Info

source	dataset	Title	.html	.rData
ecb	IVF	Investment Funds Balance Sheet Statistics	2025-08-29	2025-08-21

Data on monetary policy

source	dataset	Title	.html	.rData
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	2025-08-28	2025-08-28
ecb	BSI	Balance Sheet Items	2025-08-29	2025-08-29
ecb	BSI_PUB	Balance Sheet Items - Published series	2025-08-29	2025-08-29
ecb	FM	Financial market data	2025-08-29	2025-08-29
ecb	ILM	Internal Liquidity Management	2025-08-29	2025-08-29
ecb	ILM_PUB	Internal Liquidity Management - Published series	2025-08-29	2024-09-10
ecb	MIR	MFI Interest Rate Statistics	2025-08-29	2025-08-29
ecb	RAI	Risk Assessment Indicators	2025-08-29	2025-08-29
ecb	SUP	Supervisory Banking Statistics	2025-08-29	2025-08-29
ecb	YC	Financial market data - yield curve	2025-08-29	2025-08-29
ecb	YC_PUB	Financial market data - yield curve - Published series	2025-08-29	2025-08-29
ecb	liq_daily	Daily Liquidity	2025-08-29	2025-06-06
eurostat	ei_mfir_m	Interest rates - monthly data	2025-10-01	2025-09-26
eurostat	irt_st_m	Money market interest rates - monthly data	2025-10-01	2025-09-26
fred	r	Interest Rates	2025-10-02	2025-10-01
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
2025-10-09

Last

Code

IVF %>%
  group_by(TIME_PERIOD, FREQ) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  head(5) %>%
  print_table_conditional()

TIME_PERIOD	FREQ	Nobs
2025-Q2	Q	80679
2025-Q1	Q	80679
2025-06	M	103915
2025-05	M	103915
2025-04	M	103915

DECIMALS

Code

IVF %>%
  group_by(DECIMALS) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

DECIMALS	Nobs
0	17828535
1	44966

BS_COUNT_SECTOR

Code

IVF %>%
  left_join(BS_COUNT_SECTOR %>%
             mutate(BS_COUNT_SECTOR = as.numeric(BS_COUNT_SECTOR)),
           by = "BS_COUNT_SECTOR") %>%
  group_by(BS_COUNT_SECTOR, Bs_count_sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

REF_AREA

Code

IVF %>%
  left_join(REF_AREA,  by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

FREQ

Code

IVF %>%
  left_join(FREQ,  by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

FREQ	Freq	Nobs
M	Monthly	13806804
Q	Quarterly	4066697