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Brazilian mean years of schooling

Source: R/get_schooling.R
get_schooling.Rd

Returns harmonized series of average years of schooling at the national, macro-region, or state level, optionally broken down by color/race or sex. The bundled data comes from Walter & Kang (2023), a FGV-IBRE working paper that reconstructs the series from 1925 to 2015.

Usage

get_schooling(
  year = NULL,
  geo_level = c("BR", "region", "UF"),
  geo = NULL,
  dimension = c("none", "race", "sex"),
  source = NULL,
  wide = FALSE,
  lang = c("en", "pt")
)

Arguments

year

Integer vector or two-element c(min, max) range. NULL for all years.

geo_level

One of "BR" (national, default), "region" (macro-region), or "UF" (state). Region and UF series start in 1950.

geo

Character vector of geographic codes. For geo_level = "UF", 2-letter IBGE UF abbreviations (e.g. "SP", "BA"). For geo_level = "region", one or more of "N", "NE", "CO", "SE", "S". NULL (default) returns all geographies at that level.

dimension

Inequality breakdown. One of:

  • "none" (default) — national totals only (no race or sex split);

  • "race" — breakdown by IBGE color/race (white, black, brown, asian, indigenous), totals across sex;

  • "sex" — breakdown by sex (male, female), totals across race. Race and sub-national breakdowns are only available at geo_level = "BR".

source

Character vector of source keys. NULL returns all available sources (currently only "walter_kang_2023").

wide

Logical. If TRUE, pivots the result to wide form. For this indicator the effect is minimal (only one indicator column), but the parameter is provided for API consistency with get_enrollment(). Default FALSE.

lang

One of "en" (default) or "pt". When "pt", factor levels are translated via inst/dict/i18n.yaml.

Value

A tibble following the canonical schema in inst/dict/schema.yaml. Columns: year, geo_level, geo_code, geo_name, dim_race, dim_sex, age_group, indicator, value, unit, source, source_note. The level and network columns are omitted (not applicable to population-level attainment averages).

Examples

if (FALSE) {
# National series, all years
get_schooling()

# By race, 1960-2015
get_schooling(dimension = "race", year = c(1960, 2015))

# By sex across states
get_schooling(dimension = "sex", geo_level = "UF", geo = c("SP", "BA"))
}