Main Science and Technology Indicators

Data - OECD

Author

François Geerolf

Info

DOWNLOAD_TIME

source dataset Title Download Compile
oecd MSTI_PUB Main Science and Technology Indicators 2023-10-04 [2024-09-11]
ec INDUSTRY Industry (sector data) 2023-10-01 [2024-09-15]
eurostat ei_isin_m Industry - monthly data - index (2015 = 100) (NACE Rev. 2) - ei_isin_m 2024-09-14 [2024-09-14]
eurostat htec_trd_group4 High-tech trade by high-tech group of products in million euro (from 2007, SITC Rev. 4) 2024-09-14 [2024-09-14]
eurostat nama_10_a64 National accounts aggregates by industry (up to NACE A*64) 2024-09-14 [2024-09-14]
eurostat nama_10_a64_e National accounts employment data by industry (up to NACE A*64) 2024-09-14 [2024-09-14]
eurostat namq_10_a10_e Employment A*10 industry breakdowns 2024-09-14 [2024-09-14]
eurostat road_eqr_carmot New registrations of passenger cars by type of motor energy and engine size - road_eqr_carmot 2024-09-14 [2024-09-14]
eurostat sts_inpp_m Producer prices in industry, total - monthly data 2024-09-14 [2024-06-24]
eurostat sts_inppd_m Producer prices in industry, domestic market - monthly data 2024-09-14 [2024-09-15]
eurostat sts_inpr_m Production in industry - monthly data 2024-09-14 [2024-09-15]
eurostat sts_intvnd_m Turnover in industry, non domestic market - monthly data - sts_intvnd_m 2024-09-14 [2024-06-24]
fred industry Manufacturing, Industry 2024-09-14 [2024-09-14]
oecd ALFS_EMP Employment by activities and status (ALFS) 2024-05-12 [2024-04-16]
oecd BERD_MA_SOF Business enterprise R&D expenditure by main activity (focussed) and source of funds 2023-09-09 [2024-04-16]
oecd GBARD_NABS2007 Government budget allocations for R and D 2023-11-22 [2024-04-16]
oecd MEI_REAL Production and Sales (MEI) 2024-05-03 [2024-05-12]
oecd SNA_TABLE4 PPPs and exchange rates 2024-04-30 [2024-09-11]
wdi NV.IND.EMPL.KD Industry, value added per worker (constant 2010 USD) 2024-09-15 [2024-01-06]
wdi NV.IND.MANF.CD Manufacturing, value added (current USD) 2024-09-15 [2024-09-15]
wdi NV.IND.MANF.ZS Manufacturing, value added (% of GDP) 2024-09-15 [2024-01-06]
wdi NV.IND.TOTL.KD Industry (including construction), value added (constant 2015 USD) - NV.IND.TOTL.KD 2024-09-15 [2024-01-06]
wdi NV.IND.TOTL.ZS Industry, value added (including construction) (% of GDP) 2024-09-15 [2024-01-06]
wdi SL.IND.EMPL.ZS Employment in industry (% of total employment) 2024-09-15 [2024-01-06]
wdi TX.VAL.MRCH.CD.WT Merchandise exports (current USD) 2024-09-15 [2024-01-06]

COMPILE_TIME

COMPILE_TIME
2024-09-15

Last

obsTime Nobs
2023 57

MSTI_VAR

Code 
MSTI_PUB %>%
  left_join(MSTI_PUB_var$MSTI_VAR, by = "MSTI_VAR") %>%
  group_by(MSTI_VAR, Msti_var) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

COU

Code 
MSTI_PUB %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  group_by(COU, Cou) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

obsTime

Code 
MSTI_PUB %>%
  group_by(obsTime) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(obsTime)) %>%
  print_table_conditional()

High Technology Exports

Table

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         obsTime %in% paste0(c(1981, 1990, 2000, 2005, 2010, 2019, 2020))) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  select(MSTI_VAR, COU, Cou, obsTime, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  transmute(COU, Cou, obsTime, obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  mutate(obsValue = round(obsValue, 1)) %>%
  spread(obsTime, obsValue) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  arrange(-`2019`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

China, United States

Linear

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  select(MSTI_VAR, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1200, 100),
                     labels = dollar_format(su = " Bn")) +
  ylab("High Technology Exports = Aerospace + \nComputer, electronic and optical industry + Pharmaceutical") + xlab("")

Log

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  select(MSTI_VAR, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(1, 2, 3, 5, 8, 10, 20, 30, 50, 80, 100, 200, 300, 500, 800),
                     labels = dollar_format(su = " Bn", a = 1)) +
  ylab("High Technology Exports = Aerospace + \nComputer, electronic and optical industry + Pharmaceutical") + xlab("")

China, United States, Germany, France

Linear

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA", "DEU", "FRA")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  select(MSTI_VAR, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1200, 100),
                     labels = dollar_format(su = " Bn")) +
  ylab("High Technology Exports = Aerospace + \nComputer, electronic and optical industry + Pharmaceutical") + xlab("")

Log

All

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA", "DEU", "FRA", "EU27_2020")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  select(MSTI_VAR, COU, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  mutate(Location = ifelse(COU == "EU27_2020", "Europe", Location)) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COU == "USA", color2, color)) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(1, 2, 3, 5, 8, 10, 20, 30, 50, 80, 100, 200, 300, 500, 800),
                     labels = dollar_format(su = " Bn", a = 1)) +
  ylab("High Technology Exports = Aerospace + \nComputer, electronic and optical industry + Pharmaceutical") + xlab("")

1995-

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA", "DEU", "FRA")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(MSTI_VAR, COU, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COU %in% c("CHN", "USA"), color2, color)) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(1, 2, 3, 5, 8, 10, 20, 30, 50, 80, 100, 200, 300, 500, 800),
                     labels = dollar_format(su = " Bn", a = 1)) +
  ylab("High Tech. Exports = Aerospace + Computer, \nelectronic and optical industry + Pharmaceutical") + xlab("")

1995-

Code 
MSTI_PUB %>%
  filter(MSTI_VAR %in% c("TD_EAERO", "TD_ECOMP", "TD_EDRUG"),
         COU %in% c("CHN", "USA", "DEU", "FRA")) %>%
  left_join(MSTI_PUB_var$COU, by = "COU") %>%
  mutate(Cou = ifelse(COU == "CHN", "China", Cou)) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(MSTI_VAR, COU, Location = Cou, date, obsValue) %>%
  spread(MSTI_VAR, obsValue) %>%
  mutate(obsValue = (TD_EAERO + TD_ECOMP + TD_EDRUG)/1000) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(COU %in% c("USA"), color2, color)) %>%
  ggplot + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(1, 2, 3, 5, 8, 10, 20, 30, 50, 80, 100, 200, 300, 500, 800),
                     labels = dollar_format(su = " Mds", a = 1)) +
  ylab("Exportations de Haute Technologie = Aéronautique,  \nInformatique, Electronique, Optique, Pharmacie") + xlab("")