Récapitulatif des séries des comptes d’agents - t_recapAgent_val

Name: Récapitulatif des séries des comptes d'agents
Creator: François Geerolf
License: https://www.etalab.gouv.fr/licence-ouverte-open-licence/

Données - INSEE

Auteur

François Geerolf

Last observation: Q2 2026 (N = 374)

First observation: Q1 1949 (N = 355)

Last data update: 03 sept. 2026, 05:31

Last compile: 04 sept. 2026, 02:30

Données

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

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	2026-01-01	2026-04-01
APU	24	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	0.351	0.901	0.960
APU	28	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	10.253	18.191	18.916
ISBLSM	16	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	0.165	0.686	0.710
ISBLSM	18	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	0.046	0.161	0.174
Menages	42	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	3.142	12.723	12.751
Menages	46	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	3.148	11.311	11.368
RdM	10	NA	D41	En provenance du reste du monde	Intérêts	13.625	43.385	44.218
RdM	31	NA	D41	à destination du reste du monde	Intérêts	15.033	55.179	56.808
SF	17	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	37.052	115.827	119.533
SF	21	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	25.247	105.506	109.108
SNF	17	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	14.796	28.744	29.685
SNF	22	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	18.219	35.508	36.662

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	2026-04-01
APU	24	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	0.142	0.960
APU	28	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	8.005	18.916
ISBLSM	16	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	0.128	0.710
ISBLSM	18	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	0.028	0.174
Menages	42	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	2.301	12.751
Menages	46	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	2.304	11.368
RdM	10	NA	D41	En provenance du reste du monde	Intérêts	12.536	44.218
RdM	31	NA	D41	à destination du reste du monde	Intérêts	11.023	56.808
SF	17	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	30.652	119.533
SF	21	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	20.789	109.108
SNF	17	Compte d'affectation des revenus primaires	D41	Reçu	Intérêts	15.924	29.685
SNF	22	Compte d'affectation des revenus primaires	D41	Versé	Intérêts	16.508	36.662

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	2026-01-01	2026-04-01
APU	25	Compte d'affectation des revenus primaires	D42	Reçu	Dividendes	1.860	2.047	3.121
Menages	43	Compte d'affectation des revenus primaires	D42	Reçu	Dividendes	8.095	16.014	16.350
RdM	11	NA	D42	En provenance du reste du monde	Dividendes	13.898	31.566	31.692
RdM	32	NA	D42	à destination du reste du monde	Dividendes	11.212	19.756	19.613
SF	18	Compte d'affectation des revenus primaires	D42	Reçu	Dividendes	12.135	24.818	25.464
SF	22	Compte d'affectation des revenus primaires	D42	Versé	Dividendes	10.181	16.480	17.998
SNF	18	Compte d'affectation des revenus primaires	D42	Reçu	Dividendes	37.503	60.989	61.308
SNF	23	Compte d'affectation des revenus primaires	D42	Versé	Dividendes	46.726	75.578	76.166

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	2026-01-01	2026-04-01
APU	64	Compte de capital	B9NF	Besoin (-) ou Capacité (+) de financement	NA	-18.544	-38.734	-39.075
ISBLSM	35	Compte de capital	B9NF	Besoin (-) ou Capacité (+) de financement	NA	0.080	-0.152	-0.255
Menages	78	Compte de capital	B9NF	Besoin (-) ou Capacité (+) de financement	NA	14.447	43.064	40.418
RdM	50	NA	B9NF	Besoin (-) ou Capacité(+) de financement de la Nation	NA	-2.990	-5.634	-4.849
SF	52	Compte de capital	B9NF	Besoin (-) ou Capacité (+) de financement	NA	-1.562	-4.714	-5.813
SNF	46	Compte de capital	B9NF	Besoin (-) ou Capacité (+) de financement	NA	2.589	-5.098	-0.123

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

Basique

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF") |>
  left_join(gdp_quarterly, by = "date") |>
  transmute(date, value, gdp, sheet, value_gdp = value/gdp) |>
  
  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")

Avec label

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF") |>
  left_join(gdp_quarterly, by = "date") |>
  transmute(date, value = value/gdp, sheet) |>
  spread(sheet, value) |>
  transmute(date, `Administrations\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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 = "5 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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

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")

Avec label

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\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

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")+
  geom_hline(yintercept = 0, linetype ="dashed")

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") +
  geom_hline(yintercept = 0, linetype ="dashed")

