Incidence of unemployment by duration - DUR_I

Data - OECD

~/data/oecd/

load_data("oecd/DUR_I_var.RData")
load_data("oecd/DUR_I.RData")

Nobs - Javascript

DUR_I %>%
  left_join(DUR_I_var %>% pluck("DURATION"), by = c("DURATION" = "id")) %>%
  rename(`DURATION Description` = label) %>%
  group_by(DURATION, `DURATION Description`, SEX, AGE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Data Structure

DUR_I_var %>%
  pluck("VAR_DESC") %>%
  {if (is_html_output()) print_table(.) else .}

id	description
COUNTRY	Country
TIME	Time
SEX	Sex
AGE	Age
DURATION	Duration
FREQUENCY	Frequency
OBS_VALUE	Observation Value
TIME_FORMAT	Time Format
OBS_STATUS	Observation Status
UNIT	Unit
POWERCODE	Unit multiplier
REFERENCEPERIOD	Reference period

DURATION

DUR_I %>%
  left_join(DUR_I_var %>% pluck("DURATION"), by = c("DURATION" = "id")) %>%
  rename(`DURATION Description` = label) %>%
  group_by(DURATION, `DURATION Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

DURATION	DURATION Description	Nobs
UN3	> 3 month and < 6 months	34114
UN5	1 year and over	34094
UN4	> 6 month and < 1 year	34076
UN2	> 1 month and < 3 months	33833
UN1	< 1 month	32186

SEX

DUR_I %>%
  left_join(DUR_I_var %>% pluck("SEX"), by = c("SEX" = "id")) %>%
  rename(`SEX Description` = label) %>%
  group_by(SEX, `SEX Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

SEX	SEX Description	Nobs
MW	All persons	56946
MEN	Men	56228
WOMEN	Women	55129

AGE

DUR_I %>%
  left_join(DUR_I_var %>% pluck("AGE"), by = c("AGE" = "id")) %>%
  rename(`AGE Description` = label) %>%
  group_by(AGE, `AGE Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

AGE	AGE Description	Nobs
900000	Total	27046
2554	25 to 54	26235
1524	15 to 24	26154
5564	55 to 64	25207
2024	20 to 24	23104
1519	15 to 19	22925
6599	65+	17632

All persons, All ages

France

DUR_I %>%
  filter(AGE == "900000", 
         SEX == "MW",
         COUNTRY == "FRA") %>%
  year_to_enddate %>%
  ggplot() + theme_minimal() +
  geom_line(aes(x = date, y = obsValue/100, color = DURATION, linetype = DURATION)) + 
  scale_color_manual(values = viridis(6)[1:5]) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1920, 2025, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = scales::percent_format(accuracy = 1))

Germany

DUR_I %>%
  filter(AGE == "900000", 
         SEX == "MW",
         COUNTRY == "DEU") %>%
  year_to_enddate %>%
  ggplot() + theme_minimal() +
  geom_line(aes(x = date, y = obsValue/100, color = DURATION, linetype = DURATION)) + 
  scale_color_manual(values = viridis(6)[1:5]) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  xlab("") + ylab("Unemployment Rate (%)") +
  scale_x_date(breaks = seq(1920, 2025, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = scales::percent_format(accuracy = 1))