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National accounts

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National accounts

Tabel 1: Account 0: Goods and services by units, account name and time

NRX01_raw <- 
  statgl_url("NRX01", lang = language) %>%
  statgl_fetch(
    units          = "L",
    time           = px_top(5),
    "account name" = px_all(),
    .col_code      = TRUE
  ) %>% 
  as_tibble()
  
NRX01 <- 
  NRX01_raw %>% 
  arrange(desc(time)) %>% 
  mutate(
    time = time %>% fct_inorder(),
    `account name` = `account name` %>% str_remove_all("[:digit:]|[:punct:]|\\+") %>% trimws(),
    `account name` = `account name` %>% fct_inorder()
    ) %>% 
  drop_na() %>% 
  spread(time, value)
  
NRX01 %>% 
  select(-units) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = NRX01[["units"]] %>% table()) %>% 
  row_spec(c(8, 19), bold = TRUE)

	2021	2020	2019	2018	2017
Current prices, million dkk
Output	33.976	32.953	32.633	31.515	30.949
Taxes less subsidies on products	754	761	769	771	638
Taxes on products	1.024	998	1.010	1.010	857
Subsidies on products	270	238	240	238	220
Imports of goods and services	10.114	9.428	10.225	8.745	8.193
Imports of goods	6.664	6.276	6.903	5.717	5.310
Imports of services	3.450	3.152	3.322	3.028	2.884
Total Resources	44.844	43.143	43.627	41.032	39.780
Intermediate consumption	14.386	13.545	13.412	12.991	12.758
Final consumption expenditure	16.467	15.936	15.760	15.268	14.914
Private consumption expenditure	7.289	7.116	7.005	6.944	6.928
Off Government consumption expenditure	9.178	8.820	8.754	8.325	7.986
Individual consumption expenditure	5.278	5.098	5.158	4.986	4.762
Collective consumption expenditure	3.900	3.722	3.596	3.339	3.224
Gross fixed capital formation	6.782	6.410	6.251	4.195	4.446
Exports of goods and services	7.209	7.251	8.205	8.578	7.662
Exports of goods	5.417	5.697	6.008	6.433	5.574
Exports of services	1.792	1.554	2.197	2.145	2.088
Total use	44.844	43.143	43.627	41.032	39.780

See the table in our Statbank: NRX01

Tabel 2: Production by units, industry and time

NRX0318_raw <- 
  statgl_url("NRX0318", lang = language) %>% 
  statgl_fetch(
    units     = "L",
    industry  = paste0("0100", LETTERS[1:11]),
    time      = px_top(5),
    .col_code = TRUE
  ) %>% 
  as_tibble()


NRX0318 <- 
  NRX0318_raw %>% 
  arrange(desc(time)) %>% 
  mutate(
    time = time %>% fct_inorder(),
    industry = industry %>% fct_reorder(value, .fun = sum, .desc = TRUE)
    ) %>% 
  spread(time, value) %>% 
  mutate(industry = industry %>% str_remove("A|B|C|D|E|F|G|H|I|J|K"))



NRX0318 %>% 
  select(-units) %>% 
  rename(" " = 1) %>%  
  statgl_table() %>% 
  pack_rows(index = NRX0318[["units"]] %>% table())

	2021	2020	2019	2018	2017
Current prices, million dkk
Public adm. and service	9.635	9.267	9.277	8.875	8.495
Fishery and hunting	4.850	4.801	5.039	4.868	4.860
Construction business	4.190	4.318	3.651	3.368	3.600
Finance and business	3.892	3.566	3.254	3.150	3.170
Transport	3.283	2.978	3.335	3.337	3.142
Trade	2.960	2.931	2.776	2.431	2.740
Industry	1.906	2.021	2.165	2.364	1.697
Post, tele, IT, radio, TV etc.	1.251	1.229	1.262	1.263	1.305
Supply and renovation	993	1.012	903	930	1.039
Hotels and restaurants	699	565	729	722	703
Extraction of raw materials	316	265	242	208	196

See the table in our Statbank: NRX0318

Tabel 3: Trends in GDP by units, account and Aar

NRX10_raw <- 
  statgl_url("NRX10", lang = language) %>% 
  statgl_fetch(
    units = "K",
    account = c("01", "02", "04"),
    Aar = px_top(5),
    .col_code = TRUE
  ) %>% 
  as_tibble() %>% 
  rename("time" = Aar)

NRX10 <- 
  NRX10_raw %>% 
  arrange(desc(time)) %>% 
  mutate(time = time %>% fct_inorder()) %>% 
  spread(time, value)

NRX10 %>% 
  select(-units) %>% 
  rename(" " = 1) %>% 
  statgl_table() %>% 
  pack_rows(index = NRX10[["units"]] %>% table())

	2021	2020	2019	2018	2017
2010-prices, chained values
Annual real growth in percent	1,3	0,2	2,8	0,6	0,1
GDP, million DKK	15.740,6	15.540,1	15.511,0	15.083,8	14.990,4
Per capita, 1.000 DKK	279,3	277,4	277,4	270,4	268,8

See the table in our Statbank: NRX10

Tabel 4: Growth contribution to GDP by Kode and Aar

NRX13_raw <- 
  statgl_url("NRX13", lang = language) %>% 
  statgl_fetch(
    Aar       = px_top(5),
    Kode      = paste0("VBVT", LETTERS[1:11]),
    .col_code = TRUE
  ) %>% 
  as_tibble() %>% 
    rename("time" = Aar)


NRX13 <-
  NRX13_raw %>% 
  arrange(desc(time)) %>% 
  mutate(
    time = time %>% fct_inorder(),
    Kode = Kode %>% str_remove("A|B|C|D|E|F|G|H|I|J|K") %>% trimws(),
    Kode = Kode %>% fct_reorder(value, .fun = mean, .desc = TRUE)
  ) %>% 
  spread(time, value)

NRX13 %>% 
  rename(" " = 1) %>% 
  statgl_table()

	2021	2020	2019	2018	2017
Fishery and hunting	1,75	0,40	0,98	0,16	0,49
Public adm. and service	0,30	-0,68	1,38	0,78	0,74
Construction business	-1,72	0,69	1,13	-0,39	2,07
Trade	-0,47	-0,01	0,77	0,81	-0,11
Finance and business	0,48	0,34	0,02	-0,28	0,15
Extraction of raw materials	-0,07	0,00	0,27	0,05	0,07
Supply and renovation	-0,32	0,40	-0,02	-0,20	0,03
Transport	0,38	-1,43	0,09	0,73	-0,13
Hotels and restaurants	0,48	-0,85	-0,27	-0,17	0,09
Post, tele, IT, radio, TV etc.	-0,15	0,19	-0,30	-0,29	-0,36
Industry	0,14	0,77	-0,57	0,27	-2,68

See the table in our Statbank: NRX13

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Last updated: 17. april 2024