Employment by sex, age, job tenure and NUTS 2 regions - lfst_r_egad

Data - Eurostat

Info

Last observation: Annual: 2025 (N = 100,640)

First observation: Annual: 1999 (N = 83,846)

Last data update: 23 jul 2026, 22:13. Last compile: 24 jul 2026, 02:23

Structure

freq

unit

duration

age

sex

geo

Long-Term (60m+), Age 15+

lfst_r_egad %>%
  filter(unit == "PC",
         duration == "M_GE60",
         sex == "T",
         age == "Y_GE15",
         nchar(geo) == 4,
         time == "2018") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(20, 100, 5),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Employment (%) \nLong-Term (60m+), Age 15+")

Medium-Term (M24-59), Age 15+

lfst_r_egad %>%
  filter(unit == "PC",
         duration == "M24-59",
         sex == "T",
         age == "Y_GE15",
         nchar(geo) == 4,
         time == "2018") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 5),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Employment (%) \nMedium-Term (24-59), Age 15+")

Short-Term (M12-23), Age 15+

lfst_r_egad %>%
  filter(unit == "PC",
         duration == "M12-23",
         sex == "T",
         age == "Y_GE15",
         nchar(geo) == 4,
         time == "2018") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 2),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Employment (%) \nLong-Term (60m+), Age 15+")

Short-Term (M0-11), Age 15+

lfst_r_egad %>%
  filter(unit == "PC",
         duration == "M0-11",
         sex == "T",
         age == "Y_GE15",
         nchar(geo) == 4,
         time == "2018") %>%
  right_join(europe_NUTS2, by = "geo") %>%
  filter(long >= -13.5, lat >= 33) %>%
  ggplot(., aes(x = long, y = lat, group = group, fill = values/100)) +
  geom_polygon() + coord_map() +
  scale_fill_viridis_c(na.value = "white",
                       labels = scales::percent_format(accuracy = 1),
                       breaks = 0.01*seq(0, 100, 5),
                       values = c(0, 0.1, 0.3, 0.5, 0.7, 0.8, 1)) +
  theme_void() + theme(legend.position = c(0.15, 0.85)) +
  labs(fill = "Employment (%) \nShort-Term (M0-11), Age 15+")