Labour market transitions - quarterly data - lfsi_long_q

Data - Eurostat

Author

François Geerolf

unit

Code 
lfsi_long_q %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
PC_EMP Percentage of total employment 109323
PC_INAC Percentage of population outside the labour force 109323
PC_UNE Percentage of unemployment 109323
THS_PER Thousand persons 107001

s_adj

Code 
lfsi_long_q %>%
  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
SA Seasonally adjusted data, not calendar adjusted data 217539
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 217431

indic_em

Code 
lfsi_long_q %>%
  left_join(indic_em, by = "indic_em") %>%
  group_by(indic_em, Indic_em) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
indic_em Indic_em Nobs
E_E Transition employment - employment 48330
E_I Transition employment - outside the labour force 48330
E_U Transition employment - unemployment 48330
I_E Transition outside the labour force - employment 48330
I_I Transition outside the labour force - outside the labour force 48330
I_U Transition outside the labour force - unemployment 48330
U_E Transition unemployment - employment 48330
U_I Transition unemployment - outside the labour force 48330
U_U Transition unemployment - unemployment 48330

sex

Code 
lfsi_long_q %>%
  left_join(sex, by = "sex") %>%
  group_by(sex, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
sex Sex Nobs
F Females 144990
M Males 144990
T Total 144990

geo

Code 
lfsi_long_q %>%
  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 
lfsi_long_q %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()

France

Table

Code 
lfsi_long_q %>%
  filter(geo == "FR",
         sex == "T",
         s_adj == "SA",
         unit == "THS_PER",
         time %in% c("2015Q2", "2021Q2", "2019Q2", "2017Q2")) %>%
  filter(!is.na(values)) %>%
  left_join(indic_em, by = "indic_em") %>%
  select(indic_em, Indic_em, time, values) %>%
  spread(time, values) %>%
  print_table_conditional()
indic_em Indic_em 2015Q2 2017Q2 2019Q2 2021Q2
E_E Transition employment - employment 25257 25548 25996 26262
E_I Transition employment - outside the labour force 565 551 599 637
E_U Transition employment - unemployment 527 441 443 443
I_E Transition outside the labour force - employment 448 616 507 719
I_I Transition outside the labour force - outside the labour force 16598 16881 17133 16837
I_U Transition outside the labour force - unemployment 684 746 632 698
U_E Transition unemployment - employment 644 637 598 631
U_I Transition unemployment - outside the labour force 508 524 539 530
U_U Transition unemployment - unemployment 1864 1641 1416 1240

EE, II

Code 
lfsi_long_q %>%
  filter(geo == "FR",
         sex == "T",
         s_adj == "SA",
         unit != "THS_PER",
         indic_em %in% c("E_E", "I_I")) %>%
  filter(!is.na(values)) %>%
  left_join(indic_em, by = "indic_em") %>%
  select(indic_em, Indic_em, time, values) %>%
  quarter_to_date() %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values/100, color = Indic_em)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2022, 1), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(acc = 1))

Italy

EE, II

Code 
lfsi_long_q %>%
  filter(geo == "IT",
         sex == "T",
         s_adj == "SA",
         unit != "THS_PER",
         indic_em %in% c("E_E", "I_I")) %>%
  filter(!is.na(values)) %>%
  left_join(indic_em, by = "indic_em") %>%
  select(indic_em, Indic_em, time, values) %>%
  quarter_to_date() %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values/100, color = Indic_em)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2022, 1), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(acc = 1))