Indicator A3. How does educational attainment affect participation in the labour market?

Educational attainment and employment rates are strongly correlated. Upper secondary or post-secondary non-tertiary education is often seen as the minimum educational attainment for successful labour-market participation for most individuals (OECD, 2021[3]). There is a large increase in employment rates among 25-64 year-olds with upper secondary or post-secondary non-tertiary attainment compared to those with below upper secondary attainment. On average, only 58% of individuals with below upper secondary attainment are employed in OECD countries, but 75% of individuals with upper secondary or post-secondary non-tertiary attainment are employed. The employment rate among those with tertiary attainment is even higher, at 85%, but the difference in employment rates between upper secondary or post-secondary non-tertiary and tertiary attainment is smaller than the difference between below upper secondary and upper secondary or post-secondary non-tertiary attainment (Table A3.1).

There continues to be a strong relationship between labour-market participation and educational attainment that holds whether it is measured by employment rates, unemployment rates or inactivity rates. This relationship exists in nearly all OECD and partner countries with available data. It is very rare to find a country where a subpopulation with lower educational attainment has higher labour-market participation rates than a subpopulation with higher educational attainment Table A3.2 and Table A3.4). This positive relationship has been stable over the decades, despite the strong increase in attainment levels across the OECD (OECD, 2022[4])

While the link between educational attainment and employment rates holds for men and for women, it is particularly strong for women. Among 25-34 year-olds, in 2021, just 43% of women with below upper secondary attainment are employed, compared to 82% of those with tertiary attainment. These figures are 69% and 88% for men. The large gender difference among younger adults with below upper secondary attainment are unlikely to be solely due to employability. More likely, they are related to the persistence of traditional gender roles. Women who expect to stay home to take care of a family instead of pursuing a career have less incentive to obtain a formal education and are therefore more likely to have low educational attainment. This is reflected in inactivity rates for younger women with below upper secondary attainment that are on average more than twice as high as for men and resulting low employment rates across the OECD (Table A3.2 and (OECD, 2021[5])).

Educational attainment has increased strongly among younger adults in all OECD and partner countries with comparable data. On average across OECD countries, about 27% of 25-34 year-olds had completed a tertiary qualification in 2000 and this share increased to 48% in 2021 (see Indicator A1). The increase in attainment levels is a response to a changing labour market, in which skills are becoming ever more important and business are struggling to fill specialised positions. However, it is also putting pressure on workers who find that their qualifications, which were valuable not long ago, are no longer sufficient to compete against better qualified candidates (Lauder and Mayhew, 2020[6]).

Educational attainment and employment rates are positively correlated across different levels of tertiary attainment. Individuals aged 25-64 with a doctoral or equivalent degree have the highest employment rates of all ISCED attainment levels in all OECD countries except in Luxembourg and New Zealand. Likewise, the employment rate of individuals with a master’s or equivalent degree is higher than the employment rate of those with a bachelor’s or equivalent degree as their highest level of attainment everywhere except New Zealand. On average, individuals with a master’s or equivalent degree are 5 percentage points more likely to be employed than individuals with a bachelor’s or equivalent degree. The difference in employment rates persists throughout adults’ working life in most OECD countries. So, although master's graduates are more likely to have work experience than bachelor's graduates, their higher employment rates are not simply due to them finding employment after graduating more easily than those with a bachelor's or equivalent degree (Figure A3.2 and Table A3.1).

On average across the OECD, 25-34 year-old graduates from short-cycle tertiary programmes have almost the same employment rates as those with a bachelor’s or equivalent degree. However, this average hides large variations across countries. In some countries, short-cycle tertiary graduates have higher employment rates than those with bachelor’s or master’s or equivalent degrees, while in others they have lower rates. As short-cycle tertiary programmes aim to provide professional skills, often combined with an implicit promise of an easier transition into the labour market, these data suggest that there are differences in the effectiveness of such programmes (Figure A3.2).

At the other end of the tertiary attainment spectrum, the differences in employment rates across countries are much smaller. People with a doctoral or equivalent degree have the highest employment rate of any educational attainment level in almost all OECD countries. On average across the OECD, 93% of all 25-64 year-olds with a doctoral or equivalent degree are employed, and there are only four countries where it is below 90% (Estonia, New Zealand, Spain and the United States). In Hungary, an impressive 99% of adults with a doctoral or equivalent degree are in employment (Table A3.1).

