7.401 – Compte des ménages (S14) (En milliards d’euros) - T_7401

Name: 7.401 – Compte des ménages (S14) (En milliards d'euros)
Creator: François Geerolf
License: https://www.etalab.gouv.fr/licence-ouverte-open-licence/

Données - INSEE

Auteur

François Geerolf

Last observation: 2025 (N = 101)

First observation: 1949 (N = 74)

Last data update: 02 sept. 2026, 19:13

Last compile: 04 sept. 2026, 02:21

Bibliographie en lien

Français

« Mesurer “le” pouvoir d’achat », F. Geerolf, 9 juillet 2024. [ html] [ pdf] [ handouts] [ slides] [ slides] [ github]

« La taxe inflationniste, le pouvoir d’achat, le taux d’épargne et le déficit public », F. Geerolf, 9 juillet 2024. [ html] [ pdf] [ handouts] [ slides] [ slides] [ github]

« Inflation en France : IPC ou IPCH ? », F. Geerolf, 9 juillet 2024. [ html] [ pdf] [ handouts] [ slides] [ slides] [ github]

Exemple

Début

Code

ig_b("insee", "t_7401_1")

Milieu

Code

ig_b("insee", "t_7401_2")

Fin

Code

ig_b("insee", "t_7401_3")

All

Code

ig_b("insee", "t_7401_bind")

Sources

7.401 – Compte des ménages (S14) (En milliards d’euros):

Comptes de la Nation 2022. html / xlsx
Comptes de la Nation 2020. html / xlsx
Comptes de la Nation 2019. html

Données reliées

2.101 – Revenu disponible brut des ménages et évolution du pouvoir d’achat par personne, par ménage et par unité de consommation (En milliards d’euros et %) - T_2101. html
2.104 – Compte des ménages simplifié et ratios d’épargne (En milliards d’euros et %) - t_2104. html
2.104 – Compte des ménages simplifié et ratios d’épargne (En milliards d’euros et %) - t_2104_2018. html
7.401 – Compte des ménages (S14) (En milliards d’euros) - T_7401. html
Comptes des secteurs institutionnels - CNA-2014-CSI. html

Concepts

Revenu primaire au RDB des ménages

2021

Code

ig_b("insee", "FPORSOC22", "F29", "table2")

2020

Code

ig_b("insee", "FPS2021", "revenu-primaire-RDB")

Composition du RDB des ménages

Code

ig_b("insee", "FPS2021", "EC4", "tab1")

Prestations de protection sociale en 2018

Code

ig_b("insee", "TEF2020", "057", "prestations-sociales")

line, Line

Code

T_7401 |>
  group_by(line, variable, Variable) |>
  summarise(Nobs = n()) |>
  print_table_conditional()

gdp

Code

gdp |>
  print_table_conditional()

Croissance, 2017-2024

Code

T_7401 |>
  filter(year %in% c("2017", "2024")) |>
  select(line, code, label, year, value) |>
  spread(year, value) |>
  mutate(croissance = round(100*(`2024`/`2017`-1), 2)) |>
  arrange(desc(croissance)) |>
  print_table_conditional()

Table in 2000, 2005, 2010, 2015, 2020, 2023

Milliards

Code

T_7401 |>
  filter(year %in% c(paste0(seq(1980, 2100, 20)), 2023)) |>
  select(line, variable, Variable, year, value) |>
  spread(year, value) |>
  arrange(line) %>%
  mutate_at(vars(-line, -variable, -Variable), funs(round(.))) |>
  print_table_conditional()

%

Code

T_7401 |>
  left_join(gdp, by = "year") |>
  mutate(value_gdp = round(100 * value / gdp, 1)) |>
  filter(year %in% c(paste0(seq(1980, 2100, 20)), 2023)) |>
  select(-value, -gdp) |>
  spread(year, value_gdp) |>
  arrange(line) |>
  print_table_conditional()

D5 (line 52), D4 (line 30), B3g (line 22)

Tous

Code

T_7401 |>
  filter(line %in% c(52, 30, 22)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.6, 0.9),
        legend.title = element_blank())

