Balance of payments by country - quarterly data (BPM6)
Data - Eurostat
Info
Example
- Third quarter of 2023. EU current account surplus €85.4 bn. pdf
Data on europe
source | dataset | .html | .RData |
---|---|---|---|
eurostat | bop_gdp6_q | 2024-11-01 | 2024-10-09 |
eurostat | nama_10_a10 | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_a10_e | 2024-11-01 | 2024-11-05 |
eurostat | nama_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_lp_ulc | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_a10 | 2024-11-01 | 2024-11-05 |
eurostat | namq_10_a10_e | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_lp_ulc | 2024-11-04 | 2024-11-04 |
eurostat | namq_10_pc | 2024-11-01 | 2024-10-08 |
eurostat | nasa_10_nf_tr | 2024-11-01 | 2024-10-08 |
eurostat | nasq_10_nf_tr | 2024-11-01 | 2024-10-09 |
eurostat | tipsii40 | 2024-11-01 | 2024-11-01 |
Data on macro
source | dataset | .html | .RData |
---|---|---|---|
eurostat | nama_10_a10 | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_a10_e | 2024-11-01 | 2024-11-05 |
eurostat | nama_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_lp_ulc | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_a10 | 2024-11-01 | 2024-11-05 |
eurostat | namq_10_a10_e | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_lp_ulc | 2024-11-04 | 2024-11-04 |
eurostat | namq_10_pc | 2024-11-01 | 2024-10-08 |
eurostat | nasa_10_nf_tr | 2024-11-01 | 2024-10-08 |
eurostat | nasq_10_nf_tr | 2024-11-01 | 2024-10-09 |
fred | gdp | 2024-11-01 | 2024-11-01 |
oecd | QNA | 2024-06-06 | 2024-06-30 |
oecd | SNA_TABLE1 | 2024-09-15 | 2024-06-30 |
oecd | SNA_TABLE14A | 2024-09-15 | 2024-06-30 |
oecd | SNA_TABLE2 | 2024-07-01 | 2024-04-11 |
oecd | SNA_TABLE6A | 2024-07-01 | 2024-06-30 |
wdi | NE.RSB.GNFS.ZS | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.MKTP.CD | 2024-09-18 | 2024-09-26 |
wdi | NY.GDP.MKTP.PP.CD | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.PCAP.CD | 2024-10-15 | 2024-10-15 |
wdi | NY.GDP.PCAP.KD | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.PCAP.PP.CD | 2024-10-15 | 2024-10-15 |
wdi | NY.GDP.PCAP.PP.KD | 2024-09-18 | 2024-09-18 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-05 |
Last
Code
%>%
bop_c6_q group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2024Q2 | 659983 |
currency
Code
%>%
bop_c6_q left_join(currency, by = "currency") %>%
group_by(currency, Currency) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
currency | Currency | Nobs |
---|---|---|
MIO_EUR | Million euro | 39516535 |
MIO_NAC | Million units of national currency | 39024499 |
bop_item
Code
%>%
bop_c6_q left_join(bop_item, by = "bop_item") %>%
group_by(bop_item, Bop_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
sector10
Code
%>%
bop_c6_q left_join(sector10, by = "sector10") %>%
group_by(sector10, Sector10) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
sector10 | Sector10 | Nobs |
---|---|---|
S1 | Total economy | 34965306 |
S13 | General Government | 8191458 |
S1P | Other sectors than MFIs and general government | 5231461 |
S123 | Money market funds | 4551875 |
S121 | Central Bank | 4532541 |
S122 | Deposit-taking corporations except the central bank | 4399867 |
S12T | Monetary Financial Institutions (MFI) other than central bank | 4329913 |
S12M | Financial corporations other than MFIs | 4134071 |
S1V | Non-financial corporations, households and non-profit institutions serving households | 4123916 |
S1W | Other sectors than General Government | 3855340 |
S1Z | Sectors other than deposit-taking corporations and general government | 87588 |
S12R | Other financial corporations | 71770 |
S1X | Monetary authorities | 65928 |
sectpart
Code
%>%
bop_c6_q left_join(sectpart, by = "sectpart") %>%
group_by(sectpart, Sectpart) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
sectpart | Sectpart | Nobs |
---|---|---|
S1 | Total economy | 75471795 |
S12M | Financial corporations other than MFIs | 422660 |
S123 | Money market funds | 413042 |
S12T | Monetary Financial Institutions (MFI) other than central bank | 358214 |
S1P | Other sectors than MFIs and general government | 355728 |
S121 | Central Bank | 343054 |
S122 | Deposit-taking corporations except the central bank | 338828 |
S13 | General Government | 327852 |
S1V | Non-financial corporations, households and non-profit institutions serving households | 321954 |
S1N | Not sectorised | 176383 |
S12K | Monetary financial institutions (MFI) | 11288 |
S1Z | Sectors other than deposit-taking corporations and general government | 236 |
stk_flow
Code
%>%
bop_c6_q left_join(stk_flow, by = "stk_flow") %>%
