Balance des paiements - 6ème manuel

Data - BDF

Author

Info

source	dataset	Title	.html	.rData
bdf	BPM6	Balance des paiements - 6ème manuel	2026-02-23	2026-01-11
eurostat	bop_iip6_q	International investment position - quarterly and annual data (BPM6)	2026-02-24	2026-01-28

LAST_COMPILE

LAST_COMPILE
2026-02-26

Last

date	Nobs
2025-11-30	218

Data Structure

Code

BPM6_metadata %>%
  select(key, name) %>%
  unique %>%
  print_table_conditional()

key	name
FREQ	Frequency
ADJUSTMENT	Adjustment
REF_AREA	Reference area - ISO2
COUNTERPART_AREA	Counterpart area
REF_SECTOR	Reference sector
COUNTERPART_SECTOR	Counterpart sector
FLOW_STOCK_ENTRY	Flows and stocks indicator
ACCOUNTING_ENTRY	Accounting entries
INT_ACC_ITEM	International accounts item
FUNCTIONAL_CAT	Functional category
INSTR_ASSET	Instrument and assets classification
MATURITY	Maturity
UNIT_MEASURE	Unit of measure
CURRENCY_DENOM	Currency denominator
VALUATION	Valuation
COMP_METHOD	Compiliation methodology
TYPE_ENTITY	Structural and locational characteristics of the statistical unit

Balance des Paiements de la France

Novembre 2024

Source. html pdf

Octobre 2024

Solde des transactions courantes

Code

ig_b("bdf", "FR_Stat_Info_Balance_des_paiements_de_la_France_202410", "balance-courante")

Solde des opérations financières

Code

ig_b("bdf", "FR_Stat_Info_Balance_des_paiements_de_la_France_202410", "solde-des-operations-financieres")

Janvier 2024

Compte Courant

Table

Code

ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "table1")

Figure

Code

ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "figure1")

Compte Financier

Table

Code

ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "table2")

Figure

Code

ig_b("bdf", "BDP_FRA_2284_fr__BDP_Stat_Info_janvier_2024_FR", "figure2")

Novembre 2021

Code

ig_b("bdf", "bdp_fra_2241_fr_bdp_stat_info_septembre_2021_fr", "comptes")

Mai 2020

Code

ig_b("bdf", "BPM6-2021-07")

Novembre 2020

Code

ig_b("bdf", "BPM6-2020-11-compte")

FREQ Frequency

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

FREQ	Freq	Nobs
Q	Trimestriel	63103
M	Mensuel	33790
A	Annuel	22341

ADJUSTMENT Adjustment

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(ADJUSTMENT, by = "ADJUSTMENT") %>%
  group_by(ADJUSTMENT, Adjustment) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

ADJUSTMENT	Adjustment	Nobs
N	Brut	112879
S	CVS	6355

REF_AREA Reference area - ISO2

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

REF_AREA	Ref_area	Nobs
FR	France	119234

COUNTERPART_AREA Counterpart area

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  group_by(COUNTERPART_AREA, Counterpart_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

REF_SECTOR Reference sector

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(REF_SECTOR, by = "REF_SECTOR") %>%
  group_by(REF_SECTOR, Ref_sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

REF_SECTOR	Ref_sector	Nobs
S1	Ensemble de l`économie	88118
S13	Administrations publiques	6150
S12T	IFM autres que la Banque Centrale	5965
S121	Banque Centrale	5013
S12M	Sociétés financières autres que les IFM	3417
S1P	Autres secteurs que les IFM et les administrations publiques	3138
S1V	Sociétés non-financières, ménages et NPISH	3102
S1W	Secteurs hors administrations publiques	2672
S122	Etablissements de crédits	663
S1Z	Agents non financiers	663
S12K	Institutions financières monétaires	216
S1311	de l`Etat	117

COUNTERPART_SECTOR Counterpart sector

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(COUNTERPART_SECTOR, by = "COUNTERPART_SECTOR") %>%
  group_by(COUNTERPART_SECTOR, Counterpart_sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

