Northern Mariana Islands vs Sudan: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Northern Mariana Islands
- Sudan
How they compare
Sudan currently reports 0.466 against 0.4 in Northern Mariana Islands, a difference of 0.066.
That makes Sudan's figure about 1.2 times Northern Mariana Islands's.
Across all 20 years both countries report, Sudan has been ahead every year.
Northern Mariana Islands ranks 190th and Sudan ranks 187th of 217 countries.
Sudan has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Northern Mariana Islands | Sudan | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0.2 | 0.2 | Sudan |
| 2010s | 0.24 | 0.4936 | 0.2536 | 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, Northern Mariana Islands or Sudan?
- Sudan, at 0.466 against 0.4 in Northern Mariana Islands as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Northern Mariana Islands and Sudan?
- 0.066, with Sudan ahead.
- How many years of comparable data are there for Northern Mariana Islands and Sudan?
- 20 years are reported by both, from 2004 to 2023.
- How do Northern Mariana Islands and Sudan rank globally for dimension 1.5: data use by international organizations?
- Northern Mariana Islands ranks 190th and Sudan ranks 187th 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