Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap in Philippines
Philippines: Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap was 0.02 in 2100. ◆ Volatile
Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap in Philippines, 2010–2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
Philippines recorded 0.02 for wittgenstein projection: mean years of schooling. age 25+. gender gap in 2100. That is the highest value across all 19 years on record.
The figure is up 100.0% over five years.
Over the whole period, wittgenstein projection: mean years of schooling. age 25+. gender gap in Philippines peaked at 0.02 in 2100 and was at its lowest, -0.22, in 2030.
Philippines ranks 91st of 166 countries on this measure, in the middle of the range.
The series is highly variable year to year, so single readings are best treated with caution.
Wittgenstein Projection: Mean Years of Schooling. Age 25+. Gender Gap in Philippines, year by year
| Year | Value | Change |
|---|---|---|
| 2010 | -0.13 | — |
| 2015 | -0.17 | +30.8% |
| 2020 | -0.2 | +17.6% |
| 2025 | -0.21 | +5.0% |
| 2030 | -0.22 | +4.8% |
| 2035 | -0.21 | -4.5% |
| 2040 | -0.2 | -4.8% |
| 2045 | -0.19 | -5.0% |
| 2050 | -0.17 | -10.5% |
| 2055 | -0.14 | -17.6% |
| 2060 | -0.11 | -21.4% |
| 2065 | -0.09 | -18.2% |
| 2070 | -0.07 | -22.2% |
| 2075 | -0.05 | -28.6% |
| 2080 | -0.03 | -40.0% |
| 2085 | -0.01 | -66.7% |
| 2090 | 0 | -100.0% |
| 2095 | 0.01 | — |
| 2100 | 0.02 | +100.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | -0.15 | -0.17 | -0.13 | 2 |
| 2020s | -0.205 | -0.21 | -0.2 | 2 |
| 2030s | -0.215 | -0.22 | -0.21 | 2 |
| 2040s | -0.195 | -0.2 | -0.19 | 2 |
| 2050s | -0.155 | -0.17 | -0.14 | 2 |
| 2060s | -0.1 | -0.11 | -0.09 | 2 |
| 2070s | -0.06 | -0.07 | -0.05 | 2 |
| 2080s | -0.02 | -0.03 | -0.01 | 2 |
| 2090s | 0.005 | 0 | 0.01 | 2 |
| 2100s | 0.02 | 0.02 | 0.02 | 1 |
Countries ranked near Philippines
More reference data data for Philippines
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 2.21 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 2.95 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 12.86 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 1.43 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 12.86 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 7.4 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 10.7 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 15.23 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 67.05 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 7.76 (2050)
Frequently asked questions
- What is wittgenstein projection: mean years of schooling. age 25+. gender gap in Philippines?
- Wittgenstein projection: mean years of schooling. age 25+. gender gap in Philippines was 0.02 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: mean years of schooling. age 25+. gender gap recorded in Philippines?
- The highest recorded value was 0.02 in 2100.
- What is the lowest wittgenstein projection: mean years of schooling. age 25+. gender gap recorded in Philippines?
- The lowest recorded value was -0.22 in 2030.
- How does Philippines rank for wittgenstein projection: mean years of schooling. age 25+. gender gap?
- Philippines ranks 91st out of 166 countries with data for 2100.
- Where does this Philippines 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: Mean Years of Schooling. Age 25+. Gender Gap. 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
The difference between male and female mean number of years spent in school by age group. It is calculated by subtracting the female value from the male value. Data can be negative if the mean years of schooling for females is higher than for males. 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/