Non-financial accounts by sectors, SNA93 - SNA_TABLE14A_SNA93

Data - OECD

Author

François Geerolf


Nobs - Javascript

SECTOR

id label
S1 Total economy
S1_S2 Total economy and rest of the world
NFAS 14A- NFAS : NON FINANCIAL ACCOUNTS BY SECTORS
S11 Non-financial corporations
S14 Households
S14_S15 Households and non-profit institutions serving households
S21 The European Union
S2 Rest of the world
S15 Non-profit institutions serving households
S212 The institutions of the EU
S22 Non-member countries and international organisations
S12 Financial corporations
S13 General government
SN Not sectorized

Data Structure

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

MEASURE

id label
C Current prices

Ex 1: Gross capital formation (% of GDP)

Code 
SNA_TABLE14A_SNA93 %>%
  # NFK1R: Consumption of fixed capital
  filter(TRANSACT %in% c("NFP5P", "B1_GE"), 
         SECTOR == "S1") %>%
  left_join(SNA_TABLE14A_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(Country = label, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  mutate(NFP5P_B1_GE = (100*NFP5P / B1_GE)  %>% round(1) %>% paste("%")) %>%
  select(Country, obsTime, NFP5P_B1_GE) %>%
  group_by(Country) %>%
  summarise(year_first = first(obsTime),
            value_first = first(NFP5P_B1_GE),
            year_last = last(obsTime),
            value_last = last(NFP5P_B1_GE)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 2: Consumption of fixed capital (% of GDP)

Code 
SNA_TABLE14A_SNA93 %>%
  # NFK1R: Consumption of fixed capital
  filter(TRANSACT %in% c("NFK1R", "B1_GE"), 
         SECTOR == "S1") %>%
  left_join(SNA_TABLE14A_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(Country = label, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  mutate(NFK1R_B1_GE = (100*NFK1R / B1_GE)  %>% round(1) %>% paste("%")) %>%
  select(Country, obsTime, NFK1R_B1_GE) %>%
  group_by(Country) %>%
  summarise(year_first = first(obsTime),
            value_first = first(NFK1R_B1_GE),
            year_last = last(obsTime),
            value_last = last(NFK1R_B1_GE)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 3: Net capital formation (% of GDP)

Code 
SNA_TABLE14A_SNA93 %>%
  # NFK1R: Consumption of fixed capital
  filter(TRANSACT %in% c("NFK1R", "NFP5P", "B1_GE"), 
         SECTOR == "S1") %>%
  left_join(SNA_TABLE14A_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(Country = label, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  mutate(net_inv_B1_GE = (100*(NFP5P - NFK1R) / B1_GE)  %>% round(1) %>% paste("%")) %>%
  select(Country, obsTime, net_inv_B1_GE) %>%
  group_by(Country) %>%
  summarise(year_first = first(obsTime),
            value_first = first(net_inv_B1_GE),
            year_last = last(obsTime),
            value_last = last(net_inv_B1_GE)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 4: Net capital formation (% of GDP)

Code 
SNA_TABLE14A_SNA93 %>%
  # NFK1R: Consumption of fixed capital
  # NFP5P: Gross capital formation
  filter(TRANSACT %in% c("NFK1R", "NFP5P", "B1_GE"),
         # S1: Total economy
         SECTOR == "S1",
         LOCATION %in% c("FRA", "USA", "DEU", "JPN")) %>%
  left_join(SNA_TABLE14A_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(LOCATION_desc = label, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  year_to_date %>%
  mutate(net_inv_B1_GE = (NFP5P - NFK1R) / B1_GE) %>%
  ggplot() + 
  geom_line(aes(x = date, y = net_inv_B1_GE, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Net Capital Formation (% of GDP)") + xlab("")

Ex 5: Operating surplus and mixed income; gross (% of GDP)

Code 
SNA_TABLE14A_SNA93 %>%
  # NFB2G_B3GP: Operating surplus and mixed income
  filter(TRANSACT %in% c("NFB2G_B3GP", "B1_GE"),
         # S1: Total economy
         SECTOR == "S1",
         LOCATION %in% c("FRA", "USA", "DEU", "JPN")) %>%
  left_join(SNA_TABLE14A_SNA93_var$LOCATION, by = c("LOCATION" = "id")) %>%
  select(LOCATION_desc = label, TRANSACT, obsTime, obsValue) %>%
  spread(TRANSACT, obsValue) %>%
  na.omit %>%
  year_to_date %>%
  mutate(value = NFB2G_B3GP / B1_GE) %>%
  ggplot() + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Operating surplus and mixed income (% of GDP)") + xlab("")