On average across OECD countries, 25-64 year-old adults with a tertiary degree earn 54% more than those with only upper secondary education, while those with below upper secondary education earn 22% less.
Across all levels of educational attainment, the gender gap in earnings persists, and a large gender gap in earnings is seen between male and female full-time workers with tertiary education: across OECD countries, tertiary-educated women earn only 74% as much as tertiary-educated men.
Countries with a lower share of people with low educational attainment tend to enjoy lower income inequality. Income inequality is largest in countries with a high share of people without upper secondary education, such as Brazil, Costa Rica and Mexico, and smallest in countries with a low share of people without upper secondary education, such as the Czech Republic and the Slovak Republic.
Education at a Glance 2018
Indicator A4. What are the earnings advantages from education?
Figure A4.1. Trends in women’s earnings as a percentage of men’s earnings for full-time workers with tertiary education (2005, 2016)
1. Earnings net of income tax.
2. Year of reference differs from 2016. Refer to the source table for details.
Countries are ranked in descending order of the earnings of 25-64 year-old women as a percentage of men’s earnings in 2016.
Source: OECD (2018), Table 4.3 and Education at a Glance Database, http://stats.oecd.org/. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Context
Higher levels of education usually translate into better employment opportunities (see Indicator A3) and higher earnings. While people with higher qualifications are generally better placed to see their earnings strongly increase over time, those without upper secondary education (who usually have lower earnings at the start of their career) tend to see only a slight increase of their earnings with age (see Indicator A6 in Education at a Glance 2017 (OECD, 2017[1])). Hence, the potential for higher earnings and faster earnings progression can be an important incentive for individuals to pursue education and training. It may also be one of the decisive factors in their choice of field of study at tertiary level.
A number of factors other than education also play a role in individuals’ earnings. In many countries, earnings are systematically lower for women than men across all levels of educational attainment. This may be related to gender differences in the sectors where they work and the types of occupation (OECD, 2016[2]). Variations in earnings also reflect other factors, including the demand for skills in the labour market, the supply of workers and their skills, the minimum wage and other labour-market laws, and structures and practices (such as the strength of labour unions, the coverage of collective-bargaining agreements and the quality of working environments). These factors also contribute to differences in the distribution of earnings. In some countries, earnings vary little, while in other countries there are large earnings disparities, leading to wide inequalities.
With the recent increase in migration flows to OECD countries, the labour-market situation of foreign-born adults stimulates the public debate. According to the International Migration Outlook 2017 (OECD, 2017[3]), 13% of the total population in OECD countries are foreign-born. The size and the characteristics of this group vary across countries, and it is important to analyse these elements to better understand the composition of a country’s population. Data from the International Migration Outlook 2017 show that in 2015, 11% of the permanent migration flow was under the work category, 33% under the free-movement category, 32% under the family category and 13% under the humanitarian category. Migration Policy Debates (OECD, 2014[4]) shows that there is evidence of the positive social and economic returns to migration. Overall, foreign-born adults largely contribute to increasing the workforce, and they generally contribute more in taxes and social contributions than they receive in benefits.
Other findings
Across countries, the likelihood of earning more than the median increases with educational attainment. On average across OECD countries, two out of three tertiary-educated adults earn more than the median of all employed people, including both full-time and part-time earners, while only one out of four adults without upper secondary education do so.
In most of countries with available data, the gender gap between the earnings of men and women with tertiary education working full time has decreased between 2005 and 2016. The decrease is 5 or more percentage points in Brazil, the Netherlands and New Zealand.
In Belgium, Chile, Colombia, France, Germany, Luxembourg, Slovenia, Switzerland and the United States, the earnings of foreign-born workers with tertiary education are at the same level or even higher than the earnings of their native-born peers.
Analysis
Differences in earnings between women and men, by educational attainment
Women do not earn as much as men in any OECD and partner countries. Across OECD countries, tertiary-educated women working full time earn only 74% of the earnings of tertiary-educated men. This gender gap of 26% in earnings is slightly higher than the gap for adults with below upper secondary and for adults with upper secondary or post-secondary non-tertiary education (both 22%) (Figure A4.1 and Table A4.1).
There is a high variation in the earnings level of women working full time compared to that of men. Tertiary-educated women earn 65% of men's earnings in Brazil, Chile, and Israel and 80% or more in Belgium, Costa Rica, Latvia, Luxembourg, Slovenia, Spain, Sweden and Turkey. Costa Rica is the country where the earning of tertiary-educated women are closest to men’s earnings, but they are still 7% lower (Figure A4.1).
