Wittgenstein Projection: Population in thousands by highest level of e in Serbia
Serbia: Wittgenstein Projection: Population in thousands by highest level of e was 1.71 in 2100. ◆ Volatile
Wittgenstein Projection: Population in thousands by highest level of e in Serbia, 2010–2100
Source: Wittgenstein Centre for Demography and Global Human Capital: http://www.oeaw.ac.at/vid/dataexplorer/.
Analysis
Serbia recorded 1.71 for wittgenstein projection: population in thousands by highest level of e in 2100. That is the lowest value across all 19 years on record.
The figure is down 6.0% over ten years.
Over the whole period, wittgenstein projection: population in thousands by highest level of e in Serbia peaked at 111.58 in 2010 and was at its lowest, 1.71, in 2100.
Serbia ranks 106th 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.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 90.2 | 68.83 | 111.58 | 2 |
| 2020s | 34.12 | 26.29 | 41.95 | 2 |
| 2030s | 15.41 | 13.01 | 17.82 | 2 |
| 2040s | 8.68 | 7.51 | 9.85 | 2 |
| 2050s | 4.99 | 4.3 | 5.68 | 2 |
| 2060s | 3 | 2.68 | 3.32 | 2 |
| 2070s | 2.18 | 2.07 | 2.29 | 2 |
| 2080s | 1.92 | 1.88 | 1.95 | 2 |
| 2090s | 1.79 | 1.76 | 1.82 | 2 |
| 2100s | 1.71 | 1.71 | 1.71 | 1 |
Countries ranked near Serbia
- 103 Cape Verde 1.91 compare
- 104 Slovakia 1.87 compare
- 105 Kyrgyzstan 1.86 compare
- 107 Norway 1.59 compare
- 108 New Zealand 1.56 compare
- 109 Belize 1.47 compare
More reference data data for Serbia
- Emission Totals - Indirect emissions (N2O) - Manure applied to Soils 0.6055 (2050)
- Emission Totals - Indirect emissions (N2O) - Manure left on Pasture 0.3321 (2050)
- Emission Totals - Indirect emissions (N2O) - IPCC Agriculture 3.36 (2050)
- Emission Totals - Indirect emissions (N2O) - Crop Residues 0.3467 (2050)
- Emission Totals - Indirect emissions (N2O) - Agricultural Soils 3.36 (2050)
- Emission Totals - Emissions (N2O) - Manure applied to Soils 2.03 (2050)
- Emission Totals - Emissions (N2O) - Manure Management 1.29 (2050)
- Emission Totals - Emissions (N2O) - Manure left on Pasture 1.44 (2050)
- Emission Totals - Emissions (N2O) - IPCC Agriculture 15.2 (2050)
- Emission Totals - Emissions (N2O) - Crop Residues 1.89 (2050)
Frequently asked questions
- What is wittgenstein projection: population in thousands by highest level of e in Serbia?
- Wittgenstein projection: population in thousands by highest level of e in Serbia was 1.71 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: population in thousands by highest level of e recorded in Serbia?
- The highest recorded value was 111.58 in 2010.
- What is the lowest wittgenstein projection: population in thousands by highest level of e recorded in Serbia?
- The lowest recorded value was 1.71 in 2100.
- How does Serbia rank for wittgenstein projection: population in thousands by highest level of e?
- Serbia ranks 106th out of 166 countries with data for 2100.
- Is wittgenstein projection: population in thousands by highest level of e rising or falling in Serbia?
- Over the last ten years it is down 6.0%. The long-run trend across the full record is volatile.
- Where does this Serbia 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: Population in thousands by highest level of educational attainment. No Education. Female. Statizoid updates them automatically from the source API.
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About this data
Total population in thousands 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/