COUNTERPART_SECTOR	Counterpart_sector	Nobs
S1	Ensemble de l`économie	118096
S1N	Non sectorisé	401
_Z	Non applicable	221
S12T	IFM autres que la Banque Centrale	204
S12K	Institutions financières monétaires	108
S1Q	Autres secteurs que les IFM	108
S1311	de l`Etat	96

FLOW_STOCK_ENTRY Flows and stocks indicator

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(FLOW_STOCK_ENTRY, by = "FLOW_STOCK_ENTRY") %>%
  group_by(FLOW_STOCK_ENTRY, Flow_stock_entry) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

FLOW_STOCK_ENTRY	Flow_stock_entry	Nobs
T	Flux	90589
LE	Stocks	28335
T3M	moyenne mobile sur 3 mois	310

ACCOUNTING_ENTRY Accounting entries

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(ACCOUNTING_ENTRY, Accounting_entry) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

ACCOUNTING_ENTRY	Accounting_entry	Nobs
A	Créances	25148
C	Crédit (recettes)	21117
B	Balance (Crédit moins débit)	19258
D	Débit (dépenses)	19246
L	Engagements	17847
N	Net (avoirs moins engagements)	16555
NE	Engagements Nets (engagements moins avoirs)	63

INT_ACC_ITEM International accounts item

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  group_by(INT_ACC_ITEM, Int_acc_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

FUNCTIONAL_CAT Functional category

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(FUNCTIONAL_CAT, by = "FUNCTIONAL_CAT") %>%
  group_by(FUNCTIONAL_CAT, Functional_cat) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

FUNCTIONAL_CAT	Functional_cat	Nobs
_Z	Non applicable	46968
O	Autres investissements	23474
P	Investissements de portefeuille	22428
D	Investissements directs	17222
_T	Toutes catégories fonctionnelles confondues	4586
R	Avoirs de réserves	2309
F	Dérivés financiers (autres que les réserves) et options sur titres des salariés	1446
TXD	Toutes catégories fonctionnelles hors investissements directs	648
D1	Investisseur direct par rapport aux entreprises investies	51
D2	Entreprises investies par rapport à l`investisseur direct	51
D3	Investissement direct entre les sociétés soeurs	51

INSTR_ASSET Instrument and assets classification

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(INSTR_ASSET, by = "INSTR_ASSET") %>%
  group_by(INSTR_ASSET, Instr_asset) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

INSTR_ASSET	Instr_asset	Nobs
_Z	Non applicable	47004
F	Total	24762
F3	Instruments de dette	10405
F4	Crédits	5872
F2	Monnaie et dépôts	5214
F5	Actions et parts de fonds de placement	4913
FL	Instruments de dette (IDE)	4000
F51	d`actions et titres d`OPC	3813
F52	d`actions et OPC	2445
F81	Crédits commerciaux et avances	2338
F7	Dérivés financiers (autres que les réserves) et options sur titres des salariés	1446
F12	Droits de Tirage spéciaux (DTS)	1077
FLA	Instruments de dette autre que assurance, pension et plans d`épargnes standardisés	918
FGED	Dette extérieure brute	915
F89	Autres comptes debiteur /créditeur à l`exception des crédits commerciaux et avances	840
F5A	Actions et parts de fonds de placement autres que réinvestissements des bénéfices	702
F5B	Actions et parts de fonds de placement, réinvestissement des bénéfices	690
F519	des autres participations	411
F6	Assurance, retraites et régimes de garanties standard (F6)	366
F11	Or monétaire	323
FK	Position de réserve au FMI	281
FR2	Autres avoirs de réserves (devises, dépôts, titres, produits financiers dérivés et autres créances)	281
FNED	Dette extérieure nette	74
F511	d`actions cotées	72
F512	d`actions non cotées	72

MATURITY Maturity

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(MATURITY, by = "MATURITY") %>%
  group_by(MATURITY, Maturity) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