As women are more likely to work part time than men, the gender gap in the average earnings of workers (including full-time and part-time earners) is even larger (OECD, 2016[5]). Across OECD countries, 24% of women aged 25-64 and 17% of men in the same age group work part time or part year (OECD, 2018[6]). On average, among those with tertiary education, female workers in full-time or part-time work earn only 68% of the earnings of tertiary-educated men across OECD countries. The gender gap among women with an upper secondary education or those with below upper secondary education is about the same as among those with tertiary education (both around 68% (OECD, 2018[6])).
Reasons for the gender gap include gender stereotyping, social conventions and discrimination against women (OECD, 2017[7]), but also differences between men and women in the choice of fields of study. Men are more likely than women to study in fields associated with higher earnings, such as engineering, manufacturing and construction, or science, mathematics and computing, while a higher share of women enrol in fields associated with lower earnings, including teacher training and education science, and humanities, languages and arts (see Indicator A6 in Education at a Glance 2016, (OECD, 2016[5])). Other reasons may relate to difficulties in combining a professional career with household and family responsibilities. To manage these different commitments, women are more likely to seek less competitive career paths and greater flexibility at work, leading to lower earnings than men with the same educational attainment (OECD, 2016[2]).
In recent years, awareness of the differences in pay of men and women has increased. Many countries have introduced new national policies to reduce disparities in earnings between men and women. Some countries have put in place concrete measures, such as pay transparency, to foster equity in pay between men and women (OECD, 2017[7]). In most of the countries with available data, the gender gap between the earnings of men and women with tertiary education has decreased between 2005 and 2016 (Figure A4.1).
Relative earnings, by educational attainment
On average across OECD countries, adults (age 25-64) without upper secondary education earn about 20% less for part-time or full-time employment than those with upper secondary education, while those with a tertiary degree have an earnings advantage of about 55% (Table A4.1).
The relative earnings disadvantages for adults without an upper secondary qualification are generally smaller than the earnings advantages of the tertiary-educated. In Austria, Brazil, Chile, Mexico and the Slovak Republic, adults without upper secondary education earn about 35% less for part-time or full-time work than adults with upper secondary education. The earnings disadvantage represents about 40% for those without an upper secondary qualification in Brazil and Mexico (the highest earnings disadvantage across OECD and partner countries), but 15% or less in Australia, Estonia, Finland, Latvia, Lithuania and New Zealand (Table A4.1).
Having a tertiary degree carries a considerable earnings advantage in most OECD and partner countries. The relative earnings for full-time and part-time workers are largest in Brazil, where adults with a tertiary education earn 150% more than adults with an upper secondary education. In Chile, Colombia, Costa Rica, Hungary and Mexico, tertiary-educated adults earn about twice as much as their peers with lower educational attainment (Table A4.1). In all of these countries, the share of adults with tertiary education is among the lowest in OECD and partner countries (less than 25%), which partly explains the large earnings advantage of tertiary-educated workers (see Indicator A6 in (OECD, 2017[1])).
In some countries, the relative earnings are below the OECD average even though the share of tertiary-educated people is large (see Indicator A1). For example, in Australia, Denmark, Estonia, New Zealand and Norway, where about 40% of adults are tertiary-educated, the earnings advantage from a tertiary degree is only about 30%, and in Sweden, with a similar share of tertiary-educated people, it is just 15% (Table A4.1). However, tertiary-educated people have among the highest employment rates in these countries (see Indicator A3).
Distribution of earnings, by educational attainment
Data on the distribution of earnings among groups with different levels of education show the degree to which earnings centre around the country median. “Median earnings” refer to earnings of all workers, without adjusting for differences in hours worked.
Across OECD and partner countries, the likelihood of earning more than the median increases with educational attainment. On average across OECD countries, 68% of tertiary-educated adults earn more than the median of all employed adults, including both full-time and part-time earners, while only 26% of adults without upper secondary education do so. In Brazil, Chile, Colombia, Costa Rica, Hungary, Mexico and Portugal, more than 80% of tertiary-educated adults earn more than the median. With the exception of Colombia, Hungary and Portugal, most of these adults earn more than twice the median. The strongly skewed earnings distribution signals income inequality, which may affect the social cohesion of communities (Figure A4.2 and Table A4.2, and see the section below on income inequality and the share of adults without upper secondary education).
