Interest payments (% of revenue)

Data - WDI

Author

François Geerolf

Info

LAST_DOWNLOAD

source dataset Title Download Compile
wdi GC.XPN.INTP.RV.ZS Interest payments (% of revenue) NA [2026-07-25]
eurostat ei_mfir_m Interest rates - monthly data NA [2026-07-23]
eurostat gov_10q_ggdebt Quarterly government debt NA [2026-07-22]
fred r Interest Rates 2026-07-25 [2026-07-24]
fred saving Saving - saving 2026-07-25 [2026-07-24]
gfd debt Debt 2021-03-01 [2021-08-22]
imf FM Fiscal Monitor (FM) 2020-03-13 [2026-07-25]
imf GGXCNL_G01_GDP_PT Net lending/borrowing (also referred as overall balance) (% of GDP) 2025-08-05 [2026-07-25]
imf GGXONLB_G01_GDP_PT Primary net lending/borrowing (also referred as primary balance) (% of GDP) 2025-08-05 [2026-07-25]
imf GGXWDN_G01_GDP_PT Net debt (% of GDP) 2025-07-27 [2026-07-25]
imf HPDD Historical Public Debt Database NA [2026-07-25]
oecd QASA_TABLE7PSD Quarterly Sector Accounts - Public Sector Debt, consolidated, nominal value 2025-05-24 [2024-09-15]
wdi GC.DOD.TOTL.GD.ZS Central government debt, total (% of GDP) NA [2026-07-25]
wdi GC.XPN.INTP.CN Interest payments (current LCU) NA [2026-07-25]
wdi GC.XPN.INTP.ZS Interest payments (% of expense) NA [2026-07-25]

LAST_COMPILE

LAST_COMPILE
2026-07-26

Nobs - Javascript

Code 
GC.XPN.INTP.RV.ZS %>%
  left_join(iso2c, by = "iso2c") %>%
  group_by(iso2c, Iso2c) %>%
  mutate(value = round(value, 2)) %>%
  summarise(Nobs = n(),
            `Year 1` = first(year),
            `HH Consumption 1 (%)` = first(value),
            `Year 2` = last(year),
            `HH Consumption 2 (%)` = last(value)) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

France, Germany, Italy

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("IT", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.1, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))

Japan, Switzerland

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("JP", "CH")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
                     labels = scales::percent_format(accuracy = 1))

China, United States

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("CN", "US")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))

China, France, Germany

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("CN", "FR", "DE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))

Spain, United Kingdom, United States

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("US", "GB", "ES")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.4, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))

Argentina, Chile, Venezuela

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("AR", "CL", "VE")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(Iso2c = ifelse(iso2c == "VE", "Venezuela", Iso2c)) %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))

Greece, Hong Kong, Mexico

Code 
GC.XPN.INTP.RV.ZS %>%
  filter(iso2c %in% c("GR", "HK", "MX")) %>%
  left_join(iso2c, by = "iso2c") %>%
  year_to_enddate %>%
  mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
  mutate(value = value/100) %>%
  left_join(colors, by = c("Iso2c" = "country")) %>%
  ggplot(.) + theme_minimal() + geom_line() + 
  aes(x = date, y = value, color = color) +
  xlab("") + ylab("Expense (% of GDP)") +
  scale_color_identity() + add_flags +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 100, 2),
                     labels = scales::percent_format(accuracy = 1))