Wittgenstein Projection: Percentage of the population age 40-64 by highest level of educational attainment. No Education. Female 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 40-64 by highest level of educational attainment. No Education. Female is currently reported for 141 countries. The highest value is 0.1% in Chad; 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 40-64 by: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Chad | 0.1% | 2100 | down 31.6% | falling |
| 2 | Mali | 0.1% | 2100 | down 42.1% | falling |
| 2 | Niger | 0.1% | 2100 | down 38.9% | falling |
| 4 | Burkina Faso | 0.1% | 2100 | down 42.9% | volatile |
| 5 | Liberia | 0.1% | 2100 | down 46.2% | volatile |
| 6 | Mozambique | 0.1% | 2100 | down 40.0% | volatile |
| 7 | Benin | 0.1% | 2100 | down 37.5% | volatile |
| 7 | Sierra Leone | 0.1% | 2100 | down 37.5% | volatile |
| 9 | Guinea | 0.0% | 2100 | down 42.9% | volatile |
| 10 | Senegal | 0.0% | 2100 | down 50.0% | volatile |
| 11 | Burundi | 0.0% | 2100 | down 33.3% | volatile |
| 11 | Ethiopia | 0.0% | 2100 | down 33.3% | volatile |
| 11 | Guinea-Bissau | 0.0% | 2100 | down 50.0% | volatile |
| 11 | Madagascar | 0.0% | 2100 | down 50.0% | volatile |
| 11 | Pakistan | 0.0% | 2100 | down 60.0% | volatile |
| 11 | Sudan | 0.0% | 2100 | down 50.0% | volatile |
| 17 | Bangladesh | 0.0% | 2100 | down 50.0% | volatile |
| 17 | Cote d'Ivoire | 0.0% | 2100 | unchanged | volatile |
| 17 | Ghana | 0.0% | 2100 | down 50.0% | volatile |
| 17 | Gambia | 0.0% | 2100 | down 50.0% | volatile |
| 17 | Guatemala | 0.0% | 2100 | unchanged | volatile |
| 17 | India | 0.0% | 2100 | down 50.0% | volatile |
| 17 | Malawi | 0.0% | 2100 | unchanged | volatile |
| 17 | Rwanda | 0.0% | 2100 | unchanged | volatile |
| 17 | Somalia | 0.0% | 2100 | down 50.0% | volatile |
| 26 | Aruba | 0.0% | 2100 | — | volatile |
| 26 | Albania | 0.0% | 2100 | — | volatile |
| 26 | United Arab Emirates | 0.0% | 2100 | — | volatile |
| 26 | Argentina | 0.0% | 2100 | — | volatile |
| 26 | Australia | 0.0% | 2100 | — | volatile |
| 26 | Azerbaijan | 0.0% | 2100 | — | volatile |
| 26 | Belgium | 0.0% | 2100 | — | volatile |
| 26 | Bulgaria | 0.0% | 2100 | — | volatile |
| 26 | Bahrain | 0.0% | 2100 | — | volatile |
| 26 | Bahamas | 0.0% | 2100 | — | volatile |
| 26 | Bosnia and Herzegovina | 0.0% | 2100 | — | volatile |
| 26 | Belize | 0.0% | 2100 | — | volatile |
| 26 | Bolivia | 0.0% | 2100 | — | volatile |
| 26 | Brazil | 0.0% | 2100 | — | volatile |
| 26 | Bhutan | 0.0% | 2100 | down 100.0% | volatile |
| 26 | Central African Republic | 0.0% | 2100 | — | volatile |
| 26 | Canada | 0.0% | 2100 | — | volatile |
| 26 | Chile | 0.0% | 2100 | — | volatile |
| 26 | China | 0.0% | 2100 | — | volatile |
| 26 | Cameroon | 0.0% | 2100 | — | volatile |
| 26 | Democratic Republic of Congo | 0.0% | 2100 | — | volatile |
| 26 | Congo | 0.0% | 2100 | — | volatile |
| 26 | Colombia | 0.0% | 2100 | — | volatile |
| 26 | Comoros | 0.0% | 2100 | — | volatile |
| 26 | Cape Verde | 0.0% | 2100 | — | volatile |
| 26 | Costa Rica | 0.0% | 2100 | — | volatile |
| 26 | Cuba | 0.0% | 2100 | — | volatile |
| 26 | Germany | 0.0% | 2100 | — | volatile |
| 26 | Dominican Republic | 0.0% | 2100 | — | volatile |
| 26 | Algeria | 0.0% | 2100 | — | volatile |
| 26 | Ecuador | 0.0% | 2100 | — | volatile |
| 26 | Egypt | 0.0% | 2100 | — | volatile |
| 26 | Spain | 0.0% | 2100 | — | volatile |
| 26 | France | 0.0% | 2100 | — | volatile |
| 26 | Gabon | 0.0% | 2100 | — | volatile |
| 26 | United Kingdom | 0.0% | 2100 | — | volatile |
| 26 | Equatorial Guinea | 0.0% | 2100 | — | volatile |
| 26 | Greece | 0.0% | 2100 | — | volatile |
| 26 | Guyana | 0.0% | 2100 | — | volatile |
