Employment by activities and status (ALFS) - ALFS_EMP

Data - OECD

Last observation: 2022 (N = 3160)

First observation: 1956 (N = 1)

Last data update: 02 août 2026, 08:56

Last compile: 02 sept. 2026, 23:08

Structure

LOCATION

SUBJECT

SEX

FREQUENCY

Individual countries

United States

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "USA",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Agriculture

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("Agriculture", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Agriculture") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Industry

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("Industry", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("Construction", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

United Kingdom

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "GBR",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Agriculture

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "GBR",
         grepl("Agriculture", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Agriculture") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  #
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Industry

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "GBR",
         grepl("Industry", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  #
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "GBR",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 80000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("Construction", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "USA",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 500000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

France

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "FRA",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Agriculture

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "FRA",
         grepl("Agriculture", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Agriculture") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "FRA",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "FRA",
         grepl("Construction", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "FRA",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

Germany

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "DEU",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  year_to_date() |>
  filter(SEX == "TT",
         LOCATION == "DEU",
         grepl("Manufacturing", Subject),
         date >= as.Date("1958-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 20000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  year_to_date() |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "DEU",
         grepl("Construction", Subject),
         date >= as.Date("1961-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.3, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "DEU",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

Italy

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "ITA",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ITA",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  year_to_date() |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ITA",
         grepl("Construction", Subject),
         date >= as.Date("1961-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.3, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ITA",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

Spain

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "ESP",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ESP",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.7, 0.80),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  year_to_date() |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ESP",
         grepl("Construction", Subject),
         date >= as.Date("1961-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.3, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "ESP",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

Japan

Table

ALFS_EMP |>
  filter(SEX == "TT",
         LOCATION == "JPN",
         TIME_PERIOD %in% paste0(seq(1958, 2018, 20))) |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  select(SUBJECT, Subject, TIME_PERIOD, obsValue) |>
  spread(TIME_PERIOD, obsValue) |>
  print_table_conditional()

Manufacturing

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "JPN",
         grepl("Manufacturing", Subject)) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Manufacturing") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 20000, 1000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.5, 0.25),
        legend.title = element_blank())

Construction

ALFS_EMP |>
  year_to_date() |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "JPN",
         grepl("Construction", Subject),
         date >= as.Date("1961-01-01")) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Employment in Construction") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 8000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.3, 0.80),
        legend.title = element_blank())

All activities

ALFS_EMP |>
  left_join(ALFS_EMP_var$SUBJECT, by = "SUBJECT") |>
  filter(SEX == "TT",
         LOCATION == "JPN",
         grepl("all activities", Subject),
         !(SUBJECT %in% c("YS99TTL4_ST", "YS99TTL3_ST"))) |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Total Employment") +
  geom_line(aes(x = date, y = obsValue, color = paste0(SUBJECT, " - ", Subject))) + 
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100000, 2000),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  
  theme(legend.position = c(0.4, 0.80),
        legend.title = element_blank())

Manufacturing

Table

ALFS_EMP |>
  # YA9903L1_ST: Employees in Industry (ISIC rev.2, 2-5)
  # YS99TTL2_ST: Employees in all activities
  filter(SUBJECT %in% c("YA9903L1_ST", "YS99TTL2_ST"), 
         SEX == "TT") |>
  select(LOCATION, SUBJECT, TIME_PERIOD, obsValue) |>
  spread(SUBJECT, obsValue) %>%
  mutate(share = (100*YA9903L1_ST/YS99TTL2_ST) |> round(digits = 1)) |>
  left_join(ALFS_EMP_var$LOCATION, by = "LOCATION") |>
  filter(!is.na(share)) |>
  mutate(share = paste0(share, " %")) |>
  group_by(Location) |>
  arrange(TIME_PERIOD) |>
  summarise(`Year 1` = first(TIME_PERIOD),
            `Year 2` = last(TIME_PERIOD),
            `Share 1` = first(share),
            `Share 2` = last(share)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Industry

Table

ALFS_EMP |>
  # YW992IL1_ST: Employees in Industry (ISIC rev.2, 2-5)
  # YS99TTL2_ST: Employees in all activities
  filter(SUBJECT %in% c("YW992IL1_ST", "YS99TTL2_ST"), 
         SEX == "TT") |>
  select(LOCATION, SUBJECT, TIME_PERIOD, obsValue) |>
  spread(SUBJECT, obsValue) %>%
  mutate(share = (100*YW992IL1_ST/YS99TTL2_ST) |> round(digits = 1)) |>
  left_join(ALFS_EMP_var$LOCATION, by = "LOCATION") |>
  filter(!is.na(share)) |>
  mutate(share = paste0(share, " %")) |>
  group_by(Location) |>
  summarise(`Year 1` = first(TIME_PERIOD),
            `Year 2` = last(TIME_PERIOD),
            `Share 1` = first(share),
            `Share 2` = last(share)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Related Data

