Industry - monthly data - index (2015 = 100) (NACE Rev. 2) - ei_isin_m

Data - Eurostat

Author

François Geerolf

Info

DOWNLOAD_TIME

Code 
tibble(DOWNLOAD_TIME = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/ei_isin_m.RData")$mtime)) %>%
  print_table_conditional()
DOWNLOAD_TIME
2024-06-08

Last

Code 
ei_isin_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M05 9

indic

French

Code 
load_data("eurostat/indic_fr.RData")
ei_isin_m %>%
  left_join(indic, by = "indic") %>%
  group_by(indic, Indic) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
indic Indic Nobs
IS-IP Indice de production 583248
IS-ITT Indice du chiffre d'affaires - total 556169
IS-ITD Indice du chiffre d'affaires - marché intérieur 542663
IS-ITND Indice du chiffre d'affaires - marché extérieur 351642
IS-PPI Prix à la production de l'indice du marché intérieur (Indice des prix à la production) (NSA) 253852
IS-WSI Indice des salaires et traitements bruts 132702
IS-EPI Indice du nombre de personnes occupées 108654
IS-HWI Indice des heures travaillées 106566
IS-IMPR Indices des prix à l'importation (NSA) 104692
IS-IMPX Indices des prix à l'importation - hors zone euro (NSA) 65425
IS-IMPZ Indices des prix à l'importation - zone euro (NSA) 59694

English

Code 
ei_isin_m %>%
  left_join(indic, by = "indic") %>%
  group_by(indic, Indic) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
indic Indic Nobs
IS-IP Indice de production 583248
IS-ITT Indice du chiffre d'affaires - total 556169
IS-ITD Indice du chiffre d'affaires - marché intérieur 542663
IS-ITND Indice du chiffre d'affaires - marché extérieur 351642
IS-PPI Prix à la production de l'indice du marché intérieur (Indice des prix à la production) (NSA) 253852
IS-WSI Indice des salaires et traitements bruts 132702
IS-EPI Indice du nombre de personnes occupées 108654
IS-HWI Indice des heures travaillées 106566
IS-IMPR Indices des prix à l'importation (NSA) 104692
IS-IMPX Indices des prix à l'importation - hors zone euro (NSA) 65425
IS-IMPZ Indices des prix à l'importation - zone euro (NSA) 59694

nace_r2

Code 
load_data("eurostat/indic.RData")
ei_isin_m %>%
  left_join(nace_r2, by = "nace_r2") %>%
  group_by(nace_r2, Nace_r2) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

s_adj

Code 
ei_isin_m %>%
  left_join(s_adj, by = "s_adj") %>%
  group_by(s_adj, S_adj) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
s_adj S_adj Nobs
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 1167267
SCA Seasonally and calendar adjusted data 1026964
CA Calendar adjusted data, not seasonally adjusted data 671076

unit

Code 
ei_isin_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
I2015 Index, 2015=100 1465020
I2021 NA 1400287

geo

Code 
ei_isin_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 
ei_isin_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

C - Manufacturing

IS-IP - Industrial Production

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-IP",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "1997M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(-60, 300, 10))

IS-ITT - Turnover index - total

  • INSEE Definition. html

Turnover indices serve to provide a monthly measurement of trends in the activity of companies in the industrial, construction, retail, personal services, wholesale and miscellaneous services to enterprises sectors. They are elaborated each month from the monthly declarations (CA3) made by enterprises falling within the normal tax arrangements for the payment of value added tax (VAT). These indices are determined at the finest level of the French classification of activities (that is, the sub-classes of NAF rev.2) then aggregated to provide indices for the different levels of the composite nomenclatures (NA, NACE). The resultant indices are in volume in the retail and personal services sectors, and in value in the other sectors. The series are disseminated raw or seasonally and calendar effect adjusted.

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITT",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  filter(!is.na(values)) %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2005M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Turnover index - total") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

IS-ITD - Indice du chiffre d’affaires - marché intérieur

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITD",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2005M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Turnover index - domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

IS-ITND - Indice du chiffre d’affaires - marché extérieur

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITND",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2005M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Turnover index - non-domestic market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +  add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

MIG_DCOG - Durable Goods

IS-IP - Industrial Production

Code 
ei_isin_m %>%
  filter(nace_r2 == "MIG_DCOG",
         indic == "IS-IP",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "1997M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Durable Goods - Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) + add_3flags +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

MIG_COG - Consumer Goods

IS-IP - Industrial Production

Code 
ei_isin_m %>%
  filter(nace_r2 == "MIG_COG",
         indic == "IS-IP",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "1997M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Consumer Goods - Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

MIG_CAG - Capital Goods

IS-IP - Industrial Production

Code 
ei_isin_m %>%
  filter(nace_r2 == "MIG_CAG",
         indic == "IS-IP",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "1997M01"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  ggplot() + ylab("Capital Goods - Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

Covid-19 - Turnover index (Indice de CA)

Total

Dérivée

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITT",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  ggplot() + ylab("Turnover index - all") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_4flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

Intégrale

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITT",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  group_by(Geo) %>%
  arrange(date) %>%
  mutate(values = values-100,
         values = cumsum(values)) %>%
  ggplot() + ylab("Turnover index - all (Cum. Sum)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_4flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "2 months",
               labels = date_format("%b %y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = seq(-300, 300, 10))

Marché Externe

Dérivée

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITND",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  ggplot() + ylab("Turnover index - external market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_3flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "1 month",
               labels = date_format("%b %y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

Intégrale

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITND",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  group_by(Geo) %>%
  arrange(date) %>%
  mutate(values = values-100,
         values = cumsum(values)) %>%
  ggplot() + ylab("Turnover index - external market (Cum. Sum)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_4flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "1 month",
               labels = date_format("%b %y")) +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = seq(-300, 300, 10))

Marché Intérieur

Dérivée

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITD",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  ggplot() + ylab("Turnover index - internal market") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) + add_4flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "1 month",
               labels = date_format("%b %y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(-60, 300, 10))

Intégrale

Code 
ei_isin_m %>%
  filter(nace_r2 == "C",
         indic == "IS-ITD",
         geo %in% c("FR", "DE", "IT", "ES"),
         s_adj == "SCA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  mutate(values = 100*values/values[time == "2020M02"]) %>%
  left_join(geo, by = "geo") %>%
  month_to_date %>%
  filter(date >= as.Date("2020-02-01")) %>%
  group_by(Geo) %>%
  arrange(date) %>%
  mutate(values = values-100,
         values = cumsum(values)) %>%
  ggplot() + ylab("Turnover index - internal market (Cum. Sum)") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = Geo)) +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
  scale_x_date(breaks = "1 month",
               labels = date_format("%b %y")) + add_4flags +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = seq(-300, 300, 10))