MATURITY	Maturity	Nobs
_Z	Non applicable	86079
T	Toutes maturités d`origine	17932
S	Maturité d`origine à court terme (inférieure à 1 an)	8129
L	Maturité d`origine à long terme (supérieure à un an ou pas de maturité)	7094

UNIT_MEASURE Unit of measure

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(UNIT_MEASURE, by = "UNIT_MEASURE") %>%
  group_by(UNIT_MEASURE, Unit_measure) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

UNIT_MEASURE	Unit_measure	Nobs
EUR	Euro	119201
PCPIB	pourcentage du PIB	33

CURRENCY_DENOM Currency denominator

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(CURRENCY_DENOM, by = "CURRENCY_DENOM") %>%
  group_by(CURRENCY_DENOM, Currency_denom) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

CURRENCY_DENOM	Currency_denom	Nobs
_T	Toutes monnaies d`opération	114387
EUR	Euro	1379
XO	Toutes devises sauf Euro	1142
X1	Toutes monnaies sauf monnaie nationale	613
XDR	Droit de Tirage Special (D.T.S.) (=3.61 Xfo)	562
XAU	Or Monetaire	323
GBP	Livre Sterling	216
JPY	Yen	216
USD	Dollar des Etats-Unis	216
CNY	Yuan Ren Min Bi	180

VALUATION Valuation

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(VALUATION, by = "VALUATION") %>%
  group_by(VALUATION, Valuation) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

VALUATION	Valuation	Nobs
_X	Tous types de valorisation	80637
M	Valeur de marché	20190
N	Valeur nominale (N)	10743
V	Valeur comptable	6218
T	Net marked to market value	1446

COMP_METHOD Compiliation methodology

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  left_join(COMP_METHOD, by = "COMP_METHOD") %>%
  group_by(COMP_METHOD, Comp_method) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional

COMP_METHOD	Comp_method	Nobs
N	Méthodologie d`agrégation conforme aux règles nationales	116362
P	Méthodologie de compilation appliquée au principe directionnel étendu	2872

Compte financier vs compte courant, Différence

Compte financier et compte courant

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA._T.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(Accounting_entry) %>%
  arrange(date) %>%
  mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)) %>%
  na.omit %>%
  mutate(Int_acc_item = ifelse(Int_acc_item == "Transactions courantes", "Compte de transactions courantes", Int_acc_item)) %>%
   ggplot + geom_line(aes(x = date, y = value/1000, color = Int_acc_item)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(pre = "", su = " Md€"),
                     breaks = seq(-300000, 300000, 10000)/1000) +
  theme_minimal() + xlab("") + ylab("Cumul sur 12 mois") +
  theme(legend.position = c(0.2, 0.3),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  geom_label(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, label = paste0(round(value/1000, 1)), color = Int_acc_item)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Différence

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA._T.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(Accounting_entry) %>%
  arrange(date) %>%
  mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)) %>%
  ungroup %>%
  select(date, value, Int_acc_item) %>%
  na.omit %>%
  spread(Int_acc_item, value) %>%
  mutate(`Différence` = `Compte financier` - `Transactions courantes`) %>%
  gather(Int_acc_item, value, -date) %>%
   ggplot + geom_line(aes(x = date, y = value/1000, color = Int_acc_item)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(-300000, 300000, 10000)/1000) +
  theme_minimal() + xlab("") + ylab("") +
  theme(legend.position = c(0.2, 0.3),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  geom_label(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, label = round(value/1000, 1), color = Int_acc_item))

Investissement direct étranger

Flux

All

Monthly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(Accounting_entry) %>%
  arrange(date) %>%
  mutate(value = zoo::rollsum(x = value, 36, align = "right", fill = NA)/3) %>%
  na.omit %>%
   ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(-10000, 300000, 5000)) +
  theme_minimal() + xlab("") + ylab("") +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical")

