Récapitulatif des séries des comptes d’agents

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee t_recapAgent_val 2024-12-21 2024-12-21

Données

  • Comptes nationaux trimestriels au 4ème trimestre 2023. [html] / [xls]

Données sur le pouvoir d’achat

source dataset .html .RData
insee CNA-2014-RDB 2024-12-22 2024-12-22
insee CNT-2014-CSI 2024-12-22 2024-12-22
insee conso-eff-fonction 2024-12-22 2022-06-14
insee econ-gen-revenu-dispo-pouv-achat-2 2024-12-22 2024-07-05
insee reve-conso-evo-dep-pa 2024-12-22 2024-12-11
insee reve-niv-vie-individu-activite 2024-12-22 NA
insee reve-niv-vie-pouv-achat-trim 2024-12-22 2024-12-11
insee T_7401 2024-12-22 2024-10-18
insee t_men_val 2024-12-22 2024-12-21
insee t_pouvachat_val 2024-12-22 2024-12-21
insee t_recapAgent_val 2024-12-21 2024-12-21
insee t_salaire_val 2024-12-21 2024-12-21
oecd HH_DASH 2024-09-15 2023-09-09

LAST_COMPILE

LAST_COMPILE
2024-12-22

date

Code 
t_recapAgent_val %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(date)) %>%
  print_table_conditional

2017T2-

Table

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(date %in% c(as.Date("2017-04-01"), max(date) - months(3), max(date))) %>%
  spread(date, value) %>%
  print_table_conditional(.)

D41 - Intérêts

2017T2-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D41") %>%
  filter(date %in% c(as.Date("2017-04-01"), max(date) - months(3), max(date))) %>%
  spread(date, value) %>%
  print_table_conditional(.)
sheet column Compte operation Operation1 Operation2 2017-04-01 2024-04-01 2024-07-01
APU 24 Compte d'affectation des revenus primaires D41 Reçu Intérêts 0.352 0.759 0.722
APU 28 Compte d'affectation des revenus primaires D41 Versé Intérêts 10.253 14.169 14.756
ISBLSM 16 Compte d'affectation des revenus primaires D41 Reçu Intérêts 0.166 0.906 0.867
ISBLSM 18 Compte d'affectation des revenus primaires D41 Versé Intérêts 0.046 0.192 0.185
Menages 42 Compte d'affectation des revenus primaires D41 Reçu Intérêts 3.150 17.721 16.948
Menages 46 Compte d'affectation des revenus primaires D41 Versé Intérêts 3.160 15.500 14.816
RdM 10 NA D41 En provenance du reste du monde Intérêts 13.594 41.926 42.189
RdM 31 NA D41 à destination du reste du monde Intérêts 15.015 48.720 48.561
SF 17 Compte d'affectation des revenus primaires D41 Reçu Intérêts 37.024 129.099 128.761
SF 21 Compte d'affectation des revenus primaires D41 Versé Intérêts 25.236 108.970 106.721
SNF 17 Compte d'affectation des revenus primaires D41 Reçu Intérêts 14.800 43.008 43.244
SNF 22 Compte d'affectation des revenus primaires D41 Versé Intérêts 18.216 59.455 60.436

2021T2-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D41") %>%
  filter(date %in% c(as.Date("2021-04-01"), max(date))) %>%
  spread(date, value) %>%
  print_table_conditional(.)
sheet column Compte operation Operation1 Operation2 2021-04-01 2024-07-01
APU 24 Compte d'affectation des revenus primaires D41 Reçu Intérêts 0.139 0.722
APU 28 Compte d'affectation des revenus primaires D41 Versé Intérêts 7.897 14.756
ISBLSM 16 Compte d'affectation des revenus primaires D41 Reçu Intérêts 0.126 0.867
ISBLSM 18 Compte d'affectation des revenus primaires D41 Versé Intérêts 0.028 0.185
Menages 42 Compte d'affectation des revenus primaires D41 Reçu Intérêts 2.301 16.948
Menages 46 Compte d'affectation des revenus primaires D41 Versé Intérêts 2.318 14.816
RdM 10 NA D41 En provenance du reste du monde Intérêts 12.381 42.189
RdM 31 NA D41 à destination du reste du monde Intérêts 11.114 48.561
SF 17 Compte d'affectation des revenus primaires D41 Reçu Intérêts 30.591 128.761
SF 21 Compte d'affectation des revenus primaires D41 Versé Intérêts 20.837 106.721
SNF 17 Compte d'affectation des revenus primaires D41 Reçu Intérêts 16.193 43.244
SNF 22 Compte d'affectation des revenus primaires D41 Versé Intérêts 17.001 60.436

