Évolution de la dépense et du pouvoir d’achat des ménages - Données annuelles de 1960 à 2023

Data - Insee

Author

François Geerolf

Info

source dataset .html .RData
insee reve-conso-evo-dep-pa 2024-10-29 2024-09-05

Données sur le pouvoir d’achat

source dataset .html .RData
insee CNA-2014-RDB 2024-11-05 2024-11-05
insee CNT-2014-CSI 2024-11-05 2024-11-05
insee conso-eff-fonction 2024-11-05 2022-06-14
insee econ-gen-revenu-dispo-pouv-achat-2 2024-11-05 2024-07-05
insee reve-conso-evo-dep-pa 2024-10-29 2024-09-05
insee reve-niv-vie-individu-activite 2024-10-29 NA
insee reve-niv-vie-pouv-achat-trim 2024-10-29 2024-09-05
insee T_7401 2024-10-18 2024-10-18
insee t_men_val 2024-10-29 2024-09-02
insee t_pouvachat_val 2024-10-29 2024-09-04
insee t_recapAgent_val 2024-10-29 2024-09-02
insee t_salaire_val 2024-11-03 2024-09-02
oecd HH_DASH 2024-09-15 2023-09-09

LAST_COMPILE

LAST_COMPILE
2024-11-05

Variable

Code 
`reve-conso-evo-dep-pa` %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional
variable Nobs
Dépense de consommation finale (en volume) 64
Pouvoir d'achat arbitrable 64
Pouvoir d'achat du RDB 64

date

Code 
`reve-conso-evo-dep-pa` %>%
  year_to_date2 %>%
  group_by(date) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(date)) %>%
  print_table_conditional

Pouvoir d’achat

1959-

Code 
`reve-conso-evo-dep-pa` %>%
  arrange(year) %>%
  add_row(year = "1959", variable = "Dépense de consommation finale (en volume)", value = NA) %>%
  add_row(year = "1959", variable = "Pouvoir d'achat du RDB", value = NA) %>%
  add_row(year = "1959", variable = "Pouvoir d'achat arbitrable", value = NA) %>%
  year_to_date2 %>%
  filter(date >= as.Date("1959-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
  ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
  xlab("") + ylab("") + theme_minimal() +
  
  scale_x_date(breaks = as.Date(paste0(seq(1959, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 1000, 100)) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = index, color = variable, label = round(index, 1)))

1990-

Code 
`reve-conso-evo-dep-pa` %>%
  year_to_date2 %>%
  filter(date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
  ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
  xlab("") + ylab("") + theme_minimal() +
  
  scale_x_date(breaks = as.Date(paste0(seq(1990, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 250, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = index, color = variable, label = round(index, 1)))

1999-

Code 
`reve-conso-evo-dep-pa` %>%
  year_to_date2 %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
  ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
  xlab("") + ylab("") + theme_minimal() +
  
  scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 150, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = index, color = variable, label = round(index, 1)))

2007-

Code 
`reve-conso-evo-dep-pa` %>%
  year_to_date2 %>%
  filter(date >= as.Date("2007-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
  ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
  xlab("") + ylab("") + theme_minimal() +
  
  scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(100, 150, 2)) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = index, color = variable, label = round(index, 1)))

2017T2-

Code 
`reve-conso-evo-dep-pa` %>%
  year_to_date2 %>%
  filter(date >= as.Date("2017-01-01")) %>%
  group_by(variable) %>%
  arrange(date) %>%
  mutate(index = c(100, 100*cumprod(1 + value[-1]/100))) %>%
  ggplot() + geom_line(aes(x = date, y = index, color = variable)) +
  xlab("") + ylab("") + theme_minimal() +
  
  scale_x_date(breaks = as.Date(paste0(seq(1999, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.85),
        legend.title = element_blank()) +
  scale_y_log10(breaks = seq(50, 150, 1)) +
  geom_label_repel(data = . %>% filter(date == max(date)),
             aes(x = date, y = index, color = variable, label = round(index, 1)))