Lithuania

  • Socio-economic status may significantly impact students’ participation in education, particularly at levels of education that rely, in many countries, most heavily on private expenditure, such as early childhood education and care and tertiary education. This is less the case in Lithuania: private sources accounted for 13% of total expenditure in pre-primary institutions, lower than the OECD average of 17%. At tertiary level, 28% of expenditure comes from private sources in Lithuania, compared to 30% on average across OECD countries.

  • Tuition fees in public institutions in Lithuania are among the highest for a bachelor's programme across countries with available data. National students were charged USD 4 048 per year for a bachelor's degree in 2019/20.

  • Financial transfers from the public to the private sector and direct public financial support to students may alleviate the financial burden of education. In Lithuania, 60% of national tertiary students received financial support in the form of public scholarships, grants and student loans. In 2018, public-to-private transfers represented less than 1% of total expenditure on tertiary institutions, lower than the OECD average of 8%. Public-to-private transfers are generally less common at pre-primary level and represent 0.6% of total expenditure on average across the OECD. However in Lithuania, there are no public-to-private transfers at this level.

  • Across most OECD countries, socio-economic status influences learning outcomes more than gender and immigrant status. In Lithuania, the proportion of children from the bottom quartile of the PISA index of economic, social and cultural status (ESCS) achieving at least PISA level 2 in reading in 2018 was 32% lower than that of children from the top ESCS quartile, a larger share than the OECD average of 29%.

  • International student mobility at the tertiary level has risen steadily reaching about 6 700 students in Lithuania and representing 6% of tertiary students in 2019. The largest share of international tertiary students studying in Lithuania comes from India. Students from low and lower-middle income countries are generally less likely to study abroad. In 2019, they represented 29% of international students in OECD countries, compared to 31% in Lithuania.

  • Large differences in educational attainment may lead to starker earnings inequality in many countries. In Lithuania, 27% of 25-64 year-old adults with below upper secondary attainment earned at or below half the median earnings in 2018, similar to the OECD average.

  • In Lithuania, 0.5% of students in lower secondary and 0.4% in upper secondary initial education repeated a grade in 2019, compared to 1.9% and 3% respectively on average across OECD countries. Boys are more likely to repeat a grade at lower secondary initial education than girls. In Lithuania, 69% of repeaters at lower secondary level were boys, higher than the OECD average of 61%. At upper secondary level, the share of boys repeating a grade in Lithuania decreases to 60%, compared to 57% on average across OECD countries.

  • Men are more likely than women to pursue a vocational track at upper secondary level in most OECD countries. This is also the case in Lithuania, where 66% of upper secondary vocational graduates in 2019 were men (compared to the OECD average of 55%). Women are generally more likely to graduate from upper secondary general programmes. This is also the case in Lithuania, where women represent 53% of graduates from upper secondary general programmes, compared to 55% on average across OECD countries (Figure 1).

  • Tertiary education has been expanding in the last decades, and, in 2020, 25-34 year-old women were more likely than men to achieve tertiary education in all OECD countries. In Lithuania, 68% of 25-34 year-old women had a tertiary qualification in 2020 compared to 46% of their male peers, while on average across OECD countries the shares were 52% among young women and 39% among young men.

  • Gender differences in the distribution of tertiary entrants across fields of study are significant. Women tend to be under-represented in certain fields of science, technology, engineering and mathematics (STEM) across most OECD countries. On average, 26% of new entrants in engineering, manufacturing and construction and 20% in information and communication technologies were women in 2019. In Lithuania, women represented 23% of new entrants in engineering, manufacturing and construction programmes and 14% in information and communication technologies. In contrast, they represented 86% of new entrants to the field of education, a sector traditionally dominated by women. In Lithuania, men represent 18% of teachers across all levels of education, compared to 30% on average across OECD countries.

  • Young women are less likely to be employed than young men, particularly those with lower levels of education. Only 41% of 25-34 year-old women with below upper secondary attainment were employed in 2020 compared to 57% of men in Lithuania. This gender difference is smaller than the average across OECD countries, where 43% of women and 69% of men with below upper secondary attainment are employed.

