Non-consolidated financial balance sheets by economic sector (Quarterly table 0720) - SNA 2008 - QASA_TABLE720R
Data - OECD
François Geerolf
Nobs - Javascript
QASA_TABLE720R %>%
left_join(QASA_TABLE720R_var$TRANSACTION %>%
setNames(c("TRANSACTION", "Transaction")), by = "TRANSACTION") %>%
left_join(QASA_TABLE720R_var$SECTOR %>%
setNames(c("SECTOR", "Sector")), by = "SECTOR") %>%
group_by(TRANSACTION, Transaction, SECTOR, Sector, MEASURE) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}TRANSACTION
SECTOR
MEASURE
QASA_TABLE720R %>%
left_join(QASA_TABLE720R_var$MEASURE %>%
setNames(c("MEASURE", "Measure")), by = "MEASURE") %>%
group_by(MEASURE, Measure) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| MEASURE | Measure | Nobs |
|---|---|---|
| CAR | Current prices, annual levels | 1962606 |
| CXCAR | US $, current prices, current exchange rates, annual levels | 1829297 |
Germany
RS14_S15: Household Sector (Billions)
QASA_TABLE720R %>%
filter(LOCATION == "DEU",
# RS14_S15: Household Sector
SECTOR == "RS14_S15",
# CAR: Current prices, annual levels
MEASURE == "CAR") %>%
right_join(QASA_TABLE720R_var$TRANSACTION %>%
filter(grepl("pension", label) | grepl("Pension", label)) %>%
setNames(c("TRANSACTION", "Transaction")), by = "TRANSACTION") %>%
filter(obsValue != 0) %>%
arrange(-obsValue) %>%
quarter_to_enddate %>%
mutate(TRANSACTION_desc = paste0(TRANSACTION, ": ", Transaction)) %>%
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = obsValue / 1000, color = TRANSACTION_desc, linetype = TRANSACTION_desc)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
labels = date_format("%y")) +
scale_y_continuous(breaks = seq(0, 4000, 200),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1)) +
theme(legend.position = c(0.4, 0.9),
legend.title = element_blank())
RS14_S15: Household Sector (%)
QASA_TABLE720R %>%
filter(LOCATION == "DEU",
# RS14_S15: Household Sector
SECTOR == "RS14_S15",
# CAR: Current prices, annual levels
MEASURE == "CAR") %>%
right_join(QASA_TABLE720R_var$TRANSACTION %>%
filter(grepl("pension", label) | grepl("Pension", label)) %>%
setNames(c("TRANSACTION", "Transaction")), by = "TRANSACTION") %>%
filter(obsValue != 0) %>%
arrange(-obsValue) %>%
quarter_to_enddate %>%
mutate(TRANSACTION_desc = paste0(TRANSACTION, ": ", Transaction)) %>%
left_join(QNA_B1_GE_DEU, by = "date") %>%
mutate(obsValue = obsValue / B1_GE_CARSA) %>%
ggplot() + theme_minimal() + xlab("") + ylab("% of GDP") +
geom_line(aes(x = date, y = obsValue, color = TRANSACTION_desc, linetype = TRANSACTION_desc)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
labels = date_format("%y")) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
theme(legend.position = c(0.6, 0.5),
legend.title = element_blank())
RS1: Total economy
QASA_TABLE720R %>%
filter(LOCATION == "DEU",
# RS1: Total economy
SECTOR == "RS1",
# CAR: Current prices, annual levels
MEASURE == "CAR") %>%
right_join(QASA_TABLE720R_var$TRANSACTION %>%
filter(grepl("pension", label) | grepl("Pension", label)) %>%
setNames(c("TRANSACTION", "Transaction")), by = "TRANSACTION") %>%
filter(obsValue != 0) %>%
arrange(-obsValue) %>%
quarter_to_enddate %>%
mutate(TRANSACTION_desc = paste0(TRANSACTION, ": ", Transaction)) %>%
ggplot() + theme_minimal() + xlab("") + ylab("") +
geom_line(aes(x = date, y = obsValue / 1000, color = TRANSACTION_desc, linetype = TRANSACTION_desc)) +
scale_color_manual(values = viridis(5)[1:4]) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
labels = date_format("%y")) +
scale_y_continuous(breaks = seq(0, 4000, 200),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1)) +
theme(legend.position = c(0.38, 0.87),
legend.title = element_blank())
RS1: Total economy (%)
QASA_TABLE720R %>%
filter(LOCATION == "DEU",
# RS1: Total economy
SECTOR == "RS1",
# CAR: Current prices, annual levels
MEASURE == "CAR") %>%
right_join(QASA_TABLE720R_var$TRANSACTION %>%
filter(grepl("pension", label) | grepl("Pension", label)) %>%
setNames(c("TRANSACTION", "Transaction")), by = "TRANSACTION") %>%
filter(obsValue != 0) %>%
arrange(-obsValue) %>%
quarter_to_enddate %>%
mutate(TRANSACTION_desc = paste0(TRANSACTION, ": ", Transaction)) %>%
left_join(QNA_B1_GE_DEU, by = "date") %>%
mutate(obsValue = obsValue / B1_GE_CARSA) %>%
ggplot() + theme_minimal() + xlab("") + ylab("% of GDP") +
geom_line(aes(x = date, y = obsValue, color = TRANSACTION_desc, linetype = TRANSACTION_desc)) +
scale_color_manual(values = viridis(5)[1:4]) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
labels = date_format("%y")) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
theme(legend.position = c(0.6, 0.5),
legend.title = element_blank())
Pension Funds
QASA_TABLE720R %>%
filter(LOCATION == "DEU",
# RS129: Pension funds
SECTOR == "RS129",
MEASURE == "CAR",
# LBF90NC: Financial net worth
# LFASNC: Financial assets
# LFLINC: Financial liabilities
TRANSACTION %in% c("LBF90NC", "LFASNC", "LFLINC")) %>%
right_join(QASA_TABLE720R_var$TRANSACTION %>%
select(TRANSACTION = id, TRANSACTION_desc = label),
by = "TRANSACTION") %>%
filter(obsValue != 0) %>%
arrange(-obsValue) %>%
quarter_to_date %>%
mutate(obsValue = obsValue / 1000) %>%
select(date, TRANSACTION, TRANSACTION_desc, obsValue) %>%
ggplot() +
geom_line(aes(x = date, y = obsValue, color = TRANSACTION_desc, linetype = TRANSACTION_desc)) +
theme_minimal() +
scale_color_manual(values = viridis(5)[1:4]) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 1), "-01-01")),
labels = date_format("%y")) +
theme(legend.position = c(0.4, 0.9),
legend.title = element_blank()) +
xlab("") + ylab("Euros Managed") +
scale_y_continuous(breaks = seq(0, 4000, 100),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))