Indicator A4. What are the earnings advantages from education?
Greater educational attainment yields better earnings and this holds true for higher levels of tertiary attainment in most countries. On average across the OECD, full-time full-year workers who attained short-cycle tertiary education earned 20% more than those with upper secondary attainment in 2020. This earnings advantage increases to 44% among those who attained a bachelor’s or equivalent qualification and to 88% among those with a master’s or doctoral or equivalent degree.
The earnings advantage for attaining at least a bachelor’s or equivalent degree increases with age, probably because of seniority at work. On average across OECD countries, 25-34 year-olds with at least a bachelor’s or equivalent degree and working full time and for the full year earn 39% more than their peers with upper secondary attainment, while 45-54 year-olds earn 75% more.
Among tertiary-educated workers, those with a medical or dental degree or with a degree in the science, technology, engineering and mathematics (STEM) fields enjoy the highest earnings advantages. Despite being essential during the COVID-19 pandemic, workers with a degree in nursing or associated health field receive one of the smallest wage premiums among the eight OECD countries with available data.
Context
Higher levels of education usually translate into better employment opportunities (see Indicator A3) and higher earnings. The potential to earn more over their careers can be an important incentive for individuals to pursue education and training.
More young adults hold a tertiary degree today than ever before (see Indicator A1), and the expansion of tertiary education is ongoing. In general, labour markets continue to absorb this increasing supply, but there are substantial differences in earnings by field of study among tertiary-educated workers. Apart from cultural biases, the earnings differences by field of study may signify that some sectors and some skills are more in demand than others. In an unpredictable and changing world, it is important that education provides young people with knowledge and skills that meet labour-market and societal needs.
Variations in earnings also reflect factors other than educational attainment. For instance, the gender pay gap persists regardless of level of educational attainment and field of study. In addition, in some countries with a relatively small tertiary-educated population, the distribution of earnings is more skewed towards tertiary-educated workers than in other countries, leading to wide inequalities that can be linked to issues of social mobility.
Other findings
In nearly all OECD and partner countries, there is persistent inequality in earnings between men and women. On average across the OECD, the gender pay gap is slightly wider among tertiary-educated workers, reflecting a more dispersed earnings distribution. In recent years, awareness of the differences in pay between men and women has risen, and the gap is tending to narrow in many OECD countries.
The likelihood of earning more than the overall median increases with educational attainment and the rise is even more striking for workers earning more than twice the overall median. Among OECD countries, the distribution of earnings among tertiary-educated workers are the most skewed in Chile, Costa Rica and Mexico.
In some countries, very large earning premiums associated with tertiary degrees may be connected to relatively high levels of income inequality, which in turn is reflected in greater demands for redistributive policies among adults without tertiary education.
Note
This indicator presents three types of relative earnings. The first uses the earnings of adults with below upper secondary attainment as a baseline, the second uses men’s earnings as a baseline and the third uses the earnings of adults with upper secondary attainment as a baseline. In all cases, given the focus on relative earnings, any increase or decrease in the results could reflect a change in the interest group (numerator) or in the baseline group (denominator). Individuals with zero and/or negative earnings are considered as earners and they are taken into consideration in the calculation of relative earnings. To measure how skewed an earnings distribution is, this indicator considers the degree to which earnings are centred around the overall country median among groups with different levels of educational attainment. Overall median earnings refer to the earnings of all workers, without adjusting for differences in hours worked. Individuals with negative earnings should also be taken into account in the calculation of the overall median earnings.
Relative earnings and educational attainment
Earnings advantages from education for all workers
Higher levels of educational attainment carry greater earnings advantages. On average across OECD countries, 25-64 year-old workers with upper secondary or post-secondary non-tertiary attainment earn 29% more than those with only below upper secondary attainment. This earnings premium ranges from below 10% in Estonia and Latvia to above 45% in Brazil, Colombia and Costa Rica (Figure A4.1).
The premium for completing a tertiary degree is much higher. Across the OECD, tertiary-educated workers earn twice as much as those with below upper secondary attainment. Country differences also widen when looking at the relative earnings associated with tertiary attainment. Tertiary-educated workers earn less than 50% more than those with below upper secondary education in Estonia and New Zealand, but the premium can be between twice and just under three times earnings in Brazil, Colombia, Chile and Costa Rica (Figure A4.1).
