Final consumption expenditure of households - SNA_TABLE5

Name: Final consumption expenditure of households
Creator: François Geerolf
License: https://creativecommons.org/licenses/by/4.0/

Data - OECD

Author

François Geerolf

Last observation: 2022 (N = 8179)

First observation: 1950 (N = 4)

Last data update: 02 août 2026, 09:10

Last compile: 05 sept. 2026, 04:01

Structure

Layout - By country

OECD Website. html

United States

France

Nobs - TRANSACT, MEASURE

Code

SNA_TABLE5 |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  group_by(TRANSACT, Transact, MEASURE) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()

obsTime

Code

SNA_TABLE5 |>
  group_by(obsTime) |>
  summarise(Nobs = n()) |>
  arrange(desc(obsTime)) |>
  print_table_conditional()

France, Germany, United Kingdom, United States

% of GDP

Code

SNA_TABLE5 |>
  filter(LOCATION %in% c("FRA", "DEU", "USA", "GBR"),
         obsTime == "2017",
         MEASURE == "C") |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  select(Location, TRANSACT, Transact, obsValue) |>
  mutate(Location = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Location = paste0('<img src="../../icon/flag/vsmall/', Location, '.png" alt="Flag">')) |>
  spread(Location, obsValue) %>%
  mutate_at(vars(-1, -2), funs(round(100*./.[TRANSACT == "B1_GE"], 1))) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

% of Consumption

Code

SNA_TABLE5 |>
  filter(LOCATION %in% c("FRA", "DEU", "USA", "GBR"),
         obsTime == "2017",
         MEASURE == "C") |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  select(Location, TRANSACT, Transact, obsValue) |>
  mutate(Location = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Location = paste0('<img src="../../icon/flag/vsmall/', Location, '.png" alt="Flag">')) |>
  spread(Location, obsValue) %>%
  mutate_at(vars(-1, -2), funs(round(100*./.[TRANSACT == "P31DC"], 1))) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Housing

% of Consumption, % of GDP

Code

SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31DC", "P31CP040"),
         obsTime == "2017",
         MEASURE == "C") |>
  arrange(LOCATION, TRANSACT) |>
  select(LOCATION, TRANSACT, obsValue) |>
  spread(TRANSACT, obsValue) |>
  left_join(SNA_TABLE1 |>
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C",
                     obsTime == "2017") |>
              select(LOCATION, B1_GE = obsValue), 
            by = c("LOCATION")) |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  transmute(Flag,
            LOCATION,
            Location,
            `Housing (% of Consumption)` = (100*P31CP040 / P31DC) |> round(digits = 1),
            `Housing (% of GDP)` = (100*P31CP040 / B1_GE) |> round(digits = 1)) |>
  arrange(-`Housing (% of Consumption)`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

% of Consumption

Code

SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31DC", "P31CP040", "P31CP041", "P31CP042"),
         obsTime == "2018",
         MEASURE == "C") |>
  arrange(LOCATION, TRANSACT) |>
  select(LOCATION, TRANSACT, obsValue) |>
  spread(TRANSACT, obsValue) |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  transmute(Flag,
            LOCATION,
            Location,
            `Housing` = (100*P31CP040 / P31DC) |> round(digits = 1),
            `Rents (Actual)` = (100*P31CP041 / P31DC) |> round(digits = 1),
            `Rents (Implicit)` = (100*P31CP042 / P31DC) |> round(digits = 1)) |>
  arrange(-Housing) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Food, Health, Housing, Restaurant

Code

SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31CP010", "P31DC", "P31CP040", "P31CP060", "P31CP110"),
         obsTime == "2017",
         MEASURE == "C") |>
  arrange(LOCATION, TRANSACT) |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, Location, TRANSACT, obsValue) |>
  spread(TRANSACT, obsValue) |>
  group_by(Flag, Location) |>
  summarise(`Food` = (100*P31CP010 / P31DC) |> round(digits = 1),
            `Housing` = (100*P31CP040 / P31DC) |> round(digits = 1),
            `Health` = (100*P31CP060 / P31DC) |> round(digits = 1),
            `Restaurant` = (100*P31CP110 / P31DC) |> round(digits = 1)) |>
  na.omit() %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Implicit / real Rents

