source | dataset | .html | .RData |
---|---|---|---|
eurostat | prc_hpi_ooq | 2024-11-05 | 2024-10-09 |
Owner-occupied housing price index (2015=100) - quarterly data
Data - Eurostat
Info
Data on housing
source | dataset | .html | .RData |
---|---|---|---|
bdf | RPP | 2024-11-19 | 2024-11-19 |
bis | LONG_PP | 2024-08-09 | 2024-05-10 |
bis | SELECTED_PP | 2024-10-31 | 2024-10-31 |
ecb | RPP | 2024-10-08 | 2024-10-30 |
eurostat | ei_hppi_q | 2024-11-21 | 2024-11-21 |
eurostat | hbs_str_t223 | 2024-11-08 | 2024-11-21 |
eurostat | prc_hicp_midx | 2024-11-01 | 2024-11-21 |
eurostat | prc_hpi_q | 2024-11-05 | 2024-10-09 |
fred | housing | 2024-11-22 | 2024-11-22 |
insee | IPLA-IPLNA-2015 | 2024-11-09 | 2024-11-22 |
oecd | housing | 2024-09-15 | 2020-01-18 |
oecd | SNA_TABLE5 | 2024-09-11 | 2023-10-19 |
Last
Code
%>%
prc_hpi_ooq group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(3) %>%
print_table_conditional()
time | Nobs |
---|---|
2024Q2 | 1279 |
2024Q1 | 1278 |
2023Q4 | 1277 |
expend
Code
%>%
prc_hpi_ooq left_join(expend, by = "expend") %>%
group_by(expend, Expend) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
expend | Expend | Nobs |
---|---|---|
DW_ACQ_NEW | New dwellings | 8318 |
TOTAL | Total | 8318 |
DW_ACQ | Acquisitions of dwellings | 8313 |
DW_ACQ_OTH | Other services related to the acquisition of dwellings | 8270 |
DW_OWN | Ownership of dwellings | 8265 |
DW_ACQ_NEWP | Purchases of newly built dwellings | 8224 |
DW_OWN_RMNT | Major repairs and maintenance | 8203 |
DW_OWN_INS | Insurance connected with dwellings | 7828 |
DW_ACQ_NEWSB | Self-build dwellings and major renovations | 7549 |
DW_ACQ_EXST | Existing dwellings new to the households | 3776 |
DW_OWN_OTH | Other services related to ownership of dwellings | 3012 |
unit
Code
%>%
prc_hpi_ooq left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
unit | Unit | Nobs |
---|---|---|
I15_Q | Quarterly index, 2015=100 | 20510 |
I10_Q | Quarterly index, 2010=100 | 20220 |
RCH_Q | Quarterly rate of change | 20176 |
RCH_A | Annual rate of change | 19170 |
geo
Code
%>%
prc_hpi_ooq left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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
Code
%>%
prc_hpi_ooq group_by(time) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Greece, Europe, France, Spain, Italy, Germany
Purchase Total
Code
%>%
prc_hpi_ooq filter(expend == "TOTAL",
%in% c("EL", "FR", "ES", "IT", "DE"),
geo == "I15_Q") %>%
unit %>%
quarter_to_date group_by(geo) %>%
mutate(values = 100*values/values[date == as.Date("2011-01-01")]) %>%
filter(date >= as.Date("2009-01-01"),
<= as.Date("2016-01-01")) %>%
date left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = Geo)) +
theme_minimal() + xlab("") + ylab("100 = Janv. 2011") +
scale_x_date(breaks = seq(1960, 2021, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_color_manual(values = c("#ED2939", "#000000", "#009246", "#FFC400")) + add_4flags +
scale_y_log10(breaks = seq(0, 200, 5)) +
theme(legend.position = "none",
legend.title = element_blank())
Acquisitions of dwellings - DW_ACQ
Code
%>%
prc_hpi_ooq filter(expend == "DW_ACQ",
%in% c("EL", "FR", "ES", "IT", "DE"),
geo == "I15_Q") %>%
unit %>%
quarter_to_date group_by(geo) %>%
mutate(values = 100*values/values[date == as.Date("2011-01-01")]) %>%
filter(date >= as.Date("2009-01-01"),
<= as.Date("2016-01-01")) %>%
date left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = Geo)) +
theme_minimal() + xlab("") + ylab("100 = Janv. 2011") +
scale_x_date(breaks = seq(1960, 2021, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
scale_color_manual(values = c("#ED2939", "#000000", "#009246", "#FFC400")) + add_4flags +