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.Q.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.Q.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(Accounting_entry) %>%
  arrange(date) %>%
  mutate(value = zoo::rollsum(x = value, 12, align = "right", fill = NA)/3) %>%
  na.omit %>%
   ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(-10000, 300000, 5000)) +
  theme_minimal() + xlab("") + ylab("") +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical")

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.A.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.A.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  group_by(Accounting_entry) %>%
  arrange(date) %>%
  mutate(value = zoo::rollsum(x = value, 4, align = "right", fill = NA)/4) %>%
  na.omit %>%
   ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(pre = ""),
                     breaks = seq(-10000, 300000, 5000)) +
  theme_minimal() + xlab("") + ylab("") +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical")

2017

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.N.FR.W1.S1.S1.T.A.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.N.FR.W1.S1.S1.T.L.FA.D.F._Z.EUR._T.V.N.ALL" |
           variable == "BPM6.M.N.FR.W1.S1.S1.T.N.FA.D.F._Z.EUR._T.V.N.ALL",
            date >= as.Date("2017-01-01")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  arrange(desc(date)) %>%
   ggplot + geom_line(aes(x = date, y = value, color = Accounting_entry)) +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme_minimal() + xlab("") + ylab("") +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank(),
        legend.direction = "vertical")

Compte de transactions courantes

Biens, Services, Biens & Services

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value /gdp / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "2 years",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2, 0.2),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Biens, Services, Biens et Services (Net)") +
  scale_y_continuous(breaks = 0.01*seq(-200, 200, 1),
                labels = percent_format(accuracy = 1))

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable %in%c("BPM6.Q.N.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL",
                        "BPM6.Q.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL",
                        "BPM6.Q.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
                        "BPM6.Q.N.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "2 years",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.2),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Balance") +
  scale_y_continuous(breaks = 0.01*seq(-200, 200, 1),
                labels = percent_format(accuracy = 1))

Monthly

Par mois

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
           variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Par mois") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Md€",  accuracy = 1, prefix = ""))

Cumul sur 12 mois

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GS._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
           variable == "BPM6.M.S.FR.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  group_by(Int_acc_item) %>%
  arrange(desc(date)) %>%
  mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
  na.omit %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Cumul sur 12 mois") +
  scale_y_continuous(breaks = seq(-200, 200, 10),
                labels = dollar_format(suffix = " Md€",  accuracy = 1, prefix = "")) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))

Balance des services

BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL (Services) BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL (Services hors voyages) BPM6.M.S.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL (Services - Transport) BPM6.M.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL (Services, Voyages)

Cumul sur 12 mois

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  # Services
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
           # Services hors voyages
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL" |
           # Services - Transport
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL" |
           # Services, Voyages
         variable == "BPM6.M.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  group_by(Int_acc_item) %>%
  arrange(desc(date)) %>%
  mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
  na.omit %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Cumul sur 12 mois") +
  scale_y_continuous(breaks = seq(-200, 200, 10),
                labels = dollar_format(suffix = " Md€",  accuracy = 1, prefix = "")) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))

Cumul sur 12 mois

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  # Services
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL" |
           # Services hors voyages
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SXD._Z._Z._Z.EUR._T._X.N.ALL" |
           # Services, Voyages
         variable == "BPM6.M.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  group_by(Int_acc_item) %>%
  arrange(desc(date)) %>%
  mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
  na.omit %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Cumul sur 12 mois") +
  scale_y_continuous(breaks = seq(-200, 200, 10),
                labels = dollar_format(suffix = " Md€",  accuracy = 1, prefix = "")) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))

Balance des biens (Douanes vs. BPM6)

Cumul sur 12 mois

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G1X._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.B.GX._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  group_by(Int_acc_item) %>%
  arrange(desc(date)) %>%
  mutate(value = zoo::rollsum(value, 12, align = "left", fill = NA)) %>%
  na.omit %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Cumul sur 12 mois") +
  scale_y_continuous(breaks = seq(-200, 200, 10),
                labels = dollar_format(suffix = " Md€",  accuracy = 1, prefix = "")) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = value/1000, color = Int_acc_item, label = round(value/1000, digits = 1)))

