Séries longues sur les salaires dans le secteur privé - Base Tous salariés - Insee Résultats

Data - INSEE

Author

François Geerolf

Info

source dataset .html .RData
insee ir_salaires_SL_csv 2024-10-29 NA

Données sur les salaires

source dataset .html .RData
dares les-indices-de-salaire-de-base 2024-11-04 2024-09-21
insee CNA-2014-RDB 2024-11-05 2024-11-05
insee CNT-2014-CSI 2024-11-05 2024-11-05
insee ECRT2023 2024-11-05 2023-06-30
insee if230 2024-11-05 2021-12-04
insee INDICE-TRAITEMENT-FP 2024-11-05 2024-11-05
insee ir_salaires_SL_23_csv 2024-11-05 NA
insee ir_salaires_SL_csv 2024-10-29 NA
insee SALAIRES-ACEMO 2024-10-29 2024-11-05
insee SALAIRES-ACEMO-2017 2024-10-29 2024-11-05
insee SALAIRES-ANNUELS 2024-10-29 2024-11-05
insee t_7401 2024-10-18 2024-10-18
insee t_salaire_val 2024-11-03 2024-09-02

Info

  • Séries longues sur les salaires dans le secteur privé. html

metadonnées

Tables

Code 
metadonnees %>%
  group_by(COD_VAR, LIB_VAR) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

Tous

Code 
metadonnees %>%
  print_table_conditional()

inflation

Table

Code 
inflation %>%
  print_table_conditional()

Graph

All

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(100, 200, 300, 500, 800, 1000, 1200, 1500, 2000)) +
  theme_minimal() + xlab("") + ylab("")

1990-

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1990-01-01")) %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric,
         INFLATION = 100*INFLATION/INFLATION[date == as.Date("1990-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 10)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 1990)")

1995-

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric,
         INFLATION = 100*INFLATION/INFLATION[date == as.Date("1995-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 10)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 1990)")

1996-

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1996-01-01")) %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric,
         INFLATION = 100*INFLATION/INFLATION[date == as.Date("1996-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2024, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 5)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 1996)")

2000-

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  filter(date >= as.Date("2000-01-01")) %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric,
         INFLATION = 100*INFLATION/INFLATION[date == as.Date("2000-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 5)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 2000)")

2012-

Code 
inflation %>%
  rename(year = ANNEE14) %>%
  year_to_date2 %>%
  filter(date >= as.Date("2012-01-01")) %>%
  mutate(INFLATION = INFLATION %>% gsub(",", "\\.", .) %>% as.numeric,
         INFLATION = 100*INFLATION/INFLATION[date == as.Date("2012-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = INFLATION)) +
  scale_x_date(breaks = seq(1950, 2020, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 1)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 2012)")

IND_CR35 – En euros, pour une durée de 35 heures hebdomadaires

Table

Code 
ind_cr35 %>%
  print_table_conditional()
ANNEE12 SHBO SMICBM SMICNM PLFB PLFN SNAM_TC SNAM_EQTP IPC
2000 100.0 100.0 100.0 100.0 100.0 100 100 100.0
2001 104.3 103.6 103.8 101.7 101.8 102.1 102.3 101.6
2002 108.2 107.0 107.2 105.0 105.2 104.4 104.5 103.6
2003 111.3 111.1 110.8 108.5 108.3 106.4 106.7 105.8
2004 114.4 117.3 117.0 110.5 110.2 108.7 109.1 108.0
2005 117.9 123.9 123.4 112.3 111.8 111.9 112.2 110.0
2006 121.5 129.2 128.4 115.5 114.8 113.7 114.3 111.8
2007 124.9 132.4 131.7 119.7 119.0 117.3 117.9 113.5
2008 128.6 136.4 135.6 123.7 123.0 121.1 121.5 116.7
2009 131.9 138.9 138.1 127.6 126.9 122.8 123.1 116.8
2010 134.4 140.4 139.6 128.7 128.0 125.3 125.6 118.5
2011 137.2 142.9 142.1 131.5 130.7 128.3 128.7 121.0
2012 140.3 147.5 146.5 135.3 134.3 130.1 130.7 123.4
2013 142.9 149.4 148.2 137.7 136.6 131.1 131.5 124.5
2014 145.1 151.0 149.3 139.6 138.0 132.3 132.9 125.1
2015 146.8 152.3 150.3 141.5 139.6 133.9 134.4 125.2
2016 148.5 153.2 151.0 143.6 141.5 134.5 135.2 125.4
2017 150.3 154.7 152.3 145.9 143.7 137.6 137.9 126.7
2018 152.6 156.6 155.7 147.7 146.9 140.5 140.9 129.0
2019 155.2 159.0 159.3 150.7 151.0 nd nd 130.5
2020 157.7 160.9 161.2 153.0 153.3 nd nd 131.1

