Consumer surveys - Consumers - monthly data - ei_bsco_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_bsco_m.RData")$mtime)) %>%
  print_table_conditional()
DOWNLOAD_TIME
2024-10-09

Last

Code 
ei_bsco_m %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024M09 792

indic

French

Code 
load_data("eurostat/indic_fr.RData")
ei_bsco_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
BS-FS-LY Situation financière au cours des 12 derniers mois 23804
BS-FS-NY Situation financière au cours des 12 prochains mois 23804
BS-GES-LY Situation économique générale au cours des 12 derniers mois 23804
BS-GES-NY Situation économique générale au cours des 12 prochains mois 23804
BS-UE-NY Evolution probable du chômage au cours des 12 prochains mois 23759
BS-MP-PR La conjoncture économique est adéquate pour les achats importants 23719
BS-PT-LY Evolution des prix au cours des 12 derniers mois 23557
BS-PT-NY Evolution probable des prix au cours des 12 prochains mois 23557
BS-SFSH Situation financière actuelle du ménage 23555
BS-SV-NY Epargne au cours des 12 prochains mois 23547
BS-CSMCI Consommateur, indicateur de confiance 23442
BS-MP-NY Achats importants prévus dans les 12 prochains mois 23442

English

Code 
load_data("eurostat/indic.RData")
ei_bsco_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
BS-FS-LY Financial situation over the last 12 months 23804
BS-FS-NY Financial situation over the next 12 months 23804
BS-GES-LY General economic situation over the last 12 months 23804
BS-GES-NY General economic situation over the next 12 months 23804
BS-UE-NY Unemployment expectations over the next 12 months 23759
BS-MP-PR The current economic situation is adequate to make major purchases 23719
BS-PT-LY Price trends over the last 12 months 23557
BS-PT-NY Price trends over the next 12 months 23557
BS-SFSH Statement on financial situation of household 23555
BS-SV-NY Savings over the next 12 months 23547
BS-CSMCI Consumer confidence indicator 23442
BS-MP-NY Major purchases over the next 12 months 23442

s_adj

Code 
ei_bsco_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) 142410
SA Seasonally adjusted data, not calendar adjusted data 141384

geo

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

France, Germany, Italy

BS-CSMCI - Consumer confidence indicator

All

Code 
ei_bsco_m %>%
  filter(indic == "BS-CSMCI",
         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("Consumer 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_bsco_m %>%
  filter(indic == "BS-CSMCI",
         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("Consumer 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_bsco_m %>%
  filter(indic == "BS-CSMCI",
         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("Consumer 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))