D42 - Dividendes

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42") %>%
  filter(date %in% c(as.Date("2017-04-01"), max(date) - months(3), max(date))) %>%
  spread(date, value) %>%
  print_table_conditional(.)
sheet column Compte operation Operation1 Operation2 2017-04-01 2024-04-01 2024-07-01
APU 25 Compte d'affectation des revenus primaires D42 Reçu Dividendes 2.017 1.771 1.851
Menages 43 Compte d'affectation des revenus primaires D42 Reçu Dividendes 8.096 17.516 17.611
RdM 11 NA D42 En provenance du reste du monde Dividendes 13.900 27.362 27.742
RdM 32 NA D42 à destination du reste du monde Dividendes 11.211 21.464 21.729
SF 18 Compte d'affectation des revenus primaires D42 Reçu Dividendes 12.135 21.657 21.809
SF 22 Compte d'affectation des revenus primaires D42 Versé Dividendes 10.339 16.888 17.301
SNF 18 Compte d'affectation des revenus primaires D42 Reçu Dividendes 37.506 49.230 49.737
SNF 23 Compte d'affectation des revenus primaires D42 Versé Dividendes 46.726 67.388 67.694

B9NF - Besoin (-) ou Capacité (+) de financement

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  filter(date %in% c(as.Date("2017-04-01"), max(date) - months(3), max(date))) %>%
  spread(date, value) %>%
  print_table_conditional(.)
sheet column Compte operation Operation1 Operation2 2017-04-01 2024-04-01 2024-07-01
APU 64 Compte de capital B9NF Besoin (-) ou Capacité (+) de financement NA -17.783 -41.547 -46.582
ISBLSM 35 Compte de capital B9NF Besoin (-) ou Capacité (+) de financement NA 0.082 0.477 0.446
Menages 78 Compte de capital B9NF Besoin (-) ou Capacité (+) de financement NA 14.164 39.344 41.146
RdM 50 NA B9NF Besoin (-) ou Capacité(+) de financement de la Nation NA -2.978 -1.686 2.923
SF 52 Compte de capital B9NF Besoin (-) ou Capacité (+) de financement NA -1.345 3.008 5.335
SNF 46 Compte de capital B9NF Besoin (-) ou Capacité (+) de financement NA 1.905 -2.968 2.577

B9NF - Besoin (-) ou Capacité (+) de financement

Tous

Md€

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(sheet, " - ", Operation1))) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-200, 100, 10),
                labels = dollar_format(pre = "", su = " Md€")) +
  theme(legend.position = c(0.4, 0.8),
        legend.title = element_blank())

% du PIB

Tous

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 1),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

2000

Basique
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "2 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

Autre division
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2000-01-01")) %>%
  transmute(date, value = value/gdp, sheet) %>%
  spread(sheet, value) %>%
  transmute(date, `Administrations Publiques` = `APU`, `Sociétés (SNF + SF)` = SNF + SF, `Ménages` = Menages) %>%
  gather(sheet, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "2 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.35, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

2007-

Basique
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2007-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "2 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

Autre division
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2007-01-01")) %>%
  transmute(date, value = value/gdp, sheet) %>%
  spread(sheet, value) %>%
  transmute(date, `Administrations Publiques` = `APU`, `Sociétés (SNF + SF)` = SNF + SF, `Ménages` = Menages) %>%
  gather(sheet, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.35, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

2013-

Basique
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2013-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("2013-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

Autre division
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2013-01-01")) %>%
  transmute(date, value = value/gdp, sheet) %>%
  spread(sheet, value) %>%
  transmute(date, `Administrations Publiques` = `APU`, `Sociétés (SNF + SF)` = SNF + SF, `Ménages` = Menages) %>%
  gather(sheet, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.35, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

2017-

Basique
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2017-01-01")) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("2017-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal")

Autre division
Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "B9NF") %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2017-01-01")) %>%
  transmute(date, value = value/gdp, sheet) %>%
  spread(sheet, value) %>%
  transmute(date, `Administrations Publiques` = `APU`, `Sociétés (SNF + SF)` = SNF + SF, `Ménages` = Menages) %>%
  gather(sheet, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = sheet)) +
  xlab("") + ylab("Besoin (-) ou Capacité (+) de financement (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.35, 0.84),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed")

D42 - Dividendes

Tous

Md€

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42") %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(sheet, " - ", Operation1))) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-10, 100, 10),
                labels = dollar_format(pre = "", su = " Md€")) +
  theme(legend.position = c(0.3, 0.7),
        legend.title = element_blank())

% du PIB

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = paste0(sheet, " - ", Operation1))) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.2, 0.7),
        legend.title = element_blank())

Nets

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42") %>%
  transmute(date, value, Variable =  paste0(sheet, " - ", Operation1)) %>%
  spread(Variable, value) %>%
  transmute(date,
            `Administrations Publiques: Reçu` = `APU - Reçu`,
            `Ménages: Reçu` = `Menages - Reçu`,
            `Reste du Monde: En provenance - à destination` = `RdM - En provenance du reste du monde` - `RdM - à destination du reste du monde`,
            `Sociétés Financières: Reçu - Versé` = `SF - Reçu` - `SF - Versé`,
            `Sociétés Non Financières: Reçu - Versé` = `SNF - Reçu` - `SNF - Versé`) %>%
  gather(Variable, value, -date) %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, .5),
                labels = percent_format(acc = .1)) +
  theme(legend.position = c(0.5, 0.88),
        legend.title = element_blank())