Inflation

Code 
ind_cr35 %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  filter(date >= as.Date("2000-01-01")) %>%
  mutate(IPC = 100*IPC/IPC[date == as.Date("2000-01-01")]) %>%
  ggplot + geom_line(aes(x = date, y = IPC)) +
  scale_x_date(breaks = seq(1950, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 200, 5)) +
  theme_minimal() + xlab("") + ylab("Inflation (100 = 2000)")

Smic net, Salaire horaire de base des ouvriers

Code 
ind_cr35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "IND_COURANT_35H"), by = "COD_MOD") %>%
    filter(COD_MOD %in% c("SHBO", "IPC", "SMICNM")) %>%
  group_by(COD_MOD) %>%
  mutate(value = as.numeric(value),
         value = 100*value/value[date == as.Date("2000-01-01")]) %>%
  ggplot() + ylab("Indice (2000 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LIB_MOD1)) +
  
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

SMIC39 – Pour 40 heures puis 39 heures hebdomadaires, de 1951 à 2005 (en euros)

Table

Code 
smic39 %>%
  print_table_conditional()

Nobs

Code 
smic39 %>%
  gather(COD_MOD, value, -ANNEE13) %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
  group_by(COD_MOD, LIB_MOD1) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
COD_MOD LIB_MOD1 Nobs
COUT_SMICA Coût annuel d'un salarié au Smic 55
COUT_SMICM Coût mensuel d'un salarié au Smic 55
DUREE Durée légale mensuelle (en heures) 55
SMICBA Salaire minimum brut annuel 55
SMICBH Salaire minimum brut horaire 55
SMICBM Salaire minimum brut mensuel 55
SMICNA Salaire minimum annuel net de prélèvements 55
SMICNH Salaire minimum horaire net de prélèvements 55
SMICNM Salaire minimum mensuel net de prélèvements 55

SMIC35 – Pour 35 heures hebdomadaires (en euros)

