Population size
Mean years of schooling
Population 25 years and older
Gender gap in mean years of schooling
Male advantage, population 25 years and older
Universal lower secondary education reached in
Year 90% of 30-34 years old have at least lower secondary

Educational attainment

Hungary 1900–2010, population 25 years and older

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Population by age, sex and education

Hungary 1900–2010

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Main Findings

In 1900, only 6.2% of the Hungarian population older than 25 years had received at least lower secondary education. This proportion increased to 20.5% until 1950 and to 94.8% until 2010. By then, about 23.2% of the population aged 25 years or older finished a post-secondary education while 5.2% had primary education or less as their highest educational attainment. Mean years of schooling of the population 25 years or older increased from 2.5 years in 1900 to 4.3 years in 1950 and to 11.1 years in 2010.

Gender and Age

In Hungary, gender differences in educational attainment have been persistent and have been only slowly diminishing during the 20th century. In 1900, 7.7% of the men aged 25 years and older had at least lower secondary education, compared to about 4.7% of the women. By 1950 about 33.7% of the men and 22.8% of the women aged 30 to 34 years had achieved at least lower secondary education while for instance this share was only 13.0% and 9.7% for the population aged 65–69. Although completed lower secondary education became universal for men by 1970 (93.4%), it took five more years for Hungarian women to attain universality (1975: 95.3%). Since 1985, there has been an inverse gender gap in higher education, with larger proportions of women completing post-secondary education than men. In 2010, about 44.1% of women in the 30–34 age group had post-secondary educational attainment, compared to 31.5% of men.

About the Data

The EDU20C estimates of the population of Hungary by age, sex and education are based on several census datasets dating back to 1900. Hungarian censuses provide information on highest educational attainment in decennial intervals for the time since 1920. For the period before 1920, the EDU20C reconstruction cannot rely on any other data-points. For Hungary in the period 1950 to 2010 we have only 5 education categories as incomplete and complete primary education cannot be disaggregated and are merged in the category primary education.


In the context of World Wars I and II, Hungary, as many other countries in Europe, was facing changes in the extent of its national territory. We collected regional census reports from neighbouring countries like Austria and Italy to assemble the data corresponding to the present territory. For Hungary it was necessary to generate life tables for missing data-points by interpolating/extrapolating life expectancies at birth by sex. The model fits a logistic function to existing life expectancies at birth, given the values of upper and lower asymptotes. Based on these estimated life expectancies we use a function that interpolates the logarithms of the probabilities of dying (nqx) from two life tables to generate a comprehensive set of life tables for the entire reconstruction period. Both R functions are in their methodological core based on the Population Analysis System (PAS) Excel templates E0LGST and INTPLTF/INTPLTM. Additionally, some historical source data on the population structure were only available for insufficient large open-ended age groups (e.g. 85+ years from 1900 to 1950), what required an age structure extension to 100+ years based on Lx information from the life tables. Furthermore, it was necessary to interpolate the intercensal data-points for population by age and sex using a linear interpolation function.

Source Data

For Hungary the major source of data on population by age, sex and educational attainment in the 20th century originates from the digitised archive and compendia of the Hungarian Central Statistical Office/KSH. For the EDU20C reconstruction, we also used information on mortality extracted from the life tables available in the KSH database.