What you should know about this indicator

  • Going to school at all is the first and most basic step in a person's education. Two centuries ago, almost no one had that chance; today, in most countries, almost everyone does. This indicator tracks that change over time.
  • It combines two sources. For OECD countries, recent figures come from the OECD's Education at a Glance, which surveys people directly. For everywhere else, and for earlier years, we rely on historical estimates from Lee & Lee (2016), which go back to 1870.
  • The two sources are similar but not identical. The OECD counts people with less than a primary education, while Lee & Lee count people with no education at all. The OECD also focuses on people aged 25 to 64, while Lee & Lee cover a slightly wider range, from 15 to 64.
  • As with any indicator built by splicing different sources together, small jumps can appear in a country's series around the year it switches from one source to the other. These jumps reflect a change in measurement, not necessarily a real change in education levels.
Share of adults with no formal education
Lee and Lee; OECD
Share of adults with no formal education.
Source
Lee and Lee (2016); OECD (2025)with major processing by Our World in Data
Last updated
June 21, 2026
Next expected update
June 2027
Date range
1870–2024
Unit
%

Sources and processing

Lee and Lee – Human Capital in the Long Run

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.

Datasets 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.

Retrieved on
November 20, 2023
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Lee, Jong-Wha and Hanol Lee, 2016, “Human Capital in the Long Run,” Journal of Development Economics, vol. 122, pp. 147-169.

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.

Datasets 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.

Retrieved on
November 20, 2023
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Lee, Jong-Wha and Hanol Lee, 2016, “Human Capital in the Long Run,” Journal of Development Economics, vol. 122, pp. 147-169.

OECD – Adults' educational attainment distribution

Distribution of educational attainment among adults aged 25-64, by age group and gender. Data are based on national labour force surveys, censuses, and household surveys, mapped to the ISCED 2011 classification. Covers OECD members and selected partner economies.

Retrieved on
June 21, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD (2026). Education at a Glance - Adults' educational attainment distribution, by age group and gender.

Distribution of educational attainment among adults aged 25-64, by age group and gender. Data are based on national labour force surveys, censuses, and household surveys, mapped to the ISCED 2011 classification. Covers OECD members and selected partner economies.

Retrieved on
June 21, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD (2026). Education at a Glance - Adults' educational attainment distribution, by age group and gender.

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

For each country, we use OECD data from its earliest available year onward. For years before that, we use Lee & Lee (2016) historical estimates.

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Share of adults with no formal education”, part of the following publication: Hannah Ritchie, Veronika Samborska, Esteban Ortiz-Ospina, and Max Roser (2023) - “Global Education”. Data adapted from Lee and Lee, OECD. Retrieved from https://oecd-education-attainment-di.owid.pages.dev:8789/20260518-093348/grapher/share-of-population-15-years-and-older-with-no-education.html [online resource] (archived on May 18, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Lee and Lee (2016); OECD (2025) – with major processing by Our World in Data

Full citation

Lee and Lee (2016); OECD (2025) – with major processing by Our World in Data. “Share of adults with no formal education – Lee and Lee; OECD” [dataset]. Lee and Lee, “Human Capital in the Long Run”; OECD, “Adults' educational attainment distribution” [original data]. Retrieved June 26, 2026 from https://oecd-education-attainment-di.owid.pages.dev:8789/20260518-093348/grapher/share-of-population-15-years-and-older-with-no-education.html (archived on May 18, 2026).

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://oecd-education-attainment-di.owid.pages.dev/grapher/share-of-population-15-years-and-older-with-no-education.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear