Balance of payments by country - quarterly data (BPM6)

Data - Eurostat

Author

François Geerolf

Info

source dataset .html .RData
eurostat bop_c6_q 2025-01-31 2025-05-18

Example

  • Third quarter of 2023. EU current account surplus €85.4 bn. pdf

Data on europe

source dataset .html .RData
eurostat bop_gdp6_q 2025-02-01 2025-05-18
eurostat nama_10_a10 2025-02-01 2025-05-18
eurostat nama_10_a10_e 2025-02-01 2025-05-18
eurostat nama_10_gdp 2025-02-01 2025-05-18
eurostat nama_10_lp_ulc 2025-02-01 2025-05-18
eurostat namq_10_a10 2025-03-04 2025-05-18
eurostat namq_10_a10_e 2025-03-13 2025-05-18
eurostat namq_10_gdp 2025-02-04 2025-05-18
eurostat namq_10_lp_ulc 2025-02-01 2025-05-18
eurostat namq_10_pc 2025-02-01 2025-05-18
eurostat nasa_10_nf_tr 2025-04-23 2025-05-18
eurostat nasq_10_nf_tr 2025-02-12 2025-05-18
eurostat tipsii40 2025-01-26 2025-05-18

Data on macro

source dataset .html .RData
eurostat nama_10_a10 2025-02-01 2025-05-18
eurostat nama_10_a10_e 2025-02-01 2025-05-18
eurostat nama_10_gdp 2025-02-01 2025-05-18
eurostat nama_10_lp_ulc 2025-02-01 2025-05-18
eurostat namq_10_a10 2025-03-04 2025-05-18
eurostat namq_10_a10_e 2025-03-13 2025-05-18
eurostat namq_10_gdp 2025-02-04 2025-05-18
eurostat namq_10_lp_ulc 2025-02-01 2025-05-18
eurostat namq_10_pc 2025-02-01 2025-05-18
eurostat nasa_10_nf_tr 2025-04-23 2025-05-18
eurostat nasq_10_nf_tr 2025-02-12 2025-05-18
fred gdp 2025-05-18 2025-05-18
oecd QNA 2024-06-06 2025-03-31
oecd SNA_TABLE1 2025-03-04 2025-03-04
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 2025-03-09 2025-03-09
wdi NY.GDP.MKTP.CD 2025-03-09 2025-03-09
wdi NY.GDP.MKTP.PP.CD 2025-03-09 2025-03-09
wdi NY.GDP.PCAP.CD 2025-03-31 2025-03-31
wdi NY.GDP.PCAP.KD 2025-03-09 2025-03-09
wdi NY.GDP.PCAP.PP.CD 2025-03-31 2025-03-31
wdi NY.GDP.PCAP.PP.KD 2025-03-09 2025-03-09

LAST_COMPILE

LAST_COMPILE
2025-05-18

Last

Code 
bop_c6_q %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024Q4 678450

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 40598055
MIO_NAC Million units of national currency 40086157

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 35992191
S13 General Government 8418842
S1P Other sectors than MFIs and general government 5397627
S123 Money market funds 4650641
S121 Central Bank 4629599
S122 Deposit-taking corporations except the central bank 4503913
S12T Monetary Financial Institutions (MFI) other than central bank 4450987
S12M Financial corporations other than MFIs 4234777
S1V Non-financial corporations, households and non-profit institutions serving households 4224880
S1W Other sectors than General Government 3952381
S1Z Sectors other than deposit-taking corporations and general government 88752
S12R Other financial corporations 72774
S1X Monetary authorities 66848

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 77563625
S12M Financial corporations other than MFIs 430024
S123 Money market funds 418942
S12T Monetary Financial Institutions (MFI) other than central bank 364066
S1P Other sectors than MFIs and general government 361536
S121 Central Bank 348350
S122 Deposit-taking corporations except the central bank 344064
S13 General Government 332878
S1V Non-financial corporations, households and non-profit institutions serving households 326996
S1N Not sectorised 182035
S12K Monetary financial institutions (MFI) 11456
S1Z Sectors other than deposit-taking corporations and general government 240

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 17654376
CRE Credit 16272597
DEB Debit 11830057
NET Net 11828268
BAL Balance 11658706
LIAB Liabilities 11430568
NI Net FDI inward 2418
NO Net FDI outward 2418
II Net income on inward FDI 2402
IO Net income on outward FDI 2402

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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EA20", "EXT_EA20", "WRL_REST"),
         bop_item %in% c("GS")) %>%
  left_join(partner, by = "partner") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Partner)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("WRL_REST"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EA19"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EXT_EA19"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST"),
         bop_item %in% c("GS")) %>%
  left_join(partner, by = "partner") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Partner)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("WRL_REST"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EA19"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         currency == "MIO_EUR",
         partner %in% c("EXT_EA19"),
         bop_item %in% c("CA", "GS", "G")) %>%
  left_join(bop_item, by = "bop_item") %>%
  quarter_to_date %>%
  left_join(B1GQ, by = c("geo", "date")) %>%
  mutate(values = values / B1GQ) %>%
  select(-B1GQ) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Bop_item)) +
  
  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",
         stk_flow == "BAL",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "NET",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "BAL",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "NET",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "BAL",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "BAL",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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",
         stk_flow == "BAL",
         time == "2020Q4",
         currency == "MIO_EUR",
         partner %in% c("EA19", "EXT_EA19", "WRL_REST")) %>%
  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()