group_by(stk_flow, Stk_flow) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
stk_flow | Stk_flow | Nobs |
---|---|---|
ASS | Assets | 17204346 |
CRE | Credit | 15844675 |
DEB | Debit | 11515599 |
NET | Net | 11496440 |
BAL | Balance | 11337662 |
LIAB | Liabilities | 11133328 |
NI | Net FDI inward | 2254 |
NO | Net FDI outward | 2254 |
II | Net income on inward FDI | 2238 |
IO | Net income on outward FDI | 2238 |
partner
Code
%>%
bop_c6_q left_join(partner, by = "partner") %>%
group_by(partner, Partner) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional
geo
Code
%>%
bop_c6_q left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
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
%>%
bop_c6_q group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()
France
Goods and Services
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EA20", "EXT_EA20", "WRL_REST"),
partner %in% c("GS")) %>%
bop_item left_join(partner, by = "partner") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Partner)) +
ggplot
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("") +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
WRL_REST
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("WRL_REST"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("") +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 2),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
EA19
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EA19"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
EXT_EA19
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EXT_EA19"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
Germany
Goods and Services
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST"),
partner %in% c("GS")) %>%
bop_item left_join(partner, by = "partner") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Partner)) +
ggplot
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("") +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
WRL_REST
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("WRL_REST"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
xlab("") + ylab("") +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 2),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
EA19
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EA19"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
EXT_EA19
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "MIO_EUR",
currency %in% c("EXT_EA19"),
partner %in% c("CA", "GS", "G")) %>%
bop_item left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = values / B1GQ) %>%
select(-B1GQ) %>%
+ geom_line(aes(x = date, y = values, color = Bop_item)) +
ggplot
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.8),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-30, 30, 1),
labels = percent_format(a = 1)) +
geom_hline(yintercept = 0, linetype = "dashed", color = "black")
By Destination: Europe, ex-Europe
France
Balance (Flow)
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
print_table_conditional()
Net (Stock)
Code
%>%
bop_c6_q filter(geo == "FR",
== "NET",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
print_table_conditional()
Germany
Balance (Flow)
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select(bop_item, Bop_item, everything()) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
print_table_conditional()
Net (Stock)
Code
%>%
bop_c6_q filter(geo == "DE",
== "NET",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select(bop_item, Bop_item, everything()) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
print_table_conditional()
By Destination: Europe, ex-Europe
France
All
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select(bop_item, Bop_item, everything()) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
select(-sector10, -sectpart) %>%
print_table_conditional()
Services
Code
%>%
bop_c6_q filter(geo == "FR",
== "BAL",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select(bop_item, Bop_item, everything()) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(bop_item) %>%
select(-sector10, -sectpart) %>%
filter(grepl("Services", Bop_item)) %>%
mutate_at(vars(-bop_item, -Bop_item), funs(round(., 2))) %>%
print_table_conditional()
Germany
Code
%>%
bop_c6_q filter(geo == "DE",
== "BAL",
stk_flow == "2020Q4",
time == "MIO_EUR",
currency %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
partner left_join(bop_item, by = "bop_item") %>%
%>%
quarter_to_date left_join(B1GQ, by = c("geo", "date")) %>%
mutate(values = 100*values / B1GQ) %>%
select(bop_item, Bop_item, everything()) %>%
select_if(~n_distinct(.) > 1) %>%
spread(partner, values) %>%
arrange(-`WRL_REST`) %>%
print_table_conditional()