It is clear that higher educational attainment leads to better earnings, but interpreting relative earnings by educational attainment needs to be done with cautions. First, because earnings benefits are expressed in relative terms, greater educational attainment in countries with low earnings advantages can still provide relatively high absolute benefits. This is the case for the Netherlands and Switzerland, where relative earnings premiums are below the OECD average. However, because wage levels are high, the absolute differences between the earnings of workers with below upper secondary attainment and tertiary attainment in these two countries are among the five highest across the OECD (see Table X3.A4.4 from Annex 3 and Figure A4.1). Second, the relative supply and demand of tertiary-educated workers influences the earnings advantage from education in the labour market. Countries with very high relative earnings for tertiary attainment tend to have a smaller share of tertiary-educated individuals (see Indicator A1). Third, minimum wage laws, the strength of labour unions, the coverage of collective-bargaining agreements, the relative incidence of part-time and seasonal work, and the number of hours worked are likely to affect earnings. Box A4.1 also provides some insights on how adults without tertiary attainment perceive their earnings gap with tertiary-educated workers.
The analysis in this section has provided an overall picture of the earnings advantages from education and covers all adults with earnings from work. The rest of the analysis on relative earnings mainly focuses on full-time full-year workers to ensure better cross-country comparability.
Gender disparities in earnings for full-time full-year workers
Over the past decade, gains in educational attainment among women have contributed to a worldwide increase in their participation in the labour force (see Indicators A1 and A3). However, in nearly all OECD and partner countries, earnings inequality persists between men and women, with women not earning as much as men.
Although higher levels of educational attainment narrow gender differences in employment rates (see Indicator A3), the gender gap in earnings does not vary much across educational attainment levels. On average across OECD countries, tertiary-educated full-time full-year female workers in 2020 earned only 77% of their male counterparts' earnings, compared to 80% among those with upper secondary or post-secondary non-tertiary attainment, and 79% among those with below upper secondary attainment (Table A4.3). Costa Rica is the only exception where tertiary-educated women working full-time full-year earn slightly more than their male peers. As women are more likely to work part time and/or part year than men, the gender differences in earnings are wider among all workers than among full-time full-year workers (OECD, 2022[1]).
Differences in the choice of field of study between men and women are often considered to be one reason for the gender pay gap for those with a tertiary qualification. For example, men are more likely than women to study in the fields of science, technology, engineering and mathematics (STEM), which are associated with higher earnings, while a larger share of women study fields associated with relatively lower earnings, including education, and arts and humanities (see Indicator B4). However, even when comparing workers with a tertiary degree in the same field of study, women’s work is less well remunerated than men’s (OECD, 2022[1]).
Empirical research has found that, beyond social norms and gender stereotypes, the motherhood penalty seems to be an important contributor to wage differences between men and women in many OECD countries. On average across OECD countries, the wage gap between men and women is narrower for younger full-time full-year workers (25-34 year-olds) than their older peers, regardless of educational attainment (Table A4.3 and (OECD, 2022[1])). Many countries have introduced a mix of policies to bridge the gender pay gap, such as pay transparency laws, non-transferable paternity leave and reductions in the effective marginal tax rates for second earners (Ciminelli, Schwellnus and Stadler, 2021[2]). In recent years, wage differentials between men and women have tended to narrow across OECD countries (OECD, 2022[1]).
Relative earnings of tertiary-educated full-time full-year workers
By level of tertiary attainment
The earnings advantage of tertiary-educated workers varies considerably for different levels of tertiary attainment. Due to the large differences in earnings between tertiary-educated workers and those with below upper secondary attainment, the analysis in this section uses earnings for workers with upper secondary attainment as the baseline to better illustrate the relative position of each country.
In most OECD and partner countries, the earnings advantage tends to increase with the level of tertiary attainment. On average across OECD countries, full-time full-year workers with a short-cycle tertiary degree as their highest level of education earned 20% more than those with upper secondary attainment in 2020. The advantage increases to 44% among those with a bachelor’s or equivalent degree and to 88% among those with a master’s or doctoral or equivalent degree (Figure A4.2).
There are some exceptions to this general pattern. Estonia is the only country where full-time full-year workers who attained short-cycle tertiary education earn less than those with upper secondary attainment. However, it is noteworthy that no one has graduated with a short-cycle tertiary degree in Estonia since 2013/14. In Austria, Greece and Norway, the earnings of full-time full-year workers who attained a bachelor’s or equivalent qualification are lower than for those with short-cycle tertiary attainment (Figure A4.2).
