Statistical performance indicators (SPI): Pillar 4 data sources score in Palestine
Palestine: Statistical performance indicators (SPI): Pillar 4 data sources score was 73.2 scale 0-100 in 2024. ▲ Rising
Statistical performance indicators (SPI): Pillar 4 data sources score in Palestine, 2015–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
The most recent figure for statistical performance indicators (spi): pillar 4 data sources score in Palestine is 73.2 scale 0-100, measured in 2024. That is the highest value across all 10 years on record.
Compared with earlier readings it is up 6.7% on the previous year and up 60.2% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Palestine peaked at 73.2 scale 0-100 in 2024 and was at its lowest, 45.69 scale 0-100, in 2015.
That places Palestine 56th out of 181 countries with data for 2024, putting it in the middle of the range.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 56.88 scale 0-100 | 45.69 scale 0-100 | 61.57 scale 0-100 | 5 |
| 2020s | 68.82 scale 0-100 | 66.07 scale 0-100 | 73.2 scale 0-100 | 5 |
Countries ranked near Palestine
More public sector data for Palestine
- Arms imports 2.00 million SIPRI trend indicator values (2023)
- Armed forces personnel, total 0 (2020)
- Armed forces personnel 0.0% (2020)
- Expense 4.74 billion current LCU (2021)
- Statistical performance indicators (SPI): Pillar 1 data use score 70 scale 0-100 (2024)
- Intentional homicides 0.622 per 100,000 people (2022)
- Statistical performance indicators (SPI): Pillar 3 data products score 71.47 scale 0-100 (2024)
- Internally displaced persons, new displacement associated with disaste 250 number of cases (2022)
- Primary government expenditures as a proportion of original approved b 91.2% (2024)
- Statistical performance indicators (SPI): Pillar 5 data infrastructure 65 scale 0-100 (2024)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in Palestine?
- Statistical performance indicators (spi): pillar 4 data sources score in Palestine was 73.2 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 Palestine?
- The highest recorded value was 73.2 scale 0-100 in 2024.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Palestine?
- The lowest recorded value was 45.69 scale 0-100 in 2015.
- How does Palestine rank for statistical performance indicators (spi): pillar 4 data sources score?
- Palestine ranks 56th out of 181 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Palestine?
- Over the last ten years it is up 60.2%. The long-run trend across the full record is rising.
- Where does this Palestine 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.