Government budget allocations for R and D - GBARD_NABS2007

Data - OECD

Author

François Geerolf

Info

Last observation: A: 2023 (N = 135)

First observation: A: 1981 (N = 624)

Last data update: 02 aoû 2026, 08:59. Last compile: 18 aoû 2026, 00:03

Structure

Measure

Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2015 prices and PPPs).

Presentation

This table presents data on Government budget allocations for RD (GBARD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge: RD financed from General University Funds (GUF), General advancement of knowledge: RD financed from sources other than GUF, Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives – Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes – were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GBAORD by SEO is greater than the sum of its chapters.

Data Structure

Code 
GBARD_NABS2007_var |>
  pluck("VAR_DESC") %>%
  {if (is_html_output()) print_table(.) else .}
id description
COUNTRY Country
SEO Socio economic objective
MEASURE Measure
YEAR Year
OBS_VALUE Observation Value
TIME_FORMAT Time Format
OBS_STATUS Observation Status
UNIT Unit
POWERCODE Unit multiplier
REFERENCEPERIOD Reference period

obsTime

Code 
GBARD_NABS2007 |>
  group_by(obsTime) |>
  summarise(Nobs = n()) |>
  arrange(desc(obsTime)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Table

2018

Code 
GBARD_NABS2007 |>
  filter(obsTime == 2018,
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$SEO, by = "SEO") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  select(Country, SEO, Seo, obsValue) |>
  mutate(obsValue = round(obsValue/1000, 1)) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

2011

Code 
GBARD_NABS2007 |>
  filter(obsTime == 2011,
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$SEO, by = "SEO") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  select(Country, SEO, Seo, obsValue) |>
  mutate(obsValue = round(obsValue/1000, 1)) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

2015

Code 
GBARD_NABS2007 |>
  filter(obsTime == 2015,
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$SEO, by = "SEO") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  select(Country, SEO, Seo, obsValue) |>
  mutate(obsValue = round(obsValue/1000, 1)) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

T - Total

Nobs

Code 
GBARD_NABS2007 |>
  filter(SEO == "_T") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  group_by(COUNTRY, Country, MEASURE) |>
  summarise(Nobs = n()) |>
  spread(MEASURE, Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

DF6 - 2015 Dollars - Constant prices and PPPs

Code 
GBARD_NABS2007 |>
  filter(SEO == "_T",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  mutate(obsValue = obsValue/1000,
         Location = Country) |>
  ggplot() + theme_minimal() + xlab("") + ylab("All Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue, color = Country)) + add_4flags +
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 2)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

DC6 - PPP Dollars - Current prices

Code 
GBARD_NABS2007 |>
  filter(SEO == "_T",
         MEASURE == "DC6",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("All Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 2)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

MIO_NAC - National Currency

Code 
GBARD_NABS2007 |>
  filter(SEO == "_T",
         MEASURE == "MIO_NAC",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 2)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

NABS07 - Health

Nobs

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  group_by(COUNTRY, Country, MEASURE) |>
  summarise(Nobs = n()) |>
  spread(MEASURE, Nobs) |>
  arrange(-DC6) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Nobs - DC6

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DC6") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  group_by(COUNTRY, Country, MEASURE) |>
  summarise(Nobs = n(),
            first = first(obsTime),
            last = last(obsTime)) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

DF6 - 2015 Dollars - Constant prices and PPPs

Table

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DF6",
         obsTime %in% c("1983", "2018")) |>
  left_join(SNA_TABLE3 |>
              filter(TRANSACT == "POPNC",
                     MEASURE == "PER") |>
              select(COUNTRY = LOCATION, obsTime, POPNC = obsValue),
            by = c("COUNTRY", "obsTime")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  mutate(obsValue = 1000*obsValue/POPNC) |>
  select(COUNTRY, Country, obsTime, obsValue) |>
  spread(obsTime, obsValue) |>
  na.omit() |>
  mutate(`Growth` = 100*(`2018` / `1983`-1)) |>
  arrange(Growth) |>
  mutate(Growth = paste0(round(`Growth`), "%")) %>%
  mutate_at(vars(3, 4), funs(round(., 1))) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Country)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(COU = Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F, options = list(pageLength = 40)) else .}

