Liberia vs San Marino: Statistical performance indicators (SPI): Pillar 2 data services score
Statistical performance indicators (SPI): Pillar 2 data services score over time
- Liberia
- San Marino
How they compare
San Marino currently reports 60.73 scale 0-100 against 59.93 scale 0-100 in Liberia, a difference of 0.8 scale 0-100.
The two have swapped places 1 time across 5 shared years of data; in 2020 it was Liberia ahead.
Liberia ranks 152nd and San Marino ranks 151st of 183 countries.
Liberia has averaged higher in every one of the 1 decades both report.
Frequently asked questions
- Which has higher statistical performance indicators (spi): pillar 2 data services score, Liberia or San Marino?
- San Marino, at 60.73 scale 0-100 against 59.93 scale 0-100 in Liberia as of 2024.
- What is the difference in statistical performance indicators (spi): pillar 2 data services score between Liberia and San Marino?
- 0.8 scale 0-100, with San Marino ahead.
- How many years of comparable data are there for Liberia and San Marino?
- 5 years are reported by both, from 2020 to 2024.
- How do Liberia and San Marino rank globally for statistical performance indicators (spi): pillar 2 data services score?
- Liberia ranks 152nd and San Marino ranks 151st of 183 countries.
- Where does this data come from?
- Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 2 data services score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.
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About this data
The data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including input to national data strategies, advice on data ethics and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.