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Data

Number of adults with no formal education by region

See all data and research on:
Population Growth

What you should know about this indicator

Regional aggregates (e.g. continents) are calculated by summing population values across member countries. For these, we use OWID's region definitions.

Number of adults with no formal education by region
De facto population aged 15+ withno education in a country or region.
Source
Wittgenstein Centre (2024) – processed by Our World in Data
Last updated
February 11, 2026
Next expected update
February 2028
Date range
1950–2100
Unit
people

Sources and processing

This data is based on the following sources

Wittgenstein Centre – Human Capital, Wittgenstein Centre

This website presents the 2023 revision of the Wittgenstein Centre population projections (Version 3), following the initial projections (Version 1) in 2013 (Lutz, Butz, and KC (Eds.) 2014) and the 2018 update (Version 2) (Lutz, Goujon, KC, Stonawski, and, Stilianakis (Eds.) 2018). Further details on the updates and the revisions can be found in K.C. et al. (2024) and in other satellite papers focusing on the migration component (Yildiz and Abel 2024), the mortality component (Dhakad and KC 2024 - forthcoming), and the fertility component (Adhikari et al. 2024 - forthcoming).

In 2021, the Shared Socioeconomic Pathways (SSPs) scenario community related to the Intergovernmental Panel on Climate Change requested an update of the human core of the SSPs, which is at the origin of this version. This updated version is based on 2020 as the reference year, with adjustments to certain short-term assumptions extending to 2030. However, most long-term assumptions have not been changed. Several changes were nevertheless implemented particularly in estimating and using country-specific education differentials in mortality and migration.

This new version includes population projections by levels of educational attainment from 2020 to 2100 for 200 countries according to seven scenarios (SSP1-5, SSP2-Zero Migration and SSP2-Double Migration). The reconstruction will become available in the course of 2024.

Retrieved on
February 11, 2026
Retrieved from
https://dataexplorer.wittgensteincentre.org/wcde-v3/
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.
K.C., S., Dhakad, M., Potancokova, M., Adhikari, S., Yildiz, D., Mamolo, M., Sobotka, T., Zeman, K., Abel, G., Lutz, W., and Goujon, A. (2024). Updating the Shared Socioeconomic Pathways (SSPs) Global Population and Human Capital Projections. IIASA Working Paper. Laxenburg, Austria: WP-24-003. https://pure.iiasa.ac.at/19487. Available at: http://www.wittgensteincentre.org/dataexplorer.

This website presents the 2023 revision of the Wittgenstein Centre population projections (Version 3), following the initial projections (Version 1) in 2013 (Lutz, Butz, and KC (Eds.) 2014) and the 2018 update (Version 2) (Lutz, Goujon, KC, Stonawski, and, Stilianakis (Eds.) 2018). Further details on the updates and the revisions can be found in K.C. et al. (2024) and in other satellite papers focusing on the migration component (Yildiz and Abel 2024), the mortality component (Dhakad and KC 2024 - forthcoming), and the fertility component (Adhikari et al. 2024 - forthcoming).

In 2021, the Shared Socioeconomic Pathways (SSPs) scenario community related to the Intergovernmental Panel on Climate Change requested an update of the human core of the SSPs, which is at the origin of this version. This updated version is based on 2020 as the reference year, with adjustments to certain short-term assumptions extending to 2030. However, most long-term assumptions have not been changed. Several changes were nevertheless implemented particularly in estimating and using country-specific education differentials in mortality and migration.

This new version includes population projections by levels of educational attainment from 2020 to 2100 for 200 countries according to seven scenarios (SSP1-5, SSP2-Zero Migration and SSP2-Double Migration). The reconstruction will become available in the course of 2024.

Retrieved on
February 11, 2026
Retrieved from
https://dataexplorer.wittgensteincentre.org/wcde-v3/
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.
K.C., S., Dhakad, M., Potancokova, M., Adhikari, S., Yildiz, D., Mamolo, M., Sobotka, T., Zeman, K., Abel, G., Lutz, W., and Goujon, A. (2024). Updating the Shared Socioeconomic Pathways (SSPs) Global Population and Human Capital Projections. IIASA Working Paper. Laxenburg, Austria: WP-24-003. https://pure.iiasa.ac.at/19487. Available at: http://www.wittgensteincentre.org/dataexplorer.

How we process data at Our World in Data

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

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

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: Number of adults with no formal education by region”, part of the following publication: Hannah Ritchie, Lucas Rodés-Guirao, Edouard Mathieu, Marcel Gerber, Esteban Ortiz-Ospina, Joe Hasell, and Max Roser (2023) - “Population Growth”. Data adapted from Wittgenstein Centre. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.html [online resource] (archived on March 4, 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:

Wittgenstein Centre (2024) – processed by Our World in Data

Full citation

Wittgenstein Centre (2024) – processed by Our World in Data. “Number of adults with no formal education by region” [dataset]. Wittgenstein Centre, “Human Capital, Wittgenstein Centre 3.2” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.html (archived on March 4, 2026).

Download

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.

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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://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.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://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.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://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/total-number-of-people-aged-15-with-no-education-in-millions-by-continent-1970-2050.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear