Wittgenstein Projection: Percentage of the population age 15+ by highest level of educational attainment. No Education. Male by country
Share of the population of the stated age group that has never attended school. Projections are based on collected census and survey data for the base year (around 2010) and the Medium Shared Socioeconomic Pathways (SSP2) projection model. The SSP2 is a middle-of-the-road scenario that combines medium fertility...
What the numbers show
Wittgenstein Projection: Percentage of the population age 15+ by highest level of educational attainment. No Education. Male is currently reported for 139 countries. The highest value is 0.1% in Mali; the lowest is 0.0% in Zimbabwe.
The median across all reporting countries is 0.0%, and the mean is 0.0%.
Wittgenstein Projection: Percentage of the population age 15+ by: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Mali | 0.1% | 2100 | down 33.3% | falling |
| 1 | Chad | 0.1% | 2100 | down 28.6% | falling |
| 3 | Niger | 0.1% | 2100 | down 25.0% | volatile |
| 4 | Burkina Faso | 0.1% | 2100 | down 27.3% | volatile |
| 5 | Liberia | 0.1% | 2100 | down 36.4% | volatile |
| 6 | Mozambique | 0.1% | 2100 | down 33.3% | volatile |
| 7 | Benin | 0.1% | 2100 | down 28.6% | volatile |
| 7 | Guinea | 0.1% | 2100 | down 28.6% | volatile |
| 9 | Sierra Leone | 0.0% | 2100 | down 42.9% | volatile |
| 10 | Madagascar | 0.0% | 2100 | down 25.0% | falling |
| 10 | Pakistan | 0.0% | 2100 | down 40.0% | volatile |
| 10 | Senegal | 0.0% | 2100 | down 40.0% | volatile |
| 13 | Burundi | 0.0% | 2100 | down 50.0% | volatile |
| 13 | Bangladesh | 0.0% | 2100 | down 33.3% | volatile |
| 13 | Ethiopia | 0.0% | 2100 | down 33.3% | volatile |
| 13 | Guinea-Bissau | 0.0% | 2100 | down 50.0% | volatile |
| 13 | Sudan | 0.0% | 2100 | down 50.0% | volatile |
| 13 | Somalia | 0.0% | 2100 | down 33.3% | volatile |
| 19 | Bhutan | 0.0% | 2100 | down 66.7% | volatile |
| 19 | Cote d'Ivoire | 0.0% | 2100 | down 50.0% | volatile |
| 19 | Cape Verde | 0.0% | 2100 | unchanged | volatile |
| 19 | Ghana | 0.0% | 2100 | down 50.0% | volatile |
| 19 | Gambia | 0.0% | 2100 | down 50.0% | volatile |
| 19 | Guatemala | 0.0% | 2100 | down 50.0% | volatile |
| 19 | India | 0.0% | 2100 | down 50.0% | volatile |
| 19 | Cambodia | 0.0% | 2100 | unchanged | volatile |
| 19 | Laos | 0.0% | 2100 | unchanged | volatile |
| 19 | Morocco | 0.0% | 2100 | unchanged | volatile |
| 19 | Malawi | 0.0% | 2100 | unchanged | volatile |
| 19 | Nicaragua | 0.0% | 2100 | unchanged | volatile |
| 19 | Nepal | 0.0% | 2100 | unchanged | volatile |
| 19 | Rwanda | 0.0% | 2100 | unchanged | volatile |
| 19 | Tanzania | 0.0% | 2100 | unchanged | volatile |
| 19 | Uganda | 0.0% | 2100 | unchanged | volatile |
| 35 | Aruba | 0.0% | 2100 | — | volatile |
| 35 | Albania | 0.0% | 2100 | — | volatile |
| 35 | United Arab Emirates | 0.0% | 2100 | — | volatile |
| 35 | Argentina | 0.0% | 2100 | — | volatile |
| 35 | Armenia | 0.0% | 2100 | — | volatile |
| 35 | Australia | 0.0% | 2100 | — | volatile |
| 35 | Azerbaijan | 0.0% | 2100 | — | volatile |
| 35 | Belgium | 0.0% | 2100 | — | volatile |
| 35 | Bulgaria | 0.0% | 2100 | — | volatile |
| 35 | Bahrain | 0.0% | 2100 | — | volatile |
| 35 | Bahamas | 0.0% | 2100 | — | volatile |
| 35 | Bosnia and Herzegovina | 0.0% | 2100 | — | volatile |
| 35 | Belize | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Bolivia | 0.0% | 2100 | — | volatile |
| 35 | Brazil | 0.0% | 2100 | — | volatile |
| 35 | Central African Republic | 0.0% | 2100 | — | volatile |
| 35 | Canada | 0.0% | 2100 | — | volatile |
| 35 | Chile | 0.0% | 2100 | — | volatile |
| 35 | China | 0.0% | 2100 | — | volatile |
| 35 | Cameroon | 0.0% | 2100 | — | volatile |
| 35 | Democratic Republic of Congo | 0.0% | 2100 | — | volatile |
| 35 | Congo | 0.0% | 2100 | — | volatile |
| 35 | Colombia | 0.0% | 2100 | — | volatile |
| 35 | Comoros | 0.0% | 2100 | — | volatile |
| 35 | Costa Rica | 0.0% | 2100 | — | volatile |
| 35 | Cuba | 0.0% | 2100 | — | volatile |
| 35 | Germany | 0.0% | 2100 | — | volatile |
| 35 | Dominican Republic | 0.0% | 2100 | — | volatile |
| 35 | Algeria | 0.0% | 2100 | — | volatile |
| 35 | Ecuador | 0.0% | 2100 | — | volatile |
| 35 | Egypt | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Spain | 0.0% | 2100 | — | volatile |
| 35 | France | 0.0% | 2100 | — | volatile |
| 35 | Gabon | 0.0% | 2100 | — | volatile |
| 35 | United Kingdom | 0.0% | 2100 | — | volatile |
| 35 | Equatorial Guinea | 0.0% | 2100 | — | volatile |
| 35 | Greece | 0.0% | 2100 | — | volatile |
| 35 | Guyana | 0.0% | 2100 | — | volatile |
| 35 | Hong Kong | 0.0% | 2100 | — | volatile |
| 35 | Honduras | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Croatia | 0.0% | 2100 | — | volatile |
| 35 | Haiti | 0.0% | 2100 | — | volatile |
| 35 | Indonesia | 0.0% | 2100 | — | volatile |
| 35 | Iran | 0.0% | 2100 | — | volatile |
| 35 | Iraq | 0.0% | 2100 | — | volatile |
| 35 | Israel | 0.0% | 2100 | — | volatile |
| 35 | Italy | 0.0% | 2100 | — | volatile |
| 35 | Jamaica | 0.0% | 2100 | — | volatile |
| 35 | Jordan | 0.0% | 2100 | — | volatile |
| 35 | Kenya | 0.0% | 2100 | — | volatile |
| 35 | South Korea | 0.0% | 2100 | — | volatile |
| 35 | Kuwait | 0.0% | 2100 | — | volatile |
| 35 | Lebanon | 0.0% | 2100 | — | volatile |
| 35 | Saint Lucia | 0.0% | 2100 | — | volatile |
| 35 | Lesotho | 0.0% | 2100 | — | volatile |
| 35 | Luxembourg | 0.0% | 2100 | — | volatile |
| 35 | Macao | 0.0% | 2100 | — | volatile |
| 35 | Maldives | 0.0% | 2100 | — | volatile |
| 35 | Mexico | 0.0% | 2100 | — | volatile |
| 35 | North Macedonia | 0.0% | 2100 | — | volatile |
| 35 | Malta | 0.0% | 2100 | — | volatile |
| 35 | Myanmar | 0.0% | 2100 | — | volatile |
| 35 | Montenegro | 0.0% | 2100 | — | volatile |
| 35 | Mongolia | 0.0% | 2100 | — | volatile |
| 35 | Mauritius | 0.0% | 2100 | — | volatile |
| 35 | Malaysia | 0.0% | 2100 | — | volatile |
| 35 | Namibia | 0.0% | 2100 | — | volatile |
| 35 | New Caledonia | 0.0% | 2100 | — | volatile |
| 35 | Nigeria | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Netherlands | 0.0% | 2100 | — | volatile |
| 35 | New Zealand | 0.0% | 2100 | — | volatile |
| 35 | Panama | 0.0% | 2100 | — | volatile |
| 35 | Peru | 0.0% | 2100 | — | volatile |
| 35 | Philippines | 0.0% | 2100 | — | volatile |
| 35 | Poland | 0.0% | 2100 | — | volatile |
| 35 | Puerto Rico | 0.0% | 2100 | — | volatile |
| 35 | Portugal | 0.0% | 2100 | — | volatile |
| 35 | Paraguay | 0.0% | 2100 | — | volatile |
| 35 | Palestine | 0.0% | 2100 | — | volatile |
| 35 | French Polynesia | 0.0% | 2100 | — | volatile |
| 35 | Qatar | 0.0% | 2100 | — | volatile |
| 35 | Romania | 0.0% | 2100 | — | volatile |
| 35 | Saudi Arabia | 0.0% | 2100 | — | volatile |
| 35 | Singapore | 0.0% | 2100 | — | volatile |
| 35 | El Salvador | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Sao Tome and Principe | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Eswatini | 0.0% | 2100 | — | volatile |
| 35 | Syria | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Thailand | 0.0% | 2100 | — | volatile |
| 35 | Tajikistan | 0.0% | 2100 | — | volatile |
| 35 | East Timor | 0.0% | 2100 | — | volatile |
| 35 | Tonga | 0.0% | 2100 | — | volatile |
| 35 | Trinidad and Tobago | 0.0% | 2100 | — | volatile |
| 35 | Tunisia | 0.0% | 2100 | — | volatile |
| 35 | Turkey | 0.0% | 2100 | — | volatile |
| 35 | Uruguay | 0.0% | 2100 | — | volatile |
| 35 | United States | 0.0% | 2100 | — | volatile |
| 35 | Saint Vincent and the Grenadines | 0.0% | 2100 | — | volatile |
| 35 | Venezuela | 0.0% | 2100 | — | volatile |
| 35 | Vietnam | 0.0% | 2100 | — | volatile |
| 35 | Vanuatu | 0.0% | 2100 | down 100.0% | volatile |
| 35 | Samoa | 0.0% | 2100 | — | volatile |
| 35 | South Africa | 0.0% | 2100 | — | volatile |
| 35 | Zambia | 0.0% | 2100 | — | volatile |
| 35 | Zimbabwe | 0.0% | 2100 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 0.0%
About this data
Share of the population of the stated age group that has never attended school. Projections are based on collected census and survey data for the base year (around 2010) and the Medium Shared Socioeconomic Pathways (SSP2) projection model. The SSP2 is a middle-of-the-road scenario that combines medium fertility with medium mortality, medium migration, and the Global Education Trend (GET) education scenario. For more information and other projection models, consult the Wittgenstein Centre for Demography and Global Human Capital's website: http://www.oeaw.ac.at/vid/dataexplorer/