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

Data - OECD

~/data/oecd/

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

COUNTRY

BERD_MA_TOE %>%
  left_join(BERD_MA_TOE_var$COUNTRY, by = "COUNTRY") %>%
  group_by(COUNTRY, Country) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Country)),
         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 .}

INDU_MAIN_ACT

BERD_MA_TOE %>%
  left_join(BERD_MA_TOE_var$INDU_MAIN_ACT, by = "INDU_MAIN_ACT") %>%
  group_by(INDU_MAIN_ACT, Indu_main_act) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

TYPE_COST

BERD_MA_TOE %>%
  left_join(BERD_MA_TOE_var$TYPE_COST, by = "TYPE_COST") %>%
  group_by(TYPE_COST, Type_cost) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

TYPE_COST	Type_cost	Nobs
_T	Total costs	36027
CUR_LC	Labour costs for internal R&D personnel	33894
CUR_O	Other current costs	33849
CUR	Current costs	33717
CAP	Capital costs	33483

MEASURE

BERD_MA_TOE %>%
  left_join(BERD_MA_TOE_var$MEASURE, by = "MEASURE") %>%
  group_by(MEASURE, Measure) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

MEASURE	Measure	Nobs
DC6	PPP Dollars - Current prices	56990
DF6	2015 Dollars - Constant prices and PPPs	56990
MIO_NAC	National Currency	56990

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 .}