Balance sheets for non-financial assets, 2019 archive - SNA_TABLE9B_ARCHIVE

Data - OECD

Author

Layout

OECD Website. html

Nobs - Javascript

Code

SNA_TABLE9B_ARCHIVE %>%
  left_join(SNA_TABLE9B_ARCHIVE_var %>% pluck("TRANSACT"), by = c("TRANSACT" = "id")) %>%
  rename(`TRANSACT Description` = label) %>%
  group_by(TRANSACT, `TRANSACT Description`, SECTOR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Data Structure

Code

SNA_TABLE9B_ARCHIVE_var %>%
  pluck("VAR_DESC") %>%
  {if (is_html_output()) print_table(.) else .}

id	description
LOCATION	Country
TRANSACT	Transaction
SECTOR	Sector
MEASURE	Measure
TIME	Year
OBS_VALUE	Observation Value
TIME_FORMAT	Time Format
OBS_STATUS	Observation Status
UNIT	Unit
POWERCODE	Unit multiplier
REFERENCEPERIOD	Reference period

TRANSACT

Code

SNA_TABLE9B_ARCHIVE %>%
  left_join(SNA_TABLE9B_ARCHIVE_var %>% pluck("TRANSACT"), by = c("TRANSACT" = "id")) %>%
  rename(`TRANSACT Description` = label) %>%
  group_by(TRANSACT, `TRANSACT Description`) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

SECTOR

Code

SNA_TABLE9B_ARCHIVE %>%
  left_join(SNA_TABLE9B_ARCHIVE_var %>% pluck("SECTOR"), by = c("SECTOR" = "id")) %>%
  rename(`SECTOR Description` = label) %>%
  group_by(SECTOR, `SECTOR Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

SECTOR	SECTOR Description	Nobs
NS1	Total economy	14741
NS11	Non-financial corporations	10482
NS14_S15	Households and non-profit institutions serving households	10477
NS13	General government	10409
NS12	Financial corporations	10112
NS14	Households	2070
NS15	Non-profit institutions serving households	2070

Ex 1: Non-produced assets

Code

SNA_TABLE9B_ARCHIVE %>%
  filter(grepl("N2", TRANSACT) | TRANSACT == "B1_GE") %>%
  left_join(SNA_TABLE9B_ARCHIVE_var %>% pluck("TRANSACT"), by = c("TRANSACT" = "id")) %>%
  rename(`TRANSACT Description` = label) %>%
  group_by(LOCATION, TRANSACT, `TRANSACT Description`, SECTOR) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}