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
2025-05-18

LAST_COMPILE

LAST_COMPILE
2025-05-18

Last

Code

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

time	Nobs
2024Q4	14691

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	504761
MIO_EUR	Million euro	504662
PC_GDP	Percentage of gross domestic product (GDP)	500994

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	656928
S1312	State government	255672
S1314	Social security funds	198982
S1311	Central government	196761
S1313	Local government	196737
S212	Institutions of the EU	5337

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)	1274353
SCA	Seasonally and calendar adjusted data	208420
SA	Seasonally adjusted data, not calendar adjusted data	22860
TC	Trend cycle data	4784

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"))