Quarterly non-financial accounts for general government

Data - Eurostat

Author

Info

LAST_DOWNLOAD

Code

tibble(DOWNLOAD_TIME = as.Date(file.info("~/iCloud/website/data/eurostat/gov_10q_ggnfa.RData")$mtime)) %>%
  print_table_conditional()

DOWNLOAD_TIME
2025-10-11

LAST_COMPILE

LAST_COMPILE
2025-10-11

Last

Code

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

time	Nobs
2025Q1	14994

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	503571
MIO_EUR	Million euro	503471
PC_GDP	Percentage of gross domestic product (GDP)	501158

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	647218
S1312	State government	258312
S1314	Social security funds	200583
S1311	Central government	198360
S1313	Local government	198336
S212	Institutions of the EU	5391

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)	1287304
SCA	Seasonally and calendar adjusted data	197184
SA	Seasonally adjusted data, not calendar adjusted data	18876
TC	Trend cycle data	4836

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"))