Institut des Politiques Publiques

Data

List of Main Datasets

Javascript

Flat

tibble(id = list.files(pattern = "\\.qmd$") %>% gsub(".qmd$", "", .)) %>%
  filter(!(id == "index")) %>%
  mutate(Title = read_lines(paste0(id, ".qmd"), skip = 1, n_max = 1) %>% gsub("title: ", "", .),
         `.RData` = as.Date(file.info(paste0("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/ipp/", id, ".RData"))$mtime),
         `.html` = as.Date(file.info(paste0("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/ipp/", id, ".html"))$mtime)) %>%
  {if (is_html_output()) mutate(., `.html` = paste0("[", `.html`, "](https://fgeerolf.com/data/ipp/",id, ".html)")) else .} %>%
  {if (is_html_output()) print_table(.) else .}

id	Title	.RData	.html
bareme_ir	Barême de l'Impôt sur le Revenu	2024-02-11	[2024-02-11]
crds	Contribution au remboursement de la dette sociale (CRDS) (depuis 1996)	2024-02-11	[2024-02-11]
indicefp	Point d'indice de la fonction publique	2024-09-15	[2024-09-15]
marche-du-travail	Marché du travail	NA	[2023-09-16]
prelevements-sociaux	Prestations sociales	NA	[2023-09-16]
prestations-sociales	Prestations sociales	NA	[2023-09-16]
regimes-de-retraite	Régimes de retraite	NA	[2024-09-15]
ret_etat	"Contribution employeur à la charge de l'Etat"	2024-04-21	[2024-04-20]
revalorisation_pension	Revalorisation du Régime général de la caisse nationale d'assurance vieillesse (CNAV)	2024-09-15	[2024-09-15]
taux_de_tva	Contribution au remboursement de la dette sociale (CRDS) (depuis 1996)	2022-01-13	[NA](https:/

List of All Datasets

Javascript

Prestations sociales

RMI / RSA

Montant en €

ig_d("ipp", "prestations-sociales", "rmi-rsa")

RMI / RSA

ig_d("ipp", "prestations-sociales", "rmi-rsa-base-100")

Taux de TVA (1954-2014)

taux_de_tva %>%
  select(1:5) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

taux_de_tva %>%
  select(date, taux_reduit, taux_normal) %>%
  arrange(date) %>%
  add_row(date = Sys.Date(), taux_reduit = last(.[[2]]), taux_normal = last(.[[3]])) %>%
  complete(date = seq.Date(min(date), max(date), by = "day")) %>%
  fill(taux_normal, taux_reduit) %>%
  gather(variable, value, -date) %>%
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.65, 0.6),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 50, 1),
                     labels = percent_format(accuracy = 1)) + 
  ylab("Tax Rate (%)") + xlab("")

Taux tabac

taux_normaux_tabac %>%
  select(-date_parution_jo, -reference) %>%
  slice(1, c(1:n())) %>%
  mutate(date = ifelse(row_number() == 1, as.Date(Sys.Date()), date),
         date = as.Date(date)) %>%
  gather(variable, value, -date) %>%
  group_by(variable) %>%
  complete(date = seq.Date(min(date), max(date), by = "day")) %>%
  fill(value) %>%
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 80, 5),
                     labels = percent_format(accuracy = 1),
                     limits = c(0, 0.65)) + 
  ylab("Taux normaux tabacs (%)") + xlab("")

Taux supérieur d’IR

ig_d("ipp", "bareme_ir", "tranches-superieures")

IS

societe_taux_reduit %>%
  full_join(societe_taux_normal, by = "date") %>%
  full_join(societe_taux_intermediaire, by = "date") %>%
  gather(variable, value, -date) %>%
  group_by(variable) %>%
  complete(date = seq.Date(min(date), max(date), by = "day")) %>%
  fill(value) %>%
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.65, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 80, 5),
                     labels = percent_format(accuracy = 1),
                     limits = c(0, 0.6)) + 
  ylab("Impôt sur les Sociétés (%)") + xlab("")

CSG - Activité

csg_activite %>%
  select(-date_parution_jo, -reference, -notes) %>%
  gather(variable, value, -date) %>%
  group_by(variable) %>%
  complete(date = seq.Date(min(date), max(date), by = "day")) %>%
  fill(value) %>%
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 80, 1),
                     labels = percent_format(accuracy = 1)) + 
  ylab("CSG Activité (%)") + xlab("")

CRDS

ig_d("ipp", "crds", "crds")

Indice Fonction Publique

All

Valeur

ig_d("ipp", "indicefp", "indicefp")

Base 100

ig_d("ipp", "indicefp", "indicefp-base-100")

1990-

Valeur

ig_d("ipp", "indicefp", "indicefp-1990")

Base 100

ig_d("ipp", "indicefp", "indicefp-1990-base-100")

1992-

Valeur

ig_d("ipp", "indicefp", "indicefp-1992")

Base 100

ig_d("ipp", "indicefp", "indicefp-1992-base-100")

Revalorisation des pensions

En réel

ig_d("ipp", "revalorisation_pension", "reval-1999-reel")

Comparaison avec Indice FP

ig_d("ipp", "revalorisation_pension", "merge-indicefp")

Famille

famille %>%
  select(-date_parution_jo, -reference, -notes) %>%
  gather(variable, value, -date) %>%
  group_by(variable) %>%
  complete(date = seq.Date(min(date), max(date), by = "day")) %>%
  fill(value) %>%
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) +
  
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = c(0.3, 0.8),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 80, 1),
                     labels = percent_format(accuracy = 0.1)) + 
  ylab("Cotisation Famille (%)") + xlab("")