Unemployment rates by sex, age and educational attainment level (%) - lfsq_urgaed

Data - Eurostat

Author

François Geerolf

Info

Last observation: Quarterly: 2026Q1 (N = 19,157)

First observation: Quarterly: 1998Q1 (N = 3,014)

Last data update: 03 aoû 2026, 12:11. Last compile: 03 aoû 2026, 21:42

Structure

isced11

Code

isced11 <- read_parquet("isced11_fr.parquet")
lfsq_urgaed |>
  
  group_by(isced11, Isced11) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()

isced11	Isced11	Nobs
TOTAL	All ISCED 2011 levels	321639
ED0-2	Less than primary, primary and lower secondary education (levels 0-2)	320160
ED3_4	Upper secondary and post-secondary non-tertiary education (levels 3 and 4)	320148
ED5-8	Tertiary education (levels 5-8)	313742
NRP	No response	112129
ED35_45	Upper secondary and post-secondary non-tertiary education - vocational (levels 35 and 45)	80577
ED34_44	Upper secondary and post-secondary non-tertiary education - general (levels 34 and 44)	79657
NAP	Not applicable	144

France, EU, Italy, Germany, Spain, Netherlands

15-74, peu d’éducation

Code

lfsq_urgaed |>
  filter(isced11 == "ED0-2",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") |>
  quarter_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(color = ifelse(geo == "EA19", color2, color)) |>
  mutate(color = ifelse(geo == "ES", color2, color)) |>
  mutate(values = values / 100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + xlab("") + ylab("Taux d'emploi (1er cycle de l'enseignement secondaire)") +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
                     labels = percent_format(accuracy = 1))

Education moyenne

Code

lfsq_urgaed |>
  filter(isced11 == "ED3_4",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") |>
  quarter_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(color = ifelse(geo == "EA19", color2, color)) |>
  mutate(color = ifelse(geo == "ES", color2, color)) |>
  mutate(values = values / 100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + xlab("") + ylab("Taux d'emploi") +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
                     labels = percent_format(accuracy = 1))

Enseignement supérieur

Code

lfsq_urgaed |>
  filter(isced11 == "ED5-8",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") |>
  quarter_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(color = ifelse(geo == "EA19", color2, color)) |>
  mutate(color = ifelse(geo == "ES", color2, color)) |>
  mutate(values = values / 100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + xlab("") + ylab("Taux d'emploi") +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
                     labels = percent_format(accuracy = 1))

TOTAL

Code

lfsq_urgaed |>
  filter(isced11 == "TOTAL",
         age == "Y15-74",
         geo %in% c("ES", "DE", "FR", "IT", "EA19"),
         sex == "T") |>
  quarter_to_date() |>
  filter(date >= as.Date("1995-01-01")) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Geo = ifelse(geo == "EA19", "Europe", Geo)) |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(color = ifelse(geo == "EA19", color2, color)) |>
  mutate(color = ifelse(geo == "ES", color2, color)) |>
  mutate(values = values / 100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + 
  theme_minimal() + xlab("") + ylab("Taux d'emploi") +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1960, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-500, 200, 2),
                     labels = percent_format(accuracy = 1))

EU: Employment Rates - All

All

Code

lfsq_urgaed |>
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "T",
         unit == "PC") |>
  quarter_to_date() |>
  
  mutate(values = values/100) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + geom_line() + theme_minimal()  +
  aes(x = date, y = values, color = color) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rates") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Female

Code

lfsq_urgaed |>
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "F",
         unit == "PC") |>
  quarter_to_date() |>
  
  mutate(values = values/100) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + geom_line() + theme_minimal()  +
  aes(x = date, y = values, color = color) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rates (Female)") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))

Male

Code

lfsq_urgaed |>
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "M",
         unit == "PC") |>
  quarter_to_date() |>
  
  mutate(values = values/100) |>
  left_join(colors, by = c("Geo" = "country")) |>
  ggplot() + geom_line() + theme_minimal()  +
  aes(x = date, y = values, color = color) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.22, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("Employment Rates (Male)") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))