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
2026-01-30

LAST_COMPILE

LAST_COMPILE
2026-01-31

Last

Code

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

time	Nobs
2025Q3	14942

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	518329
MIO_EUR	Million euro	518227
PC_GDP	Percentage of gross domestic product (GDP)	515916

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	673210
S1312	State government	262968
S1314	Social security funds	204877
S1311	Central government	202656
S1313	Local government	202632
S212	Institutions of the EU	6129

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)	1326877
SCA	Seasonally and calendar adjusted data	201571
SA	Seasonally adjusted data, not calendar adjusted data	19188
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"))