Question & Audience

• Question: Do university degrees still guarantee jobs for the young people?
• Audience: Students, careers advisers, and policymakers.
• Approach: Comparing tertiary enrollment (% gross) with youth unemployment (15–24) using open World Bank data.

Data

• World Bank (WDI):
  • Tertiary enrolment (% gross): SE.TER.ENRR
    
  • Youth unemployment (male 15–24): SL.UEM.1524.MA.NE.ZS (swap to total SL.UEM.1524.ZS if preferred)
    
• Coverage: 1995–latest available.

Load & Prepare Data

path_edu <- "data/API_SE.TER.ENRR_DS2_en_excel_v2_129805.xls"
path_emp <- "data/API_SL.UEM.1524.MA.NE.ZS_DS2_en_excel_v2_2482.xls"

tidy_wb <- function(path){
  read_excel(path, sheet = 1, skip = 3) |>
    pivot_longer(cols = tidyselect::matches("^[0-9]{4}$"),
                 names_to = "year", values_to = "value") |>
    mutate(year = as.integer(year)) |>
    rename(country = `Country Name`, code = `Country Code`, indicator = `Indicator Name`) |>
    select(country, code, indicator, year, value)
}

edu <- tidy_wb(path_edu)
emp <- tidy_wb(path_emp)

merged <- full_join(edu, emp, by = c("code","year","country"),
                    suffix = c("_edu","_emp")) |>
  rename(edu_value = value_edu, emp_value = value_emp) |>
  mutate(region = countrycode(code, "iso3c", "region")) |>
  filter(!is.na(edu_value) & !is.na(emp_value), year >= 1995)

dir.create("outputs", showWarnings = FALSE)
write_csv(merged, "outputs/wb_edu_unemp_tidy.csv")

global_trend <- merged |>
  group_by(year) |>
  summarise(med_edu = median(edu_value, na.rm = TRUE),
            med_emp = median(emp_value, na.rm = TRUE), .groups = "drop")

year_counts <- merged |>
  group_by(year) |>
  summarise(n = n_distinct(code[!is.na(edu_value) & !is.na(emp_value)]), .groups = "drop") |>
  arrange(desc(year))

latest_good_year <- year_counts$year[which.max(ifelse(year_counts$n >= 80, year_counts$year, -Inf))]
if (is.infinite(latest_good_year) || is.na(latest_good_year)) latest_good_year <- max(merged$year, na.rm = TRUE)

latest <- filter(merged, year == latest_good_year)

Global Medians (1995–2024)

From this graph, university enrollment has been increasing steadily especially since the early 2000s.But the youth unemployment is not same as that progress. Even as more people study, the job market hasn’t expanded at the same pace.

This tells us that simply increasing access to education isn’t enough. The real challenge is making sure that what students learn actually matches the skills that industries and employers need.

Scatter Plot (Education vs Youth Unemployment)

World Map (Regional Youth Unemployment)

This map makes the global situation easy to see. Regions like Africa and Southern Europe are with very high youth unemployment, while areas such as North America and East Asia seem to be doing much better. The difference is likely because of how these economies are structured ,stronger economies tend to offer more stable job options, while others face slower growth or a mismatch between graduate skills and available jobs.

Live Filter (Latest Year): Choose Regions

Use the drop down to focus on one or more regions and compare positions.
East Asia often shows smoother school‑to‑work transitions; Southern Europe and parts of Africa tend to stay higher at similar education levels.