Balance Sheet Items - Published series

Data - ECB

Author

Info

source	dataset	.html	.RData
ecb	BSI_PUB	2024-06-19	2024-06-30

Data on monetary policy

source	dataset	.html	.RData
bdf	FM	2024-06-30	2024-06-18
bdf	MIR	2024-06-30	2024-06-30
bdf	MIR1	2024-06-30	2024-06-30
bis	CBPOL	2024-06-19	2024-06-07
ecb	BSI	2024-06-19	2024-05-21
ecb	BSI_PUB	2024-06-19	2024-06-30
ecb	FM	2024-06-19	2024-06-30
ecb	ILM	2024-06-19	2024-06-30
ecb	ILM_PUB	2024-06-19	2024-01-25
ecb	liq_daily	2024-06-19	2024-05-21
ecb	MIR	2024-06-19	2024-06-30
ecb	RAI	2024-06-07	2024-06-30
ecb	SUP	2024-06-19	2024-06-30
ecb	YC	2024-06-20	2024-05-21
ecb	YC_PUB	2024-06-20	2024-06-30
eurostat	ei_mfir_m	2024-06-23	2024-06-08
eurostat	irt_st_m	2024-06-23	2024-06-30
fred	r	2024-06-30	2024-06-30
oecd	MEI	2024-04-16	2024-06-30
oecd	MEI_FIN	2024-06-20	2024-05-21

LAST_COMPILE

LAST_COMPILE
2024-07-01

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	2024-05	163
M	2024-04	163
M	2024-03	163
M	2024-02	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")