3.203 – Dépenses et recettes des administrations publiques (S13) (En milliards d’euros)

Data - INSEE

Info

source	dataset	Title	.html	.rData
insee	t_3203	3.203 – Dépenses et recettes des administrations publiques (S13) (En milliards d'euros)	2025-10-10	2024-04-21

LAST_COMPILE

LAST_COMPILE
2025-10-11

Dernière

t_3203 %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  head(2) %>%
  print_table_conditional()

year	Nobs
2022	50
2021	50

2022

Ordre Ligne

t_3203 %>%
  filter(year == "2022") %>%
  select(-year) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ordre décroissant

t_3203 %>%
  filter(year == "2022") %>%
  select(-year) %>%
  arrange(-value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Charges d’intérêt

Tous

t_3203 %>%
  filter(line %in% c(7)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Hors correction au titre des services d’intermédiation financière indirectement mesurés

t_3203 %>%
  filter(line %in% c(8)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  add_row(date = as.Date("2022-01-01"), value = 53.2, gdp = 2643) %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("Charge d'intérêts (% du PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Capacité ou besoin de financement

t_3203 %>%
  filter(line %in% c(50)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  add_row(date = as.Date("2022-01-01"), value = -124.9, gdp = 2643) %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("Déficit public (% du PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-50, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Impôts et cotisations sociales

Tous

t_3203 %>%
  filter(line %in% c(33)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

1979-

t_3203 %>%
  filter(line %in% c(33)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  filter(date >= as.Date("1979-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("Impôts et cotisations sociales (% 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, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Dépenses publiques

Tous sans cotisations

t_3203 %>%
  filter(line %in% c(19, 48)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Line)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Recettes

Tous sans cotisations

t_3203 %>%
  filter(line %in% c(44, 48)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Line)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Recettes

Tous sans cotisations

t_3203 %>%
  filter(line %in% c(44, 48)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Line)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Cotisations sociales imputées, rémunération des salariés

Tous

t_3203 %>%
  filter(line %in% c(20, 3)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp, color = Line)) +
  theme_minimal() + xlab("") + ylab("Cotisations sociales imputées (% du PIB)") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 0.5),
                labels = percent_format(accuracy = .1)) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

Part croissante

t_3203 %>%
  filter(line %in% c(20, 3)) %>%
  year_to_date2 %>%
  select(-Line) %>%
  spread(line, value)  %>%
  mutate(`3-20` = `3`-`20`) %>%
  transmute(date, `Cotisations imputées (% de la rémunération totale)` = `20` / (`3`),
             `Cotisations imputées (% de la rémunération hors cotisations imputées)` = `20` / (`3`-`20`)) %>%
  gather(variable, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable)) +
  theme_minimal() + xlab("") + ylab("Cotisations sociales imputées\n(% de la rémunération des salariés)") +
  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, 500, 2),
                labels = percent_format(accuracy = 1)) +
  theme(legend.position = c(0.35, 0.85),
        legend.title = element_blank()) + 
  geom_label(data = . %>% filter(date == max(date)), aes(x = date, y = value, label = percent(value, acc = 1)))

Dépenses publiques

Tous

t_3203 %>%
  filter(line %in% c(19)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 10) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

1979-

t_3203 %>%
  filter(line %in% c(19)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  filter(date >= as.Date("1979-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  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, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())

2000-

t_3203 %>%
  filter(line %in% c(19)) %>%
  year_to_date2 %>%
  left_join(gdp, by = "date") %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value / gdp)) +
  theme_minimal() + xlab("") + ylab("% du PIB") +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 500, 1),
                labels = percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(3)[1:2]) +
  theme(legend.position = c(0.75, 0.15),
        legend.title = element_blank())