T_82XX - Comptes de patrimoine

Data - INSEE

Author

François Geerolf

Info

source dataset .html .RData
insee T_8201 2025-05-24 2025-02-25
insee T_82XX 2025-05-18 2025-02-25

Dernière année

Code 
T_82XX %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  head(1) %>%
  print_table_conditional()
year Nobs
2023 434

Ordre Ligne

N

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "N") %>%
  select(-name) %>%
  select(-year) %>%
  spread(`SECT-INST`, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

F

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "F") %>%
  select(-name) %>%
  select(-year) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  spread(`SECT-INST`, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

SECT-INST, name

Code 
T_82XX %>%
  group_by(`SECT-INST`, name) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
SECT-INST name Nobs
S1 8.201 – Comptes de patrimoine de l'économie nationale (S1) 2046
S11 8.202 – Comptes de patrimoine des sociétés non financières (S11) 1811
S12 8.203 – Comptes de patrimoine des sociétés financières (S12) 1863
S13 8.204 – Compte de patrimoine des administrations publiques (S13) 1913
S1311 8.205 – Compte de patrimoine de l'administration publique centrale (S1311) 1700
S13111 8.206 – Compte de patrimoine de l'État (S13111) 1567
S13112 8.207 – Compte de patrimoine des organismes divers d'administration centrale (S13112) 1459
S1313 8.208 – Compte de patrimoine des administrations publiques locales (S1313) 1464
S1314 8.209 – Compte de patrimoine des administrations de sécurité sociale (S1314) 1355
S14 8.210 – Compte de patrimoine des ménages (S14) 1660

asset

Code 
T_82XX %>%
  group_by(asset, Asset) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

sector

Code 
T_82XX %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  group_by(`SECT-INST`, `Sect-Inst`) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()
SECT-INST Sect-Inst Nobs
S1 S1 - Ensemble économie nationale 2046
S11 S11 - Sociétés non financières 1811
S12 S12 - Sociétés financières 1863
S13 S13 - Administrations publiques (APU) 1913
S1311 S1311 - Administrations publiques centrales (APUC) 1700
S13111 S13111 - État 1567
S13112 S13112 - ODAC 1459
S1313 S1313 - Administrations publiques locales (APUL) 1464
S1314 S1314 - Administrations de sécurité sociale 1355
S14 S14 - Ménages y compris entreprises individuelles 1660

S1 - Sociétés non financières

N - Table

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "N",
         `SECT-INST` == "S1") %>%
  select(-name, -year, -`SECT-INST`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

F - Table

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -year, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  spread(actif, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

F

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 100),
                labels = dollar_format(accuracy = 1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F2 - Numéraire et dépôts

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F2") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F3 - Titres de créance

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F3") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F4 - Crédits

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F4") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F5 - Actions

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F5") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F511 - Actions côtées

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F511") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F1 - Or monétaire

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S1") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F1") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 3000, 1),
                labels = dollar_format(accuracy = .01, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

S11 - Sociétés non financières

N - Table

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "N",
         `SECT-INST` == "S11") %>%
  select(-name, -year, -`SECT-INST`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

F - Table

Code 
T_82XX %>%
  filter(year == max(year),
         substr(asset, 1, 1) == "F",
         `SECT-INST` == "S11") %>%
  select(-name, -year, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  spread(actif, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

F

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S11") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 50),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F511

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S11") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F511") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 10),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

F5

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S11") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F5") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 50),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

S14 - Ménages

F6 - Assurances

Code 
T_82XX %>%
  filter(substr(asset, 1, 1) == "F",
         `SECT-INST` == "S14") %>%
  select(-name, -`SECT-INST`) %>%
  mutate(actif = case_when(grepl("actifs", Asset) ~ "actif",
                           grepl("passifs", Asset) ~ "passif",
                           T ~ NA)) %>%
  fill(actif) %>%
  filter(asset == "F6") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = actif)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 20),
                labels = dollar_format(accuracy = .1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

Actifs non financiers

années de PIB

Code 
T_82XX %>%
  filter(`SECT-INST` == "S1",
         asset %in% c("NN", "N1N", "N11N")) %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Asset)) +
  theme_minimal() + xlab("") + ylab("Années de PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 100),
                labels = dollar_format(accuracy = 1, pre = "", su = " ans")) +
  #scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

% du PIB

Code 
T_82XX %>%
  filter(`SECT-INST` == "S1",
         asset %in% c("NN", "N1N", "N11N")) %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Asset)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 100),
                labels = percent_format(accuracy = 1)) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

Terrains (N211N)

Milliards

Tous

Code 
T_82XX %>%
  filter(asset %in% c("N211N"),
         `SECT-INST` %in% c("S1", "S14", "S11", "S13")) %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  ggplot + geom_line(aes(x = date, y = value, color = `Sect-Inst`)) +
  theme_minimal() + xlab("") + ylab("Terrains (Années de PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 1000),
                labels = dollar_format(accuracy = 1, pre = "", su = " Md€")) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

2015-

Code 
T_82XX %>%
  filter(asset %in% c("N211N"),
         `SECT-INST` %in% c("S1", "S14", "S11", "S13")) %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  filter(year(date) >= 2015) %>%
  ggplot + geom_line(aes(x = date, y = value, color = `Sect-Inst`)) +
  theme_minimal() + xlab("") + ylab("Terrains (Années de PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 1000),
                labels = dollar_format(accuracy = 1, pre = "", su = " Md€")) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank()) +
  geom_label(aes(x = date, y = value, label = round(value, 1), color = `Sect-Inst`))

2019-

Code 
T_82XX %>%
  filter(asset %in% c("N211N"),
         `SECT-INST` %in% c("S1", "S14", "S11", "S13")) %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  filter(year(date) >= 2019) %>%
  ggplot + geom_line(aes(x = date, y = value, color = `Sect-Inst`)) +
  theme_minimal() + xlab("") + ylab("Terrains (Années de PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10000, 1000),
                labels = dollar_format(accuracy = 1, pre = "", su = " Md€")) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank()) +
  geom_label(aes(x = date, y = value, label = round(value, 1), color = `Sect-Inst`))

années de PIB

Code 
T_82XX %>%
  filter(asset %in% c("N211N"),
         `SECT-INST` %in% c("S1", "S14", "S11", "S13")) %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  mutate(date = as.Date(paste0(year, "-01-01"))) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = `Sect-Inst`)) +
  theme_minimal() + xlab("") + ylab("Terrains (Années de PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 900, 100),
                labels = dollar_format(accuracy = 1, pre = "", su = " ans")) +
  theme(legend.position = c(0.3, 0.83),
        legend.title = element_blank())

Info

Fin 2023

Code 
ig_b("insee", "ip2028", "fig2")

Fin 2022

20 décembre 2023

Code 
ig_b("insee", "ip1967", "table2")

Fin 2021

Code 
ig_b("insee", "ip1925", "tab2")

Fin 2020

Code 
ig_b("insee", "ip1874", "table2")

Fin 2019

Code 
ig_b("insee", "ip1832", "fig2")

Fin 2010

Code 
ig_b("insee", "ip1305", "tab1")

BDF

Code 
ig_b("bdf", "patrimoine-T1")

Figure

Code 
ig_b("bdf", "stock-patrimonial-en-annees")