Across most OECD countries, socio-economic status influences learning outcomes more than gender and immigrant status. In Argentina, 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 64% lower than that of children from the top ESCS quartile, a larger share than the OECD average of 29%.
Education at a Glance 2021
OECD Indicators
Report
Education at a Glance
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Argentina
Ensuring equal opportunities for students across socio-economic backgrounds
Note: All tertiary education includes short-cycle tertiary programmes, which are not presented separately in the figure.
1. Data on short-cycle tertiary programmes are based on nationality and refer to the Flemish community only.
2. Year of reference 2018.
Countries are ranked in descending order of the percentage of international or foreign students in tertiary education.
Source: OECD/UIS/Eurostat (2021), Table B6.1. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterB.pdf).
International student mobility at the tertiary level has risen steadily reaching about 109 200 students in Argentina and representing 3% of tertiary students in 2018 (Figure 1). The largest share of foreign tertiary students studying in Argentina comes from Peru. Students from low and lower-middle income countries are generally less likely to study abroad. In 2018, they represented 29% of international students in OECD countries, compared to 13% in Argentina.
Gender inequalities in education and outcomes
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 Argentina, 45% of 25-34 year-old women had a tertiary qualification in 2018 compared to 34% of their male peers, while on average across OECD countries the shares were 52% among young women and 39% among young men (Figure 2).
Note: A data point above 0 means there are more women than men attaining tertiary education. A data point below 0 means there are more men than women attaining tertiary education.
1. Year of reference differs from 2020. Refer to the source table for more details.
2. Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).
Countries are ranked in descending order of the percentage-point difference between the share of tertiary-educated women and men.
Source: OECD (2021), Table A1.2. See Source section for more information and Annex 3 for notes (https://www.oecd.org/education/education-at-a-glance/EAG2021_Annex3_ChapterA.pdf).
Young women are less likely to be employed than young men, particularly those with lower levels of education. Only 40% of 25-34 year-old women with below upper secondary attainment were employed in 2018 compared to 82% of men in Argentina. This gender difference is larger than the average across OECD countries, where 43% of women and 69% of men with below upper secondary attainment are employed.
Investing in education
Annual public expenditure per student on educational institutions provides an indication of the public investment countries make on each student. In 2018, Argentina spent less on primary to tertiary educational institutions per full-time student than the OECD average, investing a total of USD 3 560 per student (in equivalent USD converted using PPPs for GDP) compared to USD 10 000 on average across OECD countries.
The provision of education across public and private institutions influences the allocation of resources between levels of education and types of institution. Public expenditure per student on public educational institutions is USD 5 000 higher than on private institutions on average across OECD countries. However, this is not the case in Argentina, where public expenditure on public institutions from primary to tertiary level amounts to USD 5 841 per student, compared to USD 1 848 on private institutions.
The share of public expenditure devoted to educational institutions over the national wealth is higher in Argentina than on average among OECD countries. In 2018, public expenditure in Argentina reached 4.3% of its GDP on primary to tertiary educational institutions, which is 0.2 percentage points higher than the OECD average. Across levels of education, Argentina devoted a higher share of GDP than the OECD average at non-tertiary levels and a higher share at the tertiary level.
The share of capital costs on total expenditure on educational institutions is lower than the OECD average at primary to tertiary level in Argentina. At primary, secondary and post-secondary non-tertiary level, capital costs account for 3% of total spending on educational institutions, 5 percentage points below the OECD average (8%). At the tertiary level, capital costs represent 1%, 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, Argentina allocated 84% 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 Argentina, staff compensation represents 88% of current expenditure on tertiary institutions compared to 83% at non-tertiary levels. On average across OECD countries, the share is 68% at tertiary level and 77% at non-tertiary level.
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.
More information
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.
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Questions can be directed to: Marie-Helene Doumet Directorate for Education and Skills |
Country note authors: Etienne Albiser, Heewoon Bae, Andrea Borlizzi, António Carvalho, Eric Charbonnier, Corinne Heckmann, Bruce Golding, Yanjun Guo, Gara Rojas Gonzalez, Daniel Sanchez Serra, Markus Schwabe and Giovanni Maria Semeraro |
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.
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