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) 2025-10-10 2025-10-10

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) 2025-10-10 2025-10-10
eurostat nama_10_a10 Gross value added and income by A*10 industry breakdowns 2025-10-10 2025-10-10
eurostat nama_10_a10_e Employment by A*10 industry breakdowns 2025-10-10 2025-10-09
eurostat nama_10_gdp GDP and main components (output, expenditure and income) 2025-10-10 2025-10-09
eurostat nama_10_lp_ulc Labour productivity and unit labour costs 2025-10-10 2025-10-10
eurostat namq_10_a10 Gross value added and income A*10 industry breakdowns 2025-10-10 2025-10-09
eurostat namq_10_a10_e Employment A*10 industry breakdowns 2025-05-24 2025-10-10
eurostat namq_10_gdp GDP and main components (output, expenditure and income) 2025-10-10 2025-10-10
eurostat namq_10_lp_ulc Labour productivity and unit labour costs 2025-10-10 2025-09-26
eurostat namq_10_pc Main GDP aggregates per capita 2025-10-10 2025-10-09
eurostat nasa_10_nf_tr Non-financial transactions 2025-10-10 2025-10-10
eurostat nasq_10_nf_tr Non-financial transactions 2025-10-10 2025-09-26
eurostat tipsii40 Net international investment position - quarterly data, % of GDP 2025-10-10 2025-10-09

LAST_COMPILE

LAST_COMPILE
2025-10-11

Last

Code 
bop_eu6_q %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2025Q2 6720

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 882782

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) 874193
SCA Seasonally and calendar adjusted data 8589

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 582015
S13 General Government 58740
S1W Other sectors than General Government 42587
S121 Central Bank 32792
S12T Monetary Financial Institutions (MFI) other than central bank 27953
S1P Other sectors than MFIs and general government 26596
S12M Financial corporations other than MFIs 24255
S1V Non-financial corporations, households and non-profit institutions serving households 23682
S122 Deposit-taking corporations except the central bank 23285
S123 Money market funds 18919
S12Q Insurance corporations and pension funds 4464
S11 Non-financial corporations 4340
S12O Other financial institutions 4340
S12K Monetary financial institutions (MFI) 3110
S124 Non-MMF investment funds 3038
S1M Households and non-profit institutions serving households 2666

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 874579
S1P Other sectors than MFIs and general government 1203
S123 Money market funds 1152
S12M Financial corporations other than MFIs 1125
S12T Monetary Financial Institutions (MFI) other than central bank 1067
S122 Deposit-taking corporations except the central bank 823
S1N Not sectorised 722
S1V Non-financial corporations, households and non-profit institutions serving households 660
S121 Central Bank 602
S13 General Government 602
S12K Monetary financial institutions (MFI) 247

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 207434
DEB Debit 182586
BAL Balance 161856
ASS Assets 140938
LIAB Liabilities 98756
NET Net 90992
NI Net FDI inward 110
NO Net FDI outward 110

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 .}