Comptes des secteurs institutionnels

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee CNA-2014-CSI 2024-11-05 2024-11-09

Données sur la macroéconomie en France

source dataset .html .RData
bdf CFT 2024-09-30 2024-07-01
insee CNA-2014-CONSO-MEN 2024-11-09 2024-11-09
insee CNA-2014-CONSO-SI 2024-11-09 2024-11-09
insee CNA-2014-CSI 2024-11-05 2024-11-09
insee CNA-2014-FBCF-BRANCHE 2024-11-05 2024-11-09
insee CNA-2014-FBCF-SI 2024-06-07 2024-11-09
insee CNA-2014-PIB 2024-11-05 2024-11-09
insee CNA-2014-RDB 2024-11-05 2024-11-09
insee CNT-2014-CB 2024-11-05 2024-11-09
insee CNT-2014-CSI 2024-11-05 2024-11-09
insee CNT-2014-OPERATIONS 2024-11-05 2024-11-09
insee CNT-2014-PIB-EQB-RF 2024-11-05 2024-11-09
insee CONSO-MENAGES-2014 2024-11-05 2024-11-09
insee conso-mensuelle 2024-06-07 2023-07-04
insee ICA-2015-IND-CONS 2024-11-05 2024-11-09
insee t_1101 2024-11-05 2022-01-02
insee t_1102 2024-11-05 2020-10-30
insee t_1105 2024-11-05 2020-10-30

Data on macro

source dataset .html .RData
eurostat nama_10_a10 2024-11-08 2024-10-08
eurostat nama_10_a10_e 2024-11-08 2024-11-09
eurostat nama_10_gdp 2024-11-08 2024-10-08
eurostat nama_10_lp_ulc 2024-11-08 2024-10-08
eurostat namq_10_a10 2024-11-05 2024-11-09
eurostat namq_10_a10_e 2024-11-05 2024-10-08
eurostat namq_10_gdp 2024-11-05 2024-10-08
eurostat namq_10_lp_ulc 2024-11-05 2024-11-04
eurostat namq_10_pc 2024-11-05 2024-11-08
eurostat nasa_10_nf_tr 2024-11-05 2024-10-08
eurostat nasq_10_nf_tr 2024-11-05 2024-10-09
fred gdp 2024-11-09 2024-11-09
oecd QNA 2024-06-06 2024-06-30
oecd SNA_TABLE1 2024-09-15 2024-06-30
oecd SNA_TABLE14A 2024-09-15 2024-06-30
oecd SNA_TABLE2 2024-07-01 2024-04-11
oecd SNA_TABLE6A 2024-07-01 2024-06-30
wdi NE.RSB.GNFS.ZS 2024-09-18 2024-09-18
wdi NY.GDP.MKTP.CD 2024-09-18 2024-09-26
wdi NY.GDP.MKTP.PP.CD 2024-09-18 2024-09-18
wdi NY.GDP.PCAP.CD 2024-10-15 2024-10-15
wdi NY.GDP.PCAP.KD 2024-09-18 2024-09-18
wdi NY.GDP.PCAP.PP.CD 2024-10-15 2024-10-15
wdi NY.GDP.PCAP.PP.KD 2024-09-18 2024-09-18

LAST_UPDATE

Code 
`CNA-2014-CSI` %>%
  group_by(LAST_UPDATE) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(LAST_UPDATE)) %>%
  print_table_conditional()
LAST_UPDATE Nobs
2023-05-31 370
2022-11-04 82025
2022-09-30 803
2019-06-14 928
2018-12-11 920

LAST_COMPILE

LAST_COMPILE
2024-11-09

Last

Code 
`CNA-2014-CSI` %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(1) %>%
  print_table_conditional()
TIME_PERIOD Nobs
2022 5

Compte d’exploitation

Code 
i_g("bib/insee/compte-d-exploitation.png")

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

OPERATION

Code 
`CNA-2014-CSI` %>%
  left_join(OPERATION, by = "OPERATION") %>%
  group_by(OPERATION, Operation) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

COMPTE

Code 
`CNA-2014-CSI` %>%
  left_join(COMPTE, by = "COMPTE") %>%
  group_by(COMPTE, Compte) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

SECT-INST

Code 
`CNA-2014-CSI` %>%
  left_join(`SECT-INST`, by = "SECT-INST") %>%
  group_by(`SECT-INST`, `Sect-Inst`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

INDICATEUR

Code 
`CNA-2014-CSI` %>%
  left_join(INDICATEUR, by = "INDICATEUR") %>%
  group_by(INDICATEUR, Indicateur) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
INDICATEUR Indicateur Nobs
CNA_COMPTES_SI_EA Comptes de secteurs institutionnels - Emplois ou Actifs 46311
CNA_COMPTES_SI_RP Comptes de secteurs institutionnels - Ressources ou Passifs 38735

