Labour input in industry - monthly data - sts_inlb_m

Data - Eurostat

Info

Info

  • Few countries: not France

LAST_DOWNLOAD

Code
tibble(LAST_DOWNLOAD = as.Date(file.info("~/iCloud/website/data/eurostat/sts_inlb_m.RData")$mtime)) %>%
  print_table_conditional()
LAST_DOWNLOAD
2026-02-04

LAST_COMPILE

LAST_COMPILE
2026-02-05

Last

Code
sts_inlb_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2025M12 140

nace_r2

Code
sts_inlb_m %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

s_adj

Code
sts_inlb_m %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
s_adj S_adj Nobs
SCA Seasonally and calendar adjusted data 932369
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 812586
CA Calendar adjusted data, not seasonally adjusted data 583851

unit

Code
sts_inlb_m %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
I15 Index, 2015=100 671160
I21 Index, 2021=100 662884
I10 Index, 2010=100 398731
PCH_SM Percentage change compared to same period in previous year 329213
PCH_PRE Percentage change on previous period 266818

indic_bt

Code
sts_inlb_m %>%
  left_join(indic_bt, by = "indic_bt") %>%
  group_by(indic_bt, Indic_bt) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
indic_bt Indic_bt Nobs
WAGE Wages and salaries 1014887
HW Hours worked by employees 775805
EMP Persons employed 538114

geo

Code
sts_inlb_m %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

time

Code
sts_inlb_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Individual Countries

Germany

Code
sts_inlb_m %>%
  filter(nace_r2 == "C",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA",
         unit == "I15") %>%
  select(geo, indic_bt, time, values) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Portugal

Code
sts_inlb_m %>%
  filter(nace_r2 == "C",
         geo %in% c("PT"),
         s_adj == "SCA",
         unit == "I15") %>%
  select(geo, indic_bt, time, values) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Austria

Code
sts_inlb_m %>%
  filter(nace_r2 == "C",
         geo %in% c("AT"),
         s_adj == "SCA",
         unit == "I15") %>%
  select(geo, indic_bt, time, values) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))

Sweden

Code
sts_inlb_m %>%
  filter(nace_r2 == "C",
         geo %in% c("SE"),
         s_adj == "SCA",
         unit == "I15") %>%
  select(geo, indic_bt, time, values) %>%
  group_by(indic_bt) %>%
  mutate(values = 100*values/values[time == "2000M01"]) %>%
  left_join(indic_bt, by = "indic_bt") %>%
  month_to_date %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Indic_bt)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(-60, 300, 10))