Avec label

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\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

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")+
  geom_hline(yintercept = 0, linetype ="dashed")

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")+
  geom_hline(yintercept = 0, linetype ="dashed")

Avec label

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\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

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")+
  geom_hline(yintercept = 0, linetype ="dashed")

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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed")

Avec label

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\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

Sans sociétés

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\nPubliques` = `APU`, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  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(0.7, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% group_by(sheet) %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

2018-

Avec label

Code

# --- Votre préparation de données inchangée -----------------------------------
df_long <- 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) |>
  tidyr::pivot_wider(names_from = sheet, values_from = value) |>
  transmute(
    date,
    `Administrations\npubliques` = APU,
    `Sociétés\n(SNF + SF)` = SNF + SF,
    `Ménages` = Menages,
    `Reste du\nmonde` = RdM
  ) |>
  tidyr::pivot_longer(-date, names_to = "sheet", values_to = "value") |>
  arrange(sheet, date)

# --- Helpers dynamiques pour libellés -----------------------------------------
# Libellé "1er/2ème/3ème/4ème trimestre YYYY" en français
fr_trim_label <- function(d) {
  q <- lubridate::quarter(d)
  y <- lubridate::year(d)
  ord <- c("1er", "2ème", "3ème", "4ème")[q]
  paste0(ord, " trimestre ", y)
}

last_date  <- max(df_long$date, na.rm = TRUE)               # ex. 2025-04-01
last_label <- fr_trim_label(last_date)                      # "2ème trimestre 2025"
start_year <- lubridate::year(min(df_long$date, na.rm = TRUE))

# --- Points de départ/arrivée pour étiquettes --------------------------------
last_pts <- df_long |>
  group_by(sheet) |>
  slice_max(order_by = date, n = 1, with_ties = FALSE) |>
  ungroup() |>
  mutate(lbl = percent(value, accuracy = 0.01, style_positive = "plus"))

first_pts <- df_long |>
  group_by(sheet) |>
  slice_min(order_by = date, n = 1, with_ties = FALSE) |>
  ungroup() |>
  mutate(lbl = percent(value, accuracy = 0.01, style_positive = "plus"))

# --- Plot ---------------------------------------------------------------------
pal <- c(
  "Administrations\npubliques" = "#E69F00",
  "Sociétés\n(SNF + SF)"       = "#56B4E9",
  "Ménages"                    = "#009E73",
  "Reste du\nmonde"            = "#CC79A7"
)

ggplot(df_long, aes(date, value, color = sheet)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_line(linewidth = 1.1, na.rm = TRUE) +
  geom_label_repel(
    data = last_pts,
    aes(label = lbl),
    size = 3.4, segment.size = 0.3,
    label.padding = unit(0.15, "lines"),
    label.r = unit(0.15, "lines"),
    fill = "white", show.legend = FALSE
  ) +
  geom_label_repel(
    data = first_pts,
    aes(label = lbl),
    size = 3.4, segment.size = 0.3,
    label.padding = unit(0.15, "lines"),
    label.r = unit(0.15, "lines"),
    fill = "white", show.legend = FALSE
  ) +
  scale_color_manual(values = pal, NULL) +
  scale_y_continuous(
    breaks = 0.01 * seq(-100, 140, 2),
    labels = function(x) percent(x, accuracy = 1, style_positive = "plus")
  ) +
  scale_x_date(
    date_breaks = "1 year",
    date_labels = "%Y",
    expand = expansion(mult = c(0, 0.06))
  ) +
  labs(
    x = NULL,
    y = "Besoin (–) ou capacité (+) de financement\n% du PIB",
    title = paste0(
      "Capacité/Besoin de financement par secteur institutionnel"
    ),
    subtitle = paste0("Depuis ", start_year, " (trimestriel)"),
    caption  = paste0("Sources: Insee, comptes nationaux du ", last_label, ".")
  ) +
  theme_minimal(base_size = 12) +
  theme(
    plot.title = element_text(face = "bold"),
    legend.position = "top",
    legend.justification = "left",
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_line(linewidth = 0.2),
    panel.grid.major.y = element_line(linewidth = 0.2),
    axis.title.y = element_text(margin = margin(r = 8))
  )

