Gross debt (% of GDP)

Data - IMF - FM

Author

François Geerolf

Info

source dataset .html .RData

imf

GGXWDN_G01_GDP_PT

 2024-10-29 2024-05-06

Data on public debt

source dataset .html .RData

eurostat

ei_mfir_m

 2024-11-01 2024-10-08

eurostat

gov_10q_ggdebt

 2024-11-01 2024-10-08

fred

r

 2024-11-01 2024-11-01

fred

saving

 2024-11-01 2024-11-01

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
2024-11-01

Last

TIME_PERIOD FREQ Nobs
2029 A 202

FREQ

Code 
G_XWDG_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 6883

REF_AREA

Code 
G_XWDG_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 
G_XWDG_G01_GDP_PT %>%
  group_by(TIME_PERIOD) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(TIME_PERIOD)) %>%
  print_table_conditional()

Gross Government Debt (% of GDP)

Code 
G_XWDG_G01_GDP_PT %>%
  filter(TIME_PERIOD == "2018") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  select(REF_AREA, Ref_area, OBS_VALUE) %>%
  arrange(-OBS_VALUE) %>%
  na.omit %>%
  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 .}

US, Zone Euro

All

Code 
plot <- G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("US", "U2")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1999-01-01")) %>%
  left_join(REF_AREA,  by = "REF_AREA") %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", "United States")) %>%
  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("Dette publique brute, % du PIB") +
  scale_color_identity() + add_2flags +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))

save(plot, file = "G_XWDG_G01_GDP_PT_files/figure-html/US-U2-1.RData")

plot

1999-2023

Code 
plot <- G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("US", "U2")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1999-01-01"),
         date <= as.Date("2023-01-01")) %>%
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Zone euro", "États-Unis")) %>%
  #filter(date <= as.Date("2021-01-01")) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE/100, color = Ref_area)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_color_manual(values = c("#B22234", "#003399")) +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1)) +
  geom_rect(data = nber_recessions %>%
              filter(Peak > as.Date("1999-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf),
            fill = '#B22234', alpha = 0.1)  +
  geom_rect(data = cepr_recessions %>%
              filter(Peak > as.Date("1999-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = '#003399', alpha = 0.1) +
  theme(legend.position = c(0.26, 0.8),
        legend.title = element_blank()) +
  labs(caption = "Source: Fonds Monétaire International, Fiscal Monitor, NBER, CEPR")
  

save(plot, file = "G_XWDG_G01_GDP_PT_files/figure-html/US-U2-1999-2023-1.RData")

plot

France, Italy, US, Germany, Spain

All

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "ES")) %>%
  year_to_date2 %>%
  left_join(REF_AREA,  by = "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("Dette publique brute, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1990, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))

1995-

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "ES")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(REF_AREA,  by = "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("Dette publique brute, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1995, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))

1995-, années de PIB

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "ES")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(REF_AREA,  by = "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("Dette publique brute, années de PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1995, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 400, 0.2),
                     labels = dollar_format(accuracy = .1, prefix = "", suffix = " années"))

1999-

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "ES")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1999-01-01")) %>%
  left_join(REF_AREA,  by = "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("Dette publique brute, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1995, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))

2005-

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "ES")) %>%
  year_to_date2 %>%
  filter(date >= as.Date("2005-01-01")) %>%
  left_join(REF_AREA,  by = "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("Dette publique brute, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1990, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))

France, Italy, US, Germany, Japan

All

Code 
G_XWDG_G01_GDP_PT %>%
  filter(REF_AREA %in% c("FR", "IT", "US", "DE", "JP")) %>%
  year_to_date2 %>%
  left_join(REF_AREA,  by = "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) %>%
  ggplot(.) + geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  theme_minimal() + xlab("") + ylab("Dette publique brute, % du PIB") +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = seq(1990, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 400, 10),
                     labels = percent_format(accuracy = 1))