European Union and euro area balance of payments - quarterly data (BPM6)

Data - Eurostat

Author

François Geerolf

Info

source dataset Title .html .rData
eurostat bop_eu6_q European Union and euro area balance of payments - quarterly data (BPM6) 2026-02-23 2026-02-22

Data on europe

Code 
load_data("europe.RData")
europe %>%
  source_dataset_file_updates()
source dataset Title .html .rData
eurostat bop_gdp6_q Main Balance of Payments and International Investment Position items as share of GDP (BPM6) 2026-02-23 2026-02-22
eurostat nama_10_a10 Gross value added and income by A*10 industry breakdowns 2026-02-23 2026-02-22
eurostat nama_10_a10_e Employment by A*10 industry breakdowns 2026-02-23 2026-02-22
eurostat nama_10_gdp GDP and main components (output, expenditure and income) 2026-02-23 2026-02-22
eurostat nama_10_lp_ulc Labour productivity and unit labour costs 2026-02-23 2026-02-22
eurostat namq_10_a10 Gross value added and income A*10 industry breakdowns 2026-02-23 2026-02-22
eurostat namq_10_a10_e Employment A*10 industry breakdowns 2025-05-24 2026-02-22
eurostat namq_10_gdp GDP and main components (output, expenditure and income) 2025-10-27 2026-02-22
eurostat namq_10_lp_ulc Labour productivity and unit labour costs 2026-02-23 2026-02-22
eurostat namq_10_pc Main GDP aggregates per capita 2026-02-23 2026-02-22
eurostat nasa_10_nf_tr Non-financial transactions 2026-02-23 2026-02-22
eurostat nasq_10_nf_tr Non-financial transactions 2026-02-23 2026-02-22
eurostat tipsii40 Net international investment position - quarterly data, % of GDP 2026-02-23 2026-02-22

LAST_COMPILE

LAST_COMPILE
2026-02-24

Last

Code 
bop_eu6_q %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2025Q4 209

Info

  • 2023-Q2. EU current account surplus €73.0 bn. pdf / html

  • 2022-Q2. EU current account deficit €37.4 bn. pdf

currency

Code 
bop_eu6_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 890827

s_adj

Code 
bop_eu6_q %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
s_adj S_adj Nobs
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 882172
SCA Seasonally and calendar adjusted data 8655

bop_item

Code 
bop_eu6_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_eu6_q %>%
  left_join(sector10, by = "sector10") %>%
  group_by(sector10, Sector10) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
sector10 Sector10 Nobs
S1 Total economy 586978
S13 General Government 59188
S1W Other sectors than General Government 42828
S121 Central Bank 33159
S12T Monetary Financial Institutions (MFI) other than central bank 28338
S1P Other sectors than MFIs and general government 26885
S12M Financial corporations other than MFIs 24530
S1V Non-financial corporations, households and non-profit institutions serving households 23974
S122 Deposit-taking corporations except the central bank 23560
S123 Money market funds 19102
S12Q Insurance corporations and pension funds 4536
S11 Non-financial corporations 4410
S12O Other financial institutions 4410
S12K Monetary financial institutions (MFI) 3133
S124 Non-MMF investment funds 3087
S1M Households and non-profit institutions serving households 2709

sectpart

Code 
bop_eu6_q %>%
  left_join(sectpart, by = "sectpart") %>%
  group_by(sectpart, Sectpart) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
sectpart Sectpart Nobs
S1 Total economy 882551
S1P Other sectors than MFIs and general government 1215
S123 Money market funds 1162
S12M Financial corporations other than MFIs 1135
S12T Monetary Financial Institutions (MFI) other than central bank 1076
S122 Deposit-taking corporations except the central bank 830
S1N Not sectorised 727
S1V Non-financial corporations, households and non-profit institutions serving households 666
S13 General Government 609
S121 Central Bank 607
S12K Monetary financial institutions (MFI) 249

stk_flow

Code 
bop_eu6_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
CRE Credit 209005
DEB Debit 183904
BAL Balance 163100
ASS Assets 142620
LIAB Liabilities 99975
NET Net 92001
NI Net FDI inward 111
NO Net FDI outward 111

partner

Code 
bop_eu6_q %>%
  left_join(partner, by = "partner") %>%
  group_by(partner, Partner) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  mutate(Partner = ifelse(partner == "DE", "Germany", Partner)) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Partner)),
         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 .}

geo

Code 
bop_eu6_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 .}