Figure A4.2. Percentage of adults earning more than the median, by educational attainment (2016)
1. Year of reference differs from 2016. Refer to the source table for details.
2. Earnings net of income tax.
3. Data refer to full-time, full-year earners only.
Countries are ranked in descending order of the percentage of 25-64 year-olds with tertiary education earning more than the median.
Source: OECD (2018), Table A4.2. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
In contrast, on average across OECD countries, only 26% of adults without upper secondary education earn more than the median. In Italy, New Zealand and Portugal, at least 35% of adults without upper secondary education earn more than the median earnings. The share of workers without upper secondary education earning more than twice the median is only 3% on average across OECD countries. However, in Brazil, Canada, Estonia, Mexico, Portugal and Spain, 5% or more of workers without upper secondary education reach this earnings level, suggesting that factors other than educational attainment play an important role in high remuneration in these countries (Figure A4.2 and Table A4.2).
Among adults with upper secondary or post-secondary non-tertiary education, the shares of those earning more than the median earnings in a country are between the shares for those with tertiary and below upper secondary education. On average, 43% of adults with upper secondary or post-secondary non-tertiary education earn more than the median earnings across OECD countries. In Brazil, Costa Rica, Colombia, Italy, Mexico and Portugal, the share exceeds 50%. In most of these countries, the share of adults without upper secondary education is more than double the OECD average of 15%, which partly explains the higher share of workers with above-median earnings (Figure A4.2 and see Table A1.2).
Income inequality and the share of adults without upper secondary education
Over the past few decades, income inequality has risen in OECD countries. Rising income inequality has a significant impact on economic growth, as it reduces the capacity of the poorer population to invest in their own skills and education. More equal societies tend to be able to provide better education opportunities to their population and cultivate the conditions for inclusive economic growth (OECD, 2015[8]).
One common approach to measure income inequality is the ratio of the disposable income of the 90th decile to the 10th decile of the population aged 18-65 (the P90/P10 decile ratio). As shown in Figure A4.3, in Costa Rica, the per capita income of an individual at the top decile of the income distribution is ten times higher than that of an individual at the bottom decile, indicated by a P90/P10 ratio of 10. In terms of income inequality, Costa Rica is followed by Brazil, Chile, Estonia, Greece, Israel, Lithuania, Mexico, Spain, Turkey and the United States, where the P90/P10 ratio exceeds 5. The lowest income inequality can be found in the Czech Republic, Denmark, Iceland and the Slovak Republic (P90/P10 ratio of 3) (Figure A4.3 and (OECD, 2018[9])).
Figure A4.3. Percentage of 25-64 year-olds without upper secondary education and income inequality (2015)
Note: The P90/P10 decile ratio is the ratio of the upper bound value of the ninth decile (i.e. the 10% of people with highest income) to that of the upper bound value of the first decile. The income distribution is measured with regard to the disposable income of the population aged 18-65.
1. Year of reference 2014.
Source: OECD (2018), Education at a Glance Database and OECD Income Distribution database (IDD), http://stats.oecd.org/. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
When comparing P90/P10 decile income ratios across OECD and partner countries with the shares of adults without upper secondary education in their population, it seems that countries with a lower share of people without upper secondary education tend to enjoy lower income inequality. Income inequality is largest in countries with a high share of people without upper secondary education, such as Brazil, Costa Rica and Mexico, and lowest in countries with a small share of people without upper secondary education, such as the Czech Republic and the Slovak Republic. Although Figure A.4.3 suggests a relatively strong linear relationship, this correlation weakens when removing Brazil and Costa Rica, the countries with the largest income inequality (Figure A4.3).
Differences in earnings between native-born and foreign-born workers, by educational attainment
Foreign-born adults have more difficulty finding a job than their native-born peers, as they face various problems, such as recognition of credentials obtained abroad, lack of skills needed, language difficulties or discrimination when looking for work. Therefore, foreign-born workers (full-time workers) are more likely to accept any job they can get, which affects their level of earnings compared to their native-born peers (OECD, 2017[3]) (FRA, 2017[10]).
In most OECD and partner countries, earnings of foreign-born adults working full time are lower than those of their native-born peers, across educational attainment levels.