Avec label, Mds€

Code

# 1) Prep ----------------------------------------------------------------------
df_long <- 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, sheet) |>
  tidyr::pivot_wider(names_from = sheet, values_from = value) |>
  transmute(
    date,
    `Administrations\npubliques` = APU,
    `Sociétés\n(SNF + SF)` = SNF + SF,
    `Ménages` = Menages,
    `Reste du\nmonde` = RdM
  ) |>
  tidyr::pivot_longer(-date, names_to = "sheet", values_to = "value") |>
  arrange(sheet, date)


# --- Helpers dynamiques pour libellés -----------------------------------------
# Libellé "1er/2ème/3ème/4ème trimestre YYYY" en français
fr_trim_label <- function(d) {
  q <- lubridate::quarter(d)
  y <- lubridate::year(d)
  ord <- c("1er", "2ème", "3ème", "4ème")[q]
  paste0(ord, " trimestre ", y)
}

last_date  <- max(df_long$date, na.rm = TRUE)               # ex. 2025-04-01
last_label <- fr_trim_label(last_date)                      # "2ème trimestre 2025"
start_year <- lubridate::year(min(df_long$date, na.rm = TRUE))


# Last obs per series for labels
last_pts <- df_long |>
  group_by(sheet) |>
  slice_max(order_by = date, n = 1, with_ties = FALSE) |>
  ungroup() |>
  mutate(lbl = paste0(round(value, 1), " Md€"))

# First obs per series for labels
first_pts <- df_long |>
  group_by(sheet) |>
  slice_min(order_by = date, n = 1, with_ties = FALSE) |>
  ungroup() |>
  mutate(lbl = paste0(round(value, 1), " Md€"))

# 2) Plot ----------------------------------------------------------------------
# Okabe–Ito palette (colorblind-friendly)
pal <- c(
  "Administrations\npubliques" = "#E69F00",
  "Sociétés\n(SNF + SF)"       = "#56B4E9",
  "Ménages"                    = "#009E73",
  "Reste du\nmonde"            = "#CC79A7"
)

ggplot(df_long, aes(date, value, color = sheet)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_line(linewidth = 1.1, na.rm = TRUE) +
  geom_label_repel(
    data = last_pts,
    aes(label = lbl),
    size = 3.4,
    segment.size = 0.3,
    label.padding = unit(0.15, "lines"),
    label.r = unit(0.15, "lines"),
    fill = "white",
    show.legend = FALSE
  ) +
  geom_label_repel(
    data = first_pts,
    aes(label = lbl),
    size = 3.4,
    segment.size = 0.3,
    label.padding = unit(0.15, "lines"),
    label.r = unit(0.15, "lines"),
    fill = "white",
    show.legend = FALSE
  ) +
  scale_color_manual(values = pal, NULL) +
  scale_y_continuous(
    breaks = seq(-100, 140, 10),
    labels = dollar_format(pre = "", su = "Md€", acc = 0.1)
  ) +
  scale_x_date(
    date_breaks = "1 year",
    date_labels = "%Y",
    expand = expansion(mult = c(0, 0.06))  # space for labels on the right
  ) +
  labs(
    x = NULL,
    y = "Besoin (–) ou capacité (+) de financement\nMilliards",
    title = "Capacité/Besoin de financement par secteur institutionnel",
    subtitle = paste0("Depuis ", year(min(df_long$date)), " (trimestriel)"),
    caption = paste0("Sources: Insee, comptes nationaux du ", last_label)
  ) +
  theme_minimal(base_size = 12) +
  theme(
    plot.title = element_text(face = "bold"),
    legend.position = "top",
    legend.justification = "left",
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_line(linewidth = 0.2),
    panel.grid.major.y = element_line(linewidth = 0.2),
    axis.title.y = element_text(margin = margin(r = 8))
  )

2019-

Avec label

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF") |>
  left_join(gdp_quarterly, by = "date") |>
  filter(date >= as.Date("2019-01-01")) |>
  transmute(date, value = value/gdp, sheet) |>
  spread(sheet, value) |>
  transmute(date, `Administrations\nPubliques` = `APU`, `Sociétés\n(SNF + SF)` = SNF + SF, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  gather(sheet, value, -date) |>
  arrange(desc(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(0.65, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

