1.102 – Le produit intérieur brut et ses composantes en volume aux prix de l’année précédente chaînés (En milliards d’euros 2014) - t_1102

Données - INSEE

Last observation: 2019 (N = 20)

First observation: 1949 (N = 19)

Last data update: 02 août 2026, 11:05

Last compile: 04 sept. 2026, 02:12

Structure

line

• Comptes de la Nation 2021. html

• Comptes de la Nation 2020. html

• Comptes de la Nation 2019. html

2019

Désordonné

t_1102 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2019-01-01")) |>
  select(-date) %>%
  mutate(`% du PIB Réel` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ordre

t_1102 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2019-01-01")) |>
  select(-date) |>
  arrange(-value) %>%
  mutate(`% du PIB Réel` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Administration publique: Dépenses collective et individuelle

t_1102 |>
  filter(line %in% c(8, 10, 9)) |>
  left_join(gdp, by = "date") |>
  ggplot() + theme_minimal() + ylab("% du PIB Réel") + xlab("") +
  geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  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_log10(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))

GDP Components

t_1102 |>
  filter(line %in% c(8, 12, 9)) |>
  left_join(gdp, by = "date") |>
  ggplot() + theme_minimal() + ylab("Consommation (% du PIB)") + xlab("") +
  geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.7, 0.15)) +
  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_log10(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))