Myanmar Human Capital Index
Myanmar MM: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1
MM: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data was reported at 0.473 NA in 2017. MM: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.473 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.473 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Female: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Female: Scale 0-1
MM: Human Capital Index (HCI): Female: Scale 0-1 data was reported at 0.490 NA in 2017. MM: Human Capital Index (HCI): Female: Scale 0-1 data is updated yearly, averaging 0.490 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.490 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Female: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1
MM: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data was reported at 0.504 NA in 2017. MM: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.504 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.504 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Female: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Lower Bound: Scale 0-1
MM: Human Capital Index (HCI): Lower Bound: Scale 0-1 data was reported at 0.456 NA in 2017. MM: Human Capital Index (HCI): Lower Bound: Scale 0-1 data is updated yearly, averaging 0.456 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.456 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1
MM: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data was reported at 0.440 NA in 2017. MM: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 data is updated yearly, averaging 0.440 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.440 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Male: Lower Bound: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Male: Scale 0-1
MM: Human Capital Index (HCI): Male: Scale 0-1 data was reported at 0.458 NA in 2017. MM: Human Capital Index (HCI): Male: Scale 0-1 data is updated yearly, averaging 0.458 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.458 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Male: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1
MM: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data was reported at 0.474 NA in 2017. MM: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 data is updated yearly, averaging 0.474 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.474 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Male: Upper Bound: Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Scale 0-1
MM: Human Capital Index (HCI): Scale 0-1 data was reported at 0.473 NA in 2017. MM: Human Capital Index (HCI): Scale 0-1 data is updated yearly, averaging 0.473 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.473 2017 | yearly | 2017 - 2017 |
View Myanmar's Myanmar MM: Human Capital Index (HCI): Scale 0-1 from 2017 to 2017 in the chart:
Myanmar MM: Human Capital Index (HCI): Upper Bound: Scale 0-1
MM: Human Capital Index (HCI): Upper Bound: Scale 0-1 data was reported at 0.488 NA in 2017. MM: Human Capital Index (HCI): Upper Bound: Scale 0-1 data is updated yearly, averaging 0.488 NA from Dec 2017 (Median) to 2017, with 1 observations. MM: 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 Myanmar – Table MM.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 |
|---|---|---|
| 0.488 2017 | yearly | 2017 - 2017 |