  • In nearly all OECD countries and at all levels of educational attainment, 25-64 year-old women earn less than their male peers: their earnings correspond to 76%-78% of men’s earnings on average across OECD countries. This proportion varies more across educational attainment levels within countries than on average across OECD countries. Compared to other education levels, women with tertiary education in Lithuania have the lowest earnings relative to men with a similar education level, earning 76% as much, while those with below upper secondary education earn 85% as much.

  • On average across OECD countries with available data, 25-64 year-old women tend to participate slightly more in adult learning than men of the same age. In Lithuania, 32% of women participated in formal and/or non-formal education and training in 2016, compared to 24% of men. Family reasons were reported as barriers to participation in formal and/or non-formal education and training by 29% of both men and women.

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1. Includes post-secondary non-tertiary level.

Countries are ranked in descending order of the share of women in general programmes.

Source: OECD (2021). Table B3.1. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterB.pdf).

  • On average across the OECD, foreign-born adults (25-64 year-olds) account for 22% of all adults with below upper secondary attainment, 14% of those attaining upper secondary or post-secondary non-tertiary attainment, and 18% of tertiary-educated adults. However, in Lithuania, the share of foreign-born adults among all adults with a given level of educational attainment is the highest among adults with upper secondary or post-secondary non-tertiary attainment (6% in 2020).

  • The likelihood of being employed increases with the level of educational attainment, but foreign-born adults with tertiary attainment generally have lower employment prospects than their native-born peers. On average across OECD countries, 86% of native-born tertiary-educated adults are employed compared to 79% for foreign-born tertiary-educated adults. In Lithuania, among tertiary-educated adults, 90% of native-born adults and 84% of foreign-born adults are employed.

  • Foreign-born young adults (15-29 year-olds) are also more likely to be neither employed nor in education or training (NEET) than native-born young adults. On average across OECD countries, 18.8% of foreign-born and 13.7% of native-born adults are NEET. In Lithuania, the difference is 3 percentage points (15.6% compared to 12.5%).

  • National level data often hide important regional inequalities in children’s access and participation to education. In general, inequalities across regions tend to widen at non-compulsory levels of education. For example, in the majority of countries, the variation in enrolment rate of 3-5 year-olds is often greater than the variation among 6-14 year-olds. This is the case in Lithuania, where the enrolment rate of 3-5 year-olds varies from 84% in the region of Central and Western Lithuania to 95% in the region of Vilnius Region whereas the enrolment of 6-14 year-olds varies from 100% to 100% across regions. Similarly, the enrolment rate of 15-19 year-olds varies from 89% to 100% in Lithuania.

  • Tertiary attainment may vary significantly within a country. In Lithuania, the share of 25-64 year-old adults with tertiary education varies from 38% in the region of Central and Western Lithuania to 59% in the region of Vilnius Region, a similar regional variation as the average across OECD countries with available data.

  • 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 below upper secondary education (17 percentage points) than for those with tertiary education (8 percentage points). In Lithuania, there is a difference of 2 percentage points in the employment rate of adults with below upper secondary education between different regions of the country compared to 4 percentage points for tertiary-educated adults.

  • The spread of COVID-19 has continued to impede access to in-person education in many countries around the world in 2021. By mid-May 2021, 37 OECD and partner countries had experienced periods of full school closure since the start of 2020.

  • The number of instructional days when schools were fully closed since the start of 2020 due to the pandemic (excluding school holidays, public holidays and weekends) varies significantly between countries and increases with the level of education. Lithuania follows this pattern. In Lithuania, pre-primary schools were fully closed for an average of 89 days between 1 January 2020 and 20 May 2021. Meanwhile primary schools closed for 94 days, lower secondary for 137 days and upper secondary general schools for 132 days. In comparison, respective closures were 55, 78, 92 and 101 days on average across the OECD.

