Consumption - CONSUMPTION

Data - ec

Author

sector

Code

CONSUMPTION %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

sector	Sector	Nobs
TOT	TOTAL Consumer	322734

question

Code

CONSUMPTION %>%
  group_by(question, Questions) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

question	Questions	Nobs
1	Financial situation over last 12 months	23419
10	Savings at present	22597
11	Savings over next 12 months	23162
12	Statement on financial situation of household	23169
13	Intention to buy a car within the next 12 months	6934
14	Purchase or build a home within the next 12 months	6864
15	Home improvements over the next 12 months	6926
2	Financial situation over next 12 months	23419
3	General economic situation over last 12 months	23419
4	General economic situation over next 12 months	23419
5	Price trends over last 12 months	23172
6	Price trends over next 12 months	23172
7	Unemployment expectations over next 12 months	23374
8	Major purchases at present	23334
9	Major purchases over next 12 months	23177
COF	Confidence Indicator (Q1 + Q2 + Q4 + Q9) / 4	23177

answers

Code

CONSUMPTION %>%
  group_by(answers, Answers) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

answers	Answers	Nobs
B	Balance not seasonally adjusted (n.s.a)	161890
BS	Balance seasonally adjusted (s.a)	160844

country

Code

CONSUMPTION %>%
  group_by(country, Country) %>%
  summarise(Nobs = n()) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

freq

Code

CONSUMPTION %>%
  group_by(freq, Frequency) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

freq	Frequency	Nobs
M	Monthly	302010
Q	Quarterly	20724

Germany

Home improvements, Intention to buy a car, Purchase or build a home

Code

CONSUMPTION %>%
  filter(country == "DE",
         question %in% c("13", "14", "15"),
         answers == "B") %>%
  ggplot + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
  geom_line(aes(x = period, y = value, color = Questions)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 2), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.8, 0.1),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = seq(-200, 60, 10))