Nominal unit labour costs - total economy (Ratio of compensation per employee to real GDP per person employed.) - PLCD

Data - AMECO

Author

François Geerolf

geo, Country

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  group_by(COUNTRY) |>
  summarise(Nobs = n()) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(COUNTRY)),
         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 .}

France, Germany

All

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Nominal unit labour costs - total economy") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 10))

1990-

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  filter(date >= as.Date("1990-01-01")) |>
  ggplot() + ylab("Nominal unit labour costs - total economy") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 10))

France, Germany, Italy

2000-

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU", "ITA"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  filter(date >= as.Date("2000-01-01"),
         date <= as.Date("2020-01-01")) |>
  group_by(COUNTRY) |>
  mutate(value = 100*value/value[1]) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Coûts unitaires du travail, nominal - Ensemble") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(2000, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 5))

France, Germany, Spain, Italy

All

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU", "ESP", "ITA"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Nominal unit labour costs - total economy") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 5))

1999-

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU", "ESP", "ITA"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  filter(date >= as.Date("1999-01-01")) |>
  group_by(COUNTRY) |>
  mutate(value = 100*value/value[1]) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Coûts unitaires du travail, nominal (secteur manuf.)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(1999, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 5))

2000-

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU", "ESP", "ITA"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  filter(date >= as.Date("2000-01-01")) |>
  group_by(COUNTRY) |>
  mutate(value = 100*value/value[1]) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Coûts unitaires du travail, nominal (secteur manuf.)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() +
  scale_x_date(breaks = seq(2000, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  add_flags +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 5))

1995-

Viridis Colors

Code 
PLCD |>
  left_join(COU, by = "COU") |>
  filter(COU %in% c("FRA", "DEU", "ESP", "ITA"),
         vintage == 2021,
         CODE_4 == "99") |>
  select(COUNTRY, date, value) |>
  arrange(COUNTRY, date) |>
  filter(date >= as.Date("1995-01-01")) |>
  group_by(COUNTRY) |>
  mutate(value = 100*value/value[1]) |>
  left_join(colors, c("COUNTRY" = "country")) |>
  ggplot() + ylab("Nominal unit labour costs - total economy") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  geom_vline(xintercept = as.Date("2011-01-01"),
             linetype= "dashed") +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-60, 300, 5))