Money market interest rates - monthly data

Data - Eurostat

Author

François Geerolf

Info

source dataset Title .html .rData
eurostat irt_st_m Money market interest rates - monthly data 2025-10-10 2025-10-09

Data on interest rates

source dataset Title .html .rData
eurostat irt_st_m Money market interest rates - monthly data 2025-10-10 2025-10-09
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_D Policy Rates, Daily 2025-10-10 2025-08-20
bis CBPOL_M Policy Rates, Monthly 2025-10-10 2024-04-19
ecb FM Financial market data 2025-10-09 2025-08-29
ecb MIR MFI Interest Rate Statistics 2025-10-09 2025-08-29
eurostat ei_mfir_m Interest rates - monthly data 2025-10-10 2025-10-10
eurostat irt_lt_mcby_d EMU convergence criterion series - daily data 2025-10-10 2025-07-24
fred r Interest Rates 2025-10-09 2025-10-09
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
wdi FR.INR.DPST Deposit interest rate (%) 2022-09-27 2025-09-27
wdi FR.INR.LEND Lending interest rate (%) 2025-10-10 2025-09-27
wdi FR.INR.RINR Real interest rate (%) 2025-05-24 2025-09-27

LAST_COMPILE

LAST_COMPILE
2025-10-11

Last

Code 
irt_st_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2025M09 35

int_rt

Code 
irt_st_m %>%
  left_join(int_rt, by = "int_rt") %>%
  group_by(int_rt, Int_rt) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
int_rt Int_rt Nobs
IRT_M3 3-month rate 5341
IRT_DTD Day-to-day rate 4578
IRT_M1 1-month rate 4220
IRT_M6 6-month rate 4205
IRT_M12 12-month rate 3743

geo

Code 
irt_st_m %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

time

Code 
irt_st_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional

Interest Rates

Table

Code 
irt_st_m %>%
  filter(int_rt %in% c("IRT_M12"),
         time %in% c("2000M01", "2005M01", "2010M01", "2020M01", "2021M04")) %>%
  select_if(~ n_distinct(.) > 1) %>%
  left_join(geo, by = "geo") %>%
  spread(time, values) %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

UK, SE, DK, EA

All

Code 
irt_st_m %>%
  filter(int_rt %in% c("IRT_M12"),
         geo %in% c("UK", "SE", "DK", "EA")) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + theme_minimal()  + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("1 year") +
  scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
                labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black")

2000-

Code 
irt_st_m %>%
  filter(int_rt %in% c("IRT_M12"),
         geo %in% c("UK", "SE", "DK", "EA")) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + theme_minimal()  + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("1 year") +
  scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
                labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black")

2018-

Code 
irt_st_m %>%
  filter(int_rt %in% c("IRT_M12"),
         geo %in% c("UK", "SE", "DK", "EA")) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  filter(date >= as.Date("2018-01-01")) %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + theme_minimal()  + add_3flags +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("1 year") +
  scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
                labels = percent_format(a = 1)) + 
  geom_hline(yintercept = 0, linetype = "dashed",  color = "black")