Employment rates for adults with tertiary attainment are high across all fields of study. Overall, the science, technology, engineering and mathematics (STEM) fields have the strongest employment outcomes. Within these fields, employment rates are highest for people who studied ICT; on average 90% of adults with a tertiary ICT degree are in employment in OECD countries. Similarly, the average employment rate of graduates in engineering, manufacturing and construction is very high at 89%. Education, a field of special relevance for many countries, has an average employment rate that is somewhat lower, but still high at 85%. Arts and humanities, social sciences, journalism and information is the broad field of study with the lowest employment rates among tertiary-educated 25-64 year-olds, at an average of 83%. To put this into perspective, the employment rate of individuals with tertiary attainment is still about 10 percentage points higher than that of their peers with upper secondary or post-secondary non-tertiary attainment on average across the OECD. This shows that tertiary attainment provides labour-market benefits even in fields of study that mostly do not directly train students for a specified career (Figure A3.1 and Table A3.3).

While the differences in employment rates between fields of study are small, they are very consistent across OECD countries. For example, employment rates for adults with tertiary attainment in ICT are as high as or higher than for those with tertiary attainment in arts and humanities and social sciences, journalism and information in all OECD countries. Within the STEM fields, graduates in natural sciences, mathematics and statistics tend to have lower employment rates than other STEM fields in almost all countries. The gaps are especially large in Chile, the Czech Republic, Mexico and Portugal, where employment rates are on average approximately 10 percentage points lower than in other STEM fields (Table A3.3).

No internationally comparable data on employment rates by field of study exist for below tertiary attainment levels across OECD countries. However, evidence suggest that occupation has an important effect on employment rates of low-skilled workers (Autor and Dorn, 2013[7]). Many countries have shortages of workers with below tertiary attainment levels in some sectors even if overall unemployment rates of those with these attainment levels is high. Thus, field of study is also likely to have a considerable influence on employment prospects also for workers with below tertiary attainment.

On average, across OECD and partner countries with subnational data on labour-force status, there is more regional variation in employment rates among those with lower levels of educational attainment. For example, in Australia, employments rates for 25-64 year-olds adults with below upper secondary attainment range from 54% (in Canberra), to 63% (in Western Australia), compared with a range of 82% (in Tasmania) to 89% (in Northern Territory) for adults with tertiary attainment. Despite the concentration of economic activity in the capital city regions, in most countries, these regions do not generally have the highest employment rates. However, for tertiary-educated adults, the employment rate in the capital city region does tend to be slightly higher than the unweighted average of all regions in a country. In Greece, for example, the employment rate for adults with tertiary attainment in the capital city region of Attica is about 3 percentage points higher than the unweighted average of all Greece’s regions (OECD, 2022[8])

Between 2000 and 2021, tertiary attainment rates among 25-34 year-olds increased from 27% to 48% on average across OECD countries with available trend data (see Indicator A1). Despite this large increase, there are few signs that the labour-market benefits of a tertiary degree are diminishing. Among 25-34 year-olds, the average gap in unemployment rates between those with tertiary attainment and those with lower levels of attainment is almost exactly the same in 2021 as it was in 2000. In aggregate across the OECD, the labour market has absorbed a growing number of tertiary-educated workers without any noticeable effect on their unemployment rates (Figure A3.3).

Tertiary attainment also provides strong protection against the effects of economic crises. Unemployment increased strongly in the aftermath of the 2008 financial crisis for those with below upper secondary attainment, and to a lesser degree, also for those with upper secondary or post-secondary non-tertiary attainment. In contrast, the impact on tertiary-educated 25-34 year-olds was much smaller. A similar pattern can also be observed during the COVID-19 pandemic. While unemployment rates increased in 2020 for the three aggregate levels of educational attainment, the increase was much smaller for tertiary-educated younger adults than for those with lower attainment levels. In 2021, unemployment rates for tertiary-educated younger adults started to decline again, while they continued to grow for those with below upper secondary attainment and remained constant for those with upper secondary or post-secondary non-tertiary attainment (Figure A3.3).

While the data clearly suggest that increasing tertiary attainment has positive labour-market effects, two important caveats apply. First, aggregate trends across the OECD cannot rule out that, in some countries, the share of population with tertiary attainment is higher than optimal given labour-market conditions. Any conclusive analysis in this respect would not only have to consider the effects that increasing tertiary attainment has on new graduates, but also the consequences it has on the existing workforce. Second, the data do not imply that pursuing tertiary attainment is always the best choice at the individual level. For some people, upper secondary or post-secondary non-tertiary education leads to better career prospects and more fulfilling jobs than tertiary degrees. In contrast, there is little doubt that the decrease in the population with below upper secondary attainment has been a universally positive trend that should be further supported. The differences in socio-economic outcomes that are documented throughout Chapter A of this report are too large to make it plausible that any OECD country would be better off with a greater share of individuals with below upper secondary attainment.