Sans sociétés

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF") |>
  left_join(gdp_quarterly, by = "date") |>
  filter(date >= as.Date("2019-01-01")) |>
  transmute(date, value = value/gdp, sheet) |>
  spread(sheet, value) |>
  transmute(date, `Administrations\nPubliques` = `APU`, `Ménages` = Menages, `Reste du\nMonde` = RdM) |>
  gather(sheet, value, -date) |>
  arrange(desc(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(0.65, 0.9),
        legend.title = element_blank(),
        legend.direction = "horizontal") +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label_repel(data = . %>% filter(date %in% c(max(date), min(date))),
             aes(x = date, y = value, color = sheet, label = percent(value, acc = 0.1)))

Déficit extérieur vs déficit public

% du PIB

Tous

Code

library(dplyr)
library(ggplot2)
library(scales)
# optional
# install.packages("ggrepel")
# library(ggrepel)

# 1) Préparer les données une fois pour toutes
plot_df <- t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  mutate(
    Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (balance courante)"),
    value_gdp = value / gdp
  ) |>
  select(date, value_gdp, Sheet) |>
  arrange(date)

save(plot_df, file = "~/github/GraphOftheWeek_Relecture/relecture/data/data_2026_08.rds")

# 2) Dernières observations par série (pour étiquettes)
last_pts <- plot_df |>
  group_by(Sheet) |>
  filter(date == max(date, na.rm = TRUE)) |>
  ungroup()

# 3) Palette simple et cohérente
pal <- c("Solde public" = "#1f77b4", "Solde extérieur (balance courante)" = "#ff7f0e")

# --- Helpers dynamiques pour libellés -----------------------------------------
# Libellé "1er/2ème/3ème/4ème trimestre YYYY" en français
fr_trim_label <- function(d) {
  q <- lubridate::quarter(d)
  y <- lubridate::year(d)
  ord <- c("1er", "2ème", "3ème", "4ème")[q]
  paste0(ord, " trimestre ", y)
}

last_date  <- max(plot_df$date, na.rm = TRUE)               # ex. 2025-04-01
last_label <- fr_trim_label(last_date)                      # "2ème trimestre 2025"
start_year <- lubridate::year(min(plot_df$date, na.rm = TRUE))

# 4) Le graphique
p <- ggplot(plot_df, aes(x = date, y = value_gdp, color = Sheet)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_line(linewidth = 1.1) +
  # points fin de série (pour que l’étiquette "accroche" un point)
  geom_point(data = last_pts, size = 2.2) +
  # ---- Choisir l'une des deux options d'étiquetage ----
  # (A) Sans ggrepel (base)
  geom_label(
    data = last_pts,
    aes(label = label_percent(accuracy = 0.1)(value_gdp)),
    label.padding = unit(0.15, "lines"),
    label.size = 0,
    fill = "white",
    label.r = unit(0.15, "lines"),
    vjust = -0.8,
    show.legend = FALSE
  ) +
  scale_color_manual(values = pal, guide = guide_legend(title = NULL)) +
  scale_y_continuous(
    labels = label_percent(accuracy = 1),
    breaks = seq(-0.5, 0.1, by = 0.01),  # -10% à +10% (ajustez selon vos données)
    expand = expansion(mult = c(0.02, 0.05))
  ) +
  scale_x_date(
    date_breaks = "5 years",
    date_labels = "%Y",
    expand = expansion(mult = c(0.01, 0.05))
  ) +
  labs(
    x = NULL,
    y = "% du PIB",
    title = "Solde public et solde extérieur (% du PIB)",
    subtitle = paste0("Comptes trimestriels du ", last_label),
    caption = paste0("Source : Insee, comptes du ", last_label)
  ) +
  theme_minimal(base_size = 12) +
  theme(
    legend.position = c(0.25, 0.25),   # ou 'none' si vous préférez sans légende
    panel.grid.minor = element_blank(),
    plot.title = element_text(face = "bold"),
    plot.caption = element_text(color = "gray40")
  )

p

Code

save(plot_df, file = "~/github/GraphOftheWeek_Relecture/relecture/data/data_2026_08.rda")

1970-

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  arrange(desc(date)) |>
  mutate(Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (Balance courante)"),
         value_gdp = value/gdp) |>
  filter(date >= as.Date("1970-01-01")) |>
  select(date, value_gdp, Sheet, value, gdp) |>
  ggplot() + geom_line(aes(x = date, y = value_gdp, color = Sheet)) +
  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(-100, 100, 1),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.3),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label(data = . %>% group_by(Sheet) %>% filter(date == max(date)), aes(x = date, y = value_gdp, color = Sheet, label = percent(value_gdp)))

