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

Data - Eurostat

Author

François Geerolf

Info

Last observation: Annual: 2025 (N = 19,849)

First observation: Annual: 1983 (N = 1,740)

Last data update: 24 jul 2026, 00:20. Last compile: 24 jul 2026, 02:16

Structure

isced11

Code

load_data("eurostat/isced11_fr.RData")
lfsa_urgaed %>%
  
  group_by(isced11, Isced11) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

isced11	Isced11	Nobs
TOTAL	All ISCED 2011 levels	101703
ED0-2	Less than primary, primary and lower secondary education (levels 0-2)	91608
ED3_4	Upper secondary and post-secondary non-tertiary education (levels 3 and 4)	91606
ED5-8	Tertiary education (levels 5-8)	90164
NRP	No response	46358
ED35_45	Upper secondary and post-secondary non-tertiary education - vocational (levels 35 and 45)	19427
ED34_44	Upper secondary and post-secondary non-tertiary education - general (levels 34 and 44)	19201
NAP	Not applicable	72

France, EU, Italy, Germany, Spain, Netherlands

15-74, peu d’éducation

Code

lfsa_urgaed %>%
  filter(isced11 == "ED0-2",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") %>%
  year_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_5flags +
  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

lfsa_urgaed %>%
  filter(isced11 == "ED3_4",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") %>%
  year_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_5flags +
  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

lfsa_urgaed %>%
  filter(isced11 == "ED5-8",
         age == "Y15-74",
         geo %in% c("EA19", "DE", "ES", "FR", "IT"),
         sex == "T") %>%
  year_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_5flags +
  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

lfsa_urgaed %>%
  filter(isced11 == "TOTAL",
         age == "Y15-74",
         geo %in% c("ES", "DE", "FR", "IT", "EA19"),
         sex == "T") %>%
  year_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_5flags +
  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

lfsa_urgaed %>%
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "T",
         unit == "PC") %>%
  year_to_date %>%
  
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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

lfsa_urgaed %>%
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "F",
         unit == "PC") %>%
  year_to_date %>%
  
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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

lfsa_urgaed %>%
  filter(geo %in% c("EU15", "EU28", "EU27_2020"),
         age == "Y15-64",
         isced11 == "TOTAL",
         sex == "M",
         unit == "PC") %>%
  year_to_date %>%
  
  ggplot + geom_line() + theme_minimal()  +
  aes(x = date, y = values/100, color = Geo, linetype = Geo) +
  scale_color_manual(values = viridis(4)[1:3]) +
  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))