source | dataset | .html | .RData |
---|---|---|---|
eurostat | ei_mfir_m | 2024-11-17 | 2024-11-17 |
eurostat | gov_10q_ggdebt | 2024-11-17 | 2024-11-17 |
fred | r | 2024-11-09 | 2024-11-09 |
fred | saving | 2024-11-17 | 2024-11-17 |
gfd | debt | 2021-08-22 | 2021-03-01 |
imf | FM | 2024-06-20 | 2020-03-13 |
imf | GGXCNL_G01_GDP_PT | 2024-11-17 | 2024-11-17 |
imf | GGXONLB_G01_GDP_PT | 2024-11-17 | 2024-11-17 |
imf | GGXWDN_G01_GDP_PT | 2024-10-29 | 2024-05-06 |
imf | HPDD | 2024-06-20 | NA |
oecd | QASA_TABLE7PSD | 2024-09-15 | 2024-11-16 |
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 |
Primary net lending/borrowing (also referred as primary balance) (% of GDP)
Data - IMF - FM
Info
Data on public debt
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-17 |
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",
== "2018") %>%
TIME_PERIOD 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"),
<= as.Date("2019-01-01")) %>%
date 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"),
>= as.Date("1995-01-01")) %>%
date 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"),
>= as.Date("2005-01-01")) %>%
date 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")