Quarterly government debt

Data - Eurostat

Author

François Geerolf

Info

source dataset Title .html .rData
eurostat gov_10dd_edpt1 Quarterly government debt 2025-10-11 2025-10-26

LAST_DOWNLOAD

source dataset Title .html .rData
eurostat ei_mfir_m Interest rates - monthly data 2025-10-11 2025-10-26
eurostat gov_10q_ggdebt Quarterly government debt 2025-10-11 2025-10-26
fred r Interest Rates 2025-10-09 2025-10-26
fred saving Saving - saving 2025-10-09 2025-10-26
gfd debt Debt 2021-08-22 2021-03-01
imf FM Fiscal Monitor 2025-08-28 2025-09-10
imf GGXCNL_G01_GDP_PT Net lending/borrowing (also referred as overall balance) (% of GDP) 2025-08-28 2025-08-05
imf GGXONLB_G01_GDP_PT Primary net lending/borrowing (also referred as primary balance) (% of GDP) 2025-08-28 2025-08-05
imf GGXWDN_G01_GDP_PT Net debt (% of GDP) 2025-08-28 2025-07-27
imf HPDD NA NA NA
oecd QASA_TABLE7PSD Quarterly Sector Accounts - Public Sector Debt, consolidated, nominal value 2024-09-15 2025-05-24
wdi GC.DOD.TOTL.GD.ZS Central government debt, total (% of GDP) 2023-06-18 2025-09-27
wdi GC.XPN.INTP.CN Interest payments (current LCU) 2025-10-10 2025-09-27
wdi GC.XPN.INTP.RV.ZS Interest payments (% of revenue) 2023-06-18 2025-09-27
wdi GC.XPN.INTP.ZS Interest payments (% of expense) 2025-10-10 2025-09-27

LAST_COMPILE

LAST_COMPILE
2025-10-27

Last

Code 
gov_10dd_edpt1 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024 2103

unit

Code 
gov_10dd_edpt1 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
MIO_EUR Million euro 17212
MIO_NAC Million units of national currency 17212
PC_GDP Percentage of gross domestic product (GDP) 17212

sector

Code 
gov_10dd_edpt1 %>%
  left_join(sector, by = "sector") %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
sector Sector Nobs
S13 General government 34734
S1 Total economy 4077
S1311 Central government 4035
S1313 Local government 4011
S1314 Social security funds 3909
S1312 State government 870

na_item

Code 
gov_10dd_edpt1 %>%
  left_join(na_item, by = "na_item") %>%
  group_by(na_item, Na_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

geo

Code 
gov_10dd_edpt1 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  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 
gov_10dd_edpt1 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()
time Nobs
2024 2103
2023 2103
2022 2103
2021 2103
2020 1842
2019 1836
2018 1839
2017 1839
2016 1839
2015 1839
2014 1839
2013 1839
2012 1836
2011 1836
2010 1836
2009 1836
2008 1563
2007 1563
2006 1560
2005 1560
2004 1560
2003 1554
2002 1554
2001 1545
2000 1542
1999 1443
1998 1443
1997 1443
1996 1419
1995 1419

EA-19

Debt

Code 
gov_10dd_edpt1 %>%
  filter(time %in% c("2022", "2021"),
         sector == "S13",
         unit == "PC_GDP",
         na_item == "GD") %>%
  select(geo, time, values) %>%
  spread(time, values) %>%
  left_join(geo, by = "geo") %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, Geo, geo, everything()) %>%
  arrange(-`2022`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Deficit

Code 
gov_10dd_edpt1 %>%
  filter(time %in% c("2022", "2021"),
         sector == "S13",
         unit == "PC_GDP",
         na_item == "B9") %>%
  select(geo, time, values) %>%
  spread(time, values) %>%
  left_join(geo, by = "geo") %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, Geo, geo, everything()) %>%
  arrange(-`2022`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Last