Solde - Services, Transport, Voyage

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable %in% c("BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.A.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.A.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.A.N.FR.W1.S1.S1.T.B.SXCD._Z._Z._Z.EUR._T._X.N.ALL")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Balance des Services (% du PIB)") +
  scale_y_continuous(breaks = 0.01*seq(-200, 200, .2),
                labels = percent_format(accuracy = .1),
                limits = 0.01*c(-0.6, 2.2)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable %in% c("BPM6.Q.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.Q.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL",
                         "BPM6.Q.N.FR.W1.S1.S1.T.B.SXCD._Z._Z._Z.EUR._T._X.N.ALL")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Services (Balance)") +
  scale_y_continuous(breaks = 0.01*seq(-200, 200, .2),
                labels = percent_format(accuracy = .1)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Biens

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.G._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.G._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  left_join(gdp, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value / gdp / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Biens") +
  scale_y_continuous(breaks = 0.01*seq(-200, 200, 2),
                labels = percent_format(accuracy = 1))

Services

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.S._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.S._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.S._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Services de Voyage") +
  scale_y_continuous(breaks = seq(-200, 2000, 20),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Monthly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Services de Transport

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.SC._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.SC._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.SC._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Services de Voyage") +
  scale_y_continuous(breaks = seq(-200, 200, 5),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Monthly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Services de Voyage

Annual

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Services de Voyage") +
  scale_y_continuous(breaks = seq(-200, 200, 5),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Monthly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.M.S.FR.W1.S1.S1.T.B.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.C.SD._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.M.S.FR.W1.S1.S1.T.D.SD._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 1),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Investissements de portefeuille

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.Q.N.FR.W1.S1.S1.T.A.FA.P.F._Z.EUR._T.M.N.ALL" |
         variable == "BPM6.Q.N.FR.W1.S1.S1.T.N.FA.P.F._Z.EUR._T.M.N.ALL") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-200, 200, 20),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Revenus Primaires

Tous

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.IN1._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.IN1._Z._Z._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.IN1._Z._Z._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "2 years",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("Revenus Primaires") +
  scale_y_continuous(breaks = seq(-200, 1000, 20),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Portefeuille

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.P.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.P.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.P.F._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Revenus de portefeuille") +
  scale_y_continuous(breaks = seq(-200, 1000, 20),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Revenus des autres investissements

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.O.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.O.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.O.F._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Revenus de portefeuille") +
  scale_y_continuous(breaks = seq(-200, 1000, 10),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Revenus d’investissement

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P._T.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P._T.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P._T.F._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Revenus d'investissement") +
  scale_y_continuous(breaks = seq(-200, 1000, 20),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Revenus des investissements directs

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.D.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.C.D4P.D.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.D.D4P.D.F._Z.EUR._T._X.N.ALL") %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.2,0.9),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  xlab("") + ylab("Revenus des investissements directs") +
  scale_y_continuous(breaks = seq(-200, 1000, 10),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Balance

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.D.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P._T.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.O.F._Z.EUR._T._X.N.ALL" |
         variable == "BPM6.A.N.FR.W1.S1.S1.T.B.D4P.P.F._Z.EUR._T._X.N.ALL") %>%
  left_join(FUNCTIONAL_CAT, by = "FUNCTIONAL_CAT") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
  
  theme_minimal() + xlab("") + ylab("Revenus primaires") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-200, 1000, 10),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Balance

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.D4P.", variable)) %>%
  left_join(FUNCTIONAL_CAT, by = "FUNCTIONAL_CAT") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
  
  theme_minimal() + xlab("") + ylab("Revenus primaires") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-200, 1000, 10),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Revenus Secondaires

