Business enterprise R&D expenditure by main activity (focussed) and type of expenditure - BERD_MA_TOE

Data - OECD

Last observation: 2020 (N = 3858)

First observation: 2000 (N = 450)

Last data update: 02 août 2026, 08:56

Last compile: 05 sept. 2026, 03:25

Structure

COUNTRY

INDU_MAIN_ACT

TYPE_COST

MEASURE

TIME_FORMAT

UNIT

POWERCODE

REFERENCEPERIOD

Data Structure

BERD_MA_TOE_var |>
  pluck("VAR_DESC") %>%
  {if (is_html_output()) print_table(.) else .}

id	description
COUNTRY	Country
INDU_MAIN_ACT	Industry main activity
TYPE_COST	Type of costs
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

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

SECTFUND - Total

2018

BERD_MA_TOE |>
  filter(obsTime == 2017,
         MEASURE == "DF6",
         TYPE_COST == "_T",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(BERD_MA_TOE_var$INDU_MAIN_ACT, by = "INDU_MAIN_ACT") |>
  left_join(BERD_MA_TOE_var$COUNTRY, by = "COUNTRY") |>
  select(Country, INDU_MAIN_ACT, Indu_main_act, obsValue) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

2011

BERD_MA_TOE |>
  filter(obsTime == 2011,
         MEASURE == "DF6",
         TYPE_COST == "_T",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(BERD_MA_TOE_var$INDU_MAIN_ACT, by = "INDU_MAIN_ACT") |>
  left_join(BERD_MA_TOE_var$COUNTRY, by = "COUNTRY") |>
  select(Country, INDU_MAIN_ACT, Indu_main_act, obsValue) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

2015

BERD_MA_TOE |>
  filter(obsTime == 2015,
         MEASURE == "DF6",
         TYPE_COST == "_T",
         COUNTRY %in% c("DEU", "FRA", "GBR", "ITA")) |>
  left_join(BERD_MA_TOE_var$INDU_MAIN_ACT, by = "INDU_MAIN_ACT") |>
  left_join(BERD_MA_TOE_var$COUNTRY, by = "COUNTRY") |>
  select(Country, INDU_MAIN_ACT, Indu_main_act, obsValue) |>
  spread(Country, obsValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}