Balance Sheet Items - Published series
Data - ECB
Info
Data on monetary policy
source | dataset | .html | .RData |
---|---|---|---|
bdf | FM | 2024-11-18 | 2024-11-18 |
bdf | MIR | 2024-07-26 | 2024-07-01 |
bdf | MIR1 | 2024-10-16 | 2024-10-16 |
bis | CBPOL | 2024-08-09 | 2024-09-15 |
ecb | BSI | 2024-10-08 | 2024-09-16 |
ecb | BSI_PUB | 2024-10-08 | 2024-11-19 |
ecb | FM | 2024-11-18 | 2024-11-18 |
ecb | ILM | 2024-10-08 | 2024-11-11 |
ecb | ILM_PUB | 2024-10-08 | 2024-09-10 |
ecb | liq_daily | 2024-10-08 | 2024-09-11 |
ecb | MIR | 2024-06-19 | 2024-11-18 |
ecb | RAI | 2024-10-08 | 2024-10-30 |
ecb | SUP | 2024-10-08 | 2024-10-08 |
ecb | YC | 2024-10-08 | 2024-09-16 |
ecb | YC_PUB | 2024-10-08 | 2024-10-08 |
eurostat | ei_mfir_m | 2024-11-18 | 2024-11-18 |
eurostat | irt_st_m | 2024-11-18 | 2024-11-18 |
fred | r | 2024-11-18 | 2024-11-18 |
oecd | MEI | 2024-04-16 | 2024-06-30 |
oecd | MEI_FIN | 2024-09-15 | 2024-11-18 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-19 |
Last
Code
%>%
BSI_PUB group_by(TIME_PERIOD, FREQ) %>%
summarise(Nobs = n()) %>%
%>%
ungroup select(FREQ, TIME_PERIOD, Nobs) %>%
group_by(FREQ) %>%
arrange(desc(TIME_PERIOD)) %>%
filter(row_number() < 5) %>%
arrange(FREQ) %>%
print_table_conditional()
FREQ | TIME_PERIOD | Nobs |
---|---|---|
M | 2024-09 | 163 |
M | 2024-08 | 163 |
M | 2024-07 | 163 |
M | 2024-06 | 163 |
ADJUSTMENT
Code
%>%
BSI_PUB left_join(ADJUSTMENT, by = "ADJUSTMENT") %>%
group_by(ADJUSTMENT, Adjustment) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
BS_COUNT_SECTOR
Code
%>%
BSI_PUB mutate(BS_COUNT_SECTOR = paste0(BS_COUNT_SECTOR)) %>%
left_join(BS_COUNT_SECTOR, by = "BS_COUNT_SECTOR") %>%
group_by(BS_COUNT_SECTOR, Bs_count_sector) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
BS_ITEM
Code
%>%
BSI_PUB left_join(BS_ITEM, by = "BS_ITEM") %>%
group_by(BS_ITEM, Bs_item) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
BS_SUFFIX
Code
%>%
BSI_PUB left_join(BS_SUFFIX, by = "BS_SUFFIX") %>%
group_by(BS_SUFFIX, Bs_suffix) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
BS_REP_SECTOR
Code
%>%
BSI_PUB left_join(BS_REP_SECTOR, by = "BS_REP_SECTOR") %>%
group_by(BS_REP_SECTOR, Bs_rep_sector) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
COLLECTION
Code
%>%
BSI_PUB left_join(COLLECTION, by = "COLLECTION") %>%
group_by(COLLECTION, Collection) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
COUNT_AREA
Code
%>%
BSI_PUB left_join(COUNT_AREA, by = "COUNT_AREA") %>%
group_by(COUNT_AREA, Count_area) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
DATA_TYPE
Code
%>%
BSI_PUB left_join(DATA_TYPE, by = "DATA_TYPE") %>%
group_by(DATA_TYPE, Data_type) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
MATURITY_ORIG
Code
%>%
BSI_PUB left_join(MATURITY_ORIG, by = "MATURITY_ORIG") %>%
group_by(MATURITY_ORIG, Maturity_orig) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
UNIT
Code
%>%
BSI_PUB left_join(UNIT, by = "UNIT") %>%
group_by(UNIT, Unit) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
KEY
Code
%>%
BSI_PUB group_by(KEY, TITLE) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Monetary aggregates
M1, M2, M3
Niveau
Code
%>%
BSI_PUB filter(BS_ITEM %in% c("M10", "M20", "M30"),
== "E",
BS_SUFFIX == "M",
FREQ == "Y",
ADJUSTMENT == "E",
COLLECTION == "1") %>%
DATA_TYPE left_join(BS_ITEM, by = "BS_ITEM") %>%
%>%
month_to_date arrange(desc(date)) %>%
+ geom_line(aes(x = date, y = OBS_VALUE/1000, color = Bs_item)) +
ggplot xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(0, 20000, 1000)) +
geom_hline(yintercept = 0, linetype = "dashed")
Croissance
Code
%>%
BSI_PUB filter(BS_ITEM %in% c("M10", "M20", "M30"),
== "A",
BS_SUFFIX == "M") %>%
FREQ left_join(BS_ITEM, by = "BS_ITEM") %>%
%>%
month_to_date + geom_line(aes(x = date, y = OBS_VALUE/100, color = Bs_item)) +
ggplot xlab("") + ylab("") + theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-100, 90, 2),
labels = scales::percent_format(accuracy = 1)) +
geom_hline(yintercept = 0, linetype = "dashed")