Global Rise of Education

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Mohamed Nagdy and Max Roser (2016) – ‘Global Rise of Education’. Published online at OurWorldInData.org. Retrieved from: https://ourworldindata.org/global-rise-of-education/ [Online Resource]

There exist many different ways of measuring education over time and for cross-country comparisons. We can measure education using both quantity and quality measures. With regards to quantity, the most common measures are average years spent in education and graduation rates from different stages of education. With regards to quality, it is possible to measure skills and knowledge. The OECD’s Programme for International Student Assessment (PISA) is one such example of the quality approach to measuring educational standards. More information on the quality of education can be found here.

Education is an important measure for several reasons. Equalising the educational opportunities within a particular country can reduce inequality by improving the prospects of the poorest. Improvements in education can also directly lead to growth through innovations and gains to productivity. A basic understanding of science can also help overcome superstitions or misinformation that damage health; this is particularly important for combating HIV/AIDS in the developing world. Finally, education can increase the accountability of governments.

# Empirical View

Across the globe, measures of education have been increasing with remarkable stability. This rise has been caused by a combination of increased appreciation of the benefits of education to the individual and society, increased government provision and increases to mandatory minimum years of schooling.

# Population having attained at least basic education by region, 1870-2010 – OECD (2014)1

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# Share of population aged 15 and over that attend school, 1950-2010 – Max Roser2

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# Global Rise of Education since 1950

There has been a strong upward trend in the mean years of schooling for all countries since 1950, however, with only a few exceptions, the gap between developed and developing countries has changed very little. This pattern is clear in the following chart.

Despite the weak convergence in the mean years of schooling between developed and developing countries, current projections predict that the proportion of people receiving no education at all will converge to zero. By 2050, only five countries are predicted to have a rate of no education above 20%: these are Burkina Faso, Ethiopia, Guinea, Mali and Niger.

 

# Geographic Convergence of Education

As well as between country convergence in education, we do also observe within country convergence. Historic data from the US shows strong convergence between states in both literacy rates and the mean years of schooling.

# Convergence of literacy rates for adults between southern states (S) and northern states (N) in the US, 1870-1930 – Collins3

Literacy rates of the adult population in the US converged in the years 1870-1930. The following chart highlights how the initial gap between Southern and Northern states collapses.

Notes from the authors: “Calculated using IPUMS microdata (Ruggles et al. 2004). Dashed lines connect the Southern and non-Southern averages from year to year. Each open circle marks a state average in a particular year. ‘‘S’’ is noted next to Southern states. Washington, D.C., is not plotted but is included in the Southern average. Samples include everyone aged 18–64; respondents are counted as literate if they can read and write. The low outliers for 1870 and 1880 represent New Mexico.”

Convergence of Literacy Rates for adults between Southern States (denoted by S) and Northern States (denoted by N) in the US, 1870–1930 - Collins0

# Convergence in workers’ educational attainment for US states, 1940-1980 – Collins4

States with the highest average level of school attainment in 1940 saw the smallest increase in the average in the years 1940-80,  meanwhile the states with the lowest initial attainment saw the largest gains over this period. This pattern implies convergence in average high school education over the period.

Notes from the authors: “Calculated using IPUMS microdata (Ruggles et al. 2004). Averages are based on respondents’ highest grade of completion in 1940 and highest grade of attendance in 1980.”

Convergence in workers’ educational attainment, 1940–1980 by US States - Collins0

# Correlates, Determinants & Consequences

# The Relationship between GDP and Education

There is a very robust relationship between measures of GDP and educational attainment.

# Log GDP per capita (2000) and primary school enrollment (1900) – Glaeser et al.5

The following figure demonstrates how primary school enrolment a century ago (1900) is a very good predictor for present economic development (2000). The authors argue that human capital is “a more basic source of growth than… institutions” and that institutional improvement follows human capital acquisition and good policies.

Education and development link

# Education and Democracy

There are many explanation for the link between democracy and education. Two causal explanations discussed by Glaeser et al. (2007) are first, that schooling indoctrinates students with the virtues of political participation, and second, that school develops social capital.6 In the second view schooling improves an individual’s interpersonal skills facilitating civic involvement and increasing the benefit of it. More information on the democracy can be found here.

# Women’s Education and Child Mortality

There is a substantial literature on the effects of women’s education on child mortality. A more educated female population is strongly associated with lower rates of child mortality as well as both human and economic development. Some of the suggested reasons for this relationship are summarised in the figure below.

# The linkages between female education, human development and economic development – Brown and Barrett7

The linkages between female education, human development and economic development

 

# Counterfactual analysis of effect of education and gross domestic product (GDP) on child mortality globally with 1970 (A) and 1990 (B) as base years – Gakidou et al.8

Gakidou et al. find that over half the decline seen in child mortality globally between 1970-2010 can be explained by improvements in the education of women. What is more, they find that economic growth (GDP) can only explain a very small amount of the reduction in child mortality.

Explanatory notes from the authors: “The lines represent the actual child mortality rate (blue); estimated child mortality rate if GDP for each country had remained at the level it was in 1970 or 1990 (green); estimated child mortality rate if education of reproductive-age women for each country had remained at the level it was in 1970 or 1990 (red); and estimated child mortality rate if both GDP and education of reproductive-age women had remained at their 1970 or 1990 levels (purple).”

 

Child mortality and education GDP - Gakidou et al

# Data Sources

# UNESCO Institute of Statistics
  • Data: Comprehensive data on enrollments, out-of-school children, repetition, completion, gender, teachers, education expenditures, learning outcomes, educational attainment, education equality, literacy, population, labor, and EMIS.
  • Geographical coverage: Global by country
  • Time span: 1999-2015
  • Available at: http://data.uis.unesco.org/

# World Bank EdStats
  • Data: indicators on educational attainment, enrolment, attendance, teachers, financing and more
  • Geographical coverage: Global, over 200 countries
  • Time span: 1970 to most recent data year; Projections to 2050
  • Available at: It is online here

# Barro-Lee educational attainment dataset
  • Data: Educational attainment disaggregated by age group and gender
  • Geographical coverage: 146 countries worldwide
  • Time span: 1950-2010
  • Available at: It is online here

# International Institute for Applied Systems Analysis (IIASA)
  • Data: Educational attainment disaggregated by gender and age group as well as future projections
  • Geographical coverage: 123 countries worldwide
  • Time span: Actual 1970-1995, Projected 2000-2050
  • Available at: It is online here

# OECD: How Was Life? Global Well-being since 1820
  • Data: Historical data on per capita GDP, real wages, educational attainment, life expectancy, height, personal security, political institutions, environmental quality, income inequality and gender inequality
  • Geographical coverage: Global
  • Time span: 1820-2010
  • Available at: It is online here
    van Zanden, J., et al. (eds.) (2014), How Was Life?: Global Well-being since 1820, OECD Publishing, Paris. DOI: http://dx.doi.org/10.1787/9789264214262-en

# Education Policy and Data Center (EPDC)
  • Data: Key education indicators, measuring school access, participation, completion and progression, learning outcomes, level of resources such as schools and teachers, and other key measures of the education system
  • Geographical coverage: Global
  • Time span: 1999-2015
  • Available at: It is online here