Statistical performance indicators (SPI): Pillar 4 data sources score in East Timor
East Timor: Statistical performance indicators (SPI): Pillar 4 data sources score was 42.79 scale 0-100 in 2024. ▲ Rising
Statistical performance indicators (SPI): Pillar 4 data sources score in East Timor, 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 East Timor is 42.79 scale 0-100, measured in 2024. That is the highest value across all 10 years on record.
The figure is up 11.7% on the previous year and up 45.9% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in East Timor peaked at 42.79 scale 0-100 in 2024 and was at its lowest, 29.33 scale 0-100, in 2015.
That places East Timor 139th out of 182 countries with data for 2024, putting it in the bottom quarter.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 33.35 scale 0-100 | 29.33 scale 0-100 | 39.39 scale 0-100 | 5 |
| 2020s | 39.8 scale 0-100 | 38.32 scale 0-100 | 42.79 scale 0-100 | 5 |
Countries ranked near East Timor
- 136 Vanuatu 43.48 scale 0-100 compare
- 137 Cote d'Ivoire 43.38 scale 0-100 compare
- 138 Mali 43.33 scale 0-100 compare
- 140 Zambia 42.28 scale 0-100 compare
- 141 Trinidad and Tobago 41.71 scale 0-100 compare
- 142 Sierra Leone 41.69 scale 0-100 compare
More public sector data for East Timor
- Tax revenue 21.6% (2022)
- Taxes on income, profits and capital gains 30.2% (2022)
- Taxes on goods and services 5.4% (2022)
- Net investment in nonfinancial assets 4.4% (2022)
- Net lending (+) / net borrowing (-) 1.6% (2022)
- Interest payments 0.1% (2022)
- Grants and other revenue 63.0% (2022)
- Interest payments 0.1% (2022)
- Other taxes 0.1% (2022)
- Compensation of employees 14.7% (2022)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in East Timor?
- Statistical performance indicators (spi): pillar 4 data sources score in East Timor was 42.79 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 East Timor?
- The highest recorded value was 42.79 scale 0-100 in 2024.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in East Timor?
- The lowest recorded value was 29.33 scale 0-100 in 2015.
- How does East Timor rank for statistical performance indicators (spi): pillar 4 data sources score?
- East Timor ranks 139th out of 182 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in East Timor?
- Over the last ten years it is up 45.9%. The long-run trend across the full record is rising.
- Where does this East Timor 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.
Download this data
CSV · JSON — 10 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
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.