Residential Property Price Index Statistics - RPP
Data - ECB
Last observation: Q1 2019 (N = 4) · H2 2018 (N = 24) · sept. 2018 (N = 7) · 2018 (N = 79)
First observation: 1970 (N = 1) · Q1 1970 (N = 1) · H1 1970 (N = 1) · janv. 2005 (N = 7)
Last data update: 01 sept. 2026, 03:45
Last compile: 02 sept. 2026, 23:39
Structure
| source | dataset | .html | .qmd | .RData |
|---|---|---|---|---|
| ecb | RPP | 2026-09-01 | 2026-09-02 | NA |
Data on housing
| source | dataset | Title | Updated |
|---|---|---|---|
bdf |
RPP | Prix de l'immobilier - RPP | 2026-08-28 |
ecb |
RPP | Residential Property Price Index Statistics - RPP | 2026-09-01 |
bis |
LONG_PP | Residential property prices - detailed series - LONG_PP | 2026-08-31 |
bis |
SELECTED_PP | Property prices, selected series - SELECTED_PP | 2026-08-31 |
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 | 2026-09-01 |
oecd |
SNA_TABLE5 | Final consumption expenditure of households - SNA_TABLE5 | 2026-08-02 |
oecd |
housing | NA | NA |
Last
| TIME_PERIOD | FREQ | Nobs |
|---|---|---|
| 2018 | A | 79 |
| 2018-09 | M | 7 |
| 2018-S2 | H | 24 |
| 2019-Q1 | Q | 4 |
REF_AREA
Code
RPP |>
group_by(REF_AREA, Ref_area) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}TIME_PERIOD
Code
RPP |>
group_by(TIME_PERIOD) |>
summarise(Nobs = n()) |>
arrange(desc(TIME_PERIOD)) |>
print_table_conditional()




