Labour input in industry - monthly data - sts_inlb_m

Data - Eurostat

Author

François Geerolf

Info

Info

  • Few countries: not France

LAST_DOWNLOAD

Code 
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/sts_inlb_m.RData")$mtime)) %>%
  print_table_conditional()
LAST_DOWNLOAD
2024-10-08

LAST_COMPILE

LAST_COMPILE
2024-11-05

Last

Code 
sts_inlb_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M08 325

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 908885
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 797292
CA Calendar adjusted data, not seasonally adjusted data 567471

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 631210
I10 Index, 2010=100 398731
PCH_SM Percentage change compared to same period in previous year 317471
PCH_PRE Percentage change on previous period 255076

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 990627
HW Hours worked by employees 759115
EMP Persons employed 523906

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))