House price index - Item weights - prc_hpi_inw

Data - Eurostat

Info

Last observation: Annual: 2026 (N = 102)

First observation: Annual: 2005 (N = 31)

Last data update: 23 jul 2026, 22:09. Last compile: 24 jul 2026, 03:44

Structure

freq

purchase

geo

France, Germany, Spain, Italy

Weight of New Dwellings in the House Price Index

prc_hpi_inw %>%
  filter(geo %in% c("FR", "DE", "ES", "IT"),
         purchase == "DW_NEW") %>%
  year_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values/1000) %>%
  ggplot + geom_line(aes(x = date, y = values, color = color)) +
  theme_minimal() + scale_color_identity() + add_4flags +
  scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Weight of newly built dwellings in the HPI") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1))

France

New vs. Existing Dwellings

prc_hpi_inw %>%
  filter(geo == "FR",
         purchase %in% c("DW_NEW", "DW_EXST")) %>%
  year_to_date %>%
  mutate(values = values/1000) %>%
  ggplot + geom_line(aes(x = date, y = values, color = Purchase)) +
  theme_minimal() +
  theme(legend.position = c(0.5, 0.5),
        legend.title = element_blank()) +
  scale_x_date(breaks = as.Date(paste0(seq(2005, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  xlab("") + ylab("Weight in the House Price Index") +
  scale_y_continuous(labels = scales::percent_format(accuracy = 1))

Table

png

Javascript

prc_hpi_inw %>%
  filter(time == "2020") %>%
  
  mutate(values = round(values),
         Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  select(geo, Geo, purchase, values) %>%
  spread(purchase, values) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}