Asia-Europe Meeting (ASEM) - a statistical portrait - labour market

Data from April and May 2016. No planned update.

In 2015 the gender gap in employment was smaller in New Zealand, Cambodia, Mongolia, the Russian Federation and Vietnam than in the EU-28.
The unemployment rate was higher in the EU-28 than in Norway and Asian ASEM countries in 2015.
Unemployment rate by sex, 2015 (1)
Source: Eurostat (une_rt_a) and the International Labour Organisation (ILOSTAT)

This article is part of a Asia-Europe Meeting (ASEM) — A statistical portrait based on Eurostat’s publication Asia-Europe Meeting (ASEM) — A statistical portrait.

It focuses on labour market data about the European Union (EU), Norway and Switzerland in comparison with 21 Asian ASEM partners and covers key indicators concerning the labour force, employment, earnings, and unemployment.

The use of the term European ASEM partners in this article refers to the 28 Member States of the EU, Norway and Switzerland. The use of the term Asian ASEM partners in this article refers to the 10 members of the Association of Southeast Asian Nations (ASEAN) and the 11 remaining ASEM partners referred to as Northeast and South Asia (NESA).

Full article

Labour force

The labour force — also referred to as the workforce — is made up of economically active persons, in other words people who are employed or unemployed. The activity rate is the share of economically active persons in the working-age population, while the employment rate is the share of employed persons in the working-age population. The difference between the two rates reflects the level of unemployment relative to the working-age population. There are many reasons for low activity rates, including a large proportion of the working-age population that is still studying, in early retirement, or not available for employment through long-term sickness, invalidity or caring for family members.

Table 1 shows the activity and employment rates for all ASEM partners with a further analysis by sex: activity and employment rates for men in 2015 were consistently higher than those for women in each partner. The female activity rate among European ASEM partners and ASEAN members in 2015 was in a range between 50 % and 80 %, while for NESA the range was wider, with rates falling closer to one third in Bangladesh (2013 data) and one quarter in India (2014 data) and Pakistan (2010 data); it should be noted that there are differences in the age coverage for all three of these countries. Female employment rates were particularly high in Vietnam and Cambodia (both 2014 data).

Table 1a: Activity and employment rates, persons aged 15–64, 2015
(% of persons aged 15–64)
Source: Eurostat (lfsi_emp_a)
Table 1b: Activity and employment rates, persons aged 15–64, 2015
(% of persons aged 15–64)
Source: Eurostat (lfsi_emp_a)

Employment and earnings

The difference between male and female employment rates is shown in Figure 1. Among the European ASEM partners the largest differences were in Malta, Italy, Greece, Romania and the Czech Republic: for the EU-28 as a whole the difference in 2015 was 10.5 percentage points. Among the Asian ASEM partners gender differences were generally greater, as only New Zealand, Cambodia, Mongolia, the Russian Federation and Vietnam (all 2014 data, except for New Zealand) reported gender differences that were smaller than the EU-28 average. The biggest gender gaps were observed for Bangladesh, India and Pakistan, all of which reported particularly low employment rates for women.

Figure 1: Employment rates by sex, persons aged 15–64, 2015 (1)
(% of persons aged 15–64)
Source: Eurostat (lfsi_emp_a) and the International Labour Organisation (ILOSTAT)

The working status of persons in employment varied substantially between the ASEM partners as can be seen from Figure 2 which presents data for the EU-28 (for 2015) and a selection of Asian ASEM partners (mainly for 2014). The Russian Federation had a particularly high proportion of paid employees and consequently fewer self-employed persons — referred to as employers (if having paid employees) or own-account workers — and family workers. Several of the Asian ASEM partners shown in Figure 2 had much lower shares of paid employees: in Indonesia, Thailand, Cambodia and Vietnam less than half of the total workforce were employees. In Cambodia, the share of own-account workers was around 50 %, while in Vietnam the proportion of contributing family workers was more than one fifth.

Figure 2: Analysis of working status of those in employment, EU-28 and selected ASEM partners, 2014
Source: Eurostat (lfsa_egaps) and the International Labour Organisation (ILOSTAT)

Comparing earnings between countries can be complicated by a number of issues, not least the fact that a conversion to a common currency using market exchange rates does not reflect the differences in purchasing power between countries. Other comparability issues relate to the accounting nature (whether gross or net of taxes and social security contributions), the type of workers or jobs covered (full-time or not, nationals or all residents, main job or also secondary jobs) and the type of employers (public or private sector). In 2010, average monthly gross earnings in the EU-28 were EUR 2 324, a level that was surpassed among the other ASEM partners in Norway and Switzerland, as well as in New Zealand in 2014 (see Figure 3).

Figure 3: Mean monthly gross earnings of employees, 2010 or 2014, (1)
Source: Eurostat (earn_ses10_19) and (ert_bil_eur_a), the International Labour Organisation (ILOSTAT) and the United Nations Statistics Division (National Accounts Main Aggregates Database)


Unemployed persons are those without work, but actively searching work. The unemployment rate is calculated as the number of unemployed persons as a proportion of the labour force.

Just prior to the financial and economic crisis — around 2006 and 2007 — falling unemployment rates could be clearly seen in all of the economies shown in Figure 4, except for China. By 2009, this situation had reversed in the EU-28, the Russian Federation, Japan and the Republic of Korea, although the unemployment rate continued to fall in Indonesia. As the unemployment rate for the EU-28 continued to climb through to 2013 (after which it fell back), the rates for most of the other economies returned to a downward path in 2010 or 2011. Throughout the period under consideration, the unemployment rate remained relatively low and stable in China and to a lesser extent in Japan and the Republic of Korea.

