Singapore Human Capital Index
Singapore SG: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1
SG: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data was reported at 0.883 NA in 2017. SG: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.883 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.883 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Female: Scale 0-1
SG: Human Capital Index (HCI): Female: Scale 0-1 data was reported at 0.899 NA in 2017. SG: Human Capital Index (HCI): Female: Scale 0-1 data is updated yearly, averaging 0.899 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Female: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.899 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Female: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1
SG: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data was reported at 0.914 NA in 2017. SG: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.914 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.914 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Lower Bound: Scale 0-1
SG: Human Capital Index (HCI): Lower Bound: Scale 0-1 data was reported at 0.868 NA in 2017. SG: Human Capital Index (HCI): Lower Bound: Scale 0-1 data is updated yearly, averaging 0.868 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Lower Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.868 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1
SG: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data was reported at 0.851 NA in 2017. SG: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.851 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.851 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Male: Scale 0-1
SG: Human Capital Index (HCI): Male: Scale 0-1 data was reported at 0.871 NA in 2017. SG: Human Capital Index (HCI): Male: Scale 0-1 data is updated yearly, averaging 0.871 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Male: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.871 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Male: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1
SG: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data was reported at 0.889 NA in 2017. SG: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.889 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.889 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Scale 0-1
SG: Human Capital Index (HCI): Scale 0-1 data was reported at 0.884 NA in 2017. SG: Human Capital Index (HCI): Scale 0-1 data is updated yearly, averaging 0.884 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.884 2017 | yearly | 2017 - 2017 |
View Singapore's Singapore SG: Human Capital Index (HCI): Scale 0-1 from 2017 to 2017 in the chart:
Singapore SG: Human Capital Index (HCI): Upper Bound: Scale 0-1
SG: Human Capital Index (HCI): Upper Bound: Scale 0-1 data was reported at 0.900 NA in 2017. SG: Human Capital Index (HCI): Upper Bound: Scale 0-1 data is updated yearly, averaging 0.900 NA from Dec 2017 (Median) to 2017, with 1 observations. SG: Human Capital Index (HCI): Upper Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank: Human Capital Index. The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;
| Last | Frequency | Range |
|---|---|---|
| 0.900 2017 | yearly | 2017 - 2017 |