Hong Kong vs Saint Kitts and Nevis: Dimension 1.5: Data use by international organizations
Dimension 1.5: Data use by international organizations over time
- Hong Kong
- Saint Kitts and Nevis
How they compare
Hong Kong currently reports 0.6 against 0.6 in Saint Kitts and Nevis, a difference of 0.
The two have swapped places 2 times across 20 shared years of data; in 2004 it was Saint Kitts and Nevis ahead.
Hong Kong ranks 148th and Saint Kitts and Nevis ranks 148th of 217 countries.
Hong Kong has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Hong Kong | Saint Kitts and Nevis | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 0 | 0 | 0 | — |
| 2010s | 0.38 | 0.18 | 0.2 | Hong Kong |
| 2020s | 0.6 | 0.55 | 0.05 | Hong Kong |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher dimension 1.5: data use by international organizations, Hong Kong or Saint Kitts and Nevis?
- Hong Kong, at 0.6 against 0.6 in Saint Kitts and Nevis as of 2023.
- What is the difference in dimension 1.5: data use by international organizations between Hong Kong and Saint Kitts and Nevis?
- 0, with Hong Kong ahead.
- How many years of comparable data are there for Hong Kong and Saint Kitts and Nevis?
- 20 years are reported by both, from 2004 to 2023.
- How do Hong Kong and Saint Kitts and Nevis rank globally for dimension 1.5: data use by international organizations?
- Hong Kong ranks 148th and Saint Kitts and Nevis ranks 148th 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