Saint Kitts and Nevis vs Venezuela: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Saint Kitts and Nevis
- Venezuela
How they compare
Saint Kitts and Nevis currently reports 0.6 against 0.6 in Venezuela, a difference of 0.
Across all 20 years both countries report, Venezuela has been ahead every year.
Saint Kitts and Nevis ranks 148th and Venezuela ranks 148th of 216 countries.
Venezuela has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Saint Kitts and Nevis | Venezuela | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0.4 | 0.4 | Venezuela |
| 2010s | 0.18 | 0.5432 | 0.3632 | Venezuela |
| 2020s | 0.55 | 0.633 | 0.083 | Venezuela |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 1.5: data use by international organizations, Saint Kitts and Nevis or Venezuela?
- Saint Kitts and Nevis, at 0.6 against 0.6 in Venezuela as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Saint Kitts and Nevis and Venezuela?
- 0, with Saint Kitts and Nevis ahead.
- How many years of comparable data are there for Saint Kitts and Nevis and Venezuela?
- 20 years are reported by both, from 2004 to 2023.
- How do Saint Kitts and Nevis and Venezuela rank globally for dimension 1.5: data use by international organizations?
- Saint Kitts and Nevis ranks 148th and Venezuela ranks 148th 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