Wittgenstein Projection: Percentage of the population age 40-64 by in French Polynesia
French Polynesia: Wittgenstein Projection: Percentage of the population age 40-64 by was 0.0% in 2100. ◆ Volatile
Wittgenstein Projection: Percentage of the population age 40-64 by in French Polynesia, 2010–2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
French Polynesia recorded 0.0% for wittgenstein projection: percentage of the population age 40-64 by in 2100. That is the lowest value across all 19 years on record.
Over the whole period, wittgenstein projection: percentage of the population age 40-64 by in French Polynesia peaked at 0.2% in 2010 and was at its lowest, 0.0%, in 2090.
That places French Polynesia 103rd 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 40-64 by in French Polynesia, year by year
| Year | Value | Change |
|---|---|---|
| 2010 | 0.2% | — |
| 2015 | 0.1% | -16.7% |
| 2020 | 0.1% | -26.7% |
| 2025 | 0.1% | -27.3% |
| 2030 | 0.1% | -25.0% |
| 2035 | 0.0% | -33.3% |
| 2040 | 0.0% | -25.0% |
| 2045 | 0.0% | -33.3% |
| 2050 | 0.0% | +0.0% |
| 2055 | 0.0% | +0.0% |
| 2060 | 0.0% | -50.0% |
| 2065 | 0.0% | +0.0% |
| 2070 | 0.0% | +0.0% |
| 2075 | 0.0% | +0.0% |
| 2080 | 0.0% | +0.0% |
| 2085 | 0.0% | +0.0% |
| 2090 | 0.0% | -100.0% |
| 2095 | 0.0% | — |
| 2100 | 0.0% | — |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 0.2% | 0.1% | 0.2% | 2 |
| 2020s | 0.1% | 0.1% | 0.1% | 2 |
| 2030s | 0.1% | 0.0% | 0.1% | 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 French Polynesia
- 103 Albania 0.0% compare
- 103 Algeria 0.0% compare
- 103 Armenia 0.0% compare
- 103 Australia 0.0% compare
- 103 Austria 0.0% compare
- 103 Azerbaijan 0.0% compare
- 103 Belarus 0.0% compare
- 103 Belgium 0.0% compare
- 103 Bosnia and Herzegovina 0.0% compare
- 103 Bulgaria 0.0% compare
- 103 Canada 0.0% compare
- 103 Croatia 0.0% compare
- 103 Cuba 0.0% compare
- 103 Cyprus 0.0% compare
- 103 Czechia 0.0%
- 103 Denmark 0.0% compare
- 103 Egypt 0.0% compare
- 103 Estonia 0.0% compare
- 103 Finland 0.0%
- 103 France 0.0% compare
- 103 Georgia 0.0% compare
- 103 Germany 0.0% compare
- 103 Greece 0.0% compare
- 103 Hong Kong, China 0.0% compare
- 103 Hungary 0.0% compare
- 103 Ireland 0.0% compare
- 103 Italy 0.0% compare
- 103 Japan 0.0% compare
- 103 Kazakhstan 0.0% compare
- 103 Kenya 0.0% compare
- 103 Republic of Korea 0.0% compare
- 103 Kyrgyzstan 0.0% compare
- 103 Latvia 0.0% compare
- 103 Lithuania 0.0% compare
- 103 Macau, China 0.0% compare
- 103 Malaysia 0.0% compare
- 103 Malta 0.0% compare
- 103 Republic of Moldova 0.0% compare
- 103 Montenegro 0.0% compare
- 103 Netherlands 0.0% compare
- 103 New Caledonia 0.0% compare
- 103 New Zealand 0.0% compare
- 103 North Macedonia 0.0% compare
- 103 Norway 0.0%
- 103 Poland 0.0%
- 103 Puerto Rico 0.0% compare
- 103 Romania 0.0% compare
- 103 Russian Federation 0.0% compare
- 103 Saudi Arabia 0.0% compare
- 103 Serbia 0.0% compare
- 103 Singapore 0.0% compare
- 103 Slovakia 0.0%
- 103 Slovenia 0.0%
- 103 Spain 0.0% compare
- 103 Sweden 0.0% compare
- 103 Switzerland 0.0% compare
- 103 Tajikistan 0.0% compare
- 103 Tunisia 0.0% compare
- 103 Turkmenistan 0.0% compare
- 103 Ukraine 0.0%
- 103 United States of America 0.0% compare
- 103 Palestine, State of 0.0% compare
- 103 Zimbabwe 0.0% compare
More reference data data for French Polynesia
- Emission Totals - Emissions (N2O) - Burning - Crop residues 0 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure applied to Soils 5.57 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 19.48 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Manure Management 30.14 (2050)
- Emission Totals - Emissions (N2O) - Agricultural Soils 0.0603 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 0.021 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - IPCC Agriculture 69.03 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - Enteric Fermentation 22.9 (2050)
- Emission Totals - Direct emissions (N2O) - IPCC Agriculture 0.0455 (2050)
- Emission Totals - Direct emissions (N2O) - Manure applied to Soils 0.0147 (2050)
Frequently asked questions
- What is wittgenstein projection: percentage of the population age 40-64 by in French Polynesia?
- Wittgenstein projection: percentage of the population age 40-64 by in French Polynesia 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 40-64 by recorded in French Polynesia?
- The highest recorded value was 0.2% in 2010.
- What is the lowest wittgenstein projection: percentage of the population age 40-64 by recorded in French Polynesia?
- The lowest recorded value was 0.0% in 2090.
- How does French Polynesia rank for wittgenstein projection: percentage of the population age 40-64 by?
- French Polynesia ranks 103rd out of 166 countries with data for 2100.
- Where does this French Polynesia 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 40-64 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/