By age group
The earnings advantage from higher levels of educational attainment tends to increase throughout a person’s working life. In some OECD countries, short-cycle tertiary education is often considered a stepping stone into further learning and holding a short-cycle tertiary degree as the highest level of educational attainment has become less common among younger generations (see Indicator A1 and (OECD, 2022[3])). The analysis in this section compares the earnings advantages across age groups and countries among adults with at least a bachelor’s or equivalent degree compared with adults with upper secondary attainment.
In most countries, earnings increase with age for workers with all levels of educational attainment, but the increase in pay is more pronounced among tertiary-educated workers (Annex 3, Tables X3.A4.4 and A4.5). On average across OECD countries, among full-time full-year workers, younger adults (25-34 year-olds) with at least a bachelor’s or equivalent degree earned 39% more than their peers with upper secondary attainment in 2020. Among 45-54 year-olds, this premium rises to 75% more. Latvia is the only country where younger adults enjoy a higher earnings advantage from at least a bachelor’s or equivalent degree than their older peers. For the other OECD countries, although earnings advantages increase with age, there are sizable differences among countries, ranging from less than 20 percentage points between these two age groups in Denmark, Greece and the United Kingdom to over 50 percentage points in Austria, Costa Rica and Slovenia, and more than 100 percentage points in Chile (Figure A4.3).
The larger earnings advantage for older age groups could be explained by their growing work experience and responsibilities (OECD, 2019[4]). Tertiary attainment is often a prerequisite for moving up the career ladder, and some workers may pursue a tertiary degree after starting their career (see Indicator A7). All these factors contribute to the increasing earnings advantages of tertiary-educated workers over time. Since these advantages are expressed in relative terms, it could also mean that the earnings advantage has fallen for younger generations with the increasing supply of tertiary-educated workers in the labour market. However, between 2013 and 2020, the earnings advantage for younger adults having at least a bachelor’s or equivalent degree has changed by less than 5 percentage points in most OECD countries with available trend data (OECD, 2022[1]). Although these data cover less than a decade, the wage differential in favour of older generations seems to relate more to their seniority at work.
By field of study
A tertiary degree yields better earnings, but there are substantial differences across fields of study. Among the 17 OECD countries with available data, the combined STEM fields (i.e. science, technology, engineering and mathematics) are most commonly associated with the highest earnings. Only in Austria, Costa Rica and Slovenia do the earnings associated with a tertiary degree in health and welfare exceed the earnings from STEM fields combined. In contrast, degrees in the fields of education and of arts and humanities (except languages), social sciences, journalism and information yield relatively low earnings (Figure A4.4 and Table A4.4).
Disaggregating earnings advantages by narrower fields of study helps to highlight the differences that may exist within a broader field. In the eight OECD countries with available data, although the differences in earnings among the individual STEM fields are quite small except in Luxembourg, there are large differences within the broad field of health and welfare. Full-time full-year workers with a medical or dental degree earn 50% more than those with a degree in nursing or associated health, except in Germany and Latvia. In Norway, workers with a tertiary degree in nursing or associated health fields even earn slightly less than workers with upper secondary attainment (all fields combined). The COVID-19 pandemic is challenging many countries’ health systems and has underscored the lack of healthcare workers. Despite their importance, compared to all other fields of study, the earnings advantage associated with a tertiary degree in nursing or associated health fields is in the bottom three among the eight OECD countries with available data (Table A4.4).
The high earnings associated with some fields of study may relate to a potential mismatch between the supply of current graduates and labour-market needs. With rapid digitalisation, the relatively high earnings associated with an information and communication technologies (ICT) degree may reflect the imbalance between strong labour-market demand for ICT workers and the very small share of graduates who studied this field (see Indicator A1). However, supply and demand could instead be better aligned in the labour market by exploring other types of skills that may be substitutes for an ICT degree. For example, using job posting data, a recent study suggests that tertiary-educated workers with an educational background in engineering or business management seem to have technical skills that are suitable for filling vacancies in some ICT occupations (Brüning and Mangeol, 2020[5]).
The earnings differences arising from greater educational attainment create incentives for students to spend their early adulthoods pursuing higher educational degrees. Over the past decades, these earnings advantages have widened due to technological process and globalisation in most developed countries. In 2020, on average across OECD countries, tertiary-educated adults working full time and full year earn 63% more than their peers without a tertiary degree (Figure A4.5). If individuals are aware about the existence of earnings differences by educational attainment, however, how do they perceive these differences?
