source | dataset | .html | .RData |
---|---|---|---|
eurostat | sts_intvd_m | 2024-06-24 | 2024-11-05 |
eurostat | sts_intvnd_m | 2024-10-31 | 2024-10-31 |
Turnover in industry, non domestic market - monthly data - sts_intvnd_m
Data - Eurostat
Info
Data on macro
Title | source | dataset | .html | .RData |
---|---|---|---|---|
Gross value added and income by A*10 industry breakdowns | eurostat | nama_10_a10 | 2024-11-05 | 2024-10-08 |
Employment by A*10 industry breakdowns | eurostat | nama_10_a10_e | 2024-11-05 | 2024-11-05 |
GDP and main components (output, expenditure and income) | eurostat | nama_10_gdp | 2024-11-05 | 2024-10-08 |
Labour productivity and unit labour costs | eurostat | nama_10_lp_ulc | 2024-11-05 | 2024-10-08 |
Gross value added and income A*10 industry breakdowns | eurostat | namq_10_a10 | 2024-11-05 | 2024-11-05 |
Employment A*10 industry breakdowns | eurostat | namq_10_a10_e | 2024-11-05 | 2024-10-08 |
GDP and main components (output, expenditure and income) | eurostat | namq_10_gdp | 2024-11-05 | 2024-10-08 |
Labour productivity and unit labour costs | eurostat | namq_10_lp_ulc | 2024-11-05 | 2024-11-04 |
Main GDP aggregates per capita | eurostat | namq_10_pc | 2024-11-05 | 2024-10-08 |
Non-financial transactions | eurostat | nasa_10_nf_tr | 2024-11-05 | 2024-10-08 |
Non-financial transactions | eurostat | nasq_10_nf_tr | 2024-11-05 | 2024-10-09 |
Gross Domestic Product | fred | gdp | 2024-11-01 | 2024-11-01 |
Quarterly National Accounts, Per Capita | oecd | QNA | 2024-06-06 | 2024-06-30 |
Gross domestic product (GDP) | oecd | SNA_TABLE1 | 2024-09-15 | 2024-06-30 |
Non-financial accounts by sectors | oecd | SNA_TABLE14A | 2024-09-15 | 2024-06-30 |
Disposable income and net lending - net borrowing | oecd | SNA_TABLE2 | 2024-07-01 | 2024-04-11 |
Value added and its components by activity, ISIC rev4 | oecd | SNA_TABLE6A | 2024-07-01 | 2024-06-30 |
External balance on goods and services (% of GDP) | wdi | NE.RSB.GNFS.ZS | 2024-09-18 | 2024-09-18 |
GDP (current USD) | wdi | NY.GDP.MKTP.CD | 2024-09-18 | 2024-09-26 |
GDP, PPP (current international D) | wdi | NY.GDP.MKTP.PP.CD | 2024-09-18 | 2024-09-18 |
GDP per capita (current USD) | wdi | NY.GDP.PCAP.CD | 2024-10-15 | 2024-10-15 |
GDP per capita (constant 2015 USD) | wdi | NY.GDP.PCAP.KD | 2024-09-18 | 2024-09-18 |
GDP per capita, PPP (current international D) | wdi | NY.GDP.PCAP.PP.CD | 2024-10-15 | 2024-10-15 |
GDP per capita, PPP (constant 2011 international D) | wdi | NY.GDP.PCAP.PP.KD | 2024-09-18 | 2024-09-18 |
Last
Code
%>%
sts_intvnd_m group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(3) %>%
print_table_conditional()
time | Nobs |
---|---|
2024M08 | 9811 |
2024M07 | 12910 |
2024M06 | 13002 |
Info
- Source. html
The Turnover Index is a business cycle indicator showing the monthly evolution of the market of goods and services in the industrial sector. It also records the evolution of turnover over longer periods of time. The turnover of industry index is not deflated. It is therefore the objective of this indicator to measure the market activity in the industrial sector in value. Data are compiled according to the Statistical classification of economic activities in the European Community, (NACE Rev. 2, Eurostat). Industrial turnover is compiled as a “fixed base year Laspeyres type volume-index”.
indic_bt
Code
%>%
sts_intvnd_m left_join(indic_bt, by = "indic_bt") %>%
group_by(indic_bt, Indic_bt) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
indic_bt | Indic_bt | Nobs |
---|---|---|
NETTUR_NDOM | Non-domestic net turnover | 3924504 |
NETTUR_NDOM_EU | Non-domestic net turnover - euro area | 1785011 |
NETTUR_NDOM_NEU | Non-domestic net turnover - non-euro area | 1759220 |
nace_r2
Code
%>%
sts_intvnd_m left_join(nace_r2, by = "nace_r2") %>%
group_by(nace_r2, Nace_r2) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
s_adj
Code
%>%
sts_intvnd_m left_join(s_adj, by = "s_adj") %>%
group_by(s_adj, S_adj) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
s_adj | S_adj | Nobs |
---|---|---|
SCA | Seasonally and calendar adjusted data | 2870613 |
CA | Calendar adjusted data, not seasonally adjusted data | 2839496 |
NSA | Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) | 1758626 |
unit
Code
%>%
sts_intvnd_m 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 | Index, 2015=100 | 2258470 |
I21 | Index, 2021=100 | 2128157 |
I10 | Index, 2010=100 | 1451162 |
PCH_PRE | Percentage change on previous period | 832127 |
PCH_SM | Percentage change compared to same period in previous year | 798819 |
geo
Code
%>%
sts_intvnd_m 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
%>%
sts_intvnd_m group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
print_table_conditional()
EA20
C
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C",
== "I21",
unit == "SCA",
s_adj %in% c("EA20")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2005M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date >= as.Date("2005-01-01")) %>%
ggplot() + ylab("Index of turnover") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
Germany - Different Industries
C10 - Manufacture of food products
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C10",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date <= as.Date("2020-07-01"),
>= as.Date("2000-01-01")) %>%
date ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
C29 - Manufacture of motor vehicles, trailers and semi-trailers
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C29",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date <= as.Date("2020-07-01"),
>= as.Date("2000-01-01")) %>%
date ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.35),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
C20 - Manufacture of chemicals and chemical products
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C20",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date <= as.Date("2020-07-01"),
>= as.Date("2000-01-01")) %>%
date ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
C30 - Manufacture of other transport equipment
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C30",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date <= as.Date("2020-07-01"),
>= as.Date("2000-01-01")) %>%
date ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
Individual Countries
France
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C",
== "I21",
unit == "SCA",
s_adj %in% c("FR")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2000M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date <= as.Date("2020-07-01")) %>%
ggplot() + ylab("Index of turnover") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
Germany
All
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2003M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
1995-
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date >= as.Date("1995-01-01")) %>%
ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))
2000-
Code
%>%
sts_intvnd_m bind_rows(sts_intvd_m) %>%
filter(nace_r2 == "C",
== "I21",
unit == "SCA",
s_adj %in% c("DE")) %>%
geo group_by(indic_bt) %>%
mutate(values = 100*values/values[time == "2004M01"]) %>%
left_join(indic_bt, by = "indic_bt") %>%
%>%
month_to_date filter(date >= as.Date("2000-01-01")) %>%
ggplot() + ylab("Index of turnover - Non domestic market") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Indic_bt)) +
scale_x_date(breaks = seq(1920, 2100,2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.85),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(-60, 300, 10))