Business surveys - NACE Rev. 2 activity - Industry - monthly data - ei_bsin_m_r2

Data - Eurostat

Author

François Geerolf

Info

LAST_DOWNLOAD

Code 
tibble(LAST_DOWNLOAD = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/ei_bsin_m_r2.RData")$mtime)) %>%
  print_table_conditional()
LAST_DOWNLOAD
2024-10-08

LAST_COMPILE

LAST_COMPILE
2024-11-05

Last

Code 
ei_bsin_m_r2 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M09 528

indic

Code 
ei_bsin_m_r2 %>%
  left_join(indic, by = "indic") %>%
  group_by(indic, Indic) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
indic Indic Nobs
BS-IPE Production expectations over the next 3 months 26518
BS-IPT Production development observed over the past 3 months 26350
BS-IOB Assessment of order-book levels 26338
BS-ISFP Assessment of the current level of stocks of finished products 26182
BS-ICI Industrial confidence indicator 26002
BS-IEOB Assessment of export order-book levels 25812
BS-ISPE Selling price expectations over the next 3 months 25629
BS-IEME Employment expectations over the next 3 months 25358

s_adj

Code 
ei_bsin_m_r2 %>%
  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
NSA Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) 104103
SA Seasonally adjusted data, not calendar adjusted data 104086

geo

Code 
ei_bsin_m_r2 %>%
  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_bsin_m_r2 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

France, Germany, Italy

BS-IPE - Production expectations over the next 3 months

All

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-IPE",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

1995-

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-IPE",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

2000-

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-IPE",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

2015-

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-IPE",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2015-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 1) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

BS-ICI - Industrial confidence indicator

All

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-ICI",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

1995-

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-ICI",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

2000-

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-ICI",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  group_by(geo) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Industrial confidence indicator") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 5))

BS-IOB - Assessment of order books levels

All

Code 
ei_bsin_m_r2 %>%
  filter(indic == "BS-IOB",
         geo %in% c("FR", "DE", "IT"),
         s_adj == "NSA") %>%
  select(geo, time, values) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
  month_to_date %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  ggplot() + ylab("Assessment of order books levels") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_3flags + theme(legend.position = "none") +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(-2000, 2000, 10))