Enquête annuelle du SGACPR sur le financement de l’habitat 2022

Data - ACPR

Author

François Geerolf

Info

source dataset .html .RData

acpr

as151

 2024-06-17 2024-04-05

Données sur l’immobilier

Code 
load_data("immobilier.RData")
immobilier %>%
  source_dataset_file_updates()
source dataset .html .RData

acpr

as151

 2024-06-17 2024-04-05

bdf

BSI1

 2024-06-18 2024-06-14

bdf

CPP

 2024-06-18 2024-06-18

bdf

FM

 2024-06-18 2024-06-18

bdf

immobilier

 2024-06-18 2024-06-18

bdf

MIR

 2024-06-18 2024-06-18

bdf

MIR1

 2024-06-18 2024-06-18

bdf

RPP

 2024-06-18 2024-06-18

insee

CONSTRUCTION-LOGEMENTS

 2024-06-19 2024-06-18

insee

ENQ-CONJ-ART-BAT

 2024-06-19 2024-06-18

insee

ENQ-CONJ-IND-BAT

 2024-06-19 2024-06-18

insee

ENQ-CONJ-PROMO-IMMO

 2024-06-19 2024-06-18

insee

ENQ-CONJ-TP

 2024-06-19 2024-06-18

insee

ILC-ILAT-ICC

 2024-06-19 2024-06-18

insee

INDICES_LOYERS

 2024-06-19 2024-06-18

insee

IPLA-IPLNA-2015

 2024-06-19 2024-06-19

insee

IRL

 2024-06-19 2024-06-19

insee

PARC-LOGEMENTS

 2024-06-19 2023-12-03

insee

SERIES_LOYERS

 2024-06-19 2024-06-19

insee

t_dpe_val

 2024-06-19 2024-03-04

notaires

arrdt

 2024-06-18 2024-06-08

notaires

dep

 2024-06-18 2024-06-07

Liens

  • Enquête sur le financement de l’habitat 2022, 24 juil. 2023. html / xlsx / pdf

Production

Code 
ig_b("acpr", "ACPR_production_2022")

Encours

Code 
ig_b("acpr", "ACPR_encours_2022")

variable

Code 
as151 %>%
  group_by(Variable, Line) %>%
  summarise(Nobs = n()) %>%
  arrange(Line) %>%
  print_table_conditional()

date

Code 
as151 %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(date)) %>%
  print_table_conditional()
date Nobs
2022-12-31 75
2021-12-31 75
2020-12-31 75
2019-12-31 75
2018-12-31 75
2017-12-31 75
2016-12-31 75
2015-12-31 75
2014-12-31 75
2013-12-31 75
2012-12-31 75
2011-12-31 75
2010-12-31 75
2009-12-31 67
2008-12-31 67
2007-12-31 67
2006-12-31 67
2005-12-31 67
2004-12-31 67
2003-12-31 67
2002-12-31 67
2001-12-31 67

Tables

2001, 2010, 2016, 2022

Code 
as151 %>%
  mutate(year = year(date)) %>%
  select(-date) %>%
  filter(year %in% c("2001", "2010", "2016", "2022")) %>%
  spread(year, value) %>%
  print_table_conditional()

2023

Code 
as151 %>%
  mutate(year = year(date)) %>%
  select(-date) %>%
  filter(year %in% c("2022")) %>%
  spread(year, value) %>%
  print_table_conditional()

Données relatives à la production (lignes 2 à 42)

Production de prêts à l’habitat en Mds€, montant du prêt moyen (K€)

Code 
as151 %>%
  filter(Line %in% c(7, 12)) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 1000*seq(0, 500, 20),
                     labels = dollar_format(acc = 1, pre = "")) +
  theme(legend.position = c(0.35, 0.9),
        legend.title = element_blank())

Production de prêts, type

Code 
as151 %>%
  filter(Line %in% 8:10) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank())

Montant du pret moyen

Code 
as151 %>%
  
  filter(Line %in% 14:18) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 1000*seq(0, 500, 20),
                     labels = dollar_format(acc = 1, pre = "", su = "€")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank())

