Wittgenstein Projection: Percentage of the population age 20-64 by in Belarus
Belarus: Wittgenstein Projection: Percentage of the population age 20-64 by was 0.0% in 2100. ◆ Volatile
Wittgenstein Projection: Percentage of the population age 20-64 by in Belarus, 2010–2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
The most recent figure for wittgenstein projection: percentage of the population age 20-64 by in Belarus is 0.0%, measured in 2100. That is the lowest value across all 19 years on record.
Over the whole period, wittgenstein projection: percentage of the population age 20-64 by in Belarus peaked at 0.0% in 2010 and was at its lowest, 0.0%, in 2015.
That places Belarus 98th out of 166 countries with data for 2100, putting it in the middle of the range.
The series is highly variable year to year, so single readings are best treated with caution.
Wittgenstein Projection: Percentage of the population age 20-64 by in Belarus, year by year
| Year | Value | Change |
|---|---|---|
| 2010 | 0.0% | — |
| 2015 | 0.0% | -100.0% |
| 2020 | 0.0% | — |
| 2025 | 0.0% | — |
| 2030 | 0.0% | — |
| 2035 | 0.0% | — |
| 2040 | 0.0% | — |
| 2045 | 0.0% | — |
| 2050 | 0.0% | — |
| 2055 | 0.0% | — |
| 2060 | 0.0% | — |
| 2065 | 0.0% | — |
| 2070 | 0.0% | — |
| 2075 | 0.0% | — |
| 2080 | 0.0% | — |
| 2085 | 0.0% | — |
| 2090 | 0.0% | — |
| 2095 | 0.0% | — |
| 2100 | 0.0% | — |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.0% | 0.0% | 0.0% | 2 |
| 2020s | 0.0% | 0.0% | 0.0% | 2 |
| 2030s | 0.0% | 0.0% | 0.0% | 2 |
| 2040s | 0.0% | 0.0% | 0.0% | 2 |
| 2050s | 0.0% | 0.0% | 0.0% | 2 |
| 2060s | 0.0% | 0.0% | 0.0% | 2 |
| 2070s | 0.0% | 0.0% | 0.0% | 2 |
| 2080s | 0.0% | 0.0% | 0.0% | 2 |
| 2090s | 0.0% | 0.0% | 0.0% | 2 |
| 2100s | 0.0% | 0.0% | 0.0% | 1 |
Countries ranked near Belarus
- 98 Albania 0.0% compare
- 98 Algeria 0.0% compare
- 98 Armenia 0.0% compare
- 98 Australia 0.0% compare
- 98 Austria 0.0% compare
- 98 Azerbaijan 0.0% compare
- 98 Belgium 0.0% compare
- 98 Bosnia and Herzegovina 0.0% compare
- 98 Bulgaria 0.0% compare
- 98 Canada 0.0% compare
- 98 Chile 0.0% compare
- 98 Croatia 0.0% compare
- 98 Cuba 0.0% compare
- 98 Cyprus 0.0% compare
- 98 Czechia 0.0%
- 98 Denmark 0.0%
- 98 Egypt 0.0% compare
- 98 Estonia 0.0% compare
- 98 Finland 0.0%
- 98 France 0.0% compare
- 98 French Polynesia 0.0% compare
- 98 Georgia 0.0% compare
- 98 Germany 0.0% compare
- 98 Greece 0.0% compare
- 98 Hong Kong 0.0% compare
- 98 Hungary 0.0% compare
- 98 Ireland 0.0% compare
- 98 Italy 0.0% compare
- 98 Japan 0.0% compare
- 98 Jordan 0.0% compare
- 98 Kazakhstan 0.0% compare
- 98 Kenya 0.0% compare
- 98 South Korea 0.0% compare
- 98 Kyrgyzstan 0.0% compare
- 98 Latvia 0.0% compare
- 98 Lithuania 0.0% compare
- 98 Luxembourg 0.0% compare
- 98 Macao 0.0% compare
- 98 Malaysia 0.0% compare
- 98 Malta 0.0% compare
- 98 Moldova 0.0% compare
- 98 Montenegro 0.0% compare
- 98 Netherlands 0.0% compare
- 98 New Caledonia 0.0% compare
- 98 New Zealand 0.0% compare
- 98 North Macedonia 0.0% compare
- 98 Norway 0.0%
- 98 Peru 0.0% compare
- 98 Poland 0.0%
- 98 Puerto Rico 0.0% compare
- 98 Romania 0.0% compare
- 98 Russia 0.0% compare
- 98 Saudi Arabia 0.0% compare
- 98 Serbia 0.0% compare
- 98 Singapore 0.0% compare
- 98 Slovakia 0.0%
- 98 Slovenia 0.0%
- 98 Spain 0.0% compare
- 98 Sweden 0.0% compare
- 98 Switzerland 0.0% compare
- 98 Tajikistan 0.0% compare
- 98 East Timor 0.0% compare
- 98 Tunisia 0.0% compare
- 98 Turkmenistan 0.0% compare
- 98 Ukraine 0.0%
- 98 United States 0.0% compare
- 98 Palestine 0.0% compare
- 98 Zimbabwe 0.0% compare
More reference data data for Belarus
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 1.25 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.3462 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 5.24 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.3596 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 5.24 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 4.18 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 2.85 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 1.84 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 24.26 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 1.96 (2050)
Frequently asked questions
- What is wittgenstein projection: percentage of the population age 20-64 by in Belarus?
- Wittgenstein projection: percentage of the population age 20-64 by in Belarus was 0.0% in 2100, according to Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
- What is the highest wittgenstein projection: percentage of the population age 20-64 by recorded in Belarus?
- The highest recorded value was 0.0% in 2010.
- What is the lowest wittgenstein projection: percentage of the population age 20-64 by recorded in Belarus?
- The lowest recorded value was 0.0% in 2015.
- How does Belarus rank for wittgenstein projection: percentage of the population age 20-64 by?
- Belarus ranks 98th out of 166 countries with data for 2100.
- Where does this Belarus data come from?
- The figures come from Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/, published as part of Wittgenstein Projection: Percentage of the population age 20-64 by highest level of educational attainment. Primary. Female. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 19 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
About this data
Share of the population of the stated age group that has completed primary education or incomplete lower secondary education as the highest level of educational attainment. 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/