Quarterly Sector Accounts - QSA

Data - ECB

Author

François Geerolf 

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Info

source dataset Title .html .rData
ecb QSA Quarterly Sector Accounts - QSA 2026-08-07 2026-08-05

Data on monetary policy

source dataset Title .html .rData
ecb SUP Supervisory Banking Statistics 2026-08-07 2026-08-07
bdf FM Marché financier, taux 2026-08-07 2026-08-04
bdf MIR Taux d'intérêt - Zone euro 2026-08-07 2026-07-28
bdf MIR1 Taux d'intérêt - France 2026-08-07 2026-07-28
bis CBPOL Policy Rates, Daily 2026-08-07 2026-07-25
ecb BSI Balance Sheet Items 2026-08-07 2026-08-07
ecb BSI_PUB Balance Sheet Items - Published series 2026-08-07 2026-08-07
ecb FM Financial market data 2026-08-07 2026-08-07
ecb ILM Internal Liquidity Management 2026-08-07 2026-08-07
ecb ILM_PUB Internal Liquidity Management - Published series 2026-08-07 2026-08-07
ecb MIR MFI Interest Rate Statistics 2026-08-07 2026-08-07
ecb RAI Risk Assessment Indicators 2026-08-07 2026-08-07
ecb YC Financial market data - yield curve 2026-08-07 2026-08-07
ecb YC_PUB Financial market data - yield curve - Published series 2026-08-07 2026-08-07
ecb liq_daily Daily Liquidity 2026-08-07 2026-08-07
eurostat ei_mfir_m Interest rates - monthly data 2026-08-07 2026-08-07
eurostat irt_st_m Money market interest rates - monthly data 2026-08-06 2026-08-07
fred r Interest Rates 2026-08-07 2026-08-07
oecd MEI Main Economic Indicators 2026-08-07 2026-08-02
oecd MEI_FIN Monthly Monetary and Financial Statistics (MEI) 2026-08-07 2026-08-02

LAST_COMPILE

LAST_COMPILE
2026-08-08

Last

Code 
QSA |>
  group_by(TIME_PERIOD) |>
  summarise(Nobs = n()) |>
  arrange(desc(TIME_PERIOD)) |>
  head(1) |>
  print_table_conditional()
TIME_PERIOD Nobs
2026-Q1 54117

Other info

  • Households and non-financial corporations in the euro area: first quarter of 2023. html

ADJUSTMENT

Code 
QSA |>
  left_join(ADJUSTMENT,  by = "ADJUSTMENT") |>
  group_by(ADJUSTMENT, Adjustment) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
ADJUSTMENT Adjustment Nobs
N Neither seasonally nor working day adjusted 4585658
Y Working day and seasonally adjusted 22519

COUNTERPART_AREA

Code 
QSA |>
  left_join(COUNTERPART_AREA,  by = "COUNTERPART_AREA") |>
  group_by(COUNTERPART_AREA, Counterpart_area) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
COUNTERPART_AREA Counterpart_area Nobs
W0 Intra-EU (changing composition) not allocated 2257112
W2 Intra-Euro area not allocated 1965800
W1 Gaza and Jericho 381697
4Y All European Community Institutions, Organs and Organisms, including ECB, ESM and EFSF 1176
B0 Emerging and developing economies 808
B6 African ACP countries 327
D6 Candidate Countries (CCs) 327
U4 Extra Euro area 303
J9 NA 216
U2 Euro area (changing composition) 202
I9 NA 108
D0 EU (changing composition) 101

COUNTERPART_SECTOR

Code 
QSA |>
  left_join(COUNTERPART_SECTOR,  by = "COUNTERPART_SECTOR") |>
  group_by(COUNTERPART_SECTOR, Counterpart_sector) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
COUNTERPART_SECTOR Counterpart_sector Nobs
S1 Total economy 2788813
S12P Other financial institutions (Financial corporations other than MFIs, insurance corporations and pension funds) 149110
S12 Financial corporations 141673
S124 Non MMF investment funds 140110
S12K Monetary financial institutions (MFI) 137835
S11 Non financial corporations 132263
S128 Insurance corporations 130496
S12Q Insurance corporations and Pension Funds 128714
S129 Pension funds 128179
S12O Other financial institutions (Financial corporations other than MFIs, insurance corporations, pension funds and non MMFs investment funds) 128049
S13 General government 125527
S1M Households and non profit institutions serving households (NPISH) 113054
S125 Other financial intermediaries, except insurance corporations and pension funds 103591
S126 Financial auxiliaries 101840
S127 Captive financial institutions and money lenders 101710
S121 Central bank 29511
S12T Monetary financial institutions other than central bank 27323
S1V Non-financial corporations, households and NPISH 379

EXPENDITURE

Code 
QSA |>
  left_join(EXPENDITURE,  by = "EXPENDITURE") |>
  group_by(EXPENDITURE, Expenditure) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
EXPENDITURE Expenditure Nobs
_Z Not applicable 4586403
_T Total 21774