1995-

Code

T_7401 |>
  filter(line %in% c(52, 30, 22)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Revenu Disponible Brut (RDB), Ajusté (RDBA)

Code

T_7401 |>
  filter(variable %in% c("B6G", "B7G")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.15),
        legend.title = element_blank())

Revenu Disponible brut, Solde des revenus primaires bruts

Code

T_7401 |>
  filter(variable %in% c("B6G", "B5G", "B7G")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.15),
        legend.title = element_blank())

Consommation finale effective, Dépense de consommation individuelle

Code

T_7401 |>
  filter(variable %in% c("P31", "P4")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.7, 0.6),
        legend.title = element_blank())

Dividendes

% du PIB

Code

T_7401 |>
  filter(variable %in% c("D42")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("Revenus Distributés des Sociétés - Dividendes (% du PIB)") +
  scale_x_date(breaks =seq.Date(from = as.Date("1947-01-01"), to = Sys.Date(), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                     labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

Milliards

Linéaire

Code

T_7401 |>
  filter(variable %in% c("D42")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value)) +
  theme_minimal() + xlab("") + ylab("Revenus Distributés des Sociétés - Dividendes (Milliards)") +
  scale_x_date(breaks =seq.Date(from = as.Date("1947-01-01"), to = Sys.Date(), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-10, 100, 10)) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

Log

Code

T_7401 |>
  filter(variable %in% c("D42")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value)) +
  theme_minimal() + xlab("") + ylab("Revenus Distributés des Sociétés - Dividendes (Milliards)") +
  scale_x_date(breaks =seq.Date(from = as.Date("1947-01-01"), to = Sys.Date(), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(c(1, 2, 3, 5, 8), seq(-10, 100, 10))) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

Epargne brute et nette

All

Code

T_7401 |>
  filter(variable %in% c("B8G", "B8N"),
         line %in% c(100, 101)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks ="5 years",
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1978-

Code

T_7401 |>
  filter(variable %in% c("B8G", "B8N"),
         line %in% c(100, 101)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1978-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Epargne brute et nette, CCF

All

Code

T_7401 |>
  filter(variable %in% c("B8G", "B8N", "P51C"),
         line %in% c(100, 101, 6)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks ="5 years",
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1978-

Code

T_7401 |>
  filter(variable %in% c("B8G", "B8N", "P51C"),
         line %in% c(100, 101, 6)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1978-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

CCF

All

Code

T_7401 |>
  filter(variable %in% c("P51C"),
         line %in% c(100, 101, 6)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks ="5 years",
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                     labels = percent_format(accuracy = .1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1999-

Code

T_7401 |>
  filter(variable %in% c("P51C"),
         line %in% c(100, 101, 6)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1999-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .1),
                     labels = percent_format(accuracy = .1)) +
  
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Revenus de la propriété

All

Code

T_7401 |>
  filter(variable %in% c("D4", "D42", "D44"),
         line %in% c(30, 32, 35)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks ="5 years",
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1995-

Code

T_7401 |>
  filter(variable %in% c("D4", "D42", "D44"),
         line %in% c(30, 32, 35)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

2017-

% du PIB

Code

T_7401 |>
  filter(variable %in% c("D4", "D42", "D44"),
         line %in% c(30, 32, 35)) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("2017-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Base 100

Code

T_7401 |>
  filter(variable %in% c("D4", "D42")) |>
  year_to_date2() |>
  filter(date >= as.Date("2017-01-01")) |>
  group_by(Variable, line) |>
  arrange(date) |>
  mutate(value = 100*value/value[1]) |>
  ggplot() + geom_line(aes(x = date, y = value, color = paste0(Variable, " - Ligne ", line))) +
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 50)) +

  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank())

D72/D71 - primes et indemnités d’assurance dommage

% du RDB

Code

T_7401 |>
  filter(variable %in% c("D72", "D71")) |>
  left_join(rdb2, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / rdb, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du RDB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                     labels = percent_format(accuracy = .1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

