Saint Martin (French part) vs Sudan: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Saint Martin (French part)
- Sudan
How they compare
Sudan currently reports 0.466 against 0.4 in Saint Martin (French part), a difference of 0.066.
That makes Sudan's figure about 1.2 times Saint Martin (French part)'s.
Across all 20 years both countries report, Sudan has been ahead every year.
Saint Martin (French part) ranks 190th and Sudan ranks 187th of 216 countries.
Sudan has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Saint Martin (French part) | Sudan | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0.2 | 0.2 | Sudan |
| 2010s | 0.18 | 0.4936 | 0.3136 | Sudan |
| 2020s | 0.4 | 0.517 | 0.117 | Sudan |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 1.5: data use by international organizations, Saint Martin (French part) or Sudan?
- Sudan, at 0.466 against 0.4 in Saint Martin (French part) as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Saint Martin (French part) and Sudan?
- 0.066, with Sudan ahead.
- How many years of comparable data are there for Saint Martin (French part) and Sudan?
- 20 years are reported by both, from 2004 to 2023.
- How do Saint Martin (French part) and Sudan rank globally for dimension 1.5: data use by international organizations?
- Saint Martin (French part) ranks 190th and Sudan ranks 187th of 216 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