Downloads data from the Wittgenstein Centre Human Capital Data Explorer. Requires a working internet connection.

get_wcde(
  indicator = "pop",
  scenario = 2,
  country_code = NULL,
  country_name = NULL,
  include_scenario_names = FALSE
)

Arguments

indicator

One character string based on the indicator column in the wic_indicators data frame, representing the variable to be downloaded.

scenario

Vector of length one or more with numbers corresponding the scenarios. See details for more information. Defaults to 2 for the SSP2 Medium scenario.

country_code

Vector of length one or more of country numeric codes based on ISO 3 digit numeric values.

country_name

Vector of length one or more of country names. The corresponding country code will be guessed using the countrycodes package.

include_scenario_names

Logical vector of length one to indicate if to include additional columns for scenario names and short names. FALSE by default.

Value

A tibble with the data selected.

Details

If not country_name or country_code is provided data for all countries and regions are downloaded. A full list of available countries and regions can be found in the wic_locations data frame.

indicator must be set to a value in the first column in the table below of available demographic indicators:

indicatorIndicator Description
popPopulation Size (000's)
bpopPopulation Size by Broad Age (000's)
epopPopulation Size by Education (000's)
propEducational Attainment Distribution
bpropEducational Attainment Distribution by Broad Age
growthAverage Annual Growth Rate
nirateAverage Annual Rate of Natural Increase
sexratioSex Ratio
magePopulation Median Age
tdrTotal Dependency Ratio
ydrYouth Dependency Ratio
odrOld-age Dependency Ratio
ryl15Age When Remaining Life Expectancy is Below 15 years
pryl15Proportion of Population with a Remaining Life Expectancy below 15 Years
mysMean Years of Schooling by Age
bmysMean Years of Schooling by Broad Age
ggapmys15Gender Gap in Mean Years Schooling (15+)
ggapmys25Gender Gap in Mean Years Schooling (25+)
ggapedu15Gender Gap in Educational Attainment (15+)
ggapedu25Gender Gap in Educational Attainment (25+)
tfrTotal Fertility Rate
etfrTotal Fertility Rate by Education
asfrAge-Specific Fertility Rate
easfrAge-Specific Fertility Rate by Education
cbrCrude Birth Rate
macbMean Age at Childbearing
e0Life Expectancy at Birth
cdrCrude Death Rate
assrAge-Specific Survival Ratio
eassrAge-Specific Survival Ratio by Education
netNet Migration

See wic_indicators data frame for more details.

scenario must be set to one or values in the first column table below of the available future scenarios:

scenariodescription
1Rapid Development (SSP1)
2Medium (SSP2)
3Stalled Development (SSP3)
21Medium - Zero Migration (SSP2 - ZM)
22Medium - Double Migration (SSP2 - DM)

See wic_scenarios data frame for more details.

Examples

# \donttest{ # SSP2 tfr for Austria and Bulgaria get_wcde(indicator = "tfr", country_code = c(40, 100))
#> # A tibble: 60 x 5 #> scenario name country_code period tfr #> <dbl> <chr> <dbl> <chr> <dbl> #> 1 2 Austria 40 1950-1955 2.1 #> 2 2 Bulgaria 100 1950-1955 2.53 #> 3 2 Austria 40 1955-1960 2.57 #> 4 2 Bulgaria 100 1955-1960 2.3 #> 5 2 Austria 40 1960-1965 2.78 #> 6 2 Bulgaria 100 1960-1965 2.22 #> 7 2 Austria 40 1965-1970 2.57 #> 8 2 Bulgaria 100 1965-1970 2.13 #> 9 2 Austria 40 1970-1975 2.04 #> 10 2 Bulgaria 100 1970-1975 2.16 #> # ... with 50 more rows
# SSP1 and SSP2 life expectancy for Vietnam and United Kingdom (guessing the country codes) get_wcde(scenario = c(1, 2), indicator = "e0", country_name = c("Vietnam", "UK"))
#> # A tibble: 240 x 6 #> scenario name country_code sex period e0 #> <dbl> <chr> <dbl> <chr> <chr> <dbl> #> 1 1 Viet Nam 704 Male 1950-1~ 50.8 #> 2 1 United Kingdom of Great Britain a~ 826 Male 1950-1~ 66.8 #> 3 1 Viet Nam 704 Female 1950-1~ 56.5 #> 4 1 United Kingdom of Great Britain a~ 826 Female 1950-1~ 71.9 #> 5 1 Viet Nam 704 Male 1955-1~ 54 #> 6 1 United Kingdom of Great Britain a~ 826 Male 1955-1~ 67.7 #> 7 1 Viet Nam 704 Female 1955-1~ 60.7 #> 8 1 United Kingdom of Great Britain a~ 826 Female 1955-1~ 73.4 #> 9 1 Viet Nam 704 Male 1960-1~ 56.8 #> 10 1 United Kingdom of Great Britain a~ 826 Male 1960-1~ 68 #> # ... with 230 more rows
# SSP1 and SSP3 population by education for all countries get_wcde(scenario = c(1, 3), indicator = "tfr")
#> # A tibble: 13,740 x 5 #> scenario name country_code period tfr #> <dbl> <chr> <dbl> <chr> <dbl> #> 1 1 Bulgaria 100 1950-1955 2.53 #> 2 1 Myanmar 104 1950-1955 6 #> 3 1 Burundi 108 1950-1955 6.8 #> 4 1 Belarus 112 1950-1955 2.61 #> 5 1 Cambodia 116 1950-1955 6.95 #> 6 1 Algeria 12 1950-1955 7.28 #> 7 1 Cameroon 120 1950-1955 5.49 #> 8 1 Canada 124 1950-1955 3.64 #> 9 1 Cape Verde 132 1950-1955 6.57 #> 10 1 Central African Republic 140 1950-1955 5.52 #> # ... with 13,730 more rows
# }