% du RDB

Code

T_7401 |>
  filter(variable %in% c("D72", "D71")) |>
  left_join(rdb2, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / rdb, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du RDB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                     labels = percent_format(accuracy = .1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

% du PIB

Code

T_7401 |>
  filter(variable %in% c("D72", "D71")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                     labels = percent_format(accuracy = .1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

Salaires, Rémunération des salariés

Montant

All

Linear

Code

T_7401 |>
  filter(line %in% c(18, 26, 42)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 100),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Log

Code

T_7401 |>
  filter(line %in% c(18, 26, 42)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(1,2,5,8,10,20, 50, 80, 100, 200, 500, 1000, 1200, 2000, 3000, 5000, 10000),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

1995-

Linear

Code

T_7401 |>
  filter(line %in% c(18, 26, 42)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 100),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Log

Code

T_7401 |>
  filter(line %in% c(18, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1500, 100),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

2017-

Linear

Code

T_7401 |>
  filter(line %in% c(18, 26, 42)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("2017-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 100),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Log

Code

T_7401 |>
  filter(line %in% c(18, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("2017-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Milliards d'€") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(0, 1500, 100),
                     labels = dollar_format(accuracy = 1, pre = "", su ="Mds€")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

% du PIB

All

Code

T_7401 |>
  filter(variable %in% c("D1", "D11"),
         line %in% c(25, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1995-

Code

T_7401 |>
  filter(variable %in% c("D1", "D11"),
         line %in% c(25, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.7),
        legend.title = element_blank())

% du RDB

All

Code

T_7401 |>
  filter(variable %in% c("D1", "D11"),
         line %in% c(25, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(rdb2, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / rdb, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du RDB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

1995-

Code

T_7401 |>
  filter(variable %in% c("D1", "D11"),
         line %in% c(25, 26)) |>
  bind_rows(T_2101 |>
              filter(line == 3) |>
              mutate(Variable = "Salaires et traitements nets")) |>
  left_join(rdb2, by = "year") |>
  year_to_date2() |>
  filter(date >= as.Date("1995-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value / rdb, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.2, 0.7),
        legend.title = element_blank())

Dépense de consommation individuelle, revenu disponible brut

Dépense de consommation, RDB

Code

T_7401 |>
  filter(variable %in% c("B6G", "P31")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                     labels = percent_format(accuracy = 1)) +
  
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank())

Avec 0

Code

T_7401 |>
  filter(variable %in% c("B6G", "P31")) |>
  left_join(gdp, by = "year") |>
  year_to_date2() |>
  ggplot() + geom_line(aes(x = date, y = value / gdp, color = Variable)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1),
                     limits = c(0, 0.72)) +
  
  theme(legend.position = c(0.7, 0.3),
        legend.title = element_blank())

Related Data

Données sur le pouvoir d’achat

source	dataset	Title	Updated
insee	CNA-2014-RDB	Revenu et pouvoir d’achat des ménages - CNA-2014-RDB	2026-08-16
insee	CNT-2014-CSI	Comptes de secteurs institutionnels - CNT-2014-CSI	2026-08-16
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_7401	7.401 – Compte des ménages (S14) (En milliards d'euros) - T_7401	2026-09-02
insee	conso-eff-fonction	Consommation effective des ménages par fonction - conso-eff-fonction	2026-08-02
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	reve-conso-evo-dep-pa	Évolution de la dépense et du pouvoir d’achat des ménages - Données annuelles de 1960 à 2023 - reve-conso-evo-dep-pa	2026-08-02
insee	reve-niv-vie-individu-activite	Niveau de vie selon l'activité - Données annuelles - reve-niv-vie-individu-activite	2026-08-02
insee	reve-niv-vie-pouv-achat-trim	Évolution du revenu disponible brut et du pouvoir d’achat - Données trimestrielles - reve-niv-vie-pouv-achat-trim	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_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
insee	t_salaire_val	Salaire moyen par tête - SMPT (données CVS) - t_salaire_val	2026-09-03
oecd	HH_DASH	Household Dashboard - HH_DASH	2026-08-02