Salaire moyen par tête - SMPT (données CVS)

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee IPC-2015 2024-11-09 2024-11-09
insee IPCH-2015 2024-11-09 2024-11-09
insee t_salaire_val 2024-11-05 2024-09-02

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 2024-11-09 2024-11-09
insee CNT-2014-CSI 2024-11-09 2024-11-09
insee ECRT2023 2024-11-09 2023-06-30
insee if230 2024-11-09 2021-12-04
insee INDICE-TRAITEMENT-FP 2024-11-09 2024-11-09
insee ir_salaires_SL_23_csv 2024-11-09 NA
insee ir_salaires_SL_csv 2024-11-09 NA
insee SALAIRES-ACEMO 2024-11-09 2024-11-09
insee SALAIRES-ACEMO-2017 2024-11-09 2024-11-09
insee SALAIRES-ANNUELS 2024-11-09 2024-11-09
insee t_7401 2024-10-18 2024-10-18
insee t_salaire_val 2024-11-05 2024-09-02

Structure

  • Comptes nationaux trimestriels au troisième trimestre 2023. html

  • Salaires. xls

  • Comptes de branches. html

  • PIB et ses composantes. html

  • Secteurs et ses composantes. html

Bibliographie

Français

  • “Mesurer”le” pouvoir d’achat”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

  • “Inflation en France: IPC ou IPCH ?”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

  • “La taxe inflationniste, le pouvoir d’achat, le taux d’épargne et le déficit public”, F. Geerolf, Document de travail, Juillet 2024. [pdf]

variable

Code 
t_salaire_val %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
variable Nobs
(DE) à (C5) 302
(DE) à (MN), (RU) 302
(GZ) à (MN), (RU) 302
AZ 302
C 302
C1 302
C2 302
C3 302
C4 302
C5 302
DE 302
FZ 302
GZ 302
HZ 302
IZ 302
JZ 302
KZ 302
LZ 302
MN 302
OQ 302
RU 302
TOTAL 302

date

Code 
t_salaire_val %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(date)) %>%
  print_table_conditional()

2021, Trimestre 3

Code 
t_salaire_val %>%
  filter(date %in% c(as.Date("2023-01-01"), as.Date("2011-07-01"))) %>%
  spread(date, value) %>%
  mutate(evolution = 100*((`2023-01-01`/`2011-07-01`)^(1/10)-1)) %>%
  arrange(-`2023-01-01`) %>%
  print_table_conditional()
variable 2011-07-01 2023-01-01 evolution
JZ 12600.44 16176.99 2.5300574
C4 11459.67 14858.24 2.6312281
KZ 11152.06 14760.36 2.8428694
C2 13324.20 14615.38 0.9292153
C3 10572.97 12606.25 1.7744799
DE 10225.66 11841.71 1.4780953
LZ 9999.96 11809.12 1.6768135
C5 9069.05 11373.90 2.2903727
(DE) à (C5) 9034.88 11126.20 2.1039274
C 8917.54 11048.00 2.1654048
MN 8808.99 11033.89 2.2775352
FZ 8481.11 10486.59 2.1452461
(DE) à (MN), (RU) 8410.05 10453.75 2.1991663
(GZ) à (MN), (RU) 8249.55 10310.54 2.2551324
TOTAL 7850.94 9790.96 2.2328250
HZ 8201.12 9558.40 1.5432837
GZ 7304.48 9176.53 2.3078407
OQ 6745.16 8464.68 2.2967483
C1 6521.89 8271.56 2.4050551
RU 6267.34 7659.26 2.0258815
IZ 5847.97 6668.54 1.3217221
AZ 6216.56 5992.65 -0.3661578

Valeurs en Euros

KZ, JZ, C4

All

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = ""))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = ""))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("KZ", "JZ", "C4"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

C2, C3, C4, C5

All

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = ""))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = ""))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("C2", "C3", "C4", "C5"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

Agriculture, Industrie, Total

Value

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  ggplot() + ylab("Salaire moyen par tête - SMPT") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = 1000*seq(1, 300, 1),
                     labels = dollar_format(accuracy = 1, su = "€", pre = ""))

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 10),
                     labels = dollar_format(accuracy = 1, prefix = ""))

1996-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("1996-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1996-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 10),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2012-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2012-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2012-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2017-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2017-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2017T2-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2017-04-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2019T4-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2019-10-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2019-10-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2021T3-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2021-07-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr()

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 1),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2021T4-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "AZ", "C"),
         date >= as.Date("2021-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr()

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 1),
                     labels = dollar_format(accuracy = 1, prefix = ""))

Services Marchands, Total, Non Marchands

1990-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1990-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

1996-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("1996-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1996-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 5),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2012-

Code 
t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2012-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("2012-01-01")]) %>%
  ggplot() + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2017-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2017-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.5)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2017T2-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2017-04-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.5)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2019T4-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2019-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2021T2-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-04-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2021T3-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-07-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))

2021T4-

Code 
df <- t_salaire_val %>%
  filter(variable %in% c("TOTAL", "OQ", "(GZ) à (MN), (RU)"),
         date >= as.Date("2021-10-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  date_to_yearqtr %>%
  ungroup

ggplot(data = df) + ylab("") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = value, color = variable)) +
  scale_x_yearqtr(labels = date_format("%Y T%q"),
                  breaks = seq(from = min(df$date), to = max(df$date), by = 0.25)) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_log10(breaks = seq(10, 300, 2),
                     labels = dollar_format(accuracy = 1, prefix = ""))