Gabon vs Tonga: Statistical performance indicators (SPI): Pillar 5 data infrastructure
Statistical performance indicators (SPI): Pillar 5 data infrastructure over time
- Gabon
- Tonga
How they compare
Gabon currently reports 45 scale 0-100 against 45 scale 0-100 in Tonga, a difference of 0 scale 0-100.
Across all 9 years both countries report, Tonga has been ahead every year.
Gabon ranks 150th and Tonga ranks 150th of 190 countries.
Tonga has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Gabon | Tonga | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 20 scale 0-100 | 32.5 scale 0-100 | 12.5 scale 0-100 | Tonga |
| 2020s | 40 scale 0-100 | 40 scale 0-100 | 0 scale 0-100 | — |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data infrastructure, Gabon or Tonga?
- Gabon, at 45 scale 0-100 against 45 scale 0-100 in Tonga as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data infrastructure between Gabon and Tonga?
- 0 scale 0-100, with Gabon ahead.
- How many years of comparable data are there for Gabon and Tonga?
- 9 years are reported by both, from 2016 to 2024.
- How do Gabon and Tonga rank globally for statistical performance indicators (spi): pillar 5 data infrastructure?
- Gabon ranks 150th and Tonga ranks 150th of 190 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 5 data infrastructure score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.