Durée moyenne des prêts

Code 
as151 %>%
  
  filter(Line == 31) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  xlab("") + ylab("Durée moyenne des prêts") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 1),
                     labels = dollar_format(a = 1, su = " ans", pre = ""))

Taux variables vs fixes

Code 
as151 %>%
  
  filter(Line %in% c(24, 28)) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 10),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.8, 0.6),
        legend.title = element_blank())

Taux d’endettement moyen des emprunteurs à l’octroi

Code 
as151 %>%
  
  filter(Line == 47) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  
  xlab("") + ylab("Taux d'endettement moyen des emprunteurs à l'octroi") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, .2),
                     labels = dollar_format(a = .1, su = " ans", pre = ""))

Taux d’apport - Evolution

LTV moyenne à l’octroi

Code 
as151 %>%
  
  filter(Line == 41) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  xlab("") + ylab("Taux d'effort moyen (%)") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = percent_format(a = 1))

Tranches

Classique

Code 
as151 %>%
  
  filter(Line %in% 42:45) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Taux d'apport (%)") +
  
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.8, 0.9),
        legend.title = element_blank())

Joli

Code 
as151 %>%
  
  filter(Line %in% 42:45) %>%
  ggplot + geom_line(aes(x = date, y = value, color = paste0(Line))) +
  annotate("text", x = as.Date("2006-12-31"), y = 0.55, label= "Apport > 15% ", color = viridis(5)[1]) + 
  annotate("text", x = as.Date("2016-12-31"), y = 0.17, label= "5% < Apport < 15%", color = viridis(5)[2]) + 
  annotate("text", x = as.Date("2015-12-31"), y = 0.27, label= "0% < Apport < 5%", color = viridis(5)[3]) + 
  annotate("text", x = as.Date("2017-12-31"), y = 0.08, label= "Apport < 0% ", color = viridis(5)[4]) + 
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none")

Taux d’effort

Taux d’effort moyen

Code 
as151 %>%
  
  filter(Line == 34) %>%
  ggplot + geom_line(aes(x = date, y = value)) +
  
  xlab("") + ylab("Taux d'effort moyen (%)") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = percent_format(a = 1))

Tranches

Code 
as151 %>%
  
  filter(Line %in% c(35:38)) %>%
  mutate(Variable = factor(Variable, 
                           levels=c("Taux d'effort < 20%",
                                    "20% < Taux d'effort < 30%",
                                    "30% < Taux d'effort ≤ 35%",
                                    "Taux d'effort > 35%"))) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank())

Tranches

Code 
as151 %>%
  
  filter(Line %in% c(35:38)) %>%
  mutate(Variable = factor(Variable, 
                           levels=c("Taux d'effort < 20%",
                                    "20% < Taux d'effort < 30%",
                                    "30% < Taux d'effort ≤ 35%",
                                    "Taux d'effort > 35%"))) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  theme_minimal() + xlab("") + ylab("Part des emprunteurs (%)") +
  
  scale_y_continuous(breaks = 0.01*seq(0, 100, 5),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.5, 0.9),
        legend.title = element_blank())

Données relatives à la production (lignes 44 à 110)

Poids des douteux dans l’encours

Taux variables vs fixes

Code 
as151 %>%
  
  filter(Line %in% c(96, 97, 88)) %>%
  filter(value >0) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank())

Production vs encours

Durée moyenne des prêts VS résiduelle moyenne

Code 
as151 %>%
  
  filter(date >= as.Date("2010-01-01")) %>%
  filter(Line %in% c(31, 69)) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("Durée moyenne des prêts, maturité résiduelle") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 1),
                     labels = dollar_format(a = 1, su = " ans", pre = "")) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

LTV

Code 
as151 %>%
  
  filter(date >= as.Date("2010-01-01")) %>%
  filter(Line %in% c(41,67)) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("LTV") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())

Prêts taux fixes

Code 
as151 %>%
  
  filter(date >= as.Date("2010-01-01")) %>%
  filter(Line %in% c(28,64)) %>%
  ggplot + geom_line(aes(x = date, y = value, color = Variable)) +
  xlab("") + ylab("Prêts à taux fixe (encours), produits à taux fixe (production)") + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = percent_format(a = 1)) +
  theme(legend.position = c(0.3, 0.9),
        legend.title = element_blank())