  • In many countries, schools did not fully close but remained open with reduced capacity. Schools at upper secondary (general) level in Lithuania for instance experienced 139 days of partial opening between January 2020 and May 2021, 125 of which occurred in 2020 and 14 in 2021. In total, this was higher than the number of days of partial opening in the OECD on average (57 days), where there were 27 days of partially open instruction in 2020, and 30 days in 2021. When adding both the number of days where schools were fully and partially closed, learning in upper secondary general education was disrupted by 271 days in Lithuania between January 2020 and May 2021.

  • The impact of COVID-19 and school closures on educational equity has been a concern for many countries. 30 out of the 36 OECD and partner countries surveyed, including Lithuania, declared that additional measures were taken to support the education of children who might face additional barriers to learning during the pandemic. 22 of these countries, including Lithuania, stated that they had subsidised devices for students to help them access education. Measures to encourage disadvantaged or vulnerable students to return to school after closures were also implemented in 29 OECD and partner countries, including in Lithuania.

  • Countries have faced difficult decisions on how to best manage their resources to ensure that students can continue to access quality education in the safest possible conditions and to minimise disruption to learning. Before the pandemic, total public expenditure on primary, secondary and post-secondary non-tertiary education in Lithuania reached 2.2% of gross domestic product (GDP) in 2018, which was lower than the OECD average of 3.2%. About two-thirds of OECD and partner countries reported increases in the funding allocated to primary and secondary schools to help them cope with the crisis in 2020. Compared to the previous year, Lithuania reported an increase in the fiscal year education budget for primary and lower secondary general education in both 2020 and 2021.

  • 20 OECD and partner countries, although not Lithuania, stated that the allocation of additional public funds to support the educational response to the pandemic in primary and secondary schools was based on the number of students or classes. At the same time, 16 countries targeted additional funds at socio-economically disadvantaged students as a way to ensure that resources targeted those that needed them the most, including in Lithuania.

  • Countries’ approach to prioritise teachers in vaccination campaigns against COVID-19 has varied. In total, 19 OECD and partner countries, including Lithuania, have prioritised at least some teachers as part of the government’s plans to vaccinate the population on a national level (as of 20 May 2021).

  • The impact of the pandemic on the economy has raised concerns about the prospects of young adults, especially those leaving education earlier than others. In Lithuania, the unemployment rate among 25-34 year-olds with below upper secondary attainment was 23.6% in 2020, an increase of 5 percentage points from the previous year. In comparison, the average youth unemployment rate of 15.1% in 2020 across OECD countries represented an increase of 2 percentage points from 2019 (Figure 2).

  • At the same time, the number of adults participating in formal and/or non-formal education and training decreased by 27% on average in the OECD between the second quarter of 2019 and the second quarter of 2020 (i.e. during the peak of the first wave of COVID-19 in many OECD countries). In Lithuania, the participation of adults in formal and/or non-formal education and training in this period decreased by 8% in Lithuania.

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Countries are ranked in ascending order of the unemployment rate of 25-34 year-olds with below upper secondary attainment in 2020.

Source: OECD (2021), Table A3.3. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).

  • Annual expenditure per student on educational institutions provides an indication of the investment countries make on each student. After accounting for public-to-private transfers, public expenditure on primary to tertiary educational institutions per full-time student in Lithuania was USD 6 281 in 2018 (in equivalent USD converted using PPPs for GDP) compared to USD 10 000 on average across OECD countries.

  • Expenditure on core educational services such as instruction and teaching make up the largest share of education expenditure. However, ancillary services (such as student welfare) and research and development (R&D) activities also influence the level of expenditure per student. In primary to tertiary education, 87% of institutions’ expenditure per student is devoted to core educational services in Lithuania (compared to 89% on average across OECD countries). This share is generally lower at the tertiary level due to expenditure on research and development, including in Lithuania where 67% of total expenditure is devoted to core educational services.