FREQ

Code 
QSA |>
  left_join(FREQ,  by = "FREQ") |>
  group_by(FREQ, Freq) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
FREQ Freq Nobs
Q Quarterly 4597459
A Annual 10718

INSTR_ASSET

Code 
QSA |>
  left_join(INSTR_ASSET,  by = "INSTR_ASSET") |>
  group_by(INSTR_ASSET, Instr_asset) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
INSTR_ASSET Instr_asset Nobs
F4 NA 1108451
F3 Debt securities 1061400
F511 Listed shares 315592
_Z NA 252180
F2M Deposits 148055
F52 Investment fund shares/units 137238
F NA 130249
F81 NA 100368
F89 NA 99751
F51M Unlisted shares and other equity 94357
F8 NA 68672
F5 NA 68207
F51 NA 64636
F6 NA 63803
F7 NA 61672
F6M NA 60374
F6O NA 59820
F6N NA 56306
F519 NA 54624
F512 NA 54621
F6P NA 49401
F2 NA 44018
F522 NA 43897
F21 NA 41228
F22 NA 39938
F29 NA 39540
F521 NA 39057
F62 Life insurance and annuity entitlements 35914
F62B NA 31494
F63 NA 29845
F63B NA 29748
F62A NA 29063
F63A NA 23169
F1 NA 19598
F11 NA 19205
F12 NA 18317
F3T4 NA 4882
FPT NA 2072
FP NA 1805
FR0 NA 1091
NUN Housing wealth (net) 942
NYN NA 900
FX4 NA 583
N11N NA 471
N11G NA 469
N111N NA 348
N11MG NA 228
N111G NA 121
N11MN NA 121
N112N NA 120
N11LN NA 108
N21111 NA 108

PRICES

Code 
QSA |>
  left_join(PRICES,  by = "PRICES") |>
  group_by(PRICES, Prices) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
PRICES Prices Nobs
V Current prices 4599517
L Chain linked volume 3805
_Z Not applicable 2767
D Deflator (index) 1421
LR Chain linked volume (rebased) 393
Y Previous year prices 274

REF_AREA

Code 
QSA |>
  left_join(REF_AREA,  by = "REF_AREA") |>
  group_by(REF_AREA, Ref_area) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

REF_SECTOR

Code 
QSA |>
  left_join(REF_SECTOR,  by = "REF_SECTOR") |>
  group_by(REF_SECTOR, Ref_sector) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

STO

Code 
QSA |>
  left_join(STO,  by = "STO") |>
  group_by(STO, Sto) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Loans granted to households as % of GDP

QSA.Q.N.BG.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B1GQ_CY._T.S.V.N._T QSA.Q.N.SE.W0.S1V.S1.N.L.F.F3T4.T._Z.XDC_R_B1GQ_CY._T.S.V.CY._T

Loans granted to households as a ratio of GDP

Loans granted to households as a ratio of GDP: QSA.Q.N.I9.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B1GQ_CY._T.S.V.N._T

Loans granted to households as a % of GDI

Loans granted to households as a ratio of gross disposable income

QSA.Q.N.AT.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6G_CY._T.S.V.N._T

Adjusted loans

Euro area Non Financial corporations (NFCs)

Code 
# Old denominator code "B6G_CY" is now "B6GA_CY"; FR has no series under this
# key at all anymore (checked directly against QSA.parquet) so it's dropped
# here rather than guessing a substitute.
QSA |>
  filter(KEY %in% c("QSA.Q.N.DE.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T",
                    "QSA.Q.N.IT.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T")) |>
  quarter_to_date() |>
  left_join(REF_AREA, by = "REF_AREA") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  left_join(colors, by = c("Ref_area" = "country")) |>
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
  ylab("Adjusted loans vs. € area NFCs, annual growth") + xlab("") + theme_minimal() +
  add_flags(3) + scale_color_identity() +
  theme(legend.position = c(0.45, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 25),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

QSA.Q.N.I9.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T

Households

Code 
QSA |>
  filter(KEY %in% c("QSA.Q.N.AT.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T",
                    "QSA.Q.N.DE.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T",
                    "QSA.Q.N.IT.W0.S1M.S1.N.L.LE.F4.T._Z.XDC_R_B6GA_CY._T.S.V.N._T")) |>
  quarter_to_date() |>
  left_join(REF_AREA, by = "REF_AREA") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  left_join(colors, by = c("Ref_area" = "country")) |>
  ggplot() + geom_line(aes(x = date, y = OBS_VALUE, color = color)) +
  ylab("Adjusted loans vs. € area NFCs, annual growth") + xlab("") + theme_minimal() +
  add_flags(3) + scale_color_identity() +
  theme(legend.position = c(0.45, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 300, 25),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

Total financial liabilities of Non financial corporations

Non-financial corporations’ financing increased at lower annual rate of 1.5%, after 2.0%

QSA.Q.N.I9.W0.S11.S1.N.L.F.F._Z._Z.XDC._T.S.V.N._T