Gross domestic product (GDP) at market prices - annual data - tipsau10

Data - Eurostat

Author

François Geerolf

Info

Last observation: 2023 (N = 87)

First observation: 1995 (N = 62)

Last data update: 02 aoû 2026, 08:01. Last compile: 18 aoû 2026, 04:30

Structure

DOWNLOAD_TIME

Code

tibble(DOWNLOAD_TIME = as.Date(file.info("~/iCloud/website/data/eurostat/tipsau10.RData")$mtime)) |>
  print_table_conditional()

DOWNLOAD_TIME
NA

geo

All

Code

tipsau10 |>
  left_join(geo, by = "geo") |>
  group_by(geo, Geo) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

eurozone

Code

geo <- geo |>
  mutate(eurozone = ifelse(Geo %in% c("Austria", "Belgium", "Cyprus", "Estonia", "Finland", "France", 
                                      "Germany", "Greece", "Ireland", "Italy", "Latvia", "Lithuania", 
                                      "Luxembourg", "Malta", "Netherlands", "Portugal", "Slovakia",
                                      "Slovenia", "Spain"), T, F),
         non_eurozone = ifelse(Geo %in% c("Bulgaria", "Croatia", "Czechia", "Denmark", 
                                          "Hungary", "Poland", "Romania", "Sweden"), T, F))
tipsau10 |>
  left_join(geo, by = "geo") |>
  filter(eurozone) |>
  group_by(geo, Geo) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Germany, Italy, Spain, Netherlands

Code

tipsau10 |>
  filter(geo %in% c("DE", "ES", "FR", "IT", "NL"),
         unit == "CLV_PCH_PRE") |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Italy, Spain, Portugal

Code

tipsau10 |>
  filter(geo %in% c("FR", "DE", "PT", "ES", "IT"),
         unit == "CLV_PCH_PRE") |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

France, Germany, Portugal

Code

tipsau10 |>
  filter(geo %in% c("FR", "DE", "PT"),
         unit == "CLV_PCH_PRE") |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Poland, Hungary, Slovenia

Code

tipsau10 |>
  filter(geo %in% c("PL", "HU", "SI"),
         unit == "CLV_PCH_PRE") |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  left_join(colors, by = c("Geo" = "country")) |>
  mutate(values = values/100) |>
  ggplot() + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
  scale_color_identity() + add_flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("GDP growth") +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
                     labels = scales::percent_format(accuracy = 1))

Mean, Standard Deviation

All

Viridis

Code

tipsau10 |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} |>
  group_by(date) |>
  filter(n() == 19) |>
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) |>
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) |>
  gather(variable, value, -date) |>
  mutate(value = value/100) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c(viridis(3)[1], viridis(3)[2], viridis(3)[2])) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

Colors

Code

tipsau10 |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} |>
  group_by(date) |>
  filter(n() == 19) |>
  summarise(`Moyenne` = mean(values),
            `Ecart Type` = sd(values)) |>
  transmute(date, `Moyenne`,
            `Moyenne + SD` = `Moyenne` + `Ecart Type`,
            `Moyenne - SD` = `Moyenne` - `Ecart Type`) |>
  gather(variable, value, -date) |>
  mutate(value = value/100) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c("#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

With France

Code

tipsau10 |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} |>
  group_by(date) |>
  filter(n() == 19) |>
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"]) |>
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`) |>
  gather(variable, value, -date) |>
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe")) |>
  ggplot() + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_flags +
  scale_color_manual(values = c("#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.2),
        legend.title = element_blank())

With Germany

Code

tipsau10 |>
  year_to_date() |>
  left_join(geo, by = "geo") |>
  filter(unit == "CLV_PCH_PRE") %>%
  {if (eurozone) filter(., eurozone) else .} |>
  group_by(date) |>
  filter(n() == 19) |>
  summarise(`Moyenne Europe` = mean(values),
            `Ecart Type` = sd(values),
            `France` = values[geo == "FR"],
            `Allemagne` = values[geo == "DE"]) |>
  transmute(date, `Moyenne Europe`,
            `Moyenne Europe + SD` = `Moyenne Europe` + `Ecart Type`,
            `Moyenne Europe - SD` = `Moyenne Europe` - `Ecart Type`,
             `France`,
             `Allemagne`) |>
  gather(variable, value, -date) |>
  mutate(values = value/100,
         Geo = ifelse(variable == "France", "France", "Europe"),
         Geo = ifelse(variable == "Allemagne", "Germany", Geo)) |>
  ggplot() + geom_line(aes(x = date, y = values, color = variable, linetype = variable)) +
  theme_minimal() + xlab("") + ylab("") + add_flags +
  scale_color_manual(values = c("#000000", "#ED2939", "#003399", "#FFCC00", "#FFCC00")) +
  scale_linetype_manual(values = c("solid", "solid", "solid", "dashed", "dashed")) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 200, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.75, 0.2),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0.06, linetype = "dotted") +
  geom_hline(yintercept = -0.04, linetype = "dotted")