  • The provision of education across public and private institutions influences the allocation of resources between levels of education and types of institution. In 2018, Lithuania spent USD 6 550 per student at primary, secondary and post-secondary non-tertiary education, USD 3 904 lower than the OECD average of USD 10 454. At tertiary level, Lithuania invested USD 9 905 per student, USD 7 160 less than the OECD average. Expenditure per student on public educational institutions is higher than on private institutions on average across OECD countries. This is also the case in Lithuania, where total expenditure on primary to tertiary public institutions amounts to USD 7 348 per student, compared to USD 7 106 on private institutions.

  • Between 2012 and 2018, expenditure per student from primary to tertiary education increased at an average annual growth rate of 1.6% across OECD countries. In Lithuania, expenditure on educational institutions fell at an average annual rate of 1.4%, while the number of students fell on average by 3.1% per year over this period. This resulted in an average annual growth rate of 1.7% in expenditure per student over this period.

  • Lithuania was among the ten OECD countries that spent the lowest proportion of GDP on primary to tertiary educational institutions. In 2018, Lithuania spent 3.4% of GDP on primary to tertiary educational institutions, which is 1.5 percentage points lower than the OECD average. Across levels of education, Lithuania devoted a lower share of GDP than the OECD average at both non-tertiary and tertiary levels (Figure 3).

  • The share of capital costs on total expenditure on educational institutions is lower than the OECD average at primary to tertiary level in Lithuania. At primary, secondary and post-secondary non-tertiary level, capital costs account for 7% of total spending on educational institutions, 2 percentage points below the OECD average (8%). At the tertiary level, capital costs represent 6%, lower than the average across OECD countries of 11%.

  • Compensation of teachers and other staff employed in educational institutions represents the largest share of current expenditure from primary to tertiary education. In 2018, Lithuania allocated 77% of its current expenditure to staff compensation, compared to 74% on average across OECD countries. Staff compensation tends to make up a smaller share of current expenditure on tertiary institutions due to the higher costs of facilities and equipment at this level. In Lithuania, staff compensation represents 74% of current expenditure on tertiary institutions compared to 78% at non-tertiary levels. On average across OECD countries, the share is 68% at tertiary level and 77% at non-tertiary level.

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1. Primary, secondary and post-secondary non-tertiary education includes pre-primary programmes.

Countries are ranked in descending order of total expenditure on educational institutions as a percentage of GDP.

Source: OECD (2021), Table C2.1. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterC.pdf).

  • The salaries of school staff, and in particular teachers and school heads, represent the largest single expenditure in formal education. Their salary levels also have an impact on the attractiveness of the teaching profession. In most OECD countries and economies, statutory salaries of teachers (and school heads) in public educational institutions increase with the level of education they teach, and also with experience. On average, statutory salaries of teachers with maximum qualifications at the top of their salary scales (maximum salaries) were between 86% and 91% higher than those of teachers with the minimum qualifications at the start of their career (minimum salaries) at pre-primary (ISCED 02), primary and general lower and upper secondary levels in 2020. In Lithuania, maximum salaries were 40% to 51% higher than minimum salaries at each level of education (Figure 4). However, most teachers were paid between these minimum and maximum salaries.

  • Teachers’ actual salaries reflect their statutory salaries and additional work-related payments. Average actual salaries also depend on the characteristics of the teaching population such as their age, level of experience and qualification level. In Lithuania, teachers’ average actual salaries (after conversion to USD using PPPs for private consumption) amount to USD 37 389 at the pre-primary level (ISCED 02), USD 37 389 at the primary level, USD 37 389 at the general lower secondary level and USD 37 389 at the general upper secondary level. On average across OECD countries, teachers’ average actual salaries were USD 40 707, USD 45 687, USD 47 988 and USD 51 749 at the pre-primary, primary, lower secondary and upper secondary level respectively (Figure 4).

  • Teachers’ average actual salaries remained lower than those of tertiary-educated workers in almost all countries, and at almost all levels of education. Teachers’ average actual salaries at pre-primary (ISCED 02), primary and general secondary levels of education were between 81% and 96% of the earnings of tertiary-educated workers on average across OECD countries and economies. In Lithuania, the proportion ranged from 119% to 119% at pre-primary, primary and general secondary levels of education.

