source | dataset | .html | .RData |
---|---|---|---|
eurostat | nama_10_co3_p3 | 2024-11-05 | 2024-10-09 |
eurostat | prc_hicp_aind | 2024-11-01 | 2024-10-23 |
eurostat | prc_hicp_cow | 2024-11-01 | 2024-10-08 |
eurostat | prc_hicp_manr | 2024-11-01 | 2024-10-08 |
HICP (2015 = 100) - annual data (average index and rate of change)
Data - Eurostat
Info
Data on inflation
source | dataset | .html | .RData |
---|---|---|---|
bis | CPI | 2024-07-01 | 2022-01-20 |
ecb | CES | 2024-10-08 | 2024-01-12 |
eurostat | nama_10_co3_p3 | 2024-11-05 | 2024-10-09 |
eurostat | prc_hicp_cow | 2024-11-01 | 2024-10-08 |
eurostat | prc_hicp_ctrb | 2024-11-01 | 2024-10-08 |
eurostat | prc_hicp_inw | 2024-11-01 | 2024-11-05 |
eurostat | prc_hicp_manr | 2024-11-01 | 2024-10-08 |
eurostat | prc_hicp_midx | 2024-11-01 | 2024-11-05 |
eurostat | prc_hicp_mmor | 2024-11-01 | 2024-10-08 |
eurostat | prc_ppp_ind | 2024-11-01 | 2024-10-08 |
eurostat | sts_inpp_m | 2024-06-24 | 2024-10-08 |
eurostat | sts_inppd_m | 2024-10-09 | 2024-10-08 |
eurostat | sts_inppnd_m | 2024-06-24 | 2024-10-08 |
fred | cpi | 2024-11-01 | 2024-11-01 |
fred | inflation | 2024-11-01 | 2024-11-01 |
imf | CPI | 2024-06-20 | 2020-03-13 |
oecd | MEI_PRICES_PPI | 2024-09-15 | 2024-04-15 |
oecd | PPP2017 | 2024-04-16 | 2023-07-25 |
oecd | PRICES_CPI | 2024-04-16 | 2024-04-15 |
wdi | FP.CPI.TOTL.ZG | 2023-01-15 | 2024-09-18 |
wdi | NY.GDP.DEFL.KD.ZG | 2024-09-18 | 2024-09-18 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-05 |
Last
Code
%>%
prc_hicp_aind group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(2) %>%
print_table_conditional()
time | Nobs |
---|---|
2023 | 32544 |
2022 | 32567 |
unit
Code
%>%
prc_hicp_aind left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
unit | Unit | Nobs |
---|---|---|
INX_A_AVG | Annual average index | 278034 |
RCH_A_AVG | Annual average rate of change | 262188 |
CID_EA | NA | 638 |
coicop
Code
%>%
prc_hicp_aind left_join(coicop, by = "coicop") %>%
group_by(coicop, Coicop) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
geo
Code
%>%
prc_hicp_aind left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
time
Code
%>%
prc_hicp_aind group_by(time) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Quality
Code
<- function(CPname, legend.position = c(0.2, 0.2)){
compare_coicop
<- prc_hicp_aind %>%
inflation filter(unit == "INX_A_AVG",
== CPname,
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Price index")
<- nama_10_co3_p3 %>%
cons filter(unit == "PD15_EUR",
%in% c("FR", "NL", "IT", "DE", "ES"),
geo == CPname) %>%
coicop left_join(geo, by = "geo") %>%
%>%
year_to_date filter(date >= as.Date("1996-01-01")) %>%
left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Consumption Deflator")
%>%
cons bind_rows(inflation) %>%
+ geom_line(aes(x = date, y = values, color = color, linetype = variable)) +
ggplot theme_minimal() +
scale_color_identity() + xlab("") + ylab(CPname) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = legend.position,
legend.title = element_blank()) +
scale_y_log10(breaks = seq(10, 300, 10))
}
<- function(CPname, CPname2){
compare_coicop2
<- prc_hicp_aind %>%
inflation filter(unit == "INX_A_AVG",
== CPname,
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Price index")
<- nama_10_co3_p3 %>%
cons filter(unit == "PD15_EUR",
%in% c("FR", "NL", "IT", "DE", "ES"),
geo == CPname2) %>%
coicop left_join(geo, by = "geo") %>%
%>%
year_to_date filter(date >= as.Date("1996-01-01")) %>%
left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Consumption Deflator")
%>%
cons bind_rows(inflation) %>%
+ geom_line(aes(x = date, y = values, color = color, linetype = variable)) +
ggplot theme_minimal() +
scale_color_identity() + xlab("") + ylab(CPname) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.2),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(10, 300, 10))
}
CP00
Code
compare_coicop2("CP00", "TOTAL")
CP09
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP09"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP09") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_5flags +
theme(legend.position = "none")
CP08 - Communications
Annual Inflation
Code
<- prc_hicp_aind %>%
inflation_CP08 filter(unit == "INX_A_AVG",
%in% c("CP08"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Price index")
%>%
inflation_CP08 ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP08") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_5flags +
theme(legend.position = "none")
Annual Consumption Deflator Inflation
Code
<- nama_10_co3_p3 %>%
cons_CP08 filter(unit == "PD15_EUR",
%in% c("FR", "NL", "IT", "DE", "ES"),
geo == "CP08") %>%
coicop left_join(geo, by = "geo") %>%