Table

Code 
smic35 %>%
  print_table_conditional()
ANNEE12 DUREE SMICBH SMICBM SMICBA SMICNH SMICNM SMICNA COUT_SMICM COUT_SMICA
2000 151.7 6.3 957.0 11484.2 5.0 756.0 9071.4 1098.2 13178.7
2001 151.7 6.5 991.9 11902.8 5.2 784.6 9415.1 1135.1 13621.6
2002 151.7 6.8 1023.8 12285.0 5.3 810.3 9723.6 1172.7 14072.5
2003 151.7 7.0 1063.2 12758.2 5.5 837.8 10053.5 1223.0 14676.2
2004 151.7 7.4 1122.3 13468.0 5.8 884.4 10612.8 1295.3 15543.4
2005 151.7 7.8 1186.0 14232.4 6.2 932.7 11192.4 1370.4 16444.8
2006 151.7 8.2 1236.1 14833.0 6.4 970.3 11643.9 1428.5 17142.5
2007 151.7 8.4 1267.2 15206.1 6.6 995.2 11942.9 1463.3 17560.0
2008 151.7 8.6 1305.3 15664.1 6.8 1025.2 12302.6 1507.1 18085.0
2009 151.7 8.8 1329.4 15952.3 6.9 1044.1 12528.9 1536.5 18437.7
2010 151.7 8.9 1343.8 16125.2 7.0 1055.4 12664.7 1555.1 18661.7
2011 151.7 9.0 1367.4 16408.8 7.1 1074.0 12887.5 1581.5 18977.6
2012 151.7 9.3 1412.0 16944.2 7.3 1107.3 13288.2 1633.0 19595.4
2013 151.7 9.4 1430.2 17162.6 7.4 1120.4 13445.2 1655.2 19862.3
2014 151.7 9.5 1445.4 17344.6 7.4 1128.7 13544.4 1674.6 20095.5
2015 151.7 9.6 1457.5 17490.2 7.5 1136.0 13631.9 1645.5 19745.7
2016 151.7 9.7 1466.6 17599.4 7.5 1141.6 13699.4 1646.2 19754.6
2017 151.7 9.8 1480.3 17763.2 7.6 1151.5 13818.0 1660.8 19929.2
2018 151.7 9.9 1498.5 17981.6 7.8 1177.2 14125.9 1681.2 20174.6
2019 151.7 10.0 1521.2 18254.6 7.9 1204.2 14450.3 1602.3 19228.2
2020 151.7 10.2 1539.4 18473.0 8.0 1218.6 14623.2 1574.8 18897.1

Nobs

Code 
smic35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
  group_by(COD_MOD, LIB_MOD1) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
COD_MOD LIB_MOD1 Nobs
COUT_SMICA Coût annuel d'un salarié au Smic 21
COUT_SMICM Coût mensuel d'un salarié au Smic 21
DUREE Durée légale mensuelle (en heures) 21
SMICBA Salaire minimum brut annuel 21
SMICBH Salaire minimum brut horaire 21
SMICBM Salaire minimum brut mensuel 21
SMICNA Salaire minimum annuel net de prélèvements 21
SMICNH Salaire minimum horaire net de prélèvements 21
SMICNM Salaire minimum mensuel net de prélèvements 21

Cout mensuel, Salaire mensuel, salaire net mensuel - Indice

All

Code 
smic35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
    filter(COD_MOD %in% c("COUT_SMICM", "SMICBM", "SMICNM")) %>%
  group_by(COD_MOD) %>%
  mutate(value = 100*value/value[date == as.Date("2000-01-01")]) %>%
  ggplot() + ylab("Indice (2000 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LIB_MOD1)) +
  
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.3),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2012

Code 
smic35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
    filter(COD_MOD %in% c("COUT_SMICM", "SMICBM", "SMICNM"),
           date >= as.Date("2012-01-01")) %>%
  group_by(COD_MOD) %>%
  mutate(value = 100*value/value[date == as.Date("2012-01-01")]) %>%
  ggplot() + ylab("Indice (2000 = 100)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LIB_MOD1)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(0, 200, 1),
                     labels = dollar_format(accuracy = 1, prefix = ""))

Cout mensuel, Salaire mensuel, salaire net mensuel - Euros

All

Code 
smic35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
    filter(COD_MOD %in% c("COUT_SMICM", "SMICBM", "SMICNM")) %>%
  ggplot() + ylab("Montant mensuel") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LIB_MOD1)) +
  
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.3),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 2000, 100),
                     labels = dollar_format(accuracy = 1, prefix = "", suffix = "€"))

2012

Code 
smic35 %>%
  gather(COD_MOD, value, -ANNEE12) %>%
  rename(year = ANNEE12) %>%
  year_to_date2 %>%
  left_join(metadonnees %>%
              filter(COD_VAR == "SMIC"), by = "COD_MOD") %>%
    filter(COD_MOD %in% c("COUT_SMICM", "SMICBM", "SMICNM"),
           date >= as.Date("2012-01-01")) %>%
  ggplot() + ylab("Montant mensuel") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LIB_MOD1)) +
  
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.4),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 2000, 50),
                     labels = dollar_format(accuracy = 1, prefix = "", suffix = "€"))