  • The average number of teaching hours per year required of a typical teacher in public educational institutions in OECD countries tends to decrease as the level of education increases: it ranged from 989 hours at pre-primary level (ISCED 02), to 791 hours at primary level, 723 hours at lower secondary level (general programmes) and 685 hours at upper secondary level (general programmes) in 2020. In Lithuania, teachers teach 640 hours per year at pre-primary level, 830 hours per year at primary level, 854 hours at lower secondary level (general programmes) and 854 hours at upper secondary level (general programmes).

  • During their working time, teachers also perform various tasks other than teaching itself such as lesson planning and preparation, marking students’ work and communicating or co-operating with parents or guardians. At the lower secondary level, teachers in Lithuania spend 57% of their statutory working time on teaching, compared to 44% on average among countries with available data.

  • In primary and secondary education, about 35% of teachers are at least 50 years old on average across OECD countries and may reach retirement age in the next decade, while the size of the school-age population is projected to increase in some countries, putting many governments under pressure to recruit and train new teachers. In 2019, 51% of primary teachers in Lithuania were at least 50 years old, which was higher than the OECD average of 33%. On average across OECD countries, the proportion of teachers aged at least 50 years old increases with higher levels of education taught, to 36% in lower secondary education and 40% in upper secondary education. In Lithuania, this proportion varies from 55% at lower secondary level to 57% at upper secondary level.

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Note: Actual salaries include bonuses and allowances.

1. Actual base salaries.

2. Salaries at the top of the scale and the minimum qualifications, instead of the maximum qualifications.

3. Salaries at the top of the scale and the most prevalent qualifications, instead of the maximum qualifications.

4. Includes the average of fixed bonuses for overtime hours.

Countries and economies are ranked in descending order of starting salaries for lower secondary teachers with the minimum qualifications.

Source: OECD (2021), Table D3.3 and Education at a Glance Database, http://stats.oecd.org. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterD.pdf).

References

OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris, https://dx.doi.org/10.1787/69096873-en.

OECD (2021), “Regional education”, OECD Regional Statistics (database), https://dx.doi.org/10.1787/213e806c-en (accessed on 27 July 2021).

OECD (2021), “The state of global education – 18 months into the pandemic”, OECD Publishing, Paris, https://doi.org/10.1787/1a23bb23-en.

For more information on Education at a Glance 2021 and to access the full set of Indicators, see: https://doi.org/10.1787/b35a14e5-en

For more information on the methodology used during the data collection for each indicator, the references to the sources and the specific notes for each country, see Annex 3 (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3.pdf).

For general information on the methodology, please refer to the OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications (https://doi.org/10.1787/9789264304444-en).

Updated data can be found on line at http://dx.doi.org/10.1787/eag-data-en and by following the StatLinks 2under the tables and charts in the publication.

Data on subnational regions for selected indicators are available in the OECD Regional Statistics (database) (OECD, 2021). When interpreting the results on subnational entities, readers should take into account that the population size of subnational entities can vary widely within countries. For example, regional variation in enrolment may be influenced by students attending school in a different region from their area of residence, particularly at higher levels of education. Also, regional disparities tend to be higher when more subnational entities are used in the analysis.

Explore, compare and visualise more data and analysis using the Education GPS:

https://gpseducation.oecd.org/

The data on educational responses during COVID-19 were collected and processed by the OECD based on the Survey on Joint National Responses to COVID-19 School Closures, a collaborative effort conducted by the United Nations Educational, Scientific and Cultural Organization (UNESCO); the UNESCO Institute for Statistics (UIS); the United Nations Children's Fund (UNICEF); the World Bank; and the OECD.

This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of OECD member countries.

This document, as well as any data and any map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.

The statistical data for Israel are supplied by and 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.

The use of this work, whether digital or print, is governed by the terms and conditions to be found at www.oecd.org/termsandconditions/.

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