Primary net lending/borrowing (also referred as primary balance) (% of GDP)

Data - IMF - FM

Author

François Geerolf

Info

Data on public debt

source dataset .html .RData

eurostat

ei_mfir_m

 2024-10-23 2024-10-08

eurostat

gov_10q_ggdebt

 2024-10-23 2024-10-08

fred

r

 2024-10-24 2024-10-24

fred

saving

 2024-10-24 2024-10-24

gfd

debt

 2021-08-22 2021-03-01

imf

FM

 2024-06-20 2020-03-13

imf

GGXCNL_G01_GDP_PT

 2024-10-29 2024-10-29

imf

GGXONLB_G01_GDP_PT

 2024-10-29 2024-10-29

imf

GGXWDN_G01_GDP_PT

 2024-10-29 2024-05-06

imf

HPDD

 2024-06-20 NA

oecd

QASA_TABLE7PSD

 2024-09-15 2024-04-15

wdi

GC.DOD.TOTL.GD.ZS

 2023-06-18 2024-09-18

wdi

GC.XPN.INTP.CN

 2023-06-18 2024-09-18

wdi

GC.XPN.INTP.RV.ZS

 2023-06-18 2024-09-18

wdi

GC.XPN.INTP.ZS

 2024-09-18 2024-09-18

LAST_COMPILE

LAST_COMPILE
2024-10-29

Last

TIME_PERIOD FREQ Nobs
2029 A 197

FREQ

Code 
GGXONLB_G01_GDP_PT %>%
  left_join(FREQ, by =  "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Freq Nobs
A Annual 7043

REF_AREA

Code 
GGXONLB_G01_GDP_PT %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

TIME_PERIOD

Code 
GGXONLB_G01_GDP_PT %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Table

2018

Code 
GGXONLB_G01_GDP_PT %>%
  filter(INDICATOR == "GGXONLB_G01_GDP_PT",
         TIME_PERIOD == "2018") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  select(REF_AREA, Ref_area, OBS_VALUE) %>%
  mutate_at(vars(3), funs(paste0(round(as.numeric(.), 1), " %"))) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

1995-2019 Average

Code 
GGXONLB_G01_GDP_PT %>%
  year_to_date2 %>%
  filter(date >= as.Date("1995-01-01"),
         date <= as.Date("2019-01-01")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(`Average Primary Surplus (1995-2019)` = mean(OBS_VALUE)) %>%
  arrange(-`Average Primary Surplus (1995-2019)`) %>%
  mutate_at(vars(3), funs(paste0(round(as.numeric(.), 3), " %"))) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

3 countries

Italy, France, Germany

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Australia, United Kingdom, United States

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("GB", "US", "AU")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "US", color2, color)) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Euro Area, United States, France

All

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("U2", "US", "FR")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "US", color2, color)) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2010-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("U2", "US", "FR")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(color = ifelse(REF_AREA == "US", color2, color)) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Italy, France, Germany, Spain, United States, EU

2000-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2010-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2015-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_6flags +
  scale_x_date(breaks = seq(1920, 2030, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Italy, France, Germany, Spain, United States

1990-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1995-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2000-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2010-

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

1995-2021

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date <= as.Date("2021-01-01"),
         date >= as.Date("1995-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Déficit primaire, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

France, Germany, United States, Euro Area

Primary deficits

Code 
GGXONLB_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "DE", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Primary Deficit, % of GDP") +
  scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Interest payments

France, Germany, United States, Euro Area

All

Code 
GGXONLB_G01_GDP_PT2 %>%
  filter(REF_AREA %in% c("FR", "DE", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Interest Payments, % of GDP") +
  scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2010-

Code 
GGXONLB_G01_GDP_PT2 %>%
  filter(REF_AREA %in% c("FR", "DE", "US", "U2")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  mutate(color = ifelse(REF_AREA == "U2", color2, color)) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Interest Payments, % of GDP") +
  scale_color_identity() + add_4flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

Italy, France, Germany, Spain, United States

All

Code 
GGXONLB_G01_GDP_PT2 %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Interest Payments, % du GDP") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2010-

Code 
GGXONLB_G01_GDP_PT2 %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date >= as.Date("2010-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Interest Payments, % du GDP") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2026, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")

2005-2015

Code 
GGXONLB_G01_GDP_PT2 %>%
  filter(REF_AREA %in% c("IT", "FR", "DE", "ES", "US")) %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  year_to_date2() %>%
  left_join(colors, by = c("Ref_area" = "country")) %>%
  mutate(OBS_VALUE = OBS_VALUE/100) %>%
  rename(Counterpart_area = Ref_area) %>%
  filter(date <= as.Date("2015-01-01"),
         date >= as.Date("2005-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Interest Payments, % du GDP") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black")