Malaysia Human Capital Index
Malaysia Human Capital Index (HCI): Female: Lower Bound: Scale 0-1
MY: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data was reported at 0.634 NA in 2017. MY: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.634 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.634 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Female: Scale 0-1
MY: Human Capital Index (HCI): Female: Scale 0-1 data was reported at 0.645 NA in 2017. MY: Human Capital Index (HCI): Female: Scale 0-1 data is updated yearly, averaging 0.645 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.645 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Female: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Female: Upper Bound: Scale 0-1
MY: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data was reported at 0.657 NA in 2017. MY: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.657 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.657 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Lower Bound: Scale 0-1
MY: Human Capital Index (HCI): Lower Bound: Scale 0-1 data was reported at 0.611 NA in 2017. MY: Human Capital Index (HCI): Lower Bound: Scale 0-1 data is updated yearly, averaging 0.611 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.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 |
|---|---|---|
| 0.611 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Male: Lower Bound: Scale 0-1
MY: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data was reported at 0.590 NA in 2017. MY: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.590 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.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 |
|---|---|---|
| 0.590 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Male: Scale 0-1
MY: Human Capital Index (HCI): Male: Scale 0-1 data was reported at 0.601 NA in 2017. MY: Human Capital Index (HCI): Male: Scale 0-1 data is updated yearly, averaging 0.601 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.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 |
|---|---|---|
| 0.601 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Male: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Male: Upper Bound: Scale 0-1
MY: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data was reported at 0.613 NA in 2017. MY: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.613 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.613 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Scale 0-1
MY: Human Capital Index (HCI): Scale 0-1 data was reported at 0.622 NA in 2017. MY: Human Capital Index (HCI): Scale 0-1 data is updated yearly, averaging 0.622 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.622 2017 | yearly | 2017 - 2017 |
View Malaysia's Malaysia Human Capital Index (HCI): Scale 0-1 from 2017 to 2017 in the chart:
Malaysia Human Capital Index (HCI): Upper Bound: Scale 0-1
MY: Human Capital Index (HCI): Upper Bound: Scale 0-1 data was reported at 0.633 NA in 2017. MY: Human Capital Index (HCI): Upper Bound: Scale 0-1 data is updated yearly, averaging 0.633 NA from Dec 2017 (Median) to 2017, with 1 observations. MY: 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 Malaysia – Table MY.World Bank.WDI: 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 |
|---|---|---|
| 0.633 2017 | yearly | 2017 - 2017 |