Debt

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD") %>%
  group_by(geo) %>%
  filter(time == max(time)) %>%
  left_join(geo, by = "geo") %>%
  select_if(~ n_distinct(.) > 1) %>%
  arrange(values) %>%
  select(geo, Geo, everything()) %>%
  print_table_conditional()
geo Geo values
EE Estonia 23.5
BG Bulgaria 23.8
LU Luxembourg 26.3
DK Denmark 30.5
SE Sweden 34.0
LT Lithuania 38.0
IE Ireland 38.3
CZ Czechia 43.3
NL Netherlands 43.7
MT Malta 46.2
LV Latvia 46.6
RO Romania 54.8
PL Poland 55.1
HR Croatia 57.4
SK Slovakia 59.7
DE Germany 62.2
CY Cyprus 62.8
SI Slovenia 66.6
HU Hungary 73.5
AT Austria 79.9
EU27_2020 European Union - 27 countries (from 2020) 80.7
FI Finland 82.5
EA20 Euro area – 20 countries (from 2023) 87.1
EA19 Euro area - 19 countries (2015-2022) 87.2
PT Portugal 93.6
ES Spain 101.6
BE Belgium 103.9
FR France 113.2
IT Italy 134.9
EL Greece 154.2

Luxembourg, Denmark, Sweden, Netherlands, Germany, France

Debt

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD",
         geo %in% c("NL", "LU", "DK", "SE", "FR")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Public debt (years of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 260, 20),
                     labels = scales::dollar_format(acc = .1, pre = "", su = " y")) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

Deficit

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("NL", "LU", "DK", "SE", "FR")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

France, Germany, Italy, Spain, Netherlands

Debt

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD",
         geo %in% c("FR", "DE", "IT", "ES", "NL")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Public debt (years of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 260, 20),
                     labels = scales::dollar_format(acc = .1, pre = "", su = " y")) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

Deficit

All

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("FR", "DE", "IT", "ES", "NL")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

2010-

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("FR", "DE", "IT", "ES", "NL")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 1), "-01-01")),
               labels = date_format("%Y"))

Interest payments

All

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "D41PAY",
         geo %in% c("FR", "DE", "IT", "ES", "NL", "EA19")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_6flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

2005-

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "D41PAY",
         geo %in% c("FR", "DE", "IT", "ES", "NL", "EA19")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2005-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Interest payments (% of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_6flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

France, Europe

2005-

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "D41PAY",
         geo %in% c("FR", "EA19")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2005-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Interest payments (% of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_2flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, .1),
                     labels = scales::percent_format(acc = .1)) +
  scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

France, Portugal, Greece, EUrope

2005-

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "D41PAY",
         geo %in% c("FR", "EA19", "EL", "PT")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2005-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Interest payments (% of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_4flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, .5),
                     labels = scales::percent_format(acc = .1)) +
  scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

Italy, Portugal, Spain, Greece, Belgium, France

All

Debt

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD",
         geo %in% c("IT", "PT", "ES", "EL", "BE", "FR")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Public debt (years of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_6flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 260, 20),
                     labels = scales::dollar_format(acc = .1, pre = "", su = " y")) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

Deficit

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("IT", "PT", "ES", "EL", "BE", "FR")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_6flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 5), "-01-01")),
               labels = date_format("%Y"))

Debt

Years of GDP

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD",
         geo %in% c("IT", "PT", "ES", "EL", "BE", "FR", "EA19")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Public debt (years of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_7flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 260, 20),
                     labels = scales::dollar_format(acc = .1, pre = "", su = " y")) +
  scale_x_date(breaks = as.Date(paste0(seq(2015, 2100, 1), "-01-01")),
               labels = date_format("%Y"))

% of GDP…

Code 
gov_10dd_edpt1 %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "GD",
         geo %in% c("IT", "PT", "ES", "EL", "BE", "FR", "EA19")) %>%
  left_join(geo, by = "geo") %>%
  year_to_date() %>%
  mutate(values = values / 100,
         Geo = ifelse(geo == "EA19", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Public debt (% of GDP)") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_7flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 260, 20),
                     labels = scales::percent_format()) +
  scale_x_date(breaks = as.Date(paste0(seq(2015, 2100, 1), "-01-01")),
               labels = date_format("%Y"))