Expected years schooling children aged 6

Expected years of school is calculated as the sum of age-specific enrollment rates between ages 4 and 17. Age-specific enrollment rates are approximated using school enrollment rates at different levels: pre-primary enrollment rates approximate the age-specific enrolment rates for 4 and 5 year-olds; the primary rate approximates for 6-11 year-olds; the lower-secondary rate approximates for 12-14 year-olds; and the upper-secondary approximates for 15-17 year-olds. Most recent estimates are used. Year of most recent primary enrollment rate used is shown in data notes.

This statistic shows the number of years of education the average person in Germany is expected to undertake over their lifetime from 2013 to 2015. Throughout this period, the expected years of education over lifetime amounted to 18 years.

This Subnational Human Development Index Database contains for the period 1990-2017 for 1625 regions within 161 countries the national and subnational values of the Subnational Human Development Index (SHDI), for the three dimension indices on the basis of which the SHDI is constructed – education, health and standard of living --, and for the four indicators needed to create the dimension indices -- expected years of schooling, mean years of schooling, life expectancy and gross national income per capita.

This statistic shows the number of years of education the average person in Switzerland is expected to undertake over their lifetime from 2013 to 2015. The peak for this period was in 2015 with 18 years.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, female in Paraguay was reported at 8.6625 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Paraguay - Mean years of schooling of the population age 25+. Female - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

The mean years of schooling in Afghanistan in 2019 was *** years for males, compared to about *** years for females. The expected years at birth was the largest contributor to the Human Development Index (HDI) score of Afghanistan in 2019.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, both sexes in Mali was reported at 1.8744 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mali - Mean years of schooling of the population age 25+. Total - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

School life expectancy, primary and secondary, both sexes (years) in Canada was reported at 12.86 years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Canada - School life expectancy, primary and secondary, both sexes (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

The number of years of education the average person in Belgium is expected to undertake over their lifetime from 2013 to 2020 remained stable. Since 2013 the average time spend on education in Belgium remained steady at around 19 years.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, both sexes in Peru was reported at 9.6963 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Peru - Mean years of schooling of the population age 25+. Total - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, male in Estonia was reported at 13.55 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Estonia - Mean years of schooling of the population age 25+. Male - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

This statistic shows the number of years of education the average person in Poland is expected to undertake over their lifetime in 2013. That year, the expected years of education over lifetime amounted to 18 years.

Mean years education of men aged 25+ in region

Expected number of inhabitants 0 years in 5 years. The number of live-born children, deceased, displaced and displaced persons registered during the year is used to make the proscription. This information estimates fertility, mortality, number of immigrants, migration distributions and migration risks by age and gender. The estimates then form the basis for the calculation of the future development of the number of births, deaths, displaced and displaced. Please note that this prediction is based only on statistics available nationally and should not be confused with forecasts produced by the municipalities themselves. As of 2022, data will be published every three years. Data is available according to gender breakdown.

This statistic shows the number of years of education the average person in Malta is expected to undertake over their lifetime from 2013 to 2015. The peak for this period was in 2014 and 2015 with 16 years.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.

30-lt_input.csv

Life table input data.

• `id`: unique row identifier
• `region_iso`: iso3166-2 region codes
• `sex`: Male, Female, Total
• `year`: iso year
• `age_start`: start of age group
• `age_width`: width of age group, Inf for age_start 100, otherwise 1
• `nweeks_year`: number of weeks in that year, 52 or 53
• `death_total`: number of deaths by any cause
• `population_py`: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)
• `death_total_nweeksmiss`: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)
• `death_total_minnageraw`: the minimum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_maxnageraw`: the maximum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_minopenageraw`: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_maxopenageraw`: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_source`: source of the all-cause death data

• `death_total_prop_q1`: observed proportion of deaths in first quarter of year

• `death_total_prop_q2`: observed proportion of deaths in second quarter of year

• `death_total_prop_q3`: observed proportion of deaths in third quarter of year

• `death_total_prop_q4`: observed proportion of deaths in fourth quarter of year

• `death_expected_prop_q1`: expected proportion of deaths in first quarter of year

• `death_expected_prop_q2`: expected proportion of deaths in second quarter of year

• `death_expected_prop_q3`: expected proportion of deaths in third quarter of year

• `death_expected_prop_q4`: expected proportion of deaths in fourth quarter of year

• `population_midyear`: midyear population (July 1st)
• `population_source`: source of the population count/exposure data
• `death_covid`: number of deaths due to covid
• `death_covid_date`: number of deaths due to covid as of
• `death_covid_nageraw`: the number of age groups in the covid input data
• `ex_wpp_estimate`: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year
• `ex_hmd_estimate`: life expectancy estimates from the Human Mortality Database
• `nmx_hmd_estimate`: death rate estimates from the Human Mortality Database
• `nmx_cntfc`: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

• source:
  • STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)
  • ONS for GB-EAW pre 2020
  • CDC for US pre 2020
• STMF:
  • harmonized to single ages via pclm
  • pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110
  • smoothing parameters estimated via BIC grid search seperately for every pclm iteration
  • last age group set to [110,111)
  • ages 100:110+ are then summed into 100+ to be consistent with mid-year population information
  • deaths in unknown weeks are considered; deaths in unknown ages are not considered
• ONS:
  • data already in single ages
  • ages 100:105+ are summed into 100+ to be consistent with mid-year population information
  • PCLM smoothing applied to for consistency reasons
• CDC:
  • The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

• source:
  • for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019
  • for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100
• mid-year population
  • mid-year population translated into exposures:
    • if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates
    • if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364\*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

• source: COVerAGE-DB (https://osf.io/mpwjq/)
• the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

• source:
  • World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019
  • Human Mortality Database (https://mortality.org/), single year and age tables

Expected number of inhabitants 0-19 years in 5 years in the municipality divided by the expected number of inhabitants in total in 5 years in the municipality. The number of live-born children, deceased, displaced and displaced persons registered during the year is used to make the proscription. This information estimates fertility, mortality, number of immigrants, migration distributions and migration risks by age and gender. The estimates then form the basis for the calculation of the future development of the number of births, deaths, displaced and displaced. Please note that this prediction is based only on statistics available nationally and should not be confused with forecasts produced by the municipalities themselves. As of 2022, data will be published every three years. Data is available according to gender breakdown.

UIS: Mean years of schooling (ISCED 1 or higher), population 25+ years, male in Australia was reported at 12.43 Years in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Mean years of schooling of the population age 25+. Male - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

The expected number of inhabitants 85+ years in 5 years in the municipality divided by the expected number of inhabitants in total in 5 years in the municipality. The number of live-born children, deceased, displaced and displaced is used to calculate the future development of the number of births, deaths, migrants and displaced persons. Please note that this prediction is based only on statistics available nationally and should not be confused with forecasts produced by the municipalities themselves. As of 2022, data will be published every three years. Data is available according to gender breakdown.