In many countries, foreign-born workers with below upper secondary education earn less than their native-born peers. This is especially true in Estonia, New Zealand, Spain and Sweden, where the earnings gap is about 20% or more. The exceptions, where foreign-born workers without upper secondary education earn more than native-born peers, are Germany (18%) and Switzerland (6%) (Figure A4.4).
Foreign-born workers with upper secondary or post-secondary education also face a disadvantage in earnings compared to native-born workers. The earnings gap between foreign-born and native-born workers with upper secondary or post-secondary education is 30 or more percentage points in Chile, Italy and Spain. In contrast, in France and Germany, earnings of foreign-born workers with upper secondary or post-secondary non-tertiary education are similar to those of native-born workers with the same educational attainment, and in Colombia, foreign-born workers earn about 25% more than their native-born peers (Figure A4.4).
Figure A4.4. Earnings of foreign-born workers as a percentage of earnings of native-born full-time workers, by educational attainment (2016)
1. Year of reference differs from 2016. Refer to the source table for details.
2. Data refer to full-time and part-time workers.
3. Earnings net of income tax.
Countries are ranked in descending order of the earnings of tertiary-educated foreign-born workers as a percentage of earnings of tertiary-educated native-born workers.
Source: OECD (2018), Table A4.4. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
In Belgium, Chile, Colombia, France, Germany, Luxembourg, Slovenia, Switzerland and the United States, the earnings of foreign-born workers with tertiary education are at the same level or even higher than the earnings of their native-born peers. In Chile, foreign-born workers with tertiary education earn 30% more than native-born tertiary-educated adults, and in Colombia, the earnings advantage increases to about 125%. In contrast, in Estonia, Finland, Italy and Spain, foreign-born workers with tertiary education earn less than 80% of the earnings of their native-born peers (Figure A4.4).
There is a high variation in the earnings differences between native-born and foreign-born workers across countries and educational attainment levels. In Belgium, Chile, Colombia, Finland and the United States the earnings gap between educational attainment levels exceeds 20 percentage points. On the other hand, in Austria and Estonia, the difference in the earnings gap between foreign-born and native-born workers across educational attainment levels is low (less than 7 percentage points, Figure A4.4).
Box A4.1. Qualification match or mismatch and earnings
Based on data from the Survey of Adult Skills (PIAAC) (see Source section at the end of this indicator), this box explores the relationship between overqualification and underqualification and earnings. It complements Box A3.1 on qualification match or mismatch among workers, as it provides details on how qualification match or mismatch relates to earnings (see Indicator A3).
Earnings appear more closely related to job levels than to educational attainment (i.e. those working in a job requiring a tertiary degree earn similar wages independently of whether they are underqualified or well matched, but those with a tertiary degree working in a job requiring much lower qualification earn much less than well-matched workers). As shown in Figure A4.a, individuals with a qualification of upper secondary education (ISCED-97 level 3) or below working in a job needing a qualification of tertiary-type A or advanced research programmes (ISCED 5A or 6 degree) (i.e. underqualified workers) have a median earning of about USD 19 per hour, similar to well-matched workers in those jobs. In most countries no statistically significant differences can be observed between these two groups. Those holding an ISCED 5A or 6 degree working in a job needing ISCED level 3 or below (i.e. overqualified workers) have a median earning of about USD 11 per hour (Figure A4.a). The reasons for the qualification mismatch can vary across and within countries, but Box A3.1 demonstrates that those who are overqualified are likely to have lower numeracy skills. Overqualified people may be working in a job requiring lower skills than their education attainment level because they have not been able demonstrate sufficient skills to get a job at the level of their qualification (see Indicator A3).
There are differences across countries, but the patterns are fairly consistent. The largest gaps in median hourly earnings (over USD 10 per hour) between well-matched and overqualified workers are observed in Canada, Denmark, Germany, Ireland and the United States. The difference is particularly high in Canada (about USD 15 per hour), where workers with a degree at ISCED level 5A or 6 working in a job needing ISCED 3 or below earn less than half the median hourly earnings of those who are in a well-matched situation (Figure A4.a).
In contrast, in the Czech Republic, the difference in earnings between well-matched, overqualified and underqualified workers is not statistically significant. Earnings are generally low in the Czech Republic, Estonia, Greece and Turkey, but despite this low earnings level, overqualified workers are also likely to earn about half the earnings of well-matched workers. For example, in Turkey, well-matched workers with a degree at ISCED level 5A or 6 have median earnings of about USD 11 per hour, while those holding an ISCED 5A or 6 degree working in a job needing ISCED level 3 or below have median earnings of about USD 4 per hour. However, this is a limited issue, as the share of overqualified workers in Turkey (9%) is well below the average across countries that participated in the Survey of Adult Skills (PIAAC) (15%) (Figure A4.a and Table A3.a, available on line).