Long-term unemployment is a particularly damaging form of unemployment. It has severe negative consequences on the physical and mental well-being of the unemployed and their families. Moreover, the longer unemployment lasts, the harder it becomes to find a new job. Skills atrophy when they are not used and many employers are reluctant to hire the long-term unemployed even if they meet their requirements. These difficulties are aggravated by the fact that when the long-term unemployed do find a new job, they tend to be offered lower wages than those who have been unemployed for a shorter time (Abraham et al., 2016[12]). Due to these consequences, public policy needs to make particular efforts to prevent long-term unemployment.

Higher educational attainment is also effective in reducing the risk of long-term unemployment. On average, 31% of unemployed tertiary-educated adults have been unemployed for over 12 months, compared to 35% of those with upper secondary or post-secondary non-tertiary attainment and 40% for those with below upper secondary attainment. Indeed, these figures understate the differences in the total number of long-term unemployed because they do not take into account the fact that individuals with greater educational attainment have much lower unemployment rates in the first place (Table A3.5).

This pattern of lower long-term unemployment rates among those with higher educational attainment holds in almost all OECD countries. The countries where the share of long-term unemployed is higher among tertiary-educated unemployed adults than those with lower attainment tend to have per capita GDP levels that are well below the OECD average. This might be due to weaker unemployment protection schemes in these countries, forcing poorer unemployed adults, with lower attainment levels, to find a job more urgently than their wealthier peers with higher attainment levels. The only country with above-average per capita GDP where long-term unemployment is higher among tertiary-educated unemployed adults is the United States, another country with weaker unemployment protection schemes than many other OECD countries (Figure A3.5).

While unemployment receives most public attention, the economic inactivity rate – the share of people who are neither working nor actively looking for a job – is another important measure of labour-market participation. The inactive population includes people who are caring for a family or are unable to work for health reasons, but also people who were unemployed and have given up looking for a job. Thus, long-term unemployment might eventually turn into inactivity, meaning people disappear from the unemployment statistics while still suffering from its harmful consequences.

The societal costs of inactivity among individuals with tertiary attainment are especially high. Governments spend large sums to educate people to tertiary level (see Chapter C). While economic considerations are not the only reason for public spending on tertiary education, such spending is only sustainable if it creates a return in the form of higher tax revenues. Moreover, inactivity among tertiary-educated individuals removes their skills from the workforce, which also has an indirect impact on those with lower attainment levels as high-skilled employment tends to have positive spillover effects on low-skilled employment (Mazzolari and Ragusa, 2013[13]).

There are large difference among countries in the inactivity rates of tertiary-educated 25-34 year-olds across OECD countries. On average, in 2021, 10% of younger adults with tertiary attainment are not in the labour force, but in Lithuania the share is half that, at 5%, while in the Czech Republic and Italy it is more than twice the OECD average. (Figure A3.6).

Among 25-34 year-olds with upper secondary or post-secondary non-tertiary attainment, in 2021, average inactivity rates are 17%, rising to 32% for those with below upper secondary attainment across OECD countries. Notably, these rates have remained largely constant during the COVID-19 pandemic, suggesting that the feared shift towards higher inactivity rates has not materialised in most countries. While there are some countries that experienced an increase in inactivity rates, more countries experienced a decrease in inactivity rates among tertiary-educated adults from 2019 to 2021. In some countries, such as Hungary and the Slovak Republic, this decrease in inactivity rates among tertiary-educated younger adults has been substantial (over 5 percentage points) (Figure A3.6 and Table A3.4).

Labour force (active population) is the total number of employed and unemployed persons, in accordance with the definition in the Labour Force Survey.

Age groups: 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.

Employed individuals are those who, during the survey reference week, were either working for pay or profit for at least one hour or had a job but were temporarily not at work. The employment rate refers to the number of persons in employment as a percentage of the population.

Fields of study are categorised according to the ISCED Fields of education and training (ISCED-F 2013). See the Reader’s Guide for full listing of the ISCED fields used in this report.

Inactive individuals are those who, during the survey reference week, were outside the labour force and classified neither as employed nor as unemployed. Individuals enrolled in education are also considered as inactive if they are not looking for a job. The inactivity rate refers to inactive persons as a percentage of the population (i.e. the number of inactive people is divided by the number of the population of the same age group).

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 the textbox. The levels of education are defined as follows: below upper secondary corresponds to levels 0, 1, 2 and 3C short programmes; upper secondary or post-secondary non-tertiary corresponds to levels 3 and 4; and tertiary corresponds to levels 5B, 5A and 6. ISCED 5A (tertiary-type A) consists of largely theory-based programmes designed to provide sufficient qualifications for entry to advanced research programmes and professions with high skill requirements, such as medicine, dentistry or architecture. The duration is at least three years full time, although usually four or more years. These programmes are not exclusively offered at universities, and not all programmes nationally recognised as university programmes fulfil the criteria to be classified as tertiary-type A. These programmes include second-degree programmes, such as the American master’s degree. ISCED 5B consists of programmes that are typically shorter than those of tertiary-type A and focus on practical, technical or occupational skills for direct entry into the labour market, although some theoretical foundations may be covered. They have a minimum duration of two years full-time equivalent at the tertiary level. ISCED 6 consists of programmes that lead directly to the award of an advanced research qualification (e.g. PhD). The theoretical duration of these programmes is three years, full time, in most countries (for a cumulative total of at least seven years full-time equivalent at the tertiary level), although the actual enrolment time is typically longer. Programmes are devoted to advanced study and original research.

