Quarterly non-financial accounts for general government

Data - Eurostat

Author

Info

LAST_DOWNLOAD

Code

tibble(DOWNLOAD_TIME = as.Date(file.info("~/Library/Mobile\ Documents/com~apple~CloudDocs/website/data/eurostat/gov_10q_ggnfa.RData")$mtime)) %>%
  print_table_conditional()

DOWNLOAD_TIME
2024-10-09

LAST_COMPILE

LAST_COMPILE
2024-11-22

Last

Code

gov_10q_ggnfa %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()

time	Nobs
2024Q1	14757

unit

Code

gov_10q_ggnfa %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

unit	Unit	Nobs
MIO_NAC	Million units of national currency	471168
MIO_EUR	Million euro	471073
PC_GDP	Percentage of gross domestic product (GDP)	467193

sector

Code

gov_10q_ggnfa %>%
  left_join(sector, by = "sector") %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

sector	Sector	Nobs
S13	General government	616911
S1312	State government	216129
S1314	Social security funds	191863
S1313	Local government	189612
S1311	Central government	189600
S212	Institutions of the EU	5319

sector

Code

gov_10q_ggnfa %>%
  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)	1219210
SCA	Seasonally and calendar adjusted data	163339
SA	Seasonally adjusted data, not calendar adjusted data	22257
TC	Trend cycle data	4628

na_item

All

Code

gov_10q_ggnfa %>%
  left_join(na_item, by = "na_item") %>%
  group_by(na_item, Na_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

geo

Code

gov_10q_ggnfa %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  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

gov_10q_ggnfa %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  print_table_conditional()

EA-19, Deficit

Code

gov_10q_ggnfa %>%
  filter(time %in% c("2022Q2", "2022Q1"),
         sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         s_adj == "NSA") %>%
  left_join(geo, by = "geo") %>%
  select_if(~ n_distinct(.) > 1) %>%
  spread(time, values) %>%
  mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
         Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
  select(Flag, Geo, geo, everything()) %>%
  arrange(`2022Q2`) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Deficit

All

Code

gov_10q_ggnfa %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("FR", "DE", "IT", "ES", "NL"),
         s_adj == "NSA") %>%
  left_join(geo, by = "geo") %>%
  quarter_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 2), "-01-01")),
               labels = date_format("%Y"))

2000-

Code

gov_10q_ggnfa %>%
  filter(sector == "S13",
         unit == "PC_GDP",
         na_item == "B9",
         geo %in% c("FR", "DE", "IT", "ES", "NL"),
         s_adj == "NSA") %>%
  left_join(geo, by = "geo") %>%
  quarter_to_date() %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  mutate(values = values / 100) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("Deficit") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-100, 260, 1),
                     labels = scales::percent_format(acc = 1)) +
  scale_x_date(breaks = as.Date(paste0(seq(1700, 2100, 2), "-01-01")),
               labels = date_format("%Y"))