Northern Mariana Islands vs South Sudan: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Northern Mariana Islands
- South Sudan
How they compare
Northern Mariana Islands currently reports 0.4 against 0.4 in South Sudan, a difference of 0.
The two have swapped places 2 times across 20 shared years of data; in 2004 it was South Sudan ahead.
Northern Mariana Islands ranks 191st and South Sudan ranks 191st of 217 countries.
Across the 3 decades both report, Northern Mariana Islands averaged higher in 1 and South Sudan in 1.
Head to head by decade
| Decade | Northern Mariana Islands | South Sudan | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0.2 | 0.2 | South Sudan |
| 2010s | 0.24 | 0.22 | 0.02 | Northern Mariana Islands |
| 2020s | 0.4 | 0.4 | 0 | — |
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 South Sudan?
- Northern Mariana Islands, at 0.4 against 0.4 in South Sudan as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Northern Mariana Islands and South Sudan?
- 0, with Northern Mariana Islands ahead.
- How many years of comparable data are there for Northern Mariana Islands and South Sudan?
- 20 years are reported by both, from 2004 to 2023.
- How do Northern Mariana Islands and South Sudan rank globally for dimension 1.5: data use by international organizations?
- Northern Mariana Islands ranks 191st and South Sudan ranks 191st 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