. Data presented in this section stem from the EU Labour Force Survey (EU-LFS).

In 2016, 13.3 % of employees aged 20 to 64 were working on a fixed-term contract in the EU. Temporary employment in the EU has been relatively stable at around 13 % since 2006, with a slight upward tendency [24]. However, many people are not employed on a fixed-term contract by choice. Two-thirds of those working on fixed-term contracts did so in 2016 because they could not find a permanent job.

It seems involuntary temporary employment declines with age. While 16.0 % of young employees aged 15 to 24 worked on fixed-term contracts involuntarily in 2016, the share nearly halved for the age group 25 to 49 (9.3 %) and fell to only 5.2 % for elder workers (50–64 years).

For all age groups the share of women employed involuntarily on a fixed-contract exceeded that of men. In 2016 the gender gap was around 1 percentage points for all age groups except the elderly (aged 50 to 64), there the difference was only 0.3 percentage points. Interestingly, the gender gaps have been relatively stable over the past decade. The gap only widened for the age group 15 to 24 from 0.2 percentage points in 2006 to 1.1 percentage points in 2016.

In 2016, the share of involuntary temporary employees among all employed people ranged from 0.8 % in Austria to 23.7 % in Spain. Because a similar country pattern as shown in Figure 10 can be seen for the usage of temporary contracts, these differences between Member States may be partly explained by the unequal spread of temporary contracts across the EU. In Poland 27.1 % of employed worked on a temporary contract, followed by Spain (25.8 %) and Portugal (21.8 %). On the other end of the scale less than 2 % of employees in Romania and Estonia worked on temporary terms in 2016.

People killed in accidents at work

SDG 08 60 2001-2016.PNG

Fatal accidents at work fell by 9 % between 2009 and 2014.

Figure 11: Fatal accidents at work, EU-28, 2008–2014
(number per 100 000 persons employed aged 25 to 64)
Source: Eurostat online data code (sdg_08_60)
Figure 12: Fatal accidents at work, by country, 2010 and 2015
(number per 100 000 persons employed aged 25 to 64)
Source: Eurostat online data code (sdg_08_60)

Fatal accidents at work are those occurring during the course of work and lead to the death of the victim within one year. The incidence rate refers to the number of accidents per 100 000 persons in employment. Data presented in this section are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)'. The national ESAW sources are the employers' declarations of accidents at work, either to the relevant insurance companies, the national social security system, labour inspections or similar national authorities. As an exception, accident data for the Netherlands are based on survey data.

The decline in fatal accidents at work, as shown in Figure 11, went hand in hand with falls in non-fatal accidents leading to at least four calendar days of absence, indicating improvement in working conditions in the EU. In fact there is a remarkable stable ratio between fatal and non-fatal accidents at work at EU level between all years. This holds although non-fatal accidents suffer in some Member States from high levels of under-reporting (meaning that accidents occur but are not reported to public authorities for various reasons). On average, there are about 1.2 fatal accidents for 1 000 non-fatal accidents at EU level.

When disaggregated by gender, the data reveal that in 2014 the incidence rate of fatal accidents is more than ten times higher for men than for women. One reason for this gap is that the incidence rates vary greatly between different economic activities and are higher for male-dominated economic activities, such as construction, transport and agriculture. Between 2009 and 2014, the decline in fatal accidents at work was considerably stronger for women than for men, and as a consequence the gender gap has widened.

The risk of fatal accidents rises with age. Workers aged 55 to 64 face the highest risk of fatal accidents.

In 2015, the rates of fatal incidents per 100 000 employed persons ranged from 0.50 in the Netherlands to 5.56 in Romania. However, the number of fatal accidents in smaller Member States is rather low and therefore the corresponding incidence rates can vary strongly from one year to the next. For example in Cyprus the rate decreased by 73.8 %, as a result of a drop from 18 cases in 2010 to 4 in 2015 [25].

See also

Further Eurostat information

Database

Socioeconomic Development

Dedicated section

Methodology

More detailed information on EU SDG indicators for monitoring of progress towards the UN Sustainable Development Goals (SDGs), such as indicator relevance, definitions, methodological notes, background and potential linkages, can be found in the introduction of the publication ’ Sustainable development in the European Union — Monitoring report on progress towards the SDGs in an EU context (2017 edition)’.

Notes

  1. European Commission (2017), European Economic Forecast Winter 2017, p. 1.
  2. European Commission (2017), European Economic Forecast Spring 2017, p. 1.
  3. OECD (2017), Economic Outlook, Volume 2017 Issue 1, p. 20 ff.
  4. In a majority of Member States 15 to 19 year olds are still in education or training and few are not seeking employment (even part-time). Therefore, the lower age limit of the Europe 2020 strategy’s employment target has been set at 20 years. The upper age limit for the employment rate is usually set to 64 years, taking into account statutory retirement ages across Europe.
  5. Source: Eurostat (online data code (lfsa_ergan)).
  6. European Commission (2016), European Semester Thematic Factsheet Youth Employment, p.1.
  7. Source: Eurostat (online data code (lfsa_ergan)).
  8. European Commission (2016), Employment and Social Developments in Europe 2015, p. 22.
  9. Source: Eurostat (online data code (tsdec430)).
  10. Academic Network of European Disability experts (2017), European comparative data on Europe 2020 & People with disabilities, p. 58 ff.
  11. European Commission (2016), Employment and Social Developments in Europe 2015, p. 177.
  12. Source: Eurostat (online data code (lfsa_ergan)).
  13. European Commission (2016), Employment and Social Developments in Europe 2015, p. 14.
  14. Source: Eurostat (online data codes (demo_pjan) and (proj_15npms)).
  15. Eurostat (2017), Eurostat regional yearbook 2017 p.97.
  16. International data for the age group 20 to 64 are not available, therefore the comparison with other main economies refers to the age group 15 to 64.
  17. Source: Eurostat (online data code (lfsi_emp_a)) and the International Labour Organisation (ILOSTAT).
  18. Eurostat (2017), Eurostat regional yearbook 2017 p.80.
  19. European Commission (2016), Employment and Social Developments in Europe 2015, p. 13.
  20. European Commission (2017), Employment and Social Developments in Europe 2017, p.29.
  21. Source: OECD.
  22. Source: Eurostat (online data code (lfsa_upgacob)).
  23. Source: Eurostat (online data code (une_ltu_a)).
  24. Source: Eurostat (online data code (lfsa_etpgan)).
  25. Source: Eurostat (online data code (hsw_mi01)).