| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| insee | DEFAILLANCES-ENTREPRISES | Défaillances d’entreprises | 2025-12-25 | 2025-12-27 |
| bdf | DIREN | Observatoire des Entreprises | 2025-12-24 | 2025-04-29 |
| eurostat | sts_rb_q | Business registration and bankruptcy index by NACE Rev.2 activity - quarterly data - sts_rb_q | 2025-12-25 | 2025-12-27 |
Défaillances d’entreprises
Data - INSEE
Info
LAST_UPDATE
LAST_DOWNLOAD
| dataset | LAST_DOWNLOAD |
|---|---|
| DEFAILLANCES-ENTREPRISES | 2025-12-27 14:02:08 |
| 2025-02-04 14:34:02 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2025-12-27 |
TITLE_FR
Code
`DEFAILLANCES-ENTREPRISES` %>%
group_by(IDBANK, TITLE_FR) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}CORRECTION
Code
`DEFAILLANCES-ENTREPRISES` %>%
group_by(CORRECTION) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| CORRECTION | Nobs |
|---|---|
| BRUT | 157492 |
| CVS-CJO | 5160 |
| RECALAGE | 42 |
FREQ
Code
`DEFAILLANCES-ENTREPRISES` %>%
left_join(FREQ, by = "FREQ") %>%
group_by(FREQ, Freq) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| FREQ | Freq | Nobs |
|---|---|---|
| M | Monthly | 122612 |
| T | NA | 40040 |
| A | Annual | 42 |
ACTIVITE_CREAT_ENT
Code
`DEFAILLANCES-ENTREPRISES` %>%
left_join(ACTIVITE_CREAT_ENT, by = "ACTIVITE_CREAT_ENT") %>%
group_by(ACTIVITE_CREAT_ENT, Activite_creat_ent) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
{if (is_html_output()) print_table(.) else .}| ACTIVITE_CREAT_ENT | Activite_creat_ent | Nobs |
|---|---|---|
| ENS | Ensemble | 65113 |
| AZ | A10 AZ - Agriculture, sylviculture et pêche | 8871 |
| BE | A10 BE - Industrie | 8871 |
| FZ | A10 FZ - Construction | 8871 |
| G | A21 G - Commerce et réparation automobile | 8871 |
| H | A21 H - Transports | 8871 |
| I | A21 I - Hébergement, restauration | 8871 |
| JZ | A10 JZ - Information et communication | 8871 |
| KZ | A10 KZ - Activités financières et d'assurance | 8871 |
| LZ | A10 LZ - Activités immobilières | 8871 |
| MN | A10 MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien | 8871 |
| PQS | A21 P à S - Enseignement, santé humaine, action sociale et services aux ménages | 8871 |
REF_AREA
Code
`DEFAILLANCES-ENTREPRISES` %>%
group_by(REF_AREA) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()TIME_PERIOD
Code
`DEFAILLANCES-ENTREPRISES` %>%
group_by(TIME_PERIOD) %>%
summarise(Nobs = n()) %>%
arrange(desc(TIME_PERIOD)) %>%
print_table_conditional()Défaillances
2017, Juillet 2021
Code
`DEFAILLANCES-ENTREPRISES` %>%
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
TIME_PERIOD %in% c("2017-01", "2021-06"),
CORRECTION == "CVS-CJO",
FREQ == "M") %>%
left_join(ACTIVITE_CREAT_ENT, by = "ACTIVITE_CREAT_ENT") %>%
select(TIME_PERIOD, ACTIVITE_CREAT_ENT, Activite_creat_ent, OBS_VALUE) %>%
spread(TIME_PERIOD, OBS_VALUE) %>%
mutate(Croissance = round(100*(`2021-06`/`2017-01`-1), 1)) %>%
arrange(Croissance) %>%
print_table_conditional()| ACTIVITE_CREAT_ENT | Activite_creat_ent | 2017-01 | 2021-06 | Croissance |
|---|---|---|---|---|
| I | A21 I - Hébergement, restauration | 607 | 179 | -70.5 |
| PQS | A21 P à S - Enseignement, santé humaine, action sociale et services aux ménages | 444 | 137 | -69.1 |
| BE | A10 BE - Industrie | 334 | 127 | -62.0 |
| FZ | A10 FZ - Construction | 1013 | 455 | -55.1 |
| ENS | Ensemble | 4622 | 2117 | -54.2 |
| G | A21 G - Commerce et réparation automobile | 1047 | 487 | -53.5 |
| MN | A10 MN - Activités spécialisées, scientifiques et techniques et activités de services administratifs et de soutien | 498 | 277 | -44.4 |
| JZ | A10 JZ - Information et communication | 109 | 62 | -43.1 |
| H | A21 H - Transports | 152 | 92 | -39.5 |
| KZ | A10 KZ - Activités financières et d'assurance | 98 | 62 | -36.7 |
| AZ | A10 AZ - Agriculture, sylviculture et pêche | 129 | 100 | -22.5 |
| LZ | A10 LZ - Activités immobilières | 150 | 127 | -15.3 |
ENS, BE, AZ
Niveaux
Code
`DEFAILLANCES-ENTREPRISES` %>%
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
ACTIVITE_CREAT_ENT %in% c("ENS", "BE", "AZ"),
CORRECTION == "CVS-CJO",
FREQ == "M") %>%
month_to_date %>%
left_join(ACTIVITE_CREAT_ENT, by = "ACTIVITE_CREAT_ENT") %>%
ggplot() + ylab("Défaillances d'entreprises") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Activite_creat_ent)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.25, 0.8),
legend.title = element_blank()) +
scale_y_log10(breaks = c(100, 200, 300, 500, 800, 10, 20, 30, 50, 1000, 2000, 3000, 5000, 10000),
labels = dollar_format(accuracy = 1, prefix = ""))
100
Code
`DEFAILLANCES-ENTREPRISES` %>%
filter(REF_AREA == "FE",
NATURE == "VALEUR_ABSOLUE",
ACTIVITE_CREAT_ENT %in% c("ENS", "BE", "AZ"),
CORRECTION == "CVS-CJO",
FREQ == "M") %>%
month_to_date %>%
filter(date >= as.Date("2017-01-01")) %>%
left_join(ACTIVITE_CREAT_ENT, by = "ACTIVITE_CREAT_ENT") %>%
group_by(ACTIVITE_CREAT_ENT) %>%
mutate(OBS_VALUE = 100*OBS_VALUE/OBS_VALUE[date == as.Date("2017-01-01")]) %>%
ggplot() + ylab("Défaillances d'entreprises (100 = 2017)") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = OBS_VALUE, color = Activite_creat_ent)) +
scale_color_manual(values = viridis(4)[1:3]) +
scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
theme(legend.position = c(0.25, 0.2),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(10, 200, 10),
labels = dollar_format(accuracy = 1, prefix = ""))