Chômage, taux de chômage par sexe et âge (sens BIT) (1975-)

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee CHOMAGE-TRIM-NATIONAL 2024-11-15 2024-11-17

Données sur l’emploi

source dataset .html .RData
insee CHOMAGE-TRIM-NATIONAL 2024-11-15 2024-11-17
insee CNA-2014-EMPLOI 2024-06-07 2024-11-09
insee DEMANDES-EMPLOIS-NATIONALES 2024-11-09 2024-11-09
insee EMPLOI-BIT-TRIM 2024-06-07 2024-11-09
insee EMPLOI-SALARIE-TRIM-NATIONAL 2024-11-16 2024-11-16
insee TAUX-CHOMAGE 2024-11-09 2024-11-09
insee TCRED-EMPLOI-SALARIE-TRIM 2024-11-09 2024-11-09

Data on employment

source dataset .html .RData
bls jt 2024-11-12 NA
bls la 2024-11-12 NA
bls ln 2024-11-12 NA
eurostat nama_10_a10_e 2024-11-08 2024-11-09
eurostat nama_10_a64_e 2024-11-16 2024-11-16
eurostat namq_10_a10_e 2024-11-16 2024-11-16
eurostat une_rt_m 2024-11-15 2024-11-15
oecd ALFS_EMP 2024-04-16 2024-05-12
oecd EPL_T 2024-11-12 2023-12-10
oecd LFS_SEXAGE_I_R 2024-09-15 2024-04-15
oecd STLABOUR 2024-09-15 2024-06-30

LAST_UPDATE

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2024-11-13 13080
2019-08-14 5634

INDICATEUR

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  left_join(INDICATEUR,  by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
INDICATEUR Indicateur Nobs
CTTXC Taux de chômage 4776
CTCHC Nombre de chômeurs 4524
HALO Personnes dans le halo autour du chômage 3798
CTTC15 Part de chômeurs dans la population 15 ans et plus 2907
TXCHLODU Taux de chômage de longue durée 1836
CHLODU Nombre de chômeurs de longue durée 153
HALO_1 Personnes dans le halo autour du chômage : inactifs faisant des démarches actives de recherche d'emploi mais non disponibles 153
HALO_2 Personnes dans le halo autour du chômage : inactifs disponibles mais ne faisant pas de démarche active de recherche d'emploi 153
HALO_3 Personnes dans le halo autour du chômage : inactifs souhaitant travailler mais non disponibles et ne faisant pas de démarche active de recherche d'emploi 153
PCONTR1 Part des chômeurs parmi les participants au marché du travail de 15 à 64 ans 87
PCONTR2 Part des personnes au chômage ou dans le halo parmi les participants au marché du travail de 15 à 64 ans 87
PCONTR3 Part des personnes contraintes sur leur offre de travail parmi les participants au marché du travail de 15 à 64 ans 87

TIME_PERIOD

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

AGE

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  left_join(AGE,  by = "AGE") %>%
  group_by(AGE, Age) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
AGE Age Nobs
25-49 De 25 à 49 ans 3963
00- Ensemble 3396
50- 50 ans et plus 3396
00-24 Moins de 25 ans 2784
15-64 De 15 à 64 ans 1440
15-24 De 15 à 24 ans 1179
50-64 De 50 à 64 ans 1179
15- 15 ans et plus 459
55-64 De 55 à 64 ans 459
SO Sans objet 459

NATURE

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  left_join(NATURE,  by = "NATURE") %>%
  group_by(NATURE, Nature) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
NATURE Nature Nobs
VALEUR_ABSOLUE Valeur absolue 7890
TAUX Taux 6612
PROPORTION Proportion 4212

SEXE

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  left_join(SEXE,  by = "SEXE") %>%
  group_by(SEXE, Sexe) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
SEXE Sexe Nobs
0 Ensemble 6922
1 Hommes 5896
2 Femmes 5896

UNIT_MULT

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  group_by(UNIT_MULT) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
UNIT_MULT Nobs
0 10824
3 7890

REF_AREA

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  group_by(REF_AREA) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
REF_AREA Nobs
FR-D976 10692
FM 8022

Personnes dans le Halo du chômage

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(grepl("halo", TITLE_FR)) %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Halo du chomage

Ensemble

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(IDBANK %in% c("010605056", 
                       "010605048",
                       "010605049",
                       "010605050")) %>%
  select(AGE, TITLE_FR, TIME_PERIOD, OBS_VALUE) %>%
  mutate(OBS_VALUE = OBS_VALUE %>% as.numeric,
         TITLE_FR = TITLE_FR %>% gsub("\\(en milliers\\) - France hors Mayotte - Données CVS", "", .),
         TITLE_FR = TITLE_FR %>% gsub("Personnes dans le halo autour du chômage - ", "", .)) %>%
  quarter_to_date %>%
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE, color = TITLE_FR, linetype = TITLE_FR)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(0, 9000, 500),
                     labels = dollar_format(accuracy = 1, prefix = "", su = " K")) +
  ylab("Halo du Chômage (en milliers)") + xlab("")

