Comptes des secteurs institutionnels
Données - INSEE
Info
Last observation: Annuelle: 2022 (N = 5)
First observation: Annuelle: 1949 (N = 797)
Number of observations: 85 046
Last data update: 14 aoû 2026, 19:49. Last compile: 15 aoû 2026, 02:59
Structure
Données sur la macroéconomie en France
| source | dataset | Title | Updated |
|---|---|---|---|
| bdf | CFT | Comptes Financiers Trimestriels | 2026-08-10 |
| insee | CNA-2014-CONSO-SI | Dépenses de consommation finale par secteur institutionnel | 2026-08-13 |
| insee | CNA-2014-CSI | Comptes des secteurs institutionnels | 2026-08-13 |
| insee | CNA-2014-FBCF-BRANCHE | Formation brute de capital fixe (FBCF) par branche | 2026-08-13 |
| insee | CNA-2014-FBCF-SI | Formation brute de capital fixe (FBCF) par secteur institutionnel | 2026-08-13 |
| insee | CNA-2014-RDB | Revenu et pouvoir d’achat des ménages | 2026-08-13 |
| insee | CNA-2020-CONSO-MEN | Consommation des ménages | 2026-08-13 |
| insee | CNA-2020-PIB | Produit intérieur brut (PIB) et ses composantes | 2026-08-13 |
| insee | CNT-2014-CB | Comptes des branches | 2026-08-13 |
| insee | CNT-2014-CSI | Comptes de secteurs institutionnels | 2026-08-13 |
| insee | CNT-2014-OPERATIONS | Opérations sur biens et services | 2026-08-13 |
| insee | CNT-2014-PIB-EQB-RF | Équilibre du produit intérieur brut | 2026-08-13 |
| insee | CONSO-MENAGES-2020 | Consommation des ménages en biens | 2026-08-13 |
| insee | ICA-2015-IND-CONS | Indices de chiffre d'affaires dans l'industrie et la construction | 2026-08-13 |
| insee | conso-mensuelle | Consommation de biens, données mensuelles | 2026-08-02 |
| insee | t_1101 | 1.101 – Le produit intérieur brut et ses composantes à prix courants (En milliards d'euros) | 2026-08-02 |
| insee | t_1102 | 1.102 – Le produit intérieur brut et ses composantes en volume aux prix de l'année précédente chaînés (En milliards d'euros 2014) | 2026-08-02 |
| insee | t_1105 | 1.105 – Produit intérieur brut - les trois approches à prix courants (En milliards d'euros) - t_1105 | 2026-08-02 |
Data on macro
| source | dataset | Title | Updated |
|---|---|---|---|
| eurostat | nama_10_a10 | Gross value added and income by A*10 industry breakdowns | 2026-08-13 |
| eurostat | nama_10_a10_e | Employment by A*10 industry breakdowns | 2026-08-13 |
| eurostat | nama_10_gdp | GDP and main components (output, expenditure and income) | 2026-08-13 |
| eurostat | nama_10_lp_ulc | Labour productivity and unit labour costs | 2026-08-13 |
| eurostat | namq_10_a10 | Gross value added and income A*10 industry breakdowns | 2026-08-13 |
| eurostat | namq_10_a10_e | Employment A*10 industry breakdowns | 2026-08-13 |
| eurostat | namq_10_gdp | GDP and main components (output, expenditure and income) | 2026-08-13 |
| eurostat | namq_10_lp_ulc | Labour productivity and unit labour costs | 2026-08-13 |
| eurostat | namq_10_pc | Main GDP aggregates per capita | 2026-08-13 |
| eurostat | nasa_10_nf_tr | Non-financial transactions | 2026-08-13 |
| eurostat | nasq_10_nf_tr | Non-financial transactions | 2026-08-13 |
| fred | gdp | Gross Domestic Product | 2026-08-13 |
| oecd | QNA | Quarterly National Accounts | 2026-08-13 |
| oecd | SNA_TABLE1 | Gross domestic product (GDP) | 2026-08-02 |
| oecd | SNA_TABLE14A | Non-financial accounts by sectors | 2026-08-02 |
| oecd | SNA_TABLE2 | Disposable income and net lending - net borrowing | 2026-08-02 |
| oecd | SNA_TABLE6A | Value added and its components by activity, ISIC rev4 | 2026-08-02 |
| wdi | NE.RSB.GNFS.ZS | External balance on goods and services (% of GDP) | 2026-08-13 |
| wdi | NY.GDP.MKTP.CD | GDP (current USD) | 2026-08-13 |
| wdi | NY.GDP.MKTP.PP.CD | GDP, PPP (current international D) | 2026-08-13 |
| wdi | NY.GDP.PCAP.CD | GDP per capita (current USD) | 2026-08-13 |
| wdi | NY.GDP.PCAP.KD | GDP per capita (constant 2015 USD) | 2026-08-13 |
| wdi | NY.GDP.PCAP.PP.CD | GDP per capita, PPP (current international D) | 2026-08-13 |
| wdi | NY.GDP.PCAP.PP.KD | GDP per capita, PPP (constant 2011 international D) | 2026-08-13 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2026-08-15 |
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
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) |>
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")) |>
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")) |>
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")) |>
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") |>
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") |>
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` |>
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` |>
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` |>
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` |>
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))