Figure 4: Unemployment rates, EU-28 and selected Asian ASEM partners, 2005–15
(unemployed persons aged 15 and over as a % of the labour force)
Source: Eurostat (une_rt_a) and the International Labour Organisation (ILOSTAT)

Unemployment rates were below the EU-28 average (9.3 % for men and 9.5 % for women) in Norway, as well as in all of the Asian ASEM partners. In most ASEM partners, regardless of whether they were European or Asian, male and female unemployment rates were quite similar. The main exceptions in 2015 were Greece, Bangladesh (2013 data), Pakistan and India (2014 data) where female rates were notably higher and Ireland where male rates were clearly higher.

Figure 5: Unemployment rates, analysis by sex, 2015 (1)
Source: Eurostat (une_rt_a) and the International Labour Organisation (ILOSTAT)

In 2013, all ASEM partners except for Kazakhstan had higher youth unemployment rates (for persons aged 15–24) than their unemployment rates for the total labour force, as can be seen in Figure 6. It should be remembered that these rates are calculated as a percentage of the labour force (not the population) and many people between the ages of 15 and 24 years may be outside of the labour force, for example studying or travelling.

Figure 6: Youth and total unemployment rates, 2015 (1)
(unemployed persons as a % of the labour force)
Source: Eurostat (une_rt_a) and the International Labour Organisation (ILOSTAT)

The youth unemployment rate in the EU-28 stood at 20.3 % in 2015, which was around 2.2 times as high as the overall EU-28 unemployment rate. Youth unemployment rates were more than three times as high as overall unemployment rates in Italy and Romania. More than one quarter of the labour force aged 15–24 was without work in a group of southern and eastern EU Member States covering Greece, Spain, Croatia, Italy, Cyprus, Portugal and Slovakia. Indonesia reported a youth unemployment rate of 21.6 % (2013 data), while none of the other Asian ASEM partners (for which data are available) reported rates above 20 %.

The likelihood that a person faces the risk of unemployment often depends on their level of education. Figure 7 provides information for the EU-28 and a selection of Asian ASEM partners, comparing unemployment rates for persons according to their highest level of educational attainment: note that rates are not shown for all levels of education.

The EU-28, Australia, Kazakhstan, Mongolia and the Russian Federation displayed a similar pattern, with lower unemployment rates for those persons with higher levels of educational attainment. A similar situation was apparent in Indonesia, Singapore and Bangladesh as their lowest unemployment rates were among those persons having completed the first stage of tertiary education, although unemployment rates for persons having completed upper secondary education were higher than for those having completed at most lower secondary education.

The reverse pattern was displayed for Malaysia, Thailand and Vietnam, as unemployment rates rose as a function of people completing higher levels of education; note that the unemployment rates in these three countries were below 5 % for all three levels of educational attainment.

Figure 7: Unemployment rates by highest completed level of education, EU-28 and selected Asian ASEM partners, 2014 or 2015 (1)
(unemployed persons as a % of the labour force)
Source: Eurostat (lfsa_urgaed) and the International Labour Organisation (ILOSTAT)

Source data for tables and graphs

Data sources

The indicators presented are often compiled according to international — sometimes global — standards. Although most data are based on international concepts and definitions there may be certain discrepancies in the methods used to compile the data.

All of the indicators presented for the EU (and its Member States), Norway and Switzerland have been drawn from Eurobase, Eurostat’s online database.

For the Asian ASEM partners and their aggregates (ASEAN and NESA), the data presented have been extracted from a range of international sources, namely the World Bank, the United Nations Statistics Division and the International Labour Organisation (ILO).

For many of the indicators, multiple international statistical sources are available, each with their own policies and practices concerning data management (for example, concerning data validation, the correction of errors, the estimation of missing data, and the frequency of updating). In general, attempts have been made to use only one source for each indicator in order to provide a comparable analysis between the partners.

Aggregates for ASEM, the European ASEM partners and the Asian ASEM partners have been compiled from the data for individual partners as indicated above. As such, they may combine data from Eurostat and international sources.


The labour market reflects the supply of labour by individuals and demand from businesses and other employers. Workers offer labour in return for remuneration (pay). Labour market indicators concern the levels of various types of employment and unemployment, as well as information concerning labour costs and earnings.

The economically active population is also known as the labour force; it is composed of employed and unemployed persons. Employed persons include employees, the self-employed (employers and own-account workers) and family workers (persons who help another member of the family to run a farm, shop or other form of business). Economically inactive persons are neither employed nor unemployed, for example because they are studying, retired, unable to participate in the labour force or choose not to be a part of the workforce.

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Structure of earnings survey 2010 (earn_ses2010)
Monthly earnings (earn_ses10_mo)
Mean monthly earnings by sex, economic activity and collective pay agreement (earn_ses10_19)
LFS main indicators (lfsi)
Employment and activity - LFS adjusted series (lfsi_emp)
Employment (main characteristics and rates) - annual averages (lfsi_emp_a)
Unemployment - LFS adjusted series (une)
Unemployment rate by sex and age - annual average, % (une_rt_a)
LFS series - Detailed annual survey results (lfsa)
Employment - LFS series (lfsa_emp)
Employment by sex, age and professional status (1 000) (lfsa_egaps)
Total unemployment - LFS series (lfsa_unemp)
Unemployment rates by sex, age and educational attainment level (%) (lfsa_urgaed)