Population and Labour Force - ALFS_POP_LABOUR

Data - OECD

Author

François Geerolf


SUBJECT

Code 
ALFS_POP_LABOUR |>
  left_join(ALFS_POP_LABOUR_var$SUBJECT, by = "SUBJECT") |>
  group_by(SUBJECT, Subject) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()

SEX

Code 
ALFS_POP_LABOUR |>
  left_join(ALFS_POP_LABOUR_var$SEX, by = "SEX") |>
  group_by(SEX, Sex) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()
SEX Sex Nobs
TT All persons 48889
MA Males 39198
FE Females 39020

LOCATION

Code 
ALFS_POP_LABOUR |>
  left_join(ALFS_POP_LABOUR_var$LOCATION, by = "LOCATION") |>
  group_by(LOCATION, Location) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  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 .}

Unemployment rate as % civilian labour force

Code 
ALFS_POP_LABOUR |>
  filter(SUBJECT == "YT99UNPT_ST", 
         SEX == "TT") |>
  mutate(obsValue = obsValue |> round(1) |> paste("%")) |>
  left_join(ALFS_POP_LABOUR_var$LOCATION, by = "LOCATION") |>
  group_by(Location) |>
  summarise(year_first = first(obsTime),
            value_first = first(obsValue),
            year_last = last(obsTime),
            value_last = last(obsValue)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Employment / Population ratio

Code 
ALFS_POP_LABOUR |>
  # YT99CEL1_ST: Civilian employment
  # YP99TTL1_ST: Population
  filter(SUBJECT %in% c("YT99CEL1_ST", "YP99TTL1_ST"), 
         SEX == "TT") |>
  select(LOCATION, obsTime, SUBJECT, obsValue, obsTime) |>
  group_by(LOCATION, obsTime) |>
  arrange(SUBJECT) |>
  summarise(obsValue = obsValue[2]/ obsValue[1]) |>
  na.omit() |>
  mutate(obsValue = (100*obsValue) |> round(1) |> paste("%")) |>
  left_join(ALFS_POP_LABOUR_var$LOCATION, by = "LOCATION") |>
  group_by(Location) |>
  summarise(`Year 1` = first(obsTime),
            `Value 1` = first(obsValue),
            `Year 2` = last(obsTime),
            `Value 2` = last(obsValue)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

European Example

Code 
ALFS_POP_LABOUR |>
  filter(SUBJECT == "YT99CEP2_ST", 
         SEX == "TT",
         LOCATION %in% c("ITA", "DEU", "GRC", "ESP", "PRT", "FRA")) |>
  year_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(ALFS_POP_LABOUR_var$LOCATION, by = "LOCATION") |>
  group_by(LOCATION) |>
  arrange(date) |>
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-01-01")]) |>
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Location, linetype = Location)) + 
  scale_color_manual(values = viridis(7)[1:6]) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_log10(breaks = seq(70, 200, 5))

Civilian labour force, Index

Code 
ALFS_POP_LABOUR |>
  filter(SUBJECT == "YG9907L1_IXOB", 
         SEX == "TT",
         LOCATION %in% c("EA19", "USA")) |>
  year_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(ALFS_POP_LABOUR_var$LOCATION, by = "LOCATION") |>
  group_by(LOCATION) |>
  arrange(date) |>
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-01-01")]) |>
  ggplot() + geom_line(aes(x = date, y = obsValue, color = Location, linetype = Location)) + 
  scale_color_manual(values = viridis(3)[1:2]) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2100, 1) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(70, 200, 2))