Tous

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.IN2.", variable) |
         grepl("BPM6.A.N.FR.W1.S1.S1.T.C.IN2.", variable) |
         grepl("BPM6.A.N.FR.W1.S1.S1.T.D.IN2.", variable)) %>%
  left_join(ACCOUNTING_ENTRY, by = "ACCOUNTING_ENTRY") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Accounting_entry)) +
  
  theme_minimal() + xlab("") + ylab("Revenus secondaires") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-200, 1000, 10),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Balance

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(grepl("BPM6.A.N.FR.W1.S1.S1.T.B.IN2.", variable)) %>%
  left_join(FUNCTIONAL_CAT, by = "FUNCTIONAL_CAT") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Functional_cat)) +
  
  theme_minimal() + xlab("") + ylab("Revenus secondaires") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-200, 1000, 2),
                labels = dollar_format(suffix = " Mds €",  accuracy = 1, prefix = ""))

Transactions Courantes

All

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "M",
         INT_ACC_ITEM %in% c("G", "S", "G1X"),
         ADJUSTMENT == "S",
         REF_SECTOR == "S1",
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-100, 10, 1),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

2018-

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(date >= as.Date("2018-01-01"),
         FREQ == "M",
         ADJUSTMENT == "S",
         COUNTERPART_AREA == "W1",
         REF_SECTOR == "S1",
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("G", "S")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = "3 months",
               labels = date_format("%b-%y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical",
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_y_continuous(breaks = seq(-100, 10, 1),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Table - Monthly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(date == as.Date("2018-01-01"),
         FREQ == "M",
         ADJUSTMENT == "S",
         REF_SECTOR == "S1",
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B") %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  left_join(FUNCTIONAL_CAT, by = "FUNCTIONAL_CAT") %>%
  select(Int_acc_item, Functional_cat, value) %>%
  print_table_conditional

Int_acc_item	Functional_cat	value
NA	NA	NA
:------------:	:--------------:	:-----:

France vis à vis de l’Allemagne

All

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         COUNTERPART_AREA == "DE",
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("G", "S")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +  xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-40, 10, 1),
                labels = dollar_format(suffix = " Bn €",  accuracy = 1, prefix = ""))

Biens

Code

load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         COUNTERPART_AREA %in% c("DE", "CN"),
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("G")) %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  left_join(colors, by = c("Counterpart_area" = "country")) %>%
  mutate(value = value / 1000) %>%
  rename(Ref_area = Counterpart_area) %>%
  ggplot + geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_2flags +
  theme_minimal() +  xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-100, 10, 5),
                labels = dollar_format(suffix = "Mds€",  accuracy = 1, prefix = ""))

Services

Code

load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         COUNTERPART_AREA %in% c("DE", "CN"),
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("S")) %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  left_join(colors, by = c("Counterpart_area" = "country")) %>%
  mutate(value = value / 1000) %>%
  rename(Ref_area = Counterpart_area) %>%
  ggplot + geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_2flags +
  theme_minimal() +  xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-40, 10, 1),
                labels = dollar_format(suffix = "Mds€",  accuracy = 1, prefix = ""))

Biens et Services

Code

load_data("bdf/COUNTERPART_AREA.RData")
BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         COUNTERPART_AREA %in% c("DE", "CN"),
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("S", "G")) %>%
  select_if(~ n_distinct(.) > 1) %>%
  group_by(date, COUNTERPART_AREA) %>%
  summarise(value = sum(value)) %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  left_join(colors, by = c("Counterpart_area" = "country")) %>%
  mutate(value = value / 1000) %>%
  rename(Ref_area = Counterpart_area) %>%
  ggplot + geom_line(aes(x = date, y = value, color = color)) +
  scale_color_identity() + add_2flags +
  theme_minimal() +  xlab("") + ylab("Déficit Bilatéral avec la France (Source: Banque de France)") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-40, 10, 2),
                labels = dollar_format(suffix = "Mds€",  accuracy = 1, prefix = ""))

