Saint Vincent and the Grenadines vs Tuvalu: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Saint Vincent and the Grenadines
- Tuvalu
How they compare
Saint Vincent and the Grenadines currently reports 0.5 against 0.5 in Tuvalu, a difference of 0.
The two have swapped places 6 times across 20 shared years of data; in 2004 it was Tuvalu ahead.
Saint Vincent and the Grenadines ranks 175th and Tuvalu ranks 175th of 217 countries.
Tuvalu has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Saint Vincent and the Grenadines | Tuvalu | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0.2 | 0.2 | 0 | — |
| 2010s | 0.28 | 0.3 | 0.02 | Tuvalu |
| 2020s | 0.5 | 0.5 | 0 | — |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 1.5: data use by international organizations, Saint Vincent and the Grenadines or Tuvalu?
- Saint Vincent and the Grenadines, at 0.5 against 0.5 in Tuvalu as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Saint Vincent and the Grenadines and Tuvalu?
- 0, with Saint Vincent and the Grenadines ahead.
- How many years of comparable data are there for Saint Vincent and the Grenadines and Tuvalu?
- 20 years are reported by both, from 2004 to 2023.
- How do Saint Vincent and the Grenadines and Tuvalu rank globally for dimension 1.5: data use by international organizations?
- Saint Vincent and the Grenadines ranks 175th and Tuvalu ranks 175th 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