Balance of payments
Data - OECD
Info
Last observation: Quarterly: 2025-Q4 (N = 3,011) · Monthly: 2025-12 (N = 56) · Annual: 2025 (N = 3,010)
Last update of .RData: 11 Apr 2026, 09:08. Last compile: 11 Apr 2026, 09:35
Structure
Financial account
EU vs. US vs. DE vs. FR
All
Code
BOP %>%
filter(MEASURE == "FA",
REF_AREA %in% c("USA", "EU27_2020", "DEU", "FRA"),
FREQ == "Q",
UNIT_MEASURE == "USD_EXC",
ACCOUNTING_ENTRY == "N") %>%
arrange(desc(obsTime)) %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
#filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Financial Account") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1949, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10000, 10000, 500)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
1999-
Code
BOP %>%
filter(MEASURE == "FA",
REF_AREA %in% c("USA", "EU27_2020", "DEU", "FRA"),
FREQ == "Q",
UNIT_MEASURE == "USD_EXC",
ACCOUNTING_ENTRY == "N") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Financial Account") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1999, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10000, 10000, 500)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
Current account (CA, % of GDP)
Greece, EU, US, France
1999-
Quarterly
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("FRA", "GRC", "USA", "EU27_2020"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = c(seq(1990, 2100, 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") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = obsValue, label = percent(obsValue), color = color))
Smoothed
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("FRA", "GRC", "USA", "EU27_2020"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
group_by(REF_AREA) %>%
arrange(date) %>%
mutate(obsValue = zoo::rollmean(obsValue, k = 4, fill = NA, align = "right")) %>%
ungroup() %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1990, 2100, 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") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = obsValue, label = percent(obsValue), color = color))
2003-
Smoothed
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("FRA", "GRC", "USA", "EU27_2020", "ITA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
group_by(REF_AREA) %>%
arrange(date) %>%
mutate(obsValue = zoo::rollmean(obsValue, k = 4, fill = NA, align = "right")) %>%
ungroup() %>%
filter(date >= as.Date("2003-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_5flags +
scale_x_date(breaks = c(seq(1990, 2100, 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")
Greece, US, France
1999-
Quarterly
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("FRA", "GRC", "USA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = c(seq(1990, 2100, 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") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = obsValue, label = percent(obsValue), color = color))
Smoothed
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("FRA", "GRC", "USA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
group_by(REF_AREA) %>%
arrange(date) %>%
mutate(obsValue = zoo::rollmean(obsValue, k = 4, fill = NA, align = "right")) %>%
ungroup() %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_3flags +
scale_x_date(breaks = c(seq(1990, 2100, 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") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = obsValue, label = percent(obsValue), color = color))
EU vs. US
All
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EA20"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EA20", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1920, 2100, 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")
2012-
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EA20"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EA20", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
rename(Location = Ref_area) %>%
filter(date >= as.Date("2013-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1920, 2100, 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")
EU27_2020 vs. US
All
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = seq(1920, 2100, 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")
1999-
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_2flags +
scale_x_date(breaks = c(seq(1990, 2100, 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") +
geom_label(data = . %>% filter(date == max(date)),
aes(x = date, y = obsValue, label = percent(obsValue), color = color))
EU vs. US vs. IT
1999-
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "ITA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_3flags +
scale_x_date(breaks = c(seq(1997, 2100, 5), seq(1999, 2100, 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")
EU vs. US vs. DE vs. FR
All
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "DEU", "FRA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
#filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1949, 2100, 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")
1999-
Quarterly
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "DEU", "FRA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1997, 2100, 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")
Smoothed
Quarterly
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "DEU", "FRA"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
group_by(REF_AREA) %>%
arrange(date) %>%
mutate(obsValue_roll4 = zoo::rollmean(obsValue, k = 4, fill = NA, align = "right")) %>%
ungroup() %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue_roll4, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1997, 2100, 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")
EU vs. US vs. DE
All
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "DEU"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
#filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_4flags +
scale_x_date(breaks = c(seq(1949, 2100, 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")
1999-
Code
BOP %>%
filter(MEASURE == "CA",
REF_AREA %in% c("USA", "EU27_2020", "DEU"),
FREQ == "Q",
UNIT_MEASURE == "PT_B1GQ") %>%
quarter_to_date() %>%
arrange(desc(date)) %>%
mutate(Ref_area = ifelse(REF_AREA == "EU27_2020", "Europe", Ref_area)) %>%
left_join(colors, by = c("Ref_area" = "country")) %>%
mutate(color = ifelse(REF_AREA == "USA", color2, color)) %>%
mutate(obsValue = obsValue/100) %>%
filter(date >= as.Date("1999-01-01")) %>%
rename(Location = Ref_area) %>%
#filter(date <= as.Date("2021-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
theme_minimal() + xlab("") + ylab("Current Account, % of GDP") +
scale_color_identity() + add_3flags +
scale_x_date(breaks = c(seq(1997, 2100, 5), seq(1999, 2100, 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")