Table 1

Code

library(gt)
library(gtExtras)
#devtools::install_github("rstudio/gt")
countrypops_new <- countrypops |>
  select(LOCATION = country_code_3, LOCATION_2digit = country_code_2) |>
  unique()
table1 <- SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31CP042", "P31DC", "P31CP041"),
         MEASURE == "C",
         obsTime == "2019") |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  group_by(LOCATION) |>
  mutate(values = 100*obsValue /obsValue[TRANSACT == "P31DC"]) |>
  filter(TRANSACT != "P31DC") |>
  mutate(Location = case_when(LOCATION == "EA19" ~ "Euro Area (19)",
                              LOCATION == "EA27" ~ "Europe (27)",
                              T ~ Location)) |>
  left_join(countrypops_new, by = "LOCATION") |>
  mutate(LOCATION_2digit = case_when(LOCATION == "EA19" ~ "EU",
                                     LOCATION == "EA27" ~ "EU",
                              T ~ LOCATION_2digit)) |>
  ungroup() |>
  select(Location, LOCATION_2digit, Transact, values) |>
  spread(Transact, values) |>
  transmute(LOCATION_2digit, Location,
            `Actual rents` = `Actual rentals for housing`,
            `Imputed rents` = `Imputed rentals for housing`,
            `All rents` = `Actual rentals for housing` + `Imputed rentals for housing`) |>
  gt() |>
  fmt_number(columns = 3:5 , locale = "fr", decimals = 1, pattern = "{x}%") |>
  cols_align(align = "center", columns = 3:5) |> 
  fmt_flag(columns = LOCATION_2digit, height = "1.5em") |>
  cols_width(3:5 ~ px(50)) |> 
  gt_theme_538()


gtsave(table1, filename = "SNA_TABLE5_files/figure-html/table1.png")
i_g("data/oecd/SNA_TABLE5_files/figure-html/table1.png")

France, Germany, US

Code

SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31CP042", "P31DC", "P31CP041"),
         MEASURE == "C",
         LOCATION %in% c("FRA", "DEU", "USA")) |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  year_to_date() |>
  group_by(date, LOCATION) |>
  mutate(obsValue = obsValue /obsValue[TRANSACT == "P31DC"]) |>
  filter(TRANSACT != "P31DC") |>
  add_flag_color("Location") |>
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color, linetype = Transact)) + 
  scale_color_identity() + add_6flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-7, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  ylab("Rentals (% of Consumption)") + xlab("")

Italy, Spain, Netherlands

Code

SNA_TABLE5 |>
  filter(TRANSACT %in% c("P31CP042", "P31DC", "P31CP041"),
         MEASURE == "C",
         LOCATION %in% c("ITA", "ESP", "NLD")) |>
  left_join(SNA_TABLE5_var$LOCATION, by = "LOCATION") |>
  left_join(SNA_TABLE5_var$TRANSACT, by = "TRANSACT") |>
  year_to_date() |>
  group_by(date, LOCATION) |>
  mutate(obsValue = obsValue /obsValue[TRANSACT == "P31DC"]) |>
  filter(TRANSACT != "P31DC") |>
  add_flag_color("Location") |>
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color, linetype = Transact)) + 
  scale_color_identity() + add_6flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-7, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  theme(legend.position = c(0.2, 0.9),
        legend.title = element_blank()) +
  ylab("Rentals (% of Consumption)") + xlab("")

Related Data

Data on housing

source	dataset	Title	Updated
bdf	RPP	Prix de l'immobilier - RPP	2026-09-03
bis	LONG_PP	Residential property prices - detailed series - LONG_PP	2026-09-03
bis	SELECTED_PP	Property prices, selected series - SELECTED_PP	2026-09-03
ecb	RPP	Residential Property Price Index Statistics - RPP	2026-09-03
eurostat	ei_hppi_q	House price index (2015 = 100) - quarterly data - ei_hppi_q	2026-07-15
eurostat	hbs_str_t223	Mean consumption expenditure by income quintile - hbs_str_t223	2026-07-15
eurostat	prc_hicp_midx	HICP (2015 = 100) - monthly data (index) - prc_hicp_midx	2026-08-07
eurostat	prc_hpi_q	House price index (2015 = 100) - quarterly data - prc_hpi_q	2026-07-14
fred	housing	House Prices - housing	2026-09-01
insee	IPLA-IPLNA-2015	Indices des prix des logements neufs et Indices Notaires-Insee des prix des logements anciens - IPLA-IPLNA-2015	2026-09-04
oecd	SNA_TABLE5	Final consumption expenditure of households - SNA_TABLE5	2026-08-02
oecd	housing	NA	NA