{"id":808865,"name":"Combined gross enrolment ratio for tertiary education, male","unit":"%","createdAt":"2023-08-17T18:18:39.000Z","updatedAt":"2026-05-11T12:37:41.000Z","coverage":"","timespan":"1820-2025","datasetId":6195,"shortUnit":"%","columnOrder":0,"shortName":"m_tertiary_enrollment_rates_combined_wb","catalogPath":"grapher/education/2023-07-17/education_lee_lee/education_lee_lee#m_tertiary_enrollment_rates_combined_wb","descriptionFromProducer":"Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Tertiary education, whether or not to an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level.\n\n### Limitations and exceptions:\nEnrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.\n\n### Statistical concept and methodology:\nGross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","descriptionProcessing":"Historical data up to the year 1985 has been sourced from 'Human Capital in the Long Run' by Lee and Lee (2016). This historical data was then combined with recent estimates provided by the World Bank.\n\nFor the period before 1985, regional aggregates were computed by Our World in Data through yearly population-weighted averages, where annual values are proportionally adjusted to emphasize the influence of larger populations.","type":"float","dataChecksum":"16555423162248215230","metadataChecksum":"-4282466115183611134","datasetName":"Human Capital in the Long Run (Lee and Lee 2016), WDI (World Bank) and UNESCO","datasetVersion":"2023-07-17","nonRedistributable":false,"display":{"unit":"%","shortUnit":"%","numDecimalPlaces":1},"schemaVersion":2,"processingLevel":"major","presentation":{"topicTagsLinks":["Global Education"]},"descriptionKey":["Total enrolment in tertiary education regardless of age expressed as a percentage of the population in the 5-year age group immediately following upper secondary education."],"dimensions":{"years":{"values":[{"id":1820},{"id":1825},{"id":1830},{"id":1835},{"id":1840},{"id":1845},{"id":1850},{"id":1855},{"id":1860},{"id":1865},{"id":1870},{"id":1875},{"id":1880},{"id":1885},{"id":1890},{"id":1895},{"id":1900},{"id":1905},{"id":1910},{"id":1915},{"id":1920},{"id":1925},{"id":1930},{"id":1935},{"id":1940},{"id":1945},{"id":1950},{"id":1955},{"id":1960},{"id":1965},{"id":1970},{"id":1975},{"id":1980},{"id":1986},{"id":1990},{"id":2003},{"id":2004},{"id":2009},{"id":2011},{"id":2014},{"id":2018},{"id":2020},{"id":2002},{"id":2005},{"id":2006},{"id":2007},{"id":2008},{"id":2010},{"id":2012},{"id":2013},{"id":2015},{"id":2016},{"id":2017},{"id":2019},{"id":2021},{"id":2022},{"id":2023},{"id":2024},{"id":1989},{"id":1998},{"id":1999},{"id":1985},{"id":1987},{"id":2000},{"id":2001},{"id":1988},{"id":1995},{"id":1991},{"id":1992},{"id":1993},{"id":1994},{"id":1996},{"id":2025},{"id":1997}]},"entities":{"values":[{"id":15,"name":"Afghanistan","code":"AFG"},{"id":273,"name":"Africa","code":"OWID_AFR"},{"id":16,"name":"Albania","code":"ALB"},{"id":17,"name":"Algeria","code":"DZA"},{"id":246,"name":"American 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Afghanistan and Pakistan (WB)","code":"WB_MENAP"},{"id":111,"name":"Moldova","code":"MDA"},{"id":214,"name":"Monaco","code":"MCO"},{"id":112,"name":"Mongolia","code":"MNG"},{"id":215,"name":"Montenegro","code":"MNE"},{"id":110,"name":"Morocco","code":"MAR"},{"id":109,"name":"Mozambique","code":"MOZ"},{"id":142,"name":"Myanmar","code":"MMR"},{"id":108,"name":"Namibia","code":"NAM"},{"id":107,"name":"Nepal","code":"NPL"},{"id":5,"name":"Netherlands","code":"NLD"},{"id":106,"name":"New Zealand","code":"NZL"},{"id":105,"name":"Nicaragua","code":"NIC"},{"id":104,"name":"Niger","code":"NER"},{"id":103,"name":"Nigeria","code":"NGA"},{"id":294,"name":"North America","code":"OWID_NAM"},{"id":278896,"name":"North America (WB)","code":"WB_NA"},{"id":128,"name":"North Korea","code":"PRK"},{"id":66,"name":"North 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Islands","code":"VIR"},{"id":459,"name":"Upper-middle-income countries","code":"OWID_UMC"},{"id":63,"name":"Uruguay","code":"URY"},{"id":62,"name":"Uzbekistan","code":"UZB"},{"id":221,"name":"Vanuatu","code":"VUT"},{"id":238,"name":"Venezuela","code":"VEN"},{"id":84,"name":"Vietnam","code":"VNM"},{"id":355,"name":"World","code":"OWID_WRL"},{"id":61,"name":"Yemen","code":"YEM"},{"id":60,"name":"Zambia","code":"ZMB"},{"id":80,"name":"Zimbabwe","code":"ZWE"}]}},"origins":[{"id":13528,"title":"World Development Indicators","description":"The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.","producer":"UNESCO Institute for Statistics (UIS) Data API, via World Bank","citationFull":"Data API, UN Educational, Scientific and Cultural Organization (UNESCO), uri: https://databrowser.uis.unesco.org/resources, note: The data are obtained through the UIS API.  Detailed documentation is available at: https://api.uis.unesco.org/api/public/documentation/, publisher: UNESCO Institute for Statistics (UIS), type: Bulk file (csv), date accessed: 2025-09-22, date published: 2025-09. Indicator SE.TER.ENRR.MA (https://data.worldbank.org/indicator/SE.TER.ENRR.MA). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.","versionProducer":"125","urlMain":"https://data.worldbank.org/indicator/SE.TER.ENRR.MA","urlDownload":"https://databankfiles.worldbank.org/public/ddpext_download/WDI_CSV.zip","dateAccessed":"2026-02-27","datePublished":"2026-01-28","license":{"url":"https://datacatalog.worldbank.org/search/dataset/0037712/World-Development-Indicators","name":"CC BY 4.0"}},{"id":218,"title":"Human Capital in the Long Run","description":"Datasets on estimated school enrollment ratios from 1820 to 2010 and estimated educational attainment for the total, female, and male populations from 1870 to 2010. The estimates are available in five-year intervals for 111 countries.\n\nDatasets were last updated in 2021 September. The research provides insightful analysis on the progression and trends of educational attainment over a long historical period, offering a comprehensive understanding of educational developments globally.\n","producer":"Lee and Lee","citationFull":"Lee, Jong-Wha and Hanol Lee, 2016, “Human Capital in the Long Run,” Journal of Development Economics, vol. 122, pp. 147-169.","urlMain":"https://barrolee.github.io/BarroLeeDataSet/DataLeeLee.html","dateAccessed":"2023-11-20","datePublished":"2016","license":{"url":"https://barrolee.github.io/BarroLeeDataSet/OUPProj.html","name":"2021 by Robert J. Barro and Jong-Wha Lee."}}]}