Hungary vs Mexico: Statistical performance: Pillar 5 data infrastructure score
Statistical performance: Pillar 5 data infrastructure score over time
- Hungary
- Mexico
How they compare
Hungary currently reports 80 scale 0-100 against 80 scale 0-100 in Mexico, a difference of 0 scale 0-100.
The two have swapped places 1 time across 9 shared years of data; in 2016 it was Hungary ahead.
Hungary ranks 50th and Mexico ranks 50th of 192 countries.
Hungary has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Hungary | Mexico | Difference | Ahead |
|---|---|---|---|---|
| 2010s | 100 scale 0-100 | 68.75 scale 0-100 | 31.25 scale 0-100 | Hungary |
| 2020s | 92 scale 0-100 | 78 scale 0-100 | 14 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, Hungary or Mexico?
- Hungary, at 80 scale 0-100 against 80 scale 0-100 in Mexico as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 5 data between Hungary and Mexico?
- 0 scale 0-100, with Hungary ahead.
- How many years of comparable data are there for Hungary and Mexico?
- 9 years are reported by both, from 2016 to 2024.
- How do Hungary and Mexico rank globally for statistical performance indicators (spi): pillar 5 data?
- Hungary ranks 50th and Mexico 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.