Data on employment

source	dataset	Title	Updated
oecd	STLABOUR	Short-Term Labour Market Statistics - STLABOUR	2026-08-02
bls	jt	NA	NA
bls	la	NA	NA
bls	ln	NA	NA
eurostat	nama_10_a10_e	Employment by A*10 industry breakdowns - nama_10_a10_e	2026-08-31
eurostat	nama_10_a64_e	National accounts employment data by industry (up to NACE A*64) - nama_10_a64_e	2026-08-04
eurostat	namq_10_a10_e	Employment A*10 industry breakdowns - namq_10_a10_e	2026-08-31
eurostat	une_rt_m	Unemployment by sex and age – monthly data - une_rt_m	2026-08-28
oecd	ALFS_EMP	Employment by activities and status (ALFS) - ALFS_EMP	2026-08-02
oecd	EPL_T	Strictness of employment protection – temporary contracts - EPL_T	2026-08-02
oecd	LFS_SEXAGE_I_R	LFS by sex and age - indicators - LFS_SEXAGE_I_R	2026-08-02

Data on industry

source	dataset	Title	Updated
oecd	ALFS_EMP	Employment by activities and status (ALFS) - ALFS_EMP	2026-08-02
ec	INDUSTRY	Industry (sector data) - INDUSTRY	2026-08-01
eurostat	ei_isin_m	Industry - monthly data - index (2015 = 100) (NACE Rev. 2) - ei_isin_m	2026-08-30
eurostat	htec_trd_group4	High-tech trade by high-tech group of products in million euro (from 2007, SITC Rev. 4) - htec_trd_group4	2026-07-14
eurostat	nama_10_a64	National accounts aggregates by industry (up to NACE A*64) - nama_10_a64	2026-08-28
eurostat	nama_10_a64_e	National accounts employment data by industry (up to NACE A*64) - nama_10_a64_e	2026-08-04
eurostat	namq_10_a10_e	Employment A*10 industry breakdowns - namq_10_a10_e	2026-08-31
eurostat	road_eqr_carmot	New registrations of passenger cars by type of motor energy and engine size - road_eqr_carmot	2026-07-31
eurostat	sts_inpp_m	Producer prices in industry, total - monthly data - sts_inpp_m	2026-08-30
eurostat	sts_inppd_m	Producer prices in industry, domestic market - monthly data - sts_inppd_m	2026-08-30
eurostat	sts_inpr_m	Production in industry - monthly data - sts_inpr_m	2026-08-28
eurostat	sts_intvnd_m	Turnover in industry, non domestic market - monthly data - sts_intvnd_m	2026-08-30
fred	industry	Manufacturing, Industry - industry	2026-08-30
oecd	BERD_MA_SOF	Business enterprise R&D expenditure by main activity (focussed) and source of funds - BERD_MA_SOF	2026-08-02
oecd	GBARD_NABS2007	Government budget allocations for R and D - GBARD_NABS2007	2026-08-02
oecd	MEI_REAL	Production and Sales (MEI) - MEI_REAL	2026-08-02
oecd	MSTI_PUB	Main Science and Technology Indicators - MSTI_PUB	2026-08-02
oecd	SNA_TABLE4	PPPs and exchange rates - SNA_TABLE4	2026-08-02
wdi	NV.IND.EMPL.KD	Industry, value added per worker (constant 2010 USD) - NV.IND.EMPL.KD	2026-09-01
wdi	NV.IND.MANF.CD	Manufacturing, value added (current USD) - NV.IND.MANF.CD	2026-09-01
wdi	NV.IND.MANF.ZS	Manufacturing, value added (% of GDP) - NV.IND.MANF.ZS	2026-09-01
wdi	NV.IND.TOTL.KD	Industry (including construction), value added (constant 2015 USD) - NV.IND.TOTL.KD	2026-09-01
wdi	NV.IND.TOTL.ZS	Industry, value added (including construction) (% of GDP) - NV.IND.TOTL.ZS	2026-09-01
wdi	SL.IND.EMPL.ZS	Employment in industry (% of total employment) - SL.IND.EMPL.ZS	2026-09-01
wdi	TX.VAL.MRCH.CD.WT	Merchandise exports (current USD) - TX.VAL.MRCH.CD.WT	2026-09-01