Emission et détention de titres - France - SC1

Données - BDF

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LAST_DOWNLOAD
NA

LAST_COMPILE

LAST_COMPILE
2026-07-24

Last

date	Nobs
2026-05-31	73

Encours de titres de dette par secteur émetteur

Depuis 2008

Code

SC1 %>%
  
  filter(REF_AREA == "FR",
         SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
         SEC_ITEM == "F33000",
         DATA_TYPE_SEC == "1",
         CURRENCY == "Z01",
         SERIES_DENOM == "E",
         SEC_SUFFIX == "Z",
         FREQ == "Q") %>%
  mutate(Secteur = recode(SEC_ISSUING_SECTOR,
                           "100Z" = "Ensemble des résidents",
                           "1100" = "Sociétés non financières",
                           "122Z" = "Établissements de crédit",
                           "123Z" = "Autres organismes financiers",
                           "1300" = "Administrations publiques")) %>%
  arrange(date) %>%
  ggplot(.) + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
  theme_minimal() + xlab("") + ylab("Md €") +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
  theme(legend.position = c(0.25, 0.75),
        legend.title = element_blank())

5 dernières années

Code

SC1 %>%
  
  filter(REF_AREA == "FR",
         SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
         SEC_ITEM == "F33000",
         DATA_TYPE_SEC == "1",
         CURRENCY == "Z01",
         SERIES_DENOM == "E",
         SEC_SUFFIX == "Z",
         FREQ == "Q") %>%
  filter(date >= Sys.Date() - years(5)) %>%
  mutate(Secteur = recode(SEC_ISSUING_SECTOR,
                           "100Z" = "Ensemble des résidents",
                           "1100" = "Sociétés non financières",
                           "122Z" = "Établissements de crédit",
                           "123Z" = "Autres organismes financiers",
                           "1300" = "Administrations publiques")) %>%
  arrange(date) %>%
  ggplot(.) + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
  theme_minimal() + xlab("") + ylab("Md €") +
  scale_x_date(breaks = "6 months",
               labels = date_format("%b %Y")) +
  scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
  theme(legend.position = c(0.25, 0.75),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))

Emissions nettes de titres de dette (cumul 12 mois)

Code

SC1 %>%
  
  filter(REF_AREA == "FR",
         SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
         SEC_ITEM == "F33000",
         DATA_TYPE_SEC == "4",
         CURRENCY == "Z01",
         SERIES_DENOM == "M",
         SEC_SUFFIX == "Z",
         FREQ == "M") %>%
  mutate(Secteur = recode(SEC_ISSUING_SECTOR,
                           "100Z" = "Ensemble des résidents",
                           "1100" = "Sociétés non financières",
                           "122Z" = "Établissements de crédit",
                           "123Z" = "Autres organismes financiers",
                           "1300" = "Administrations publiques")) %>%
  arrange(date) %>%
  ggplot(.) + geom_line(aes(x = date, y = value / 1000, color = Secteur)) +
  theme_minimal() + xlab("") + ylab("Cumul sur 12 mois, Md €") +
  scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(labels = dollar_format(prefix = "", suffix = " Md€")) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black") +
  theme(legend.position = c(0.25, 0.8),
        legend.title = element_blank())

Encours par secteur - dernière période

Code

SC1 %>%
  
  filter(REF_AREA == "FR",
         SEC_ISSUING_SECTOR %in% c("100Z", "1100", "122Z", "123Z", "1300"),
         SEC_ITEM == "F33000",
         DATA_TYPE_SEC == "1",
         CURRENCY == "Z01",
         SERIES_DENOM == "E",
         SEC_SUFFIX == "Z",
         FREQ == "Q") %>%
  mutate(Secteur = recode(SEC_ISSUING_SECTOR,
                           "100Z" = "Ensemble des résidents",
                           "1100" = "Sociétés non financières",
                           "122Z" = "Établissements de crédit",
                           "123Z" = "Autres organismes financiers",
                           "1300" = "Administrations publiques")) %>%
  filter(date == max(date)) %>%
  transmute(Secteur, `Encours (Md €)` = round(value / 1000, 1), Date = date) %>%
  arrange(desc(`Encours (Md €)`)) %>%
  print_table_conditional()

Secteur	Encours (Md €)	Date
Ensemble des résidents	5748.5	2026-03-31
Administrations publiques	3138.3	2026-03-31
Établissements de crédit	1506.0	2026-03-31
Sociétés non financières	742.3	2026-03-31
Autres organismes financiers	361.9	2026-03-31