D42, D44

% du PIB

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("D42", "D44"),
         sheet == "Menages") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Operation2)) +
  xlab("") + ylab("Dividendes reçus, Ménages (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                labels = percent_format(acc = 0.1)) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank())

Mds€

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("D42", "D44"),
         sheet == "Menages") %>%
  ggplot + geom_line(aes(x = date, y = value, color = Operation2)) +
  xlab("") + ylab("Dividendes reçus, Ménages") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 2)) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank())

1999

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("D42", "D44", "B6", "D11"),
         sheet == "Menages") %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(Operation2) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(Operation1, Operation2))) +
  xlab("") + ylab("Dividendes reçus, Ménages") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 100)) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank())

1999

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("D51", "D611", "D613"),
         sheet == "Menages") %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(Operation2) %>%
  arrange(date) %>%
  mutate(value = 100*value/value[1]) %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(Operation1, Operation2))) +
  xlab("") + ylab("Dividendes reçus, Ménages") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 10)) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank())

B2 (y compris B3)

1999-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B2 (y compris B3)"),
         sheet == "Menages") %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(Operation2) %>%
  arrange(date) %>%
  mutate(value_index = 100*value/value[1]) %>%
  ggplot + geom_line(aes(x = date, y = value_index, color = paste0(Operation2))) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 10)) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  geom_label_repel(data = . %>% filter(date == max(date) | date == min(date)),
                   aes(x = date, y = value_index, label = round(value), color = Operation2))

2017-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B2 (y compris B3)"),
         sheet == "Menages") %>%
  filter(date >= as.Date("2017-01-01")) %>%
  group_by(Operation2) %>%
  arrange(date) %>%
  mutate(value_index = 100*value/value[1]) %>%
  ggplot + geom_line(aes(x = date, y = value_index, color = Operation2)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 1000, 5)) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  geom_label_repel(data = . %>% filter(date == max(date) | date == min(date)),
                   aes(x = date, y = value_index, label = round(value), color = Operation2))

Comptes des ménages

Dividendes

Md€

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42",
         sheet == "Menages") %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(sheet, " - ", Operation1))) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-10, 100, 2),
                labels = dollar_format(pre = "", su = " Md€")) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank())

% du PIB

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation == "D42",
         sheet == "Menages") %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp)) +
  xlab("") + ylab("Dividendes reçus, Ménages (% du PIB)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 0.1),
                labels = percent_format(acc = 0.1)) +
  theme(legend.position = c(0.2, 0.8),
        legend.title = element_blank())

Revenu

% du PIB

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B6", "B7"),
         sheet == "Menages") %>%
  arrange(date) %>%
  left_join(gdp_quarterly, by = "date") %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Operation1)) +
  xlab("") + ylab("% du PIB") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Epargne

% du revenu

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B8", "B9NF", "B6", "P51"),
         sheet == "Menages") %>%
  select(date, value, operation) %>%
  arrange(date) %>%
  unique %>%
  spread(operation, value) %>%
  transmute(date,
            `Epargne brute des ménages B8/B6` = B8/B6,
            `Besoin (-) ou Capacité (+) de financement B9NF/B6` = B9NF/B6,
            `Formation brute de capital fixe P51/B6` = P51/B6) %>%
  gather(variable, value, -date) %>%
  ggplot + geom_line(aes(x = date, y = value, color = variable)) +
  xlab("") + ylab("% du revenu disponible brut (B6)") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

% du PIB

Tous

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B8", "B9NF", "P51"),
         sheet == "Menages") %>%
  arrange(date) %>%
  left_join(gdp_quarterly, by = "date") %>%
  mutate(Variable = ifelse(operation %in% c("B8", "B9NF"),
                           Operation1, Operation2)) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Variable)) +
  xlab("") + ylab("% du PIB") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "5 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

2006-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B8", "B9NF", "P51"),
         sheet == "Menages") %>%
  arrange(date) %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2006-01-01")) %>%
  mutate(Variable = ifelse(operation %in% c("B8", "B9NF"),
                           Operation1, Operation2)) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Variable)) +
  xlab("") + ylab("% du PIB") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "2 years"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

2015-

Code 
t_recapAgent_val %>%
  left_join(variable, by = c("sheet", "column")) %>%
  filter(operation %in% c("B8", "B9NF", "P51"),
         sheet == "Menages") %>%
  arrange(date) %>%
  left_join(gdp_quarterly, by = "date") %>%
  filter(date >= as.Date("2015-01-01")) %>%
  mutate(Variable = ifelse(operation %in% c("B8", "B9NF"),
                           Operation1, Operation2)) %>%
  ggplot + geom_line(aes(x = date, y = value/gdp, color = Variable)) +
  xlab("") + ylab("% du PIB") + theme_minimal() +
  scale_x_date(breaks = seq.Date(from = as.Date("1900-01-01"), to = as.Date("2100-10-01"), by = "1 year"),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 2),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())