%>%
year_to_date filter(date >= as.Date("1996-01-01")) %>%
left_join(colors, by = c("Geo" = "country")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
%>%
ungroup mutate(variable = "Consumption Deflator")
%>%
cons_CP08 + geom_line(aes(x = date, y = values, color = color)) +
ggplot theme_minimal() + add_5flags +
scale_color_identity() + xlab("") + ylab("Communications (08)") +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.2, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(10, 300, 10))
Bind
Code
compare_coicop("CP08")
CP041
Bind
Code
compare_coicop("CP041", legend.position = c(0.2, 0.8))
CP041
Bind
Code
compare_coicop("CP04", legend.position = c(0.2, 0.8))
CP09
Bind
Code
compare_coicop("CP09")
CP091
Bind
Code
compare_coicop("CP091")
CP10
Bind
Code
compare_coicop("CP10", legend.position = c(0.2, 0.8))
CP11
Bind
Code
compare_coicop("CP11", legend.position = c(0.2, 0.8))
CP12
Bind
Code
compare_coicop("CP12", legend.position = c(0.2, 0.8))
CP082_083 - Telephone and telefax equipment
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP082_083"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP082_083") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_5flags +
theme(legend.position = "none")
CP0820 - Telephone and telefax equipment
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP0820"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP0820 - Telephone and telefax equipment") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_3flags +
theme(legend.position = "none")
CP091
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP091"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP091") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_5flags +
theme(legend.position = "none")
CP08202 - Mobile Telephone equipment
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP08202"),
coicop %in% c("DE", "FR", "IT", "ES", "NL")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
arrange(time) %>%
%>%
year_to_date group_by(Geo) %>%
arrange(date) %>%
mutate(values = 100*values/values[1]) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("CP08202 - Mobile Telephone equipment") +
scale_x_date(breaks = seq(1960, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = c(seq(0, 200, 10), 2, 3, 5, 15, 8, 4)) +
scale_color_identity() + add_5flags +
theme(legend.position = "none")
Greece, Europe, France, Spain, Italy, Germany
2011-2013 -
HICP
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
== "CP00",
coicop %in% c("EL", "FR", "ES", "IT", "DE")) %>%
geo %>%
year_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)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
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_identity() + add_5flags +
scale_y_log10(breaks = seq(0, 200, 2)) +
theme(legend.position = "none",
legend.title = element_blank())
Rents
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
== "CP041",
coicop %in% c("EL", "FR", "ES", "IT", "DE")) %>%
geo %>%
year_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)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
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_identity() + add_5flags +
scale_y_log10(breaks = seq(0, 200, 2)) +
theme(legend.position = "none",
legend.title = element_blank())
Real Rents
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP041", "CP00"),
coicop %in% c("EL", "FR", "ES", "IT", "DE")) %>%
geo left_join(geo, by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
spread(coicop, values) %>%
mutate(values = 100*CP041/CP00) %>%
%>%
year_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 mutate(Geo = ifelse(geo == "EA", "Europe", Geo),
Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = values, color = color)) +
theme_minimal() + xlab("") + ylab("Real Rents (100 = Janv. 2011)") +
scale_x_date(breaks = seq(1960, 2021, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_color_identity() + add_5flags +
scale_y_log10(breaks = seq(0, 200, 2)) +
theme(legend.position = "none",
legend.title = element_blank())
Europe - Real Rents
Value
Code
%>%
prc_hicp_aind filter(unit == "INX_A_AVG",
%in% c("CP041", "CP00"),
coicop %in% c("EA")) %>%
geo left_join(tibble(geo = c("EA", "EA18", "EA19"),
Geo = c("Euro Area (time-dep geography)")),
by = "geo") %>%
select(geo, Geo, coicop, time, values) %>%
spread(coicop, values) %>%
mutate(values = 100*CP041/CP00) %>%
%>%
year_to_date ggplot(.) + geom_line(aes(x = date, y = values)) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1960, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = seq(0, 200, 1)) +
scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.position = c(0.5, 0.85),
legend.title = element_blank())