The OECD Risks That Matter Survey (2020) asked respondents whether they thought governments should reduce income differences between the rich and the poor by collecting taxes and providing social benefits. On average across countries participating in this survey, 62% of respondents believe that governments should do more, or much more to reduce income inequality – the possible response options were “much less”, “less”, “about the same as now”, “more” and “much more”. Respondents could also choose “can’t choose” (OECD, 2021[6])
The results also reveal some differences by education level: on average, 65% of adults without any university-level education support more redistribution from the rich to the poor, compared to 61% of those with some university-level education (OECD, 2021[6]). Note that the education level mentioned here is not the same as the attainment levels used in the main analysis. Adults with some university-level education includes some who might not have completed it and therefore might not hold a tertiary degree.
Although income inequality is a broader concept than differences in earnings, labour income is still the main contributor to pre-tax income inequality (including differences in capital income) (OECD, 2012[7]). The notions of “rich” and “poor” used in the Risks that Matter Survey are conceptual and do not have definitions. Using the earnings differences between full-time full-year workers with and without tertiary attainment as a proxy for income inequality, Figure A4.5 shows that in general, a higher earnings premium from tertiary education is associated with greater support for more redistribution among adults without university-level education.
In Denmark and France, where the earnings premium of tertiary education is relatively low, adults without university-level education are among the least likely to reply that government should be doing more or much more to reduce income differences. Canada, Finland, Germany, the Netherlands, Norway and Switzerland also fit into this pattern, with relatively low earnings differences and less support for government intervention to reduce income gaps (Figure A4.5). These countries tend to already have relatively high levels of income redistribution and/or relatively low level of pre-tax income inequality, combined with relatively high earnings for workers without a tertiary degree (see Table X3.A4.4 from Annex 3 and (OECD, 2021[8])).
The opposite situation is observed in Chile, Israel, Lithuania, Mexico, Poland, Portugal, Slovenia and the Republic of Türkiye. In Chile, the earnings premium of tertiary education is the highest among all countries shown in the figure (exceeding 170%), and almost nine in ten adults without tertiary education would support more redistributive measures from their governments. This is probably related to the fact that Chile has the lowest level of income redistribution after government intervention among OECD countries (OECD, 2021[8]). The United States stands out for its relatively low level of support for more redistribution among non-tertiary educated adults despite relatively high earnings differentials (Figure A4.5). A 2019 survey in the United States reveals that other issues ((e.g. health care affordability, terrorism and gun violence) are rated as higher priorities than reducing income inequality (Pew Research Center, 2020[9]).
Share of working students, by age group
Some young adults combine education with some forms of employment, and they receive remuneration from work before graduation (see Indicator A2). On average across OECD countries, 40% of students aged between 15 and 24 have income from employment over a year. There are large variations across countries, ranging from less than 10% in Belgium and Luxembourg to over 70% in Canada, Costa Rica, Denmark, Mexico and Türkiye (OECD, 2022[1]).
The costs of staying in the education system is likely to increase with age and in all OECD countries with available data, 25-29 year-old students are more likely to have paid jobs than 15-24 year-old students. On average across the OECD, 67% of 25-29 year-old students receive income from employment. This may partly be because, as students get older, they may enrol in higher levels of tertiary education; in some countries, tuition fees are higher for master’s or doctoral or equivalent degrees than for lower tertiary programmes (see Indicator C5). It may also be the case that some 25-29 year-olds have already started working and are returning to education while continuing their careers. There is less cross-country variation in the share of working students among 25-29 year-olds than among 15-24 year-olds: the share of older students with income from employment ranges from 31% in Belgium to 90% in Norway (OECD, 2022[1]).
Distribution of earnings relative to the median, by educational attainment
Similar to relative earnings, the likelihood of earning more than the overall median increases with educational attainment. On average across OECD countries, 26% of workers with below upper secondary attainment earn more than the median, compared to 43% of those with upper secondary or post-secondary non-tertiary attainment. This share reaches 68% among workers with tertiary attainment (OECD, 2022[1]).
The differences are more considerable when looking at the share of workers earning more than twice the median. Across OECD countries, an average of 23% of tertiary-educated workers earn more than twice the median, compared to only 7% of those with upper secondary or post-secondary non-tertiary attainment and 3% of those with below upper secondary attainment (Table A4.2).
