Regional Labour - REGION_LABOUR

Data - OECD

Author

François Geerolf

TL

Code 
REGION_LABOUR %>%
  left_join(REGION_LABOUR_var$TL, by = "TL") %>%
  group_by(TL, Tl) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
TL Tl Nobs
2 Large regions (TL2) 1002078
3 Small regions (TL3) 904247
1 Country 149552
NOG Non Official Grids (NOG - Canada, France and Germany) 143800
1_IN Country - intermediate regions 19878
1_PU Country - predominantly urban regions 19084
1_PR Country - rural regions 16918

REG_ID

Code 
REGION_LABOUR %>%
  left_join(REGION_LABOUR_var$REG_ID, by = "REG_ID") %>%
  group_by(REG_ID, Reg_id) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

VAR

Code 
REGION_LABOUR %>%
  left_join(REGION_LABOUR_var$VAR, by = "VAR") %>%
  group_by(VAR, Var) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SEX

Code 
REGION_LABOUR %>%
  left_join(REGION_LABOUR_var$SEX, by = "SEX") %>%
  group_by(SEX, Sex) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
SEX Sex Nobs
T Total 1209391
F Females 680618
M Males 365548

POS

Code 
REGION_LABOUR %>%
  left_join(REGION_LABOUR_var$POS, by = "POS") %>%
  group_by(POS, Pos) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
POS Pos Nobs
ALL All regions 1994921
MIN Lowest regional value in the country by Territorial Level and selected indicators 93470
MAX Highest regional value in the country by Territorial Level and selected indicators 92390
AVG National average 74776

POS

Code 
REGION_LABOUR %>%
  group_by(TIME) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
TIME Nobs
1995 23742
1996 28924
1997 29007
1998 31279
1999 64160
2000 72104
2001 91732
2002 93706
2003 94274
2004 98727
2005 101564
2006 102183
2007 129031
2008 133157
2009 132747
2010 127719
2011 129313
2012 129758
2013 129728
2014 125869
2015 109038
2016 109495
2017 100578
2018 62979
2019 4743

UNEM_RA_15_MAX

Table

Code 
REGION_LABOUR %>%
  filter(VAR == "UNEM_RA_15_MAX",
         SEX == "T",
         UNIT == "PC",
         POS == "ALL",
         TIME %in% c("1997", "2017", "2012", "2007", "2002")) %>%
  left_join(REGION_LABOUR_var$REG_ID, by = "REG_ID") %>%
  select(TL, REG_ID, Reg_id, TIME, obsValue) %>%
  spread(TIME, obsValue) %>%
  print_table_conditional()

Belgium

Code 
REGION_LABOUR %>%
  filter(REG_ID %in% c("BE1", "BE2", "BE3"),
         VAR == "UNEM_RA_15_MAX",
         SEX == "T",
         POS == "ALL") %>%
  left_join(REGION_LABOUR_var$REG_ID, by = "REG_ID") %>%
  group_by(REG_ID) %>%
  arrange(TIME) %>%
  mutate(date = paste0(TIME, "-01-01") %>% as.Date) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue/100, color = Reg_id)) +
  scale_color_manual(values = viridis(4)[1:3]) + theme_minimal() +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.2, 0.87),
        legend.title = element_blank()) +
  xlab("") + ylab("Unemployment (%)") +
  scale_y_continuous(breaks = 0.01*seq(0, 200, 1),
                     labels = scales::percent_format(accuracy = 1))