scale_y_log10(breaks = seq(0, 200, 5)) +
theme(legend.position = "none",
legend.title = element_blank())
Ownership of new dwellings - DW_NEW
Code
%>%
prc_hpi_ooq filter(expend == "DW_OWN",
%in% c("EL", "FR", "ES", "IT", "DE"),
geo == "I15_Q") %>%
unit %>%
quarter_to_date group_by(geo) %>%
mutate(values = 100*values/values[date == as.Date("2011-01-01")]) %>%
filter(date >= as.Date("2009-01-01"),
<= as.Date("2016-01-01")) %>%
date left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = Geo)) +
theme_minimal() + xlab("") + ylab("100 = Janv. 2011") +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_color_manual(values = c("#ED2939", "#000000", "#009246", "#FFC400")) + add_4flags +
scale_y_log10(breaks = seq(0, 200, 2)) +
theme(legend.position = "none",
legend.title = element_blank())
2006Q1
Code
%>%
prc_hpi_ooq filter(time == "2006Q1") %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Purchase Total
Nobs
Code
%>%
prc_hpi_ooq filter(expend == "TOTAL",
== "I15_Q") %>%
unit left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
group_by(geo, Geo) %>%
arrange(time) %>%
summarise(first = first(time),
last = last(time),
Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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 .} {
France, Italy, Germany
Code
%>%
prc_hpi_ooq filter(expend == "TOTAL",
%in% c("FR", "IT", "DE"),
geo == "I15_Q") %>%
unit %>%
quarter_to_date left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
ggplot() + geom_line(aes(x = date, y = values, color = Geo)) + theme_minimal() + add_3flags +
scale_color_manual(values = c("#ED2939", "#000000", "#009246", "#FFC400")) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-100, 300, 5)) +
ylab("House Price Index") + xlab("")
Belgium, Denmark, Sweden, United Kingdom
Code
%>%
prc_hpi_ooq filter(expend == "TOTAL",
%in% c("BE", "DK", "SE", "UK"),
geo == "I15_Q") %>%
unit %>%
quarter_to_date left_join(geo, by = "geo") %>%
ggplot() + geom_line(aes(x = date, y = values, color = Geo)) + theme_minimal() + add_4flags +
scale_color_manual(values = c("#000000", "#C60C30", "#FECC00", "#6E82B5")) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-100, 300, 10)) +
ylab("House Price Index") + xlab("")
All Series
France
Code
%>%
prc_hpi_ooq filter(geo %in% c("FR"),
== "I15_Q") %>%
unit %>%
quarter_to_date left_join(geo, by = "geo") %>%
left_join(expend, by = "expend") %>%
ggplot() + geom_line() + theme_minimal() +
aes(x = date, y = values, color = Expend, linetype = Expend) +
scale_color_manual(values = viridis(11)[1:10]) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.75, 0.3),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-100, 300, 10)) +
ylab("House Price Index") + xlab("")
Germany
Code
%>%
prc_hpi_ooq filter(geo %in% c("DE"),
== "I15_Q") %>%
unit %>%
quarter_to_date left_join(geo, by = "geo") %>%
left_join(expend, by = "expend") %>%
ggplot() + geom_line() + theme_minimal() +
aes(x = date, y = values, color = Expend, linetype = Expend) +
scale_color_manual(values = viridis(11)[1:10]) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.35, 0.9),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-100, 300, 10)) +
ylab("House Price Index") + xlab("")
Italy
Code
%>%
prc_hpi_ooq filter(geo %in% c("IT"),
== "I15_Q") %>%
unit %>%
quarter_to_date left_join(geo, by = "geo") %>%
left_join(expend, by = "expend") %>%
ggplot() + geom_line() + theme_minimal() +
aes(x = date, y = values, color = Expend, linetype = Expend) +
scale_color_manual(values = viridis(12)[1:11]) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.6, 0.9),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-100, 300, 5)) +
ylab("House Price Index") + xlab("")