Produit Intérieur Brut - CHELEM_2018_PIB_VA_BvD_20180702

Données - CEPII

Last observation: 2023 (N = 234)

First observation: 1960 (N = 234)

Last data update: 01 août 2026, 21:29

Last compile: 14 sept. 2026, 23:59

Nobs - Javascript

CHELEM_2018_PIB_VA_BvD_20180702 |>
  left_join(iso3c, by = "iso3c") |>
  group_by(iso3c, Iso3c) |>
  summarise(Nobs = n(),
            date1 = first(date),
            date2 = last(date)) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Produit Intérieur Brut

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(date %in% (c(1960, 1980, 2000, 2020) |> paste0("-01-01") |> as.Date())) |>
  mutate(year = year(date)) |>
  select(-date) |>
  spread(year, value) |>
  arrange(-`2020`) %>%
  mutate_at(vars(-iso3c), funs(paste0("$ ", round(./1000), " Bn"))) |>
  left_join(iso3c, by = "iso3c") |>
  group_by(iso3c, Iso3c) |>
  select(iso3c, Iso3c, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Produit Intérieur Brut (%)

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(date %in% (c(1960, 1980, 2000, 2020) |> paste0("-01-01") |> as.Date())) |>
  mutate(year = year(date)) |>
  select(-date) |>
  spread(year, value) |>
  arrange(-`2020`) %>%
  mutate_at(vars(-iso3c), funs(paste0(round(100*./.[1], 1), " %"))) |>
  left_join(iso3c, by = "iso3c") |>
  group_by(iso3c, Iso3c) |>
  select(iso3c, Iso3c, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

GDP in France, Italy, Germany

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(iso3c %in% c("FRA", "DEU", "ITA")) |>
  left_join(iso3c, by = "iso3c") |>
  ggplot() + theme_minimal() + scale_color_manual(values = viridis(4)[1:3]) +
  geom_line(aes(x = date, y = value/1000, color = Iso3c, linetype = Iso3c)) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_log10(breaks = c(seq(0, 50, 10), seq(0, 500, 100), seq(0, 7000, 500)),
                labels = dollar_format(suffix = " Bn", accuracy = 1))

GDP in USA, EU, China

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(iso3c %in% c("USA", "UE", "CHN")) |>
  ggplot() + 
  geom_line(aes(x = date, y = value/1000, color = iso3c, linetype = iso3c)) + 
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_log10(breaks = c(seq(0, 500, 100), seq(0, 5000, 1000), seq(0, 30000, 10000)),
                labels = dollar_format(suffix = " Bn", accuracy = 1))

GDP

France

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(iso3c %in% c("FRA")) |>
  select(date, GDP = value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Germany

CHELEM_2018_PIB_VA_BvD_20180702 |>
  filter(iso3c %in% c("DEU")) |>
  select(date, GDP = value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}