Statistical performance indicators (SPI): Pillar 4 data sources score in Gambia
Gambia: Statistical performance indicators (SPI): Pillar 4 data sources score was 48.31 scale 0-100 in 2024. ▲ Rising
Statistical performance indicators (SPI): Pillar 4 data sources score in Gambia, 2015–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
Gambia recorded 48.31 scale 0-100 for statistical performance indicators (spi): pillar 4 data sources score in 2024. That is the highest value across all 10 years on record.
The figure is up 5.9% on the previous year and up 13.5% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Gambia peaked at 48.31 scale 0-100 in 2024 and was at its lowest, 36.88 scale 0-100, in 2017.
That places Gambia 119th out of 182 countries with data for 2024, putting it in the middle of the range.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 40.54 scale 0-100 | 36.88 scale 0-100 | 42.7 scale 0-100 | 5 |
| 2020s | 46.64 scale 0-100 | 45.61 scale 0-100 | 48.31 scale 0-100 | 5 |
Countries ranked near Gambia
- 116 Burkina Faso 49.23 scale 0-100 compare
- 117 Sao Tome and Principe 48.59 scale 0-100 compare
- 118 Angola 48.58 scale 0-100 compare
- 119 Saint Vincent and the Grenadines 48.31 scale 0-100 compare
- 121 Vietnam 48.23 scale 0-100 compare
- 122 Lebanon 48.12 scale 0-100 compare
More public sector data for Gambia
- Arms imports 0 SIPRI trend indicator values (2023)
- Military expenditure 0.6% (2024)
- Military expenditure 14.43 million current USD (2024)
- Armed forces personnel, total 4,000 (2020)
- Armed forces personnel 0.6% (2020)
- Statistical performance indicators (SPI): Pillar 1 data use score 90 scale 0-100 (2024)
- Statistical performance indicators (SPI): Pillar 3 data products score 80.19 scale 0-100 (2024)
- Military expenditure 992.92 million current LCU (2024)
- Proportion of seats held by women in national parliaments 8.6% (2025)
- Military expenditure 2.5% (2024)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in Gambia?
- Statistical performance indicators (spi): pillar 4 data sources score in Gambia was 48.31 scale 0-100 in 2024, according to Statistical Performance Indicators, World Bank (WB).
- What is the highest statistical performance indicators (spi): pillar 4 data sources score recorded in Gambia?
- The highest recorded value was 48.31 scale 0-100 in 2024.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Gambia?
- The lowest recorded value was 36.88 scale 0-100 in 2017.
- How does Gambia rank for statistical performance indicators (spi): pillar 4 data sources score?
- Gambia ranks 119th out of 182 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Gambia?
- Over the last ten years it is up 13.5%. The long-run trend across the full record is rising.
- Where does this Gambia data come from?
- The figures come from Statistical Performance Indicators, World Bank (WB), published as part of Statistical performance indicators (SPI): Pillar 4 data sources score (scale 0-100). Statizoid updates them automatically from the source API.
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About this data
The data sources overall score is a composite measure of whether countries have data available from the following sources: Censuses and surveys, administrative data, geospatial data, and private sector/citizen generated data. The data sources (input) pillar is segmented by four types of sources generated by (i) the statistical office (censuses and surveys), and sources accessed from elsewhere such as (ii) administrative data, (iii) geospatial data, and (iv) private sector data and citizen generated data. The appropriate balance between these source types will vary depending on a country's institutional setting and the maturity of its statistical system. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics (in the data production pillar) may reflect a lack of use of (and low score for) geospatial data (in the data sources pillar). This type of linkage is inherent in the data cycle approach and can help highlight areas for investment required if country needs are to be met.