Salaire moyen par tête - SMPT (données CVS) - t_salaire_val

Name: Salaire moyen par tête - SMPT (données CVS)
Creator: François Geerolf
License: https://www.etalab.gouv.fr/licence-ouverte-open-licence/

Données - INSEE

Auteur

François Geerolf

Last observation: Q2 2026 (N = 22)

First observation: Q1 1949 (N = 22)

Last data update: 03 sept. 2026, 05:31

Last compile: 06 sept. 2026, 14:47

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)	310
(DE) à (MN), (RU)	310
(GZ) à (MN), (RU)	310
AZ	310
C	310
C1	310
C2	310
C3	310
C4	310
C5	310
DE	310
FZ	310
GZ	310
HZ	310
IZ	310
JZ	310
KZ	310
LZ	310
MN	310
OQ	310
RU	310
TOTAL	310

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	12768.65	16336.46	2.4946737
KZ	11185.27	15081.70	3.0339578
C4	11388.75	15030.07	2.8131095
C2	13263.02	14987.31	1.2297412
C3	10514.33	12779.07	1.9698463
DE	10101.34	12025.02	1.7584966
LZ	9918.17	11787.47	1.7416802
C5	8925.36	11309.23	2.3954666
(DE) à (C5)	8880.06	11143.21	2.2961859
MN	8962.99	11093.07	2.1550602
C	8760.36	11046.34	2.3457105
FZ	8506.33	10582.37	2.2078073
(DE) à (MN), (RU)	8415.63	10524.61	2.2614480
(GZ) à (MN), (RU)	8288.86	10389.13	2.2841729
TOTAL	7851.81	9841.73	2.2845801
HZ	8147.86	9541.16	1.5911232
GZ	7255.33	9141.19	2.3374418
OQ	6733.73	8476.34	2.3281840
C1	6303.35	8272.30	2.7555967
RU	6249.46	7687.53	2.0926397
IZ	5978.69	7258.14	1.9581462
AZ	6317.28	5936.60	-0.6195941

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T1-

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2017T1-

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

2021T4-

Nominal

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 = "")) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value, color = variable, label = round(value, 1)))

Related Data

Évolution du pouvoir d’achat depuis 2017

source	dataset	Title	Updated
insee	t_salaire_val	Salaire moyen par tête - SMPT (données CVS) - t_salaire_val	2026-09-03
dares	les-indices-de-salaire-de-base	Les indices de salaire de base - les-indices-de-salaire-de-base	2026-08-30
eurostat	nama_10_pc	Main GDP aggregates per capita - nama_10_pc	2026-09-03
eurostat	nasq_10_nf_tr	Non-financial transactions - nasq_10_nf_tr	2026-08-28
insee	CNA-2020-CONSO-MEN	Consommation des ménages - CNA-2020-CONSO-MEN	2026-09-04
insee	INDICES_LOYERS	Indices des loyers d’habitation (ILH) - INDICES_LOYERS	2026-09-04
insee	IPEA-2021	Indice des prix d’entretien-amélioration des bâtiments - Base 2021 - IPEA-2021	2026-09-04
insee	IRL	Indice pour la révision d’un loyer d’habitation - IRL	2026-09-04
insee	SALAIRES-ANNUELS	Salaires annuels - SALAIRES-ANNUELS	2026-09-04
insee	SMIC-COTISATIONS	Taux de cotisations et salaires minima garantis - SMIC-COTISATIONS	2026-09-04
insee	T_2101	2.101 – Revenu disponible brut des ménages et évolution du pouvoir d’achat par personne, par ménage et par unité de consommation (En milliards euros et %) - T_2101	2026-09-02
insee	T_2103	2.103 – Dépense de consommation finale pré-engagée des ménages à prix courants (En milliards d’euros et %) - T_2103	2026-09-06
insee	T_7401	7.401 – Compte des ménages (S14) (En milliards d’euros) - T_7401	2026-09-02
insee	econ-gen-revenu-dispo-pouv-achat-2	Revenu disponible brut et pouvoir d’achat - Données annuelles - econ-gen-revenu-dispo-pouv-achat-2	2026-08-02
insee	t_men_val	Revenu, pouvoir d’achat et comptes des ménages - Valeurs aux prix courants - t_men_val	2026-09-03
insee	t_pib_vol	PIB et ses composantes - Equilibre emplois-ressources - volumes aux prix de l’année précédente chaînés - t_pib_vol	2026-09-03
insee	t_pouvachat_val	Pouvoir d’achat et ratios des comptes des ménages - t_pouvachat_val	2026-09-03
insee	t_recapAgent_val	Récapitulatif des séries des comptes d’agents - t_recapAgent_val	2026-09-03
ipp	indicefp	Point d’indice de la fonction publique - indicefp	2026-09-04
ipp	revalorisation_pension	Revalorisation du Régime général de la caisse nationale d’assurance vieillesse (CNAV) - revalorisation_pension	2026-08-01
oecd	PRICES_ALL	Consumer price indices (CPIs) - PRICES_ALL	2026-09-05

Analyse des Données de Salaires

source	dataset	Title	Updated
insee	t_salaire_val	Salaire moyen par tête - SMPT (données CVS) - t_salaire_val	2026-09-03
dares	les-indices-de-salaire-de-base	Les indices de salaire de base - les-indices-de-salaire-de-base	2026-08-30
insee	INDICE-TRAITEMENT-FP	Indice de traitement brut dans la fonction publique de l’État - INDICE-TRAITEMENT-FP	2026-09-04
insee	SALAIRES-ACEMO	Indices trimestriels de salaires dans le secteur privé - Résultats par secteur d’activité - SALAIRES-ACEMO	2026-09-04
insee	SALAIRES-ACEMO-2017	Indices trimestriels de salaires dans le secteur privé - SALAIRES-ACEMO-2017	2026-09-04
insee	SALAIRES-ANNUELS	Salaires annuels - SALAIRES-ANNUELS	2026-09-04
insee	SMIC-COTISATIONS	Taux de cotisations et salaires minima garantis - SMIC-COTISATIONS	2026-09-04
insee	T_2101	2.101 – Revenu disponible brut des ménages et évolution du pouvoir d’achat par personne, par ménage et par unité de consommation (En milliards euros et %) - T_2101	2026-09-02