NATURE

Code 
`CNA-2014-CSI` %>%
  left_join(NATURE, by = "NATURE") %>%
  group_by(NATURE, Nature) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
NATURE Nature Nobs
SO Sans objet 80193
VALEUR_ABSOLUE Valeur absolue 3680
PROPORTION_POURCENTAGE Proportion en % 1173

UNIT_MEASURE

Code 
`CNA-2014-CSI` %>%
  group_by(UNIT_MEASURE) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
UNIT_MEASURE Nobs
EUROS_COURANTS 82617
EUROS 1256
POURCENT 1173

TITLE_FR

Code 
`CNA-2014-CSI` %>%
  group_by(IDBANK, TITLE_FR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Revenu des ménages

D1, D4

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("D1", "D4")) %>%
  select_if(~ n_distinct(.) > 1) %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = paste0(Operation, " - ", Compte))) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.6),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 5),
                     labels = percent_format(acc = 1))

D63, D631_2010 - Transferts sociaux

All

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("D63", "D631_2010")) %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Operation)) + 
  theme_minimal() +  xlab("") + ylab("") +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 1),
                     labels = percent_format(acc = 1))

1995-

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("D63", "D631_2010")) %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Operation)) + 
  theme_minimal() +  xlab("") + ylab("") +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 1),
                     labels = percent_format(acc = 1))

D5, D4

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("D5")) %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = paste0(Operation, " - ", Compte))) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.6),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 1),
                     labels = percent_format(acc = 1))

B6G, B6N, B7G, B7N

All

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("B6G", "B6N", "B7G", "B7N"),
         COMPTE == "EA") %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = paste0(Operation, " - ", Compte))) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 5),
                     labels = percent_format(acc = 1))

1995-

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S14",
         UNIT_MEASURE == "EUROS_COURANTS",
         OPERATION %in% c("B6G", "B6N", "B7G", "B7N"),
         COMPTE == "EA") %>%
  left_join(OPERATION, by = "OPERATION") %>%
  left_join(COMPTE, by = "COMPTE") %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = paste0(Operation, " - ", Compte))) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 5),
                     labels = percent_format(acc = 1))

Valeur ajoutée brute

Mds €

Code 
`CNA-2014-CSI` %>%
  left_join(`SECT-INST`,  by = "SECT-INST") %>%
  filter(`SECT-INST` %in% c("S11", "S12", "S14", "S13"),
         OPERATION %in% c("B1G")) %>%
  year_to_date() %>%
  select(date, `SECT-INST`, `Sect-Inst`, OBS_VALUE, UNIT_MEASURE) %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/1000, color = `Sect-Inst`)) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(0, 2000, 100),
                     labels = dollar_format(suffix = " Mds€", prefix = "", accuracy = 1))

% du PIB

Code 
`CNA-2014-CSI` %>%
  left_join(`SECT-INST`,  by = "SECT-INST") %>%
  filter(`SECT-INST` %in% c("S11", "S12", "S14", "S13"),
         OPERATION %in% c("B1G")) %>%
  year_to_date() %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = `Sect-Inst`)) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.75, 0.6),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 5),
                     labels = percent_format(acc = 1))

Revenus de la propriété

Mds€

Code 
`CNA-2014-CSI` %>%
  left_join(`SECT-INST`,  by = "SECT-INST") %>%
  left_join(OPERATION,  by = "OPERATION") %>%
  filter(`SECT-INST` %in% c("S0"),
         OPERATION %in% c("D41", "D42", "D43", "D44")) %>%
  year_to_date() %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/1000, color = Operation)) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(0, 2000, 100),
                     labels = dollar_format(suffix = " Mds€", prefix = "", accuracy = 1))

% du PIB

Code 
`CNA-2014-CSI` %>%
  left_join(`SECT-INST`,  by = "SECT-INST") %>%
  left_join(OPERATION,  by = "OPERATION") %>%
  filter(`SECT-INST` %in% c("S0"),
         OPERATION %in% c("D41", "D42", "D43", "D44")) %>%
  year_to_date() %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = OBS_VALUE/gdp, color = Operation)) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 2000, 5),
                     labels = percent_format(acc = 1))

S11 - Sociétés non financières

D1/B1G - Rémunération des salariés

Code 
`CNA-2014-CSI` %>%
  filter(`SECT-INST` == "S11",
         OPERATION %in% c("D1", "B1G"),
         NATURE == "SO",
         INDICATEUR == "CNA_COMPTES_SI_EA") %>%
  year_to_date() %>%
  select(date, OBS_VALUE, OPERATION) %>%
  spread(OPERATION, OBS_VALUE) %>%
  ggplot + geom_line(aes(x = date, y = D1/B1G)) + 
  theme_minimal() +  xlab("") + ylab("") +
  
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-2, 90, 1),
                     labels = scales::percent_format(accuracy = 1))