Money market interest rates - monthly data

Data - Eurostat

Author

François Geerolf

Info

source dataset .html .RData
eurostat irt_st_m 2024-11-01 2024-10-08

Data on interest rates

source dataset .html .RData
bdf FM 2024-07-26 2024-10-16
bdf MIR 2024-07-26 2024-07-01
bdf MIR1 2024-10-16 2024-10-16
bis CBPOL_D 2024-09-13 2024-05-10
bis CBPOL_M 2024-08-09 2024-04-19
ecb FM 2024-10-30 2024-11-01
ecb MIR 2024-06-19 2024-10-30
eurostat ei_mfir_m 2024-11-05 2024-10-08
eurostat irt_lt_mcby_d 2024-11-05 2024-08-28
eurostat irt_st_m 2024-11-01 2024-10-08
fred r 2024-11-01 2024-11-01
oecd MEI 2024-04-16 2024-06-30
oecd MEI_FIN 2024-09-15 2024-05-21
wdi FR.INR.RINR 2024-08-28 2024-09-18

LAST_COMPILE

LAST_COMPILE
2024-11-05

Last

Code 
irt_st_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M09 14

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 5253
IRT_DTD Day-to-day rate 4476
IRT_M1 1-month rate 4132
IRT_M6 6-month rate 4117
IRT_M12 12-month rate 3667

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")