Dépenses des administrations publiques - CNA-2014-DEP-APU

Données - INSEE

Auteur

François Geerolf

Last observation: 2020 (N = 4400)

First observation: 1995 (N = 2480)

Last data update: 05 sept. 2026, 01:12

Last compile: 05 sept. 2026, 02:23

Structure

First

Code 
`CNA-2014-DEP-APU` |>
  group_by(TIME_PERIOD) |>
  summarise(Nobs = n()) |>
  arrange(desc(TIME_PERIOD)) |>
  tail(1) |>
  print_table_conditional()
TIME_PERIOD Nobs
1995 4400

Education, Santé

Tous

Code 
`CNA-2014-DEP-APU` |>
  filter(FONCTION %in% c("FON07", "FON09"),
         `SECT-INST` == "S13",
         INDICATEUR == "CNA_DEP_APU",
         TIME_PERIOD == "2019") %>%
  select_if(~ n_distinct(.) > 1) |>
  
  
  select(FONCTION, OPERATION, OBS_VALUE) |>
  spread(FONCTION, OBS_VALUE)
# # A tibble: 10 × 3
#    OPERATION  FON07  FON09
#    <chr>      <dbl>  <dbl>
#  1 D1         53496  89479
#  2 D2951       4447   1095
#  3 D3            41   3489
#  4 D4             0      6
#  5 D6M       104695   6742
#  6 D7          2323   4515
#  7 D9           476    608
#  8 OTE       194017 127926
#  9 P2         22702  12613
# 10 P5K2        5837   9378

OTE

Code 
`CNA-2014-DEP-APU` |>
  filter(FONCTION %in% c("FON07", "FON09"),
         `SECT-INST` == "S13",
         INDICATEUR == "CNA_DEP_APU",
         OPERATION == "OTE") %>%
  select_if(~ n_distinct(.) > 1) |>
  year_to_date() |>
  left_join(gdp, by = "date") |>
  
  ggplot() + theme_minimal() + ylab("Consommation (% du PIB)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/(gdp), color = FONCTION)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.91)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 0.5),
                     labels = scales::percent_format(accuracy = 0.1))

D1

Code 
`CNA-2014-DEP-APU` |>
  filter(FONCTION %in% c("FON07", "FON09"),
         `SECT-INST` == "S13",
         INDICATEUR == "CNA_DEP_APU",
         OPERATION == "D1") %>%
  select_if(~ n_distinct(.) > 1) |>
  year_to_date() |>
  left_join(gdp, by = "date") |>
  
  ggplot() + theme_minimal() + ylab("Consommation (% du PIB)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/(gdp), color = FONCTION)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.91)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 0.5),
                     labels = scales::percent_format(accuracy = 0.1))

P2 - Consommation intermédiaire (emploi intermédiaire)

Code 
`CNA-2014-DEP-APU` |>
  filter(FONCTION %in% c("FON07", "FON09"),
         `SECT-INST` == "S13",
         INDICATEUR == "CNA_DEP_APU",
         OPERATION == "P2") %>%
  select_if(~ n_distinct(.) > 1) |>
  year_to_date() |>
  left_join(gdp, by = "date") |>
  
  ggplot() + theme_minimal() + ylab("Consommation (% du PIB)") + xlab("") +
  geom_line(aes(x = date, y = OBS_VALUE/(gdp), color = FONCTION)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.91)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 0.1),
                     labels = scales::percent_format(accuracy = 0.1))