Among tertiary-educated workers, the distribution of earnings can vary considerably depending on the level of tertiary attainment. In nearly all OECD and partner countries, the share of workers earning more than twice the median increases at each level from short-cycle tertiary, to bachelor’s or equivalent and master’s or doctoral or equivalent degrees. On average across OECD countries, 13% of workers with a short-cycle tertiary degree earn more than twice the median. The share increases to 20% among those with a bachelor’s or equivalent degree and to 33% among those with a master’s or doctoral or equivalent degree (Figure A4.6).
In some countries, the earnings distribution is more skewed than in others. For example, in Chile, Costa Rica and Mexico, the share of tertiary-educated workers earning more than twice the median is at least twice the OECD average (e.g. at least 46% compared to the average of 23%) (Table A4.2). In these countries, the tertiary-educated share of the population is also much lower than the OECD average (see Indicator A1). A strongly skewed earnings distribution among tertiary-educated workers may signal barriers to pursuing higher levels of education among students with disadvantaged socio-economic background.
Adults refer to 25-64 year-olds; younger adults refer to 25-34 year-olds.
Educational attainment refers to the highest level of education successfully completed by an individual.
Fields of study are categorised according to the ISCED Fields of Education and Training (ISCED-F 2013). See the Reader’s Guide for a full listing of the ISCED fields used in this report and Annex 3 for more details.
Levels of education: See the Reader’s Guide at the beginning of this publication for a presentation of all ISCED 2011 levels.
Individuals with zero earnings refer to individuals who have earnings but the result of their business activities is exactly zero.
Individuals with negative earnings refer to individuals who reported deficit in business activities.
The analysis of relative earnings of the population with specific educational attainment and 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. The analysis of differences in earnings between men and women includes full-time workers only. For the definition of full-time earnings, countries were asked whether they had applied a self-designated full-time status or a threshold value for the typical number of hours worked per week.
Earnings data are based on an annual, monthly or weekly reference period, depending on the country. This Indicator presents annual data, and earnings data with a reference period shorter than a year are adjusted. Please refer to Table X3.A4.1 in the Annex 3 for more information on the adjustment methods. 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 health care and free schooling, for example.
Data presented at the country level are average earnings, but there can be significant variations for individuals. Data shown in Table A4.2, “Distribution of workers by educational attainment and level of earnings relative to the median earnings (2020)”, illustrate the earnings variations among individuals. Median earnings are for all adults with earnings from work, regardless of educational attainment.
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.
Category totals for fields of study may not be equivalent to the sum of the subcategories because some programmes cannot be classified into a specific subcategory but are included in the total. In addition, data on humanities (except languages), social sciences, journalism and information refers to the field social sciences, journalism and information only in Australia, Austria, Chile, Luxembourg and the United Kingdom.
In the earnings data, individuals with zero and/or negative earnings should be reported as earners. Individuals with negative earnings should also be taken into account in the calculation of the overall median earnings. However, data on individuals with zero and/or negative earnings are not available for all countries. Individuals with zero earnings are included for Belgium, Canada, Germany, Ireland, New Zealand, Norway, Sweden, Switzerland, Türkiye and the United States. Individuals with negative earnings are included for Belgium, Canada, Denmark, Italy, New Zealand, Norway, Spain, Sweden and the United States. Refer to the Definitions section for the definition of individuals with zero and negative earnings.
The shares of working students are not comparable with the values presented in Indicator A2, due to differences in the reference period, age group and the definition of student status. Please refer to Table X3.A4.2 for more information.
Please see the OECD Handbook for Internationally Comparative Education Statistics 2018 (OECD, 2018[10]) for more information and Annex 3 for country-specific notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf).
This indicator is based on the data collection on education and earnings by the OECD Labour Market and Social Outcomes of Learning Network (LSO Network). The data collection takes account of earnings for individuals working full time and 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, the European Union Statistics on Income and Living Conditions (EU-SILC), or other dedicated surveys collecting data on earnings. About one-quarter of countries use data from tax or other registers. Please see Annex 3 for country-specific notes on national sources (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf).
References
[5] Brüning, N. and P. Mangeol (2020), What skills do employers seek in graduates?: Using online job posting data to support policy and practice in higher education, OECD Publishing, Paris, https://doi.org/10.1787/bf533d35-en.
[2] Ciminelli, G., C. Schwellnus and B. Stadler (2021), Sticky floors or glass ceilings? The role of human capital, working time flexibility and discrimination in the gender wage gap, OECD Publishing, Paris, https://doi.org/10.1787/02ef3235-en.
