Investment Funds Balance Sheet Statistics

Data - ECB

Info

source dataset Title .html .rData
ecb IVF Investment Funds Balance Sheet Statistics 2026-04-15 2026-01-11

Data on monetary policy

source dataset Title .html .rData
bdf FM NA NA NA
bdf MIR NA NA NA
bdf MIR1 NA NA NA
bis CBPOL Policy Rates, Daily 2026-04-08 2026-04-15
ecb BSI NA NA NA
ecb BSI_PUB NA NA NA
ecb FM Financial market data 2026-04-15 2026-04-15
ecb ILM NA NA NA
ecb ILM_PUB NA NA NA
ecb MIR NA NA NA
ecb RAI NA NA NA
ecb SUP NA NA NA
ecb YC NA NA NA
ecb YC_PUB NA NA NA
ecb liq_daily NA NA NA
eurostat ei_mfir_m Interest rates - monthly data 2026-04-15 2026-04-15
eurostat irt_st_m Money market interest rates - monthly data 2026-04-16 2026-04-15
fred r Interest Rates 2026-04-15 2026-04-12
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
2026-04-27

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