Bolivia vs Cambodia: Statistical performance: Pillar 5 data infrastructure score
Statistical performance: Pillar 5 data infrastructure score over time
- Bolivia
- Cambodia
How they compare
Bolivia currently reports 65 scale 0-100 against 65 scale 0-100 in Cambodia, a difference of 0 scale 0-100.
Across all 9 years both countries report, Cambodia has been ahead every year.
Bolivia ranks 93rd and Cambodia ranks 93rd of 192 countries.
Cambodia has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Bolivia | Cambodia | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 16.25 scale 0-100 | 41.25 scale 0-100 | 25 scale 0-100 | Cambodia |
| 2020s | 48 scale 0-100 | 55 scale 0-100 | 7 scale 0-100 | Cambodia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data, Bolivia or Cambodia?
- Bolivia, at 65 scale 0-100 against 65 scale 0-100 in Cambodia as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data between Bolivia and Cambodia?
- 0 scale 0-100, with Bolivia ahead.
- How many years of comparable data are there for Bolivia and Cambodia?
- 9 years are reported by both, from 2016 to 2024.
- How do Bolivia and Cambodia rank globally for statistical performance indicators (spi): pillar 5 data?
- Bolivia ranks 93rd and Cambodia 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.