Germany, France, United Kingdom, Italy

Plot

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government Budget Allocations for R&D (2015$ Bn)") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  geom_image(data = . %>%
               group_by(Country) %>%
               summarise(date = last(date),
                         obsValue = last(obsValue)) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/1000, image = image), asp = 1.5) +
  theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5))

Plot - français

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Santé - Crédits Budgétaires Publics de R&D ($2015, PPA)") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  geom_image(data = . %>%
               group_by(Country) %>%
               summarise(date = last(date),
                         obsValue = last(obsValue)) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/1000, image = image), asp = 1.5) +
  theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5))

Table

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA"),
         obsTime %in% c("2011", 2018)) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  select(COUNTRY, Country, obsTime, obsValue) |>
  spread(obsTime, obsValue) |>
  mutate(`Growth (%)` = (`2018`/`2011`-1)*100) %>%
  mutate_at(vars(-COUNTRY, -Country), funs(round(., 1))) %>%
  {if (is_html_output()) print_table(.) else .}
COUNTRY Country 2011 2018 Growth (%)
DEU Germany 1508.8 1996.1 32.3
FRA France 1464.5 1225.5 -16.3
GBR United Kingdom 2944.4 3486.5 18.4
ITA Italy 1365.3 1201.4 -12.0

South Korea, Switzerland, Spain

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DF6",
         COUNTRY %in% c("KOR", "CHE", "ESP")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  geom_image(data = . %>%
               group_by(Country) %>%
               summarise(date = last(date),
                         obsValue = last(obsValue)) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/1000, image = image), asp = 1.5) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

DC6 - PPP Dollars - Current prices

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "DC6",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  geom_image(data = . %>%
               group_by(Country) %>%
               summarise(date = last(date),
                         obsValue = last(obsValue)) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/1000, image = image), asp = 1.5) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

MIO_NAC - National Currency

Germany, France, United Kingdom, Italy

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS07",
         MEASURE == "MIO_NAC",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  geom_image(data = . %>%
               group_by(Country) %>%
               summarise(date = last(date),
                         obsValue = last(obsValue)) %>%
               mutate(date = as.Date("2020-01-01"),
                      image = paste0("../../icon/flag/", str_to_lower(gsub(" ", "-", Country)), ".png")),
             aes(x = date, y = obsValue/1000, image = image), asp = 1.5) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

NABS133 - R&D related to Medical and health sciences - financed from sources other than GUF

Nobs

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS133") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  group_by(COUNTRY, Country, MEASURE) |>
  summarise(Nobs = n()) |>
  spread(MEASURE, Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

DF6 - 2015 Dollars - Constant prices and PPPs

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS133",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("R&D related to Medical and health sciences") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

DC6 - PPP Dollars - Current prices

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS133",
         MEASURE == "DC6",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("R&D related to Medical and health sciences") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

MIO_NAC - National Currency

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS133",
         MEASURE == "MIO_NAC",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

NABS123 - R&D related to Medical and health sciences - financed from GUF

Nobs

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS123") |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  group_by(COUNTRY, Country, MEASURE) |>
  summarise(Nobs = n()) |>
  spread(MEASURE, Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

DF6 - 2015 Dollars - Constant prices and PPPs

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS123",
         MEASURE == "DF6",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("R&D related to Medical and health sciences - financed from GUF") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

DC6 - PPP Dollars - Current prices

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS123",
         MEASURE == "DC6",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())

MIO_NAC - National Currency

Code 
GBARD_NABS2007 |>
  filter(SEO == "NABS123",
         MEASURE == "MIO_NAC",
         COUNTRY %in% c("DEU", "FRA", "ITA", "GBR")) |>
  left_join(GBARD_NABS2007_var$COUNTRY, by = "COUNTRY") |>
  year_to_date() |>
  ggplot() + theme_minimal() + xlab("") + ylab("Health Government budget allocations for R&D") +
  geom_line(aes(x = date, y = obsValue/1000, color = Country)) + 
  scale_color_manual(values = c("#002395", "#000000", "#009246", "#CF142B")) +
  theme(legend.position = c(0.85, 0.9),
        legend.title = element_blank()) +
  scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 5, 0.5)) +
  theme(legend.position = c(0.25, 0.9),
        legend.title = element_blank())