Dimension 1.5: Data use by international organizations in Guam
Guam: Dimension 1.5: Data use by international organizations was 0.4 in 2023. ◆ Volatile
Dimension 1.5: Data use by international organizations in Guam, 2004–2023
Source: Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).
Analysis
In 2023, dimension 1.5: data use by international organizations in Guam stood at 0.4.
That represents a change of up 100.0% over ten years.
Over the whole period, dimension 1.5: data use by international organizations in Guam peaked at 0.6 in 2016 and was at its lowest, 0, in 2004.
That places Guam 188th out of 214 countries with data for 2023, putting it in the bottom quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2000s | 0 | 0 | 0 | 6 |
| 2010s | 0.32 | 0.2 | 0.6 | 10 |
| 2020s | 0.4 | 0.4 | 0.4 | 4 |
Countries ranked near Guam
- 185 Sudan 0.466 compare
- 185 Suriname 0.466 compare
- 185 Syria 0.466 compare
- 188 American Samoa 0.4 compare
- 188 Aruba 0.4 compare
- 188 Bermuda 0.4 compare
- 188 British Virgin Islands 0.4 compare
- 188 Cuba 0.4 compare
- 188 Faroe Islands 0.4 compare
- 188 French Polynesia 0.4 compare
- 188 Gibraltar 0.4 compare
- 188 Greenland 0.4 compare
- 188 Isle of Man 0.4 compare
- 188 Northern Mariana Islands 0.4 compare
- 188 Puerto Rico 0.4 compare
- 188 South Sudan 0.4 compare
- 188 Saint Martin (French part) 0.4 compare
- 188 United States Virgin Islands 0.4 compare
More reference data data for Guam
- Emission Totals - Emissions (CO2eq) (AR5) - Agricultural Soils 0.0037 (2050)
- Emission Totals - Emissions (N2O) - Burning - Crop residues 0 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture 0.004 (2050)
- Emission Totals - Direct emissions (N2O) - Crop Residues 0 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Crop Residues 0.0037 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Agricultural Soil 0.0037 (2050)
- Emission Totals - Emissions (CO2eq) from N2O (AR5) - Burning - Crop re 0.0003 (2050)
- Emission Totals - Direct emissions (N2O) - IPCC Agriculture 0 (2050)
- Emission Totals - Emissions (CH4) - IPCC Agriculture 0 (2050)
- Emission Totals - Emissions (CO2eq) (AR5) - IPCC Agriculture 0.0052 (2050)
Frequently asked questions
- What is dimension 1.5: data use by international organizations in Guam?
- Dimension 1.5: data use by international organizations in Guam was 0.4 in 2023, according to Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators).
- What is the highest dimension 1.5: data use by international organizations recorded in Guam?
- The highest recorded value was 0.6 in 2016.
- What is the lowest dimension 1.5: data use by international organizations recorded in Guam?
- The lowest recorded value was 0 in 2004.
- How does Guam rank for dimension 1.5: data use by international organizations?
- Guam ranks 188th out of 214 countries with data for 2023.
- Is dimension 1.5: data use by international organizations rising or falling in Guam?
- Over the last ten years it is up 100.0%. The long-run trend across the full record is volatile.
- Where does this Guam data come from?
- The figures come from Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators), published as part of Dimension 1.5: Data use by international organizations. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 20 observations, free to reuse under CC BY 4.0 (World Bank Open Data).
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