Data show that workers have to demonstrate skills commensurate with their formal level of qualification for employers to offer a salary they would expect with that level of qualification. The importance of skills is shown, in contrast, when underqualified workers have earnings surpassing their formal qualification, as employers recognise their actual skills rather than their formal qualifications. It is, therefore, important to assess the mismatch situation more closely, especially for the overqualified population who invested in their human capital and for whom society invested in their education, without fully developing skills rewarded in the labour market.
Figure A4.a. Median hourly earnings, by selected qualification match or mismatch among workers (2012 or 2015)
Note: Some data points are not displayed because there are too few observations to provide a reliable estimate. Data from the Survey of Adult Skills (PIAAC) are based on ISCED-97. See Definitions, Methodology and Source sections for more information.
1. The earnings difference between well-matched and underqualified workers is not statistically significant at 5%.
2. The earnings difference between overqualified and underqualified workers is not statistically significant at 5%.
3. Reference year is 2015; for all other countries and economies the reference year is 2012.
4. The earnings difference between well-matched and overqualified workers is not statistically significant at 5%.
* See note on data for the Russian Federation in the Source section.
Countries are ranked in descending order of the median hourly earnings of the population reporting that their educational attainment matches the attainment level needed for their job (well matched).
Source: OECD (2018), Table A.4a, available on line. See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Definitions
Adults refer to 25-64 year-olds.
Educational attainment refers to the highest level of education attained by a person.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
The previous classification, ISCED-97, is used for the analyses based on the Survey of Adult Skills (PIAAC) in Box A4.1. See Indicator A3 for the definition of the different education levels based on ISCED-97.
Qualification match/mismatch: See Indicator A3 for this definition.
Methodology
The analysis of relative earnings of the population with specific educational attainment (Table A4.1) includes full-time and part-time workers. The analysis of differences in earnings between men and women (Table A4.3) and the analysis of differences in earnings between native-born and foreign-born workers (Table A4.4) include full-time workers only. The analysis of the distribution of earnings includes full-time and part-time workers. It does not control for hours worked, although the number of hours worked is likely to influence earnings in general and the distribution in particular. For the definition of full-time earnings, countries were asked whether they had applied a self-designated full-time status or a threshold value of the typical number of hours worked per week.
Earnings data are based on an annual, monthly or weekly reference period, depending on the country. The length of the reference period for earnings also differs. Data on earnings are before income tax for most countries. Earnings of self-employed people are excluded for many countries and, in general, there is no simple and comparable method to separate earnings from employment and returns to capital invested in a business.
This indicator does not take into consideration the impact of effective income from free government services. Therefore, although incomes could be lower in some countries than in others, the state could be providing both free healthcare and free schooling.
The total average for earnings (men plus women) is not the simple average of the earnings figures for men and women. Instead it is the average based on earnings of the total population. This overall average weights the average earnings separately for men and women by the share of men and women with different levels of educational attainment.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[11]) for more information and Annex 3 for country-specific notes (http://dx.doi.org/10.1787/eag-2018-36-en).
For the methodology used in Box A4.1 please see the Methodology section in Indicator A7.
Lithuania was not an OECD member at the time of preparation of this publication. Accordingly, Lithuania does not appear in the list of OECD members and is not included in the zone aggregates.
Source
The indicator is based on the data collection on education and earnings by the OECD LSO (Labour Market and Social Outcomes of Learning) Network. The data collection takes account of earnings for individuals working full time full year, as well as part time or part year, during the reference period. This database contains data on dispersion of earnings from work and on student earnings versus non-student earnings. The source for most countries is national household surveys such as Labour Force Surveys (LFS), European Union Statistics on Income and Living Conditions (EU-SILC) or other dedicated surveys collecting data on earnings. About one fourth of countries use data from tax or other registers.
Data used in Box A4.1 are based on the OECD Programme for the International Assessment of Adult Competencies (the Survey of Adult Skills [PIAAC]).
