Colombia vs Hungary: Statistical performance: Pillar 5 data infrastructure score
Statistical performance: Pillar 5 data infrastructure score over time
- Colombia
- Hungary
How they compare
Colombia currently reports 80 scale 0-100 against 80 scale 0-100 in Hungary, a difference of 0 scale 0-100.
Across all 9 years both countries report, Hungary has been ahead every year.
Colombia ranks 50th and Hungary ranks 50th of 192 countries.
Hungary has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Colombia | Hungary | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 50 scale 0-100 | 100 scale 0-100 | 50 scale 0-100 | Hungary |
| 2020s | 76 scale 0-100 | 92 scale 0-100 | 16 scale 0-100 | Hungary |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 5 data, Colombia or Hungary?
- Colombia, at 80 scale 0-100 against 80 scale 0-100 in Hungary as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data between Colombia and Hungary?
- 0 scale 0-100, with Colombia ahead.
- How many years of comparable data are there for Colombia and Hungary?
- 9 years are reported by both, from 2016 to 2024.
- How do Colombia and Hungary rank globally for statistical performance indicators (spi): pillar 5 data?
- Colombia ranks 50th and Hungary ranks 50th 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.