Balance Sheet Items - Published series
Data - ECB
Info
Data on monetary policy
| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| ecb | BSI_PUB | Balance Sheet Items - Published series | 2025-11-13 | 2025-08-29 |
| bdf | FM | Marché financier, taux | 2025-08-28 | 2025-08-28 |
| bdf | MIR | Taux d'intérêt - Zone euro | 2025-08-28 | 2025-08-04 |
| bdf | MIR1 | Taux d'intérêt - France | 2025-08-28 | 2025-08-04 |
| bis | CBPOL | Policy Rates, Daily | 2025-10-11 | 2025-10-11 |
| ecb | BSI | Balance Sheet Items | 2025-11-13 | 2025-08-29 |
| ecb | FM | Financial market data | 2025-11-13 | 2025-08-29 |
| ecb | ILM | Internal Liquidity Management | 2025-11-13 | 2025-08-29 |
| ecb | ILM_PUB | Internal Liquidity Management - Published series | 2025-08-29 | 2024-09-10 |
| ecb | MIR | MFI Interest Rate Statistics | 2025-11-13 | 2025-08-29 |
| ecb | RAI | Risk Assessment Indicators | 2025-11-13 | 2025-08-29 |
| ecb | SUP | Supervisory Banking Statistics | 2025-11-13 | 2025-08-29 |
| ecb | YC | Financial market data - yield curve | 2025-11-13 | 2025-08-29 |
| ecb | YC_PUB | Financial market data - yield curve - Published series | 2025-11-13 | 2025-08-29 |
| ecb | liq_daily | Daily Liquidity | 2025-11-13 | 2025-06-06 |
| eurostat | ei_mfir_m | Interest rates - monthly data | 2025-11-14 | 2025-11-13 |
| eurostat | irt_st_m | Money market interest rates - monthly data | 2025-11-14 | 2025-11-13 |
| fred | r | Interest Rates | 2025-10-09 | 2025-10-26 |
| oecd | MEI | Main Economic Indicators | 2024-04-16 | 2025-07-24 |
| oecd | MEI_FIN | Monthly Monetary and Financial Statistics (MEI) | 2024-09-15 | 2025-07-24 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2025-11-15 |
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 | 2025-07 | 163 |
| M | 2025-06 | 163 |
| M | 2025-05 | 163 |
| M | 2025-04 | 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"),
BS_SUFFIX == "E",
FREQ == "M",
ADJUSTMENT == "Y",
COLLECTION == "E",
DATA_TYPE == "1") %>%
left_join(BS_ITEM, by = "BS_ITEM") %>%
month_to_date %>%
arrange(desc(date)) %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE/1000, color = Bs_item)) +
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"),
BS_SUFFIX == "A",
FREQ == "M") %>%
left_join(BS_ITEM, by = "BS_ITEM") %>%
month_to_date %>%
ggplot + geom_line(aes(x = date, y = OBS_VALUE/100, color = Bs_item)) +
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")