Gross domestic expenditure on research and development (R&D) - tipsst10
Data - Eurostat
Info
Last observation: Annual: 2024 (N = 57)
First observation: Annual: 1995 (N = 47)
Last data update: 11 aoû 2026, 21:56. Last compile: 12 aoû 2026, 04:02
Structure
geo
eurozone
Code
eurozone_countries <- c("Austria", "Belgium", "Cyprus", "Estonia", "Finland", "France",
"Germany", "Greece", "Ireland", "Italy", "Latvia", "Lithuania",
"Luxembourg", "Malta", "Netherlands", "Portugal", "Slovakia",
"Slovenia", "Spain")
non_eurozone_countries <- c("Bulgaria", "Croatia", "Czechia", "Denmark",
"Hungary", "Poland", "Romania", "Sweden")
tipsst10 |>
filter(Geo %in% eurozone_countries) |>
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
tipsst10 |>
filter(geo %in% c("DE", "ES", "FR", "IT", "NL"),
unit == "PC_GDP") |>
year_to_date() |>
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
tipsst10 |>
filter(geo %in% c("FR", "DE", "PT", "ES", "IT"),
unit == "PC_GDP") |>
year_to_date() |>
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
tipsst10 |>
filter(geo %in% c("FR", "DE", "PT"),
unit == "PC_GDP") |>
year_to_date() |>
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
tipsst10 |>
filter(geo %in% c("PL", "HU", "SI"),
unit == "PC_GDP") |>
year_to_date() |>
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
tipsst10 |>
year_to_date() |>
filter(unit == "PC_GDP") |>
mutate(eurozone = Geo %in% eurozone_countries) %>%
{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
tipsst10 |>
year_to_date() |>
filter(unit == "PC_GDP") |>
mutate(eurozone = Geo %in% eurozone_countries) %>%
{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
tipsst10 |>
year_to_date() |>
filter(unit == "PC_GDP") |>
mutate(eurozone = Geo %in% eurozone_countries) %>%
{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
tipsst10 |>
year_to_date() |>
filter(unit == "PC_GDP") |>
mutate(eurozone = Geo %in% eurozone_countries) %>%
{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, .5),
labels = scales::percent_format(accuracy = .1)) +
theme(legend.position = c(0.75, 0.2),
legend.title = element_blank())