Qualification mismatch: For the analysis in the textbox, an overqualified worker is defined as a job holder who has attained an education at ISCED 5A or 6 while holding a job that needs only ISCED 3 or less. An underqualified worker is defined as a job holder who has attained ISCED 3 or below while holding a job that needs ISCED 5A or 6.

Unemployed individuals are those who, during the survey reference week, were without work, actively seeking employment and currently available to start work. The unemployment rate refers to unemployed persons as a percentage of the labour force (i.e. the number of unemployed people is divided by the sum of employed and unemployed people).

For information on methodology, see Indicator A1.

Please see the OECD Handbook for Internationally Comparative Education Statistics (OECD, 2018[14]) for more information and Annex 3 for country-specific notes (https://www.oecd.org/education/education-at-a-glance/EAG2022_X3-A.pdf).

The distribution of unemployment by its duration in Table A3.5 does not take into account unemployed adults who reported unknown duration of unemployment. The share of adults who have been unemployed for at least 3 months but less than 12 months refer to the share of those who have been unemployed for less than 12 months in Argentina, Australia, Colombia, Finland, Portugal, Switzerland and Türkiye.

The qualification mismatch presented in Box A3.1 does not reflect misalignments between the field of study of the worker and what is needed for the job. The definitions of overqualification can vary across different studies on the topic. The question asked by the Survey of Adult Skills on job requirements is the following: “Still talking about your current job: If applying today, what would be the usual qualifications, if any, that someone would need to get this type of job?”. The analysis focuses on the comparison between ISCED 3 or below with ISCED 5A or 6 and does not look at the situation for ISCED 5B. This decision is driven by the blurred boundary between ISCED 5B and ISCED 5A or 6 and it also takes into account the fact that the ISCED 4 level is not well defined in the labour market.

For information on sources, see Indicator A1.

Data on subnational regions for selected indicators are available in the OECD Regional Statistics (database) (OECD, 2022[8])

References

[12] Abraham, K. et al. (2016), “The consequences of long-term unemployment: Evidence from linked survey and administrative data”, NBER Working Papers, No. 22665, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w22665.

[1] Arntz, M., T. Gregory and U. Zierahn (2016), “The risk of automation for jobs in OECD countries: A comparative analysis”, OECD Social, Employment and Migration Working Papers, No. 189, OECD Publishing, Paris, https://doi.org/10.1787/5jlz9h56dvq7-en.

[7] Autor, D. and D. Dorn (2013), “The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market”, American Economic Review, Vol. 103/5, pp. 1553-1597, https://doi.org/10.1257/aer.103.5.1553.

[6] Lauder, H. and K. Mayhew (2020), “Higher education and the labour market: An introduction”, Oxford Review of Education, Vol. 46/1, pp. 1-9, https://doi.org/10.1080/03054985.2019.1699714.

[13] Mazzolari, F. and G. Ragusa (2013), “Spillovers from High-Skill Consumption to Low-Skill Labor Markets”, Review of Economics and Statistics, Vol. 95/1, pp. 74-86, https://doi.org/10.1162/rest_a_00234.

[4] OECD (2022), Education at a Glance Database - Educational attainment and labour-force status, http://stats.oecd.org/Index.aspx?datasetcode=EAG_NEAC (accessed on 20 July 2022).

[8] OECD (2022), OECD Regional Database - Education, https://stats.oecd.org/Index.aspx?DataSetCode=REGION_EDUCAT (accessed on 20 July 2022).

[3] OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/b35a14e5-en.

[5] OECD (2021), Education at a Glance Database - Education and earnings, OECD, http://stats.oecd.org/Index.aspx?datasetcode=EAG_EARNINGS.

[2] OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris, https://doi.org/10.1787/9ee00155-en.

[10] OECD (2018), Education at a Glance 2018: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/eag-2018-en.

[14] 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 (2013), OECD Skills Outlook 2013: First Results from the Survey of Adult Skills, OECD Publishing, Paris, https://doi.org/10.1787/9789264204256-en.

[11] Verhaest, D. and R. Van Der Velden (2013), “Cross-country differences in graduate overeducation”, European Sociological Review, Vol. 29/3, https://doi.org/10.1093/esr/jcs044.

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