Cambodia vs Togo: Statistical performance: Pillar 5 data infrastructure score
Statistical performance: Pillar 5 data infrastructure score over time
- Cambodia
- Togo
How they compare
Cambodia currently reports 65 scale 0-100 against 65 scale 0-100 in Togo, a difference of 0 scale 0-100.
The two have swapped places 3 times across 9 shared years of data; in 2016 it was Cambodia ahead.
Cambodia ranks 93rd and Togo ranks 93rd of 192 countries.
Across the 2 decades both report, Cambodia averaged higher in 1 and Togo in 1.
Head to head by decade
| Decade | Cambodia | Togo | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 41.25 scale 0-100 | 36.25 scale 0-100 | 5 scale 0-100 | Cambodia |
| 2020s | 55 scale 0-100 | 57 scale 0-100 | 2 scale 0-100 | Togo |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data, Cambodia or Togo?
- Cambodia, at 65 scale 0-100 against 65 scale 0-100 in Togo as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data between Cambodia and Togo?
- 0 scale 0-100, with Cambodia ahead.
- How many years of comparable data are there for Cambodia and Togo?
- 9 years are reported by both, from 2016 to 2024.
- How do Cambodia and Togo rank globally for statistical performance indicators (spi): pillar 5 data?
- Cambodia ranks 93rd and Togo ranks 93rd of 192 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.