1950-1960: De gaulle

10 août 1957 (franc Gaillard)7 : dévaluation « déguisée » de 20 % par le président du Conseil Félix Gaillard, laquelle fut légalisée en juin 1958.
En juin 1958, Charles de Gaulle valide une dévaluation de 20 %. Elle est considérée comme une réussite.
En 1958 la France se trouvait dans une situation particulièrement difficile, malgré l’ ” opération 20 % ” réalisée par M. Félix Gaillard durant l’été 1957 (dévaluation déguisée ayant pris la forme d’une prime aux exportations et d’une taxation de la plupart des importations), malgré aussi l’” opération vérité des prix ” qui tendait à réduire la consommation intérieure en augmentant les tarifs publics pour freiner l’inflation.

https://www.lemonde.fr/archives/article/1969/08/11/la-devaluation-de-1958-un-outil-contre-l-inflation-et-pour-l-ouverture-des-frontieres_2410945_1819218.html#:~:text=Le%20déficit%20budgétaire%20de%20l,(19%20millions%20de%20dollars).

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  filter(date >= as.Date("1952-01-01"),
         date <= as.Date("1964-01-01")) |>
  mutate(Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (Balance courante)")) |>
  ggplot() + geom_line(aes(x = date, y = value/gdp, color = Sheet)) +
  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(-100, 100, 1),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.73, 0.2),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label(data = . %>% filter(date %in% c(as.Date("1960-01-01"), as.Date("1957-01-01"))), aes(x = date, y = value/gdp, color = Sheet, label = percent(value/gdp)))

1970-1980: Arrivée

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  filter(date >= as.Date("1970-01-01"),
         date <= as.Date("1980-01-01")) |>
  mutate(Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (Balance courante)")) |>
  ggplot() + geom_line(aes(x = date, y = value/gdp, color = Sheet)) +
  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(-100, 100, 1),
                labels = percent_format(acc = 1)) +
  theme(legend.position = c(0.3, 0.3),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label(data = . %>% filter(date %in% c(max(date), as.Date("1976-07-01"))), aes(x = date, y = value/gdp, color = Sheet, label = percent(value/gdp)))

Sur 12 mois

Tous

Code

plot_df <- t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  group_by(sheet) |>
  mutate(value = rollsum(value, 4, fill = NA, align = "right"),
         gdp = rollsum(gdp, 4, fill = NA, align = "right")) |>
  arrange(desc(date)) |>
  mutate(Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (balance courante)"),
         value_gdp = value/gdp) |>
  select(date, value_gdp, Sheet) |>
  ungroup() |>
  add_row(date = as.Date("2025-10-01"),
          value_gdp = -0.054,
          Sheet = "Solde public",
          sheet = "APU")  |>
  arrange(desc(date),sheet)


save(plot_df, file = "~/github/GraphOftheWeek_Relecture/relecture/data/data_2026_08.rda")

plot_df |>
  ggplot() + geom_line(aes(x = date, y = value_gdp, color = Sheet)) +
  xlab("") + ylab("Capacité de financement, APU ou RdM\n% du PIB, sur 12 mois") + 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, 0.3),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label(data = . %>% group_by(Sheet) %>% filter(date == max(date)), aes(x = date, y = value_gdp, color = Sheet, label = percent(value_gdp)))

1990-

Code

t_recapAgent_val |>
  left_join(variable, by = c("sheet", "column")) |>
  filter(operation == "B9NF",
         sheet %in% c("RdM", "APU")) |>
  left_join(gdp_quarterly, by = "date") |>
  group_by(sheet) |>
  mutate(value = rollsum(value, 4, fill = NA, align = "right"),
         gdp = rollsum(gdp, 4, fill = NA, align = "right")) |>
  arrange(desc(date)) |>
  mutate(Sheet = ifelse(sheet == "APU", "Solde public", "Solde extérieur (Balance courante)"),
         value_gdp = value/gdp) |>
  select(date, value_gdp, Sheet, value, gdp) |>
  filter(date >= as.Date("1990-01-01")) |>
  ggplot() + geom_line(aes(x = date, y = value_gdp, color = Sheet)) +
  xlab("") + ylab("Capacité de financement, APU ou RdM\n% du PIB, sur 12 mois") + 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, 0.15),
        legend.title = element_blank()) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  geom_label(data = . %>% group_by(Sheet) %>% filter(date == max(date)), aes(x = date, y = value_gdp, color = Sheet, label = percent(value_gdp)))

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())