France vis à vis de la Chine

All

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         COUNTERPART_AREA == "CN",
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("G", "S")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3,0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-100, 10, 5),
                labels = dollar_format(suffix = " Mds€",  accuracy = 1, prefix = ""))

Quarterly

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(FREQ == "A",
         INT_ACC_ITEM %in% c("G", "S", "G1X"),
         COUNTERPART_AREA == "CN",
         REF_SECTOR == "S1",
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B",
         INT_ACC_ITEM %in% c("G", "S")) %>%
  left_join(INT_ACC_ITEM, by = "INT_ACC_ITEM") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Int_acc_item)) +
  
  theme_minimal() +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  xlab("") + ylab("") +
  scale_y_continuous(breaks = seq(-50, 10, 5),
                labels = dollar_format(suffix = " Mds€",  accuracy = 1, prefix = ""))

Table

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(date == as.Date("2020-03-31"),
         FREQ == "Q",
         INT_ACC_ITEM %in% c("G"),
         REF_SECTOR == "S1",
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B") %>%
  select(COUNTERPART_AREA, Variable, value) %>%
  print_table_conditional

COUNTERPART_AREA	Variable	value
B6	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis de l'Union européenne (27 membres) - Trimestriel - Brut	-7510
CH	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Suisse - Brut	798
CN	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Chine - Brut	-8069
I8	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Zone Euro - Brut	-8908
I9	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Zone Euro - Brut	-7142
J8	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis hors Zone Euro - Brut	-7378
J9	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis hors Zone Euro - Brut	-6778
JP	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Japon - Brut	-938
Q6	Transactions courantes - Biens - Ensemble de l'économie - Solde -France vis-à-vis de l'Union européenne à 28, hors zone euro à 18, à l?exclusion du Royaume-Uni, du Danemark et de la Suède - Brut	-416
US	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis États Unis - Brut	651
W1	Transactions courantes - Biens - Ensemble de l'économie - Solde - France vis-à-vis Reste du monde - Brut	-13919

Goods

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(date >= as.Date("2016-12-31"),
         FREQ == "Q",
         INT_ACC_ITEM %in% c("G"),
         REF_SECTOR == "S1",
         COUNTERPART_AREA %in% c("W1", "I8", "J8"),
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B") %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Counterpart_area)) +
  
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-30, 30, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

2010

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(date >= as.Date("2010-12-31"),
         FREQ == "Q",
         INT_ACC_ITEM %in% c("G"),
         REF_SECTOR == "S1",
         COUNTERPART_AREA %in% c("W1", "I8", "J8"),
         COUNTERPART_SECTOR == "S1",
         FLOW_STOCK_ENTRY == "T",
         ACCOUNTING_ENTRY == "B") %>%
  left_join(COUNTERPART_AREA, by = "COUNTERPART_AREA") %>%
  ggplot + geom_line(aes(x = date, y = value / 1000, color = Counterpart_area)) +
  
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = "1 year",
               labels = date_format("%Y")) +
  theme(legend.position = c(0.6, 0.1),
        legend.title = element_blank(),
        legend.direction = "vertical") +
  scale_y_continuous(breaks = seq(-30, 30, 2),
                labels = dollar_format(suffix = " Tn €",  accuracy = 1, prefix = ""))

Dette Exterieure Nette

Code

BPM6 %>%
  left_join(BPM6_var, by = "variable") %>%
  filter(variable %in% c("BPM6.A.N.FR.W1.S1.S1.LE.N.FA._T.FNED._Z.PCPIB._T._X.N.ALL",
                         "BPM6.A.N.FR.W1.S1.S1.LE.N.FA._T.F._Z.PCPIB._T._X.N.ALL")) %>%
  ggplot + geom_line(aes(x = date, y = value/100, color = Variable)) + 
  xlab("") + ylab("") + theme_minimal() +
 
  scale_x_date(breaks = "2 years",
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-200, 140, 10),
                labels = percent_format(accuracy = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank(),
        legend.direction = "vertical")