[1] OECD (2022), Education at a Glance Database, OECD.Stat website, https://stats.oecd.org (accessed on 17 June 2022).
[3] OECD (2022), Pathways to Professions: Understanding Higher Vocational and Professional Tertiary Education Systems, OECD Reviews of Vocational Education and Training, OECD Publishing, Paris, https://doi.org/10.1787/a81152f4-en.
[8] OECD (2021), Government at a Glance 2021, OECD Publishing, Paris, https://doi.org/10.1787/1c258f55-en.
[6] OECD (2021), Main Findings from the 2020 Risks that Matter Survey, OECD Publishing, Paris, https://doi.org/10.1787/b9e85cf5-en.
[4] OECD (2019), Working Better with Age, Ageing and Employment Policies, OECD Publishing, Paris, https://doi.org/10.1787/c4d4f66a-en.
[10] 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.
[7] OECD (2012), Economic Policy Reforms 2012: Going for Growth, OECD Publishing, Paris, https://doi.org/10.1787/growth-2012-en.
[9] Pew Research Center (2020), Most Americans Say There is Too Much Income Inequality in the U.S. but Fewer Than Half Call it a Top Priority, Pew Research Center website, https://www.pewresearch.org/social-trends/2020/01/09/most-americans-say-there-is-too-much-economic-inequality-in-the-u-s-but-fewer-than-half-call-it-a-top-priority/ (accessed on 23 May 2022).
Cut-off date for the data: 17 June 2022. Any updates on data can be found on line at: https://doi.org/10.1787/eag-data-en. More breakdowns can also be found at http://stats.oecd.org, Education at a Glance Database.
Table A4.1. Relative earnings of workers, by educational attainment (2020) |
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25-64 year-olds with income from employment (full-time full-year workers); upper secondary attainment = 100 |
 |
Note: There are cross-country differences in the inclusion/exclusion of zero and negative earners. 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 differs from 2020: 2019 for Belgium, Canada, Finland, Ireland, Israel and Spain; 2018 for France, Greece, Italy, Lithuania and Mexico; 2017 for Chile. |
2. Index 100 refers to the combined ISCED levels 3 and 4 in the ISCED 2011 classification. See the Reader’s Guide for the list of ISCED levels. |
Source: OECD (2022). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf). Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations. |
Table A4.2. Distribution of workers by educational attainment and level of earnings relative to the median earnings (2020) |
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Median earnings from work for 25-64 year-olds with earnings (full- and part-time workers) for all levels of educational attainment |
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Note: There are cross-country differences in the inclusion/exclusion of zero and negative earners. For a given level of educational attainment, the figures by level of earnings relative to the median earnings may not add up to 100% because of missing data. See Definitions and Methodology sections for more information. Data and more breakdowns available at: http://stats.oecd.org/, Education at a Glance Database. |
2. Year of reference differs from 2020: 2019 for Canada, Finland, Ireland, Israel and Spain; 2018 for France, Greece, Italy, Lithuania and Mexico; 2017 for Chile. |
Source: OECD (2022). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf). Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations. |
Table A4.3. Women’s earnings as a percentage of men's earnings, by educational attainment and age group (2020) |
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Average earnings of adults with income from employment (full-time full-year workers) |
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Note: There are cross-country differences in the inclusion/exclusion of zero and negative earners. 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 differs from 2020: 2019 for Belgium, Canada, Finland, Ireland, Israel and Spain; 2018 for France, Greece, Italy, Lithuania and Mexico; 2017 for Chile. |
Source: OECD (2022). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf). Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations. |
Table A4.4. Relative earnings of tertiary-educated adults, by field of study (2020) |
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25-64 year-olds with income from employment (full-time full-year workers); upper secondary education (all fields) = 100 |
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Note: There are cross-country differences in the inclusion/exclusion of zero and negative earners. In addition, data on humanities (except languages), social sciences, journalism and information might refer to the broad field social sciences, journalism and information only. 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 differs from 2020: 2019 for Finland; 2017 for Chile and the United States. |
5. Arts and humanities, social sciences, journalism and information does not include the subfield of languages. |
6. Index 100 refers to combined ISCED levels 3 and 4 in the ISCED 2011 classification. See the Reader’s Guide for the list of ISCED levels. |
7. Data refer to bachelor’s degree field, even for those with additional tertiary degrees. |
Source: OECD (2022). See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf). Please refer to the Reader's Guide for information concerning symbols for missing data and abbreviations. |