Non-financial accounts by economic sector - QASA_TABLE801

Data - OECD

Author

Code

load_data("oecd/QASA_TABLE801.RData")
load_data("oecd/QASA_TABLE801_var.RData")

Nobs - Javascript

Code

QASA_TABLE801 %>%
  left_join(QASA_TABLE801_var$TRANSACTION %>% rename(TRANSACTION_desc = label), by = c("TRANSACTION" = "id")) %>%
  group_by(TRANSACTION, TRANSACTION_desc, SECTOR, MEASURE, TIME_FORMAT, ADJUSTED) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

SECTOR

Code

QASA_TABLE801_var$SECTOR %>%
  {if (is_html_output()) print_table(.) else .}

id	label
S1	Total economy
S11	Non-financial corporations
S11DO	Domestically controlled non-financial corporations
S11001	Public non financial corporations
S11002	National private non financial corporations
S12	Financial corporations
S12K	Monetary financial institutions (MFI)
S12P	Other financial institutions (Financial corporations other than MFIs, insurance corporations and pension funds)
S12Q	Insurance corporations and pension funds
S13	General government
S14_S15	Households and non-profit institutions serving households
S14	Households
S15	Non-profit institutions serving households
SN	Not sectorized
S2	Rest of the world

MEASURE

Code

QASA_TABLE801_var$MEASURE %>%
  {if (is_html_output()) print_table(.) else .}

id	label
CAR	Current prices, annual levels
CQR	Current prices, quarterly levels
PER	Persons
HRS	Hours worked

Data Structure

Code

QASA_TABLE801_var$VAR_DESC %>%
  {if (is_html_output()) print_table(.) else .}

id	description
LOCATION	Country
TRANSACTION	Transaction
SECTOR	Sector
MEASURE	Measure
ADJUSTED	Adjusted
TIME	Period & Frequency
OBS_VALUE	Observation Value
TIME_FORMAT	Time Format
OBS_STATUS	Observation Status
UNIT	Unit
POWERCODE	Unit multiplier
REFERENCEPERIOD	Reference period

TRANSACTION

Code

QASA_TABLE801_var$TRANSACTION %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

ADJUSTED

Code

QASA_TABLE801_var$ADJUSTED %>%
  {if (is_html_output()) print_table(.) else .}

id	label
NSA	Not seasonally adjusted
SA	Seasonally adjusted

Ex 1: Net capital formation (% of GDP)

Code

QASA_TABLE801 %>%
  # K1PAY: Consumption of fixed capital
  # P5PAY: Gross capital formation
  # B1GPAY: Gross domestic product / Gross value added
  filter(TRANSACTION %in% c("P5PAY", "K1PAY", "B1GPAY"), 
         SECTOR == "S1",
         MEASURE == "CQR",
         TIME_FORMAT == "P1Y", 
         ADJUSTED == "NSA") %>%
  left_join(QASA_TABLE801_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(Country = label, TRANSACTION, obsTime, obsValue) %>%
  filter(substr(obsTime, 6, 6) != "Q") %>%
  arrange(Country, obsTime, TRANSACTION) %>%
  spread(TRANSACTION, obsValue) %>%
  group_by(Country, obsTime) %>%
  summarise(obsValue = (P5PAY - K1PAY) / B1GPAY) %>%
  group_by(Country) %>%
  summarise(year_first = first(obsTime),
            value_first = first(obsValue),
            year_last = last(obsTime),
            value_last = last(obsValue)) %>%
  na.omit %>%
  mutate_at(vars(value_first, value_last), 
            funs(ifelse(!is.na(.), paste0(round(100*., digits = 1), " %"), .))) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}