Note regarding data from Israel
The statistical data for Israel are supplied by and are under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
Note regarding data from the Russian Federation in the Survey of Adult Skills (PIAAC)
The sample for the Russian Federation does not include the population of the Moscow municipal area. The data published, therefore, do not represent the entire resident population aged 16-65 in the Russian Federation but rather the population of the Russian Federation excluding the population residing in the Moscow municipal area. More detailed information regarding the data from the Russian Federation as well as that of other countries can be found in the Technical Report of the Survey of Adult Skills, Second Edition (OECD, 2016[12]).
References
[10] FRA (2017), Second European Union Minorities and Discrimination Survey: Main Results, FRA (European Union Agency for Fundamental Rights), Vienna, http://dx.doi.org/10.2811/268615.
[6] OECD (2018), Education at a Glance Database - Education and earnings, http://stats.oecd.org/Index.aspx?datasetcode=EAG_EARNINGS.
[11] OECD (2018), OECD Handbook for Internationally Comparative Education Statistics 2018: Concepts, Standards, Definitions and Classifications, OECD Publishing, Paris, https://doi.org/10.1787/9789264304444-en.
[9] OECD (2018), OECD Income Distribution database (IDD), http://stats.oecd.org/Index.aspx?DataSetCode=IDD (accessed on 31 May 2018).
[1] OECD (2017), Education at a Glance 2017: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2017-en.
[3] OECD (2017), International Migration Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2017-en.
[7] OECD (2017), The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264281318-en.
[5] OECD (2016), Education at a Glance 2016 : OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/eag-2016-en (accessed on 12 January 2018).
[2] OECD (2016), OECD Employment Outlook 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2016-en.
[12] OECD (2016), Technical Report of the Survey of Adult Skills (PIAAC), 2nd Edition, OECD, Paris, http://www.oecd.org/skills/piaac/PIAAC_Technical_Report_2nd_Edition_Full_Report.pdf.
[8] OECD (2015), In It Together: Why Less Inequality Benefits All, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264235120-en.
[4] OECD (2014), “Is migration good for the economy?”, Migration Policy Debates, https://www.oecd.org/migration/OECD%20Migration%20Policy%20Debates%20Numero%202.pdf (accessed on 05 February 2018).
Indicator A4 Tables
Table A4.1. Relative earnings of workers, by educational attainment (2016)
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2016)
Table A4.3. Differences in earnings between female and male full-time workers, by educational attainment and age group (2016)
Table A4.4. Differences in earnings between native- and foreign-born full-time workers, by educational attainment and age group (2016)
Cut-off date for the data: 18 July 2018. Any updates on data can be found on line at http://dx.doi.org/10.1787/eag-data-en. More breakdowns can be found at http://stats.oecd.org/, Education at a Glance Database.
Table A4.1. Relative earnings of workers, by educational attainment (2016)
25-64 year-olds with income from employment (full- and part-time workers); upper secondary education = 100
Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Index 100 refers to the combined ISCED levels 3 and 4 of the educational attainment levels in the ISCED 2011 classification.
3. Year of reference 2014.
4. Earnings net of income tax.
5. Year of reference 2012.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Table A4.2. Level of earnings relative to median earnings, by educational attainment (2016)
Median earnings from work for the 25-64 year-olds with earnings (full- and part-time workers) for all levels of education
Note: See Definitions and Methodology sections for more information. Data and more breakdowns are available at http://stats.oecd.org/, Education at a Glance Database.
1. Earnings net of income tax.
2. Year of reference 2015.
3. Year of reference 2014.
4. Year of reference 2012.
5. Data refer to full-time, full-year earners only.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Table A4.3. Differences in earnings between female and male full-time workers, by educational attainment and age group (2016)
Adults with income from employment (full-time workers), average annual earnings of women as a percentage of men’s earnings
Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Year of reference 2015.
2. Year of reference 2014.
3. Earnings net of income tax.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.
Table A4.4. Differences in earnings between native- and foreign-born full-time workers, by educational attainment and age group (2016)
Adults with income from employment (full-time workers), average annual earnings of foreign-born workers as a percentage of native-born workers’ earnings
Note: See Definitions and Methodology sections for more information. Data and more breakdowns available at http://stats.oecd.org/, Education at a Glance Database.
1. Earnings refer to full-time and part-time workers.
2. Year of reference 2015.
3. Year of reference 2014.
4. Earnings net of income tax.
Source: OECD (2018). See Source section for more information and Annex 3 for notes (http://dx.doi.org/10.1787/eag-2018-36-en).
Please refer to the Reader’s Guide for information concerning symbols for missing data and abbreviations.