Croatia vs Latvia: Statistical performance indicators (SPI): Pillar 3 data products score
Statistical performance indicators (SPI): Pillar 3 data products score over time
- Croatia
- Latvia
How they compare
Latvia currently reports 81.81 scale 0-100 against 81.77 scale 0-100 in Croatia, a difference of 0.04 scale 0-100.
The two have swapped places 3 times across 20 shared years of data; in 2005 it was Croatia ahead.
Croatia ranks 47th and Latvia ranks 46th of 215 countries.
Across the 3 decades both report, Croatia averaged higher in 2 and Latvia in 1.
Head to head by decade
| Decade | Croatia | Latvia | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 51.05 scale 0-100 | 40.95 scale 0-100 | 10.1 scale 0-100 | Croatia |
| 2010s | 53.59 scale 0-100 | 51.82 scale 0-100 | 1.77 scale 0-100 | Croatia |
| 2020s | 72.29 scale 0-100 | 76.01 scale 0-100 | 3.72 scale 0-100 | Latvia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 3 data products score, Croatia or Latvia?
- Latvia, at 81.81 scale 0-100 against 81.77 scale 0-100 in Croatia as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 3 data products score between Croatia and Latvia?
- 0.04 scale 0-100, with Latvia ahead.
- How many years of comparable data are there for Croatia and Latvia?
- 20 years are reported by both, from 2005 to 2024.
- How do Croatia and Latvia rank globally for statistical performance indicators (spi): pillar 3 data products score?
- Croatia ranks 47th and Latvia ranks 46th of 215 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 3 data products 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 products overall score is a composite score measuring whether the country is able to produce relevant indicators, primarily related to SDGs. The data products (internal process) pillar is segmented by four topics and organized into (i) social, (ii) economic, (iii) environmental, and (iv) institutional dimensions using the typology of the Sustainable Development Goals (SDGs). This approach anchors the national statistical system's performance around the essential data required to support the achievement of the 2030 global goals, and enables comparisons across countries so that a global view can be generated while enabling country specific emphasis to reflect the user needs of that country.