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

Data - Eurostat

Author

François Geerolf

Last observation: août 2026 (N = 196)

First observation: janv. 1980 (N = 76)

Last data update: 23 sept. 2026, 21:45

Last compile: 23 sept. 2026, 22:14

Structure

indic

French

Code 
indic <- read_parquet("indic_fr.parquet")
ei_isin_m |>
  
  group_by(indic, Indic) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
indic Indic Nobs
IS-IP Production index 622096
IS-ITT Turnover index - total 590002
IS-ITD Turnover index - domestic market 578611
IS-ITND Turnover index - non-domestic market 373970
IS-PPI Output prices of the domestic market index (producer price index) (NSA) 269088
IS-WSI Gross wages and salaries index 138918
IS-IMPR Import price index (NSA) 113912
IS-EPI Number of persons employed index 113158
IS-HWI Hours worked index 111198
IS-IMPX Import price index - non euro area (NSA) 72485
IS-IMPZ Import price index - euro area (NSA) 66380

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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1997M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2005M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2005M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2005M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1997M01"]) |>
  
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) |>
  month_to_date() |>
  add_flag_color("Geo") |>
  ggplot() + ylab("Durable Goods - Industrial Production") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) + add_flags +
  scale_color_identity() +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1997M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "1997M01"]) |>
  
  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_flags +
  scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
  scale_x_date(breaks = seq(1920, 2100, 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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  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, Geo, time, values) |>
  group_by(geo) |>
  mutate(values = 100*values/values[time == "2020M02"]) |>
  
  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_flags +
  theme(legend.position = "none") +
  scale_y_continuous(breaks = seq(-300, 300, 10))