| 26 | Hong Kong | 0.0% | 2100 | — | volatile |
| 26 | Honduras | 0.0% | 2100 | — | volatile |
| 26 | Croatia | 0.0% | 2100 | — | volatile |
| 26 | Haiti | 0.0% | 2100 | — | volatile |
| 26 | Hungary | 0.0% | 2100 | — | volatile |
| 26 | Indonesia | 0.0% | 2100 | — | volatile |
| 26 | Iran | 0.0% | 2100 | — | volatile |
| 26 | Iraq | 0.0% | 2100 | — | volatile |
| 26 | Israel | 0.0% | 2100 | — | volatile |
| 26 | Italy | 0.0% | 2100 | — | volatile |
| 26 | Jamaica | 0.0% | 2100 | — | volatile |
| 26 | Jordan | 0.0% | 2100 | — | volatile |
| 26 | Kenya | 0.0% | 2100 | — | volatile |
| 26 | Cambodia | 0.0% | 2100 | down 100.0% | volatile |
| 26 | South Korea | 0.0% | 2100 | — | volatile |
| 26 | Kuwait | 0.0% | 2100 | — | volatile |
| 26 | Laos | 0.0% | 2100 | down 100.0% | volatile |
| 26 | Lebanon | 0.0% | 2100 | — | volatile |
| 26 | Saint Lucia | 0.0% | 2100 | — | volatile |
| 26 | Lesotho | 0.0% | 2100 | — | volatile |
| 26 | Luxembourg | 0.0% | 2100 | — | volatile |
| 26 | Macao | 0.0% | 2100 | — | volatile |
| 26 | Morocco | 0.0% | 2100 | — | volatile |
| 26 | Maldives | 0.0% | 2100 | — | volatile |
| 26 | Mexico | 0.0% | 2100 | — | volatile |
| 26 | North Macedonia | 0.0% | 2100 | — | volatile |
| 26 | Malta | 0.0% | 2100 | — | volatile |
| 26 | Myanmar | 0.0% | 2100 | — | volatile |
| 26 | Montenegro | 0.0% | 2100 | — | volatile |
| 26 | Mongolia | 0.0% | 2100 | — | volatile |
| 26 | Mauritius | 0.0% | 2100 | — | volatile |
| 26 | Malaysia | 0.0% | 2100 | — | volatile |
| 26 | Namibia | 0.0% | 2100 | — | volatile |
| 26 | New Caledonia | 0.0% | 2100 | — | volatile |
| 26 | Nigeria | 0.0% | 2100 | — | volatile |
| 26 | Nicaragua | 0.0% | 2100 | down 100.0% | volatile |
| 26 | Netherlands | 0.0% | 2100 | — | volatile |
| 26 | Nepal | 0.0% | 2100 | down 100.0% | volatile |
| 26 | New Zealand | 0.0% | 2100 | — | volatile |
| 26 | Panama | 0.0% | 2100 | — | volatile |
| 26 | Peru | 0.0% | 2100 | — | volatile |
| 26 | Philippines | 0.0% | 2100 | — | volatile |
| 26 | Puerto Rico | 0.0% | 2100 | — | volatile |
| 26 | Portugal | 0.0% | 2100 | — | volatile |
| 26 | Paraguay | 0.0% | 2100 | — | volatile |
| 26 | Palestine | 0.0% | 2100 | — | volatile |
| 26 | French Polynesia | 0.0% | 2100 | — | volatile |
| 26 | Qatar | 0.0% | 2100 | — | volatile |
| 26 | Romania | 0.0% | 2100 | — | volatile |
| 26 | Saudi Arabia | 0.0% | 2100 | — | volatile |
| 26 | Singapore | 0.0% | 2100 | — | volatile |
| 26 | El Salvador | 0.0% | 2100 | — | volatile |
| 26 | Serbia | 0.0% | 2100 | — | volatile |
| 26 | Sao Tome and Principe | 0.0% | 2100 | — | volatile |
| 26 | Suriname | 0.0% | 2100 | — | volatile |
| 26 | Slovenia | 0.0% | 2100 | — | volatile |
| 26 | Eswatini | 0.0% | 2100 | — | volatile |
| 26 | Syria | 0.0% | 2100 | — | volatile |
| 26 | Thailand | 0.0% | 2100 | — | volatile |
| 26 | Tajikistan | 0.0% | 2100 | — | volatile |
| 26 | East Timor | 0.0% | 2100 | — | volatile |
| 26 | Tonga | 0.0% | 2100 | — | volatile |
| 26 | Trinidad and Tobago | 0.0% | 2100 | — | volatile |
| 26 | Tunisia | 0.0% | 2100 | — | volatile |
| 26 | Turkey | 0.0% | 2100 | — | volatile |
| 26 | Tanzania | 0.0% | 2100 | — | volatile |
| 26 | Uganda | 0.0% | 2100 | down 100.0% | volatile |
| 26 | Uruguay | 0.0% | 2100 | — | volatile |
| 26 | United States | 0.0% | 2100 | — | volatile |
| 26 | Saint Vincent and the Grenadines | 0.0% | 2100 | — | volatile |
| 26 | Venezuela | 0.0% | 2100 | — | volatile |
| 26 | Vietnam | 0.0% | 2100 | — | volatile |
| 26 | Vanuatu | 0.0% | 2100 | — | volatile |
| 26 | Samoa | 0.0% | 2100 | — | volatile |
| 26 | South Africa | 0.0% | 2100 | — | volatile |
| 26 | Zambia | 0.0% | 2100 | — | volatile |
| 26 | 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/