Statistical performance indicators (SPI): Pillar 4 data sources score in Micronesia (country)
Micronesia (country): Statistical performance indicators (SPI): Pillar 4 data sources score was 22.1 scale 0-100 in 2024. ▼ Falling
Statistical performance indicators (SPI): Pillar 4 data sources score in Micronesia (country), 2015–2024
Source: Statistical Performance Indicators, World Bank (WB). Measured in scale 0-100.
Analysis
In 2024, statistical performance indicators (spi): pillar 4 data sources score in Micronesia (country) stood at 22.1 scale 0-100.
That represents a change of down 0.5% on the previous year and up 0.1% over ten years.
Over the whole period, statistical performance indicators (spi): pillar 4 data sources score in Micronesia (country) peaked at 28.49 scale 0-100 in 2016 and was at its lowest, 22.08 scale 0-100, in 2015.
That places Micronesia (country) 169th out of 182 countries with data for 2024, putting it in the bottom quarter.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 25.75 scale 0-100 | 22.08 scale 0-100 | 28.49 scale 0-100 | 5 |
| 2020s | 23.69 scale 0-100 | 22.1 scale 0-100 | 28.07 scale 0-100 | 5 |
Countries ranked near Micronesia (country)
- 166 Chad 24.74 scale 0-100 compare
- 167 Democratic Republic of Congo 24.35 scale 0-100 compare
- 168 Congo 23.85 scale 0-100 compare
- 170 Afghanistan 20.68 scale 0-100 compare
- 171 Yemen 20.52 scale 0-100 compare
- 172 Guinea-Bissau 19.92 scale 0-100 compare
More public sector data for Micronesia (country)
- Arms imports 7.00 million SIPRI trend indicator values (2023)
- Tax revenue 7.0% (2020)
- Taxes on income, profits and capital gains 10.9% (2020)
- Taxes on goods and services 3.4% (2020)
- Net investment in nonfinancial assets 10.5% (2020)
- Net lending (+) / net borrowing (-) 6.9% (2020)
- Interest payments 0.4% (2020)
- Grants and other revenue 81.0% (2020)
- Interest payments 0.6% (2020)
- Other taxes 0.2% (2020)
Frequently asked questions
- What is statistical performance indicators (spi): pillar 4 data sources score in Micronesia (country)?
- Statistical performance indicators (spi): pillar 4 data sources score in Micronesia (country) was 22.1 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 Micronesia (country)?
- The highest recorded value was 28.49 scale 0-100 in 2016.
- What is the lowest statistical performance indicators (spi): pillar 4 data sources score recorded in Micronesia (country)?
- The lowest recorded value was 22.08 scale 0-100 in 2015.
- How does Micronesia (country) rank for statistical performance indicators (spi): pillar 4 data sources score?
- Micronesia (country) ranks 169th out of 182 countries with data for 2024.
- Is statistical performance indicators (spi): pillar 4 data sources score rising or falling in Micronesia (country)?
- Over the last ten years it is up 0.1%. The long-run trend across the full record is falling.
- Where does this Micronesia (country) 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.