Inactifs

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR %in% c("CHLODU", "HALO_1", "HALO_2", "HALO_3"),
         REF_AREA == "FR-D976") %>%
  quarter_to_date %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  mutate(Indicateur = gsub("Personnes dans le halo autour du chômage : ", "", Indicateur)) %>%
  arrange(date) %>%
  select(date, OBS_VALUE, INDICATEUR, Indicateur) %>%
  ggplot() + ylab("Halo du Chômage (en milliers)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = OBS_VALUE, color = Indicateur, linetype = Indicateur)) +
  
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.55, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(0, 9000, 200),
                     labels = dollar_format(accuracy = 1, prefix = ""),
                     limits = c(0, 2000))

Nombre de chômeurs

Tous

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTCHC",
         AGE == "00-",
         SEXE == "0") %>%
  quarter_to_date %>%
  left_join(REF_AREA, by  = "REF_AREA") %>%
  ggplot() + theme_minimal() + ylab("Nombre de chômeurs") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Ref_area)) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.15),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(0, 3000, 500),
                     labels = dollar_format(accuracy = 1, pre = "", su = " K"))

Taux de chômage

Tous

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         AGE == "00-",
         SEXE == "0") %>%
  quarter_to_date %>%
  left_join(REF_AREA, by  = "REF_AREA") %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Ref_area)) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.15),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 20, 1),
                     labels = percent_format(accuracy = 1)) + 
  geom_hline(yintercept = 0.05, linetype = "dashed")

1990-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         AGE == "00-",
         SEXE == "0") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  left_join(REF_AREA, by  = "REF_AREA") %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE, color = Ref_area)) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.15),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 20, 1),
                     labels = percent_format(accuracy = 1))

Genre

Tous

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         AGE == "00-") %>%
  quarter_to_date %>%
  left_join(SEXE, by  = "SEXE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Sexe, linetype = Sexe)) +
  scale_color_manual(values = c("black", "red", "blue")) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.3),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 20, 1),
                     labels = percent_format(accuracy = 1))

2005-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         AGE == "00-") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(SEXE, by  = "SEXE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Sexe, linetype = Sexe)) +
  scale_color_manual(values = c("black", "red", "blue")) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% 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(0, 20, .5),
                     labels = percent_format(accuracy = .1))

2010-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         AGE == "00-") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2010-01-01")) %>%
  left_join(SEXE, by  = "SEXE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Sexe, linetype = Sexe)) +
  scale_color_manual(values = c("black", "red", "blue")) +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 20, .5),
                     labels = percent_format(accuracy = .1))

Nombre de chômeurs

All

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR %in% c("CTCHC", "CHLODU"),
         SEXE == "0",
         AGE == "00-24") %>%
  quarter_to_date %>%
  left_join(REF_AREA, by  = "REF_AREA") %>%
  ggplot() + theme_minimal() + ylab("Nombre de chômeurs") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE*1000, color = Ref_area)) +
  
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.88),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(100, 1100, 50),
                     labels = dollar_format(pre = ""))

1990-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTCHC",
         SEXE == "0",
         AGE == "00-24") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1990-01-01")) %>%
  left_join(REF_AREA, by  = "REF_AREA") %>%
  ggplot() + theme_minimal() + ylab("Nombre de chômeurs") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE*1000, color = Ref_area)) +
  
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.4, 0.88),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 1000*seq(100, 1100, 50),
                     labels = dollar_format(pre = ""))

Age (Tous)

Tous

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0") %>%
  quarter_to_date %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.12, 0.88),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 5),
                     labels = percent_format(accuracy = 1))

2005-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 2),
                     labels = percent_format(accuracy = 1))

2010-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 2),
                     labels = percent_format(accuracy = 1))

2017-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2017-01-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = "6 months",
               labels = date_format("%b %y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 2),
                     labels = percent_format(accuracy = 1))

Age (sauf - de 25 ans)

Tous

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0",
         AGE != "00-24") %>%
  quarter_to_date %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 1),
                     labels = percent_format(accuracy = 1),
                     limits = c(0, 0.13))

2005-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0",
         AGE != "00-24") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 1),
                     labels = percent_format(accuracy = 1))

2010-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0",
         AGE != "00-24") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 1),
                     labels = percent_format(accuracy = 1))

2017-

Code 
`CHOMAGE-TRIM-NATIONAL` %>%
  filter(INDICATEUR == "CTTXC",
         REF_AREA == "FR-D976",
         SEXE == "0",
         AGE != "00-24") %>%
  quarter_to_date %>%
  filter(date >= as.Date("2017-04-01")) %>%
  left_join(AGE, by  = "AGE") %>%
  ggplot() + theme_minimal() + ylab("Taux de chômage (%)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/100, color = Age)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.9, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 1),
                     labels = percent_format(accuracy = 1))