San Marino vs Saint Lucia: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- San Marino
- Saint Lucia
How they compare
San Marino currently reports 0.7 against 0.7 in Saint Lucia, a difference of 0.
Across all 20 years both countries report, Saint Lucia has been ahead every year.
San Marino ranks 134th and Saint Lucia ranks 134th of 217 countries.
Saint Lucia has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | San Marino | Saint Lucia | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0.1333 | 0.1333 | Saint Lucia |
| 2010s | 0.23 | 0.68 | 0.45 | Saint Lucia |
| 2020s | 0.65 | 0.75 | 0.1 | Saint Lucia |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 1.5: data use by international organizations, San Marino or Saint Lucia?
- San Marino, at 0.7 against 0.7 in Saint Lucia as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between San Marino and Saint Lucia?
- 0, with San Marino ahead.
- How many years of comparable data are there for San Marino and Saint Lucia?
- 20 years are reported by both, from 2004 to 2023.
- How do San Marino and Saint Lucia rank globally for dimension 1.5: data use by international organizations?
- San Marino ranks 134th and Saint Lucia ranks 134th of 217 countries.
- Where does this data come from?
- Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators), published as Dimension 1.5: Data use by international organizations. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
Five measures usefulness or reliability of country produced measures for international organizations. First, on comparability of poverty estimates for the World Bank reporting on international poverty (Source: Povcalnet). Second on usable surveys for statistics on child mortality for the UN Inter-agency Group for Child Mortality Estimation (Source: https://childmortality.org/). Third on accuracy of debt reporting as classified by the World Bank (Source: World Bank WDI metadata). Fourth, on availability of safely managed drinking water data for use by JMP. Fifth, on labor force participation data for use by ILO. We recognize that these data sources provide only partial coverage but consider that they do at least provide some indication of the performance of the national statistical system. With more complete data sources it would be possible to assess this further